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1- PhD Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Bu-Ali Sina University, Hamadan, Iran.
2- Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Bu-Ali Sina University, Hamadan, Iran.
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1.(3-8)

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Afsun Nodehi Moghadam, PhD

University of Social Welfare and Rehabilitation Sciences, Iran.

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University of Social Welfare and Rehabilitation Sciences, Iran.

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University of Social Welfare and Rehabilitation Sciences, Iran.

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Associate Professor, University of Social Welfare and Rehabilitation Sciences, Iran.

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Associate Professor, University of Social Welfare and Rehabilitation Sciences, Iran.

Noureddin Karimi, PhD, PT

Assistant Professor, University of Social Welfare and Rehabilitation Science, Iran.

Afsoon Nodehi Moghaddam, PhD, PT

Associate Professor, University of Social Welfare and Rehabilitation Science, Iran.

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Professor, North Georgia University, US.

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Associate Professor, Shahid Beheshti University of Medical Sciences & Health Services, Iran.

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PHYSICAL TREAAWT IMAGEMENTS

April 2016 . Volume 6 . Number 1

ISSN:2423-5830

In the Name of God

University of Social Welfare

& Rehabilitation (USWR)

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PHYSICAL TREAAWT IMAGEMENTS

Negah Institute

for Scientific Communication

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51

Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players With and Without Hamstring Tightness

PHYSICAL TREAAWT IMAGEMENTS

April 2016 . Volume 6 . Number 1

Table of Contents

Relationship between Physical Activity and Risk Factors in Patients Suspected with Coronary Artery Disease (CAD) with the Number of Involved Arteries in Tehran City

Afsun Nodehi Moghadam1, Somayyeh Amiri Arimi1, Leila Ghamkhar1*, Shahrzad Mohammadi Rad1, Mahnaz Emami1, Ali Zadmehr2, Enayat Allah Bakhshi3, Aylin Talimkhani1

1. Department of Physiotherapy, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

2. Department of Cardiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.

3. Department of Statistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

Keywords:

Coronary artery disease, Risk factor, Physical activity

* Corresponding Author:

Leila Ghamkhar, PhD Candidate

Address: Department of Physiotherapy, University of Social Welfare and Rehabilitation Sciences, Koodakyar Ave., Daneshjoo Blvd., Evin, Tehran, Iran.

Phone: +98 (21) 22180039

E-mail: lghamkhar@yahoo.com

19 Oct. 2015

26 Feb. 2016

Citation: Nodehi Moghaddam A, Arimi S, Ghamkhar L, Mohammadi Rad Sh, Emami M, Zadmehr A, et al. Relationship Between Physical Activity and Risk Factors in Patients Suspected With Coronary Artery Disease (CAD) With the Number of Involved Arteries in Tehran City. Physical Treatments. 2016; 6(1):3-8.

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Purpose: Due to unhealthy lifestyles, there has been an increase in the prevalence of coronary artery disease (CAD) and a reduction in its age of onset. Given the high cost of diagnosis and treatment of CAD, there is an urgent need to teach people strategies helpful in changing their lifestyles as this can help reduce the risk factors of the disease. Therefore, the goal of the present study was to examine the relationship between physical activity and risk factors of CAD in patients suspected with thid disese in Tehran City.

Methods: In this cross-sectional study, a total of 92 patients with suspicion of CAD were examined. Interviews, patient medical history, and angiography reports were used to collect data. In addition, the International Physical Activity Questionnaires (IPAQ) was used to determine the level of physical activity of the patients.

Results: The study results indicated 6% increase in the chance of having CAD for each one-year increase in age. Patients who smoked cigarettes were about four times more likely to have coronary atherosclerosis than non-smokers. Among all participants, 34.7% had low physical activity, 43.47% had moderate physical activity, and 21.73% had high physical activity. A reverse and significant relationship was seen between the level of physical activity and number of narrowed coronary arteries. There were direct and significant relationships between blood glucose, cholestrol , and LDL with the number of involved coronary arteries.

Conclusion: Among the effective factors for heart diseases, older age and smoking had the highest correlations with the chance of catching CAD. Based on the study results, changing lifestyle, including diet and more physical activity is related to the number of involved coronary arteries.

CrossMark

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1. Introduction

ardiovascular Disease (CVD) is one the most common and costly diseases that can lead to disability and finally death [1, 2]. In 2006, the prevalence of CVD in the United States was reported to be 36.9% for both men and women. It was also estimated that the diagnosis and treatment of CVD cost more than 500 million dollars in the United States in 2010 [3]. Although the prevalence of CVD is higher in men, its mortality has been reported to be higher in women. Unfortunately, there is no information about the prevalence of this disease or its treatment and diagnostic costs in Iran. Coronary Artery Disease (CAD), the most common type of CVD, involves atherosclerosis that occurs in the epicardial coronary arteries. Atherosclerotic plaques narrow progressively the internal canal of coronary arteries, leading to reduced blood supply to the myocardium. The low blood flow in coronary artries will results in manifestation of signs and symptoms in rest and activity that in severe cases of reduced blood flow to myocardium can lead to myocardial infarction [3].

CAD is very common among the Iranian population and is responsible for about 50% of deaths in Iran each year [4]. Research studies have shown that 80% of patients with CAD live in countries with low or moderate income [5]. Many diagnostic and therapeutic methods are available for these patients, but these methods are too costly. Therefore, it is necessary to develop prevention strategies for this disease and reduce its cost of treatment especially in poor and developing countries. In this regard, detecting the risk factors for CAD and preventing them is one of the highest priorities. Age, gender, high blood pressure, smoking, diabetes, body fat, low physical activity, and family history of the disease are among the most important risk factors of CAD [6-10].

Low physical activity has been regarded as a major factor that increases the chance of CVD [10-12]. Inactivity refers to the lack of activity that increases the heart and breathing rate [3]. According to the reports by the American Heart Association [15], all people need to do moderate-intensity activities for 30 minutes a day (5 days a week) or high-intensity activities for 20 minutes a day (3 days a week). Many studies have examined the relationship between higher physical activities and lower chance of getting CVD. [14-22]

As modern today's living has changed people's lifestyle, especially their diet and activity level , there is a probable increase in the chance of catching related diseases. Therefore, the goal of the present study is to examine the physical activity and predisposing factors of CAD in suspected patients in Tehran City.

2. Materials and Methods

This study is a cross-sectional research and explored the relationship between level of physical activity and the predisposing risk factors of CVD in suspected patients. Using a convenience sampling method, a total of 92 patients suspected of CAD, aged 20-80 years, who had been admitted to the Shahid Rajaee Heart Center in Tehran, were selected as the study sample and evaluated. Interviews, patient medical history, and angiography reports were used to collect data. In addition, we used the International Physical Activity Questionnaires (IPAQ) (translated into Persian and validated by Vashaghani et al.) to determine the level of physical activity of the participants, one week before the first sign of pain in the chest or back [23].

IPAQ has 27-item and 7-item forms and can be completed in three ways: by patient, by phone, or by interview. In the present study, the 27-item form of the questionnaire was completed using interviews. The 27-item form of the questionnaire has 7 items about job-related activity, 6 items about patient transportation, 6 items about housework, and 6 items about recreation activities and 2 items about resting time. The level of physical activity was recorded with regard to the number of days per week, total time spent on each activity, and the index for moderate and intense activities for four domains of activity.

Procedure

After obtaining the angiography reports, patients who signed the informed consent forms approved by the University of Social Welfare and Rehabilitation Sciences were included in the study. It was decided that the examiner himself completed the demographic questionnaire and IPAQ after asking the patient in order to prevent problems, such as illiteracy of some old participants and also to reduce the number of unanswered questions. The data related to blood glucose and cholestrol were extracted from the last laboratory results in patient's file. Weight was calculated in kilograms, using a digital scale; during scaling, participants wore a thin cloth without shoes. Height was calculated in centimeters, using a tape measure attached to the wall; when measuring the height, the participants stood barefoot in the standard manner, so that their shoulders were in a normal position.

The study data from questionnaires were analyzed using SPSS 21. In this study, to present descriptive statistics of quantitative variables, measures of central tendency (mean), and dispersion (standard deviation, and range) and in qualitative variables, number and frequency were calculated. The Kolmogorov–Smirnov test (K-S test) was used to test the normality of the data. Also, the Pearson and Spearman correlation were used to determine the linear relationship between variables. The odds ratio and relative risk with %95 CI were calculated with regard to different variables to chance of catching CAD.

3. Results

Table 1 shows the descriptive characteristics of the quantitative variables and normality of variables. Of the total study sample, 62% were males and 38% females. It was found that 19.6% smoked at the time of the study or had a history of smoking. Angiography examination results indicated that 28.1% of the participants had no atherosclerosis in their coronary arteries, 41.6% had atherosclerosis in one artery, 23.6% had atherosclerosis in two arteries, and 6.7% had atherosclerosis in three arteries. About 55.6% of the participants, needed other invasive methods for revascularization of arteries, such as angioplasty, were used, but this was not necessary for the remaining 44.4% of the participants.

Of 95 participants, 32 (34.7%) had low physical activity, 40(43.47%) had moderate physical activity, and 20(21.73%) had high physical activity. There was a reverse but insignificant relationship between moderate physical activity and the number of involved coronary arteries (r=-0.17, P=0.1). However a a reverse and significant relationship was seen between high physical activity and the number of involved coronary arteries (r=-0.27, P=0.01). There was a significant relationship between blood glucose, cholesterol, and LDL with the number of involved coronary arteries. However no significant relationship was seen between diastolic/systolic pressure and trigyceride level with the number of coronary arteries involved (Table 2).

The results of inferential statistics indicated 6 fold increase in the chance of having CAD for each one-year increase in age. The probability for smokers to have CAD was about four times higher than that for non-smokers. The group with low physical activity was considered as the reference group, and the relative chance for moderate and high activity groups to have CAD was determined to be 45% and 42%, respectively (Table 3).

4. Discussion

The purpose of the present study was to examine the relationship between physical activity before start of first sign of pain in the chest and back of patients suspected with CAD with some predisposing factors of this disease and its effects on the chance of catching it in Tehran City. The results indicated that age and smoking had the strongest correlations with the probability of catching CAD. It was also found that a one-year increase in age increased the probability of having CAD by 6 fold. This finding is consistent with the findings of Ferrari et al. [21] who examined the prevalence of CAD in relationship with age and gender. They selected patients with CAD (22.5% females and mean age of 64 years) from 45 countries in Africa, Asia, Australia, and North, South, and Central America. They found that the CAD symptoms were more prevalent among women than men, and women with CAD were older than men with this disease. the elderly people, maybe because they were less active.

The study results also showed that the chance of having CAD was about four times higher in smokers than in non-smokers. Hatmi et al. [4] and Namayandeh et al. [25] also found smoking to be a major risk factor for catching CAD. Smoking damages artery walls , including nourishing arteries to heart, brain and other organs.the damaged artery walls are prone to create atherosclerosis plaques. On the other hand, smoking increases the platelets aggregation which leads to blood clot and arteries blockades [26, 27].

The other finding of this study was the relationship between blood glucose and fat with the number of the involved coronary arteries. A lot of studies have been done in this topic which confirms this relationship [28, 30]. high blood fat leads to gradual creation of fat precipitation or plaques in the inner layer of arterial walls. This percipitation constrict blood flow and eventually blocks it.

The study results also indicated a reverse and significant relationship between harsh physical activity (high heart and breath rate) before start of pain in the chest and back with the number of involved coronary arteries. Consistent with this finding, the results of a study on examining the role of physical activity and the risk factors for CAD in healthy men and women, showed that people with higher physical activity in their lifetime were at a lower risk of having CAD [31]. In another study, the effect of long-term exercise on baroreflex1 and cardiopulmonary function was studied [32]. Their results indicated that long-term exercise led to positive effects on baroreflex and cardiopulmonary function in patients with CAD.

The modern urban lifestyle leads to low physical activity and sometime inactivity of people. Long before, physical activity and exercise was considered a theraputic and preventive methods of diseases especially CVDs. Exercise could reduce the incidence of heart attacks to a large extent. It also prevent the progress of atherosclerosis by reducing risk factors including hypertension, blood glucose and fat [32]. Therefore, based on the results of this study, we can argue that it is possible to decrease the chance of having CAD with regular exercise.

The present study had some limitations. One of them lack of studying the physical activity of patients with CVD after their treatment. It is suggested that in the future studies, the level of physical acticities of patients with CVD were compared before and after treatment. Conducting prospective studies could study better the relation between physical activity and the chance of catching CAD.

Acknowledgements

This paper had no financial support.

Conflict of Interest

The authors declared no conflict of interests.

References

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  25. Patel MR, Peterson ED, Dai D, Brennan JM, Redberg RF, Anderson HV, et al. Low diagnostic yield of elective coronary angiography. New England Journal of Medicine. 2010; 362(10):886-95. doi: 10.1056/nejmoa0907272
  26. Eastwood JA, Doering LV, Dracup K, Evangelista L, Hays RD. Health-related quality of life: The impact of diagnostic angiography. Heart & Lung: The Journal of Acute & Critical Care. 2011; 40(2):147-55. doi: 10.1016/j.hrtlng.2010.05.056
  27. Pedersen SS, Martens EJ, Denollet J, Appels A. Poor health-related quality of life is a predictor of early, but not late, cardiac events after percutaneous coronary intervention. Psychosomatics. 2007; 48(4):331-37. doi: 10.1176/appi.psy.48.4.331
  28. Vasheghani-Farahani A, Tahmasbi M, Asheri H, Ashraf H, Nedjat S, Kordi R. The Persian, last 7-day, long form of the International Physical Activity Questionnaire: translation and validation study. Asian Journal of Sports Medicine. 2011; 2(2):106-15. doi: 10.5812/asjsm.34781
  29. Ferrari R, Abergel H, Ford I, Fox KM, Greenlaw N, Steg PG, et al. Gender-and age-related differences in clinical presentation and management of outpatients with stable coronary artery disease. International journal of cardiology. 2013; 167(6):2938-43. doi: 10.1016/j.ijcard.2012.08.013
  30. Namayandeh SM, Sadr SM, Ansari Z, Rafiei M. A cross-sectional study of the prevalence of coronary artery disease traditional risk factors in Yazd urban population, Yazd healthy heart project. International Cardivascular Research Journal. 2011; 5(1):7-13.
  31. Boekholdt SM, Sandhu MS, Day NE, Luben R, Bingham SA, Peters RJ, et al. Physical activity, C-reactive protein levels and the risk of future coronary artery disease in apparently healthy men and women: The EPIC–Norfolk prospective population study. European Journal of Cardiovascular Prevention & Rehabilitation. 2006; 13(6):970-76. doi: 10.1097/01.hjr.0000209811.97948.07
  32. Mameletzi D, Kouidi E, Koutlianos N, Deligiannis A. Effects of long-term exercise training on cardiac baroreflex sensitivity in patients with coronary artery disease: A randomized controlled trial. Clinical Rehabilitation. 2011; 25(3):217-27. doi: 10.1177/0269215510380825
  33. Kendziorra K, Walther C, Foerster M, Möbius-Winkler S, Conradi K, Schuler G, et al. Changes in myocardial perfusion due to physical exercise in patients with stable coronary artery disease. European Journal of Nuclear Medicine & Molecular Imaging. 2005; 32(7):813-19. doi: 10.1007/s00259-005-1768-1
  34. Chomistek AK, Manson JE, Stefanick ML, Lu B, Sands-Lincoln M, Going SB, et al. Relationship of sedentary behavior and physical activity to incident cardiovascular disease: results from the Women's Health Initiative. Journal of the American College of Cardiology. 2013; 61(23):2346-54. doi: 10.1016/j.jacc.2013.03.031

1. Baroreflex is a mechanism that regulates blood pressure using baroreceptors. When blood pressure increases, this reflex leads to widening of the blood vessels and a reduction in the heart rate, and when blood pressure decreases, this mechanism regulates that by narrowing the blood vessels and increasing the heart rate.

Ghamkhar L, et al. Relationship Between Physical Activity and Risk Factors in Patients Suspected with Coronary Artery Disease (CAD). 2016; 6(1):3-8.

Table 1. Measures of central tendency and dispersion (n=92).

K-S Values

Maximum

Minimum

SD

Mean

Variables

0.658

79

24

10.49

54.69

Age (year)

0.380

188

145

9.14

165.27

Height (cm)

0.083

167

43

16.59

78.86

Weight (kg)

-

193

100

19.30

134.53

Systolic blood pressure (mm/Hg)

-

100

45

11.07

77.69

Diastolic blood pressure (mm/Hg)

-

449

73

56.52

122.73

Blood sugar

-

395

97

55.10

166.22

Cholesterol

-

341

59

63.05

142.35

Triglyceride

-

135

31

12.71

43.53

HDL

-

292

36

43.77

95.77

LDL

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Ghamkhar L, et al. Relationship Between Physical Activity and Risk Factors in Patients Suspected with Coronary Artery Disease (CAD). 2016; 6(1):3-8.

Table 2 . Relative chance of CAD for age, smoking, and physical activity variables.

Confidence Interval

Chance for Having CAD

Variables

1.01-1.11

1.062

Age

1.14-14.7

4.10

Smoking

-

-

Low physical activity

0.16-1.31

0.45

Moderate physical activity

0.12-1.47

0.42

High physical activity

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Table 3. The odds ratio of catching coronary artery disease with respect to variables of age, smoking, physical activity.

Confidence Interval

Odds Ratio

Variables

1.01-1.11

1.06

Age

1.14-14.7

4.10

Smoking

0.16-1.31

0.45

Moderate physical activity

0.12-1.47

0.42

High physical activity

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Ghamkhar L, et al. Relationship Between Physical Activity and Risk Factors in Patients Suspected with Coronary Artery Disease (CAD). 2016; 6(1):3-8.

Ghamkhar L, et al. Relationship Between Physical Activity and Risk Factors in Patients Suspected with Coronary Artery Disease (CAD). 2016; 6(1):3-8.

Ghamkhar L, et al. Relationship Between Physical Activity and Risk Factors in Patients Suspected With Coronary Artery Disease (CAD). 2016; 6(1):3-8.

The Relationship between Demographic, Health, Physical Fitness and Socioeconomic Determinants and Functional Performance of Elderly People

Mohamad Rostami1, Zahra Mosallanezhad1*, Afsun Nodehi Moghadam1, Enayat Allah Bakhshi2, Shapoor Jaberzadeh3

1. Department of Physical Therapy, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

2. Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.

5. Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia.

Keywords:

Elderly, Performance, Health, Cognition, Physical fitness, Socio-economic status

* Corresponding Author:

Zahra Mosallanezhad, PhD

Address: Department of Physical Therapy, University of Social Welfare and Rehabilitation Sciences, Koodakyar Ave., Daneshjoo Blvd., Evin, Tehran, Iran.

Phone: +98 (21) 22180039

E-mail: zmosallanezhad@yahoo.com

02 Sep. 2015

09 Jan. 2016

Citation: Rostami M, Mosallanezhad Z, Nodehi Moghadam A, Bakhshi E, Jaberzadeh Sh. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants and Functional Performance of Elderly People. Physical Treatments. 2016; 6(1):9-18.

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Purpose: Increased life expectancy leads to an increase in the elderly population. However, with an increase in the age, the number of chronic diseases and cognitive disorders also increases. Since the social, cultural, environmental, lifestyle and health-related behavior is specific to each nation, the present study aimed at investigating the relationship between socio-economic status, health, physical fitness, and cognitive function in older adults with functional performance in Iran.

Methods: It is a cross-sectional study involving 42 older adults (20 women, 22 men) through a survey questionnaire and accessible sampling method. The age range of the study participants was 60 to 91 years. The questionnaire was used by the examiner to collect information on the age, height and weight, history of diseases, health status, physical fitness, and socio-economic status, for assessing the functional performance of older adults. The three performed tests included Sit-to-Stand test to examine the strength and lower extremity function, the Timed Up and Go (TUG) test to measure the speed and balance while walking and the Purdue Pegboard Test (PPT) for measuring the hand function. A step-wise regression model analysis was applied by using SPSS (version 19).

Results: In sit-to-stand test, the test of significance of regression coefficients was profound in case of dependent variables (marital status (P=0.003) and overweight (P=0.014)). In TUG test, the dependent variables, age (P=0.002), marital status (P=0.081), and cognitive function (P=0.048) were influential on the TUG performance. In PPT, the independent variables, age (P=0.041), gender (P=0.012), marital status (P=0.058), and cognitive function (P=0.001), had a significant effect on the hand function.

Conclusion: Age-related changes, cognitive functions, and socioeconomic status were the most important factors affecting the functional performance of the elderly. Weight and gender also affected some aspects of functional performance. The author further recommends controlling and preventing loss of cognitive function and improving the social status and age-related changes in the older Iranian adults.

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1. Introduction

ging is considered as a quiet and hidden biological process associated with certain degenerative changes in the body structure after maturation, causing a reduction in body functions. Since 1999, the UN Commission on Population and Development has considered the age of sixty as the entering to the elderly age, and those who have passed this age are considered as older adults [1]. Mortality reduction and increased life expectancy have caused an increase in the number of the elderly. In Iran, which is a developing country, based on 2011 census the elderly population has made up to 7% of the total population.

The predictions indicate a considerable increase of about 20-25% in elderly population by 2050 [2]. With aging, the incidence of chronic diseases and cognitive disorders also increases. In addition, some degenerative changes have been observed in the motor system, musculoskeletal system, and brain cortex, possessing a significant effect on the motor functioning in the elderly [3]. Performance deficiency and reduction in the quality of life are the problems experienced by 5-20% of the elderly [4]. For instance, in a study on the performance of the elderly, it was found that the most number of declining in the balance and walking speed occurred from the age of 60 to 70 years [5]. Low-speed walking and decreased physical activity are the major creators of disability, and this reduction or lack of physical activity can be the most important risk factors for the development of morbidity and even mortality [6].

The results of a recent study on the Iranian elderly showed that the performance disorders do have a high contagion, and the life quality and health status creates a dissatisfactory situation [7]. In a study comparing the Iranian and Swedish elderly, it was found that the Iranian elderly have a lower physical health, functional performance, and physical performance as compared to their Swedish counterparts, which justifies the importance of elderly care in Iran [8]. The functional performance include the necessary physical and mental activities for maintaining a healthy life [9] and can be measured with direct and indirect indexes [3].

In this study, to measure the performance capacity of the elderly three tests, such as speed walking and balance, getting up from the chair, and hand function has been used to evaluate the motor functioning of different motion body parts including the upper and the lower limbs. Habits and methods related to the physical activities of each person are formed during the person’s life, and various factors including cultural, social and economic indexes with the social level of the society affect it [10]. Different socioeconomic aspects, such as individual characteristics, urban life, and cultural issues (including perception, tendencies, and behaviors) can affect the health status of every person [11-13]. These dissimilar characteristics of the elderly cause a different rate of disability among the countries worldwide [14].

In this study, the survey questionnaires were used to assess the health status, mental performance, smoking habits, etc., in the elderly, which was self-reported. The survey results were validated are documented as an independent marker for morbidity, mortality, and performance in the elderly [15]. Specific aspects of social, cultural and environmental as well as health-related lifestyle and specific behaviors vary among different nations. The studies conducted in the area of the factors affecting different aspects of the performance in the elderly are mostly related to the western societies, which is very different from the status, lifestyle, beliefs and behaviors, and also some other personal, environmental and social factors in a country such as Iran [10, 11]. The study aimed at analyzing the relationship between demographic, health, physical fitness and socioeconomic determinants, and functional performance of elderly people.

2. Materials and Methods

Participants

In this cross-sectional study, a sample size of 42 senior citizens consisting of 22 men and 20 women were analyzed. The target population included Iranian elderly with an age range of 60 to 91 years (mean age of 70±8.8 years). The samples were chosen in accordance with the convenience sampling method and with the power of 80% as based on the pre-study.

This study was conducted under the confirmation of the Ethics Committee of Tehran University of Social Welfare and Rehabilitation, in different parts of the city of Tehran in 2015. After receiving the complete data and information about the study conditions, the subjects filled in the satisfaction forms and questionnaires and gave their consent for participation. The inclusion criteria were 60 years of age and above [1], independent older adults who were capable of doing their daily activities with or without assistive devices [16], and mini mental state examination (MMSE) test score more than 23, which was used for detecting the cognitive disorders [17].

If any of the candidates had suffered from any severe musculoskeletal defects, visual and auditory deficiencies, balance disorders, and frequent dizziness, which were registered in their medical records or at the time of conducting the study were excluded from the study. According to the opinion of the medical supervisor, these disorders could block the elderly cooperation in the study [18].

Data collection

Data collection instruments

The data-collecting questionnaire was used as a study instrument through which the age, height, weight, history of the diseases of various body systems, health status, and physical fitness was determined by the tester and completed in interviews and self- report [8]. The data related to the performance activities was collected through evaluating the elderly people during the test [8, 9].

Background information

The data with relation to age, gender, height, weight, and hand function of the most of the samples were recorded. To measure the weight and height, a scale and a tape meter were used, respectively.

Health status

The questions were answered in the self-report method. The questions included:

  • How do you evaluate your health status? (Very bad, bad, almost good, good, very good),
  • Do you feel a general tiredness? (Yes, no), and
  • How much do the musculoskeletal problems affect your general health status? (Very much, much, average, little, very little).

And finally, various health problems such as heart-vascular system, respiratory system, digestive system, etc. which threaten the one’s health were questioned. MMSE test was also used to analyze the individual’s psychological health.

Physical fitness status

The factors like body mass index (BMI), regular work out (yes, no), and physical fitness status (very bad, bad, almost good, good, very good) were recorded by the subjects in the self-report.

Socioeconomic status

The subjects were asked to report their level of academic education (including under diploma, diploma, BA, MA, MSc., and any higher degrees) and marital status (the elderly ones who were living with their spouse were considered married, and those who have lost their spouse or divorced were considered single).

Smoking/drinking habits

The subjects were questioned about their smoking or alcohol drinking habits and duration of the habits (at present, it’s been five years I have stopped, it’s been more than five years I have stopped).

Functional performance

The elderly in this study were evaluated for their performance activities through the following tests:

Sit to Stand Test

This test is known as the 30-second-Chair-Stand Test (CST), which analyzes and evaluates the physical performance in the elderly people. The test analyzes the muscle strength around the knee muscle and lower limb in the elderly. The CST test is widely preferred in case of elderly because it is very simple and applicable for elderly with a lot of simple moving problems [19, 20]. The subject is asked to simultaneously sit down and stand up on a 43 cm chair for 30 sec, and the repetition of the action is calculated [21].

Time Up and Go (TUG) test

This is a functional test in which the walking speed, balance, and the one’s performance are analyzed. It is also considered as a simple and cost effective way that includes daily movements [22, 23]. This test includes getting up from the 45 cm chair, walking for 3 m, turning and coming back, and then sitting down on the chair. The time taken by the subject for completion of the process is calculated [23].

Hand performance test

This test is known as the Purdue Pegboard Test (PPT), which was designed by Joseph Tiffin in 1948 to analyze the hand skill and the coordination between the two hands. This test is capable of analyzing two different features, such as the gross and fine hand movement and fingers. This test includes a board with some holes on it and some small iron bars and two kinds of washer, which are placed in the holes as per the instruction manual [24]. Data analysis was conducted through a step-wise Logistic Regression model, with the use of SPSS version 19.

3. Results

Descriptive statistics

Almost about half of the participants were women (47.6%). The mean age of the women and men participating in this study was 79.7±8.68 years and 44.9±9.71years, respectively. Sixty-nine percent of the participant lived with their spouses, and 31% of them have lost their spouses or were divorced. Twenty-three of the total participants (54.7%) were overweight (BMI≥25). The MMSE mean score in the study was 27.9±1 (23≤MMSE≥30). Only 23% of the elderly had a regular exercise program, and exactly the same percentage of participants felt general tiredness. Fifty percent of the total elderly people reported good health status, and 47.7% of them reported almost good health status. Whereas the physical fitness status of 50% elderly was almost good, for 43% it was good, and for 7% it was very good.

Regression analysis

For each of the performance tests, a separate regression model was evaluated. In each of the models, one of the performance tests (Chair Sand Test, walking and balance speed test or hand performance test) was considered as the dependent variable, and the collection of the background variables, variables related to the health status, physical fitness, and socioeconomic status were chosen as the independent variables in the study.

Chair Stand Test (CST)

The regression coefficient and the level of the significance related to the effects of the dependent and independent variables in the Chair Stand Test showed that the variables of marital status (P=0.003) and overweight (0.014) had a significant influence on the performance of standing P-value from the chair (Table 1). The results showed that in the case of overweight elderly, the proportion specific to CST was 1.58 lower than the elderly with normal weight. In the elderly who lived with their spouses, the amount of CST was 2.93, which was more than those who lived alone.

Timed Up and Go Test

The analysis of regression coefficient and the level of the significance in relation to the effects of the independent variables on the independent variable of the speed and the balance of walking showed that the variables of age (P=0.002), marital status (P=0.081), and cognitive status (P=0.048) had a significant influence on TUG (Table 2). The results showed that:

  • With the increase in the age, the time taken by the elderly for completion of the TUG test increased by 0.27, and
  • With the increase of MMSE score, the time of the TUG test is reduced by 0.90.

In the elderly who lived with their spouses, the time of performing the TUG was 2.92 credits less than those who lived alone.

Hand Performance Test

The analysis of regression coefficient and the level of the significance in relation to the independent variables on the independent variables of hand performance showed that the variables of age (P=0.041), gender (P=0.012), marital status (P=0.058), and cognitive status (P=0.001) had a significant influence on the hand performance (Table 3). The results showed that:

  • With increasing age, the PPT level decreased by 0.237,
  • In the case of women subjects, the PPT score was more than 5.032 as compared to the male counterpart,
  • With each unit increase in the MMSE score, the amount of PPT is increased to size 1.88, and
  • Elderly who lived with their spouses, the PPT was 4.15 more than the elderly who lived alone.

4. Discussion

Overview of the results

The overall results showed that marital status and overweight were the factors affecting the chair stand test, whereas the factors affecting the Timed Up and Go test were age, marital status, and the MMSE test score. In addition, the factors affecting hand performance were age, gender, MMSE test score, and marital status.

Chair Stand Test

Based on our findings, the married elderly with lower weight could perform the chair stand test better. However, the overweight factor in the elderly can hasten the declining physical performance. This Age related process can cause weakness and morbidity and reduction in the quality of life in the elderly performances [25, 26]. Many factors from the physiologic and cognitive aspects are related to the chair stand test. Hence, this test is not considered as the sole indicator of the power in the lower limbs.

In a study by Lord et al. (2002), the performing chair stand test in addition to knee flexor muscle highlighted the other important factors, such as body weight, pain, anxiety and worries, depression, mood, and other sensory-motor processes. Body weight, as an independent indicator, indicates that lifting and lowering a body with high weight requires more energy and work. On the other hand, the elderly performance in this study was not dependent on the height, gender, and age, which could be in the same way as suggested by our results.

The participants’ motivation and perception along with the three other factors of anxiety, pain, and vitality are the influencing psychological factors in this test [27], which can be related to the marital status of the elderly. This refers to those who live with their spouses and are presented with less anxiety level, better physical performance, and more satisfaction in life [28]. In a study by Kaplan et al. (1993), they could not find any significant relationship between the weight and activities of daily living, functional performance and mobility of elderly subjects. [29]. But in this study, it was shown that there is a significant correlation between being married and physical performance in the elderly. Those who live with their spouse showed a higher physical performance [29]. In our study, gender did not influence the performance, but in the study by Cardoso et al. (2013), it was seen that men did show a lower performance [30].

TUG test is used to evaluate the performance of the lower limb and components such as speed and balance. The results of this study indicated that the physical performance is influenced by variables, such as age, marital status, and cognitive status of the subjects. In a previous study, it was observed that there was no difference between balance and walking characteristics between both the genders, which means the range and the age of starting disorders in men and women are the same. However, in lower age, balance problems are associated with more disorders in comparison to the walking speed [5].

Many studies have reported that the walking speed and balance decrease with aging [31-34]. Balance, walking speed, and mobility start decreasing from 40 to 60 years old [31, 34-36]. TUG test is a disability-indicating test. It is said that walking speed is related to the disability [6, 37, 38]. In a study by Samson et al. (2001), the results indicated that walking speed decreases with aging, but weight does not have any specific effects on walking speed, which is in the same line with the results of the present study [39]. In a study by Rosano et al. (2004), it was shown that there was a statistically significant relationship between the physical performance and cognitive performance. In this study, they used Teng-modified MMSE to evaluate the cognitive status of the elderly, which included the characteristics of the MMSE test. The results of this study supported the hypothesis that lower walking speed can be indicative of the weaker cognitive performance, which is in the same line with the present study results [40].

Among other findings of the present study, hand performance in both the genders was seen to decrease with aging. In fact, the more is the age, less is the PPT score [41]. The greater decrease was seen in elderly after the age of 65 years. The worse hand performance in the elderly is mostly related to the second and degenerative changes in the musculoskeletal, cardiovascular, and nervous system [42]. MMSE is one of the most applied methods for evaluating the cognitive disorders in the elderly [43]. Leveille et al. (1998) stated a clear relationship between the MMSE low scores and difficulty in performing daily activities [44].

In another study by Weuve et al. (2004), it was observed that those who have a high level of activity possessed better cognitive performances. And the cognitively active people showed less decrease in their performance [45]. As it is seen in the present study, in both the hand and walking speed tests, two variables of age and MMSE were influential. This was confirmed by other studies in which the MMSE score test decreased with aging, and this decrease intended towards more speed in elderly more than 70 years old [46, 47]. Marital status had significant relationship with other three performance tests. One of the reasons can be the effect of being married on the quality of life in aged population. Among other possibilities, it can be referred to the fact that some other tests are not just related to the muscle power and some psychological factors are also involved in determining the quality of performing these tests [27].

In a study by Kaplan (1993), the results indicated a relationship between marital status and physical performance in the elderly [48]. The quality of life of the married elderly is of high level, and separated or divorced elderly have the least amount of life quality. Quality of life includes different aspects, such as physical performance, self-care, life satisfaction, depression, and anxiety [28, 49]. These findings are in the same line with the present study.

One the variables affecting hand performance is the gender, and this variable has been only observed in PPT in which used for determining the hand performance level. Senior women in comparison to their men counterparts showed a better performance. Gender differences in upper limbs performance are dissimilar in the studies. In the studies dealing with healthy samples, and PPT has been used as a test, and the results indicated that women’s performance was much better than the men [24, 41].

In a comparative study which was among the elderly people in Iran and Sweden, it was observed that the level of physical activity in senior women was more than the men, which was opposite of the findings in Sweden [8]. In another study by Hackel et al. (1992), they used Jebsen test to evaluate hand performance. Based on the results, gender had a slight effect on the hand performance, but in some parts of the test, women performed better and faster than men [50]. On the other hand, in a study by Smith et al. (1999), which was about the slight hand movement of the elderly, the results showed no difference between both the genders [51]. In another study, the mean score of PPT for senior men was 8.20, and for women, it was 3.20, which was the opposite of the findings of this study [52]. Hence, it can be concluded that the women doing simple hand performance showed better performance than the men [53].

The present findings indicate a significant effect of the marital status, age, cognitive status of the elderly, gender, and also the weight of the elderly on different parts of the body performance, such as upper and lower limbs.

The most important and significant limitation of this study was the smaller sample size of the target population who were analyzed. Hence, the deduced findings might not be a generalized indicator for the total elderly population. Such limitation can be overcome by random sampling among the elderly in the society, and a larger sample size needs to be studied for better generalization of the outcomes.

Application

The findings of the present study can provide useful information to recognize the effective of various factors on the performance of the elderly and suggest effective ways to apply to their performance in the area of rehabilitation, such as improving the cognitive status of the elderly and reducing the mental pressure on them and their loneliness.

Acknowledgements

This paper had no financial supporters. We highly appreciate the elderly people who have given their consent for participation and have collaborated in this study. .

Conflict of Interest

The authors declared no conflict of interests.

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  53. Michimata A, Kondo T, Suzukamo Y, Chiba M, Izumi SI. The manual function test: norms for 20- to 90-year-olds and effects of age, gender, and hand dominance on dexterity. The Tohoku Journal of Experimental Medicine. 2008; 214(3):257-67. doi: 10.1620/tjem.214.257

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Table 1. The effective variables on the chair standing in the elderly.

Sig.

T-Score

Non-Standard Regression Coefficient

Standard Regression Coefficient

Independent Variable (Predictor)

Dependent Variable (Criterion)

0.014

-2.565

-0.376

-1.851

Overweight

30 second chair stand test

0.003

3.193

2.390

0.451

Marital status (the married)

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Table 2. The effective variables on the speed and the balance of the elderly more than 60 years old.

Sig.

T-Score

Non-standard Regression Coefficient

Standard Regression Coefficient

Independent Variable (Predictor)

Dependent Variable (Criterion)

0.002

3.384

0.269

0.472

Age

Timed up and go

0.048

-2.041

-0.896

-0.307

MMSE

0.081

-1.791

-2.924

-0.272

Marital status (married)

AWT IMAGE

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Table 3. The effective variables on hand performance in the elderly population of more than 60 years old.

Sig

T-Score

Non-Standard Regression Coefficient

Standard Regression Coefficient

Independent Variable (Predictor)

Dependent Variable (Criterion)

0.041

-2.111

-0.237

-0.317

Age

Purdue Pegboard Test

0.012

-2.641

-5.032

-0.385

Gender (men)

0.001

3.550

1.876

0.489

MMSE*

0.058

1.949

4.154

0.294

Marital status (married)

*MMSE: Mini Mental State Examination.

PHYSICAL TREAAWT IMAGEMENTS

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

Rostami M, et al. The Relationship Between Demographic, Health, Physical Fitness and Socioeconomic Determinants & Functional Performance. Physical Treatments. 2016; 6(1):9-18.

The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women

Safoura Ghasemi1*, Heydar Sadeghi1, Ahmad Tahamoli Roudsari2, Zahra Basiri2

1. Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Kharazmi University, Tehran, Iran.

2. Department of Rheumatology, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.

Keywords:

Bone density, Water exercise, Land exercise, Combined environment exercise, Premenopause

* Corresponding Author:

Safoura Ghasemi, PhD Candidate

Address: Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Kharazmi University, Tehran, Iran.

Phone: +98 (918) 8117079

E-mail: safouraghasemi@gmail.com

13 Nov. 2015

28 Jan. 2016

Citation: Ghasemi S, Sadeghi H, Tahamoli Roudsari A, Basiri Z. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

AWT IMAGE

: :

A B S T R A C T

Purpose: Given that physical activity is the most important environmental moderating factor, it has been known as an effective, available, low-cost and non-pharmacological approach to increase or maintain bone density at different ages. The purpose of this study was to investigate the effect of 12 weeks of training in water, on land and combined environment on bone mineral density in premenopausal women.

Methods: In this quasi-experimental study with a pretest-posttest design and a control group, 40 premenopausal women aged between 40 and 45 years were divided into four groups (with 10 patients each) based on the exercise environment: water, land, combined, and controlled. Each group exercised three days a week for 12 weeks, with each session lasting 70 minutes. The lumbar vertebrae bone mineral density of the participants was measured by DEXA before and after 12 weeks and the data were analyzed using descriptive statistics, ANOVA, Analysis of covariance and LSD, with the significance level of .For statistical calculations, SPSS software version 21 was used.

Results: In the combined environment group, the lumbar vertebrae bone mineral density showed a significant increase (P>0.05), while in the control group first vertebra bone density loss was observed for the second and fourth lumbar vertebrae(P<0.05). In comparison with the control group, there was a significant difference among the first and fourth lumbar vertebrae bone mineral density in the water exercise group;first, third and fourth lumbar vertebrae density in the land exercise group; and all lumbar vertebrae density in the combined environment group.

Conclusion: Given that there was no difference observed between water and land exercise groups,exercise in any environment is recommended for premenopausal women because the least effect that exercise can have is prevention of bone loss in these ages.

CrossMark

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O

1. Introduction

steoporosis is the most common metabolic bone disease that reduces bone mass density (BMD) and destroys its microstructure, which increases the risk of fractures. With aging, women lose 30-50% of trabecular bone mass and 25-30% of cortical bone mass. Women lose most of their bone mass during premenopause and postmenopause. The prevalence of osteopenia and osteoporosis among premenopausal women is 15% and 6%, respectively [1] and the reported decrease in BMD for these women is between 0.25% and 1% per annum [2]. Studies have shown that maintaining optimal level of bone mineral density during premenopause is important for reducing the risk of osteoporosis and fractures during the post-menopause period, which is associated with an increased relative risk by 1.5 to 3 times [1].

There are different strategies for different age groups to increase or maintain bone density [2]. However, one effective, low-cost and non-pharmacological approach to achieve this goal is physical activity, which is the most important environmental factor modulator to increase or maintain bone mineral density in adults and children [3]. Habib-Zadeh et al. (2010) investigated the effect of walking on BMD (hip and lumbar vertebrae) of 40 obese and thin non-athlete girls and did not observe a significant effect on hip and waist BMD of the subjects [4].

Molhim (2004) showed that three months of jogging led to an increase in hip and spinal bone density and weight loss in obese, active women aged between 25 and 50 [5]. Kahn’s study (2001) showed that bone mineral density is higher in organs that are tolerant of body weight [6]. Bassey and Ramsdale (1995) investigated the effect of weight-bearing exercise of high and low intensity within a year on postmenopausal women and did not observe a significant difference in BMD values of the subjects [7]. Kelley et al. (2001) showed the positive effect of stretching exercises on bone mineral density of the hip, radius and lumbar vertebrae of postmenopausal women [8].

Smidt et al. (1992) investigated the effect of a year of stretching exercises on postmenopausal women and did not observe a significant relationship between exercise and bone mineral density of the hip and lumbar vertebrae [9]. Chien et al. (2000) studied the effect of 24 weeks of aerobic exercises on bone density in postmenopausal women and showed a positive impact in increasing bone density in cervical, lumbar and thigh vertebrae [10]. Mousavian et al. (2015) examined the effect of Pilates exercise on osteoporosis of women aged 50 to 60 years and observed that 12 weeks of Pilates exercise increases the bone density of the hip and waist [11].

Most research has been carried out in a land environment, while exercise in water has a positive impact on coordination and perceptual, vestibular and visual systems [12]. Besides, a water environment imposes a resistance tailored to the needs of each individual’s body, causes muscle activity and engages the larger muscle groups to overcome resistance. It also increases mechanical stress on bones and thus stimulates bone formation [13]. In this context, there are few studies on the impact of exercises in water on BMD. Vanaki et al. (2014) investigated the effect of 12 weeks of weight-bearing exercises in water on bone density of sedentary middle-aged women and concluded that exercise in water increased bone density [14].

Tofighi and Hefz Allesan (2010) examined the effect of 12 weeks of aerobic and resistance exercises in water on bone mineral density of postmenopausal obese women and observed a significant increase in bone mineral density [15]. Mohammadi (2013) reported in his master’s thesis that 8 weeks of exercise on land and water increased bone density in postmenopausal women of 50-75 years of age [16]. However, Bravo et al. (1997) concluded that 12 weeks of weight-bearing exercises in water had no effect on bone mineral density of the thigh and caused a decrease in lumbar bone mineral density in postmenopausal women [17].  

A review of the literature suggests that most studies have been conducted in a land or water environment and they show contradictory results. On the other hand, most researches have been carried out on postmenopausal women while a more appropriate approach would be to investigate the effect of exercise on bone density before menopause. Such a study could help prevent osteoporosis by designing optimum exercise strategies, including the type of exercise (endurance and strength, weight-bearing) and the environment (land, water or a combination of both) that is more suitable for a particular part of the body. Therefore, the aim of the present study was to investigate the effect of 12 weeks of exercise in water, on land and in a combined environment on bone mineral density in premenopausal women.

2. Materials and Methods

Subjects

The population of this quasi-experimental study pretest-posttest with the control group that is of applied type study consisted of premenopausal women of 40 to 45 years of age living in Hamadan in 2015. The research protocol was approved by the Research Ethics Committee and informed consent was obtained from the individuals. A questionnaire was distributed among 100 women. It included fields for age, height, weight, history of fractures later in life, medicine consumption, calcium intake, physical activity, number of deliveries, age of menarche, pregnancy and disease.

Based on a doctor’s reference, 40 women with the inclusion criteria voluntarily participated in the study. The inclusion criteria consisted of the following: Lack of rheumatoid arthritis diseases, hypothyroidism or hyperthyroidism, parathyroid and adrenal disorders, diabetes mellitus, renal failure, advanced liver failure, cardiovascular disease, neurological disorders, traumatic brain injury, lower extremity injuries, menopausal symptoms, fractures, any type of cancer, menstrual disorders beginning after 18 years of age, permanent cessation of menstruation or cessation during the last quarter, less than 6 months period in the previous year, ovary removal before menopause and infertility or pregnancy or breast-feeding during the study period, smoking and alcohol consumption, drug addiction, deformity of the vertebrae, hospitalization due to illness during the two weeks prior to the study, complete bed rest for 3 consecutive months, consumption of estrogen and progesterone medicines, t-score less than -2.5, and consumption of calcium, multivitamins and vitamin D pills and injections of vitamin D3.

The participants were divided in four groups of 10 people each based on the environment in which they were to exercise: in water, on land, in a combined environment, and as a control group. Each of the first three groups performed sport activities for 12 weeks, three times a week with each session lasting for 70 minutes. At least one day of rest was provided between sessions. The control group had no sport activities during these 12 weeks. All participants were asked to avoid food supplements, vitamin D tablets and calcium intake during the period of investigation and were prohibited from using any medicinal drugs (particularly those that affect bone density) without consulting their doctor.

Exercise protocols

Exercise protocol in the water

The water temperature was set between 29 and 30°C and the water level varied from the seventh cervical vertebra (first four weeks), to Xiphoid (fourth-eighth week) and the anterior superior iliac vertebrae to (ninth-twelfth week) [18]. When participants entered the water, they performed warming-up and stretching exercises (20 minutes), for the muscles of the lumbar region and the lower extremities. Resistance exercises (20 minutes) were performed without aid in the first four weeks with waterproof equipment being used in weeks 5 to 12.

Bars, dumbbells and barbell were used to exercise the upper body resistance. These exercises included bench press, rotation of the waist, lumbar flexion and extension. On the other hand, foam pads were used to exercise the lower body resistance through plantar and ankle dorsiflexion, leg press, knee flexion and extension, hip abduction and adduction and hip flexion-extension. These aid tools cause resistance when the water moves. Since water resistance increases with faster movements, the participants performed the exercises in a range of motion sand at greater speed. To control the exercise intensity, the heart rate was measured at each session. Endurance exercises (20 minutes) in water included walking, hopping and jumping in different directions. Cool-down exercises in the water included muscle relaxation exercises such as floating and stretching [19, 20].

Exercise protocol on land

A 10-minute warm-up routine included walking, running at slow speed and stretching exercises. Strength exercises (35 minutes), with 50% in open kinetic chain and 50% in closed kinetic chain, included 8 motions (stretching Latissimus, flexion of the knee, standing leg press, trunk extension, seated knee press, knee extension, seated leg press and sit-ups) [21-22]. For the first four weeks, with 1-2 sets of ten repetitions with an intensity of 60-65%, 1RM was considered. For the second four weeks with 3 sets of 8 repetitions and the intensity of 70-75%, 1RM and for the third four weeks with 3 sets with 10 repetition sand intensity of 75-80% 1RM was considered for exercise [21-22]. A minute’s rest was considered between sets. In addition to identifying 1RM before the exercise, the first of each month 1RM was repeated. Endurance exercises (15 minutes) included walking on the treadmill with 60-65% of maximum heart rate (30 seconds between each set) and cool down (10 minutes) including relaxation and stretching.

Combined environment protocol

It included 6 weeks of training in water and 6 weeks of training on land. Instead of dividing the exercise routine into three blocks of four weeks each, this type of exercise divided it into three blocks of two weeks each. Exercises during each two-week block were carried out based on the protocols established for water (first week) and land (second week).

Tools and data collection

To measure the height (cm), a standing stadiometer with 1 mm accuracy (after a normal exhale) was used, while the weight (kg) was recorded by using a digital scale with 0.01 kg accuracy with minimal clothing and without shoes. Bone density at two locations  (Proximal femoral and lumbar vertebrae L1 to L4) were measured by DEXA with Dexa X-ray, model Dexxum-T of OSTEOSYS Co. made in South Korea (Figure 1), evaluated by a specialist. After obtaining the weight, bone densitometry was measured by the central apparatus, during which the subject lay on her back on the machine bed with the receiver of the device placed on the area of the body that was intended to measure bone density.

The X-ray was directed towards the bones of the lumbar vertebrae and the hip in the pelvic area. This method is simple, quick, non-invasive and painless; it does not require general or local anesthesia for testing and measures bone density within 10 to 20 minutes. Prior to the study, densitometry and its possible harmful side effects were explainedto all participants. Bone mineral density was calculated in grams per square centimeter and its results were instantly ready via computers connected to the device.

All tests related to bone density were investigated before and after the exercise period of 12 weeks, with a 48- to 72-hour interval after the last exercise session. For statistical analysis, the mean and standard deviation was used to describe the information, the Kolmogorov-Smirnov test was used for examining normality assumption for the measured parameters, and parametric ANOVA, analysis of covariance and LSD were used to investigate significant group differences. To perform the analysis of covariance, first analysis assumptions were examined. To ensure that the data for this study are the underlying assumptions to estimate covariance analysis, four assumptions of Covariance including the natural distribution of scores (P≥0.05), Homogeneity of variances (P≥0.05), Conformance slope of regression (P≥0.05), and Pre-test and linear correlation and the dependent variable (P≤0.05) were reviewed and approved and the LSD post hoc test was used to compare the groups. Tests were analyzed at a significance level of 0.05 using SPSS version 21.

3. Results

As may be observed in the table related to the mean, standard deviation and anthropometric characteristics of the subjects (Table 1), ANOVA revealed that the participating groups were homogenous in terms of age, height, weight, and body mass index (BMI).

The mean and standard deviation of Bone Density of Lumbar Vertebrae L1, L2, L3 and L4 in the pre-test and post-test of water exercise, land exercise, combined exercise and control groups are provided in Table 2. Mean bone density increased in all the variables in water exercise, land exercise and combination groups, while in the control group bone density decreased in all the variables after 12 weeks.

The results of analysis of covariance (Table 2) for the first and fourth lumbar vertebrae variables (Lumbar Vertebrae), the first lumbar vertebrae (L1), the second lumbar vertebrae (L2), the third lumbar vertebra (L3) and fourth lumbar vertebra (L4) after the exercise shows that by removing the effect of pre-test and post-test scores, values of these variables are statistically different (P<0.05). Except for the first and fourth lumbar vertebrae (Lumbar Vertebrae), no significant difference was observed in the results of analysis of covariance in this variable among the groups (P<0.05).

Comparing the groups two-by-two (LSD) in Table 3 shows that in the Lumbar Vertebrae, only the combination group compared with the control group (P=0.19) showed a significant difference; in the other groups, no difference was observed in this variable. In the region of L1, water exercise group (P=0.008), land exercise (P=0.017) and combination (P=0.037) showed a significant difference compared with the control group and in comparing the two other groups, no significant difference was observed in this variable. In the L2 area, water exercise group (P=0.016) and combination group (P=0.002) showed a significant difference compared with the control group and in comparison of pairs of other groups no significant difference was observed in this variable. In the L3 area, water exercise group (P=0.013) and combination group (P=0.001) showed a significant difference compared with the control group, the combined group had a significant difference with the land group (P=0.014). There was no significant difference in the other groups in this variable. In the area of L4, the water exercise group (P=0.06), the land exercise group (P=0.012), and the combination group (P=0.001) showed a significant difference compared with the control group.

4. Discussion

The current study has been conducted to investigate the effect of 12 weeks of training in water, on land and in a combined environment on bone mineral density of premenopausal women. Earlier studies have been conducted only on postmenopausal women. On the other hand, the current study took into consideration premenopausal women, and that too in specific training environments.

The study has been conducted on premenopausal women in three training environments (water, land and combination of both). The results showed that 12 weeks of exercise in all three environments increased bone mineral density of the lumbar vertebrae, though only the combined environment showed this increase to be significant (first to fourth lumbar vertebra and the second lumbar vertebrae). In the control group, loss of bone mineral density of the lumbar vertebrae (first, second and fourth) was observed.

In comparison with the control group, there was a significant difference among the first and fourth lumbar vertebrae bone mineral density in the water exercise group; First, third and fourth lumbar vertebrae density in the land exercise group; And all lumbar vertebrae density in the combined environment group. While pair test results showed no statistical difference among the groups (excluding the difference observed between the combination training group with group of exercise on land in the second and third lumbar vertebrae).

The results of this study were consistent with the study by Kahn et al. (2001), which reported higher density in body weight bearing organs. In this study, it seems that exercise caused the increased density with some mechanical stress imposed on the lumbar vertebrae. Results of exercise on the land group showed significant increase in first, third and fourth vertebrae in comparison with the control group and there are similarities with the findings of Molhim (2004), who conducted the training for a similar period as in this study. However, the age of participants in Molhim’s study was between 25 and 50 years [5] and the study examined all the vertebrae [5].

Kelley et al. (2001) showed the positive impact of stretching exercises on the lumbar vertebrae [6] and the results were consistent with the findings of the present study. However, but the difference is that their sample comprised postmenopausal women and exercises were of stretching type, while the current study followed combined exercises, which had a significant positive effect on the entire vertebrae. The results of Chain (2000) were also consistent with the results of this study [10], but the duration of their study was twice that of the present study and their study was conducted on postmenopausal women. On the other hand, the present study showed positive results with a shorter duration and more pressure on younger women.

Results of this study are consistent with the study by Mousavian et al. (2015), which had a duration similar to the current study [11], but the exercises of their study were of Pilates type and performed on land by women of 60 to 65 years of age. In contrast, the exercises of this study were carried out in water, on land and in a combined environment on much younger subjects. In the present study, exercise on land had a positive effect only on the first, third and fourth lumbar vertebrae. In this study, results of the water exercise group showed a significant increase in L1 to L4 area compared with the control group, which is consistent with the results of a study by Vanaki et al. (2014), which was conducted over 12 weeks and in the form of weight bearing exercises in water [14].

However, the subjects in the research by Vanaki et al. were sedentary women aged 50 to 70 years and the study observed a significant effect on the lumbar vertebrae. In comparison, the subjects in this study were younger and the exercises just had a positive effect on single lumbar vertebrae and no significant effect on the first to fourth vertebrae. Tawfighi and Hefz Allesan (2010) investigated the effect of 12 weeks of aerobic and resistance exercises in water on the lumbar and hip vertebrae and observed a significant increase in hip bone mineral density [15]. Like the current research, they observed no significant difference in the entire level of the lumbar vertebrae. Their research was on obese postmenopausal women, a significant departure from this study.

The results of the current research can also be compared with the study by Mohammadi et al. (2013) on osteoporosis in postmenopausal women with an exercise regimen of 8 weeks in land and water environments [17]. In their study, exercise in water was more influential than exercise on land, while in the present study there is no statistical difference between exercise on land and water. In this study, in conjunction with the group of exercises in the combination environment, a significant increase was observed in all variables compared with the control group, but other similar studies are lacking.

Results of this research were inconsistent with a study by Habib-Zadeh et al. (2010) in which significant effects on bone mineral density was observed on obese and thin girls [4]. Possible causes of this inconsistency can be the shorter duration (two months), low-intensity workouts (walking with a heart rate of 50% to 75%) or lower age and weight of subjects compared to the current study. The results of this research were inconsistent with Smidt et al. (1992) and Bassey and Ramsdale (1995) [7, 9]. Duration of exercises in their study was a year. It seems that the difference was probably due to the difference in intensity and age of participants (in their research postmenopausal women were investigated). Research by Bravo et al. (1997) was also inconsistent with our research. They observed that 12 weeks of weight-bearing exercises in water caused a decrease in lumbar bone mineral density in postmenopausal women [16]. Inconsistency of this research may be due to menopause and its negative effects on bone mineral density.

A holistic comparison of the current study with previous researches shows that there was consistency in some areas and exercise types and inconsistency in some variables. A reason for this could be that in previous researches the first and fourth lumbar vertebrae were considered generally and not evaluated separately. However, in this study, in addition to the first and fourth vertebrae, the individual vertebrae were investigated separately to provide more precise information on the effect of exercise on bone mineral density of the lumbar vertebrae.

According to the findings, although the exercise environment (water, land, or a combination of both) and study area (lumbar vertebrae in whole or discrete) are the significant factors affecting bone density, but in general, exercise has a positive effect on bone mineral density of the lumbar vertebrae. Therefore, the least effect that exercise can have is prevention of bone loss at an age approaching menopause.

Despite supplementation and drug control on the subjects of this study, the inability to control daily calorie intake in people over a period of 12 weeks was a limitation of this study. It is suggested that future researches need to consider additional information about the effect of exercise on muscles, bone density of the hip area at the same time with the lumbar vertebrae, and conduct the investigation with more number of subjects over a longer duration to investigate the follow-up effects of exercise on bone mineral density.

Acknowledgments

This paper was extracted from the first author' PhD dissertation, Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Kharazmi University, Tehran. The cooperation of all subjects participating in this study and officials of bone densitometry at Hamadan clinic, gym and pool is appreciated.

Conflict of Interest

The authors declared no conflict of interests.

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  21. Liang MT, Braun W, Bassin SL, Dutto D, Pontello A, Wong ND, et al. Effect of high-impact aerobics and strength training on BMD in young women aged 20-35 years. International Journal of Sports Medicine. 2011; 32(2):100-08. doi: 10.1055/s-0030-1268503
  22. Kisner C, Colby LA. Therapeutic exercise: Foundations and techniques. Philadelphia: F. A. Davis Company; 2012.

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

AWT IMAGE

Figure 1. DEXA, X-ray Dexa, Model Dexxum-T, OSTEOSYS Co. made in South Korea.

PHYSICAL TREAAWT IMAGEMENTS

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

Table 1. Anthropometric characteristics of the subjects participating in this study.

Group of Water Exercise

Group of Land Exercise

Combined Environment Group

Control Group

P

SD

Mean

SD

Mean

SD

Mean

SD

Mean

Age

1.64

43.30

2.20

42.20

1.72

42.50

1.84

43.50

0.35

Height

3.62

158.11

7.87

158.10

6.52

160.72

6.46

160.53

0.66

Weight

11.09

75.53

6.83

72.68

9.13

71.02

11.60

71.07

0.51

Body Mass Index*

4.07

30.17

3.74

29.24

3.44

27.74

4.73

27.68

0.34

*BMI: Proportion of weight to square of height (Kg/m2).

PHYSICAL TREAAWT IMAGEMENTS

Table 2. Descriptive and analytical results of analysis of covariance in four groups and five bone density areas before and after exercise.

Area

Test

Water

Land

Combination of Both

Control

First to fourth lumbar vertebrae

Post-test

1.32±40.104

1.263±0.102

1.322±0.092

1.253±0.154

Pre-test

1.278±0.116

1.226±0.093

1.240±0.156

1.279±0.200

First lumbar vertebrae (L1)

Post-test

1.308±0.123

1.251±0.079

1.257±0.136

1.223±0.131

Pre-test

1.274±0.114

1.204±0.117

1.233±0.129

1.294±0.145

Second lumbar vertebrae (L2)

Post-test

1.333±0.124

1.240±0.096

1.327±0.163

1.255±0.128

Pre-test

1.291±0.094

1.230±0.089

1.251±0.139

1.304±0.161

Third lumbar vertebrae (L3)

Post-test

1.334±0.096

1.210±0.108

1.318±0.147

1.235±0.164

Pre-test

1.309±0.121

1.201±0.118

1.249±0.175

1.274±0.183

Fourth lumbar vertebrae (L4)

Post-test

1.309±0.121

1.189±0.120

1.264±0.221

1.220±0.187

Pre-test

1.301±0.107

1.164±0.129

1.215±0.239

1.296±0.230

Area

Resource

Sum of Square Type III

Degree of Freedom

F Statistics

P-Value

First to fourth lumbar vertebrae

Constant

0.170

1

24.720

0.000

Pre-test

0.242

1

35.120

0.000

Group

0.047

3

2.290

0.095

First lumbar vertebrae (L1)

Constant

0.055

1

9.076

0.005

Pre-test

0.297

1

48.640

0.000

Group

0.060

3

3.272

0.032*

Second lumbar vertebrae (L2)

Constant

0.017

1

2.838

0.101

Pre-test

0.393

1

64.247

0.000

Group

0.076

3

4.156

0.013*

Third lumbar vertebrae (L3)

Constant

0.045

1

12.295

0.001

Pre-test

0.496

1

136.387

0.000

Group

0.059

3

5.447

0.002*

Fourth lumbar vertebrae (L4)

Constant

0.033

1

7.864

0.008

Pre-test

0.869

1

206.689

0.000

Group

0.068

3

5.389

0.004*

*Significant difference in level of P≤0.05.

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

PHYSICAL TREAAWT IMAGEMENTS

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

Table 3. The results of comparing groups two-by-two in LSD post hoc test.

Areas of Bone Density

Groups

Groups

Mean Difference

SD

P

First to fourth lumbar vertebrae

Control

Water

-0.071

0.037

0.064

Land

-0.040

0.037

0.293

Combination

-0.091

0.037

0.019*

Water

Land

-0.031

0.037

0.414

Combination

-0.020

0.037

0.588

Land

Combination

-0.051

0.037

0.176

First lumbar vertebrae (L1)

Control

Water

-0.099

0.035

0.008*

Land

-0.091

0.036

0.017*

Combination

-0.077

0.035

0.037*

Water

Land

0.008

0.036

0.816

Combination

0.022

0.035

0.535

Land

Combination

0.014

0.035

0.699

Second lumbar vertebrae (L2)

Control

Water

-0.088

0.035

0.016*

Land

-0.047

0.036

0.194

Combination

-0.116

0.035

0.002*

Water

Land

0.041

0.036

0.256

Combination

-0.028

0.035

0.435

Land

Combination

-0.069

0.035

0.057

Third lumbar vertebrae (L3)

Control

Water

-0.071

0.027

0.013*

Land

-0.032

0.027

0.253

Combination

-0.102

0.027

0.001

Water

Land

0.039

0.027

0.169

Combination

-0.031

0.027

0.267

Land

Combination

-0.070

0.027

0.014*

Fourth lumbar vertebrae (L4)

Control

Water

-0.085

0.029

0.006*

Land

-0.079

0.030

0.012*

Combination

-0.112

0.029

0.001*

Water

Land

0.006

0.030

0.840

Combination

-0.027

0.029

0.372

Land

Combination

-0.033

0.029

0.269

AWT IMAGE

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

Ghasemi S, et al. The Effect of 12 Weeks of Training in Water, on Land and Combined Environment on Bone Mineral Density in Premenopausal Women. Physical Treatments. 2016; 6(1):19-28.

D

1. Introduction

isability is a natural and social phenomenon that can affect different communities in different ways. Some of its common manifestations include lack of independence in life and physical inactivity, resulting in the development of physical and motor weaknesses, such as poor balance and difficulty in walking independently [1]. Hence, mental retardation shows the significant limitation in an individual’s adaptive performance, which includes a below average performance (IQ of 70 or below) accompanied with limited skills in the field of environmental compatibility [1]. According to the available statistics, about 3% of the world’s population has an IQ of less than 68, among which over 80% are educable [2].

Mobility is one of the main aspects of life, and walking as a basic human skill and the original way of a child’s movement and relocation, has appropriated the daily motor activity of humans [3, 4]. Due to the special mental conditions and the resulting social problems, the mentally retarded people are more immobile with less physical activities compared to the healthy people, which results in physical and motor weaknesses [1, 2]. Physical inactivity leads to reduced voluntary power and capacity of muscle function, impaired simultaneous activation of agonist and antagonist muscles, and ultimately lowered performance and efficiency of the neuromuscular system [3, 4]. Specifically, children with mental problems and abnormalities act slower than their normal peers in initiation and implementation of targeted exercises and movement’s reaction time [3, 4].

Previous studies have shown that the mentally retarded children usually have poor body conditions with low physical vitality [5]. Enkelaar et al. (2012) stated that the mentally retarded people are involved in unbalanced and unstable ways of walking, indicating their overall weak coordination [5]. In a review of literature related to gait analysis in people with mental retardation highlighted the existence of biomechanical weaknesses that can be associated with high risk of falling. For example, in a biomechanical analysis of mentally retarded adults’ gaits conducted by Haynes et al. it was shown that these people have less stride lengths than the normal individuals. In addition, they have further stride widths for balancing for slower walking speed, while their probabilities of sliding from side to side are more than the normal people [6, 7].

The high prevalence of mental retardation, the role of walking as a factor of communication with the environment, and enhancement of muscle performance, despite some kinetic and kinematic studies on their gaits, less attention has been paid to the assessment of lower extremity muscle activity. A study on the muscular behavior of mentally retarded individuals during walking leads to better understanding of the kinetics and helps in determining specific exercise programs that can improve their walking abilities and independence level. Therefore, the aim of this study was to assess the surface electromyography (sEMG) characteristics of some selected lower extremity muscles during walking in mentally retarded adolescents compared to the healthy subjects.

2. Materials and Methods

Fifteen students with mental retardation and 15 normal subjects, aged from 10 to 14 years participated in this causal-comparative study. The mentally retarded subjects were randomly selected from primary and secondary exceptional schools of Hamedan city in 2014. The sample size was determined based on the previous similar studies. The inclusion criteria included an IQ of 50 to 70, not having 2 disabilities along with Down syndrome, no history of surgical operation and injuries or burning in the lower extremity, no mutilation, and absence of any cardiovascular problems. After obtaining the permission of their parents and medical records at the school, the students in the afflicted group were selected from special schools of Hamadan City. The research council of Bu Ali Sina University, in agreement with the Declaration of Helsinki, approved all the procedures before the beginning of the study.

After the anthropometric measurements, certain selected areas of the skin, such as vastus medialis (VM], vastus lateralis (VL), biceps femoris (BF), semi-tendinosus (ST), tibialis anterior (TA), long peroneal (LP), medial gastrocnemius (MG), and soleus muscles, were connected to the electrodes according to SENIAM (European Recommendations for Surface Electromyography) instructions [8]. The collected data were normalized to their Maximum Voluntary Isometric Contractions (MVICs) that were obtained from the muscles.

For the BF and ST MVIC, the subjects were seated on the examination table, and their knee and hip were flexed at 90°. The subject was instructed to maximally flex the knee against the manual resistance of the investigator. For the VM, VL and RF MVIC, the maximum isometric knee extension was performed with the hip at 90º and the knee at 60º of flexion. MVIC of PL was performed against the manual resistance of the investigator while the subject was in a sitting position attempting ankle eversion and plantar flexion. For TA MVIC, the subjects exerted a maximal voluntary isometric contraction during ankle dorsiflexion. Soleus MVIC was collected with the subject in a quadruped position with knee and hips flexed to 90 degrees on the table and strapped around the metatarsal heads. MG MVIC was collected with the subject lying prone with the test limb off the end of the table and the strap across the metatarsal heads.

To determine the key points of the walking phases, two-foot switches were attached under the most posterior part of the lateral heel and the great toe. Electromyography data were recorded by a 16 channel EMG system (Biomonitor ME6000 T16, Mega Electronics Ltd., Kuopio, Finland).

After attachment of the electrodes and foot switches, the familiarity, and compatibility of the instruments were checked based on the lab conditions. The subjects walked along a 17 m walkway for six times at self-selected speed, and their muscle activities were recorded at the same time. The sampling rate of EMG muscle activity was set at 2000 Hz with the common signal rejection ratio of 110 dB in the differential amplifier. The data were analyzed based on the signal quality of foot switch from the 3rd stride in each trial.

For EMG data analysis, Megawin software, version 3.1 was used. To refine the data obtained from EMG, a band-pass filter of 10 to 450 Hz was employed. To normalize the data, the maximum value of Root Mean Square (RMS) amplitude for each muscle during each stride was considered, and the average RMS muscle activity was expressed in terms of percentage with relation to the maximum activity during MVIC [9]. Ultimately, the different gait phases were analyzed based on the heel contact, mid-stance, propulsion sub-phases, and total stance phase.

To obtain the co-contraction index, the following equa-tion was used [17]:

Co-contraction=

Antagonist & antantagonist muscle activities

AWT IMAGE

Antagonist muscle activity × 2

×100

The co-contraction of agonist and antagonist muscles around the joint is of high biomechanical importance to maintain joint position and stability. Co-contraction values were calculated and analyzed for the muscles around the knee and calf in the anterior-posterior or medial-lateral directions during heel contact, mid-stance, propulsion, and total stance.

The normal distribution of the data was evaluated using Shapiro-Wilk test. The assumption of homogeneity of variance was tested using Levene’s Test of Equality of Variances (P>0.05). To compare the study parameters, an independent t-test was used at a significance level of α=0.05. All the statistical analyses were performed using SPSS software, version 18.

3. Results

The demographic information of the present participants of each group is shown in Table 1. The subjects of both the groups had no differences based on demographic size. Table 2 presents the muscle activities of both mentally retarded and healthy groups during the heel contact, mid-stance and propulsion sub-phase, and total stance phase.

As it can be seen, the biceps femoris activity of the mentally retarded subjects was significantly higher than the healthy group during the heel contact sub-phase (P=0.003). During mid-stance sub-phase, the vastus medialis (P=0.015) and long peroneal (P=0.026) muscles had higher activities in people with mental retardation in comparison with the healthy group. A comparison of the activities of the lower extremity muscles in the propulsion sub-phase showed higher activities of vastus lateralis (P=0.035) and soleus (P=0.002) muscles, and lower activity of the vastus medialis (P=0.045) muscle in mental retardation group.

There were differences in muscle activities of the two groups during the whole stance phase of gait. According to the results, vastus lateralis (P=0.018), biceps femoris (P=0.001), and long peroneal (P=0.011) muscles demonstrated higher activities in the subjects with mental retardation.

Comparison of co-contraction activity between muscles around the knee and ankle joints during heel contact, mid-stance and propulsion sub-phases, and total stance phase of gait in both the study groups are presented in Table 3. The co-contraction rate of medial gastrocnemius and anterior tibialis muscles in individuals with mental retardation during heel contact sub-phase was higher (P=0.040) compared to the healthy group. However, no significant differences were found between the two groups during any other sub-phases. Co-contraction rates of hamstring and quadriceps muscles of knee joint showed no significant differences. Similarly, there was no significant difference found between long peroneal and anterior tibialis muscles of the ankle joint during sub-phases of the stance phase of walking.

4. Discussion

The purpose of this study was to compare the activity of the lower extremity muscles of mentally retarded adolescents and their healthy peers while walking. The results demonstrated that during the heel contact sub-phase, the biceps femoris muscle had greater activity in individuals with mental retardation. In the mid-stance sub-phase, the vastus medialis and long peroneal muscles showed higher activities in mentally retarded subjects. In the propulsion sub-phase, vastus lateralis and soleus muscles of those with mental retardation were more active, while their vastus medialis muscles showed less activity. Also, in the stance phase, their vastus lateralis, biceps femoris, and soleus muscles showed higher activities. In addition, medial gastrocnemius and tibialis anterior co-contraction rates were higher in the mentally retarded group during heel contact sub-phase as compared to the healthy individuals.

During the heel contact sub-phase, the mentally retarded persons’ biceps femoris muscles displayed more activities. A study by Haines et al. (2012) showed that the mentally retarded individuals were involved in greater joint flexion during heel contact when walking [6, 7, 11], which was in line with the results of the present study. Therefore, the additional flexion during heel contact is caused by the greater activity of biceps femoris muscle in people with mental retardation. In the mid-stance sub-phase, the vastus medialis and long peroneal muscle activities were found to be higher in mentally retarded participants. Previous studies have shown that mentally retarded individuals with Down syndrome have more flexion in their knees in the mid-stance sub-phase [11-14].

Winter (1983), reported that more knee flexion indicates walking inefficiency, causing an increase in bone-on-bone forces [15]. To avoid and overcome such inefficiency, more knee extensor muscles strengthening activities needs to be performed [15]. Thus, the vastus medialis muscles of people with mental retardation perform more activities to overcome extra knee flexion and reduce walking inefficiencies. In a study by Fournier et al. (2010) showed that the pressure on the interior part of the foot is greater in mentally retarded people during walking [16]. Murley et al. (2009) reported that further activity of long peroneal muscle increases the load on the medial zone of the foot [17]. Therefore, in case of higher pressure on the internal part of the leg in people with mental retardation, it can be concluded that the enhanced long peroneal muscle activity leads to an increased pressure on the leg interior part, and lead to plantar injuries and bone problems, especially those of the plantar-toe joint over time [16].

The study results revealed that soleus muscle activity in people with mental retardation is greater in the propulsion phase. In a study by Cioni et al. (2001) showed that the flexor plantar torque is lower in such people in the propulsion sub-phase compared to the healthy ones [7]. Therefore, further soleus muscle activities need to be done to compensate for the weak plantar flexion within the mentioned sub-phase.

A review study by Enkelaar et al. (2012) concluded that people with mental retardation have more flexion in their lower extremity joints during the stance phase of gait, and this could be a risk factor for frequent falls [5, 6]. During the current investigation, vastus lateralis, biceps femoris, and long peroneal muscles of the mentioned subjects displayed higher activities during the entire stance phase. It seems that the difference in muscle activity between the two groups, which was observed in this study, can be the cause of kinetic and kinematic changes reported in the previous research [5, 6].

In terms of biomechanics, the co-contraction of agonist and antagonist muscles around the joint is of great importance to maintain the joint stability [18]. The concurrent muscle activity around the joint is called co-contraction that is of the two general and directed types, the latter of which provides joint stability [18]. In the joints where there is an articular laxity and instability, the agonist and antagonist muscles coordinate to produce joint stiffness through co-contraction [19]. In this study, a greater co-contraction was observed in the knee joints of mentally retarded subjects during the swing phase. Further co-contraction could be associated with more lower-limb rigidity [9].

Gontijo et al. (2008) stated that people with mental retardation have a ligamentous laxity and stiffness in their lower extremity joints during the swing and heel contact phases of gait [8]. More laxity in the knee joint during swing phase leads to a skid, imbalance, and risk of falling while walking [10]. It seems that the nervous systems of mentally retarded persons use a more co-contraction rate strategy to compensate for and overcome the further knee joint laxity during the swing phase [9].

Additionally, within the heel contact sub-phase, the co-contraction rate of ankle joint was found to be higher for people with mental retardation compared to the healthy subjects, which could also be due to the ligamentous laxity and lower joint stiffness [9]. The World Health Organization has mentioned brain inefficiency, balance (vestibular, visual, and sensory) systems, and living conditions as the three main mechanisms that reduce the mobility of people with mental retardation. Moreover, their lower IQs cause different patterns of muscle recruitment during the performance of daily activities [2, 9].

Our results provide objective evidence of differences in muscle activation patterns during gait between the mentally retarded individuals and healthy people. These results would be helpful to the therapists and persons involved in the care of these children with special needs. As a result, special attention should be given to their lower extremity muscles during their corrective power exercises.

An important limitation of this study was the lack of kinematic and kinetic variables related to the gait analysis. For instance, gait analysis necessitates identification of heel-strike and toe-off to define the enhanced key components of the gait cycle. This is most accurately quantified using force platforms where a threshold is defined to determine heel-strike and toe-off. Future investigations using more sophisticated techniques, such as the use of force platform, may be of benefit to further understand the strategies used by the mentally retarded adolescents for walking.

Acknowledgements

This study was extracted from the second author's MA thesis of Physical Education at Bu-Ali Sina University. Authors would like to thank the children and their parents for their consent to participate in this study.

Conflict of Interest

The authors declared no conflict of interests.

References

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  2. Salari M, Kashaninia Z, Davachi A, Zoladl M, Babaie G. [Effect of education on coping strategies of mothers who have educable mentally retarded children (Persian)]. Armaghan Danesh. 2001; 6(23):1-9.
  3. Craik RL, Oatis CA. Gait analysis: Theory and application. 1st ed. Missouri: Mosby; 1995.
  4. Edwards W, Luckasson RA. Mental retardation: Definition, classification, and systems of supports. 10th ed. New York: American Association of Mental Retardation; 2002.
  5. Enkelaar L, Smulders E, van Schrojenstein Lantman-de Valk H, Geurts AC, Weerdesteyn V. A review of balance and gait capacities in relation to falls in persons with intellectual disability. Research in Developmental Disabilities. 2012; 33(1):291-306. doi: 10.1016/j.ridd.2011.08.028
  6. Haynes CA, Lockhart TE. Evaluation of gait and slip parameters for adults with intellectual disability. Journal of biomechanics. 2012; 45(14):2337-341. doi: 10.1016/j.jbiomech.2012.07.003
  7. Cioni M, Cocilovo A, Rossi F, Paci D, Valle MS. Analysis of ankle kinetics during walking in individuals with Down syndrome. American Journal on Mental Retardation. 2001; 106(5):470-8. doi: 10.1352/0895-8017(2001)106<0470:aoakdw>2.0.co;2
  8. Hermens HJ, Freriks B, Merletti R, Stegeman D, Blok J, Rau G, et al. European recommendations for surface electromyography. Enschede: Roessingh Researchand Development; 1999.
  9. Gontijo AP, Mancini MC, Silva PL, Chagas PS, Sampaio RF, Luz RE, et al. Changes in lower limb co-contraction and stiffness by toddlers with Down syndrome and toddlers with typical development during the acquisition of independent gait. Human Movement Science. 2008; 27(4):610-21. doi: 10.1016/j.humov.2008.01.003
  10. Winter DA. Biomechanics and motor control of human movement. 4th ed. Philadelphia: John Wiley & Sons; 2009.
  11. Sparrow WA, Shinkfield AJ, Summers JJ. Gait characteristics in individuals with mental retardation: unobstructed level-walking, negotiating obstacles, and stair climbing. Human Movement Science. 1998; 17(2):167-87. doi: 10.1016/s0167-9457(97)00028-6
  12. Smith BA, Ulrich BD. Early onset of stabilizing strategies for gait and obstacles: older adults with Down syndrome. Gait & Posture. 2008; 28(3):448-55. doi: 10.1016/j.gaitpost.2008.02.002
  13. Finlayson J, Jackson A, Cooper SA, Morrison J, Melville C, Smiley E, et al. Understanding predictors of low physical activity in adults with intellectual disabilities. Journal of Applied Research in Intellectual Disabilities. 2009; 22(3):236-47. doi: 10.1111/j.1468-3148.2008.00433.x
  14. Galli M, Rigoldi C, Mainardi L, Tenore N, Onorati P, Albertini G. Postural control in patients with Down syndrome. Disability Rehabilitation. 2008; 30(17):1274-278. doi: 10.1080/09638280701610353
  15. Winter DA. Knee flexion during stance as a determinant of inefficient walking. Physical Therapy. 1983; 63(3):331-33. PMID: 6828560
  16. Fournier KA, Kimberg CI, Radonovich KJ, Tillman MD, Chow JW, Lewis MH, et al. Decreased static and dynamic postural control in children with autism spectrum disorders. Gait & Posture. 2010; 32(1):6-9. doi: 10.1016/j.gaitpost.2010.02.007
  17. Murely GS, Menz HB, Londorf KB. Foot posture influences the electromyographic activity of selected lower limb muscles during gait. Journal of Foot & Ankle Research. 2009; 2:35. doi: 10.1186/1757-1146-2-35
  18. Lloyd DG, Buchanan TS. Strategies of muscular support of varus and valgus isometric loads at the human knee. Journal of Biomechanics. 2001; 34(10):1257-267. doi: 10.1016/s0021-9290(01)00095-1
  19. Esmaeili H, Anbarian M, Hajiloo B, Sanjari MA. [The immediate effect of foot insole on electromyography activity and co-contraction of leg muscles in individuals with flat feet (Persian)]. Journal of Research in Rehabilitation Sciences. 2013; 9(2):295-307.

sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents

Mehrdad Anbarian1*, Younes Bagheri Fard1, Hamed Esmaili1

1. Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Bu-Ali Sina University, Hamadan, Iran.

Keywords:

Mentally retarded, Walking, Electromyography, Lower extremity, Co-contraction

* Corresponding Author:

Mehrdad Anbarian, PhD

Address: Department of Sports Biomechanics, Faculty of Physical Education and Sport Sciences, Bu-Ali Sina University, Hamadan, Iran.

Phone: +98 (918) 8152907

E-mail: m_anbarian@yahoo.com

12 Oct. 2015

01 Mar. 2016

Citation: Anbarian M, Bagheri Fard Y, Esmaili H. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

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: :

A B S T R A C T

Purpose: Less attention has been paid to the electromyographic activity of the lower extremity muscles, which is considered as an essential part of the kinetic studies on the gait of mentally retarded individuals. Hence, the study aims at determining the surface electromyography characteristics of the lower extremity muscles of mentally retarded adolescents during walking.

Methods: It is a causal-comparative study. Fifteen mentally retarded and 15 normal adolescents with an age range of 10 to 14 years participated in this study. To record the activities of vastus medialis, vastus lateralis, biceps femoris, semi-tendinosus, tibialis anterior, long peroneal, medial gastrocnemius, and soleus muscles, sEMG was employed during the stance phase of gait. For the data analysis, an independent sample t-test was conducted using SPSS version 18.

Results: The results revealed that the mentally retarded adolescents had higher level of biceps femoris muscle activity in the heel contact sub-phase (P=0.016) compared to the normal group. Also, the vastus medialis (P=0.015) and the long peroneal (P=0.026) muscles showed higher EMG activity. Furthermore, their vastus lateralis (P=0.039) and Soleus (P=0.002), and vastus medialis (P=0.045) muscles demonstrated higher and lower activities, respectively. The co-contraction rate of medial gastrocnemius and anterior tibialis muscles during the heel contact was higher (P=0.040) in individuals with mental retardation compared to the healthy group. Conclusion: It can be concluded that the mentally retarded individuals use different muscle activation patterns in comparison to healthy people. As a result, special attention should be given to the functioning of their lower extremity muscles during the corrective power exercises.

CrossMark

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Anbarian M, et al. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

Table 1. Descriptive statistics of demographic variables.

P

Group

Variables

Healthy Subjects

Patients

0.672

11.96±1.6

11.89±1.2

Age (years)

0.385

150.37±5.43

147.31±4.62

Height (cm)

0.324

38.33±4.27

36.78±3.51

Weight (kg)

0.574

16.72

16.02

BMI

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Anbarian M, et al. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

Table 2. Comparison of the EMG activity of muscles (MVIC%) during the stance phase of gait in the study groups (Mean±SD).

P

t

Groups

Muscles

Phases

Patients

Healthy

0.113

-1.635

20.855±6.0

16.860±7.3

Vastus lateralis

0.514

0.662

18.479±4.8

20.272±9.3

Vastus medialis

0.003

-2.555

20.745±7.3

14.118±6.9

Biceps femoris

0.184

-1.362

15.149±10.5

10.349±8.7

Semi-tendinosus

Heel contact

0.101

1.697

13.400±6.7

17.956±7.9

Tibialis anterior

0.061

-1.951

19.847±6.0

14.850±7.9

Long peroneal

0.628

-0.490

13.640±8.1

12.355±6.2

Medial gastrocnemius

0.703

-0.385

18.444±7.1

17.331±8.7

Soleus

0.123

-1.590

14.973±6.4

10.836±7.8

Vastus lateralis

0.015

-2.596

21.152±6.2

14.751±7.2

Vastus medialis

0.135

-1.539

16.557±9.0

11.145±10.2

Biceps femoris

0.550

-0.605

9.604±5.7

8.381±5.4

Semi-tendinosus

Mid-stance

0.996

0.005

7.742±3.8

7.752±6.1

Tibialis anterior

0.026*

-2.345

25.618±9.0

18.553±7.5

Long peroneal

0.842

-0.201

18.236±5.0

17.868±5.0

Medial gastrocnemius

0.209

-1.285

31.310±11.7

26.825±6.8

Soleus

0.035*

-2.220

11.311±7.5

6.633±3.5

Vastus lateralis

0.045*

2.097

9.545±3.9

13.311±5.8

Vastus medialis

0.325

-1.003

7.636±5.2

5.878±4.3

Biceps femoris

0.573

-0.571

5.268±3.2

4.633±2.9

Semi-tendinosus

Propulsion

0.287

-1.106

12.709±5.1

10.776±4.5

Tibialis anterior

0.084

-1.926

20.119±4.9

16.324±5.8

Long peroneal

0.451

-0.764

12.247±7.6

10.601±3.5

Medial gastrocnemius

0.002*

-3.415

19.539±5.1

13.354±4.8

Soleus

0.018*

-2.507

16.360±4.4.

11.656±5.8

Vastus lateralis

0.982

0.023

15.915±4.4

15.958±5.7

Vastus medialis

0.001*

-3.682

18.393±7.5

9.312±5.9

Biceps femoris

0.148

-1.486

11.367±5.9

8.466±4.8

Semi-tendinosus

Total stance

0.378

-0.895

10.701±3.9

9.490±3.5

Tibialis anterior

0.011*

-2.742

21.122±6.9

15.155±4.9

Long peroneal

0.560

-0.590

16.141±5.7

15.010±4.7

Medial gastrocnemius

0.105

-1.675

25.286±8.8

21.008±4.6

Soleus

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Abbreviations: NS stands for No Significant; MVIC stands for Maximum Voluntary Isometric Contractions.

*P<0.05.

Anbarian M, et al. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

Table 3. Comparison of co-contraction activity between the knee and ankle muscles (MVIC%) during the stance phase of gait in the study groups (Mean±SD).

P

t

Groups

Phases

Muscles

Patients

Healthy

0.040

-2.150

82.693±21.2

66.923±18.9

Heel contact

0.832

-0.214

59.332±24.7

57.401±24.6

Mid-stance

0.650

-0.458

106.286±44.2

100.246±25.4

Propulsion

TA and MG

0.684

-0.411

81.628±27.7

77.857±22.2

Total stance

0.107

-1.667

78.935±14.1

68.535±19.6

Heel contact

0.194

-1.331

69.670±14

61.082±20.7

Mid-stance

0.296

-1.065

78.525±18.8

68.010±33.3

Propulsion

Q and H

0.058

-1.980

93.577±16.7

76.494±28.9

Total stance

0.285

1.089

79.155±24.1

86.625±11.2

Heel contact

0.275

1.113

48.191±23.4

59.096±29.9

Mid-stance

0.550

0.605

75.708±22.2

80.981±25.4

Propulsion

TA and LP

0.338

0.975

68.812±23.2

78.031±28.4

Total stance

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Abbreviations: TA stands for Tibialis Anterior; MG stands for Medial Gastrocnemius; LP stands for Long Peroneal; Q stands for Quadriceps; H stands for Hamestring muscles; NS stands for No Significance.

Anbarian M, et al. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

Anbarian M, et al. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

Anbarian M, et al. sEMG Characteristics of the Lower Extremity Muscles During Walking in Mentally Retarded Adolescents. Physical Treatments. 2016; 6(1):29-36.

The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography

Majid Fatahi1*, Gholam Ali Ghasemi2, Yosef Mongashti Joni3, Vahid Zolaktaf2, Faraj Fatahi1

1. Department of Sport Injuries and Corrective Exercises, Faculty of Physical Education & Sport Sciences, University of Isfahan, Isfahan, Iran.

2. Department of Pathology and Corrective Exercises, Faculty of Physical Education & Sport Sciences, University of Isfahan, Isfahan, Iran.

3. Department of Management and Sport Sciences, Faculty of Physical Education & Sport Sciences, Urmia University, Urmia, Iran.

Keywords:

Electromyography, Postural control, Fatigue, Y balance, Lower extremity muscles

*Corresponding Author:

Majid Fatahi, MSc.

Address: Department of Sport Injuries and Corrective Exercises, Faculty of Physical Education & Sport Sciences, University of Isfahan, Isfahan, Iran.

Phone: +98 (916) 3056603

E-mail: fatahi879913@yahii.com

29 Sep. 2015

10 Jan. 2016

Citation: Fatahi M, Ghasemi GHA, Mongashti Joni Y, Zolaktaf V, Fatahi F. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

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: :

A B S T R A C T

Purpose: Postural control preserves organs and body parts in a proper biomechanical stance which exists in two forms: static and dynamic. Fatigue is one of the factors that affects postural control. This study aimed to compare the electromyography (EMG) activity of the lower extremity muscles before and after fatigue.

Methods: This study was descriptive correlational and based on the research type a field study. Study sample comprised 20 male students majored in physical education; they were purposefully selected by non-accidental all-accounted method. Surface EMG activities of lower extremity muscles before and after fatigue were evaluated by electromyogram. To create fatigue in lower extremity muscles, we used fatigue protocol by the Biodex system. Data analysis was carried out by using SPSS 21. The paired t test was used for statistical analysis with a significance level of P<0.05.

Results: The paired t test results indicated that the activity level of the rectus femoris, hamstrings, tibialis anterior, and gastrocnemius muscles significantly changed before and after fatigue. The study results also supported that lower extremity muscle fatigue had a negative effect on the activity of the muscles around the knee joint. Furthermore, there was a significant relationship between the postural control and the activity level of rectus femoris and tibialis anterior muscles on pretest. However, there were no significant relationships between postural control and activity level of lateral hamstrings and gastrocnemius muscles on pretest and posttest, nor the activity level of rectus femoris and tibialis anterior posttest.

Conclusion: Muscle fatigue increases joints vulnerability. These results can be used in designing athlete’s rehabilitation programs and trainings to prevent injuries or changes in biomechanical parameters of walking.

CrossMark

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1. Introduction

ostural control is the key factor and essential for daily activities and exercises. It maintains the organs and different body parts in an appropriate biomechanical stance which exists in the two forms of static and dynamic [27]. Postural control is the quantitative measurement of neuromuscular control that plays an important role in the dynamic joint stability and keeping the body away from the injuries [38]. Postural control is achieved through biomechanical and sensorimotor processes. It results from contribution of three systems; visual, vestibular, and somatosensory. The cooperation of these systems leads to postural control and balance [32].

The research indicates that the muscles of the lower extremity have a very important role in maintaining postural control, especially in single-leg movements. Inefficiency or weakness of these muscles during dynamic movements may disturbs the dynamic postural control, affects the stability of the posture, and leads to imperfect movements. Performing daily activities and exercises considerably depends on keeping balance which is defined as the ability to maintain or return the body center of mass within the support base or control and keep the body position in space to achieve stability and orientation. Balance is the most important factor in doing exercise [15]. It is a complicated skill which describes the dynamic posture of the body in preventing from falling [13]. Various factors affect the person’s ability in keeping and recovering the postural control of the body; the most important of them are nervous system injuries, inefficiency of the optic nerves, stress, vestibular system defects, and fatigue. To study the effects of these factors on the body control system, special laboratory, equipment, and field tools are used [17].

Muscular fatigue decreases the performance of the metabolic and neuromuscular systems which results in persistent muscle contraction and reduction in its steady activity. Thus, muscle contraction cannot continue for a long time [3]. This is an unpleasant phenomenon which may happen after a short- or long-term activity (maximal or submaximal) [4]. Research indicates that muscle fatigue increases postural sway and reduces the ability to keep the balance [16]. Fatigue is a transient disability in keeping the muscle strength to perform consecutive contractions [25].

With respect to the nervous system, fatigue is categorized into central and peripheral types. Lack of activation and sending impulses from central nervous system to the muscles and their inability for producing proper tension and response are defined, respectively, as the main causes of the central and peripheral fatigue [1]. Because most exercises are done in a dynamic condition, dynamic balance is one of the most important factors of fitness and doing sport activities [10].

Gribble and Hertel (2004) demonstrated that thigh muscle fatigue can impair postural control in sagittal and frontal planes and affect body functions [14]. Di Giulio et al. (2009) reported a high correlation between EMG activity of the tibialis anterior muscle and body sway (as a function) in the standing position. These results indicated a relationship between the EMG activity of the lower extremity muscles and displacement of the body center of the gravity. They have also reported a moderate relationship between the EMG activities of the gastrocnemius and soleus muscles with body sway in standing position [9].

Most sport injuries occur near the end of the sport activities and competitions. Thus, the negative and accumulative effects of fatigue, especially near the end of the competitions, on the neuromuscular control can lead to dangerous movement strategies and an increase in the risk of injury. The results indicated that fatigue not only decreases the muscle capacity in producing energy but also deeply affects the coordination of movements, motor control acuity, muscle reaction time, and proprioception ability, which causes a significant reduction in muscle performance [24]. This negative effect is important with regard to injury prevention because muscles, besides contraction, have other duties, such as reduction of impact forces, bending forces on bones, and increasing joint stability. If muscles perform their functions well, they can support body against injuries. Any changes in muscle function due to fatigue reduces muscle ability to prevent sport injuries [36].

Today, the electromyography (EMG) is widely used in all areas of medicine, rehabilitation, and sport. EMG is an experimental technique in which the electrical signals of the muscle are detected, recorded, and analyzed. It has several advantages which “monitoring the electrical activity of the muscle directly and without intermediaries” might be its most important advantage [22]. This study aimed to examine the relationship between lower extremity muscle activity with using tests of lower limb performance and postural control and also the effect of fatigue by using EMG. In this study, the Y Balance Test was used to assess the dynamic postural control. This test is a valid and reliable instrument to quantify the dynamic postural control [25].

2. Materials and Methods

This research is a descriptive correlational and field study. The research design is intragroup with pretest and posttest of the study variables; EMG activity of the lower limb muscles and postural control before fatigue and after administering fatigue protocol.

Study participants

The present study was conducted on the male students of the Faculty of Physical Education and Sport Sciences University of Isfahan who enrolled in the academic year 2013-2014. The study subjects were 20 male students (mean (SD) age: 24.9(2.44) y, mean (SD) weight: 69.16(7.51) kg, mean (SD) height: 175.05(4.54) cm) who were chosen purposefully. Subjects with a history of neuromuscular disorders, fracture or surgery of the lower limbs during the past six months, ankle sprains in the past year, lower limb abnormalities such as valgus deformity, flat foot and arch foot, and vestibular impairment were excluded from the study. All tests were performed in the laboratory of Isfahan University, Faculty of Physical Education. Before the study, the experimental protocol was explained to all participants who all signed informed consent forms.

Study procedure

The Y Balance Test was used to measure the dynamic balance of the participants. This is a test based on the star excursion balance test (SEBT) which Grybl et al. (2012) considered it as a valid test for the evaluation of dynamic balance [5]. SEBT is a reliable and validated test to predict lower extremity injuries, determine the dynamic balance impairments in people with lower extremity injuries, ascertain the effects of fatigue on the balance, and also the effects of exercise to improve balance.

Taking this test needs power, flexibility, neuromuscular control, core stability, proprioception, and balance; therefore, it is an excellent-test for evaluating pre-season and medical assessments [5]. Plisky et al. (2009) designed the Y Balance Test to evaluate dynamic balance and to standardize SEBT assessment [35]. In this test, three directions (anterior, posteromedial, and posterolateral) are drawn at an angle of 135° to each other. Because of significant correlation of this test with leg length, to perform this test and normalize the data, the leg length was measured from the anterior superior iliac spine to the medial malleolus in the supine position while the subject lying on the ground [6].

To run the test, each subject with one leg (the dominant one) practiced the test 4 times to learn test procedure (the subject with right dominant leg performed the test in the counterclockwise direction, and the subject with the left dominant leg did it in the clockwise direction). The subject stood at the center of the test on one leg and with the other leg, in the direction which the examiner chose, performed the error-free maximum-reach performance and then returned to the normal position. To eliminate the effect of learning, each subject practiced each direction, 4 times with 15-second intervals rest. After a 5-minute break, the subject started the test in the direction that the examiner had chosen randomly (Figure 1).

The examiner measured the subject’s leg location to the center of the test in centimeter. The test was repeated 3 times for the subjects. The best record was divided by the leg length, and then multiplied by 100 until the reach distance in terms of leg length was obtained. If an error occurred during the test such as subject’s stance leg moved out the center or his balance was disrupted, the subject would be asked to repeat the test [35].

Data collection

The measurement procedure can be divided into 5 steps:

  • Filling out the questionnaire and warming up;
  • Preparing subjects and electrode placement;
  • Measuring lower extremity EMG activity by using tests of lower extremity function under normal conditions (without exhaustion);
  • Administering lower extremity muscle fatigue protocol by using Biodex system; and
  • Measuring lower extremity EMG activity by using lower extremity function test after the fatigue protocol.

Filling out the questionnaire and warming up

At the beginning of each session, the researcher explained to each subject the purpose of the research, its measuring instruments, and the process. After providing this information and subject’s willingness to participate in this study, a questionnaire was handed to the subject to provide the required information. After filling out the questionnaire, he was asked to participate in the test with sport clothes. Participants’ leg length and height were measured and recorded by the tape and a digital scale, respectively. The dominant leg of the subject was determined by the examiner. Next, the researcher taught the participants how to do the lower extremity function in the test.

Preparing samples and electrode placement

Since much information about the range of EMG variables in this study was related to lower limb muscles, subjects’ preparation and installation of surface electrodes were conducted in the following way. First, according to the instructions provided by the examiner, each subjects shaved all the skin appendages, coarse and fine hairs over electrode placement areas on the quadriceps, hamstring, tibialis anterior, and gastrocnemius muscles by using a disposable personal razor blades.

To reduce ohmic resistance of the skin surface, a special, gentle, and soft sandpaper was used to scrub the skin. Then, by using 5% isopropyl alcohol, the scrub residuals and skin sweating were wiped out to provide a proper condition to place the electrode pads on the skin surface. Next, the electrode pad placement on the muscles was determined according to SENIAM European Protocol [39].

After specifying the desired muscles, the places of the electrode positions were determined as follows [18]:

  • Rectus femoris muscle: In the middle of the line between the anterior superior iliac spine and upper part of patella;
  • Lateral hamstring muscle: In the middle of the line between the ischial tuberosity and the lateral epicondyle of tibia;
  • Tibialis anterior muscle: Upper third on the line between tip of fibula and ankle; and
  • Medial gastrocnemius muscle: The most protruding part.

In addition, to ensure the location of the muscle, the isometric muscle contraction proposed by the Kendall was used to determine the bulk muscle in all cases [44]. After determination of the electrode pad placements, they were put and attached on the specified places. Lower extremity EMG activities were measured by using tests of lower extremity function under normal conditions (without exhaustion).

Performing the experiment to record the EMG activity

To record the EMG activity of the lower extremity, the function tests included the Y Balance Test. At first, the test method was explained to each subject and asked him to perform the test with his maximum power and speed, upon hearing the command of “ready, go” (which was simultaneous with the start of electromyogram). During the test, the subject stood on one leg at the center of the test and moved the other leg in the direction chosen by the experimenter to achieve maximum error-free reach and then returned to normal condition. If an error occurred during the test such as subject’s stance leg moved out the center or his balance was disrupted, he would be asked to repeat the test [37]. For Y Balance Test, the distance was calculated by a tape meter; the examiner permitted the start move by holding the EMG instrument.

After finishing the test, the memory card from the surface electromyogram was transferred to the computer and the recorded EMG waves were analyzed. The electrodes were not detached from the subject’s body to repeat the test in case of any mistake found in recording the waves. After being ensured of the correctness of the EMG waves recording, the electrodes were separated from the subject’s body and their places were cleaned with water and alcohol.

Lower extremity muscle fatigue protocol

Among the various methods of evaluating and creating fatigue, voluntary contraction, has been always the first choice and criterion to quantify the fatigue. Furthermore, using the maximum voluntary contraction has been considered as a gold standard [42]. In the current study, administering fatigue protocol to reach 50% of maximum torque repeated contractions, provides the study feedback, and moreover, it is a reproducible and standardized measure. However, the administration of the motioned fatigue protocol in some similar and previous studies has caused significant changes in balance control indices [18, 38].

To administer fatigue in the targeted muscle groups, the Biodex system was used. For this purpose, first the maximum torque of knee flexor and extensor muscles was recorded. To administer fatigue in knee area, the angle of the trunk and knees flexion were set at 110° and 90°, respectively (at the start). To avoid involving other muscles in the test, subject’s trunk, hip, and knees were fixed to the Biodex system by seat belt.

At the beginning of the program, to warm up muscles and familiarize subjects with the movements in the system, some submaximal movements were performed. Then to record the maximum torque of each subject, three knee flexion and extension moves (to record for maximum muscle torque knee) were carried out with maximum effort and the average of three movements was recorded as the maximum torque. During the study on knee muscles area, the selected contraction was isokinetic with concentric/concentric type. Also, the contraction speed for extension and flexion movements of knee was 360° per second. It was assumed that when subject’s torque after three consecutive moves reduced to less than 50% of maximum torque (recorded during the first movement), then he would experience fatigue [18]. Lower extremity EMG activities were measured using lower extremity function test after administering the fatigue protocol (Figure 2).

Final processing of EMG data

Because 4 electrodes were connected to target muscles of each subject, we received 4 raw EMG wave for each subject. To analyze raw EMG waves, RMS computing method was used. Di Fabio algorithm was used to show the muscle activity during functional tests as well as starting and finishing moves of RMS EMG data [8]. On the rest part of the algorithm, a t1 point was randomly selected to mark the onset of contraction. Time t2 was set 3 to 5 ms after the time t1. Then, mean RMS between t1 and t2 was calculated and recorded as the start time. Also, to measure the end of contraction time, on the rest part at the end of the algorithm, a t3 point was randomly selected, then t4 time was set 3 to 5 ms after the time t3. Finally, the average RMS was recorded as the end of the contraction. In addition, to normalize the data of the start and finishing time, the formula

Th=EMG(rest)+3SD,

was used. Next, the mean RMS between the beginning and end of each sample’s contraction was used as the raw score for each subject [41].

Raw EMG signals were entered in MegaWin 3.0.1 to calculate the level of muscle activity. With regard to the nature of the RMS signal, there was no need to unidirectionalize the signals first. RMS was also calculated from maximum voluntary isometric contraction data recorded by the Biodex system. For this purpose, RMS was also calculated from raw EMG signal data, which were recorded by the Biodex system. Then, by dividing the amount of obtained activity for each muscle on the MVC and multiplying the resulting number by 100, the percentage of each muscle activity was determined (Figure 3) [2].

Each isometric maximal voluntary contraction was divided on the RMS data to be normalized and presented. Such analyses were performed on all EMG data obtained from all subjects.

Statistical methods

After data collection, the subjects’ characteristics, including age, height, and weight were analyzed with descriptive and inferential statistics using SPSS 21. Excel 2013 was used to draw the study charts and the graphs. The Kolmogorov-Smirnov test was used to be ensured of the data normality. Also, paired t-test was used to examine the mean difference of the functional tests results before and after the fatigue. Finally, the Pearson correlation coefficient was also used to examine the relationship between the activity of lower limb muscles and postural control before and after the fatigue. All data analyses were done at confidence level of 95%.

3. Results

Demographic characteristics of study subjects, including their mean and standard deviation of height, weight, and age are presented in Table 1. Descriptive information (mean and standard deviation) of the measured variables in the study group before and after the fatigue are presented in Table 2. To investigate the changes in each variable, the results of analysis for repeated data are provided in Table 3.

Features of the variables

In this study, the level of postural control is the predictor variable measured by function tests. Also the level of EMG activities of the lower limb muscles (quadriceps, biceps femoris, tibialis anterior, and gastrocnemius) were the criteria variables assessed before and after fatigue. The features of these variables are presented in the following tables. To investigate the difference between the average level of the lower limb muscle activities of the subjects before and after the fatigue, the paired t-test was used. The results of this test are presented in Table 4.

Paired t-test results indicated a significant difference between the activity level of rectus femoris muscles, hamstrings, tibialis anterior, and medial gastrocnemius (P<0.01, P<0.01, P<0.01, P=0.02, respectively) before and after the test.

The results of the correlation coefficient indicated significant relationships between the rectus femoris and tibialis anterior muscle activity levels with subjects’ postural control before the fatigue stage (P=0.02, P=0.04, respectively). However, there were no significant relationships between the activity level of lateral hamstring and medial gastrocnemius muscles and subjects’ postural control before the fatigue (P=0.34, P=0.48, respectively). Also, there were no significant relationships between the rectus femoris, hamstring, tibialis anterior, and medial gastrocnemius muscles with the subjects’ postural control after fatigue (P= 0.94, P=0.61, P=0.35, P=0.09, respectively) (Table 5).

4. Discussion

The study results indicated that after lower extremity muscle fatigue protocol, the electrical activity of muscles and the Y Balance Test scores significantly reduced in all directions. Therefore, lower extremity muscle fatigue had a negative effect on dynamic balance of study participants.

Lower extremity besides being the body base and support, moves the body as well. Therefore, the muscles in this part aside from providing stability of the lower extremity in the standing position, affect the body movements in dynamic conditions [30]. The muscles of the lower extremity help pelvic stability and kinetic chain during functional activities. When these muscles work well, they properly generate and distribute the maximum power with minimal compression and shear forces in kinetic chain joints. They also provide optimal control of the movements and absorb properly impact forces during landing due to ground reaction forces [23].

The dynamic balance decline caused by fatigue of lower extremity muscles can be justifiable. Fatigue can decrease the ability in generating forces, neuromuscular coordination, the exact kinetic control, proprioception, muscles stability, and co-contraction of the muscles. It can also increase the reaction time which its main result would be reduction in the muscles performance [31]. Gribble et al. (2004) considered some factors such as power, flexibility, neuromuscular control, core stability, proprioception, and joint range of motion, effective in successful execution of SEBT. They considered this test as a proper test to analyze the effects of the fatigue on the dynamic balance. Considering the negative effects of the fatigue on the muscles which are major players in performing the SEBT, the reduction in the test results seems reasonable [9].

However in this study, the Y Balance Test (which is based on SEBT) was used. To perform the Y Balance Test, the subject, instead of 8 directions in SEBT, performs only three directions of the anterior, posteromedial, and posterolateral. The Y Balance Test is conducted in closed kinetic chain and thigh muscles play an important role in the function and lower extremity alignment during closed kinetic chain activities [42].

Studies have shown that thigh muscles are extremely influential to maintain balance [26]. Hart et al. (2006) observed a reduction in the function of quadriceps muscles after fatigue in trunk extensor muscles of healthy people and sick ones suffering from backache [23, 24]. On the other hand, the results of an EMG study showed the quadriceps muscles are active during all directions of SEBT [10]. Therefore, the reduction in the balance test scores can be attributed to the muscle tiredness due to the fatigue protocol of the lower extremity muscles.

Quadriceps muscles are very important in generating proper torque and controlling knee joint [7]. During standing on one leg, the quadriceps muscles are contracted in an eccentric way to control the lowered center of the body and at the same time reduce the imported loading contacts [26]. Gribble (2004, 2009) reported that the changes in the proximal muscle activities due to the fatigue could reduce the range of knee and hip joints motion and finally reduce the reach performance in SEBT [19, 20].

Filipa et al. (2009) also believed that muscle coordination and proprioception on performing the SEBT and loss of neuromuscular coordination of the body due to fatigue can negatively affect the stability of lower extremity muscles [15]. When a person tries to maintain the posture, the corrective contractions happen constantly in response to small joints disturbances. Since fatigue can decrease the nerve conduction velocity, the ability to make contractions around the muscles may be reduced which results in the neuromuscular control weakness and more changes around joints. The further changes in joints range of motion may reduce the balance in the absence of corrective actions of the muscles.

Our study results indicated that after administration of fatigue protocol, the activity of the rectus femoris muscle reduced significantly. The quadriceps muscles with their concentric contractions control the knee flexion and are ready to open knee and support the body weight. Low muscle activity leads to less torque and impaired control of knee flexion, as well as support of the body weight. Therefore, it may cause problems in body posture. Di Giulio et al. (2009) reported a strong relationship between the EMG activities of tibialis anterior muscle and postural sway (as a function) in standing position. These results indicated a relationship between the EMG activity of the lower extremity and displacement of the body center of gravity.

According to what was said, reduction in the tibialis anterior muscle activities, after administration of the fatigue program, can impair the sensory receptors and balance corrections in this area. Therefore, applying the fatigue protocol can be more influential in postponing balance corrections and as a result, obtaining a shorter reach distance during the Y Balance Test compared to that distance before fatigue. Thus, the lower extremity muscle activity can reduce the reach distance and weaken dynamic balance because the subject must rely on neuromuscular control around the muscles of lower extremity for reaching longer distances which in the case of untimed start of the balance corrections and lack of generating enough forces, would cause problems for muscles around joints in performing the optimum movement.

According to the study findings, to maintain an optimum dynamic balance during sport activities, the proper level of the muscle activities around lower extremity joints, especially in the anterior region of the leg is very important.

Our study results indicated that the level of the activities in hamstring muscle decreased. Fatigue of the quadriceps muscles may probably affect the co-contraction pattern of the hamstring muscle [12], and thus reduces hamstring muscle activities. Similarly, Parijat (2008) reported the reduction in the hamstring muscle activities during heel contact phase, but he attributed the hamstring muscle activity reduction in walking phase to increase in the speed of heel contact after local fatigue in the quadriceps muscles [42].

Base on the study results, the EMG activities of all studied muscles decreased. The study results were consistent with some other studies like Pincivero et al. (2006) [44]. The reason for a significant difference between the levels of the activity in the lower extremity muscles, before and after fatigue, may be attributed to the fatigue that causes problems in the sensory receptors and balance corrections. Therefore, applying the fatigue program can have a more significant role in postponing the balance corrections and as a result, reaching a shorter distance during the Y Balance Test compared to that distance before the fatigue.

Also, with regard to more obvious effects of administering fatigue protocol by the Biodex system, one can point to the received massages to the brain from sensory receptors of all parts of body due to the exhaustion. Because applying the fatigue program to the exhaustion stage sends messages from sensory receptors of nearly all muscles to the central nervous system to reduce activities and prevent any injuries.

Therefore, to increase the dynamic balance and decrease the effects of fatigue, and consequently, the probable injuries after physical activities, it is suggested that trainers pay special attention to muscular endurance exercises in planning sport programs and physical fitness, especially in the lower extremities and their anterior part. In summary, fatigue in the lower extremity muscles of the body, probably through a negative effect on neuromuscular coordination, motion control acuity, stability of the proximal joints, and the transfer of such destructive effect to the distal joints, causes functional impairment in chain kinetics [26]. Finally, poor balance decreases the ability in performing skilled activities and limits the functional movements [39].

Also, other findings of this research indicated a significant relationship between the activity levels of the rectus femoris and tibialis anterior muscles with subjects’ postural control before fatigue, but there was no such significant relationship after fatigue. Earl and Hertel research indicated that in all directions of SEBT, there were coordinated contractions of the quadriceps and hamstring muscles. Rectus femoris muscle was active during three excursions of the test. To do anterior excursion, the subject lean back and the trunk extension helps maintaining balance. The gravity exerted to the upper body leads to a great momentarily flexion in the knee which must be controlled by the momentarily extension generated by the quadriceps muscles [39].

The study results indicated high activities of the rectus femoris muscle during three directions of the Y Balance Test which had a significant relationship with reach level in different directions of the test. That is because during performing the test, the subject must rely on the neuromuscular control around lower extremity muscles to reach for the maximum distance. To this end, the person must lean backward and the trunk be in the extension position to keep the balance. In this position, the force of gravity acting on the upper part of the body causes a high torque of knee flexion that must be controlled by the extension torque generated by eccentric contraction of quadriceps muscles.

The study results indicated that after applying the fatigue protocol, the activities of quadriceps muscles significantly reduced. Quadriceps muscles of the thigh with a concentric contractions control the knee flexion and are ready to open the knee and support of the body weight [58, 59]. The reduction in the muscles activities lowers generated torque, disturbs knee flexion control and body support [42], and consequently may lead to problems in the postural control.

By all accounts, decline in the tibialis anterior muscle activity after applying fatigue, will impair the sensory receptors and balance corrections in this area. Low activity of lower extremity muscles will result in decreasing reach distance and dynamic balance, as during the reach process, the subject must rely on the neuromuscular control around lower extremity muscles to reach the maximum distance and without balance correction at the start point and lack of generating enough forces around muscles, there will be problems in performing the proper mentioned movements. Based on the study findings, for maintaining an optimum dynamic balance during sport activities, the level of the proper activities of the performing muscles around lower extremity joints especially in the anterior region of the leg is of most importance.

According to the above mentioned topics, the researcher assumed that if the lower extremity muscles get tired and weak, and lower extremity functional tests are undertaken at this stage, a significant relationship may be found between the level of the muscles activities and postural control. However, the research results indicated that the mentioned relationship was not significant at the time of fatigue. At the present study, the relationship between the muscles activities and postural control differed after fatigue compared to normal condition before fatigue.

In most cases, there was a stronger relationship between postural control and the rectus femoris and tibialis anterior muscle before fatigue, but this relationship was not significant between postural control and activities of the lateral hamstring and medial gastrocnemius muscles. In other words, it did not follow any specific and fixed pattern to deduce a correlation. With regard to previous discussions, because the Y Balance Test is conducted in a closed kinetic chain, the produced changes resulted from fatigue in proximal parts affect the distal parts and reduce the Y Balance Test scores. Therefore, the function of the lower extremity muscles influences the dynamic balance of male university athletes in this study.

Postural control is the key factor for performing the daily activities and exercises. With regard to the effects of strength, range of motion, and neuromuscular control over the lower body while performing special tasks in sports, the factors that change the postural control in doing these tasks can affect the performance or the demands on the muscles. The study results indicated a significant relationship between the postural control and the level of the lower limb muscles (rectus femoris and tibialis anterior) activities in the normal condition, but after fatigue, no significant relationship was observed in any lower limb muscles. Also, fatigue in the lower limb extremity muscles significantly reduced all functional test scores and the level of the muscles activities of the sportsmen. Considering the negative effect of fatigue on lower limb muscles, it can be concluded that lower limb muscles functions and their fatigue affect the lower limb performance.

The study has some limitations too. One of them is lack of a control group and randomly-chosen samples that can negatively affect the results. The other limitation of the study was lack of control over participants’ mental conditions, skill level, and their motivation.

With regard to the negative effects of fatigue on the function of lower body muscles, also considering that the devastating effects of fatigue is modifiable, exercises that improve and facilitate the contraction of the muscles of the lower extremity muscles and increase their ability to cope with fatigue could be used by trainers to prevent lower limb function loss caused by fatigue during prolonged exercise activities. Also for a better understanding of biomechanical differences between before fatigue phase and after that, we suggest that the kinematic, kinetic, and EMG characteristics of these two phases be compared.

Acknowledgments

This study was extracted from the master’s thesis submitted to the University of Isfahan. Hereby, we appreciate the assistance of the authorities of Faculty of Physical Education of Isfahan University for allowing laboratory use, and all people participating in this research.

Conflict of Interest

The authors declared no conflict of interests.

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Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Posterior-Exterior

Standing on the left leg

Anterior

Posterior-Exterior

Posterior-Exterior

Standing on the right leg

Anterior

Posterior-Exterior

A

Figure 1. Y Balance Test.

A: Schematic view of Y Balance Test.

B: The subject performing the Y Balance Test.

B

slide1

PHYSICAL TREAAWT IMAGEMENTS

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

AWT IMAGE

Figure 2. A view of the EMG diagram recorded during the execution of the Y Balance Test.

0 1 2 3 4 5 6 7 8

PHYSICAL TREAAWT IMAGEMENTS

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Figure 3. A view of the RMS EMG diagram recorded during the execution of Y Balance Test.

AWT IMAGE

0.5 1/5 2/5 3/5 4/5 5/5 6/5 7/5 8/5

PHYSICAL TREAAWT IMAGEMENTS

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Table 1. The study participants’ characteristics including age, height, and weight.

Subjects’ Characteristics

Mean

SD

Weight (kg)

69.16

6.99

Height (cm)

175.05

3.74

Age (y)

24.11

1.88

AWT IMAGE

Table 3. The mean and SD level of the muscles’ activities before and after fatigue (mV) during Y Balance Test.

Y Test Results

Before Fatigue

After Fatigue

EMG Activity of Muscles

Mean

SD

Mean

SD

Rectus femoris

0.507

0.116

0.427

0.120

Lateral hamstring

0.525

0.086

0.404

0.141

Anterior tibialis

0.530

0.095

0.415

0.076

Medial gasterocnemius

0.600

0.093

0.438

0.119

AWT IMAGE

Table 4. Paired t-test results of lower extremity muscles before and after fatigue in the Y Balance Test.

t

SD

Sig.

Rectus femoris

2.61

0.11

0.02

Lateral hamstring

1.66

0.18

0.00

Tibialis anterior

4.31

0.08

0.00

Medial gastrocnemius

4.07

0.14

0.00

AWT IMAGE

Table 2. The mean and SD of Y Balance Test results, before and after fatigue.

Before Fatigue

After Fatigue

Mean

SD

Mean

SD

Y, cm

80.85

8.76

76.85

10.40

AWT IMAGE

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Table 5: The Pearson correlation coefficient examining the relationship between the postural control and lower limb muscles activities before and after fatigue.

R

P

R

P

Rectus femoris

0.61

0.02

0.02

0.94

Lateral hamstring

0.20

0.48

0.14

0.61

Tibialis anterior

0.64

0.04

0.33

0.35

Medial gastrocnemius

0.27

0.34

0.46

0.09

AWT IMAGE

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

Mongashti Joni Y, et al. The Effect of Lower Extremity Muscle Fatigue on Dynamic Postural Control Analyzed by Electromyography. Physical Treatments. 2016; 6(1):37-50.

F

1. Introduction

lexibility is one of the factors of physical fitness as well as a key component in preventing sporting injury and improving athletic performance. Flexibility is defined as the ability of a joint to move through a normal range of motion, without causing any overpressure on the muscle-tendon unit [1, 2]. Connective tissue “tightness” is a common clinical problem. Tightness may be due to scarring or adaptive shortening of the connective tissues resulting from a disease, injury, or immobilization. Tightness may limit the motion of the affected joints resulting in clinical syndromes [3]. Knee and hamstring muscle play an important role in the lower extremity movements, especially during walking [4, 5]. Several studies have reported high incidence of tightness and injuries of this muscle. Tightness and injuries of hamstring muscle are caused by several reasons such as strength imbalance between hamstrings and quadriceps, repetitive muscle strain, immobilization of lower extremity and scarring in the tissue [6, 7].

The skeletal structure of a person may be a risk factor for injuries [8]. Scar tissue and improper movement patterns resulting from a previous injury that could lead to impaired kinetic chain are the possible mechanisms that reveal the occurrence of musculoskeletal impairment based on kinetic chain system. Injury in one part of the body may lead to muscular imbalances around the joints, eventually resulting in musculoskeletal disorders [9, 10]. Research suggests that abnormalities may damage the anatomical structure [11].

Some abnormalities are congenital and gradually lead to more energy consumption, fatigue in athletes, and development of secondary postures. However, there still exist many ambiguities regarding the effects of these malalignments on athlete’s performances [11]. Many past studies have investigated lower extremity alignment. For instance, Haim et al. (2006) investigated the validity of clinical and radiological features of patellofemoral pain syndrome (PFPS) [12]. Samu Kawa et al. (2007) also examined the effect of tibial rotation on the presence of instability in case of anterior cruciate ligament deficiency [13].

Hamstring muscles are antigravity muscles, and whose decreased flexibility is associated with a wide range of sports injuries from strains to ligament ruptures [5]. Furthermore, a contracture of this muscle may further lead to various problems such as functional abnormalities in the knee, disruption of lumbopelvic rhythm, postural deviations of trunk, lower back, and plantar fasciitis [12, 14-17]. Accordingly, Cibulka, Rose, Delitto and Sinacore (1986) suggested that not only muscle but also sacroiliac joint and distal and proximal joints should be considered for the treatment of hamstring disorders [4]. It can, therefore, be said that appropriate length of this muscle group is necessary for the prevention of several sports-related functional disorders and injuries [18].

On the other hand, lower extremities are a chain of columns and connections that bear the body weight and make shock absorption and walking possible. This chain includes hip, knee, ankle, toes, and their joints, which enable an individual to adapt to the static and dynamic conditions and help them maintain proper body dynamics during the sports activities [11]. Therefore, it is important to understand the lower extremity biomechanics and pathomechanics for preventing any injury during the sports activities [19].

Explosive activities, repeated running, and nature of the game of Futsal imposes a lot of pressure and force on the hip, leg, foot joints, and abdomen [20]. The abnormal adaptation of the body to such movements results in functional abnormalities in athletes [21]. Since appropriate alignment of lower extremity facilitates joint motions, one of the important aims of physical activities is to have an appropriate physical posture and keep normal body alignment [22, 23]. When this alignment is distorted, the joints undergo bad postures and consequently lose their optimum rotation. These changes lead to the distortion of the joint structure and as well as common physical postures in athletes [23].

It is noteworthy that deviation from the desirable physical posture results in decreased mechanical efficiency of the individual, thus making them vulnerable to muscular or nerve injuries [24, 25]. While several past studies have reported that the loss of alignment in a part of the body for a longer duration causes lengthened or shortened muscles, some researchers believe that abnormal alignment may be even caused by muscle imbalance or change in ligament complex, articular capsule or musculotendinous structures [26]. However, not much clarity has been gained on the effect of lower extremity alignment on hamstring performance.

The present study was conducted to gain a better understanding of the risk factors and symptoms of these disorders and designing of rehabilitation programs to cater to these health issues. We believe that hamstring length is one of the key factors for appropriate kinematics of knee. In this paper, we further hypothesize that hamstring tightness may affect the amount of Q angle and tibial torsion among Premier League Futsal players.

2. Materials and Methods

Setting

This study was of descriptive-comparative nature.

Subjects

Thirty male participants aged 18 to 25 years were non-randomly and purposefully (no probable convenience sampling) selected from among Premier League Futsal players of Karaj City and assigned to two 15-member groups, with and without hamstring tightness, respectively. According to the reports of Alborz Province Football Association, this province has 50 futsal players, who had played at least for one season in Premier League in the past five years. Cochran’s formulas were applied to determine the sample size of the subjects in this study.

The exclusion criteria included a history of the spine and lower extremity trauma or surgery, severe injury in knee joint such as anterior cruciate ligament injury (ACL) and meniscus ruptures and a history of any pain in the anterior knee. Prior to any measurement, the procedures were explained to the subjects in detail, and they were asked to give a written consent and information about their age, sports activities, training sessions per week, and injury history.

Measurements

A goniometer (MSD model, Sweden) was used to determine the hamstring tightness and value of Q angle. Each variable was measured three times, and the average was recorded as the individual’s score.

AKE (Active Knee Extension) test

The participants were assessed on a plinth in the supine position. Each assessor marked the greater trochanter, and another to the lateral knee joint line with washable ink. Two lines were drawn from this point. The first was drawn to the greater trochanter, and another to the apex of the lateral malleolus. The participants were asked to flex the hip until the thigh touched the horizontal PVC bar (Figure 1).

While maintaining the contact between the thigh and horizontal PVC bar, the participants were asked to extend the leg as much as possible while keeping their foot relaxed and to hold the position for about five seconds. The goniometer was placed over the previously marked joint axis with its arms aligned along the femur and fibula (Figure 2). The test was positive if the person felt severe tension on his back, knee and thigh before reaching the last 250 [27, 28].

Measurement of Q angle

Q angle or action angle of quadriceps is the angle between the line drawn from anterior superior iliac spine (ASIS) to the middle of the patella and the line drawn from the middle of the patella to the center of tibial tubercle [27]. In order to measure the Q angle, the first line marking was drawn from the ASIS to the middle of the patella and the second line was drawn from the mid patella to the tibial tubercle [29]. The midpoint of the patella was determined by the intersection of the line from the medial to the lateral patella and the line from the inferior to the superior patella [30]. The axis of a manually extendable arm goniometer was placed over the center of the right patella, with its proximal arm placed over the anterior superior iliac spine and the distal arm over the center of the tibial tubercle [31].

Tibial torsion

In order to measure tibial torsion, Thigh-malleoli Method was used. The participants were positioned in the prone position with both knees held in ­90-degree flexion. Centers of medial and lateral malleoli were connected with a line drawn from the cross of the foot. The arms of the goniometer were aligned with the bimalleolar axis (vertical line on this line) and the longitudinal axis of the thigh. The angle formed between bimalleolar and longitudinal axis was reported as the angle of tibial torsion [32] (Figure 3).

Statistical analysis

Independent T-test was used to compare the parameters of the normal distribution at P=0.05. Normal distribution of data and homogeneity of variance were explored by Shapiro–Wilk and Leven Tests, respectively. SPSS, version 21.0, was used for statistical analysis.

3. Results

Subject characteristics including age, body height and weight, and sports activity history are shown in Table 1. In the pilot study conducted on 10 futsal players, Repeatability ICC (Intraclass Correlation Coefficient) was reported to be 0.96 and 0.90 for Q angle and tibia torsion measurements, respectively. The Shapiro-Wilk Test indicated that Q angle and tibial torsion data had the normal distribution in both the groups.

A summary of the independent T-test results is presented in Table 2. According to these results, there is a statistically significant difference between two groups in terms of Q angle and tibial torsion variables (P≤0.05). In the present study, the Q angle and tibial torsion were found to be significantly higher in futsal players with short hamstring as compared to the normal futsal players (without short hamstring).

4. Discussion

According to the results of the present study, tibial torsion and Q angle was found to be higher in the futsal players with hamstring tightness as compared to those without hamstring tightness.

The normal range of tibial torsion is reported to be about 13-18 degrees. More than 18 degrees is defined as the external torsion, and less than 13 degrees is considered as internal torsion [33, 34]. The present study was consistent with the reports of Samu Kawa et al. [13] and indicated that futsal players with hamstring tightness had increased tibial torsion as compared to the control group. On the other hand, the later consisting of 20 normal subjects and 20 subjects with ACL-deficient knees, showed that the amount of tibial rotation was higher in ACL ruptured knees than in uninjured knees, and such higher amounts of tibial rotation affected the figure-of-eight running index. Furthermore, the hamstrings may be vital anterior and rotational stabilizers of the tibia, a role similar to that of the anterior cruciate ligament [35]. Given the weakness and tightness in hamstring muscles in both the groups (ACL ruptured group and futsal players with hamstring tightness), it seems that the effect of hamstring length on knee joint kinematics is one of the possible reasons for such similar results.

The results of this study indicated that Q angle was significantly higher in futsal players with hamstring tightness than in the control group, which is consistent with Haim et al. [12], who suggested that the Q angle higher than 20 degrees was associated with anterior knee pain. Since imbalance of muscles is one of the reasons for knee injuries and pain, we can conclude that tightness in hamstrings against quadriceps resulted in such malalignments (increased Q angle).

Increased Q angle may be due to anteversion of hip or increased external tibial torsion, which further leads to lateral stretch from the rectus femoris muscle to the patella. Due to the naturally wider pelvis, women tend to have higher Q angle. The normal Q angle is about 15 and 10 degrees in women and men, respectively [12].

Muscle tightness or hyperactivity of one muscle or group of muscles is often the initial cause of muscle imbalances that initiates a predictable pattern of kinetic dysfunction [36-38]. Agonist muscle tightness and hyperactivity combined with inhibited and weak antagonist muscles result in disrupted normal force-couple relationship between them thereby implying muscular imbalance [36, 37]. Initial disruption in the normal force-couple relationship between these muscles stimulates a series of events that further perpetuates the altered force-couple relationship. Due to the force imbalance between agonist and antagonist muscles, the joint tends to position itself in the direction of the tight agonist muscle that has an adverse effect on the normal postural alignment [36, 37].

There are several possible mechanisms describing musculoskeletal impairment based on the kinetic chain system, which includes scar tissue and improper movement patterns caused by a previous injury resulting in impaired kinetic chain. Injury in one part of the body may lead to muscular imbalances around the joints, eventually resulting in musculoskeletal disorders. Also, to compensate disruption, the other parts of the body away from the injured part are activated to take over some of the lost action. However, this involvement is one of the possible reasons for disruption in weight bearing and improper distribution of plantar pressure [9, 10].

Prentice (2011) stated that in the case of postural malalignments, the athletic trainers (ATs) should take into consideration those patterns of muscle tightness and weakness that would well correspond to such malalignments [39]. It should be noted that the condition of postural malalignments arising due to muscular imbalance may be addressed through physical rehabilitation techniques [34]. Muscular imbalances can cause both altered postural alignment and bony deformity [36, 37]. Therefore, it is very crucial that the athletic trainers determine the correct cause of postural malalignments, as it might influence the rehabilitation options.

The present study showed that the gradual hamstring tightness can lead to reduced load-bearing capacity of this muscle [40]. Hamstring is one of the major muscles controlling tibial torsion [41]. Decreased load-bearing ability of these muscles results in increased tibial torsion, which further results in increased value of patellar tendon angle with tibia and Q angle [42].

Therefore, to prevent injuries in athletes, especially futsal players, it is much necessary that the coaches and sports science experts pay special attention to these variables. Since, these impairments can be easily detected and corrected by the coaches and sports medicine professionals, the activity of designing and executing the preventive programs should be integrated into the daily programs of athletes.

Some limitations of this study include participation of less number of Futsal player subjects, and lack of electromyography (EMG) measurement, which perhaps could have helped gain a better understanding of the muscle compatibility involved in lower limb movements.

Acknowledgements

This paper had no financial support. The authors express their sincere thanks to all the Futsal players who participated in this study and coaches of Premier League futsal team of Karaj City.

Conflict of Interest

The authors declared no conflict of interests.

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Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with & without Hamstring Tightness

Hooman Minoonejad1, Ehsan Tasoujian2*, Hossein Amiri3, Reza Manteghi3

1. Department of Health and Sports Medicine, Faculty of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran.

2. Department of Sports Injury and Corrective Exercises, Faculty of Physical Education and Sport Sciences, Kharazmi University, Tehran, Iran.

3. Department of Sports Injury and Corrective Exercises, Faculty of Physical Education and Sport Sciences, University of Tehran, Tehran, Iran.

Keywords:

Tibia torsion, Q angle, Hamstring tightness, Athletes, Futsal

* Corresponding Author:

Ehsan Tasoujian, MSc.

Address: Department of Sports Injury and Corrective Exercises, Faculty of Physical Education and Sport Sciences, Kharazmi University, Tehran, Iran.

Phone: +98 (935) 7037875

E-mail: ehfarehsan@gmail.com

03 Nov. 2015

27 Feb. 2016

Citation: Minoonejad H, Tasoujian E, Amiri H, Manteghi R. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players With and Without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

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A B S T R A C T

Purpose: Hamstring muscle is a two-jointed muscle, which is attached to the pelvis at one end and to tibia at the other. Contractures of the hamstring muscles affect the position of proximal and distal joints. The present study aims to compare the value of quadriceps angle (‘Q angle’) and tibial torsion among Premier League Futsal players with and without hamstring tightness.

Methods: In this expost facto study, 30 male players, aged 18 to 25 years old, were non-randomly and purposefully selected as subjects. They were assigned to two 15-member groups, one containing players with hamstring tightness and the other without hamstring tightness. The goniometer was used to check the hamstring muscle tightness and measure the Q angle and tibial torsion. Independent t-test was used to analyze the data at a significance level of 0.05. SPSS version 21.0 was used for statistical analysis.

Results: According to the findings of the present study, there was a significant difference in the value of Q angle and tibial torsion between the healthy athletes and group with hamstring tightness (P≤0.05).

Conclusion: To prevent injuries in Futsal players with hamstring muscles tightness, special attention should be paid to the Q angle and tibial torsion.

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Tasoujian E, et al. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with and without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

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Figure 1. Flexion of the knee until the thigh touches the horizontal PVC bar.

PHYSICAL TREAAWT IMAGEMENTS

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Figure 3. Measurement of tibial torsion by Thigh-malleoli Method.

PHYSICAL TREAAWT IMAGEMENTS

Tasoujian E, et al. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with and without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

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Figure 2. Knee position during AKE test.

PHYSICAL TREAAWT IMAGEMENTS

Table 1. Subject characteristics.

Sports Activity History (Years)±SD

Height (M)±SD

Weight (kg)±SD

Age (Years)±SD

n

Group

3.8±1.26

176.4±6.16

69.4±8.95

22.33±1.95

15

With hamstring tightness

4.26±1.33

175.1±8.64

70.6±9.95

22.33±1.83

15

Without hamstring tightness

0.98

0.46

0.34

0.00

t-test

0.33

0.65

0.73

1.0

P-value

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Table 2. Independent T-test results.

P

T

Without Hamstring Tightness M±SD

With Hamstring Tightness M±SD

Variable

0.043

2.12

10.4±8.04

15.06±5.03

Q angle (degree)

0.026

2.39

16.46±3.87

21.33±6.86

Tibial torsion (degree)

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Tasoujian E, et al. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with and without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

Tasoujian E, et al. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with and without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

Tasoujian E, et al. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with and without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

Tasoujian E, et al. Comparison of Q Angle and Tibial Torsion Among Premier League Futsal Players with and without Hamstring Tightness. Physical Treatments. 2016; 6(1):51-58.

Prevalence Rate of Postural Damages, Disorders & Anomalies among Computer Users

Arvin Fathi1*

1. Department of Computer-Software Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

Keywords:

Damage, Musculoskeletal, Computer users

* Corresponding Author:

Arvin Fathi, MSc.

Address: Department of Computer-Software Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

Phone: +98 (915) 1171993

E-mail: arvin.fathi@ymail.com

17 Nov. 2015

03 Mar. 2016

Citation: Fathi A. Prevalence Rate of Postural Damages, Disorders and Anomalies Among Computer Users. Physical Treatments. 2016; 6(1):59-65.

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Purpose: Globalization of computer use in the past two decades has increased the prevalence of musculoskeletal problems and different damages to computer users. Therefore, the present study aims to determine the prevalence rate of musculoskeletal damages and postural anomalies and disorders among computer users.

Methods: This is a descriptive research study carried out as a field project on 160 university students with 3 years of experience working with computers. The data were collected using a questionnaire developed by the researcher, which was of high reliability and validity. Moreover, for evaluation of the changes in postural alignment, the New York posture rating chart was used. Data analyses were performed by using descriptive statistics, which was done using Excel software and SPSS version 21.0.

Results: The findings of this study revealed that the participants suffered from pain in the head (81.25%), eyes (87.50%), neck (100%), shoulders (100%), waist (81.25%), wrist (100%), fingers (100%), pelvis (93.75%), and knees (100%). Risk factors such as not using suitable chairs, incorrect way of sitting, and lack of movement (i.e. inactivity during work) were of great significance. Moreover, the findings of this research indicated the following as the prevalent postural anomalies among university students: 85% forward head posture, 90% drooping shoulders, 70% pectoral kyphosis, 65% posterior pelvic tilt, 40% bowed knees or X-shaped legs, and 30% ankle rotation.

Conclusion: Sore neck and shoulders, sore eyes, painful wrist, and fingers are very common among computer users. Forward head posture, drooping shoulder (that of the user’s dominant hand), and bowed knees or X-shaped legs were found to be the basic and prevalent postural problems among university students. Inactivity caused by over-work and not attending to ergonomic principles while working was among the key risk factors observed in this study.

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A

1. Introduction

dvancements in science and technology, as well as the efforts to speed up common activities and official affairs worldwide, have necessitated the use of modern equipment. This rising trend has been achieved due to human novelties and innovations. The dominant belief is that consumption of less time and energy with the help of advanced science paves the way for more satisfaction. However, each invention comes along with certain disadvantages, such as unemployment or damages caused by the use of new technology [1-2].

Computer is one such instrument that was initially used in a restricted way but has now become a commercial good for export in small and big countries. Its applications also include significant governmental and official systems, universities, and minor companies [3-4]. However, computer manufacturing companies and all other related organizations have paid less attention to the common standards used in the world. For a higher sale and income, manufacturers believe in designing various computers of attractive models and forms so as to attract more customers in the market [1].

Organizations using this instrument pay no heed to the workstation, type of room and lightings used, one’s positioning in front of the computer system, and so on. They demand more efforts from users, and a lack of attention to these standards would cause severe damages to the users [1, 3]. Musculoskeletal damages caused by frequent computer use comprise a major group of harmful diseases that can lead to fatigue, pain, and disability in users’ limbs. In these diseases, the tendons, ligaments, joints, nerves, blood muscles, and veins are damaged [3]. A myriad of research has showed that these diseases have a wide range of economic effects on users, organizations, and societies [5]. In many countries, preventing diseases among computer users is a national priority [6].

Body positioning, as viewed by the Posture Committee in the Academy of Orthopedic Surgeons, is a relative alignment of the different parts of the body. A proper body posture is defined as a balanced muscular and skeletal state accompanied by the proper alignment of different body segments. Maintaining body in that position should require the least amount of energy. The privilege of a desirable body posture is that it poses the least stress possible on body tissues [1, 2]. Anomaly or defective body posture is any modification in the relative alignment of body parts accompanied by an excessive pressure or tension on body tissues and structures [1, 3].

This postural anomaly caused by contextual stimuli is often of a correctable or reversible type [4]. On the one hand, it is caused by the mechanical life, minimal use of one’s body and inactivity, and on the other hand, it is a function of excessive attention of modern human to an easier and apparently more pleasant life [5]. In fact, people often spend hours in a stable and inappropriate position working or using a computer [6]. According to the reports, people’s working hours from 1997 to 2003 have changed from 5.9 to an average 14.6 hours per day. However, this rising trend has certain side effects such as muscular disorders, headache, and sore neck [7, 8].

A body of research has indicated a correlation between using computer and these pains. The results of a study on computer users in New Zealand showed that sore limbs is the most common musculoskeletal side effect in 81% of the subjects [9]. The prevalence and risk factors of these diseases in developing countries are being investigated [7]. The relevant risk factors are yet not completely known [9]. Previous studies have also revealed that sore neck and shoulder are significantly correlated with lower health state and quality of life [10]. The Bureau of Statistics in the U.S. stated in 1996 that 64% of all disability cases as a function of computer use pertain to sore neck and shoulders [11]. Pain in computer users’ body limbs in the U.S. has imposed medical costs as high as 45 to 55 billion dollars [7].

Advanced science and technology and efforts to speed up official and daily activities have made computer use an indispensable part of social life. As an instance, in 2006, the number of PCs in the U.S., a developed country, was estimated to be about 240 million sets, and in Iran, a developing country, it was about 7.5 million sets [9]. According to research findings, a long-term use of computers can cause musculoskeletal problems in the upper-body parts, especially the neck, shoulders, arms, wrists and fingers [9, 12]. Millions of computer users worldwide are susceptible to the risk of sore limbs. Previous body of research has showed a correlation between working on computer and the occurrence of such painful disorders [13, 14].

Postural control and maintenance is one’s ability to keep the stability of different body parts and react against forces threatening a number of body limbs. To maintain the body’s balance, the central nervous system can react to all this input with proper output. The musculoskeletal system should have a proper range of movement for certain activities. Muscle shrinkage or weakness caused by improper long-term posturing can lead to spasm and contraction [2]. In an extensive review study, the prevalence rate of musculoskeletal diseases was estimated to be 9%-50% among keyboard users. In the control group, however, this rate was 4.5%-17% [15].

In 1997, the U.S. Bureau of Statistics estimated the number of injuries induced by such recurrent activities as typing on the keyboard or working on computer to be 92.576; 55% of these injuries affected the wrists [16]. Ehsani et al. (2013) reported a significant correlation between long-term working on computers and forward head posture. The chance of affliction with sore neck among those working on computers for more than 3 hours a day was estimated to be 5.52 times higher than those who spent less time on computers [17]. Long-term use of computers is very common among the university student population of Iran. Many students suffer from the pain induced by postural disorders. Investigating the underlying factors can help to prevent and treat these pains and enhance their health state.

Little research has been done so far concerning the postural damages faced by computer users in Iran. To the best of our knowledge, no such research has been carried out in Mashhad County. Therefore, the present study seeks to determine the prevalence rate of musculoskeletal damages and the relevant postural anomalies among computer users who studied Engineering at Ferdowsi University of Mashhad.

2. Materials and Methods

This descriptive research was carried out in 2015 on students of the School of Engineering Department who were enrolled in the academic year 2014-15 in Ferdowsi University of Mashhad. A total of 160 subjects volunteered to participate in this study and were selected by available sampling method. The selection criteria consisted of an average of three years of experience using computers and five hours of working with computer each day. People who were injured due to an accident or trauma were excluded. The average age of the population under study is 20.06±4.93 years, the average height is 163.26±7.27 cm, the average weight is 65.59±9.01 kg, and the average body mass index (BMI) is 24.8±4.93.

Data was collected by using a research questionnaire that consisted of two parts, and the results were analyzed. The first part consisted of information such as age, weight, height, and history of working with computers while the second part consisted of questions about injuries of the person who responded to the questionnaire. Cronbach’s alpha test was used to evaluate internal compliance. Cronbach’s alpha coefficient was 0.80 that reflects a relatively high reliability and an acceptable questionnaire. The reliability of the questionnaire was evaluated by using test-retest agreement, and it was found to be 0.73 to 0.88, which is considered to be normal. For evaluation of the changes in postural alignment, the New York posture rating (NYPR) chart was used.

The NYPR was originally published in 1958 (The New York Physical Fitness Test), and its modified form was later published by Howley and Franks (1992) [18]. The NYPR applies a quantitative approach to assess proper and improper alignment of various body segments for an individual in the anatomical position. The NYPR published in 1958 includes a set of three figure drawings for each of 13 body alignment segments contributing to overall postural alignment. The 13 body alignment segments include posterior views of the head, shoulders, spine, hip, feet, and arches, and lateral (left side) views of the neck, chest, shoulders, upper back, trunk, abdomen, and lower back. Short verbal descriptions are provided to indicate the visual cues for use as criteria in deciding the score. In this original version, each body segment was scored 5 (correct posture), 3 (slight deviation), or 1 (pronounced deviation).

Data analysis

Excel software and SPSS Base 21.0 were used for data analysis. Data analyses were performed by analysis of descriptive statistics, calculation of the mean and standard deviation, and analysis of the charts.

3. Results

The distributed frequency and characteristics of participants in the study are presented in Table 1. The results of the damage questionnaire revealed that the prevalence of musculoskeletal disorders in computer users in the last three years (Table 2) is in the head (81.25%), eye (87.50%), neck (100%), shoulder (100%), back (81.25%), forearm (75%), wrist (100%), fingers (100%), pelvis (93.75%), and knees (100%). Based on the results, the highest prevalence of musculoskeletal disorders among computer users (Table 3) has been reported in the area of the head, eyes, neck, shoulder, back, forearm, wrist, hand, hip, and knee, and the lowest degree of damage has been reported in parts of the legs, feet, toes and the palms. The causes and risk factors among computer users are continuous and excessive use of computers, inadequate rest, body fatigue at work, inadequate physical exercise and physical movement, and not following ergonomic conditions.

The findings of this research indicated that the most prevalent postural anomalies among university students are as follows: 85% forward head posture, 90% drooping shoulders, 70% pectoral kyphosis, 65% posterior pelvic tilt, 40% bowed knees or X-shaped legs, and 30% ankle rotation.

4. Discussion

The findings of the present research revealed that musculoskeletal damages are highly prevalent in the target population. The highest prevalence rate of musculoskeletal anomalies are as follows: 81.25% in the head, 87.5% in eyes, 100% in neck, 100% in shoulders, 81.25% in waist, 75% in forearms, 100% in wrists, 100% in fingers, 93.75% in pelvis, and 100% in knees. In Bastani and Lahmi’s study, the highest rate of side effects was also observed in neck (53%), back (48%), and shoulders (12%) [7].

A comparison of these two findings reveals that the highest prevalence rate of musculoskeletal damages among computer users is in the neck, waist, back, and shoulders. Since computer operation is a sedentary job and involves many recurrent movements, it mostly exposes the upper body parts such as the neck and back to musculoskeletal damages. A comparison of national (the present research as well as Bastani and Lahmi’s) and international body of research reveals that the prevalence of musculoskeletal damages to the neck and back among computer users is much lower in Iran than it is in other countries.

In other parts of body, however, there is a little difference [7]. According to the results obtained, the prevalence rates of sore neck and sore shoulder were the same, i.e., equal to 100%. This was higher than the findings reported by similar research in Sudan [12], China [13], New Zealand [9], and the Netherlands [15]. A body of research indicates that alternative keyboards can keep one’s neck, shoulders, wrist and forearm in a neutral position and can, therefore, reduce the negative effects [15].

Other review studies carried out on this issue were also in line with the findings of the present research. In a cross-sectional study carried out by Choubineh et al., the highest prevalence rate of damages belonged to shoulders (59.6%) and neck (58.2%) among professional computer users working in the banks of Shiraz. These rates are lower than those found in the present study [19]. In another investigation conducted on 150 computer users in San Francisco (the U.S.), a significant correlation was found between the hours of using computer, limited choice at work, and musculoskeletal diseases [20]. This is similar to the finding of our research since university student computer users also referred to the constant use of computer as the main reason for musculoskeletal disorders. Among the other findings is the fact that longer hours of working on computers during the day and night further exhausts the eyes and other parts of the body. Working for long hours takes away the chance of resting and removing the tensions from the eyes. Looking at the monitor for long hours would reduce eye accommodation power and could lead to weakness, strain, and even headache [21]. Eyes play an essential role when working on a computer. To work optimally, they need enough rest depending on the working hours. Otherwise, one is initially faced with optic disorders such as strain, which would gradually lead to more serious complaints in later working years [22].

The results of the present research revealed that drooping shoulders, forward head posture, pectoral kyphosis, posterior pelvic tilt, bowed knees, X-shaped leg,s and ankle rotation are the prevalent postural anomalies among university student computer users. In the research reported by Bastani and Lahmi [7], the highest rate of side effects was observed in the neck (53%), back (48%), and shoulders (12%). A comparison of these two reveals that the highest prevalence of musculoskeletal disorders among computer users is in the neck, back, waist, and shoulders. All these damages are induced by carelessness, no attention to correct rules and criteria, and no heed to the desirable standards required to be followed in both manufacturing computers and using them.

In a number of studies, a significant correlation has been reported between the abnormal positioning of the head and body while working (sitting in a rotated body posture or with a bent neck) and complaints of sore neck and shoulder [20]. Keeping one’s neck bent to the front for a long time while working has been also stated to be significantly correlated with sore neck [20]. In an investigation carried out on 150 computer users in San Francisco, longer hours of working on computer and limited choice at work have been showed to be significantly correlated with musculoskeletal diseases [21].

This is in a similar line with the findings of this research study since the university student computer users also mentioned constant overwork as the main cause of their musculoskeletal diseases. In Germany, Sudan, Denmark, and Lebanon, female computer users also reported a higher rate of sore neck and shoulders, as compared to the male users. This gender-based difference in pain reports can be due to the fact that on the average, women tend to do more repetitive activities. However, men do not tend to work for long in a sedentary position. Moreover, mostly because of domestic chore and childcare, women are more susceptible to stress than men [22-24].

Many studies have investigated the damages and anomalies induced by PC and laptop computers. Among them are the works reported by Biswas and Lamba (2012).Similar to our findings, they also reported that pectoral kyphosis and posterior pelvic tilt were more prevalent due to a stable and inappropriate posture in front of the computer. These anomalies are more severe in females than in males [25]. Gerr et al. (2004) also reported the occurrence of such anomalies as forward head posture, bowed knees or X-shaped legs, and rotated ankle as a function of daily activities such as studying and working on computer among financial clerks [26]. However, in previous studies, pectoral kyphosis was found to be induced by such activities as keeping one’s hands forward for a long time [3, 27, 28].

As a result of these problems, one’s body imposes the forward head posture in order to get coordinated and facilitate structural movements [29, 30]. In the case one is adequately susceptible to lordosis, an approximation of the above-mentioned problem worsens this disorder [30]. Considering this issue, performing ergonomic interventions in one’s working environment seems to be essential. The limitations of this study include lack of control over the participants’ lifestyle (the amount of sleep, rest and extra-curricular activities) and the small number of subjects considered in this study.

The prevalence of symptoms of musculoskeletal disorders in the target population was found to be high, especially in the head, eyes, forearm, wrist, fingers, neck, and knees. To treat these damages, people should use certain stretching and physical exercises designed for the limbs involved in working with computer. These exercises should be provided by physical educationalists.

Moreover, a well-designed workstation, proper instruction, and raising the awareness of ergonomic rules can help prevent chronic damage and fatigue among computer users. Furthermore, the forward head posture, drooping dominant shoulders of computer users, bowed knees or X-shaped legs were found to be the prevalent postural anomalies among university students. It had its origin in inactivity due to constant working on computers and not attending to ergonomic rules. Therefore, performing ergonomic interventions in the workplace seems to be essential. A well-designed workstation, instructing users and making them aware of ergonomic rules while working as well as creating variety at work and in their duties can be portions of this suggested program.

Acknowledgments

This research was carried out with personal funds. We express our gratitude to the Engineering students at the Faculty of Engineering of the Ferdowsi University of Mashhad.

Conflict of Interest

The author declared no Conflict of interests.

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Fathi A, et al. Prevalence Rate of Postural Damages, Disorders and Anomalies among Computer Users. Physical Treatments. 2016; 6(1):59-65.

Fathi A, et al. Prevalence Rate of Postural Damages, Disorders and Anomalies among Computer Users. Physical Treatments. 2016; 6(1):59-65.

Table 1. Mean and standard deviation of age, height, and weight variables and body mass index of computer users.

Index

Group

Number

Mean±Standard Deviation

Age (Year)

Weight (Kg)

Height (Cm)

Body Mass Index (Kg/m2)

Computer users

160

20.06±5.91

59.65±8.4

163.27±5.65

24.80±2.99

AWT IMAGE

Fathi A, et al. Prevalence Rate of Postural Damages, Disorders and Anomalies among Computer Users. Physical Treatments. 2016; 6(1):59-65.

Table 2. Frequency and prevalence of musculoskeletal injuries in computer users.

Body Parts

Organs

Musculoskeletal Injuries

Fatigue

Pain

Slight

Medium

Sever

Slight

Medium

Sever

F

%

F

%

F

%

F

%

F

%

F

%

Head and face

Skull

0

0

30

18.75

130

81.25

0

0

30

18.75

130

81.25

Eye

0

0

20

12.50

140

87.50

0

0

20

12.50

140

87.50

Body and spine

Neck

0

0

-

-

160

100

0

0

0

0

160

100

Back

30

18.75

100

62.25

30

18.75

50

31.25

50

31.25

60

37.50

Waist

10

6.25

20

12.50

130

81.25

20

12.50

10

6.25

130

81.25

Rib

60

37.50

80

50

20

12.50

60

37.50

80

50

20

12.50

Upper extremities

Shoulder

0

0

0

0

160

100

0

0

0

0

160

100

Arm

20

12.50

90

56.25

50

31.25

20

12.50

90

56.25

50

31.25

Elbow

20

12.50

90

56.25

50

31.25

20

56.25

90

56.25

50

31.25

Forearm

0

0

40

25

120

75

0

0

30

18.75

120

75

Wrist

0

0

0

0

160

100

0

0

0

0

160

100

Palm

20

12.50

90

56.25

50

80

40

25

90

56.25

30

18.75

Fingers

0

0

0

0

160

100

0

0

0

0

160

100

Upper extremities

Pelvis

0

0

10

6.25

150

93.75

0

0

10

6.25

150

93.75

Thigh

70

43.75

60

37.50

30

18.75

70

43.75

60

37.50

30

18.75

Knee

0

0

0

0

160

100

0

0

0

0

160

100

Leg

110

68.75

40

25

10

6.25

110

-

40

25

10

6.25

Ankle

20

12.50

90

56.25

50

31.25

40

25

90

56.25

30

18.75

Sole

120

75

30

18.75

10

6.25

120

75

20

12.50

20

12.50

Toes

125

75

30

18.75

10

6.25

120

75

30

18.75

10

6.25

AWT IMAGE

Fathi A, et al. Prevalence Rate of Postural Damages, Disorders and Anomalies among Computer Users. Physical Treatments. 2016; 6(1):59-65.

Table 3. Results of musculoskeletal disorders in computer users.

Hyperlordosis

Lowered Shoulders

Chest Kyphosis

Posterior Pelvic Tilt

GenoVarum and GenoValgum

Ankle Deviation

F

%

F

%

F

%

F

%

F

%

F

%

136

85

144

90

112

70

104

65

64

40

48

30

AWT IMAGE

Fathi A, et al. Prevalence Rate of Postural Damages, Disorders and Anomalies among Computer Users. Physical Treatments. 2016; 6(1):59-65.

Fathi A, et al. Prevalence Rate of Postural Damages, Disorders and Anomalies among Computer Users. Physical Treatments. 2016; 6(1):59-65.

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Type of Study: Research | Subject: Special
Received: 2015/10/12 | Accepted: 2016/03/1 | Published: 2016/04/1

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