RESEARCH ARTICLE |
https://doi.org/10.5005/jp-journals-11003-0148 |
Association between Body Mass Index and Hamstring Flexibility among Indian Doctors
1–5Department of Anatomy, Punjab Institute of Medical Sciences (PIMS), Jalandhar, Punjab, India
Corresponding Author: Harpreet S Gulati, Department of Anatomy, Punjab Institute of Medical Sciences (PIMS), Jalandhar, Punjab, India, Phone: +91 9888692783, e-mail: drharpreetonline@gmail.com
Received: 19 July 2024; Accepted: 22 October 2024; Published on: 31 December 2024
ABSTRACT
Introduction: Clinicians in the current scenario are persistently exposed to a heavy workload and an enormous degree of stress, which can hamper the musculoskeletal component of the body significantly. The health of doctors is a critical component in the goal of creating a disease-free society since they form a resolute pillar of the healthcare sector.
Aim of the study: The objective was to determine the effect of body mass index on hamstring flexibility in clinicians. This will establish a relationship between obesity and body stretchability.
Materials and methods: The study was conducted in outpatient department (OPD) clinics of various departments at Punjab Institute of Medical Sciences, Jalandhar, and OPDs of NIMS Hospital, Jaipur, over a period of 2 years from July 2019 to June 2021. BMI was calculated as the ratio of weight (kg) to the square of height (m). Hamstring flexibility was checked by obtaining the sit-and-reach test score using a sit-and-reach test box.
Results: Body flexibility reduced significantly with advancing age and increasing body mass index (BMI). Above-average back and hamstring flexibility was seen in only 8.5% of the doctors, while 12% of the clinicians demonstrated poor flexibility range.
Conclusion: The present study yields a significant association in terms of linear correlation between hamstring flexibility and obesity among clinicians. The professionals can take note of this information and use it as caution to protect their own health.
Keywords: Clinicians, Flexibility, Hamstring, Medical, Obesity, Surgical
How to cite this article: Gulati HS, Wadhwa A, Kaur K, et al. Association between Body Mass Index and Hamstring Flexibility among Indian Doctors. J Med Acad 2024;7(2):60–65.
Source of support: Nil
Conflict of interest: None
BACKGROUND
The health issue of doctors is a growing concern in the healthcare industry because of the simple fact that the good health of clinicians themselves goes a long way in providing better health for the patients. So, there must be adequate care and concern for those who are providing health to all. The additive effect of overexertion in clinicians and overweight may have led to increased cumulative trauma disorders (CTDs). The term CTD has been used in connection with certain conditions that are also referred to as work-related musculoskeletal disorders, repetitive strain injuries, or overuse syndromes.1 All these terms refer to injuries that may involve soft tissue around the joints, like tendons, ligaments, or nerve trapping, which can affect body flexibility.
Flexibility is an important measure as well as an element of muscle fitness. This is all the more significant because flexibility, as an element of health-related fitness, reflects the prevention of orthopedic deterioration in the later part of life, especially in the form of back pain. Thus, flexibility is an important requisite constituent to avoid the risk of musculoskeletal problems with age.2 Flexibility is often a neglected aspect of physical fitness, though it forms an essential core of physical fitness. It is useful not only for athletes and sportspersons but also for the general health of people regarding fitness and injury prevention. Basically, fitness can be elucidated as the potential of the muscle-tendon unit to lengthen within the physiological limits of the joint concerned. Thus, it gives an impression of a person’s physical capacity. Joint flexibility is dependent upon a number of factors, like the configuration of the joint, the muscles and tendons surrounding it, the articular capsule of the joint, and even the amount of fat tissue in and around the joint.3
The range of flexibility correlated with high body mass index (BMI) can be interpreted by the deposition of abdominal fat, lower degree of muscle mass and strength, decreased functional capacity, and pronounced trouble in performing routine day-to-day activities.4 Rafique et al. conducted a comparison of body mass index and flexibility by means of the sit-and-reach test. The idea was to explore BMI and flexibility status of a comparatively same-age and same-gender population. The results obtained were indicative of reasonably good accuracy of the procedure. The sit-and-reach test was found to be a good alternative to BMI. There was a significant relation of BMI with flexibility, such that subjects with high BMI tended to be poor in flexibility of the body as such.5 A cross-sectional study to establish an association between body flexibility and body mass index, using a self-structured questionnaire to assess flexibility, outlined a definite relation between body mass index and flexibility.6 Bittencourt et al. stressed the importance of preventive management with the need for prediction of the degree of functional deterioration among overweight individuals.7 The study aimed at inferring the effect of overweight on both flexibility and functional capacity. All the study participants were subjected to anthropometric, flexibility range, muscle strength, and endurance testing. The majority of the overweight were males and reported significant shortening of iliopsoas, pectoral, and piriformis muscles.
It is imperative to investigate any potential relationships between body flexibility and BMI in light of the rising obesity trends and the burden that Indian practitioners face. The study’s goal is to identify the correlational impact of high BMI on Indian doctors’ hamstring and back flexibility. The current study will provide insight into the incidence of obesity among doctors as well as its association with physical health.
MATERIALS AND METHODS
The present descriptive study was carried out on 400 doctors working in outpatient departments (OPDs) of a few medical colleges in North India from July 2019 to June 2021. The study was undertaken with prior approval from the Institutional Ethics Committee, NIMS University, Jaipur, vide Ref. no. NIMSUNI/IEC/2019/PhD/142 dated 30-07-2019.
Inclusion Criteria
The study used a systematic random selection approach to identify subjects who were willing to participate, were between the ages of 25 and 60, of both genders, and had at least three years of clinical work experience with a minimum working duration of 6 hours a day on clinical tasks.
Exclusion Criteria
Those doctors who were suffering from any chronic physical illness, who underwent any major surgery in the preceding year, who had a history of trauma, or who had any congenital anomaly were excluded from the present study.
Sample Size Calculation
The sample size was calculated with the help of software G*Power version 3.1.9.2 to be 372. It was measured at 99% confidence, keeping the margin of error at 5% from a total study population of 845 doctors on our list. They were selected by systematic random sampling method. For better interpretation, the total number of clinicians taken for the study was 400. For better generalization among both genders and types of clinicians, the sample size was divided into 200 males and 200 females, as well as 200 medical and 200 surgical clinicians. Various clinical specialists were categorized into two broad groups, namely, medical clinicians and surgical clinicians. The specialists of medicine, psychiatry, pulmonary medicine, pediatrics, dermatology, emergency medicine, radiology, rheumatology, medical oncology, radiation oncology, anesthesia, cardiology, neurology, endocrinology, gastroenterology, neonatology, nephrology, and graduate general physicians were included as medical clinicians, whereas the specialists of general surgery, orthopedics, obstetrics and gynecology, otorhinolaryngology, ophthalmology, neurosurgery, urology, surgical gastroenterology, pediatric surgery, plastic surgery, cardiac surgery, and surgical oncology were included as surgical clinicians for the study.
Procedure
The flexibility of the body was determined on the basis of extensibility of the lower back and hamstring muscles. This was done by obtaining the sit-and-reach test score using a sit-and-reach test box.8 The sit-and-reach test box is made of wood or plastic with the following dimensions:
Base: 18” in length × 12” in width × 13 – 3/4” in height; and
Top: 27 – 1/2” in length × 12” in width.
These dimensions are as per the Lafayette adjustable sit-and-reach flexibility tester, model 2003. This test was tested and found to have a good test-retest reliability (0.989).
The sit-and-reach test was performed by sitting on the ground with the subject’s back and head pushed against a wall, lower extremities fully stretched and extended in such a way that the soles of the feet were in firm contact with the sit-and-reach test box. After this, the subject was made to place his/her hands one over the other with the palms facing downwards, extending the arms anteriorly while keeping the head and back still against the wall. The distance between the fingertips and the box was measured with a scale. This position was labeled as zero or the starting point. Then, the subject was asked to bend forward slowly and reach as far forward as possible by sliding the fingers over the ruler of the box, pausing at the final position for a minimum of 2 seconds. This distance was again measured and noted. The whole procedure was done three times on each subject, and the best distance recorded was finally noted as the flexibility sit-and-reach test score.
The sit-and-reach test scoring: The scores of the sit-and-reach test were interpreted in the following 7 grades9,10: Very poor (1), Poor (2), Fair (3), Average (4), Good (5), Excellent (6), Super (7).
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Very poor (Grade 1) consists of a sit-and-reach test score of <–20 for men and <–15 for women.
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Poor (Grade 2) consists of a sit-and-reach test score between –19 to –9 for men and –14 to –8 for women.
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Fair (Grade 3) consists of a sit-and-reach test score between –8 to –1 for men and –7 to 0 for women.
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Average (Grade 4) consists of a sit-and-reach test score between 0 to +5 for men and +1 to +10 for women.
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Good (Grade 5) consists of a sit-and-reach test score between +6 to +16 for men and +11 to +20 for women.
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Excellent (Grade 6) consists of a sit-and-reach test score between +17 to +27 for men and +21 to +30 for women.
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Super (Grade 7) consists of a sit-and-reach test score of >+27 for men and >+30 for women.
Statistical Analysis
The independent variables included in this study were age, gender, BMI, and type of clinician. These were associated with hamstring flexibility, which is the dependent variable. The data were given statistical treatment with the software IBM Statistical Package for the Social Sciences (SPSS) Statistics version 21. The Chi-squared test of association was checked between different categories of BMI and flexibility. Analysis of variance (ANOVA) and Student’s t-test were employed to reflect the association between the mean flexibility score with different levels of BMI and gender, respectively. Pearson’s correlation coefficient was also established to determine the linear correlation between BMI and hamstring flexibility in doctors.
RESULTS
When considering the overall distribution of BMI among physicians, Table 1 below makes clear that the majority of clinicians reported having high BMIs (n = 199, 49.8%), placing them in the overweight category, while 11.5% (n = 46) of clinicians had BMIs >30, placing them in the obese category. As a result, 61.3% of clinicians overall were overweight relative to their height.
| BMI category | Total n (%) | Gender | Age-groups | Type of clinician | |||||
|---|---|---|---|---|---|---|---|---|---|
| Male (n = 200) | Female (n = 200) | ≤30 years n (%) | 31–40 years n (%) | 41–50 years n (%) | >50 years n (%) | Medical (n = 200) | Surgical (n = 200) | ||
| Low | 12 (3) | 4 (2) | 8 (4) | 2 | 3 | 7 | 0 | 10 (5) | 2 (1) |
| Normal | 143 (35.8) | 83 (41.5) | 60 (30) | 17 | 47 | 46 | 33 | 77 (38.5) | 66 (33) |
| High | 199 (49.8) | 95 (47.5) | 104 (52) | 14 | 57 | 71 | 57 | 88 (44) | 111 (55.5) |
| Very high | 46 (11.5) | 18 (9) | 28 (14) | 5 | 15 | 23 | 3 | 25 (12.5) | 21 (10.5) |
| Chi-squared test | χ2 = 7.614, p = 0.055; Not significant |
χ2 = 18.960, p = 0.026; Significant |
χ2 = 9.186, p = 0.027; Significant |
||||||
Age, gender, and type of physician all had an impact on the prevalence of high BMI. We found that BMI was substantially (p = 0.026) correlated with various age-groups (Fig. 1). The age range of 41–50 years old had the highest percentage of obese doctors, whereas the group of 51–60 years old had the highest rate of overweight doctors, as it was found that for the majority of clinicians, BMI increased after the fourth decade of life. The Chi-squared test revealed no significant association (p > 0.05) between gender and BMI; however, overall, women reported slightly more overweight and obese doctors. There was, however, a significant association (p = 0.027) of BMI with the type of clinician, as it was seen that a higher percentage of high to very high BMI clinicians were surgical specialists (66%) compared to medical doctors (56.5%).
Fig. 1 Frequency distribution of flexibility range in clinicians
The flexibility range of lower back muscles and hamstrings, assessed with the help of the sit-and-reach test, was categorized into the following seven grades: very poor, poor, fair, average, good, excellent, and super. In the present study, none of the study participants was found to have flexibility in the two extreme ranges, that is, very poor or super flexibility. Thus, the distribution of doctors into the remaining five grades, namely, poor, fair, average, good, and excellent, is depicted in the form of a pie chart in Figure 2 below. The majority (45.5%) of the doctors exhibited fair flexibility, while 34% of them were found to have average flexibility. Above-average back and hamstring flexibility was seen in only 8.5% of the doctors, while 12% of the clinicians demonstrated poor flexibility range.
Fig. 2 Association of flexibility with different age-groups of clinicians
Table 2 shows the relative relationship of body flexibility with different age-groups in doctors. The association, measured by the statistical test of chi-square analysis, showed a highly significant relationship (χ2 = 54.621, p < 0.001) between an increase in age-groups and a decline in flexibility. It is evident that the percentage of clinicians showing poor and fair (below average) body flexibility increased manifold in the age-groups 41–50 years and 51–60 years compared to the younger age-group 31–40 years. A high prevalence of good flexibility was noted in the younger age-groups of <30 years and 31–40 years, as compared to a very low incidence of good flexibility in senior age-groups. Thus, age has a critical bearing on the flexibility of the lower back and hamstrings.
| Gender | Flexibility | ||||
|---|---|---|---|---|---|
| Poor | Fair | Average | Good | Excellent | |
| Females (n = 200) | 24 | 91 | 79 | 4 | 2 |
| 12.0% | 45.5% | 39.5% | 2.0% | 1.0% | |
| Males (n = 200) | 24 | 91 | 57 | 28 | 0 |
| 12.0% | 45.5% | 28.5% | 14.0% | 0.0% | |
Chi-square value = 23.559; df = 4, p < 0.001 (highly significant)
Deriving the relationship between flexibility and gender, Pearson Chi-squared test revealed a very significant association between the two, as shown in Table 3. Though below-average flexibility was reported equally in both males and females, a far higher percentage of males (14%) had good flexibility range compared to only 2% of females possessing good flexibility.
| Type of clinician | Flexibility | ||||
|---|---|---|---|---|---|
| Poor | Fair | Average | Good | Excellent | |
| Medical (n = 200) | 20 | 84 | 78 | 18 | 0 |
| 10.0% | 42.0% | 39.0% | 9.0% | 0.0% | |
| Surgical (n = 200) | 28 | 98 | 58 | 14 | 2 |
| 14.0% | 49.0% | 29.0% | 7.0% | 1.0% | |
Chi-square value = 7.851; df = 4; p = 0.097 (not significant)
Table 4 below shows the association between body flexibility and clinician type, which was determined by Chi-squared test as nonsignificant (p > 0.05). Both medical and surgical clinicians were evenly distributed among different grades of flexibility. Considering mild differences, surgical clinicians had a very negligible higher prevalence of below-average flexibility than medical specialists.
| BMI category | Flexibility | ||||
|---|---|---|---|---|---|
| Poor | Fair | Average | Good | Excellent | |
| Underweight (n = 12) | 0 | 0 | 10 | 2 | 0 |
| 0.0% | 0.0% | 83.3% | 16.7% | 0.0% | |
| Normal weight (n = 143) | 4 | 42 | 74 | 22 | 1 |
| 2.8% | 29.4% | 51.7% | 15.4% | 0.7% | |
| Overweight (n = 199) | 20 | 118 | 52 | 8 | 1 |
| 10.1% | 59.3% | 26.1% | 4.0% | 0.5% | |
| Obese (n = 46) | 24 | 22 | 0 | 0 | 0 |
| 52.2% | 47.8% | 0.0% | 0.0% | 0.0% | |
Chi-square value = 156.048; df = 12; p < 0.001 (highly significant)
Flexibility was analyzed for its relationship with BMI by means of Pearson Chi-squared test of association. The statistical analysis revealed a highly significant association between high BMI and a decline in body flexibility (p < 0.001). The range of flexibility decreased remarkably with an increase in body weight, as shown in Table 5. While normal weight clinicians had only 32.2% prevalence of below-average flexibility, the same rate increased to 69.4% in the case of overweight doctors. It was of notable significance that all obese clinicians fell in the categories of below-average (poor and fair) flexibility, while no underweight clinician fell in that category. Such is the impact of high BMI on body flexibility.
| Flexibility score | p-value | ||||
|---|---|---|---|---|---|
| Mean | SD | SEM | |||
| Age# | ≤30 (n = 38) | 0.342 | 5.3488 | 0.8677 | <0.001** |
| 31–40 (n = 122) | 0.926 | 6.2406 | 0.5650 | ||
| 41–50 (n = 147) | –2.565 | 6.2582 | 0.5162 | ||
| >50 (n = 93) | –4.677 | 4.8682 | 0.5048 | ||
| BMI# | Low (n = 12) | 4.750 | 1.8647 | 0.5383 | <0.001** |
| Normal (n = 143) | 1.483 | 5.5486 | 0.4640 | ||
| High (n = 199) | –2.859 | 5.8110 | 0.4119 | ||
| Very high (n = 46) | –8.391 | 2.2753 | 0.3355 | ||
| Gender$ | Male (n = 200) | –2.105 | 6.1729 | 0.4365 | 0.213; NS |
| Female (n = 200) | –1.325 | 6.3245 | 0.4472 | ||
| Type of clinician$ | Medical (n = 200) | –1.055 | 6.0593 | 0.4285 | 0.035* |
| Surgical (n = 200) | –2.375 | 6.3889 | 0.4518 | ||
#ANOVA; $Student t-test; SD, standard deviation; SEM, standard error mean; NS, p > 0.05, not significant; *, p < 0.05, significant; **, p < 0.001, highly significant
Table 6 below depicts the comparison of mean flexibility scores in centimeters with different age categories and BMI categories by means of analysis of variance. The mean flexibility score decreased with increasing age-groups as well as BMI groups and showed a negative value in clinicians aged above 40 years and with BMI greater than 25. A Student’s t-test applied to compare mean flexibility scores among both genders and types of clinicians yielded a significant p-value in the case of clinician type. Mean flexibility was found to be –1.055 cm in medical specialists and was worse in surgical specialists at –2.375 cm.
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Sum of squares | df | Mean square | F | p | ||
| Regression | 6301.261 | 2 | 3150.630 | 134.462 | 0.000 | |
| Residual | 9302.249 | 397 | 23.431 | |||
| Total | 15603.510 | 399 | ||||
| Variables | Coefficient | Std. error | t | p | 95% confidence interval | |
| Lower bound | Upper bound | |||||
| (Constant) | 36.134 | 2.321 | 15.570 | 0.000 | 31.572 | 40.697 |
| Age | –0.224 | 0.029 | –7.849 | 0.000 | –0.280 | –0.168 |
| BMI | –1.080 | 0.077 | –13.966 | 0.000 | –1.232 | –0.928 |
Using multiple regression analysis (Fig. 3), flexibility compared with age and BMI was found to have a highly significant relationship by ANOVA (F = 134.462, p < 0.001). The coefficients for age (–0.224) and BMI (–1.080) underline the negative association of flexibility with age and BMI. The results also imply that age and BMI can be accurately used to predict flexibility based on the current study parameters.
Fig. 3 Sit and reach test box
Pearson correlation coefficient for the correlation of flexibility with age (r = –0.333) and BMI (r = –0.558) shows a highly significant p-value (<0.001). The results depict that flexibility of the back and hamstrings declines with advancing age and an increase in BMI.
DISCUSSION
One area that has generally received insufficient attention in our society is the health of doctors, even though it requires significant focus. Physicians should be made aware of the consequences of neglecting their own health, particularly in regards to excessive weight gain brought on by a stressful and sedentary work environment. The majority of the doctors in the study population had a high BMI, according to the current study. The prevalence of overweight and obese clinicians is much higher (61.3%) than the national rate (42.01%) of overweight and obese people with a BMI >25. However, in terms of obese individuals with a BMI >30, the percentage of clinicians in this category (11.5%) was very close to the obesity rate (10.03%) in a study by Hadaye et al.11 A doctor’s BMI can have significant negative effects on their patients. It is crucial for doctors to consider their own weight when advising patients about weight loss treatments and strategies. Bleich et al. evaluated the influence of doctors’ BMIs on the quality of obesity care they provided to patients and discovered that doctors with normal BMIs who engage in healthy lifestyle habits and exercise are more likely to talk to their patients about weight loss techniques and exercise than obese doctors.12
There have been earlier studies involving the assessment of flexibility and physical fitness in the Indian population.2,13,14 The current study has taken equal samples of males and females to improve the generalizability of the study. The age-groups included were those actively involved in hospital work and patient care. The present study found that the majority of clinicians (57.5%) had below-average flexibility, with only 8% having good flexibility and just 0.5% possessing excellent flexibility. The level of flexibility among clinicians is very poor in comparison to the general population.
In support of our findings, de Greef et al., studying the evaluation of physical fitness in older individuals living a sedentary lifestyle, found a marked decrease in physical fitness levels in subjects aged 55-65 years.15 Stathokostas et al. also observed that the flexibility of the shoulder and hip joints decreases by roughly 6° with every decade of life from ages 55 to 86 years.16 Mistry et al., in their study on the association of hamstring flexibility with age and gender, concluded that hamstring flexibility declines gradually with advancing age, with a more pronounced effect in males than in females.17 A recent study indicated a notable difference in fascia thickness between young and old individuals.18 The researchers opined that age-related alterations in fascia thickness could contribute to limitations in joint range of motion and flexibility, thereby inferring that flexibility reduces with increasing age. The results of our investigation showed a highly significant correlation between high BMI and decreased flexibility. All doctors with very high BMIs (>30) exhibited below-average back and hamstring flexibility due to the strong influence of excess weight. In support of our results, Jarral et al. concluded that there is a definite negative association between BMI and flexibility, finding that excessive mass restricts the range of motion, ultimately affecting flexibility.6
In contrast to the current study, Arora et al. reported only a low association between BMI and hamstrings/back flexibility among adolescents.2 This could be due to the lower mean age of all the study participants, as compared to the present study, where we observed a definite inverse relationship between age and flexibility, which is also supported by many authors. Yahaya also did not find any statistically significant correlation between flexibility and height or weight among badminton players.3 However, in their study, the mean flexibility score was much higher than in the present study, as all the subjects were professional badminton players engaged in regular body exercise. On the other hand, the subjects in the current study are far more sedentary workers.
Most clinicians have been found to have body flexibility on the lower side, which may be due to excessive sitting in air-conditioned OPDs, where muscles become stiff and tend to shorten, ultimately leading to a decline in flexibility range. This, in turn, may jeopardize the musculoskeletal system by causing higher muscle strain. A biochemical study revealed that maximum oxygen uptake is closely related to adiposity and BMI among all other variables of physical fitness, with the result that premature fatigue of the musculature is the key factor for the downfall in physical fitness and flexibility.19 Thus, by all means, BMI has a well-defined inverse relationship with body flexibility.
Surgeons have been found to have less flexibility compared to medical physicians, which may be due to prolonged standing in operation theatres, leading to hamstring impairment. A study on resident orthopedic surgeons found them to have a high prevalence of hamstring tightness, which is believed to be due to their busy schedules involving long hours of surgery.20
Limitations
The current study’s geographical generalization is limited because it only includes doctors from Jalandhar to Jaipur, two Indian cities. Another drawback is that the current study did not assess the clinicians’ overall health.
CONCLUSION
Body flexibility reduced significantly with advancing age and increasing BMI and was seen to be more affected in males. There was no significant correlation with the type of clinician. Notably, it has been observed that doctors who are concerned about improving their own health or have the desire to be healthy are more likely to advocate for their patients regarding the prevention of illness and make healthy habits a priority.
ACKNOWLEDGMENT
We gratefully acknowledge the contribution of Mr Gurinderjit Singh (statistician) for his help in statistical data analysis.
ORCID
Harpreet S Gulati https://orcid.org/0000-0001-5388-1559
Jasveen Kaur https://orcid.org/0009-0000-3253-2966
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