Authors : Athulya John; Rejimol Jos Pulicken; Remya N; Manju Unnikrishnan; Jisha Thampi; Chinchu Alwin; Rakhi Balagopal; Anumol C; Reeba Roy

Volume/Issue : Volume 10 - 2025, Issue 2 - February

Google Scholar : https://tinyurl.com/3cr486e5

Scribd : https://tinyurl.com/yebbb5t5

DOI : https://doi.org/10.5281/zenodo.14965884

Abstract :  Background Obesity rates continue to rise locally and globally, which is related a concurrent rise in medical and economic costs. Previous literature has not comprehensively discussed the association of weight-for-height index with health-oriented physical fitness, gait speed, and health-related quality of life in middle-aged subjects. Such information is valuable in predicting future health-related risks and formulating interventions to slow the disabling process. Hence, the study aims to estimate the association of weight-for-height index with health-oriented physical fitness, gait speed, and health-related quality of life.  Objective To determine the association of weight-for-height index with health-oriented physical fitness, gait speed, and health-related quality of life in middle-aged subjects.  Methods 62 subjects were recruited based on inclusion criteria and divided into five different weight-for-height index categories. Six measures of physical fitness (waist-hip ratio, hand grip strength, 30-second chair stand test, modified push-up test, 2-minute walk test, chair sit and reach test) were measured. Physical Fitness Index was calculated as the mean of these six fitness test scores and gait speed was analyzed using a 10-meter walk test and health-related quality of life using the SF-12 questionnaire.  Result and Discussion The bivariate analysis showed a decreasing trend in physical fitness, gait speed, and health-related quality of life across the weight-for-height index categories. All variables showed a significant inverse relation (p<.05) with the weight-for-height index. The results may be due to the increased presence of type II muscle fibers and adiposity in higher weight-for-height index which might cause a detrimental impact on physical fitness. Excess adipose tissue modifies the ideal ratio of fat and fat-free mass, as well as the quality and function of skeletal muscle. The above might have implied an overall negative effect on gait speed and health-related quality of life.  Conclusion The study observed an association between weight-for-height index with health-oriented physical fitness, gait speed, and health-related quality of life in middle-aged subjects.

Keywords : Weight-For-Height Index; Health-Oriented Physical Fitness; Physical Fitness Index; Gait Speed; Health-Related Quality of Life; Middle-Aged Subject.

References :

1. Bodymassindex(BMI).Who.int.2022.https://www.who.int/data/gho/data/themes/topics/topic-details/GHO/body-mass-index
2. Nguyen P, Scott S, Headey D, Singh N, Tran L, Menon P et al. The double burden of malnutrition in India: Trends and inequalities (2006–2016). PLOS ONE. 2021;16(2): e0247856.
3. Caballero B. The Global Epidemic of Obesity: An Overview. Epidemiologic Reviews. 2007;29(1):1-5.
4. Ullas.AS. Kerala's obesity rate surpasses national average. https://www.onmanorama.com/news/kerala/2021/11/29/kerala-obesity-rate-surpasses-national-average.html     
5. Luhar S, Timaeus I, Jones R, Cunningham S, Patel S, Kinra S et al. Forecasting the prevalence of overweight and obesity in India to 2040. PLOS ONE. 2020;15(2): e0229438.
6. HU G, Tuomilehto J, Silventoinen K, Barengo N, Jousilaht P. Joint effects of physical activity, body mass index, waist circumference and waist-to-hip ratio with the risk of cardiovascular disease among middle-aged Finnish men and women. European Heart Journal. 2004;25(24):2212-2219.
7. Tian Y, Jiang C, Wang M, Cai R, Zhang Y, He Z, et al. BMI, leisure-time physical activity, and physical fitness in adults in China: results from a series of national surveys, 2000-14. Lancet Diabetes Endocrinol. 2016;4(6):487–97.
8. Unnikrishnan S. Having potbelly adds to risk of Covid, say experts as NFHS report cites high prevalence of obesity in Kerala. 2022. Available from: https://www.newindianexpress.com/states/kerala/2022/mar/14/having-potbellyadds-to-risk-of-covid-say-experts-as-nfhs-report-cites-high-prevalence-of-obesity-in-kerala-2429783.
9. Tabue-Teguo M, Perès K, Simo N, Le Goff M, Perez Zepeda M, Féart C et al. Gait speed and body mass index: Results from the AMI study. PLOS ONE. 2020;15(3): e0229979.
10. Shinkai S. Walking speed as a good predictor for the onset of functional dependence in a Japanese rural community population. Age and Ageing. 2000;29(5):441-446.
11. Matsuzawa Y, Shimomura I, Nakamura T, Keno Y, Kotani K, Tokunaga K. Pathophysiology and pathogenesis of visceral fat obesity. Obes Res. 1995;3(S2):187s–94s.
12. Suni J, Oja P, Miilunpalo S, Pasanen M, Vuori I, Bös K. Health-related fitness test battery for middle-aged adults: Associations with physical activity patterns. Int J Sports Med. 2007;20(03):183–191.
13. Peters D, Fritz S, Krotish D. Assessing the reliability and validity of a shorter walk test compared with the 10 meter walk test for measurements of gait speed in healthy, older adults. journal of geriatric physical therapy. 2013;36(1):24-30.
14. Wee C, Davis R, Hamel M. Comparing the SF-12 and SF-36 health status questionnaires in patients with and without obesity. Health and Quality of Life Outcomes. 2008;6(1):11.
15. Lumeng CN, Saltiel AR. Inflammatory links between obesity and metabolic disease. Journal of Clinical Investigation. 2011;121(6):2111–7.
16. Kelley DE, Thaete FL, Troost F, Huwe T, Goodpaster BH. Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. American Journal of Physiology-Endocrinology and Metabolism. 2000;278(5).
17. Armstrong A, Jungbluth Rodriguez K, Sabag A, Mavros Y, Parker HM, Keating SE, et al. Effect of aerobic exercise on waist circumference in adults with overweight or obesity: A systematic review and meta‐analysis. Obesity Reviews. 2022;23(8).
18. Laxmi CC, Udaya IB, Vinutha SS. Effect of body mass index on cardiorespiratory fitness in young healthy males. Int J Sci Res Publ. 2014;4(2):1-4.
19. Ahima RS, Flier JS. Adipose tissue as an endocrine organ. Trends in Endocrinology & Metabolism. 2000 Oct 1;11(8):327-32.
20. Abellan van Kan G, Rolland Y, Andrieu S, Bauer J, Beauchet O, Bonnefoy M, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging. 2009;13(10):881–889.
21. Dufour AB, Hannan MT, Murabito JM, Kiel petersDP, McLean RR. Sarcopenia definitions considering body size and fat mass are associated with mobility limitations:the Framingham Study. J Gerontol A Biol Sci Med Sci. 2013; 68(2):168–174.
22. Verghese J, Wang C, Allali G, Holtzer R, Ayers E. Modifiable risk factors for new-onset slow gait in older adults. J Am Med Dir Assoc. 2016;17(5):421–425.               
23. Hardy R, Cooper R, Aihie Sayer A, Ben-Shlomo Y, Cooper C, Deary IJ, et al. Body mass index, muscle strength and physical performance in older adults from eight cohort studies: The Halcyon Programme. PLoS ONE. 2013;8(2).
24. Lad UP. A study on the correlation between the body mass index (BMI), the body fat percentage, the handgrip strength and the handgrip endurance in underweight, normal weight and overweight adolescents. journal of clinical and diagnostic research. 2013
25. Benetti FA, Bacha IL, Junior AB, Greve JM. Analyses of balance and flexibility of obese patients undergoing bariatric surgery. Clinics. 2016;71(2):78–81.
26. Rietman ML, van der A DL, van Oostrom SH, et al. The Association between BMI and Different Frailty Domains: A U-Shaped Curve? J Nutr Health Aging. 2018; 22(1):8–15
27. Stenholm S, Sainio P, Rantanen T, et al. High body mass index and physical impairments as predictors of walking limitation 22 years later in adult Finns. J Gerontol A Biol Sci Med Sci. 2007; 62(8):859–865.
28. Stenholm S, Alley D, Bandinelli S, Griswold ME, Koskinen S, Rantanen T, et al. The effect of obesity combined with low muscle strength on decline in mobility in older persons: results from the In Chianti study. Int J Obes. 2009;33(6):635–644.      
29. Zoico E, Di Francesco V, Mazzali G, et al. High baseline values of fat mass, independently of appendicular skeletal mass, predict 2-year onset of disability in elderly subjects at the high end of the functional spectrum. Aging Clin Exp Res. 2007; 19(2):154–159.