Dietary Intake, Lifestyle Factors, and Metabolic Risk: Insights from Health Check-Ups at a Private Healthcare Facility in Coimbatore, India
Asupan Makanan, Faktor Gaya Hidup, dan Risiko Metabolik: Wawasan dari Pemeriksaan Kesehatan di Fasilitas Kesehatan Swasta di Coimbatore, India
Downloads
Background: Over the last decade (2014–2024), the global prevalence of metabolic risk factors such as dyslipidemia (5-8%), hypertension (5-10%), obesity (10-15%) and elevated blood glucose levels (10-15%) has been steadily increasing.
Objectives: To determine the correlation among the dietary consumption, lifestyle factors, and metabolic risk factors among the respondent of age 18-65 years.
Methods: The respondent (n=419) were enrolled from August 2023 to February 2024 in Coimbatore, India. The sociodemographic characteristics, dietary intake, stress levels, and physical activity were measured using questionnaires. The respondent’s anthropometry, HbA1c level, blood pressure, and liver function tests were examined, and those with abnormal liver enzymes underwent abdominal ultrasonography for fatty liver diagnosis. The descriptive, Chi square and Kendall’s tau correlation coefficient were performed for statistical analysis.
Results: This research showed a weak correlation among protein intake of the respondent and obesity (r=0.084 and p-value=0.026). A significant association was observed among blood pressure range and the consumption of fat (r=0.079, p-value=0.039), protein (r=0.158, p-value<0.001). Correspondingly, the intake of nutrient such as energy (r=0.102, p-value<0.001), carbohydrate (r=0.089, p-value<0.001), and fat (r=0.156, p-value<0.001) was positively correlated with an increased hyperglycaemic risk. Further, energy (r=0.202, p-value<0.001), carbohydrate (r=0.146, p-value<0.001) consumption level had positive correlation with fatty liver disease.
Conclusions: A significant positive correlation as observed between and metabolic risk factors and dietary intake. Modifying the interventions to target these risk factors may aid lower the risk of hypertension, obesity, hyperglycaemia, and fatty liver disease in diverse inhabitants.
Swarup, S., Ahmed, I., Grigorova, Y. et al. Metabolic syndrome. In: StatPearls [Internet]. StatPearls Publishing; 2024. Available from: https://www.ncbi.nlm.nih.gov/books/NBK459248/ (accessed 7 March 2024).
Saxena, V. Rising trends of overweight and obesity among women in India. Healthline J. Indian Assoc. Prev. Soc. Med. 13, 390 (2022). https://doi.org/10.51957/healthline_390_2022
Mohammad, R., Dhananjay, W. & Bansod, H. Hypertension in India: A gender-based research of prevalence and associated risk factors. Preprint at https://doi.org/10.21203/rs.3.rs-4303137/v1 (2024).
Agrawal, A. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res. Clin. Pract. 186, 109119 (2022). https://doi.org/10.1016/j.diabres.2021.109119
Riazi, K., Azhari, H., Charette, J.H. et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol. Hepatol. 7, 851–861 (2022). https://doi.org/10.1016/S2468-1253 (22)00165-0
Teng, M.L., Ng, C.H., Huang, D.Q. et al. Global incidence and prevalence of non-alcoholic fatty liver disease. Clin. Mol. Hepatol. 29 (Suppl), S32–S42 (2023). https://doi.org/10.3350/cmh.2022.0365
Varghese, J.S., Mohammed, K. & Ali, M.K. Abstract 13817: Diabetes prevalence, screening, diagnosis, treatment and control in India: A cross-sectional research of individuals aged 18 years and older. Circulation 146 (Suppl 1), A13817 (2022). https://doi.org/10.1161/circ.146.suppl_1.13817
Anjana, R.M., Unnikrishnan, R., Deepa, M. et al. Metabolic non-communicable disease health report of India: The ICMR-INDIAB national cross-sectional research (ICMR-INDIAB-17). Lancet Diabetes Endocrinol. 11, 474–489 (2023). https://doi.org/10.1016/S2213-8587 (23)00119-5
Elhence, A.S., Bansal, B., Gupta, H. et al. Prevalence of non-alcoholic fatty liver disease in India: A systematic review and meta-analysis. J. Clin. Exp. Hepatol. 12, 818–829 (2022).
Liss, D.T., Uchida, T., Wilkes, C.L. et al. General health checks in adult primary care: A review. JAMA 325, 2294–2306 (2021). https://doi.org/10.1001/jama.2021.6524
Olatona, F.A., Onabanjo, O.O., Ugbaja, R.N. et al. Dietary habits and metabolic risk factors for non-communicable diseases in a university undergraduate population. J. Health Popul. Nutr. 37, 21 (2018). https://doi.org/10.1186/s41043-018-0152-2
Reinhardt, S.L., Boehm, R., Blackstone, N.T. et al. Systematic review of dietary patterns and sustainability in the United States. Adv. Nutr. 11, 1016–1031 (2020). https://doi.org/10.1093/advances/nmaa026
Gutiérrez-Pliego, L.E., Camarillo-Romero, E., Montenegro-Morales, L.P. et al. Dietary patterns associated with BMI and lifestyle in Mexican adolescents. BMC Public Health 16, 850 (2016). https://doi.org/10.1186/s12889-016-3527-6
Cordain, L., Eaton, S.B., Sebastian, A. et al. Origins and evolution of the Western diet: Health implications for the 21st century. Am. J. Clin. Nutr. 81, 341–354 (2005). https://doi.org/10.1093/ajcn.81.2.341
Imamura, M., Sasaki, H., Shinto, T. et al. Association between Na, K, and lipid intake in each meal and blood pressure. Front. Nutr. 9, 853118 (2022). https://doi.org/10.3389/fnut.2022.853118
Sanz-Valero, J., Banerjee, P.G., Reddy, B., Panda, H.K., Kumar, T.S., Reddy, J., & SubbaRao, M.G. Diets, lifestyles and metabolic risk factors among corporate information technology (IT) employees in South India. Nutrients 15, 3404 (2023). https://doi.org/10.3390/nu15153404
Charan, J., Kaur, R., Bhardwaj, P., Singh, K., Ambwani, S. & Misra, S. Respondent size calculation in medical research: A primer. Ann. Natl. Acad. Med. Sci. India 57, 74–80 (2021).
Topolski, T.D., LoGerfo, J., Patrick, D.L., Williams, B., Walwick, J. & Patrick, M.B. The Rapid Assessment of Physical Activity (RAPA) among older adults. Prev. Chronic Dis. 3, A118 (2006).
Cohen, S., Kamarck, T. & Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 24, 386–396 (1983).
Taufik, M. A. et al. Reducing Perceived Stress of Family Caregivers of Older Adult: The Role of Caregiving Self- Efficacy and Social Support. International Journal of Academic Research in Business and Social Sciences 13, (2023).
Zhang, K. et al. Metabolic diseases and healthy aging: Identifying environmental and behavioral risk factors and promoting public health. Front. Public Health 11, 1253506 (2023). https://doi.org/10.3389/fpubh.2023.1253506
Hu, J., Du, Y., Zhou, Y. & Wang, H. High sensitivity troponins and mortality in the population with metabolic dysfunction-associated steatotic liver disease. Sci. Rep. 14, 19541 (2024).
Nayak, D., Mayappanavar, R. & Sonavane, R. Assessment of risk factor profile of non-communicable diseases among bank employees in the Gadag district. Int. J. Community Med. Public Health 10, 2160–2164 (2023). https://doi.org/10.18203/2394-6040.ijcmph20231697 (Accessed: 9 September 2024).
Gupta, S., Ramtej, K.S.J., & Verma, J. Prevalence of alcoholic and non-alcoholic fatty liver disease among different occupations and associated metabolic changes: A hospital-based research. J. Med. Pharm. Allied Sci. 11, 2338 (2022). https://doi.org/10.55522/jmpas.v11i2.2338
Zhang, F. et al. Smoking and risk of non-alcoholic fatty liver disease: A meta-analysis of observational studies. Liver Int. 40, 1350–1360 (2020). https://doi.org/10.1111/liv.14411
Knop, J.A., Vølund, K., O’Donnell, M.M. et al. Chronic alcohol consumption and its effects on glucose metabolism: A review. Alcohol. Clin. Exp. Res. 42, 119–129 (2018). https://doi.org/10.1111/acer.13516
Reuter, A.M., Lee, S.E. & Roberts, J.T. Associations of meat consumption with risk of non-alcoholic fatty liver disease and type 2 diabetes. Am. J. Clin. Nutr. 111, 662–671 (2020). https://doi.org/10.1093/ajcn/nqz287
Arini, H.R.B., Leech, R.M., Tan, S-Y. & McNaughton, S.A. Association between protein intake, diet quality, and obesity in Australian adults: A comparison of measurement units. Proc. Nutr. Soc. (2024). https://doi.org/10.1017/s0029665124001290
Pezeshki, A., Zapata, R.C., Singh, A., Yee, N.J., & Chelikani, P.K. Low protein diets produce divergent effects on energy balance. Sci. Rep. 6, 25145 (2016). https://doi.org/10.1038/srep25145
Zhou, C., Wu, Q., Ye, Z. et al. Inverse association between variety of proteins with appropriate quantity from different food sources and new-onset hypertension. Arter. Gipertenz. (2022). https://doi.org/10.1161/HYPERTENSIONAHA.121.18222
Coelho-Júnior, H.J. et al. High protein intake at lunch is negatively associated with blood pressure in community-dwelling older adults: A cross-sectional research. Nutrients 15, 1251 (2023). https://doi.org/10.3390/nu15051251
Furukawa, T. et al. Effect of the interaction between physical activity and estimated macronutrient intake on HbA1c: Population-based cross-sectional and longitudinal studies. BMJ Open Diabetes Res. Care 10, e002479 (2022). https://doi.org/10.1136/bmjdrc-2021-002479
Batten, T. Systematic review and meta-analysis: The role of diet in the development of nonalcoholic fatty liver disease. Clin. Gastroenterol. Hepatol. 21, 1–20 (2023). https://doi.org/10.1016/j.cgh.2021.11.026
Szilagyi, A. Is increased caloric intake a feature of NAFLD regardless of the presence of obesity? Clin. Gastroenterol. Hepatol. (2023). https://doi.org/10.1016/j.cgh.2023.08.032
Hamberger, U. Physical activity and obesity: Underlying mechanisms and practical actions. (2024). https://doi.org/10.23785/tu.2024.03.003
Amirudin, I. Physical activity and blood glucose levels in diabetes mellitus patients. J. Bina Sehat 7, 483 (2023). https://doi.org/10.29082/ijnms/2023/vol7/iss2/483
Asonye, C.C. Diabetes distress: The untold hidden struggle of living with diabetes mellitus. Afr. J. Health Nurs. Midwifery 7, (2023). https://doi.org/10.52589/ajhnm-98vrwpip
Halim, R. et al. Stress is the dominant factor of hypertension. East Asian J. Multidiscip. Res. 1, 1612 (2022). https://doi.org/10.55927/eajmr.v1i9.1612
Firanggi, Z.A. et al. Correlation between socio-economic factors and stress with hypertension cases during the COVID-19 pandemic. Poltekita: J. Ilmu Kesehatan 16, (2023). https://doi.org/10.33860/jik.v16i4.1626
Kang, D. et al. Perceived stress and non-alcoholic fatty liver disease in apparently healthy men and women. Sci. Rep. 10, 57036 (2020). https://doi.org/10.1038/S41598-019-57036-Z
Manish, V., Madhulika, T. & Brijesh, K. S. Dietary determinants of metabolic syndrome: Focus on obesity and metabolic dysfunction-associated steatotic liver disease (MASLD). IntechOpen (2024). https://doi.org/10.5772/intechopen.114832
Beeke, P., Vahlhaus, J. & Pivovarova-Ramich, O. Meal timing and its role in obesity and associated diseases. Front. Endocrinol. (2024). https://doi.org/10.3389/fendo.2024.1359772
Copyright (c) 2024 Amerta Nutrition
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
AMERTA NUTR by Unair is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
1. The journal allows the author to hold the copyright of the article without restrictions.
2. The journal allows the author(s) to retain publishing rights without restrictions
3. The legal formal aspect of journal publication accessibility refers to Creative Commons Attribution Share-Alike (CC BY-SA).
4. The Creative Commons Attribution Share-Alike (CC BY-SA) license allows re-distribution and re-use of a licensed work on the conditions that the creator is appropriately credited and that any derivative work is made available under "the same, similar or a compatible license”. Other than the conditions mentioned above, the editorial board is not responsible for copyright violation.
