ASSESSING THE IMPACT OF SOCIO-DEMOGRAPHIC AND LIFESTYLE FACTORS ON COMMUNITY HEALTH OUTCOMES: AN EVIDENCE-BASED ANALYSIS FOR PUBLIC HEALTH AND SOCIAL CARE INTERVENTIONS
DOI:
https://doi.org/10.69980/ysjzsd32Keywords:
Community Health, Healthcare Utilization, Lifestyle FactorsAbstract
Understanding the determinants of community health outcomes is essential in the context of rising chronic disease burden and increasing pressure on healthcare systems. While socio-demographic and lifestyle factors are widely recognized as key influences on health, their direct relationship with healthcare utilization remains insufficiently understood. This study addresses this gap by examining the impact of socio-demographic and lifestyle-related factors on healthcare visits using a structured community health dataset comprising 1,000 observations. The objective is to assess the relative contribution of age and body mass index (BMI) to variations in healthcare utilization. The analysis employs exploratory data analysis, correlation assessment, and multiple linear regression modeling to evaluate associations and predictive effects. The results indicate that age is a statistically significant and dominant predictor of healthcare utilization, demonstrating a strong positive relationship with the number of visits, whereas BMI does not exhibit a significant effect. These findings suggest a disconnect between lifestyle-related health risk and actual engagement with healthcare services. The study highlights the importance of distinguishing between determinants of health risk and healthcare demand, emphasizing the need for age-responsive healthcare planning and strengthened preventive strategies. The findings contribute to improving evidence-based public health interventions and resource allocation in community health systems.
References
1. Arija, V., Villalobos, F., Pedret, R., Vinuesa, A., Timón, M., Basora, T., … Pas-a-Pas Research Group. (2017). Effectiveness of a physical activity program on cardiovascular disease risk in adult primary health-care users: The “Pas-a-Pas” community intervention trial. BMC Public Health, 17(1), 576.
2. Armoon, B., Higgs, P., Fleury, M. J., Bayat, A. H., Moghaddam, L. F., Bayani, A., & Fakhri, Y. (2021). Socio-demographic, clinical and service use determinants associated with HIV-related stigma among people living with HIV/AIDS: A systematic review and meta-analysis. BMC Health Services Research, 21(1), 1004.
3. Baldisserotto, J., Kopittke, L., Nedel, F. B., Takeda, S. P., Mendonça, C. S., Sirena, S. A., … Nicolau, B. (2016). Socio-demographic characteristics and prevalence of risk factors in a hypertensive and diabetic population: A cross-sectional study in primary health care in Brazil. BMC Public Health, 16(1), 573.
4. Chowdhury, M. R. K., Rahman, M. S., Billah, B., Kabir, R., Perera, N. K., & Kader, M. (2022). The prevalence and socio-demographic risk factors of coexistence of stunting, wasting, and underweight among children under five years in Bangladesh: A cross-sectional study. BMC Nutrition, 8(1), 84.
5. Dey, S., Mukherjee, A., Pati, M. K., Kar, A., Ramanaik, S., Pujar, A., … N, S. (2022). Socio-demographic, behavioural and clinical factors influencing control of diabetes and hypertension in urban Mysore, South India: A mixed-method study conducted in 2018. Archives of Public Health, 80(1), 234.
6. Gate, L., Warren-Gash, C., Clarke, A., Bartley, A., Fowler, E., Semple, G., … Rodger, A. (2016). Promoting lifestyle behaviour change and well-being in hospital patients: A pilot study of an evidence-based psychological intervention. Journal of Public Health, 38(3), e292–e300.
7. Gelaw, Y. A., Koye, D. N., Alene, K. A., Ahmed, K. Y., Assefa, Y., Erku, D. A., … Melaku, Y. A. (2023). Socio-demographic correlates of unhealthy lifestyle in Ethiopia: A secondary analysis of a national survey. BMC Public Health, 23(1), 1528.
8. Kolokotroni, O., Mosquera, M. C., Quattrocchi, A., Heraclides, A., Demetriou, C., & Philippou, E. (2021). Lifestyle habits of adults during the COVID-19 pandemic lockdown in Cyprus: Evidence from a cross-sectional study. BMC Public Health, 21(1), 786.
9. Lu, C. H., Tang, S. T., Lei, Y. X., Zhang, M. Q., Lin, W. Q., Ding, S. H., & Wang, P. X. (2015). Community-based interventions in hypertensive patients: A comparison of three health education strategies. BMC Public Health, 15(1), 33.
10. Murray, F., Allen, M., Clark, C. M., Daly, C. J., & Jacobs, D. M. (2021). Socio-demographic and economic factors associated with 30-day readmission for conditions targeted by the hospital readmissions reduction program: A population-based study. BMC Public Health, 21(1), 1922.
11. Nienaber-Rousseau, C., Sotunde, O. F., Ukegbu, P. O., Myburgh, P. H., Wright, H. H., Havemann-Nel, L., … Kruger, H. S. (2017). Socio-demographic and lifestyle factors predict 5-year changes in adiposity among a group of black South African adults. International Journal of Environmental Research and Public Health, 14(9), 1089.
12. Osok, J., Kigamwa, P., van der Stoep, A., Huang, K. Y., & Kumar, M. (2018). Depression and its psychosocial risk factors in pregnant Kenyan adolescents: A cross-sectional study in a community health centre of Nairobi. BMC Psychiatry, 18(1), 136.
13. Sarkar, C., Webster, C., & Gallacher, J. (2015). UK Biobank Urban Morphometric Platform (UKBUMP): A nationwide resource for evidence-based healthy city planning and public health interventions. Annals of GIS, 21(2), 135–148.
14. Shidhaye, R., Gangale, S., & Patel, V. (2016). Prevalence and treatment coverage for depression: A population-based survey in Vidarbha, India. Social Psychiatry and Psychiatric Epidemiology, 51(7), 993–1003.
15. WhimsicalMuffin. (2024). Community health information dataset. Kaggle. https://www.kaggle.com/datasets/whimsicalmuffin/community-health-information-dataset
16. Xu, F., & Brodszky, V. (2024). The impact of COVID-19 on health-related quality of life: A systematic review and evidence-based recommendations. Discover Psychology, 4(1), 90.
17. Yadav, U. N., Thapa, T. B., Mistry, S. K., Pokhrel, R., & Harris, M. F. (2020). Socio-demographic characteristics, lifestyle factors, multi-morbid conditions and depressive symptoms among Nepalese older adults. BMC Psychiatry, 20(1), 261.
18. Zejnullahu, V. A., Ukella-Lleshi, D., Miftari, E., & Govori, V. (2021). Prevalence of postpartum depression at the clinic for obstetrics and gynecology in Kosovo teaching hospital: Demographic, obstetric and psychosocial risk factors. European Journal of Obstetrics & Gynecology and Reproductive Biology, 256, 215–220.
