The biopsychosocial model of health was created by psychiatrist George Engel, and it is used to demonstrate the multiple factors (biological, psychological, social) that make up one's health outcomes. These factors (apart from genetics) are are not fixed and interact with each other over time, resulting in how an individual's health presents itself.
I will be using the biopsychosocial model of health to explain how multiple factors can affect a population of my interest: pregnant mothers who have gestational diabetes mellitus (GDM).
GDM is hyperglycemia that develops during pregnancy and resolves after delivery. Biological: Genetics play a role in one's risk of developing GDM, and there are certain ethnic groups that are predisposed. Ménard et al. (2020) found that South Asian, East Asian, and Pacific women were more likely to develop GDM than other ethnic groups after adjusting for other variables such as lifestyle factors. Dyck et al. (2020) found that First Nations women in Saskatchewan were more likely to develop GDM than non-First Nations women. Women with increased BMIs, unhealthy diets, and lack of exercise were also found to have an increased risk of GDM. Psychological: As discussed above, a woman's diet and level of exercise plays a large role in her risk of developing GDM. A pregnant women's attitude and beliefs about diet during would greatly impact these lifestyle factors. Also, a woman's mental state, emotions, and coping skills during pregnancy could impact behaviours such as unhealthy eating and binge eating. A woman who feels depressed or has a low mood may also feel reluctant to eat healthy foods or exercise regularly. Social: Social determinants of health such as income, education, and environment can also impact a woman's risk of developing GDM. A study by Rönö et al. (2019) found that a women with higher incomes and higher educational attainment had lower levels of GDM. Kahr et al. (2016) performed a geospatial analysis within a county in Texas, looking at the density of fast food restaurants and convenience stores within each neighbourhood. They found that women who lived in neighbourhoods with a high density of unhealthy food options were more likely to develop GDM than in those with a lower density of unhealthy food options. References: Dyck, R. F., Karunanayake, C., Pahwa, P., Stang, M., & Osgood, N. D. (2020). Epidemiology of diabetes in pregnancy among First Nations and non-First Nations women in Saskatchewan, 1980-2013. Part 2: Predictors and early complications; results from the DIP:ORRIIGENSS project. Canadian Journal of Diabetes, 44, 605-614. Lehman, B. J., David, D. M., & Gruber, J. A. Rethinking the biopsychosocial model of health: Understanding health as a dynamic system. Social and Personality Psychology Compass, 11(8). McIntyre, H. D., Catalano, P., Zhang, C., Desoye, G., Mathieson, E. R., & Damm, P. (2019).
Gestational diabetes mellitus. Nature Reviews, 5(47).
Ménard, V., Sotunde, O. F., & Weiler, H. A. (2020). Ethnicity and immigration status as risk
factors for gestational diabetes mellitus, anemia and pregnancy outcomes among food
insecure women attending the Montreal Diet Dispensary Program. Canadian Journal of
Diabetes, 44, 139-145. Rönö, K., Masalin, S., Kautiainen, H., Gissler, M., Raina, M., Eriksson, J. G., Laine, M. K.
(2019). Impact of maternal income on the risk of gestational diabetes mellitus in primiparous women. Diabetic Medicine, 36(2), 214-220.
Comments