Name
Chamberlain University
NR-717: Concepts in Population Health Outcomes & Health Policy
Prof. Name
Datea
The chosen practice problem for this week is obesity among non-Hispanic Black African Americans living in Prince George’s County, Maryland. This public health concern requires a multifaceted strategy that combines epidemiological principles, targeted health surveillance, and ethical practices in data utilization. Both national and county-level data illustrate that obesity disproportionately affects this group, with the burden shaped by social determinants such as income, education, cultural norms, and access to resources.
Epidemiology plays a critical role in identifying risk groups, examining potential causes, and guiding interventions (CDC, 2022). Meanwhile, health surveillance enables ongoing monitoring of trends, resource distribution, and the development of equitable health policies. Embedding ethical standards into surveillance ensures transparency, strengthens trust, and reduces disparities in health outcomes (Maryland Department of Health and Mental Hygiene, 2022).
The Maryland Department of Health and Mental Hygiene (2022) defines overweight and obesity using BMI classifications as follows:
| Category | Definition |
|---|---|
| Overweight (Adults) | BMI 25.0–29.9 |
| Obese (Adults) | BMI ≥ 30.0 |
| Overweight (Children/Adolescents) | BMI ≥ 85th percentile for age/height |
| Obese (Children/Adolescents) | BMI ≥ 95th percentile for age/height |
Obesity poses severe health risks, including increased chances of developing type 2 diabetes, hypertension, cardiovascular disease, arthritis, certain cancers, and early mortality (Miller et al., 2022).
National Level:
At the U.S. level, obesity prevalence differs significantly by race and ethnicity. The CDC (2022) reports that:
Non-Hispanic Blacks have the highest prevalence (46.8%).
Non-Hispanic Whites follow at 37.9%.
Non-Hispanic Asians show the lowest prevalence (12.7%).
This disparity underscores how systemic inequalities contribute to obesity across the nation.
Local Level – Prince George’s County (PGC):
Prince George’s County, with its large African American population, shows even more concerning trends:
In 2015, 30.7% of adults and 15.1% of adolescents were obese.
By 2021, the obesity prevalence among Black African American adults rose to 43.8%, exceeding both Maryland (34.1%) and national averages (33.9%).
| Population Group | Obesity Prevalence (%) | Source |
|---|---|---|
| U.S. Adults (Overall) | 33.9 | HHS, 2020 |
| Maryland Adults | 34.1 | HHS, 2020 |
| Prince George’s County Adults | 43.8 | HHS, 2020 |
| Black African Americans (PGC) | 77.3 | CDC, 2022 |
| Black Women (PGC) | 75.5 | CDC, 2022 |
| White Women (PGC) | 61.8 | CDC, 2022 |
Descriptive epidemiology focuses on person, place, and time trends:
By Person: Black women in PGC exhibit a disproportionately higher prevalence of obesity (75.5%) than White women (61.8%).
By Place: Food deserts and unsafe neighborhoods contribute to poor dietary choices and limited opportunities for physical activity.
By Time: Obesity prevalence has steadily increased over the last 20 years (CDC, 2024).
This translates into higher mortality, with African Americans in Maryland experiencing a 19% higher all-cause mortality rate compared with Whites (Maryland Department of Health and Mental Hygiene, 2022).
Analytic epidemiology investigates the determinants and causal factors of obesity in PGC:
Socioeconomic status (SES): Limited income reduces the ability to purchase healthier food and engage in recreational activities (Barrington et al., 2021).
Environmental influences: A high density of fast-food restaurants and a lack of grocery stores drive unhealthy eating (Bleich et al., 2021).
Healthcare barriers: Racial bias, limited access to preventive services, and a lack of culturally competent care hinder effective obesity management (Hui et al., 2020).
Surveillance can be a powerful tool to reduce disparities and guide targeted interventions in PGC:
Trend Monitoring: Tracking changes in obesity prevalence can highlight the effectiveness of policies and programs.
Resource Allocation: Identifying high-risk communities allows for better distribution of resources such as nutrition programs and fitness facilities.
Policy Development: Data can support legislation promoting urban redesign, food subsidies, and school-based health education.
Technology Integration: Digital health platforms can help clinicians and communities monitor obesity trends in real-time.
Ethical concerns are central when using surveillance data for obesity management:
| Ethical Concern | Description |
|---|---|
| Confidentiality & Privacy | Protecting individual health information from misuse. |
| Bias & Stigma | Avoiding weight-based discrimination and culturally insensitive narratives. |
| Equity in Access | Ensuring fair availability of health services across socioeconomic groups. |
| Systemic Racism | Recognizing and addressing structural racism that influences obesity disparities. |
| Informed Consent | Respecting patient rights during health data collection. |
Culturally competent care, equitable policies, and inclusive messaging are essential for preventing further stigmatization and ensuring trust in public health systems (Payne-Sturges et al., 2021).
Addressing obesity among African Americans in Prince George’s County requires an integrated approach that leverages descriptive and analytic epidemiology, robust health surveillance, and ethical data practices. Surveillance systems not only identify trends but also empower policymakers and healthcare providers to implement targeted, culturally competent interventions. By ensuring equity, transparency, and community engagement, these efforts can reduce health disparities, promote trust, and improve long-term population health outcomes.
Barrington, D. S., James, S. A., & Williams, D. R. (2021). Socioeconomic correlates of obesity in African American and Caribbean-Black men and women. Journal of Racial and Ethnic Health Disparities, 8(2), 422–432. https://doi.org/10.1007/s40615-020-00798-4
Bleich, S. N., & Ard, J. D. (2021). COVID-19, obesity, and structural racism: Understanding the past and identifying solutions for the future. Cell Metabolism, 33(2), 234–241. https://doi.org/10.1016/j.cmet.2021.01.010
Centers for Disease Control and Prevention. (2022). Obesity prevalence in the U.S. https://www.cdc.gov
Centers for Disease Control and Prevention. (2024). Trends in obesity-related health outcomes. https://www.cdc.gov
Fryar, C. D., Carroll, M. D., & Afful, J. (2021). Prevalence of overweight, obesity, and severe obesity among adults: United States, 1960–2018. National Center for Health Statistics. https://www.cdc.gov/nchs
Hui, B. Y., Roberts, A., & Thompson, K. J. (2020). Outcomes of bariatric surgery in African Americans: An analysis of MBSAQIP registry data. Obesity Surgery, 30(12), 4275–4285. https://doi.org/10.1007/s11695-020-04820-w
Lofton, H., Ard, J. D., Hunt, R. R., & Knight, M. G. (2023). Obesity among African Americans: A review. Obesity, 31(2), 306–315. https://doi.org/10.1002/oby.23640
Longmire-Avital, B., & McQueen, C. (2019). Exploring race-related stress and emotional eating among Black women. Women & Health, 59(3), 240–251. https://doi.org/10.1080/03630242.2018.1478361
Maryland Department of Health and Mental Hygiene. (2022). Obesity in Maryland and Prince George’s County. https://www.princegeorgescountymd.gov
Miller, H. N., Perrin, N., Thorpe, R. J., Evans, M. K., Zonderman, A. B., & Allen, J. (2022). Discrimination and BMI trajectories: A prospective study of African American adults. Family & Community Health, 45(3), 206–213. https://doi.org/10.1097/FCH.0000000000000326
Payne-Sturges, D. C., Gee, G. C., & Cory-Slechta, D. A. (2021). Confronting racism in environmental health sciences. Environmental Health Perspectives, 129(5), 055002. https://doi.org/10.1289/EHP8186
U.S. Department of Health and Human Services, Office of Minority Health. (2020). Minority health framework for eliminating disparities. https://minorityhealth.hhs.gov
