A community health task force is preparing to launch a campaign promoting obesity awareness and education in the area. The task force studies epidemiologic data from the county health department, which show that the prevalence of obesity is 3 times higher in a cluster of 5 specific ZIP codes compared to the county average. The task force leader approaches a reputed physician working at a local university to ask for assistance in understanding this pattern. Which of the following should be performed first to understand the etiology of the disparity in obesity prevalence?

Question

A community health task force is preparing to launch a campaign promoting obesity awareness and education in the area.  The task force studies epidemiologic data from the county health department, which show that the prevalence of obesity is 3 times higher in a cluster of 5 specific ZIP codes compared to the county average.  The task force leader approaches a reputed physician working at a local university to ask for assistance in understanding this pattern.  Which of the following should be performed first to understand the etiology of the disparity in obesity prevalence?

Quizplus · Accepted Answer

11ec160b_3734_2c2c_9249_cbee17d666d9_MD0001_00 Obesity is a multifactorial condition with genetic, environmental, and behavioral causes. In this community, obesity prevalence is significantly higher in specific ZIP codes, indicating a possible health disparity (ie, preventable health differences associated with social, environmental, or economic disadvantage). Obesity-related health disparities represent a major public health concern with increased prevalence, severity, and complications affecting vulnerable communities. Such disparities involve factors relating to health care (eg, provider screening and treatment, access to care), patients (eg, diet and activity, health knowledge), and neighborhood (eg, density of grocery stores, which influences dietary patterns; crime rate, which influences physical activity). Given the multifactorial nature of obesity and related disparities, the first step in researching this community's trend is to generate hypotheses. This is best achieved through cross-sectional analysis of demographic and behavioral data, which is relatively easy to perform and can depict multiple risk factors at one point in time (a "snapshot") to: reveal differences in distribution (prevalence) of demographic factors (eg, poverty, ethnicity, insurance status) across ZIP codes. identify variables correlated (associated) with obesity risk (eg, poverty is more prevalent in high-obesity ZIP codes). generate hypotheses (eg, poverty increases obesity risk by decreasing ability to consume foods promoting optimal weight). Other study designs are more appropriate for testing or refining hypotheses following broader cross-sectional analysis. (Choices B and D) Like cross-sectional analysis, cohort studies and qualitative surveys offer observational data for generating hypotheses. However, each of these approaches focuses on a single, patient-related hypothesis (eg, leptin, patient knowledge and attitudes) for obesity differences. Cross-sectional analysis involving this community's demographic factors is a better first step, as it can analyze multiple potential influences and tailor hypotheses to this setting. (Choice C) Quality improvement studies analyze and test clinical processes (eg, providing obesity screening) affecting health care quality. They are less useful for generating broad hypotheses for community epidemiological patterns (eg, obesity trends). (Choice E) Randomized controlled trials are more appropriate for testing (rather than generating) hypotheses; such trials would be premature at this stage. Moreover, this approach tests only health care factors whereas cross-sectional analysis can assess how other risk factors correlate to obesity risk in this community. Educational objective: Obesity-related health disparities affect vulnerable populations (eg, lower socioeconomic status) and arise from patient, health care, and community-related factors. Cross-sectional analysis can identify specific risk factors (eg, insurance status, health behaviors) correlated to obesity in different settings, helping to generate hypotheses for further research. __________ References: The social determinants of chronic disease. (http://www.ncbi.nlm.nih.gov/pubmed/27989293) Mind the gap: Race/ethnic and socioeconomic disparities in obesity. (http://www.ncbi.nlm.nih.gov/pubmed/26377742)

A Community Health Task Force Is Preparing to Launch a Campaign