Data-driven insights into neighborhood adherence to cancer prevention guidelines in Philadelphia

Forty percent of new cancer cases in the United States are attributed to modifiable risks, which can be influenced by the built environment. Recent cancer prevention guidelines include recommendations for making communities conducive to healthy living. Focused on the city of Philadelphia, the present study aims to 1) evaluate neighborhood-level adherence to cancer prevention guidelines by developing two novel indices and 2) identify factors driving low compliance in neighborhoods with high cancer mortality.

Philadelphia neighborhoods were compared to the city overall on ten cancer prevention recommendations. Comparison scores informed two indices: one focused on the American Cancer Society's guidelines for Physical Activity, Nutrition, and Smoking, and the other focused on Healthy People 2030's guidelines for Prevention Services. Indices were mapped by neighborhood and compared to cancer mortality. Where low adherence overlapped with high cancer mortality, the recommendations driving low compliance were identified.

Distinct geospatial patterns were observed in adherence to guidelines, and while drivers of low adherence varied by neighborhood, general trends emerged in different areas of the city. Concerning Physical Activity, Nutrition, and Smoking Guideline adherence, some areas appeared to be more influenced by the built environment, while others were impacted by specific behavioral risk factors such as excessive alcohol consumption. Preventive Service recommendation adherence was driven in some parts by self-reported poor health and, in others, low cancer screening rates and a high physician-to-resident ratio. In neighborhoods where poor guideline adherence overlapped with high cancer mortality, the built environment emerged as a potentially important factor.

This study considers the importance of the built environment in influencing adherence to cancer prevention guidelines. Policymakers and public health officials can use this information to prioritize interventions for neighborhoods with low guideline adherence and high cancer burden and tailor interventions to focus on indicators of low guideline adherence.