BACKGROUND: The WISEWOMAN program focuses on reducing cardiovascular disease (CVD) risk factors by providing screening and lifestyle interventions for many low-income and uninsured women. To provide the most effective interventions possible, it is important to understand the characteristics of WISEWOMAN participants and their communities. METHODS: We used baseline data collected for WISEWOMAN participants from five states (Connecticut, Michigan, Nebraska, North Carolina, and South Dakota) who had enrolled in WISEWOMAN between January 2001 and December 2002 in order to examine body mass index (BMI) and smoking behavior for evidence of spatial clustering. We then examined whether neighborhood characteristics in clusters of high-risk factors differed from neighborhood characteristics in other locations. RESULTS: Six percent of the WISEWOMAN participants lived in ZIP codes with high-BMI clusters, and 4% lived in ZIP codes with high-smoking clusters. High-BMI and high-smoking clusters occurred, however, in different locations from each other. The high-BMI-clustered ZIP codes were, on average, located in more disadvantaged areas. Most of the differences between the high-smoking-clustered ZIP codes and the remaining ZIP codes were not statistically significant. CONCLUSIONS: Our analysis revealed spatial clustering in CVD risk factors among WISE-WOMAN participants. We also found evidence of a correlation between high-BMI clusters and low socioeconomic status of the surrounding community. A more in-depth analysis of the relationship between risk factors (e.g., BMI) and community characteristics in clustered locations will provide further information concerning the role of the community in affecting individual behavior and should allow for tailoring interventions to reduce these risk factors more effectively.
BACKGROUND: The WISEWOMAN program focuses on reducing cardiovascular disease (CVD) risk factors by providing screening and lifestyle interventions for many low-income and uninsured women. To provide the most effective interventions possible, it is important to understand the characteristics of WISEWOMAN participants and their communities. METHODS: We used baseline data collected for WISEWOMAN participants from five states (Connecticut, Michigan, Nebraska, North Carolina, and South Dakota) who had enrolled in WISEWOMAN between January 2001 and December 2002 in order to examine body mass index (BMI) and smoking behavior for evidence of spatial clustering. We then examined whether neighborhood characteristics in clusters of high-risk factors differed from neighborhood characteristics in other locations. RESULTS: Six percent of the WISEWOMAN participants lived in ZIP codes with high-BMI clusters, and 4% lived in ZIP codes with high-smoking clusters. High-BMI and high-smoking clusters occurred, however, in different locations from each other. The high-BMI-clustered ZIP codes were, on average, located in more disadvantaged areas. Most of the differences between the high-smoking-clustered ZIP codes and the remaining ZIP codes were not statistically significant. CONCLUSIONS: Our analysis revealed spatial clustering in CVD risk factors among WISE-WOMANparticipants. We also found evidence of a correlation between high-BMI clusters and low socioeconomic status of the surrounding community. A more in-depth analysis of the relationship between risk factors (e.g., BMI) and community characteristics in clustered locations will provide further information concerning the role of the community in affecting individual behavior and should allow for tailoring interventions to reduce these risk factors more effectively.
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