Small-Area Estimation and Prioritizing Communities for Obesity Control in Massachusetts
Bibliographic Data
Objectives. We developed a method to evaluate geographic and temporal variations in community-level obesity prevalence and used that method to identify communities in Massachusetts that should be considered high priority communities for obesity control. Methods. We developed small-area estimation models to estimate community-level obesity prevalence among community-living adults 18 years or older. Individual-level data from the Behavioral Risk Factors Surveillance System from 1999 to 2005 were integrated with community-level data from the 2000 US Census. Small-area estimation models assessed the associations of obesity (body mass index ≥ 30 kg/m 2 ) with individual- and community-level characteristics. A classification system based on level and precision of obesity prevalence estimates was then used to identify high-priority communities. Results. Estimates of the prevalence of community-level obesity ranged from 9% to 38% in 2005 and increased in all communities from 1999 to 2005. Fewer than 7% of communities met the Healthy People 2010 objective of prevalence rates below 15%. The highest prevalence rates occurred in communities characterized by lower income, less education, and more blue-collar workers. Conclusions. Similar to the rest of the nation, Massachusetts faces a great challenge in reaching the national obesity control objective. Targeting high-priority communities identified by small-area estimation may maximize use of limited resources
American Community Survey · Body mass index · Census · Environmental health · Estimation · Geography · Obesity · Population · Public health · Small area estimation · Sociology · Community Health and Development · Demography · Health disparities and outcomes · Medicine · Obesity, Physical Activity, Diet · Gerontology
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| Unique citing works | 14 |
|---|---|
| Citations per year | 0,93 |
| Citation span | 2011 - 2025 (15) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 14 |