Challenges and lessons learned in developing a community-based health survey.

BACKGROUND: Collecting community-level data to inform health interventions and monitor health status is critical to improving community health and eliminating health disparities. Ideally, the process for designing and utilizing these data collection tools will include representation from community, service, and academic institutions. The process for incorporating these entities' diverse needs and perspectives, however, can be challenging. OBJECTIVES: This paper describes how a community-academic partnership designed a survey in 2003 and 2005 to examine factors influencing the health of residents in an urban city and surrounding county area. METHODS: The partnership used community-based public health research principles to guide the development of the telephone surveys. LESSONS LEARNED: Through these two survey development processes, we learned three key lessons: To regularly examine our partnership and process; to communicate directly with and obtain the support of each individual partner; and to focus on building the capacity of the partners and partnership.

Using GIS to facilitate community-based public health planning of diabetes intervention efforts.

Data from a community survey were analyzed geographically to help facilitate local diabetes prevention efforts. Data were available from the Speak to Your Health! Community Survey, designed and implemented by The Prevention Research Center of Michigan (PRC/MI), whose central mission is to strengthen community capacity to improve health. This survey was developed collaboratively by the university and community partners that comprise the PRC/MI and focuses on health and social issues at the heart of the community of Genesee County, Michigan. Survey data were used to calculate and geographically map diabetes-risk scores and mapped diabetes-screening rates. These maps indicated that those areas where the estimated risk of diabetes was the highest had only moderate rates of diabetes screening relative to other areas. It is hoped that these results will reach those involved in local diabetes-intervention programs with the intent that the data will be used in planning local prevention and intervention efforts.