Self-Reported and Diagnosed Depression in Rural Colorado: Findings from the San Luis Valley Community Health Survey.

PURPOSE: To gain a better understanding of depression in a rural community, survey results were used to compare differences in self-reported depressive symptoms and medical professional diagnosed depression among demographic groups. METHODS: A chi-square test of independence was performed to examine relationships among the depression-related variables. Logistic regression analyses were also performed to ascertain the effects of demographic characteristics and social support on depression. FINDINGS: A statistically significant association was found between the two depression-related variables (X2=145.17, P <.001). Income was significantly associated with both depression-related variables. Hispanic ethnicity, higher income, and some high school education were associated with decreased odds of self-reported medically diagnosed depression. Those reporting no or some social support had increased odds of both depression-related variables compared with those who reported always having social support. CONCLUSIONS: These findings provide a better understanding of depression in a rural community and may inform future public health interventions.

A Community-Engaged Approach to Collecting Rural Health Surveillance Data.

PURPOSE: In order for communities to make health-related, data-driven decisions concerning resource allocation, needed services, and intervention priorities, they need an accurate picture of the health status of residents. While state and national health surveillance systems exist to help local communities make data-driven health decisions, rural communities face unique challenges including: (1) limited county-level data; (2) underrepresented segments of the population; and (3) a lack of survey items to address local health concerns. The purpose of this study was to take a community-engaged approach to collecting population-based health status data in a rural area in an effort to address some of these unique challenges. METHODS: Using a community-based participatory research (CBPR) approach, over 1,500 residents from 6 rural and frontier counties were randomly selected with a stratified, multistage cluster study design. Surveys were primarily completed over the phone. FINDINGS: Response rates by county ranged from 59% to 80% (overall = 66%). Males and younger adults (18-24 year olds) were underrepresented in the sample, but Hispanics, low-income residents, and cell phone-only users were adequately represented. Prevalence rates for chronic disease and health behavior varied by county. CONCLUSIONS: The implications of this project are that engaging stakeholders in community surveillance efforts increases the quality, relevance and utility of the information collected and can help reach otherwise difficult-to-reach populations. This can result in a more accurate picture of the health status of residents, which can lead to making health-related, data-driven decisions concerning resource allocation, needed services, and intervention priorities.