Abstract
Introduction: The RURAL cohort study addresses critical knowledge gaps regarding heart and lung disorders in rural Southeastern USA. Using CDC mortality data, RURAL selected ten counties from four states (Alabama, Mississippi, Louisiana, and Kentucky) that are ecologically paired for their five-year low and high CVD mortality rates. RURAL will recruit a representative sample of 4600 participants using addressed-based sampling and an intensive community engagement, yet representative sampling from rural areas is challenging. Hypothesis: Address-based sampling using dedicated mailings and telephone calls will yield representative samples from the ten target counties. Methods: A dynamic sampling strategy was implemented to obtain balanced response rates for sex, age groups and race. An initial wave of random addresses was used to estimate response rates. A second wave with Bernoulli probabilities was used to reduce overrepresented subgroups. Finally, a third wave with requests for referrals (network sampling) will be used to increase underrepresented subgroups. Eligible participants collected from households and referrals are rostered, complete a baseline exam, undergo an mHealth assessment and are scheduled for a medical examination in a mobile examination unit (MEU). Results: Sampling of 693 participants from 19,460 inhabitants in age range 25 to 64 years started in Dallas County, Alabama. Address sizes, rostered participants and sample size imbalances are listed in the Table. Bernoulli probabilities [55-64 men: 80%; 55-65 women: 55%; 45-55 women:76%] corrected the imbalance in response rates for sex and age groups 45-54 and 55-64 (see Table). Referrals in wave 2 will further balance the sample. Conclusion: Our initial sampling experiences in rural Alabama showed lower than expected response rates and imbalances across subgroups. These results emphasize the importance of network sampling with well-adjusted Bernoulli probabilities for representative sampling in rural areas.
Published Version
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