![]() This method targets the whole population of interest and often results in minority under-representation. Simple random sampling can also pose a problem for studies conducting research in minority populations. convenience sampling) have no known inclusion probabilities, producing bias and unbalanced sample representation. random sampling) requires a defined population, where each possible unit has a known possibility of being selected. Sampling for cross-sectional survey studies can be probability based or non-probability based. Here we describe the use of a novel GIS-based population based sampling approach to minimize selection bias in a community based study. In order to conduct community level surveys to collect this type of data, it is crucial to ensure representativeness of both Hispanic and non-Hispanic populations in the study sample. To date, most studies among Hispanics have focused on individual risk factors of obesity, with less attention on interpersonal, community and environmental determinants. Among adults living in the United States in 2015, the prevalence of obesity was 47% among Hispanics compared to 38% among non-Hispanic whites, highlighting the need to examine factors that contribute to this increased risk. Hispanics are the largest and fastest growing racial/ethnic minority group in the United States, comprising 17.3% of the population in 2014, with disproportionately high obesity rates. Obesity is a leading risk factor for the development of diabetes, cardiovascular illness, cancer and other chronic conditions that cause significant morbidity and mortality as well as increased health care costs. ![]() The integration of area based randomized sampling using tools such as GIS in future community-based research should be considered, particularly when trying to reach disparate populations. Utilizing a standardized area based randomized sampling approach allowed us to successfully recruit an ethnically balanced sample while conducting door to door surveys in a rural, community based study. The proportion of Hispanic surveys completed per strata matched our proposed distribution: 7% for strata 1, 30% for strata 2, 58% for strata 3 and 83% for strata 4. ![]() The final sample included 106 Hispanic and 111 non-Hispanic participants. The proposed sample included 109 Hispanic and 107 non-Hispanic participants to be recruited from 44 Census blocks. To ensure a balanced sample of both ethnic groups, we designed an area stratified random sampling procedure involving three stages: (1) division of the sampling area into non-overlapping strata based on Hispanic household proportion using GIS software (2) random selection of the designated number of Census blocks from each stratum and (3) random selection of the designated number of housing units (i.e., survey participants) from each Census block. We conducted a community based survey to collect and examine social determinants of health and their association with obesity prevalence among a sample of Hispanics and non-Hispanic whites living in a rural community in the Southeastern United States. ![]() We describe the use of a novel Geographic Information System (GIS)-based population based sampling to minimize selection bias in a rural community based study. Conducting community based surveys to study these determinants must ensure representativeness of disparate populations. Most studies among Hispanics have focused on individual risk factors of obesity, with less attention on interpersonal, community and environmental determinants. ![]()
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