Implications of supermarket access, neighbourhood walkability and poverty rates for diabetes risk in an employee population

• Published in: Public health nutrition Vol. 19; no. 11; pp. 2040 - 2048
• Main Authors: Herrick, Cynthia J, Yount, Byron W, Eyler, Amy A
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.08.2016
• Subjects: Adult; at-risk population; Built environment; Censuses; Cholesterol; Convenience stores; Cross-Sectional Studies; data collection; Diabetes; Diabetes Mellitus - epidemiology; Diet; Economics and environment; Employees; Epidemiologic Factors; Exercise; Fast food industry; Female; Glucose; Health care; Health promotion; Health risks; Home environment; human resources; Humans; Information systems; Logistic Models; Low income groups; Male; Middle Aged; Multivariate Analysis; Neighborhoods; Nutrition research; Obesity; Occupational health; Poverty; Public health; Regression analysis; Research Papers; Residence Characteristics; Retrospective Studies; risk; Risk Factors; Social Determinants of Health; Socioeconomic factors; Supermarkets; Walking; Weight control; St Louis Missouri; United States > US; Poverty; Neighbourhood environment; Diabetes risk; Employee health
• ISSN: 1368-9800; 1475-2727; 1475-2727
• DOI: 10.1017/S1368980015003328

Diabetes is a growing public health problem, and the environment in which people live and work may affect diabetes risk. The goal of the present study was to examine the association between multiple aspects of environment and diabetes risk in an employee population. This was a retrospective cross-sectional analysis. Home environment variables were derived using employees' zip code. Descriptive statistics were run on all individual- and zip-code-level variables, stratified by diabetes risk and worksite. A multivariable logistic regression analysis was then conducted to determine the strongest associations with diabetes risk. Data were collected from employee health fairs in a Midwestern health system, 2009-2012. The data set contains 25 227 unique individuals across four years of data. From this group, using an individual's first entry into the database, 15 522 individuals had complete data for analysis. The prevalence of high diabetes risk in this population was 2·3 %. There was significant variability in individual- and zip-code-level variables across worksites. From the multivariable analysis, living in a zip code with higher percentage of poverty and higher walk score was positively associated with high diabetes risk, while living in a zip code with higher supermarket density was associated with a reduction in high diabetes risk. Our study underscores the important relationship between poverty, home neighbourhood environment and diabetes risk, even in a relatively healthy employed population, and suggests a role for the employer in promoting health.