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

  • Cynthia J Herrick (a1), Byron W Yount (a2) and Amy A Eyler (a3)

Abstract

Objective

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.

Design

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.

Setting

Data were collected from employee health fairs in a Midwestern health system, 2009–2012.

Subjects

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.

Results

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.

Conclusions

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.

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Copyright

Corresponding author

* Corresponding author: Email cherrick@dom.wustl.edu

References

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Keywords

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

  • Cynthia J Herrick (a1), Byron W Yount (a2) and Amy A Eyler (a3)

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