Relationship between Employment Characteristics and Obesity among Employed U.S. Adults

Author:

Park Sohyun,Pan Liping,Lankford Tina

Abstract

Purpose. This study examined associations between employment characteristics and obesity among a sample representing civilian noninstitutionalized U.S. adults. Design. Quantitative, cross-sectional study. Setting. Workplace. Subjects. The 2010 National Health Interview Survey data for 15,121 employed adults (>18 years). Measures. The outcome variable was weight status, and exposure variables were employment characteristics (number of employees, work hours, paid by the hour, paid sick leave, and health insurance offered). Analysis. Multivariate logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for employment characteristics associated with obesity (body mass index [BMI] ≥ 30 kg/m2) after controlling for age, sex, race/ethnicity, education, family income, fruit/vegetable intake, physical activity, smoking, and occupations. Results. Nationwide, 28% of employed adults were obese. From multivariate logistic regression, the odds of being obese was significantly greater among adults who worked at a company with 100 to 499 employees (OR = 1.19, 95% CI = 1.02–1.39) vs. with 1 to 24 employees and those who worked >50 hours/week (OR = 1.32, 95% CI = 1.05–1.65) vs. < 30 hours/week. Conclusion. Approximately 3 out of 10 employees were obese and 6 out of 10 were overweight or obese. A better understanding of why these employment characteristics are associated with obesity could help employers better develop and target interventions for obesity prevention and treatment in the worksites.

Publisher

SAGE Publications

Subject

Public Health, Environmental and Occupational Health,Health (social science)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3