This exploratory study aims to develop and test a generalizable process for measuring the relationship between long-term work in a particular occupation and the onset of chronic disease later in life. A secondary aim is to test the utility o that process for assessing the relationship between long-term exposure to various job characteristics and activities (e.g., handling materials and objects) and subsequent chronic disease outcomes (e.g., arthritis). The proposed project is based on a conceptual model that transcends traditional notions of the distinction between work-related and nonwork-related illness. We hypothesize that aggregated long-term work experiences over several decades in particular occupations with characteristic job requirements can potentially affect the propensity for workers to develop specific chronic conditions later in life. This will be perhaps the first sudy in the U.S using long-term longitudinal data to estimate the relative risks of chronic disease by occupational category. The study will help answer questions about whether the development of common chronic health conditions among workers 45 years and older, such as arthritis, asthma, and diabetes, may be related to long-term exposure to work in particular occupations and job activities. The proposed analytical process has broad relevancy and can potentially be applied to numerous occupations, job activities/characteristics, and chronic conditions. The study has practical relevance for the establishment of workplace-based chronic disease prevention programs and chronic disease surveillance. The proposed study uses publicly available de-identified data from the National Longitudinal Survey of Youth-1979 (NLSY79) and the Occupational Information Network (O*NET), and applies occupational codes from the U.S. Census and the Standard Occupational Classifications (SOC) coding systems. O*NET contains ratings (on a scale of 0 to 100) of 277 descriptors characterizing each of 974 occupations. We will conduct two demonstration studies to test the efficacy and utility of using these O*NET codes and ratings to estimate the relative risk of subsequent chronic disease. Study #1 has two components: a) an analysis of the association between aggregated exposure to """"""""handling and moving materials"""""""" (one of the 277 O*NET job descriptors) and diagnosis of arthritis later in life (one of nine chronic conditions outcomes assessed by NLSY79) and b) a subanalysis of the data limited to arthritis outcomes initially reported in surveys years 2000 to 2010. In Study #2a, we will analyze the association between aggregated years in an occupational classification and the risk for arthritis (and potentially any of the other eight chronic conditions assessed by NLSY79: diabetes, asthma, hypertension, heart disease, non-skin cancer, chronic lung disease, emotional and psychiatric disorders, and general health limitations). Additionally, in Study #2b, we will assess arthritis outcomes in five broad occupational groupings compared to a referent group of white-collar occupations (e.g., clerical and sales). By extension, this same process could then potentially be extended to any of the other chronic disease outcomes.
The rising prevalence of chronic disease among people over 45 years old is perhaps the greatest health challenge facing America. Insufficient attention has been paid to investigating possible connections between long-term job history in specific occupations and the risk of eventual chronic disease. This study will greatly advance knowledge in this field, and help target appropriate interventions (e.g., workplace surveillance for chronic conditions) in high-risk occupations.
| Dembe, Allard E; Yao, Xiaoxi (2016) Chronic Disease Risks From Exposure to Long-Hour Work Schedules Over a 32-Year Period. J Occup Environ Med 58:861-7 |
| Dembe, Allard E; Yao, Xiaoxi; Wickizer, Thomas M et al. (2014) Using O*NET to estimate the association between work exposures and chronic diseases. Am J Ind Med 57:1022-31 |
| Dembe, Allard E; Yao, Xiaoxi; Wickizer, Thomas M et al. (2014) A novel method for estimating the effects of job conditions on asthma and chronic lung disease. J Asthma 51:799-807 |
