OBJECTIVES: Industry and occupation variables are overlooked in many public health surveillance efforts, yet they are useful for describing the burden and distribution of various public health diseases, behaviors, and conditions. This study is the first ever analysis of the Colorado Behavioral Risk Factor Surveillance System (BRFSS) to describe chronic conditions and risk behaviors by occupation. It is intended to provide a new perspective on this existing data source and demonstrate the value of occupation as a core demographic variable for public health research, policy, and practice. METHODS: Two standardized employment questions were included in the 2012 Colorado BRFSS survey and administered to eligible survey respondents who were employed, self-employed, or out of work for less than one year. Occupation data were coded using the National Institute for Occupational Safety and Health (NIOSH) Industry and Occupation Computerized Coding System. We analyzed health behaviors and conditions by major occupation groups. We calculated prevalence estimates and 95% confidence intervals (CIs). RESULTS: The prevalence of chronic conditions, health statuses, and risk behaviors (e.g., smoking and seatbelt use) varied significantly by occupation. For example, compared with all workers (93.6%, 95% CI 92.7, 94.5), significantly fewer workers in farming, forestry, fishing and construction, extraction jobs (87.0%, 95% CI 82.0, 92.0) reported always or nearly always wearing a seatbelt while driving. Additionally, significantly more office and administrative support workers (27.5%, 95% CI 22.5, 32.4) compared with all workers (20.6%, 95% CI 19.3, 22.0) were obese. Further observation and research is needed to understand the effects of occupation on health outcomes and behaviors. CONCLUSION: There are no other Colorado state-level datasets that link health behaviors and chronic conditions with occupation. This study shows that the prevalence of chronic conditions and risk behaviors varies substantially by occupation. Other states conducting the BRFSS may choose to adopt the NIOSH industry and occupation module and add other questions to further investigate health issues by occupation.
OBJECTIVES: Industry and occupation variables are overlooked in many public health surveillance efforts, yet they are useful for describing the burden and distribution of various public health diseases, behaviors, and conditions. This study is the first ever analysis of the Colorado Behavioral Risk Factor Surveillance System (BRFSS) to describe chronic conditions and risk behaviors by occupation. It is intended to provide a new perspective on this existing data source and demonstrate the value of occupation as a core demographic variable for public health research, policy, and practice. METHODS: Two standardized employment questions were included in the 2012 Colorado BRFSS survey and administered to eligible survey respondents who were employed, self-employed, or out of work for less than one year. Occupation data were coded using the National Institute for Occupational Safety and Health (NIOSH) Industry and Occupation Computerized Coding System. We analyzed health behaviors and conditions by major occupation groups. We calculated prevalence estimates and 95% confidence intervals (CIs). RESULTS: The prevalence of chronic conditions, health statuses, and risk behaviors (e.g., smoking and seatbelt use) varied significantly by occupation. For example, compared with all workers (93.6%, 95% CI 92.7, 94.5), significantly fewer workers in farming, forestry, fishing and construction, extraction jobs (87.0%, 95% CI 82.0, 92.0) reported always or nearly always wearing a seatbelt while driving. Additionally, significantly more office and administrative support workers (27.5%, 95% CI 22.5, 32.4) compared with all workers (20.6%, 95% CI 19.3, 22.0) were obese. Further observation and research is needed to understand the effects of occupation on health outcomes and behaviors. CONCLUSION: There are no other Colorado state-level datasets that link health behaviors and chronic conditions with occupation. This study shows that the prevalence of chronic conditions and risk behaviors varies substantially by occupation. Other states conducting the BRFSS may choose to adopt the NIOSH industry and occupation module and add other questions to further investigate health issues by occupation.
Authors: Dwayne W Jarman; Timothy S Naimi; Stephen P Pickard; Walter Randolph Daley; Anindya K De Journal: Prev Chronic Dis Date: 2007-09-15 Impact factor: 2.830
Authors: Sarah L Kerns; Chunkit Fung; Sophie D Fossa; Paul C Dinh; Patrick Monahan; Howard D Sesso; Robert D Frisina; Darren R Feldman; Robert J Hamilton; David Vaughn; Neil Martin; Robert Huddart; Christian Kollmannsberger; Deepak Sahasrabudhe; Shirin Ardeshir-Rouhani-Fard; Lawrence Einhorn; Lois B Travis Journal: JNCI Cancer Spectr Date: 2020-03-20