Physically demanding work at later ages, which is especially prevalent among disadvantaged groups, is associated with long-term health outcomes and may contribute to health inequality over the life course. Past studies of these issues have relied on occupational characteristics from the Occupational Information Network (O*NET), but few have assessed how O*NET compares to survey reports when measuring occupational exposures in analyses of socioeconomic status, work conditions, and health. We compare Health and Retirement Study (HRS, N = 16,683 working respondents) and O*NET measurements of general physical activity, frequency of lifting/handling objects, and frequency of stooping-related postures required at work. Pearson correlations between the HRS items and corresponding O*NET items vary from weak to moderate for lifting/handling and stooping-related postures to relatively large for general physical activity. Though they are measured on different scales, both the HRS and O*NET measures of physical demands reveal similar sex, racial/ethnic, and educational differentials in exposure to physically strenuous work. We fit random effects Poisson models to assess how these measures predict accumulation of functional limitations, a potential long-term consequence of strenuous working conditions. Comparable HRS and O*NET measures have similar associations with functional limitations. We also consider an average of physical demand items available in O*NET, finding that this measure has similar associations with functional limitations as the O*NET measure of general physical activity. These results suggest that O*NET characteristics and HRS respondent reports produce comparable disparities in physical work exposures (PWEs) and associations between physically demanding work and declines in physical functioning.
Innovative solutions to help older adults increase physical activity are critically important. In this qualitative study, we explored older adults' acceptance, capability, and experiences of using three different types of electronic wearable devices over a period of 4-24 weeks for self-monitoring and promoting physical activity. We conducted 23 semistructured interviews with older adults who participated in three physical activity intervention studies. Two researchers analyzed the data using NVivo version 12, applying a directed content analysis that was partially guided by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Six themes emerged: (1) device learning, (2) hedonic motivation, (3) habit and adherence, (4) facilitating conditions, (5) effort expectancy, and (6) performance expectancy. Although most older adults (95.8%) from this study were first-time users, they reflected positive experiences and generally enjoyed using electronic wearable devices. Participants reported issues related to electronic wearable device functionalities that can be improved to better enhance user experience and motivate increased physical activity. Future research should explore the role of electronic wearable devices in older adults' physical activity with an emphasis on behavioral change over time.