%0 Journal Article %J Population Research and Policy Review %D 2019 %T Comparability of mortality estimates from social surveys and vital statistics data in the United States. %A Dustin C. Brown %A Joseph T. Lariscy %A Lucie Kalousova %K Comparisons %K Mortality %K Survey Methodology %X Social surveys prospectively linked with death records provide invaluable opportunities for the study of the relationship between social and economic circumstances and mortality. Although survey-linked mortality files play a prominent role in U.S. health disparities research, it is unclear how well mortality estimates from these datasets align with one another and whether they are comparable with U.S. vital statistics data. We conduct the first study that systematically compares mortality estimates from several widely-used survey-linked mortality files and U.S. vital statistics data. Our results show that mortality rates and life expectancies from the National Health Interview Survey Linked Mortality Files, Health and Retirement Study, Americans' Changing Lives study, and U.S. vital statistics data are similar. Mortality rates are slightly lower and life expectancies are slightly higher in these linked datasets relative to vital statistics data. Compared with vital statistics and other survey-linked datasets, General Social Survey-National Death Index life expectancy estimates are much lower at younger adult ages and much higher at older adult ages. Cox proportional hazard models regressing all-cause mortality risk on age, gender, race, educational attainment, and marital status conceal the issues with the General Social Survey-National Death Index that are observed in our comparison of absolute measures of mortality risk. We provide recommendations for researchers who use survey-linked mortality files. %B Population Research and Policy Review %V 38 %P 371-401 %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/31156286?dopt=Abstract %R 10.1007/s11113-018-9505-1 %0 Journal Article %J Work, Aging and Retirement %D 2018 %T A comparison of subjective and objective job demands and fit with personal resources as predictors of retirement timing in a national U.S. Sample %A Amanda Sonnega %A Helppie-McFall, Brooke %A Péter Hudomiet %A Robert J. Willis %A Gwenith G Fisher %K Comparisons %K Job stressors %K Retirement Planning and Satisfaction %X Population aging and attendant pressures on public budgets have spurred considerable interest in understanding factors that influence retirement timing. A range of sociodemographic and economic characteristics predict both earlier and later retirement. Less is known about the role of job characteristics on the work choices of older workers. Researchers are increasingly using the subjective ratings of job characteristics available in the Health and Retirement Study in conjunction with more objective measures of job characteristics from the Occupational Information Network (O*NET) database. Employing a theoretically-informed model of job demands-personal resources fit, we constructed mismatch measures between resources and job demands (both subjectively and objectively assessed) in physical, emotional, and cognitive domains. When we matched comparable measures across the 2 data sources in the domains of physical, emotional, and cognitive job demands, we found that both sources of information held predictive power in relation to retirement timing. Physical and emotional but not cognitive mismatch were associated with earlier retirement. We discuss theoretical and practical implications of these findings and directions for future research. %B Work, Aging and Retirement %V 4 %G eng %U https://academic.oup.com/workar/article-lookup/doi/10.1093/workar/wax016 %N 1 %& 37–51 %R 10.1093/workar/wax016 %0 Journal Article %J Quality of Life Research %D 2018 %T Cross-national health comparisons using the Rasch model: findings from the 2012 US Health and Retirement Study and the 2012 Mexican Health and Aging Study %A Ickpyo Hong %A Timothy A Reistetter %A Díaz-Venegas, Carlos %A Alejandra Michaels-Obregon %A Rebeca Wong %K Arthritis %K Chronic conditions %K Comparisons %K Disabilities %K MHAS %X Purpose Cross-national comparisons of patterns of population aging have emerged as comparable national micro-data have become available. This study creates a metric using Rasch analysis and determines the health of American and Mexican older adult populations. Methods Secondary data analysis using representative samples aged 50 and older from 2012 U.S. Health and Retirement Study (n = 20,554); 2012 Mexican Health and Aging Study (n = 14,448). We developed a function measurement scale using Rasch analysis of 22 daily tasks and physical function questions. We tested psychometrics of the scale including factor analysis, fit statistics, internal consistency, and item difficulty. We investigated differences in function using multiple linear regression controlling for demographics. Lastly, we conducted subgroup analyses for chronic conditions. Results The created common metric demonstrated a unidimensional structure with good item fit, an acceptable precision (person reliability = 0.78), and an item difficulty hierarchy. The American adults appeared less functional than adults in Mexico (β = − 0.26, p < 0.0001) and across two chronic conditions (arthritis, β = − 0.36; lung problems, β = − 0.62; all p < 0.05). However, American adults with stroke were more functional than Mexican adults (β = 0.46, p = 0.047). Conclusions The Rasch model indicates that Mexican adults were more functional than Americans at the population level and across two chronic conditions (arthritis and lung problems). Future studies would need to elucidate other factors affecting the function differences between the two countries. %B Quality of Life Research %V 27 %P 2431-2441 %8 09/2018 %G eng %U https://link-springer-com.proxy.lib.umich.edu/article/10.1007%2Fs11136-018-1878-4 %N 9 %0 Journal Article %J American Journal of Epidemiology %D 2018 %T Development, Construct Validity, and Predictive Validity of a Continuous Frailty Scale: Results from Two Large U.S. Cohorts. %A Wu, Chenkai %A G John Geldhof %A Xue, Qian-Li %A Dae H Kim %A Anne B Newman %A Michelle C Odden %K Comparisons %K Frailty %K Survey Methodology %X Frailty is an age-related clinical syndrome of decreased resilience to stressors. Among numerous assessments of frailty, the frailty phenotype (FP) scale, proposed by Fried and colleagues has been the most widely used one. We aimed to develop a continuous frailty scale that may overcome limitations facing the categorical FP scale and to evaluate its construct validity, predictive validity, and measurement properties. Data were from the Cardiovascular Health Study (N = 4243) and Health and Retirement Study (N = 7600). Frailty was conceptualized as a continuous construct, measured by five measures used in FP scale: gait speed, grip strength, exhaustion, physical activity, and weight loss. We used confirmatory factor analysis to investigate the relationship between five indicators and the latent frailty construct. We examined the association of the continuous frailty scale with mortality and disability. The unidimensional model fit the data satisfactorily; similar factor structure was observed across two cohorts. Gait speed and weight loss were the strongest and weakest indicators, respectively; grip strength, exhaustion, and physical activity had similar strength in measuring frailty. In each cohort, the continuous frailty scale was strongly associated with mortality and disability and persisted to be associated with outcomes among robust and prefrail persons classified by the FP scale. %B American Journal of Epidemiology %V 187 %P 1752-1762 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/29688247?dopt=Abstract %R 10.1093/aje/kwy041 %0 Journal Article %J Annual Review of Economics %D 2012 %T International Comparisons in Health Economics: Evidence from Aging Studies %A James P Smith %A James Banks %K Aging %K Comparisons %K Cross-National %K Meta-analyses %X The authors provide an overview of the growing literature that uses micro-level data from multiple countries to investigate health outcomes, and their link to socioeconomic factors, at older ages. Since the data are at a comparatively young stage, much of the analysis is at an early stage and limited to a handful of countries, with analysis for the US and England being the most common. What is immediately apparent as they get better measures is that health differences between countries amongst those at older ages are real and large. Countries are ranked differently according to whether one considers life-expectancy, prevalence or incidence of one condition or another. And the magnitude of international disparities may vary according to whether measures utilize doctor diagnosed conditions or biomarker-based indicators of disease and poor health. But one key finding emerges – the US ranks poorly on all indicators with the exception of self-reported subjective health status. %B Annual Review of Economics %V 4 %P 57-81 %G eng %R 10.1146/annurev-economics-080511-110944