Longitudinal Uses of the Population Assessment of Tobacco and Health Study.

OBJECTIVES: The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative study of the US population on tobacco use and its effects on health, with 3 waves of data collection between 2013 and 2016. Prior work described the methods of the first wave. In this paper, we describe the methods of the subsequent 2 waves and provide recommendations for how to conduct longitudinal analyses of PATH Study data. METHODS: We use standard survey quality metrics to evaluate the results of the follow-up waves of the PATH Study. The recommendations and examples of longitudinal and cross-sectional analyses of PATH Study data follow a design-based statistical inference framework. RESULTS: The quality metrics indicate that the PATH Study sample of approximately 40,000 continuing respondents remains representative of its target population. Depending on the intended analysis, different survey weights may be appropriate. CONCLUSION: The PATH Study data are a valuable resource for regulatory scientists interested in longitudinal analysis of tobacco use and its effects on health. The availability of multiple sets of specialized survey weights enables researchers to target a wide range of tobacco-related analytic questions.

Lost productive work time costs from health conditions in the United States: results from the American Productivity Audit.

The American Productivity Audit (APA) is a telephone survey of a random sample of 28,902 U.S. workers designed to quantify the impact of health conditions on work. Lost productive time (LPT) was measured for personal and family health reasons and expressed in hours and dollars. Health-related LPT cost employers 225.8 billion US dollars/year (1685 US dollars/employee per year); 71% is explained by reduced performance at work. Personal health LPT was 30% higher in females and twice as high in smokers (> or =1 pack/day) versus nonsmokers. Workers in high-demand, low-control jobs had the lowest average LPT/week versus the highest LPT for those in low-demand, high-control jobs. Family health-related work absence accounted for 6% of all health-related LPT. Health-related LPT costs are substantial but largely invisible to employers. Costs vary significantly by worker characteristics, suggesting that intervention needs vary by specific subgroups.

Cost of lost productive work time among US workers with depression.

CONTEXT: Evidence consistently indicates that depression has adversely affected work productivity. Estimates of the cost impact in lost labor time in the US workforce, however, are scarce and dated. OBJECTIVE: To estimate the impact of depression on labor costs (ie, work absence and reduced performance while at work) in the US workforce. DESIGN, SETTING, AND PARTICIPANTS: All employed individuals who participated in the American Productivity Audit (conducted August 1, 2001-July 31, 2002) between May 20 and July 11, 2002, were eligible for the Depressive Disorders Study. Those who responded affirmatively to 2 depression-screening questions (n = 692), as well as a 1:4 stratified random sample of those responding in the negative (n = 435), were recruited for and completed a supplemental interview using the Primary Care Evaluation of Mental Disorders Mood Module for depression, the Somatic Symptom Inventory, and a medical and treatment history for depression. Excess lost productive time (LPT) costs from depression were derived as the difference in LPT among individuals with depression minus the expected LPT in the absence of depression projected to the US workforce. MAIN OUTCOME MEASURE: Estimated LPT and associated labor costs (work absence and reduced performance while at work) due to depression. RESULTS: Workers with depression reported significantly more total health-related LPT than those without depression (mean, 5.6 h/wk vs an expected 1.5 h/wk, respectively). Eighty-one percent of the LPT costs are explained by reduced performance while at work. Major depression accounts for 48% of the LPT among those with depression, again with a majority of the cost explained by reduced performance while at work. Self-reported use of antidepressants in the previous 12 months among those with depression was low (<33%) and the mean reported treatment effectiveness was only moderate. Extrapolation of these survey results and self-reported annual incomes to the population of US workers suggests that US workers with depression employed in the previous week cost employers an estimated 44 billion dollars per year in LPT, an excess of 31 billion dollars per year compared with peers without depression. This estimate does not include labor costs associated with short- and long-term disability. CONCLUSIONS: A majority of the LPT costs that employers face from employee depression is invisible and explained by reduced performance while at work. Use of treatments for depression appears to be relatively low. The combined LPT burden among those with depression and the low level of treatment suggests that there may be cost-effective opportunities for improving depression-related outcomes in the US workforce.

Lost productive time and cost due to common pain conditions in the US workforce.

CONTEXT: Common pain conditions appear to have an adverse effect on work, but no comprehensive estimates exist on the amount of productive time lost in the US workforce due to pain. OBJECTIVE: To measure lost productive time (absence and reduced performance due to common pain conditions) during a 2-week period. DESIGN AND SETTING: Cross-sectional study using survey data from the American Productivity Audit (a telephone survey that uses the Work and Health Interview) of working adults between August 1, 2001, and July 30, 2002. PARTICIPANTS: Random sample of 28 902 working adults in the United States. MAIN OUTCOME MEASURES: Lost productive time due to common pain conditions (arthritis, back, headache, and other musculoskeletal) expressed in hours per worker per week and calculated in US dollars. RESULTS: Thirteen percent of the total workforce experienced a loss in productive time during a 2-week period due to a common pain condition. Headache was the most common (5.4%) pain condition resulting in lost productive time. It was followed by back pain (3.2%), arthritis pain (2.0%), and other musculoskeletal pain (2.0%). Workers who experienced lost productive time from a pain condition lost a mean (SE) of 4.6 (0.09) h/wk. Workers who had a headache had a mean (SE) loss in productive time of 3.5 (0.1) h/wk. Workers who reported arthritis or back pain had mean (SE) lost productive times of 5.2 (0.25) h/wk. Other common pain conditions resulted in a mean (SE) loss in productive time of 5.5 (0.22) h/wk. Lost productive time from common pain conditions among active workers costs an estimated 61.2 billion dollars per year. The majority (76.6%) of the lost productive time was explained by reduced performance while at work and not work absence. CONCLUSIONS: Pain is an inordinately common and disabling condition in the US workforce. Most of the pain-related lost productive time occurs while employees are at work and is in the form of reduced performance.

Variable selection and raking in propensity scoring.

This paper discusses some practical issues in applying propensity scoring in the context of endpoint analysis in a pre-/posttest longitudinal design with an ordinal measure of treatment intensity and a high-dimensional potential covariate space: how many covariates to include in propensity models; how to evaluate the adequacy of tentative propensity models; and how to tailor models to provide hypercontrol on a limited subset of covariates. These issues arose in the evaluation of a health communication program.