Whitney P. Witt

Social class gradients in health during adolescence

Study objective: To review existing data on social class gradients in adolescent health and to examine whether such gradients exist in new data concerning US adolescents. Design: Review of relevant publications and unpublished data; regression analyses using adolescent self reported health status data to determine whether there are gradients by social class, using three classes categorised by adolescent reported parental work status and education. Participants: Adolescents of ages 11–17. Main results: Findings from the literature indicate the presence of social class gradients in some but not all aspects of adolescent health. Results from new data showed social class gradients in several domains of health and in profiles of health. The likelihood of being satisfied with ones health, of being more resilient (better family involvement, better problem solving, more physical activity, better home safety), having higher school achievement, and of being in the best health profiles were significantly and progressively greater as social class rose. Moreover, the probability of being in the poorest health profile type group was progressively higher as social class declined. Conclusions: The review of existing data and the new findings support the existence of social class gradients in satisfaction with ones health, in resilience to health threats, in school achievement, and in being in the best health overall (as manifested by the health profiles composed of four major domains of health). The study had two especially notable findings: (1) the paucity of studies using the same or similar indicators, and (2) the consistent existence of social class gradients in characteristics related to subsequent health, particularly intake of nutritional foods and physical activity. The sparseness of existing data and the different aspects of health investigated in the relatively few studies underscore the need for (1) the development of conceptual models specifically focused on adolescent health and social class; (2) additional inquiry into the measurement of social class and adolescent perceptions of class; (3) inclusion of contextual variables in study design; and (4) longitudinal cohort studies to better understand the specific determinants of health during adolescence.

Health insurance coverage and the risk of decline in overall health and death among the near elderly, 1992-2002.

Background:Although individuals’ health insurance coverage changes frequently, previous analyses have not accounted for changes in insurance coverage over time. Objective:We sought to determine the independent association between lack of insurance and the risk of a decline in self-reported overall health and death from 1992 to 2002, accounting for changes in self-reported overall health and insurance coverage. Methods:We analyzed data from the Health and Retirement study, a prospective cohort study of a national sample of community-dwelling adults age 51–61 years old at baseline. Major decline in self-reported overall health and mortality was determined at 2-year intervals. Results:People who were uninsured at baseline had a 35% (95% confidence interval [CI] 12–62%) higher risk-adjusted mortality from 1992 to 2002 compared with those with private insurance. However, when we analyzed outcomes over 2-year intervals, individuals who were uninsured at the start of each interval were more likely to have a major decline in their overall health (pooled adjusted relative risk 1.43, 95% CI 1.28–1.63), but they were equally likely to die (pooled adjusted relative risk 0.96, 95% CI 0.73–1.27). Of the 1512 people who were uninsured at baseline, 220 (14.6%) died; of those who died, only 70 (31.8%) were still uninsured at the HRS interview prior to death. Conclusions:Death does not appear to be a short-term consequence of being uninsured. Instead, higher long-term mortality among the uninsured results from erosion in this populations health status over time and the attendant higher mortality associated with this. Most deaths among the uninsured occur after individuals have gained either public or private health insurance.

A framework to evaluate the economic impact of pharmacogenomics.

INTRODUCTIONnPharmacogenomics and personalized medicine promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings realized by eliminating costs associated with failed treatment. This paper describes a framework using health claims data for analyzing the potential value of pharmacogenomic testing in clinical practice.nnnMETHODSnWe evaluated a model of alternate clinical strategies using asthma patients data from a retrospective health claims database to determine a potential cost offset. We estimated the likely cost impact of using a hypothetical pharmacogenomic test to determine a preferred initial therapy. We compared the annualized per patient costs distributions under two clinical strategies: testing all patients for a nonresponse genotype prior to treating and testing none.nnnRESULTSnIn the Test All strategy, more patients fall into lower cost ranges of the distribution. In our base case (15% phenotype prevalence, 200 US dollars test, 74% overall first-line treatment efficacy and 60% second-line therapy efficacy) the cost savings per patient for a typical run of the testing strategy simulation ranged from 200 US dollars to 767 US dollars (5th and 95th percentile). Genetic variant prevalence, test cost and the cost of choosing the wrong treatment are key parameters in the economic viability of pharmacogenomics in clinical practice.nnnCONCLUSIONSnA general tool for predicting the impact of pharmacogenomic-based diagnostic tests on healthcare costs in asthma patients suggests that upfront testing costs are likely offset by avoided nonresponse costs. We suggest that similar analyses for decision making could be undertaken using claims data in which a population can be stratified by response to a drug.

Changes in health for the uninsured after reaching age-eligibility for medicare

BACKGROUND: Uninsured adults in late middle age are more likely to have a health decline than individuals with private insurance.OBJECTIVE: To determine how health and the risk of future adverse health outcomes changes after the uninsured gain Medicare.DESIGN: Prospective cohort study.PARTICIPANTS: Participants (N=3.419) in the Health and Retirement Study who transitioned from private insurance or being uninsured to having Medicare coverage at the 1996, 1998, 2000, or 2002 interview.MEASUREMENTS: We analyzed risk-adjusted changes in self-reported overall health and physical functioning during the transition period to Medicare (t−2 to t0) and the following 2 years (t0 to t2).RESULTS: Between the interview before age 65 (t−2) and the first interview after reaching age 65 (t0), previously uninsured individuals were more likely than those who had private insurance to have a major decline in overall health (adjusted relative risk [ARR] 1.46; 95% confidence interval [CI] 1.03 to 2.04) and to develop a new physical difficulty affecting mobility (ARR 1.24; 95% CI 0.96 to 1.56) or agility (ARR 1.33; 95% CI 1.12 to 1.54). Rates of improvement were similar between the 2 groups. During the next 2 years (t0 to t2), adjusted rates of declines in overall health and physical functioning were similar for individuals who were uninsured and those who had private insurance before gaining Medicare.CONCLUSIONS: Gaining Medicare does not lead to immediate health benefits for individuals who were uninsured before age 65. However, after 2 or more years of continuous coverage, the uninsured no longer have a higher risk of adverse health outcomes.

THE IMPACT OF MISSING LINKAGE DATA IN FAMILY HEALTH RESEARCH: RESULTS FROM THE 1994–1995 NATIONAL HEALTH INTERVIEW SURVEY DISABILITY SUPPLEMENT

Family health can be studied using the 1994–1995 National Health Interview Survey Disability Supplement by linking children to their mothers and other family members. However, the data item required to link is missing for 13% of children. We found that unlinked children and their probable mothers differed in many respects from their counterparts who could be linked, and exclusion of these mothers and their children from the analysis could bias results by introducing error due to incomplete coverage of the target population. We developed and validated a simple algorithm to match these children with their probable mother.