Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7 Page 8 Page 9 Page 10 Page 11 Page 12 Page 13 Page 14 Page 15 Page 16 Page 17 Page 18 Page 19 Page 20 Page 21 Page 22 Page 23 Page 24 Page 25 Page 26 Page 27 Page 28 Page 29 Page 30 Page 31 Page 32 Page 33 Page 34 Page 35 Page 36 Page 37 Page 38 Page 39 Page 40 Page 41 Page 42 Page 43 Page 44 Page 45 Page 46 Page 47 Page 48 Page 49 Page 50 Page 51 Page 52 Page 53 Page 54 Page 55 Page 56 Page 57 Page 58 Page 59 Page 60 Page 61 Page 62 Page 63 Page 64 Page 65 Page 66 Page 67 Page 68 Page 69 Page 70 Page 71 Page 72 Page 73 Page 74 Page 75 Page 76 Page 77 Page 78 Page 79 Page 80 Page 81 Page 82 Page 83 Page 84 Page 85 Page 86 Page 87 Page 88 Page 89 Page 90 Page 91 Page 92 Page 93 Page 94 Page 95 Page 96 Page 97 Page 98 Page 99 Page 100 Page 101 Page 102 Page 103 Page 104 Page 105 Page 106 Page 107 Page 108The HRS offers the scientific community open access to in-depth, longitudinal data about adults over age 50, enabling researchers to explore critical aging-related concerns. Since the study began in 1992, 7,000 qualified scientists have registered to use the data, and nearly 1,000 researchers have tapped the data to produce more than 1,000 papers and dissertations, including over 600 peer-reviewed journal articles and book chapters (Figure A-1). The study’s broad national representation allows it to look at the older population in general, as well as the great diversity and variability of aging. Thus, while for most people retirement is a relatively smooth transition for which they have planned and prepared, there are impor- tant exceptions. One study using HRS data showed that households that are otherwise similar in many respects, including total lifetime income, nevertheless reach retirement with very different levels of wealth, implying very different patterns of saving and consumption (Venti and Wise 1998). The HRS helps researchers to investigate both current issues and changes over time. For example, HRS data from before 2006 have shown that people age 65 and older were less likely than younger adults to have prescription drug insurance coverage. Research using the data has further shown that, regardless of age, people without prescription drug coverage are less likely than those with it to fill all of their prescriptions, posing an increased risk for adverse health outcomes (Heisler et al. 2004). The HRS also is actively following the impact of the new Medicare Part D prescription drug benefit on medication use and ultimately on the older population’s health. The HRS permits researchers to probe the impacts of unexpected health events, such as a cancer diagnosis, heart attack, stroke, or the onset of chronic disease on other aspects of individuals’ lives. For example, analyses using the HRS data have shown that household income and wealth decline considerably after a “health shock” and that the income losses persist for at least a decade (Smith 2003). Further, much of the loss of household wealth comes from loss of earnings rather than high average out-of-pocket medical expenses, suggesting that some people are under-insured for disability. The HRS also is one of the first national health surveys to measure cognitive health and cognitive-impairment risk factors at the population level. The HRS, along with other studies worldwide that were based on the its design, allows for comparisons of trends in aging and retirement worldwide. Cross-national exchange of information in developing the other studies has brought new ideas and approaches, both for the other studies and the HRS. For example, the 2006 HRS survey wave gath- ered biomarker data, a key feature of the English Longitudinal Study of Ageing (ELSA). HRS and ELSA data also were used to compare the health of the U.S. and English White populations, finding that the English population was significantly healthier even after controlling for weight, exercise, smoking, and alcohol consumption (Banks et al. 2006). For more about these studies, see the box on page 18. Unique Features of the HRS Among the HRS’s important contributions to the study of aging and to social science research: 13