also contain, if only implicitly, forecasts of how today's preteenagers, teenagers, and young adults (who will constitute the 65-and-older age group in the year 2050), and the future immigrants who will join them, will identify their race and ethnicity when they are asked these questions in the year 2050. It is likely that the race and ethnicity categories used in census and official statistics will change several times by then.

This potential for change underscores an important point for the analyses discussed here: race and ethnicity are fluid categories, whose meanings vary and are to be understood in a particular social and historical context. They are not biological taxa. In this volume we have, wherever possible, used the racial and ethnic classification adopted for reporting purposes in federal government publications (Office of Federal Statistical Policy and Standards, 1978).1 Many of the large data sets analyzed in the chapters that follow used these categories, and vital rates and population figures with which the smaller studies are compared tend to use them. But within these categories there is much diversity (cultural, socioeconomic, behavioral, genetic) that is relevant to health outcomes. Several of the chapters address some of the challenges associated with identifying membership in particular groups.

It is common for researchers concerned with health outcomes (including mortality) to control for race and ethnicity in their analyses. Such procedures statistically adjust for a range of factors that are known to be related to health and that vary across racial and ethnic groups. Of late, however, there has been renewed interest in understanding these racial and ethnic differences and their potential implications for the mix and distribution of health states within the population. Socioeconomic arguments cite the consequences of lifelong poverty. Relevant factors include both early-life differences, such as birth weight and childhood nutrition, and midlife variables, such as access to employer-provided health insurance, the strain of physically demanding work, and exposure to a broad range of toxins, both behavioral (e.g., smoking) and environmental (e.g., workplace exposures). Over the life cycle, these factors combine to increase the demand for health care, while potentially limiting consumption of necessary health services. In late life, these factors may affect the age of onset of both morbidity and disability, the severity of symptoms, and ultimately the age at, and cause of, death. Recent research also highlights the enduring effects of education. Increased education appears to lower the risks for some chronic diseases—most notably, coronary heart disease and, perhaps most intriguingly, organic dementias—while retarding the pace of disease progression for other conditions (Snowdon et al., 1996; Feinstein, 1993).

1  

The Office of Management and Budget has issued a proposed statistical directive allowing multiple racial and ethnic classification, to replace the system set up in 1979. For a discussion of the history of the current system and issues affecting proposed revisions, see Edmonston et al., 1996.



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