BEHAVIORAL VARIATION

Some behavior risk factors clearly affect health in late life, as a variety of studies show. For instance, Østbye et al. (2002) looked longitudinally at the effects of various behaviors on a variety of health outcomes, including inability to work, dependence on others in activities of daily living, self-reported health status, and hospitalization. For middle-aged and older Americans, smoking was consistently related to ill health however measured, as was lack of exercise and obesity (though a very low body mass index, or BMI, also increased risk) and past problems with alcohol (see also, e.g., Allison et al., 1997; Burke et al., 2001; Davis et al., 1994; Launer et al., 1994; Stuck et al., 1999; Thun et al., 1997). These behaviors are among the major risk factors associated with heart disease, cancer, and other morbidities (McGinnis and Foege, 1993). They appear to explain part—though generally a small part—of variation by education and income in functional and self-rated health and disease (Crimmins et al., 2004; Lantz et al., 2001).

A few studies suggest age limits to the effects of some behavior risk factors. Perhaps beyond age 70 or so, those who are still healthy may be less affected by continuing to smoke or being overweight (Crimmins, 2001; Seeman et al., 1994; Strawbridge et al., 1996). Other studies, however, show continued effects at advanced ages (Reed et al., 1998). Previous behavior, at younger ages, could, in particular cases, be of diminishing relevance. This effect has been demonstrated for smoking: people who quit smoking by their mid-40s show no adverse effects by their late 50s, if they survive to that age, relative to those who never smoked (Østbye et al., 2002; Peto et al., 2000). More generally, however, behavior earlier in life predicts later behavior and may have long-term effects not fully accounted for (Warner and Hayward, 2002).

Racial and ethnic groups differ on these behaviors (Bolen et al., 2000; Schoenborn and Barnes, 2002); see Table 5-1. Relative to whites, American Indians and Alaska Natives exhibit less healthy behaviors, and Asians generally healthier behaviors, except in having less leisure-time physical activity. Blacks and Hispanics also have less leisure-time physical activity than whites, and both these groups are more likely to be obese, though the contrast is less sharp for Hispanics. In addition, Hispanics report slightly more binge drinking than whites, but blacks report sharply less. (Drinking patterns are complex, however, showing cultural patterning across nationality groups that persists across generations [Dawson, 1998].)

TABLE 5-1

Self-Reported Health Risk Behaviors, by Race and Ethnicity.

These risk behaviors may not be independently chosen but may represent a syndrome of risk affinity or aversion. Counting the number of behavior risk factors—and adding such preventive behaviors as colorectal screening—Hahn et al. (2000) confirm that American Indians and Alaska Natives and blacks have a significantly larger number of behavior risk factors than whites, and Asians a significantly smaller number, even controlling for socioeconomic factors.

Men and women are not distinguished in Table 5-1, but gender differences could be important (Winkleby and Cubbin, 2004). If one looks specifically at men and women aged 65-74, the picture becomes more complicated, particularly for blacks. Higher levels of obesity and inactivity, relative to whites, appear mainly for older black women, but not for older black men. And cigarette smoking does appear relatively more common among older black men relative to whites, though not among younger black men nor among black women of any age (Sundquist et al., 2001; Winkleby and Cubbin, 2004).

REASONS FOR VARIATION

Socioeconomic disadvantage is one reason for differences in behavior risk factors. Less education, for instance, is associated with more smoking and less physical activity, even among high-functioning people aged 70-79 (Kubzansky et al., 1998). Controlling for education and income reduces the apparent behavioral disadvantages of blacks and Hispanics at all adult ages. However, it does not increase any advantage in lower alcohol consumption, and one marginal difference—a Hispanic advantage in lower cigarette smoking—becomes significant when socioeconomic factors are taken into account (Winkleby and Cubbin, 2004). Some differences clearly cannot be explained by socioeconomic factors, at least to the extent socioeconomic differences can presently be measured (Braveman et al., 2001; Kaufman et al., 1997). Whether controlling for home ownership and other assets would eliminate more of the behavioral differences is not known. Even adding such controls in one study, however, leaves untouched a large part of the black disadvantage, relative to whites, in cardiovascular disease indicators (Rooks et al., 2002).

Another source of behavioral differences may be cultural, or more specifically, degree of acculturation among immigrants and their descendants (Espino et al., 1991; Jasso et al., 2000). The more acculturated a person—whether Hispanic, Asian, or black—the more prone the person is to smoking and obesity, whether acculturation is determined from United States versus foreign birth, duration of residence in the United States, or language spoken at home (Singh and Siahpush, 2002; Winkleby and Cubbin, 2004). Various cultural beliefs, such as the presumed attractiveness of moderately overweight women, have also been proposed as important (Stevens et al., 1994).

An additional factor that may produce behavioral differences is the residential environment. Neighborhoods provide stimuli, such as outlets for alcohol or illegal drugs, or limit options for healthy nutrition or exercise. Black neighborhoods appear more likely to suffer from such institutional risk factors as the proliferation of liquor stores and insufficient supplies of prescription drugs (LaVeist and Wallace, 2000; Morrison et al., 2000). However, since blacks have lower rates of drinking and smoking than whites—an advantage that increases when socioeconomic status is controlled—the implications of such neighborhood disadvantages are unclear. Differences do indeed appear across neighborhoods in smoking, dietary practices, physical activity, and substance abuse (Morenoff and Lynch, 2004; Winkleby and Cubbin, 2004). Whether these are due mainly to socioeconomic deprivation in poorer neighborhoods or actually reflect some effect of the neighborhood environment is difficult to verify.

EFFECTS OF VARIATION AND TRENDS

Does variation in these behavior risk factors account for some portion of racial and ethnic differences in health? This issue has been insufficiently studied, especially for comparisons other than black and white. Behavioral factors clearly do not explain all differences, and how much they do explain is unclear.

Looking at black-white differences in mortality, Otten et al. (1990) combined behavior risk factors (smoking, BMI, and alcohol intake) and some health outcomes closely linked to behavior (systolic blood pressure, cholesterol level, and diabetes). Among persons 35-54 years old, those factors combined explained 31 percent of the excess mortality for blacks relative to whites. Slightly more of the mortality differential was explained by income, while a larger proportion remained unexplained.

With a narrower definition of behavior risk factors, less of the health differences can be accounted for. In a separate analysis of self-reported health among individuals aged 51-61 years (Smith and Kington, 1997), a cluster of behavioral factors—the most important of which was BMI—account for only about one-sixth of the black disadvantage relative to whites, and it did not affect the Hispanic disadvantage. Among individuals aged 70 and older, the effect of behavior risk factors on self-reported health is slightly greater, with the black disadvantage reduced by one-third and the Hispanic disadvantage by close to one-fifth. These results are largely independent of socioeconomic status.

The role of behavior risk factors is even smaller in a study by Warner and Hayward (2002) of a sample of older men. They find that, once socioeconomic and demographic factors are taken into account, behavior factors do not explain the mortality gap. The opposite is true: with socioeconomic and demographic factors controlled, black risk behavior appears more favorable for health than white behavior, mainly because, with socioeconomic status controlled, blacks smoke less.

Such comparisons are mostly confined to black and whites. Given the somewhat contradictory patterns—Hispanics and Asians both having lower mortality rates than whites (but in one case exhibiting generally riskier behavior and in the other case less risky behavior)—it seems unlikely that, whatever the effects of these behaviors, they account for a substantial portion of health differences.

Could the effects of similar behaviors be different across racial and ethnic groups? Systematic study of this question has not been done, though hypotheses to this effect have been offered (e.g., Pampel, 1998). Work on obesity and alcohol consumption may be used to illustrate the possibilities and the uncertainties.

Obesity among older blacks, according to several studies summarized by Stevens (2000), is less of a risk factor for mortality than among whites (see also Sanchez et al., 2000). This differential effect appears mainly to involve black women. Although a dose-response relationship can be shown between BMI (above a minimum BMI of around 23) and mortality rate for whites of either gender, no such effect is visible for black women in several studies (e.g., Calle et al., 1999; Stevens, 2000; Stevens et al., 1998). It has also been suggested that obesity may even have a protective effect among older Hispanics (Stern et al., 1990). There are contradictory studies, however. For instance, Allison et al. (1997) find the same association of BMI with mortality for blacks and whites among men and women 70 years and older. And Grabowski and Ellis (2001) find, for a predominantly white sample of people of the same age, no association of elevated BMI with mortality. Several explanations are possible for such conflicting findings, including restricted samples, the uneven effect of selection, variations in model specification, the confounding relationship of smoking with BMI, and possible differences in the distribution of body fat (Stern et al., 1990). Some generally negative effect of obesity on health—though not necessarily moderate overweight—is likely (Casper, 1995; Rössner, 2001), though attending to ethnicity clearly complicates the issue.

Alcohol consumption may also vary in its effects across racial and ethnic groups. As with BMI, alcohol consumption has a U-shaped or J-shaped relationship to mortality, at least beginning around age 35. The number of drinks associated with minimum mortality risk rises with age (White et al., 2002). Epidemiological studies have also found a minimum for deterioration in cognitive performance, which begins around four to eight drinks a day for men and two to four drinks a day for women (Dufouil et al., 1997; Elias et al., 1999; Kalmijn et al., 2002). For older Japanese Americans in Hawaii, however, cognitive performance declines at lower levels, beginning at about one drink a day (Bond et al., 2001; Galanis et al., 2000). A genetic factor may be involved: the fact that 50 percent of Japanese and Chinese lack the active form of aldehyde hydrogenase (ALDH2) and therefore have a lower alcohol elimination rate (Bond et al., 2001; Eckardt et al., 1998).

Health-related risk behaviors could get worse for groups with large proportions of immigrants. As noted above, acculturation is related to increases in both smoking and obesity, which are initially lower among immigrants than natives. Nor does rising socioeconomic status among minorities always reduce risky behavior. Consider the relationship between obesity and education. Educational levels are rising, from which one might infer the spread of healthier behavior. However, higher education increases physical activity more for whites than blacks, as well as reducing alcohol consumption more among whites (Gallant and Dorn, 2001). Furthermore, within each educational level, obesity is also rising—and it is rising faster among blacks than whites (Himes and Reynolds, 2002). Future generations of the older adults will be made up of individuals whose youthful habits, for whatever environmental and generational reasons, will have been less favorable to maintaining health.

OTHER BEHAVIORS

We have considered major behavior risk factors that affect chronic illness. Other behaviors may also be relevant. Substance abuse and unsafe sex, for instance, may also vary across groups and produce racial and ethnic differences (Anderson, 1995). These behaviors are of greater concern among younger adults, but they are also relevant for older people. In a British sample of people over 50 years old, for instance, 7 percent reported behavior that put them at risk of contracting sexually transmitted diseases (Gott, 2001), a proportion that could conceivably vary by race and ethnicity in the United States, given variation in sexually transmitted diseases by socioeconomic status. In addition, behavior at younger ages could have long-term health effects or determine which people survive to older ages. Other behaviors, such as suicide, are more directly relevant to older adults, though suicide may be better addressed as a consequence of such factors as depression (Myers and Hwang, 2004). (Preventive health behaviors are considered below in relation to health care.)

As an illustration of the potential effect on differences of a range of other behavior risk factors, consider such a simple behavior—with complex causes—as staying in one's home versus going out regularly. One case shows how this can produce racial and ethnic differences in mortality. A heat wave in Chicago in July 1995 killed at least 521 and possibly as many as 739 people, mostly older adults (Klinenberg, 2002; Whitman et al., 1997). The age-adjusted black death rate was 50 percent higher than the white rate. Hispanic fatalities were so low that a rate could not be calculated. Those most vulnerable proved to be people who lived alone, did not leave home daily, had medical problems, were confined to bed, and had no air conditioning (Semenza et al., 1996). The ethnic difference had much to do with the quality of neighborhood life. Equally poor black and Hispanic neighborhoods were characterized by relatively empty and unsafe versus bustling streets, and few commercial attractions versus animated public spaces. Overall, a pervasive fear of violence in black neighborhoods kept seniors especially indoors, with disastrous results (Klinenberg, 2002). Other behavioral factors can therefore be highly consequential for health differences, and are tied in to neighborhood features, which may in turn have roots in discrimination and lack of social support, factors that we consider further below.

NEEDED RESEARCH

Much is uncertain about the role of behavior risk factors in racial and ethnic differences, leading to a number of important research issues.

Research Need 8: Study how behavior risk factors act over the life course in different racial and ethnic groups.

The effects of behavior among older adults, in contrast to the effects at younger ages, sometimes appear weaker or nonexistent, and carefully designed studies are needed to avoid such pitfalls as inadequate samples and unrecognized selection effects. Behavior does show some consistency over time, but it can also change. The intricacies of attending to cohort and period changes in such factors as smoking, diet, and exercise, their delayed effects on health outcomes in later years, and the differences in these relationships across racial and ethnic groups provide a substantial challenge to researchers.

The possibility that behavior has different effects for different groups needs broader investigation. Work in this area has focused mainly on obesity among blacks and whites, leading so far to inconclusive findings. If different effects can be confirmed, more work would be needed to investigate the possible reasons. Attention is also needed to other ethnic groups, such as Hispanics, for whom obesity may still be risky but possibly proportionally less of a risk: if this is confirmed, it might shed further light on the mechanisms involved.

Variation in behavior risk factors across racial and ethnic groups cannot be accounted for solely by socioeconomic factors. While other factors have been suggested, especially acculturation, these are probably insufficient to account, for instance, for the relatively unhealthy behaviors among American Indians and Alaska Natives and blacks. Such problematic conditions as obesity among black women need to be better understood. The reasons for the high rates, and the reasons that obesity sometimes appears to have proportionally less effect than in other groups, need to be clarified. Cutler et al. (2003) argue that overweight and obesity have increased most among those, often women, who have benefited most from technological innovations that have made foods more convenient and reduced food preparation effort. Whether this argument has anything to do with the obesity problems among black women deserves exploration.

The role that social context—families, peer groups, neighborhoods, communities—plays in such contrasts, and generally in deterring healthy behavior and facilitating risky behavior, deserves further study. For instance, how are neighborhood factors related to racial and ethnic composition? Are neighborhood factors simply socioeconomic in origin, or are there modifiable features that could be made more favorable to healthy behavior even in the absence of reductions in poverty? Systematic data on neighborhoods could be collected (Morenoff and Lynch, 2004; Raudenbush and Sampson, 1999), and geographical analysis of national data sets could focus on “very small areas” (Bond Huie et al., 2002; see also Chandra and Skinner, 2004).

The focus of research in this area has been largely on blacks and whites, and, to a lesser extent, on Hispanics. Work is desirable to clarify behavioral differences for the other major groups—American Indians (particularly on reservations) and Asians, as well as subgroups of these groups. The behavior of these two groups appears to provide clear contrasts with whites, but the analysis necessary to determine whether these contrasts are at root socioeconomic has not been done. Does acculturation affect the behavior of these groups in the same way it affects Hispanics? If this could also be determined, one might have further clues to how the negative behavioral effects of acculturation might be arrested. Within the major racial and ethnic groups, subgroups may differ in behavior risk factors, which is worth attending to for the clues it might provide about the reasons for and the consequences of behavioral variation.

None of the group contrasts should be assumed to be static. Socioeconomic change and acculturation modify behavior over time. Trends in behavior risk factors for racial and ethnic groups require continued monitoring. The trends are not all benign, and the reasons for them are certainly not well understood.