Mortality Differentials Research Paper

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Differentials in mortality by socioeconomic status and the nature of social relationships have been well established. In general, persons of higher socioeconomic status (SES) and persons who are more socially integrated experience lower death rates than their respective counterparts. These associations have been found across time, place, and age. Three sets of hypotheses have been proposed by researchers to explain these patterns. The first encompasses causal mechanisms through which socioeconomic status and social relationships potentially affect health status and the risk of dying. A second type of explanation, referred to as selection or reverse causation, pertains to a set of pathways whereby unhealthy individuals may reduce their social position or become socially more isolated as a consequence of their inferior health status. A third explanation relates to artifactual or spurious mechanisms, such as measurement error.

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1. SES And Mortality

Differences in rates of morbidity and mortality by SES have been identified for the vast majority of illnesses, along a social gradient: persons of higher SES fare better than those lower in the social hierarchy (Adler et al. 1993). These differences (a) are present regardless of whether socioeconomic status is defined in terms of income (or other measures of wealth), education, or occupation; (b) exist at every level of the social hierarchy (i.e., not simply between the poor and the nonpoor); and (c) have been documented in a large number of studies in both industrialized and developing countries, based on vital registration, census, and survey data. An individual’s health has been shown to relate not only to absolute income, but also to relative income: greater income inequality in a society is associated with higher mortality. Socioeconomic inequalities in overall mortality are typically smaller among women than men, although there are exceptions for some causes of death (Mackenbach et al. 1999).

Many of the studies have been carried out in the United States or Britain. One that has received wide recognition is the Whitehall Study of British Civil Servants (Marmot et al. 1995). This study has demonstrated that the mortality gradient is present even within a relatively homogeneous group: civil servants in one type of occupation (stable office jobs) and one geographical location (London), but in different grades of employment. Numerous studies in Britain and the US have shown that both countries have experienced widening mortality differentials in recent decades (Pappas et al. 1993).

Many recent investigations have focused on assessing the extent to which causal rather than selective or spurious mechanisms drive the observed socioeconomic inequalities in health. To reduce the impact of selection bias in the statistical analysis, researchers have relied largely on prospective (longitudinal) data; these data generally allow the analyst to measure preexisting conditions that may confound the association between SES and health, and to relate changes in SES to changes in health. There is a general consensus that the observed disparities in health are not driven by social selection, also referred to as social drift. Specifically, while there is some downward drift in SES among persons in poor health (e.g., schizophrenics are apt to lose economic resources), this type of selection is unlikely to be an important part of the association between SES and a wide range of health indicators (see, for example, Davey Smith et al. 1994, Marmot et al. 1995, Macintyre 1997). The findings also suggest that indirect selection mechanisms, i.e., background (or spurious) factors, such as height, that affect both social and health status later in life, are unlikely to be of major importance because the relationships between indicators of SES and health persist in the presence of controls for these background variables (Marmot et al. 1995). Artifactual mechanisms (e.g., errors of measurement, such as census undercounts, ‘numerator-denominator’ problems, such as inconsistencies in reports between registration and census data, or inappropriate measures of mortality or SES) are also not considered to be a powerful explanation of the observed associations.

The rejection of both selection and artifactual explanations has led researchers to conclude that the persistent mortality and morbidity differences by SES result largely from causal processes. Many mechanisms, some of which are interrelated, may be operating. These include differences by socioeconomic status in: (a) access to medical care, both preventive and curative; (b) access to information regarding health risks and health care; (c) patterns of health risk behaviors (such as smoking, drinking, unhealthy diet, and inadequate exercise); (d) exposure to environments that are not conducive to good health and longevity (e.g., poor housing conditions, occupational hazards, pollution, and crime); (e) exposure to stressful situations; (f) access to resources that mediate the physiological consequences of stress; (g) ability to control one’s environment and feel secure about one’s position; and (h) the availability of social relationships and support.

Researchers who have focused on a single mechanism have concluded that multiple pathways almost certainly underlie the observed associations. For example, although the higher death rates experienced by persons of lower SES in several British and American studies have been shown to result in part from higher rates of smoking, poorer diets, and inadequate levels of exercise, these differences in behavior were insufficient to account for the observed mortality differentials (Marmot et al. 1995, Macintyre 1997). Similarly, the widening of mortality differentials by SES between the 1960s and 1980s in Britain and the US—despite the presence of the National Health Service in the former and Medicaid in the latter—has been taken as evidence that the explanation goes beyond inequities in access to medical care.

2. Social Relationships And Mortality

A related area of research has examined the associations between social relationships and health and mortality. These undertakings have concluded that persons who are less socially integrated have higher rates of illness and lower life expectancy than their counterparts. The associations are present for a wide range of causes of death. The possible interpretations of these findings mirror those described above, namely causal vs. selection-type arguments. Causal explanations encompass a broad set of pathways described below. Selection-type arguments posit that unhealthy people are less likely to establish and maintain social relationships or that some other (often difficult to measure) variables reduce a person’s ability to have positive relationships and maintain good health.

As with studies of SES, prospective studies have provided much more convincing evidence than cross-sectional or retrospective studies regarding the importance of causal mechanisms in producing the association between social relationships and health. Findings from surveys have been strengthened by experimental and clinical research which has demonstrated that variations in the degree of social contact have psychological and physiological effects in both animals and humans (House et al. 1988).

2.1 Marital Status And Mortality

The earliest research in the area of social connection and health—dating as far back as the mid-1800s—focused largely on marital status. Since that time, hundreds of studies, primarily in industrialized countries, have demonstrated that married persons have greater longevity and experience better health than single, divorced, and widowed persons. These results hold across time, place, gender, and age, and the differentials have been consistently larger for men than for women. The dominant explanations once again can be classified as causation or selection.

Causal hypotheses, often termed marriage protection in this literature, encompass a broad range of social, psychological, economic, and environmental benefits that are presumed to be associated with having a spouse. For example, the presence of a spouse is hypothesized to: (a) result in greater emotional and social support; (b) lead to higher income; (c) facilitate access to medical information and health services; (d) constrain risk-taking behavior and encourage healthier lifestyles; (e) act as a buffering mechanism in the presence of stress; and (f) substitute for inferior or inaccessible formal health care. Moreover, the termination of marriage—either by divorce or death of a spouse—is believed to lead to higher risks of dying because of the stresses associated with the loss of a spouse (e.g., berea ement effects in the case of widowhood) and the accompanying decline in social and economic resources.

The state of being unmarried may be associated with health disadvantages that extend beyond the absence of an intimate partner: e.g., in societies where marriage is an integral part of one’s social status, persons (especially women) who remain single or get divorced are likely to face discrimination and, consequently, poorer health.

Marriage selection arguments, by contrast, are based on the premise that mentally and physically healthier persons are more likely to marry in the first place, less likely to become widowed or divorced, and more likely to remarry if a previous marriage dissolves. The factors that drive the selection criteria may be far from obvious. For example, spouses may be selected for better health not only through the direct exclusion of mentally and physically ill persons from first marriage or remarriage, but also through a range of criteria that govern mate selection (i.e., indirect selection) such as income, physical appearance (e.g., height, weight, and beauty), health-related habits (e.g., smoking and drinking), and emotional stability.

In line with studies of SES and social connection, analyses focusing on marital status have typically concluded that the associations with mortality are produced predominantly by various benefits associated with having a spouse and not by marital selection. While this conclusion may generally be correct, many of the inferences drawn by researchers have not been justifiable. In addition, selection appears to be the dominant source of the observed differentials in at least one population (described below).

Two types of problems of inference have been noted. The first is that demographers have often based their arguments on cross-sectional data. In particular, some demographers have reached conclusions about the importance of marital selection on the basis of aggregate patterns of mortality by marital status, e.g., age patterns of mortality differentials and the direction and strength of the relationship between the magnitude of the mortality differential and the relative size of the single population. Results from a simple simulation model demonstrate that the resulting inferences are not justifiable because both causal and selection processes could lead to the same aggregate patterns of mortality (Goldman 1993a).

The second type of weakness pertains to unjustifiable inferences derived from prospective data. Although these data have permitted researchers to conclude that the health benefits of marriage (or of higher socioeconomic status) persist in the presence of controls for selection, they have also led some to argue that selection mechanisms are unimportant. The latter conclusion has generally been unwarranted: existing statistical analyses frequently include controls for selection processes, but most were not designed to measure the impact of selection. Only in the past few years have demographers used longitudinal data to directly assess health-related selection into first marriage and into divorce. These studies have demonstrated that health-related characteristics and behaviors are used (explicitly or implicitly) as selection criteria for marriage and divorce. For example, in the US, users of illicit drugs, heavy drinkers, and obese persons have lower marriage rates than their respective counterparts (Fu and Goldman 1996).

Perhaps because demographers (like other social scientists) have been most interested in identifying causal mechanisms, they have failed to recognize that the impact of selection on mortality differentials by marital status is likely to vary across time and place. A recent study of atypically high mortality among nevermarried Japanese demonstrates this point clearly. Data from a variety of sources strongly suggest that the Japanese arranged marriage process, which was still widely prevalent in the mid-1900s, appears to be largely responsible for the huge disadvantages in longevity (10–15 years) faced by single Japanese during the period 1950–80. Several characteristics of arranged marriages are particularly noteworthy in this context: the importance of mental and physical health in the choice of a potential spouse; the inclusion of family, friends, go-betweens, and even private detectives in the selection of a mate; and, the efficiency of the marriage process (Goldman 1993b).

3. Future Directions

In spite of extensive research focusing on mortality differentials by socioeconomic status and by the nature of social relationships, relatively little is known about the relative importance of different pathways in producing the associations. Two current trends in data collection are likely to increase scientists’ understanding of these linkages in the future. The first is the increasing richness and detail of longitudinal surveys in the social sciences. The second is the inclusion of biomedical markers (e.g., obtained from blood or urine samples or physician’s exams) in social and demographic surveys. By identifying some of the biological pathways relating aspects of the social environment to physiological outcomes (such as neuroendocrine response, immune function, and cardiovascular function), social scientists may be more successful in elucidating the complicated linkages that underlie the observed mortality differentials.


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