Effects of spouses' socioeconomic characteristics on mortality among men and women in a Norwegian longitudinal study
Introduction
In research on health inequalities among couples, several studies have examined the influence of partner's socioeconomic (SE) characteristics on one's health (Bartley, Martikainen, et al., 2004, Jaffe et al., 2006, Martikainen, 1995, Monden, 2003). Different SE measures have been utilized as indicators of spouse's SE position (SEP), most importantly education, occupation and income. The effect of spouse's educational attainment has been investigated most often (Jaffe et al., 2006, Monden, 2003), especially the influence of wife's characteristics on husband's health (Bosma et al., 1995, Egeland et al., 2002). Wives' low education has been shown to be positively associated with increased risk of mortality and cardiovascular disease (CVD) in their husbands (Bosma et al., 1995, Jaffe et al., 2005), whereas for women's CVD mortality, husband's education has little effect (Jaffe et al., 2006). Partner's education has also been shown to influence own self-reported health, and to exert an indirect effect through household income and neighbourhood characteristics (Monden, 2003).
Only a few studies have looked at the effects of partner's occupation and income. Husband's class and employment status, together with material conditions, were found to influence women's self-assessed health, but not long-standing illness (Arber, 1997). Another study (Bartley, Martikainen, et al., 2004) found effects of husband's social class on behavioural risk factors in women, but no reciprocal effects for wife's class. Elevated spousal income increased men's odds of dying, while the inverse was true for women (McDonough, Williams, House, & Duncan, 1999). Among Finnish elderly, spouse's education, occupation and household income was associated with mortality (Martelin, 1994). In a comparison of effects of own and spouse's education and occupation on cause-specific mortality differentials among Finnish women, own and spouse's indicators were found to be more or less equally strong predictors (Martikainen, 1995).
The findings of these studies imply that spouse's SE characteristics should be taken into account in addition to own SE indicators, in order to assess the effects of SE factors on health to their full extent (Martikainen, 1995, Monden, 2003). However, in previous studies only one or two spouse characteristics have been scrutinized, or a household income variable employed. Recently, attention has been drawn to the distinct meaning of the three main SE indicators, since each indicator explains different aspects of the SEP (Bartley, 2004, Geyer et al., 2006, Næss et al., 2005). It has also been suggested that these indicators be analysed in combination to compare the magnitude of their gross and net effects on health (Braveman et al., 2005, Geyer et al., 2006, Lahelma et al., 2004). To our knowledge, however, no previous study has assessed the relative importance of the several different indicators among couples.
The purpose of the present study is to compare the relative effects of three partner's SE indicators (education, occupational class and income) on women's and men's mortality, using linked data from the Nord-Trøndelag Health Study (HUNT 1). We assess if and to what extent partner's SE characteristics influence one's mortality. Secondly, we examine whether the effect of spouse's education is mediated by spouse's occupation. We investigate whether the effect of spouse's occupation on mortality is mediated by spouse's income; or whether the effect of partner's occupational class is direct. In addition, we compare the relative importance of partner's characteristics for specific causes of mortality.
Section snippets
Materials and methods
The Nord-Trøndelag Health Study (HUNT 1, 1984–1986) is based on a cross-sectional survey in a county population in middle Norway (www.hunt.ntnu.no). All inhabitants of the county aged 20 years or more were approached and 74,599 persons participated (88.1 % of the adult population). Our study is restricted to married men (18,100) and women (23,046) aged 24 years or older who were linked via family registry to their spouses who participated in the same survey. The linkage of the sample to the
Results
Men were more educated and had higher incomes than women (Table 1a, Table 1b). The occupational distribution varied substantially between the sexes: 2% of the men and 23.6% of the women could not be assigned to any class according to the EGP scheme. Correlations between the various SE variables were moderate. In women, the correlation between husband's education and occupation was r = 0.44, for husband's education and income it was r = 0.39, and for husband's occupation and income, r = 0.31. For men,
Discussion
In this study, we compared the relative importance of three spouses' SE indicators to mortality for both genders. All husband's SE indicators were associated with women's mortality to a similar but rather small extent, whereas in men, only wife's education mattered – particularly large risk ratios according to wife's education were observed at older ages. Husband's occupation was mainly associated with ischemic heart disease and lung cancer mortality in women. Wife's education was the strongest
Summary and conclusion
In households, people pool and exchange their resources in order to maximize their well-being. Because many of these resources are health-relevant, married people tend to be healthier than non-married people. Our findings suggest that women's level of education adds more to the household's resources than men's education – perhaps because women spend more time in the household, and have household roles which benefit from education, such as nutritional care and organisation of home life. It is
Acknowledgments
The authors gratefully acknowledge helpful comments from Johan Mackenbach, Kristen Ringdal, Graham Scambler and four anonymous referees. The Nord-Trøndelag Health Study (the HUNT Study) is a collaboration between the National Health Screening Service of Norway, Oslo, the National Institute of Public Health, Community Medicine Research Unit, Verdal, the Nord-Trøndelag County Council and the Norwegian University of Science and Technology (NTNU).
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