Abstract
Schooling generally is positively associated with better health-related outcomes—for example, less hospitalization and later mortality—but these associations do not measure whether schooling causes better health-related outcomes. Schooling may in part be a proxy for unobserved endowments—including family background and genetics—that both are correlated with schooling and have direct causal effects on these outcomes. This study addresses the schooling-health-gradient issue with twins methodology, using rich data from the Danish Twin Registry linked to population-based registries to minimize random and systematic measurement error biases. We find strong, significantly negative associations between schooling and hospitalization and mortality, but generally no causal effects of schooling.
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Notes
Many studies have considered such possibilities, some of which have focused on the relative schooling (and other aspects of socioeconomic status) effects on health (e.g., Adams et al. 2002; Adler et al. 1994; Brooks-Gunn et al. 1997; Case et al. 2002a, b; Deaton 2001a, b; Deaton and Paxson 1998, 1999, 2001; Elo and Preston 1992, 1996; Kawachi et al. 1999; Marmot 1999; Mellor and Milyo 2002; Preston 1975; Preston and Elo 1995; Ross and Mirowsky 1999; Smith 1999; Strauss and Thomas 1998; Wilkinson 1992, 1996, 2000). Most of these studies did not control for the endogenous choice of schooling, but a relatively few studies did (see the Previous Related Studies section).
Many studies have documented the association of genetic endowments with physical and mental health (e.g., Amouyel et al. 1996; Bartres-Faz et al. 2000; Chen et al. 2001; Christensen et al. 1995, 1998, 2000a; Clee et al. 2001; Eicher et al. 2002; Forsberg et al. 2002; Frosst et al. 1995; Humbert et al. 1993; Jenny et al. 2002; Jiang et al. 2001; Kelly et al. 2002; Kluijtmans et al. 1996; Morita et al. 1997; Myllykangas et al. 2001; Pericak-Vance and Haines 1995; Roses 1998; Sawano et al. 2001; Voetsch et al. 2002). For simplicity, we represent the endowments here as if they were scalars. However, they may be vectors with different components, for example, that differentially affect schooling versus health and that are not perfectly correlated and, indeed, not necessarily positively correlated. In fact, some recent studies have suggested that innate education and health components of endowments may be negatively correlated (Behrman et al. 2008; Behrman and Rosenzweig 2004).
This formulation is consistent with standard models of intrahousehold allocation of investments in children (e.g., Becker 1991; Becker and Tomes 1976; Behrman et al. 1982, 1995). Behrman et al. (1994) used a similar formulation with MZ and DZ twins to estimate whether such intrahousehold allocations reinforce or compensate for individual-specific endowment differences among siblings (and found reinforcement).
In general, endowments of all members of a sibship affect the investments in any member of the sibship, but the effects of all siblings other than the other twin drop out in the within-twin estimators because the characteristics of other siblings are the same for the two members of a twinship. We expect the direct effect to be greater than the cross effect (α a > α s ). If the coefficient of the cross effect is positive, there is compensating behavior in that parents invest more in sibling j if sibling k is better endowed. If the coefficient of the cross effect is negative, there is reinforcing behavior (i.e., reinforcing endowment differences) in that parents invest less in sibling j if sibling k is better endowed. In the within-MZ estimator, the two twins have identical individual-specific endowments, so a ij and a kj cancel out. The only estimates of which we are aware that are consistent with this framework and that estimate the cross-twin effect using a combination of MZ and DZ twins indicated reinforcing behavior (Behrman et al. 1994).
Differences in birth weights between MZ twins have been used to estimate the impact of in utero nutrition on subsequent life cycle outcomes, but such differences could be due to factors such as differential placement in the womb relative to the placenta even if the two members of a twinship were identical at conception (e.g., Behrman and Rosenzweig 2004; Conley et al. 2006). However, for some observable outcomes for which MZ twins are discordant in a few percent of births, such as congenital malformations, some studies suggested that the differences originate at least in part in differences in genes, perhaps related to the process of twinning (e.g., Hall 2003; Kondo et al. 2002; Lubinsky and Hall 1991), and not just in the environment in the womb. For such reasons, within–MZ twins estimates may not control perfectly for endowments at conception (as we assume herein), but they nevertheless control better than other options for such endowments.
Amin et al. (2010) tested for the impact of this possibility by including birth weights in their estimates and found that this does not change their estimates of the schooling coefficient substantially.
In their discussion, they state: “In summary, the current study showed possible causal effects of education on perceived global health and on smoking habits among males, but did not suggest direct associations between schooling and the other health outcomes studied.” (Fujiwara and Kawachi 2009:1320). The significant outcomes for males to which they refer, however, did not occur in within-MZ estimates, but only in within-MZ and -DZ combined estimates.
Lundborg (2008) also explored the impacts of schooling on health-related behaviors and reported little evidence of significant impacts.
This has been a valuable source of data for study of a number of biomedical, biodemographic, and socioeconomic topics. For more information and some examples, see Andersen-Ranberg et al. (1999); Bingley et al. (2009); Christensen et al. (1995, 1996, 1998, 1999, 2000b); Gaist et al. (2000); Hauge (1981); Kohler and Kohler (2002); Kohler and Rodgers (1999, 2000); Kohler et al. (1999, 2001, 2002, 2003, 2005); Kyvik et al. (1996); Rodgers et al. (2008); and Skytthe et al. (1998, 2002). Some have been concerned that twins have a different health and aging trajectory profile owing to the fact that they experience growth restrictions in the womb, but extensive tests generally have found no differences in health and aging trajectories between twins and singletons in high-income populations (Christensen and McGue 2008).
The data includes birth cohorts up to 1975, but we limit this analysis to the 1921–1950 birth cohorts because the dependent variables on which we focus are primarily relevant for older adults.
If migration or early mortality is affected by endowments that also affect schooling and the health outcomes that we study, the inability to include individuals who migrated or experienced early mortality biases the estimated impact of schooling on health using standard OLS individual estimates. However, within–MZ twins estimates control for the first-order effects of such endowments and thus do not suffer from the same biases of sample selection due to endowment-related migration or early mortality as do OLS estimates.
The hypothesis of equal means for men and women is rejected at with a p value of .016 for the cohort 1921–1935, but the means for men and women are not statistically different for the 1936–1950 cohort.
The Ns are slightly smaller for this variable than for the other two because of some mortality in 1980–1982 (see Table 1).
We use “years of schooling,” as is conventional in this literature, to mean the years of schooling required to attain a given level or grade of schooling with full-time school attendance and no grade repetition or skipping. If there is grade repetition or part-time attendance, the calendar years attending school may exceed the years of schooling as we use the term (and if there is skipping of grades, the reverse may hold).
Both individual population census self-reports and education institution reports are for training undertaken and qualifications attained. The Ministry determined which is the highest qualification separately along academic and vocational lines according to “normal” completion times. The data that are available to us are normal completion times for highest qualification achieved. In a few cases where the highest vocational/academic training is unknown in the data, the minimal required years of schooling for these cohorts (= 7 years) was used for years of schooling.
This approach is advantageous relative to an alternative tabulation of schooling differences by average twin pair schooling level because by construction, the mean difference in the years of schooling will tend to become small for twin pairs that have either a very high or very low mean schooling level.
If the correlation in measurement error between siblings (ρ w ) is nonzero, plim
, where 
. Note that the measurement error bias in the within-sibling estimate is decreasing in ρ
w
and is less in the within-sibling estimate than in the standard estimate if ρ
w
> ρ
S
. We are not aware of any estimates of ρ
w
. What appears to be random noise in cross-sectional data may have a family component if the measurement error is due to such unobserved factors as exaggeration or modesty or to failure to control for school quality, all of which may be shared by siblings.With the alternative specifications in the Appendix (Tables 8 and 9), the differences between the cross-sectional estimates and the within-MZ estimates appear even stronger. For example, for the two measures of hospitalization per year both of the cross-sectional estimates are significantly negative at high levels, but in the within-MZ estimates, both of these are positive, although not significant at the .05 level.
Amin et al. (2010) also reported no significant effect of schooling regardless of whether a nonlinear or continuous measure of schooling was used.
, where 
. Note that the measurement error bias in the within-sibling estimate is decreasing in ρ
w
and is less in the within-sibling estimate than in the standard estimate if ρ
w
> ρ
S
. We are not aware of any estimates of ρ
w
. What appears to be random noise in cross-sectional data may have a family component if the measurement error is due to such unobserved factors as exaggeration or modesty or to failure to control for school quality, all of which may be shared by siblings.References
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Acknowledgments
This study is part of a large collaborative project, involving the authors of this article and others, that is supported in part by NICHD Grants HD046144 (“Causal Effects of Schooling on Adult and Child Health”) and HD043417 (“Bio-Social Determinants of Fertility and Related Behaviors”). The authors thank participants at a session in which this article was presented at the 2006 annual meetings of the Population Association of America in Los Angeles, CA; three reviewers; the editor; and Mia Madsen for helpful comments on previous versions of the article.
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Behrman, J.R., Kohler, HP., Jensen, V.M. et al. Does More Schooling Reduce Hospitalization and Delay Mortality? New Evidence Based on Danish Twins. Demography 48, 1347–1375 (2011). https://doi.org/10.1007/s13524-011-0052-1
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DOI: https://doi.org/10.1007/s13524-011-0052-1