Full-length ArticleDoes education lower allostatic load? A co-twin control study
Introduction
A large and growing literature has examined the relationship between education and health (Albouy and Lequien, 2009, Amin et al., 2015, Arendt, 2005, Behrman et al., 2011, Buckles et al., 2013, Clark and Royer, 2013, Fonseca and Zheng, 2011, Fujiwara and Kawachi, 2009, Gruenewald et al., 2012, Jürges et al., 2013, Lleras-Muney, 2005, Lundborg, 2013, Lundborg et al., 2012, Madsen et al., 2014, Manor et al., 2004, Mazumder, 2008, Meghir et al., 2012, Rosengren et al., 2009, Spasojevic, 2010, Strand and Tverdal, 2004, van Kippersluis et al., 2011, Webbink et al., 2010). Findings include that education is associated with better self-reported health (Amin et al., 2015, Fujiwara and Kawachi, 2009, Lundborg, 2013), lower mortality (Buckles et al., 2013, Lleras-Muney, 2005, Manor et al., 2004, van Kippersluis et al., 2011), greater longevity (Lundborg et al., 2012), lower odds of hypertension and diabetes (Fonseca and Zheng, 2011), reduced risk for acute myocardial infarction (Rosengren et al., 2009), and fewer chronic conditions (Lundborg, 2013).
An important index of health that has also been found to correlate with education is allostatic load. This term captures the cumulative toll of dysregulation across major physiological systems, including the cardiovascular, endocrine, metabolic, hypothalamic–pituitary–adrenal (HPA), sympathetic, and immune systems (McEwen, 2000, Taylor et al., 2011). Allostatic load is based on the concept of allostasis, which refers to bodily changes in response to environmental demands. An example of allostasis is the fact that bears prepare for winter by eating larger amounts of food and gaining body fat. Allostasis thus represents an effort to adapt to the environment. But when environmental stressors are chronic or persistent, ongoing adaptational efforts can lead to physiological dysregulation. Allostatic load captures the cumulative burden of this dysregulation, which is “the price the body pays” for adaptation (McEwen, 2000; p. 110).
Of relevance to the current study, low education is a marker of socioeonomic stress and may thus take a toll on physiological functioning (e.g., Gruenewald et al., 2012). A few studies have specifically examined the association between education and allostatic load (e.g., Gruenewald et al., 2012, Kubzansky et al., 1999), and additional investigations have documented socioeconomic gradients in specific health indices that can be considered measures of allostatic load (e.g., markers of inflammation; Loucks et al., 2010, Pollitt et al., 2008). Collectively, these studies indicate that higher levels of education are associated with a lower allostatic load, denoting a healthier profile. The findings are consistent with the rest of the literature in showing that higher levels of education are related to better health.
Several explanations exist for the association between education and better health, including that (1) more educated individuals are more health–literate and health–conscious (Buckles et al., 2013), (2) more educated individuals are better positioned to access health resources, including high-quality medical care (Buckles et al., 2013, Lundborg, 2013), (3) low education is a marker of socioeconomic adversity, which has been proposed to up-regulate pro-inflammatory genes and down-regulate antiviral genes, increasing risk for disease (Cole, 2013), and (4) unobserved factors, such as one’s genetic endowment and familial upbringing, account for the association between education and health (Amin et al., 2015, Madsen et al., 2014). Methodologically, it is challenging to adjudicate between these various causal and non-causal hypotheses. Several studies have used sophisticated methodologies, such as instrumental variables or twin designs, to interrogate causal claims. Whereas some of these studies have found enduring evidence for an effect of education on health after taking steps to control for confounding influences (Buckles et al., 2013, Fonseca and Zheng, 2011, Lundborg, 2013, Lundborg et al., 2012, Spasojevic, 2010, van Kippersluis et al., 2011), others have concluded that evidence for a causal link is limited and not particularly compelling (Albouy and Lequien, 2009, Amin et al., 2015, Behrman et al., 2011, Clark and Royer, 2013, Fujiwara and Kawachi, 2009, Madsen et al., 2014, Mazumder, 2008).
The discordant twin design is especially useful for investigating causality in observational research (McGue et al., 2010). This design examines if differences in an exposure variable (e.g., education) within twin pairs are associated with an outcome of interest (e.g., health). The strength of the design is that it controls for all familial contributions to the exposure. Thus, in the case of monozygotic (MZ) twins who are genetically identical, the design would control for all confounds related to the rearing environment as well as all genetic confounds. In the case of dizygotic (DZ) twins who share about 50% of their genes on average, the discordant twin design would partially control for genetic factors while fully controlling for other familial factors. Seven discordant twin studies have examined the association between education and health so far. Results are mixed overall, with four studies (Amin et al., 2015, Behrman et al., 2011, Fujiwara and Kawachi, 2009, Madsen et al., 2014) indicating that shared familial factors largely account for the association between education and health, two studies (Lundborg, 2013, Lundborg et al., 2012) finding a residual causal effect, and one study (Webbink et al., 2010) suggesting the causal effect is evident only in men. In general, existing studies find that education may result in better self-rated global health (i.e., how participants rate their health overall; Amin et al., 2015, Fujiwara and Kawachi, 2009, Lundborg, 2013). Evidence for a causal effect of education on more specific measures of health (e.g., body-mass index or cardiovascular disease) or health-related behaviors (e.g., smoking) is much more limited.
Most studies have relied on survey data, hospital records, or registries in inferring health status (e.g., Amin et al., 2015, Behrman et al., 2011, Fujiwara and Kawachi, 2009, Lundborg, 2013, Lundborg et al., 2012, Madsen et al., 2014, Webbink et al., 2010), and no twin study so far has included direct biological measures of health. The current study builds on the extant literature by examining the relationship between years of education and a direct, multi-system measure of allostatic load that captures dysregulation across the cardiovascular, inflammation, metabolic, HPA, sympathetic, and parasympathetic systems. No prior studies of education and allostatic load have used a discordant twin design. Thus, ours is the first discordant twin study to investigate the causal nature of the relationship between education and health using directly measured biomarkers from multiple regulatory systems.
Section snippets
Participants
Data come from the MIDUS study, which examines physical health, psychological wellbeing, and social responsibility throughout midlife. The MIDUS sample is representative of non-institutionalized English-speaking adults living in the United States. Participants were recruited through random-digit dialing in 1995–1996 and were assessed via a 30–45 min telephone interview and two self-administered questionnaires that were mailed to individuals. Available participants were re-assessed in 2004–2006.
Analytic plan
We first examined the association between education and allostatic load in an individual-level regression analysis. This analysis yields the individual-level effect of exposure (i.e., education) on outcome (i.e., allostatic load), without controlling for genetic or other familial confounding. Next, we applied a co-twin control (CTC) design that has been previously employed to strengthen causal inference in observational twin research (e.g., Burt et al., 2010, Huibregtse et al., 2011, Irons et
Descriptive statistics
Table 3 presents demographic statistics for the current sample, as well as for the total biomarker sample. As can be seen from the table, participants included in the current study were representative of the larger biomarker sample from which they derived in terms of age, sex, education, and allostatic load.
Preliminary analyses
Preliminary correlational analyses show that our composite, biologically based measure of allostatic load was moderately correlated with various self-report measures of health (e.g., it
Discussion
The existing literature indicates that education is positively associated with health, though it is unclear whether this relationship is causal. Several studies have used sophisticated methodologies, such as instrumental variables or twin designs, to investigate causality. They have produced rather conflicting findings, with some supporting a causal relationship and others failing to do so. A few studies have found that education may result in better self-rated global health (Amin et al., 2015,
Acknowledgments
The MIDUS study was supported by the John D. and Catherine T. MacArthur Foundation Research Network on Successful Midlife Development and by the National Institute on Aging Grant AG20166.
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