Abstract Background and Objectives The current study assesses the unique influences of family economic hardship (FEH) in early and late midlife on husbands’ and wives’ body mass index (BMI) and the influence of BMI on the onset of cardiometabolic (CM) disease in later adulthood. The protective role of marital integration is also considered in relation to the stress-response link between FEH and BMI. Research Design and Methods Analyses were performed using structural equation modeling with prospective data from 257 husbands and wives in enduring marriages over a period of 25 years beginning when they were approximately 40 years old. A multigroup analysis tested the moderating role of marital integration. Results The distal influence of FEH in early midlife on BMI in later adulthood remained statistically significant even after controlling for proximal FEH. Proximal FEH in later midlife was influential for wives’, but not husbands’, BMI. BMI in later midlife was related to the onset of CM disease in their later life. Moderation analysis showed that FEH and subsequent BMI were associated for couples with below average levels of behavioral integration but not for couples with above average levels of integration. Discussion and Implications Taken together, these findings suggest a family-health process stemming from early FEH and operating cumulatively over the life course. FEH in early midlife is a persistent determinant of physiological dysregulation as reflected by BMI. Findings identify BMI as a modifiable leverage point for the long-term reduction of CM disease risk and highlight the role of spouses as a buffer against the detrimental stress–health association. Health, Heart disease, Life course/life span, Economics, Body mass index, Marriage Although midlife, defined as ages 40–50, is generally considered a time of relatively good health (Lachman & James, 1997), an increasing number of studies have shown that it is a life stage with a notable increase in physical health problems. Chronic disease onset is relatively common in midlife, and there is an increase in interindividual health differences (Lorenz, Elder, Bao, Wickrama, & Conger, 2000; McDonough & Berglund, 2003). Specifically, high body mass index (BMI) and associated cardiometabolic (CM) diseases often accelerate over middle and later years (Mezuk, 2009). Increasing chronic disease risk and health inequalities may be partly attributed to men’s and women’s stressful life experiences at previous life stages (Lorenz, Wickrama, Conger, & Elder, 2006; Wickrama et al., 2001). Family economic hardship (FEH) is a particularly powerful stressor that exerts a persistent influence on CM disease risk (Jones et al., 2009; Levine, 2011). FEH and CM Health Chronic and repeated economic hardship results in frequent activation of physiological systems leading to the dysregulation of multiple body systems over time, also known as “weathering” (Geronimus, Hicken, Keene, & Bound, 2006). This dysregulation is observable through various biomarkers, including elevated BMI (McEwen & Gianaros, 2010). More specifically, previous research has shown that life stressors activate the hypothalamic–pituitary–adrenocortical axis and the sympathetic-adrenal medullary system leading to increased neuroendocrine and cardiovascular reactivity along with decreased immunological functioning (McEwen & Gianaros, 2010; Nealey-Moore, Smith, Uchino, Hawkins, & Olson-Cerny, 2007) and the accelerated production of proinflammatory cytokines (Kiecolt-Glaser et al., 2005). High BMI partly reflects these physiological dysregulations, which increase the likelihood of CM disease onset (Dyer, Stamler, Garside, & Greenland, 2004; Glei, Goldman, Chuang, & Weinstein, 2007; Wang & Nakayama, 2010). Yet, even though research documents the cumulative physiological influence of FEH, previous research has rarely investigated the long-term, persistent health influence of FEH over the adult life course using prospective data. We draw our overall theoretical framework from the life course stress process perspective (Pearlin & Skaff, 1996), which combines the stress–health connection emphasized in stress theory with the life course perspectives’ emphasis on taking a “long view” and considering resources as moderators. The life course stress process perspective entails two basic premises. First, early stressors proliferate into later stressors, and these distal and proximal stressors independently contribute to health problems over the life course. That is, health in later adulthood is thought to reflect a lifetime of past experiences (Glymour, Ertel, & Berkman, 2009). This is consistent with the cumulative disadvantage notion (O’Rand & Hamil-Luker, 2005) and cumulative biological models (Glymour et al., 2009); in that, distal stressors are expected to have a cumulative influence on later health outcomes. Accordingly, as shown in Figure 1, we expect that FEH in early midlife proliferates as continued FEH in later midlife, and both of these stressors independently contribute to individuals’ physiological dysregulation (as evidenced by a high BMI) through stress-response mechanisms (McEwen & Gianaros, 2010). Consequently, consistent with biobehavioral research, we expect high BMI, as an indicator of this dysregulation, is ultimately a predictor of cardiovascular and metabolic disease onset (Dyer et al., 2004; Glei et al., 2007; Wang & Nakayama, 2010). Second, as shown in Figure 1, the life course stress process perspective contends that psychosocial resources may moderate the stress-response connection between stress exposure and health consequences. Thus, we posit that the connection between FEH exposure and physiological response, as reflected by BMI, will vary depending on marital context, specifically, couple’s marital integration. Figure 1. View largeDownload slide A life course stress process perspective linking family economic hardship and cardiometabolic disease. Figure 1. View largeDownload slide A life course stress process perspective linking family economic hardship and cardiometabolic disease. Distal and Proximal Effects of FEH Consistent with the “historical timing” concept from the life course perspective (Elder & Giele, 2009), we situate our study by considering that husbands and wives comprising the current sample are from the Midwest and belong to the baby boom cohort. Consequently, many of these families faced chronic FEH from the “farm crisis” of the 1980s (Elder & O’Rand, 1995), which included chronically low prices of agricultural products, unemployment, low income, indebtedness, as well as displacement from their communities for many families (Lorenz et al., 2000) during their early middle years. Regardless of whether these families “escaped” from early FEH and experienced more favorable socioeconomic conditions after midlife, the distal association between earlier FEH and BMI is expected to persist. That is, midlife FEH is thought to create stressful life circumstances (e.g., work stress) and amplify the effects of more normative stressors experienced during this life stage (e.g., burden of child rearing, caring for aging parents) resulting in physiological repercussions (evidenced through high BMI). The symptoms of physiological damage stemming from early FEH, such as elevated BMI, may persist over the life course. Alternatively, according to “latency models” (Meaney et al., 1996), the effects of FEH at one life stage (e.g., early midlife) may not manifest until several years after the exposure. Relatedly, FEH in early midlife may result in a lack of health resources (e.g., medical checkups, care, treatments, and information required to initiate and maintain a healthy lifestyle) placing these individuals at increased risk for the development of poor health in the years (Singh-Manoux, Ferrie, Chandola, & Marmot, 2004). While the lack of health resources likely influences physical health outcomes primarily through behavioral mechanisms (e.g., unhealthy eating) (Schade, Sandberg, & Busby, 2014), affective mechanisms (e.g., elevated depressive symptoms) may also explain why FEH in early midlife has subsequent detrimental physical health consequences, particularly related to elevated BMI (Wickrama et al., 2017). Although it is important to acknowledge related behavioral and affective mechanisms, the current study does not aim to specifically identify the unique influence of these mechanisms. Instead, the current study aims to assess the total effect of FEH in early midlife on high BMI a decade later and subsequent onsets of CM diseases in the later years. In addition to the distal effects of FEH in early midlife on BMI in later midlife, we also expect FEH in later midlife may exert a significant influence on BMI (i.e., a proximal association), independent of early midlife FEH for several reasons. First, although early FEH may disappear, new age-graded economic difficulties may arise in later midlife (e.g., supporting young adult children financially). That is, consistent with the concept of “life cycle squeezes” (Oppenheimer, 1974), the impact of early FEH may vary across stages of the life course, depending on the family needs. Second, individuals who experienced stressful life events may have developed heightened stress sensitivity in later years through stress sensitization or potentiation processes (Dich et al., 2015; Grabe et al., 2012; Loman & Gunnar, 2010). Thus, we expect that later midlife FEH will have a significant proximal influence on husbands’ and wives’ high BMI. Previous research has not adequately investigated this type of cumulative biological model in relation to FEH and CM health in older adult populations. Furthermore, consistent with the contagion perspective, weight gain, or increasing BMI, can be “induced” and can “spread” from one partner to the other (Cacioppo, Fowler, & Christakis, 2009). This contagion may be attributed to common or shared health risk behaviors, such as poor eating behavior, lack of exercise, and excessive drinking. This contagion could create dependencies, or bivariate simultaneous associations, between husbands’ and wives’ BMI outcomes. Protective Role of Marital Integration Consistent with the stress process perspective’s emphasis on psychosocial attributes as buffers, or protective factors, that may offset the negative stress–health effect, recent research suggests that marital integration may protect husbands and wives from the detrimental health impacts of stressful life experiences, including FEH (Bryant, Wickrama, O’Neal, & Lorenz, 2017). In the present study, we focus specifically on behavioral integration between couple members, assessed by their joint participation in pleasurable activities that couples often do together, including hobbies, socialization with friends, going out, and overnight trips. We argue that the extent to which couples engage in these joint activities is not only a proxy for their behavioral closeness, but is also an indicator of marital strength, which at least partly reflects various marital attributes, including social connections, mutual support, caring, common interests and attitudes, marital stability, and effective communication. That is, couples who lack these marital strengths likely exhibit low levels of behavioral integration. For this reason, we expect that couples with a high level of marital integration may be protected from the adverse health influence of FEH. This may be attributed to their weakened emotional and physiological responses to stress stemming from their tendency toward less negative appraisals and insulation from stressors. The marital relationship may be a particularly salient protective factor given the long-standing nature of the relationship for this sample of couples in enduring marriages (spanning an average of 44 years by the last measurement occasion in 2015). There is also support for the protective role of marital integration from interdependence theory (Kelley & Thibaut, 1978) and emotional investment perspectives (Berscheid, Snyder, & Omoto, 1989), which emphasize that couples who exhibit more behavioral closeness (an indicator of a healthier marital functioning) are often interdependent with one another and emotionally invested in each other’s well-being (Knobloch & Solomon, 2004). Couples’ emotional investment and interdependence may serve as a resourceful context for husbands and wives—a context under which they can more effectively cope with FEH. Thus, we hypothesize that the association between FEH and BMI, which is largely a stress response process, will be moderated by marital integration. However, to our knowledge, previous research has not investigated the protective role of marriage in this manner as it relates to the association between FEH and BMI of husbands and wives in enduring marriages. Findings from the current study have important implications for health policies and programs as the findings can help identify the long-term significance of FEH for CM health throughout the adult years for older adults in enduring couple relationships. Elucidating the stress-response mechanisms linking FEH and CM disease can inform prevention and intervention programs suggesting modifiable factors, such as weight management, as leverage points for reducing the prevalence of CM disease. Also, findings will shed light on the acceleration of CM disease onset for members of the baby boom cohort who are now past midlife and currently in later adulthood. Furthermore, findings related to the moderating role of couples’ marital integration will aid counselors and program/policy planners as they identify marital attributes that may protect couples from the negative health consequences of FEH. The Present Study The current study addresses limitations of previous research using prospective data collected from husbands and wives in 257 enduring marriages over a period of 25 years (1991–2015) with a sample of consistently married couples who were parents of early adolescents in 1991 when they were in their early middle years (approximately age 40). As shown in Figure 1, the distal influence of early midlife FEH and the proximal influence of late midlife FEH (approximately age 50) on BMI and the subsequent onset of CM disease in their late life (65 years or more) is assessed. The protective role of couple’s marital integration is also considered in relation to the link between FEH and BMI using a multigroup approach (i.e., an “above mean,” or high integration, group and a “below mean,” or low integration, group). Analyzing dyadic models of husbands and wives allows for consideration to be given to the dependency between spouses. Specific Hypotheses Early midlife FEH (1991) will be associated with increased BMI (2001) for husbands and wives a decade later, which, in turn, will be associated with the onset of CM disease in later adulthood (2015) (distal effect). Independent of early midlife FEH (1991), FEH in later midlife (2001) will be associated with husbands’ and wives’ elevated BMI (2001) (proximal effect). Husbands’ and wives’ BMIs in later midlife (2001) will be contemporaneously associated. Couples’ marital integration (averaged across 1991 and 1994) will act a protective factor to insulate husbands and wives from the detrimental influence of FEH in early and later midlife (1991 and 2001) on BMI in 2001. In other words, marital integration will moderate the stress-response associations between FEH and BMI. Design and Methods Respondents and Procedures The data used to evaluate these hypotheses are from the Family Transition Project (FTP), the Midlife Transitions Project (MTP), and the Later Adulthood Study (LAS). Together, these projects comprise a 27-year panel study of rural families from a cluster of eight counties in north-central Iowa closely mirroring the economic diversity of the rural Midwest (1989–2015). The FTP represents an extension of the earlier the Iowa Youth and Family Project (IYFP) (Conger & Elder, 1994), which began in 1989 as a study of rural couples with children, at least one of whom was a seventh grader in 1989. Families meeting the selection criteria were enumerated through contacts with public and private schools and then randomly selected and recruited into the study, with 78% of the married couples and 99% of the single mothers agreeing to participate (Conger & Elder, 1994). Parents from the FTP participated in the MTP in 2001 and the LAS in 2015. The median yearly family income in 1989 was $33,240 (ranged from $0 to $259,000). In terms of employment, the most common occupations for men in the sample included: craftsmen, foremen, and farmers (38.4%); professionals, managers, owners, and officials (23.8%); and operatives and kindred workers (16.6). Nineteen percent of the wives were homemakers. The most common employments for women included sales workers, clerical, service workers, and private household workers (46.1%) and professionals, managers, owners, and officials (23.7%). In 1991, the first measurement occasion utilized in the current study, spouses were in their early middle years; the average ages of husbands and wives were 42 and 40 years, respectively, and their ages ranged from 33 to 59 for husbands and 31 to 55 for wives. On average, the couples had been married for 19 years and had three children from their marriage together. The median age of the youngest child was 12. In 1989, the average number of years of education for husbands and wives was 13.68 and 13.54 years, respectively. Because there are very few minorities in the rural area studied, all participating families were White. The 257 couples in the current study are those who participated in 1991, 1994, 2001, and 2015 data collections and were consistently married throughout the study period. Data in 1991 were used as the first time point for the current study due to the availability of study variables. The current study sample includes 57% of 450 couples who participated in the study from 1989 to 2015. The majority of the excluded couples (43%) divorced or separated by 2015. An attrition analysis showed that, in general, respondents lost to attrition were not significantly different from those who remained in the sample in terms of age, education, income, reported general health, and illness in 1991. Men who remained in the sample had an average of one more illness in 1991 than those who were lost to attrition (mean difference = 0.74, p < .001). Women who remained in the sample reported less financial strain than those who were lost to attrition (mean difference = 0.19, p < .05). Detailed information about the MTP and IYFP can be found in Conger and Conger (2002) and Conger and Elder (1994). Measures Family Economic Problems The list of economic problems was adapted from Dohrenwend, Krasnoff, Askenasy, and Dohrenwend (1978) to capture families’ economic hardship. Separately for 1991 and 2001, husbands and wives indicated economic problems they experienced from a list of 27 items. Their “yes” responses were summed to indicate the number of economic problems (1 = yes, 0 = no). Husbands’ and wives’ scores were then summed to create a family-level index of economic hardship. The list of economic problems included items such as “borrowed money to help pay bills,” “sold possessions or cashed in life insurance,” and “changed food shopping or eating habits to save money.” Body Mass Index Respondents reported their height and weight in 2001. From this information, their BMI, the ratio of weight to height squared ([lbs*703]/inches2), was calculated and utilized as a proximal predictor of CM disease onset. CM Disease In 2015, respondents indicated if they were diagnosed by a physician with any CM diseases as an adult. Sample diseases assessed included diabetes, hypertension, thickening of arteries, and heart attacks. A binary variable was created indicating the presence of CM disease (1 = yes; 0 = no). A similar illness measure from 2001 was used as a control variable so that the 2015 measure reflects CM disease onset between the years of 2001 and 2015. Couples’ Marital Integration Couples’ marital integration was assessed by a 10-item measure of engagement in joint activities created for the IYFP (Wickrama, Lorenz, Conger, Matthews, & Elder, 1997). Sample items included how often the partners: “Got involved together in community, church, or school activities,” “Did household chores or yard work together,” and “Socialized with friends.” These items were rated on a four-point scale and scored so that higher scores indicated higher joint activities (1 = never, 4 = always). Mean scores were computed for each partner during the years of 1991 and 1994. This measure had good internal reliability across the years with alphas ranging from .70 to .78 for husbands and wives. The correlations between marital integration in 1991 and 1994 were .51 (p < .05) and .39 (p < .05) for husbands and wives, respectively. Next, a couple-level score was computed by taking the mean of their individual-level scores to indicate their average marital integration over time. This couple-level marital integration score was dichotomized based on a mean-split to distinguish couples who were above mean (n = 114; considered relatively “high marital integration”) from those who were below the mean (n = 119; considered relatively “low marital integration”) for the multigroup moderation analysis. Analysis Analyses were performed using a structural equation modeling (SEM) framework, using the maximum likelihood estimating procedure available in Mplus software (version 8.0; Muthén & Muthén 1998–2017) to account for the categorical outcome variable (i.e., CM disease onset). SEM within the context of an actor partner interdependence model (Kenny, Kashy, & Cook, 2006) allowed for the modeling of dyadic associations between husbands and wives, and, consequently, variables for husbands and wives were allowed to correlate (e.g., husbands’ and wives’ BMI and CM diseases). We also tested for indirect effects using Sobel tests in Mplus. We tested the moderating role of couple’s marital integration by conducting a multigroup analysis to determine how association between FEH and BMI within the model differed under conditions of low and high marital integration (mean split) (Hayes, 2013). We relied on a range of indices to evaluate the fit of our models, including the chi-square statistic, the comparative fit index (CFI), and the root mean square error of approximation (RMSEA). Bentler (1990) states that a CFI of more than .95 indicates a respectable model fit, and MacCallum, Browne, and Sugawara (1996) report that a RMSEA of .08 or less indicates reasonably good model fit as well. Results Descriptive statistics and correlation coefficients for all study variables are shown in Table 1. Table 1. Descriptive Statistics and Correlations Among Study Variables 1 2 3 4 5 6 7 8 9 1. H. CM disease 2015 – 2. W. CM disease 2015 .16~ – 3. H. BMI 2001 .22* .09 – 4. W. BMI 2001 .03 .25* .33* – 5. FEH 2001 .03 .5 .10 .21* – 6. H. CM disease 2001 .42** −.01 .23* .01 .02 – 7. W. CM disease 2001 .07 .35** .21* .33* .06 .12~ – 8. FEH 1991 .09 .05 .17* .21* .50** .07 .11~ – 9. Marital integration 1991/1994 −.06 .03 −.08 .17* −.01 −.18* .92 −.01 – Mean .67 .56 29.66 28.74 6.85 .33 .25 10.34 .49 SD .47 .50 5.02 6.09 6.69 .47 .44 9.63 .50 1 2 3 4 5 6 7 8 9 1. H. CM disease 2015 – 2. W. CM disease 2015 .16~ – 3. H. BMI 2001 .22* .09 – 4. W. BMI 2001 .03 .25* .33* – 5. FEH 2001 .03 .5 .10 .21* – 6. H. CM disease 2001 .42** −.01 .23* .01 .02 – 7. W. CM disease 2001 .07 .35** .21* .33* .06 .12~ – 8. FEH 1991 .09 .05 .17* .21* .50** .07 .11~ – 9. Marital integration 1991/1994 −.06 .03 −.08 .17* −.01 −.18* .92 −.01 – Mean .67 .56 29.66 28.74 6.85 .33 .25 10.34 .49 SD .47 .50 5.02 6.09 6.69 .47 .44 9.63 .50 Notes: CM = cardiometabolic; BMI = body mass index; FEH = family economic hardship; H, husbands; W = wives. ~p < .10. *p < .05. **p < .01. View Large Table 1. Descriptive Statistics and Correlations Among Study Variables 1 2 3 4 5 6 7 8 9 1. H. CM disease 2015 – 2. W. CM disease 2015 .16~ – 3. H. BMI 2001 .22* .09 – 4. W. BMI 2001 .03 .25* .33* – 5. FEH 2001 .03 .5 .10 .21* – 6. H. CM disease 2001 .42** −.01 .23* .01 .02 – 7. W. CM disease 2001 .07 .35** .21* .33* .06 .12~ – 8. FEH 1991 .09 .05 .17* .21* .50** .07 .11~ – 9. Marital integration 1991/1994 −.06 .03 −.08 .17* −.01 −.18* .92 −.01 – Mean .67 .56 29.66 28.74 6.85 .33 .25 10.34 .49 SD .47 .50 5.02 6.09 6.69 .47 .44 9.63 .50 1 2 3 4 5 6 7 8 9 1. H. CM disease 2015 – 2. W. CM disease 2015 .16~ – 3. H. BMI 2001 .22* .09 – 4. W. BMI 2001 .03 .25* .33* – 5. FEH 2001 .03 .5 .10 .21* – 6. H. CM disease 2001 .42** −.01 .23* .01 .02 – 7. W. CM disease 2001 .07 .35** .21* .33* .06 .12~ – 8. FEH 1991 .09 .05 .17* .21* .50** .07 .11~ – 9. Marital integration 1991/1994 −.06 .03 −.08 .17* −.01 −.18* .92 −.01 – Mean .67 .56 29.66 28.74 6.85 .33 .25 10.34 .49 SD .47 .50 5.02 6.09 6.69 .47 .44 9.63 .50 Notes: CM = cardiometabolic; BMI = body mass index; FEH = family economic hardship; H, husbands; W = wives. ~p < .10. *p < .05. **p < .01. View Large Results from the estimated path analysis are shown in Figure 2. Consistent with Hypothesis 1, FEH in early midlife (assessed in 1991) was associated with both husbands’ and wives’ BMI in later midlife (2001) (b = .12, p < .01 for husbands and b = .08, p < .05 for wives). In turn, BMI in later midlife was associated with the onset of CM disease in later years (2015) (b = .03, p < .05 for husbands and b = .03, p < .001) after controlling for earlier CM disease (2001). Thus, more FEH in early midlife (1991) generally resulted in higher BMI for both husbands and wives a decade later (2001), and higher BMI in later midlife was implicated in the subsequent onset of CM disease. The logistic coefficient of .03 (that is, an odds ratio of 1.03) for both husbands and wives indicates that, on average, a one unit increase in BMI in later midlife was associated with a 3% increase in the odds of CM disease onset approximately 14 years later. For women, there was support for Hypothesis 2, as FEH in later midlife (2001) was associated with higher BMI (2001) for wives but not husbands (b = .14, p < .01) after accounting for the distal influence of FEH in early midlife. The influence of more proximal FEH in later midlife on subsequent CM disease onset was not statistically significant. Husbands’ and wives’ age was controlled for in the model. However, age was only related to BMI (2001) (b for husbands and wives = .08 and .04, respectively, p < .05). We also tested for indirect effects related to significant paths shown in Figure 2 using Sobel tests. The indirect effect of FEH (1991) on CM diseases via BMI (2001) was .004, p <.05 and .005, p <.10 for husbands and wives, respectively. The indirect effect of FEH (2001) on CM disease via BMI (2001) for wives was .002, p < .05. Figure 2. View largeDownload slide Results from a model examining family economic hardship, body mass index, and cardiometabolic disease onset for husbands and wives after controlling for age. Notes:~p < .06. *p < .05. **p < .01. ***p < .001. Unstandardized coefficients are shown with SEs in parentheses (n = 257 couples). CFI = .92. RMSEA = .07. χ2 (df) = 220 (72). Age was significantly related to body mass index (2001) (not shown in the figure). Figure 2. View largeDownload slide Results from a model examining family economic hardship, body mass index, and cardiometabolic disease onset for husbands and wives after controlling for age. Notes:~p < .06. *p < .05. **p < .01. ***p < .001. Unstandardized coefficients are shown with SEs in parentheses (n = 257 couples). CFI = .92. RMSEA = .07. χ2 (df) = 220 (72). Age was significantly related to body mass index (2001) (not shown in the figure). As a supplementary analysis (not shown in Figure 2), we also tested the mediating role of BMI in 1994 (BMI in 1991 is not available) in relation to the path between FEH (1991) and BMI (2001) for both husbands and wives. The results indicated that BMI in 1994 mediated the association between FEH (1991) and BMI (2001) for both husbands and wives. However, for wives, but not husbands, the direct effect between FEH (1991) and BMI (2001) remained statistically significant even after accounting for assessments of BMI in 1994. There was also evidence of contemporaneous associations between spouses. Consistent with Hypothesis 3, husbands’ and wives’ BMI in later midlife (2001) were significantly correlated, such that when one spouse had a high BMI, their spouse tended to have a similarly high BMI (r = .34, p < .001). The amount of CM disease present in later adulthood was also correlated between husbands and wives (r = .22, p < .05). Overall, the model shown in Figure 2 fit the data reasonably well (CFI = .99, RMSEA = .03, and χ2/df = 1.03). The model explained 27% and 25% of the variance in husbands’ and wives’ CM disease in later adulthood, respectively. CM disease in later midlife was also related to several other variables in the model. (Note that these paths are not shown in the figure to ensure readability.) More specifically, in families experiencing more economic hardship in early midlife, wives averaged more CM disease diagnoses in later midlife (2001) (b = .57, p < .05), and wives with a higher BMI in later midlife (2001) also tended to concurrently report more CM disease diagnoses (2001) (b = .14, p < .01). Marital Integration Moderation Last, we examined the protective, or moderating, role of marital integration to determine if the hypothesized associations among FEH and BMI varied across couples that were relatively high and low in marital integration using a multigroup analyses (see Figure 3A and B). Recall that high and low groups were created by mean splits of the marital integration measure. Overall, the multigroup model fit the data well (χ2 (df) = 21.64 (20), CFI = .99, RMSEA = .03). Figure 3. View largeDownload slide Results from a multigroup analysis assessing marital integration as a protective factor against the detrimental health influence of family economic hardship. Notes: *p < .05. **p < .01. ***p < .001. “High Integration” couples were those with above average marital integration scores (A). “Low Integration” couples were those with below average marital integration scores (B). Unstandardized coefficients are shown with SEs in parentheses. CFI = .99. RMSEA = .03. χ2 (df) = 20.64 (20). Figure 3. View largeDownload slide Results from a multigroup analysis assessing marital integration as a protective factor against the detrimental health influence of family economic hardship. Notes: *p < .05. **p < .01. ***p < .001. “High Integration” couples were those with above average marital integration scores (A). “Low Integration” couples were those with below average marital integration scores (B). Unstandardized coefficients are shown with SEs in parentheses. CFI = .99. RMSEA = .03. χ2 (df) = 20.64 (20). In general, a comparison of the model separately for the two groups with differing marital integration scores indicated an absence of detrimental effects of distal FEH (1991) for couples with a higher level of marital integration while these effects were statistically significant for individuals with a lower level of marital integration (Hypothesis 4). More specifically, the paths between FEH in early midlife and BMI in later midlife were statistically significant for husbands and wives with a low level of marital integration (b = .19, p < .01 and b = .16, p < .05, respectively). Yet, these paths were not statistically significant in the sample comprised of couples with a relatively high level of marital integration (b = .01 and .00 for husbands and wives, respectively). However, for wives, the contemporaneous path from FEH (2001) to BMI (2001) was significant in both groups. Additionally, a chi-square difference test was performed to examine the statistical significance of marital integration as a moderator of FEH-BMI paths. Overall, the model fit differently between the two levels of marital integration (high and low marital integration), thus when comparing an unconstrained model to a constrained model where the two paths in question (FEH in 1991 to BMI in 2001 for husbands and wives) were constrained to be equal across two models, these two models were significantly different (Δχ2 (df) = 6.01 (2), p < .05). When assessing pairwise comparisons to determine differences in individual paths, the path for husbands was significantly different across the two models (p < .05). The difference in the path for wives did not achieve significance at the .05 level (p < .10). These results suggest that, in general, marital integration has an important moderating role in the relationship between FEH and husbands’ and wives’ BMI scores. Discussion Previous research has rarely investigated this total FEH-BMI association in a life course framework, particularly in enduring marriages, with FEH in a previous life stage as a distal family-level stressor thought to influence CM disease in later years in both husbands and wives. This limitation in the research may partly be attributed to the lack of available data from husbands and wives over extended periods of time. To address these limitations, using prospective data over a period of 25 years, the current study examined FEH in early midlife leading to husbands’ and wives’ CM disease in later life. By so doing, the present study also advances stress–health research by investigating dyadic stress–health models, which have rarely been examined in previous studies. We drew our overall theoretical framework from the life course stress process perspective (Pearlin & Skaff, 1996), which contends that early stressors proliferate into later stressors and these distal and proximal stressors independently contribute health problems over the life course. Previous research has shown that high BMI and associated chronic diseases, particularly cardiovascular and metabolic diseases, often accelerate over middle and later years (Mezuk, 2009). Increasing CM diseases and health inequalities may be partly attributed to men’s and women’s stressful life experiences, such as FEH, at previous life stages (Jones et al., 2009; Levine, 2011) largely through the cumulative dysregulation of multiple body systems (Geronimus et al., 2006) reflected, in part, by high BMI levels (Wang & Nakayama, 2010). Notably, FEH may also contribute to CM disease through behavioral and affective mechanisms, and research suggests that these mechanisms leading to CM diseases may also be evident, in part, by high BMI (Wickrama, Bae, & O’Neal, 2017). Thus, in the present study, we aimed to evaluate the total association between FEH and BMI rather than focusing on specific linking mechanisms. The findings showed that for both husbands and wives, FEH in early midlife is implicated in CM disease onset in later adulthood through elevated levels of BMI. This is consistent with the life course stress process perspective, which contends that health in later life reflects a lifetime of past experiences (Glymour et al., 2009; Pearlin & Skaff, 1996). A dyadic model including data from both husbands and wives showed that this life course process can stem from a relatively common family-level stressor, FEH. The findings also revealed husband–wife contemporaneous dependencies in terms of BMI and CM disease. Consistent with a contagion perspective, these dependencies suggest nondirectional or reciprocal associations between husbands’ and wives’ BMI, which may be attributed to their similarities and shared activities (e.g., eating, exercising, and engaging in screen-time together). Taken together, these associations suggest a family-health process stemming from early FEH and operating cumulatively over the life course. These findings are consistent with the relational perspective (Berscheid & Ammazzalorso, 2001) and the contagion concept, which suggests that activities between couple members should be considered in the couple context, rather than in isolation. That is, spouses’ lifestyle behaviors are influenced by family context and can also be transmitted to their partners due to the interpersonal nature of these behaviors and the dependencies between husbands and wives. Future studies should extend family-health research by further investigating such multilevel processes within the family context in combination with research assessing simultaneous individual processes. Importantly, the distal influence of early FEH in early midlife on CM disease in later adulthood seems to prevail even after taking the influence of proximal FEH into account, suggesting that early FEH is a powerful and persistent determinant of physiological dysregulation for both husbands and wives. This may indicate that early midlife is a particularly salient time in the life course for FEH (i.e., a sensitive period effect). That is, husbands and wives may be more sensitive to stressors such as FEH in their early middle years, a life stage during which many couples are heavily committed to numerous potential stressful activities including raising their adolescent children and caring for aging parents. Furthermore, consistent with the notion of “life cycle squeezes” (Oppenheimer, 1974), although new age-graded economic difficulties (FEH) may arise in later midlife (e.g., helping young adult children with higher education expenses) for both spouses, it appears that this proximal FEH is influential only for wives’ BMI. This suggests that for wives, in addition to the distal process of earlier FEH, there is a proximal stress–health process involving FEH and BMI in later midlife. This may be attributed to wives, but not husbands, who experienced stressful life experiences in previous stages developing a heightened stress sensitivity and response to proximal FEH (Dich et al., 2015). These findings are consistent with previous studies that have shown females are more emotionally vulnerable to stressful circumstances, such as FEH, than men (Ahnquist, Fredlund, & Wamala, 2007; Verma, Balhara, & Gupta, 2011). If these emotional responses are chronic or occur repeatedly, physiological dysregulations may occur, and this dysregulation may partly be reflected by high BMI (McEwen & Gianaros, 2010). Studies should further investigate this important gender difference in developing stress sensitivity in late midlife. For both husbands and wives, BMI in later middle years appeared to contribute to the onset of CM disease in their later years (when husbands and wives averaged 61 and 66 years of age, respectively). This highlights elevated BMI as a powerful risk factor for later CM disease and is consistent with recent psychophysiological research documenting that high BMI is one of several important biomarkers reflecting the extent of physiological dysregulation in cardiovascular, metabolic, and immune systems (Glei et al., 2007; Wang & Nakayama, 2010). Because the collection of BMI data is less invasive and easier to capture in survey studies than other biomarkers, BMI may be a reliable and valid proxy for physiological dysregulation in social epidemiological studies. Although the accuracy of BMI-related measurements via self-report is a concern, it is minimized, and measurement reliability improves, when measurements are taken by trained professionals. Consistent with the life course stress process perspective (Pearlin & Skaff, 1996), the present study also examined the protective role of couples’ marital integration in relation to the association between FEH and husbands’ and wives’ BMI using a multigroup approach. The impact of FEH on husbands’ and wives’ BMI varied depending on the couples’ marital integration, as measured through their joint activities. Recall that analyses were conducted separately for two groups representing high integration (above mean) and low integration (below mean). For couples with less integration, FEH in early midlife had a relatively strong impact on husbands’ and wives’ BMI. In the model comprised of couples with above average marital integration, these paths were not statistically significant. These results are supported by interdependence theory (Kelley & Thibaut, 1978) and emotional investment theories (Kelley et al., 1983). These relational theories suggest that couples with higher levels of marital integration, exhibited by behavioral closeness, become interdependent and emotionally invested with one another working together to accomplish shared goals. This couple solidarity may act as a buffer against the adverse influence of distal FEH. However, marital integration did not moderate the contemporaneous association between FEH and BMI in 2001 for wives, suggesting that the moderating role of marital integration may be more pronounced in long-term processes over extended periods of time linking stress exposure and physiological responses. There are several limitations to the current study that should be noted. First, the sample was comprised only of White individuals living in rural Iowa. Studies testing similar models with a more diverse population are needed. For instance, future samples should include multiple ethnicities, greater variation in length of marriage, and other geographic locations. Second, the historical and economic environment (i.e., the farm crisis) in which the respondents lived represents a rather unique context. Thus, future studies should investigate the study hypotheses with families who have experienced less extreme FEH or a qualitatively different economic context. Because of the self-report nature of all study constructs, self-report biases are possible. Furthermore, while there are limitations of self-report measures of stress experience, such as FEH, there are also strengths as well. More specifically, consistent with stress appraisal theory (Lazarus, 1999) and family stress theory (Boss, Mancini, & Bryant, 2017), more subjective, self-report measures assess individuals’ perceptions and their own “way of viewing the world,” which is often a central determinant of the physiological response elicited by an event or stressor. Each approach to moderation analyses has its strengths and weaknesses. One of the strengths of our multigroup analysis approach is the provision of a clear interpretation of the buffering role of marital integration, but this approach also limits our understanding of more nuanced differences that may exist in the findings. Assessing moderation with a continuous measure of marital integration may provide additional insight on more subtle effects. Furthermore, while one of the strengths of this research is the analysis of dyadic (actor and partner) effects, our analytical approach to moderation required averaging husbands’ and wives’ perceptions of marital integration, which removes the within-dyad nuance of how spouses perceive relationships similarly or differently. Future research should address how each partner’s perceptions of marital integration may uniquely moderate the findings of the current study. Finally, because research suggests that some individuals are genetically more prone to develop CM disease when faced with stressful life experiences (Ising & Holsboer, 2006), future studies should investigate potential genetic moderations of the observed associations. Implications Despite these limitations, findings from the current study have important implications for health policies and programs, particularly the identification of the significance of FEH for CM health throughout the adult years and into later adulthood. Elucidating BMI as a stress-response mechanism linking FEH and CM disease informs prevention and intervention programs by suggesting weight management as a modifiable leverage point for reducing the prevalence of CM disease and situating this in the understanding that BMI is linked to FEH a decade earlier. Also, the findings shed light on the acceleration of CM disease onset for members of the baby boom cohort who are now in later life, and they highlight the need to consider these associations within a life course family-health process. The persistent, life stage-dependent influence of FEH on BMI can be utilized to improve social welfare interventions, including food-focused interventions aimed to help families struggling economically. Beyond providing an important basic need during a time of crisis, these interventions could potentially reduce the long-term health impacts suffered by affected families, if healthy food options that decrease the likelihood of high BMI are incorporated. Findings related to the moderating effect of marital integration are particularly important for helping professionals and clinicians as they consider protective factors that can buffer individuals from the negative health consequences of stressful FEH. These findings on marital integration suggest that facilitating effective coping with FEH from a couple-focused perspective, including enhancing basic marital attributes, such as marital integration, can potentially minimize the detrimental psychophysiological processes for husbands and wives. Thus, couple-focused interventions may be a successful tool for combatting CM disease onset for this population (Gorin et al., 2008). Funding This research is currently supported by a grant from the National Institute on Aging (AG043599, K. A. S. Wickrama, PI). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Support for earlier years of the study also came from multiple sources, including the National Institute of Mental Health (MH00567, MH19734, MH43270, MH59355, MH62989, MH48165, MH051361), the National Institute on Drug Abuse (DA05347), the National Institute of Child Health and Human Development (HD027724, HD051746, HD047573, HD064687), the Bureau of Maternal and Child Health (MCJ-109572), and the MacArthur Foundation Research Network on Successful Adolescent Development Among Youth in High-Risk Settings. Conflict of interest None declared. References Ahnquist , J. , Fredlund , P. , & Wamala , S. P . ( 2007 ). Is cumulative exposure to economic hardships more hazardous to women's health than men's? A 16-year follow-up study of the Swedish Survey of Living Conditions . Journal of Epidemiology and Community Health , 61 , 331 – 336 . doi:10.1136/jech.2006.049395 Google Scholar CrossRef Search ADS PubMed Bentler , P. M . ( 1990 ). Comparative fit indexes in structural models . Psychological Bulletin , 107 , 238 – 246 . doi:10.1037//0033-2909.107.2.238 Google Scholar CrossRef Search ADS PubMed Berscheid , E. , & Ammazzalorso , H . ( 2001 ). Emotional experience in close relationships . In G. J. Fletcher & M. S. Clark (Eds.), Blackwell handbook of social psychology: Interpersonal process (pp. 308 – 330 ). Malden, MA : Blackwell . Google Scholar CrossRef Search ADS Berscheid , E. , Snyder , M. , & Omoto , A. M . ( 1989 ). The relationship closeness inventory: Assessing the closeness of interpersonal relationships . Journal of Personality and Social Psychology , 57 , 792 – 807 . doi:10.1037//0022-35184.108.40.2062 Google Scholar CrossRef Search ADS Boss , P. , Bryant , C. M. , & Mancini , J. A . ( 2017 ). Family stress management: A contextual approach ( 3rd ed .). Thousand Oaks, CA : Sage . Bryant , V. , Wickrama , K. A. S. , O’Neal , C. W. , & Lorenz , F. O . ( 2017 ). Family hostility and depressive symptoms in middle-aged couples: Moderating effect of marital integration . Journal of Family Psychology 31 , 765 – 774 . doi: 10.1037/fam0000306 Google Scholar CrossRef Search ADS PubMed Cacioppo , J. T. , Fowler , J. H. , & Christakis , N. A . ( 2009 ). Alone in the crowd: The structure and spread of loneliness in a large social network . Journal of Personality and Social Pychology , 97 , 977 – 991 . Google Scholar CrossRef Search ADS Conger , R. D. , & Conger , K. J . ( 2002 ). Resilience in Midwestern families: Selected findings from the first decade of a prospective, longitudinal study . Journal of Marriage and Family , 64 , 361 – 373 . Google Scholar CrossRef Search ADS Conger , R. D. , & Elder , Jr., G. H . ( 1994 ). Families in troubled times: Adapting to change in rural America . Hawthorne, NY : Walter de Gruyter . Dich , N. , Hansen , Å. M. , Avlund , K. , Lund , R. , Mortensen , E. L. , Bruunsgaard , H. , & Rod , N. H . ( 2015 ). Early life adversity potentiates the effects of later life stress on cumulative physiological dysregulation . Anxiety, Stress, and Coping , 28 , 372 – 390 . doi: 10.1080/10615806.2014.969720 Google Scholar CrossRef Search ADS PubMed Dohrenwend , B. S. , Krasnoff , L. , Askenasy , A. R. , & Dohrenwend , B. P . ( 1978 ). Exemplification of a method for scaling life events: The peri life events scale . Journal of Health and Social Behavior , 19 , 205 – 229 . doi:10.2307/2136536 Google Scholar CrossRef Search ADS PubMed Dyer , A. R. , Stamler , J. , Garside , D. B. , & Greenland , P . ( 2004 ). Long-term consequences of body mass index for cardiovascular mortality: The Chicago Heart Association Detection Project in Industry study . Annals of Epidemiology , 14 , 101 – 108 . doi: 10.1016/S1047-2797(03)00121-2 Google Scholar CrossRef Search ADS PubMed Elder , Jr., G. H. , & Giele , J. Z . ( 2009 ). The craft of life course research . New York : Guilford Press . Elder , G. H. , Jr. , & O’Rand , A. M . ( 1995 ). Adult lives in a changing society . In K. S. Cook , G. A. Fine , & J. S. House (Eds.), Sociological perspectives on social psychology (pp. 452 – 475 ). Boston : Allyn & Bacon . Geronimus , A. T. , Hicken , M. , Keene , D. , & Bound , J . ( 2006 ). “Weathering” and age patterns of allostatic load scores among blacks and whites in the United States . American Journal of Public Health , 96 , 826 – 833 . doi: 10.2105/AJPH.2004.060749 Google Scholar CrossRef Search ADS PubMed Glei , D. A. , Goldman , N. , Chuang , Y. L. , & Weinstein , M . ( 2007 ). Do chronic stressors lead to physiological dysregulation? Testing the theory of allostatic load . Psychosomatic Medicine , 69 , 769 – 776 . doi: 10.1097/PSY.0b013e318157cba6 Google Scholar CrossRef Search ADS PubMed Glymour , M. M. , Ertel , K. A. , & Berkman , L. F . ( 2009 ). What can life-course epidemiology tell us about health inequalities in old age ? Annual Review of Gerontology and Geriatrics , 29 , 27 – 56 . doi:10.1891/0198-8794.29.27 Google Scholar CrossRef Search ADS Gorin , A. A. , Wing , R. R. , Fava , J. L. , Jakicic , J. M. , Jeffery , R. , West , D. S. , … DiLillo , V. G . ( 2008 ). Weight loss treatment influences untreated spouses and the home environment: Evidence of a ripple effect . International Journal of Obesity , 32 , 1678 – 1684 . doi:10.1038/ijo.2008.150 Google Scholar CrossRef Search ADS PubMed Grabe , H. J. , Schwahn , C. , Mahler , J. , Schulz , A. , Spitzer , C. , Fenske , K. , … Freyberger , H. J . ( 2012 ). Moderation of adult depression by the serotonin transporter promoter variant (5-HTTLPR), childhood abuse and adult traumatic events in a general population sample . American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics , 159B , 298 – 309 . doi: 10.1002/ajmg.b.32027 Google Scholar CrossRef Search ADS Hayes , A. F . ( 2013 ). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach . New York : Guilford . Ising , M. , & Holsboer , F . ( 2006 ). Genetics of stress response and stress-related disorders . Dialogues in Clinical Neuroscience , 8 , 433 – 444 . Google Scholar PubMed Jones , C. A. , Perera , A. , Chow , M. , Ho , I. , Nguyen , J. , & Davachi , S . ( 2009 ). Cardiovascular disease risk among the poor and homeless—what we know so far . Current Cardiology Reviews , 5 , 69 – 77 . doi: 10.2174/157340309787048086 Google Scholar CrossRef Search ADS PubMed Kelley , H. H. , Berscheid , E. , Christensen , A. , Harvey , J. H. , Huston , T. L. , Levinger , G. , … & Peterson , D. R . ( 1983 ). Close relationships (pp. 265 – 314 ). New York : Freeman . Kelley , H. H. , & Thibaut , J. W . ( 1978 ). Interpersonal relationships. A theory of interdependence . New York : John Wiley & Sons . Kenny , D. A. , Kashy , D. A. , & Cook , W. L . ( 2006 ). The analysis of dyadic data . New York : Guilford Press . Kiecolt-Glaser , J. K. , Loving , T. J. , Stowell , J. R. , Malarkey , W. B. , Lemeshow , S. , Dickinson , S. L. , & Glaser , R . ( 2005 ). Hostile marital interactions, proinflammatory cytokine production, and wound healing . Archives of General Psychiatry , 62 , 1377 – 1384 . doi: 10.1001/archpsyc.62.12.1377 Google Scholar CrossRef Search ADS PubMed Knobloch , L. K. , & Solomon , D. H . ( 2004 ). Interference and facilitation from partners in the development of interdependence within romantic relationships . Personal Relationships , 11 , 115 – 130 . doi:10.1111/j.1475-6811.2004.00074.x Google Scholar CrossRef Search ADS Lachman , M. E. , & James , J. B . (Eds.) ( 1997 ). Multiple paths of midlife development . Chicago : University of Chicago Press . Lazarus , R. S . ( 1999 ). Stress and emotion: A new synthesis . New York : Springer . Levine , J. A . ( 2011 ). Poverty and obesity in the U.S . Diabetes , 60 , 2667 – 2668 . doi: 10.2337/db11-1118 Google Scholar CrossRef Search ADS PubMed Loman , M. M. , & Gunnar , M. R .; Early Experience, Stress, and Neurobehavioral Development Center . ( 2010 ). Early experience and the development of stress reactivity and regulation in children . Neuroscience and Biobehavioral Reviews , 34 , 867 – 876 . doi: 10.1016/j.neubiorev.2009.05.007 Google Scholar CrossRef Search ADS PubMed Lorenz , F. O. , Elder , G. H. , Bao , W. N. , Wickrama , K. A. S. , & Conger , R. D . ( 2000 ). After farming: Emotional health trajectories of farm, nonfarm, and displaced farm couples . Rural Sociology , 65 , 50 – 71 . doi:10.1111/j.1549-0831.2000.tb00342.x Google Scholar CrossRef Search ADS Lorenz , F. O. , Wickrama , K. A. , Conger , R. D. , & Elder , G. H. Jr . ( 2006 ). The short-term and decade-long effects of divorce on women’s midlife health . Journal of Health and Social Behavior , 47 , 111 – 125 . doi: 10.1177/002214650604700202 Google Scholar CrossRef Search ADS PubMed MacCallum , R. C. , Browne , M. W. , & Sugawara , H. M . ( 1996 ). Power analysis and determination of sample size for covariance structure modeling . Psychological Methods , 1 , 130 – 149 . doi:10.1037//1082-989x.1.2.130 Google Scholar CrossRef Search ADS McDonough , P. , & Berglund , P . ( 2003 ). Histories of poverty and self-rated health trajectories . Journal of Health and Social Behavior , 44 , 198 – 214 . doi:10.2307/1519808 Google Scholar CrossRef Search ADS PubMed McEwen , B. S. , & Gianaros , P. J . ( 2010 ). Central role of the brain in stress and adaptation: Links to socioeconomic status, health, and disease . Annals of the New York Academy of Sciences , 1186 , 190 – 222 . doi: 10.1111/j.1749-6632.2009.05331.x Google Scholar CrossRef Search ADS PubMed Meaney , M. J. , Bhatnagar , S. , Larocque , S. , McCormick , C. M. , Shanks , N. , Sharma , S. , … Plotsky , P. M . ( 1996 ). Early environment and the development of individual differences in the hypothalamic-pituitary-adrenal stress response . In C. R. Pfeffer (Ed.), Severe stress and mental disturbance in children (pp. 85 – 127 ). Washington, DC : American Psychiatric Press . Mezuk , B . ( 2009 ). Epidemiology of diabetes and cardiovascular disease: The emergence of health disparities over the life span . Annual Review of Gerontology & Geriatrics , 29 , 77 – 97 . doi:10.1891/0198-8794.29.77 Google Scholar CrossRef Search ADS Muthén , L. K. , & Muthén , B. O . ( 1998–2017 ). Mplus user’s guide ( 8th ed .). Los Angeles, CA : Muthén & Muthén . Nealey-Moore , J. B. , Smith , T. W. , Uchino , B. N. , Hawkins , M. W. , & Olson-Cerny , C . ( 2007 ). Cardiovascular reactivity during positive and negative marital interactions . Journal of Behavioral Medicine , 30 , 505 – 519 . doi: 10.1007/s10865-007-9124-5 Google Scholar CrossRef Search ADS PubMed Oppenheimer , V. K . ( 1974 ). The life-cycle squeeze: The interaction of men’s occupational and family life cycles . Demography , 11 , 227 – 245 . doi: 10.2307/2060561 Google Scholar CrossRef Search ADS PubMed O’Rand , A. M. , & Hamil-Luker , J . ( 2005 ). Processes of cumulative adversity: Childhood disadvantage and increased risk of heart attack across the life course . The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences , 60 ( Spec No 2 ), 117 – 124 . doi:10.1093/geronb/60.special_issue_2.s117 Google Scholar CrossRef Search ADS Pearlin , L. I. , & Skaff , M. M . ( 1996 ). Stress and the life course: A paradigmatic alliance . The Gerontologist , 36 , 239 – 247 . doi:10.1093/geront/36.2.239 Google Scholar CrossRef Search ADS PubMed Schade , L. C. , Sandberg , J. , & Busby , D . ( 2014 ). Does this marriage make me look fat? Marital quality as a predictor of perceptions of body weight, activity level, and eating habits . The American Journal of Family Therapy , 42 , 42 – 52 . doi:10.1080/01926187.2013.767617 Google Scholar CrossRef Search ADS Singh-Manoux , A. , Ferrie , J. E. , Chandola , T. , & Marmot , M . ( 2004 ). Socioeconomic trajectories across the life course and health outcomes in midlife: Evidence for the accumulation hypothesis ? International Journal of Epidemiology , 33 , 1072 – 1079 . doi: 10.1093/ije/dyh224 Google Scholar CrossRef Search ADS PubMed Verma , R. , Balhara , Y. P. , & Gupta , C. S . ( 2011 ). Gender differences in stress response: Role of developmental and biological determinants . Industrial Psychiatry Journal , 20 , 4 – 10 . doi: 10.4103/0972-6748.98407 Google Scholar PubMed Wang , Z. , & Nakayama , T . ( 2010 ). Inflammation, a link between obesity and cardiovascular disease . Mediators of Inflammation , 2010 . Wickrama , K. A. , Lorenz , F. O. , Conger , R. D. , Matthews , L. , & Elder , G. H. Jr . ( 1997 ). Linking occupational conditions to physical health through marital, social, and intrapersonal processes . Journal of Health and Social Behavior , 38 , 363 – 375 . doi:10.2307/2955431 Google Scholar CrossRef Search ADS PubMed Wickrama , K. K. , Klopack , E. T. , O’Neal , C. W. , Beach , S. R. , Neppl , T. , Lorenz , F. O. , & Bae , D . ( 2017 ). Life course patterns of concurrent trajectories of BMI and affective symptoms of rural mothers: Socioeconomic antecedents and disease outcomes in later life . The Journals of Gerontology: Series B . doi: 10.1093/geronb/gbx121 Wickrama , K. A. S. , Bae , D. , & O’Neal , C. W . ( 2017 ). Explaining the association between early adversity and young adults’ diabetes outcomes: Physiological, psychological, and behavioral mechanisms . Journal of Youth and Adolescence , 46 , 2407 – 2420 . doi: 10.1007/s10964-017-0639-y Google Scholar CrossRef Search ADS PubMed Wickrama , K. A. S. , Lorenz , F. O. , Wallace , L. E. , Peiris , L. , Conger , R. D. , & Elder , G. H. Jr . ( 2001 ). Family influences on physical health during the middle years: The case of onset of hypertension . Journal of Marriage and Family , 63 , 527 – 539 . doi:10.1111/j.1741-3737.2001.00527.x Google Scholar CrossRef Search ADS © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
The Gerontologist – Oxford University Press
Published: May 25, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera