Jacobs Journal of Community Medicine

What’s Love Got to Do with It? The Relationship of Marriage to Health

*Dr. Karen Patricia Williams
Department Of Community Medicine, College Of Nursing, The Ohio State University, 362 Newton Hall, 1585 Neil Avenue, Columbus, OH 43210, Virgin Islands, British

*Corresponding Author:
Dr. Karen Patricia Williams
Department Of Community Medicine, College Of Nursing, The Ohio State University, 362 Newton Hall, 1585 Neil Avenue, Columbus, OH 43210, Virgin Islands, British
Email:williams.5963@osu.edu

Published on: 2018-12-18

Abstract

What’s Love Got to Do with It? The Relationship of Marriage to Health

Keywords

Marriage.Health,Psychological distress

Introduction

Traditional thinking and scholarship has indicated that marriage is a life saver – extends life. Robles and Kiecolt-Glaser’s [1] review found that the functionality of marriage was important to reduce poor physiological health outcomes. With the declining rates of younger women and women of color committing to traditional religious or civil marriage (female and male) [2, 3], it raises a question if the traditional thinking is valid for all women. According to the 2010 census, 48.4% of the over 115 million U.S. households are led by husband-wife dyads; 13.1% are led by female heads of household, with nearly half caring for children less than the age of 18. These households were more likely to be headed by African American and Hispanic women. Marriage (as a social support) has traditionally been heralded as a buffer to poor health outcomes [3-9], yet women of color may not experience such protections from being married or partnered. The reasons for the phenomena are complex and not well understood. While it is known that African Americans are the least likely to wed, it remains unclear as to the role of race, culture, or social structural constraints, in making the decision to marry. Some reports in the literature indicate that perhaps African American women may perceive and value marriage differently than others [10-13]. Simmons, Simmons, Lei, and Landor [14]postulate that African Americans, particularly those who have experienced societal hardships and have a non-nuclear family composition may possess a level of mistrust that hinders establishment of potential long-term relationships. Harknett and McLanahan [12] also reported that shortages of eligible African American men may adversely impact a women’s likelihood of marrying. Though marriage is less-likely for African American and Hispanic women, these women found social support within their natural and built families perhaps explaining some of the indifference among health outcomes in spite of marital status [15].

Confounding the perspective that marriage is a protective factor for one’s health is that social support, which is a protective factor for women of color, is not fully conclusive [16]. For example, Fiori et al. [17] found no differences in depressive symptoms by gender or race, while Roxburgh [18] found that never being married was protective against depression for African Americans.

In the current study, using the 2015 National Health Interview Survey (NHIS) [19], we examine the relationship between marital status and health as well as marital status and psychological distress among African American, Hispanic, and White women.

Materials and Methods

Data Source

Data from the 2015 NHIS was used in this study. NHIS is an annual cross-sectional survey of a nationally representative sample of a civilian non-institutionalized population in the United States. The survey collects a broad range of health information (e.g., health status, behavior, health care access and utilization) through personal household interviews. The files used for the present study included 1) adult file, which contains data from one randomly selected civilian adult (age 18 years or older) per family, and 2) family file, which contains family-level information such as family structure and family poverty level.

Study Population

From the adult file of the 2015 NHIS data, we identified a sample of women who were a parent of one or more minor children (n=4,899), representing 35,304,211 such women across the United States.

Measures

Sample characteristics.

Women’s age, race/ethnicity (hereafter non-Hispanic White, known as White; non-Hispanic Black, known as African American; Hispanic, or Other), marital status (married, divorced/separated/widowed, or never married), and work status (working, not working, or retired) were extracted from the NHIS Sample Adult file. Family income (<100% Federal poverty level [FPL], >=100% to <200% FPL, or >=200% FPL), family size (2, 3-4, or 5+), number of children aged 18 or younger (1, 2, or 3+), number of elderly aged 65 or older (none vs. one or more) in the family were extracted from NHIS Family file and linked to each individual woman by family and household ID.

Psychological distress.

NHIS uses the K6 scale, developed and validated by Kessler et al, to screen for non-specific psychological distress [20, 21]. The K6 consists of six Likertscale questions that ask how often in the past 30 days a person felt 1) nervous, 2) hopeless, 3) restless, 4) so depressed that nothing could cheer you up, 5) that everything was an effort, and 6) worthless. Each question is scored from 0 (none of the time) to 4 (all of the time). The total score ranges from 0 to 24, with higher score indicating greater stress. A woman was identified as having psychological distress if her K6 score was 13 or higher [21].

Chronic conditions.

Women with chronic condition(s) were identified if they 1) had ever been told by a doctor or health care provider that they had hypertension, coronary heart disease, stroke, diabetes, cancer, arthritis, hepatitis, or COPD in the past 12 months; 2) currently had asthma; or 3) had experienced weak or failing kidneys during the past month [22].

Statistical Analysis

Descriptive statistics were used to summarize sample characteristics and the prevalence of psychological distress and chronic conditions, by marital status. Bivariate tests (analysis of variance and Chi-square statistics) were used to compare the prevalence of psychological distress and chronic conditions among the women of different marital status. Logistic regression modeling was used to estimate the effects of marital status, race/ethnicity, and their interactions, adjusting for age, work status, FPL, number of minor children, and number of elderly in the family. All the analyses were properly weighted based on the population weight Jacobs Publishers 2 provided by NHIS and conducted using SAS 9.4 [23].

Results

Table 1 presents the weighted descriptive statistics for the full sample and by marital status. A small proportion of the women had disruptive marriage (divorced, separated, or widowed, 13.1%) or were never married (13.3%). The average age of the women was 37.8 years (95% CI=37.4, 38.1), while those with disrupted marriage were older (average age = 40.9, 95% CI=40.0, 41.7) and those never married were younger (average age=31.4, 95% CI=30.6, 32.1). There was higher proportion of non-Hispanic white women in the married group (62.6% vs. 51.8% in the women with disrupted marriage vs. 29.5% in the women never married). More people were working among women with disrupted marriage (76.7%), compared to married women and those never married (67.5% and 63.7%, respectively). About 44.2% women never married had family income below federal poverty level (FPL), comparing to 30.9% in women with disrupted marriage and 10.3% in married women. Married women had greater family size, more children, and less number of elderly in the family than women in the other two groups.

Table 2 shows the prevalence of psychological distress and chronic conditions for the full sample and stratified by marital status. Overall, there were 3.5% (95% CI=2.8, 4.2) of the women having psychological distress, 34.3% of the women having at least one chronic condition. Hypertension was the most prevalent chronic condition (16.3%), followed by arthritis (11.3%), asthma (8.3%), diabetes (3.6%), COPD (3.6%), cancer (3.2%), liver disease (1.1%), kidney disease (0.9%), stroke (0.6%), and chronic heart disease (0.4%). Women with disrupted marriage had the highest prevalence of psychological distress (6.7%), followed by women never married (5.9%) and married women (2.5%). The same pattern exists for physical health, including the number of chronic conditions and prevalence of individual condition.

Table 3 shows the results from the multiple logistic regression models. After adjusting for other factors in the model, women with disruptive marriage had double (OR=2.18, 95% CI=1.24, 3.86) the likelihood of having psychological distress, compared to married women.All the minority groups tended to have lower likelihood of having psychological distress than White women, but only the Other vs White women comparison reached statistical significance (OR=0.25, 95% CI=0.12, 0.54). Other significant risk factors of psychological distress included not working/retired (OR=2.94, 95% CI=1.85, 4.17) and lower family income (ORs=3.47 and 2.44 for <100% FPL and 100-200% FPL, respectively). For the multiple logistic regression models for the chronic conditions, marital status was not significantly associated with the likelihood of having chronic conditions after adjusting for other factors in the model. Significant risk factors for having any chronic conditions included older age (OR=1.06, 95% CI=1.04, 1.07), being African American (OR=1.34, 95% CI=1.04, 1.72), not working/retired (OR=1.22, 95% CI=1.02, 1.45), lower family income (ORs=1.57 and 1.50 for <100% FPL and 100-200% FPL, respectively).

We also found significant interaction effect of marital status and race/ethnicity in the multiple logistic regression models for psychological distress. It is illustrated in Figure 1. There was greater difference between married women and those with disrupted marriage in the prevalence of psychological distress among White women than that in African American and Hispanic women. No significant interaction between marital status and race/ethnicity was found in the multiple logistic regression models for chronic conditions.

Table 1. Sample Characteristics (Data Source: NCHS, National Health Interview Survey, 2015)

Table 2. Prevalence of psychological distress and chronic conditions, by marital status (Data Source: NCHS, National Health Interview Survey, 2015)

Table 3. Factors associated with psychological distress and chronic conditions using multiple logistic regression analysis (Data Source: NCHS, National Health Interview Survey, 2015)

Figure 1. Proportion of women with psychological distress, by marital status (married, divorced/separated/widowed, never married) and race/ethnicity (Data Source: NCHS, National Health Interview Survey, 2015)

Discussion

Perspectives of marriage have been evolving for women and its expression in their health outcomes appears to be dynamic. While some women may make marriage their primary goal; if this doesn’t happen, it causes psychological distress, or; if it is disrupted in some way, they experience stress. Other women may delay or decide not to marry, resulting in low levels of psychological stress compared to women who decide not to remain married. The major findings of our study indicate that there were differences in marital status of African American and Hispanic women compared non-Hispanic Whites, yet psychological distress was less likely to be a related factor among women of color. Further, women of color were less likely to report psychological distress than their counterparts, leading one to believe that African American and Hispanic women possess factors that attribute to psychological resilience [24]. This is particularly interesting since African American and Hispanic women experience more socioeconomic hardships.

In relation to lesser influence of marital status among women of color, these findings substantiate the fact that social support from a spouse was not associated with differences in psychological distress [25]. To examine potential factors, some suggest that African American men may not be seen as beneficial financial partners as White men [26] due to the inequality in wages. Among married African American women, being married and having other societal connections correlated with greater financial strain and less stability [15, 27, 28]. Lanza di Scalea et al. [28] reported that married roles and reward may be mismatched. African American Women earn 68% less than White men, while White women earn 81% less than White men according to the American Association of University Women. (http:// www.aauw.org/) Bryant, Taylor, Lincoln, Chatters, and Jackson [30] found that among African American couples that were surveyed, 68% were satisfied with their marriages. However, others believe that lack of a spouse among African American and Hispanic women may be off-set by other social networks [31, 32].

In this study, socioeconomic factors were related to psychological distress. Similarly, Waite and Lehrer [33] and Mulvaney-Day et al. [32]implied that socioeconomic status was a larger factor in health outcomes than marriage. This postulation is further supported by Downey, Crowder, and Kemp [34] who found that single heads of household were more likely to earn lower incomes and have less education than dyad households. Though women of color are more likely to have lower socioeconomic status, associations of marriage were smaller than in Whites [35].

Those that were less resilient were found to be more likely to suffer from psychological distress [36]. Todd and Worrell [37] found that resilience among low-income African American women was most influenced by problematic social interactions and comparing one’s self to others who are less fortunate, rather than by social support. Heilemann, Lee, and Kury [38] also identified lower resilience among Hispanic women who had lower income and education and greater health problems than their peers. These findings corroborate the weak correlation between marriage (a social connection) and health among African Americans and Hispanics in this study. Additionally, racism which is a known instigator of a problematic social interaction and a known deterrent to the best health outcome, cannot be ignored. Women of color are resilient despite racism and combating chronic illnesses, using cultural values and coping mechanisms that evolve over their life course [39, 40].

Conclusions

Our findings also suggest that White women with disrupted marriages are at highest-risk for psychological distress. Despite the fact that African American and Hispanic women reported socioeconomic hardships, these women of color consistently fared better psychologically. Further research is needed to understand the effects of disruption in marriage. Also, factors contributing to resilience should be explored to better inform interventions aimed at decreasing psychological distress. Additionally, future directions for research could include same sex marriages.

Limitations

Though our study was of a nationally representative sample, there were potential limitations. First, the categorization of marital status did not account for women who were partnered but not married. Thus, non-traditional partnerships and other partnerships were not captured in the data.

Author Disclosure Statement

No competing financial interests exist

Compliance with Ethical Standards

Potential conflicts of interest:

The authors declare that they have no conflicts of interest

Research involving Human Participants and/or Animal:

This article does not contain any studies with human or animal participants performed by any of the authors. We did not obtain ethics approval from our institution Ethical Review Board because de-identified and publicly available data was used from the National Center for Health Statistics in this study. There were no identifying data for participants in the dataset used in this study.

Research involving Human Participants and/or Animal:

This article does not contain any studies with human or animal participants performed by any of the authors. We did not obtain ethics approval from our institution Ethical Review Board because de-identified and publicly available data was used from the National Center for Health Statistics in this study. There were no identifying data for participants in the dataset used in this study.

Acknowledgements

Barbara Bradley for her role in final preparation.

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