Edited by: Haichang Xin, University of Alabama at Birmingham, USA
Reviewed by: Christina Dalla, National and Kapodistrian University of Athens, Greece; Mildred Audrey Pointer, North Carolina Central University, USA; Darlene A. Kertes, University of Florida, USA
Specialty section: This article was submitted to Epidemiology, a section of the journal Frontiers in Public Health
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Although stressful life events (SLEs) predict subsequent risk of developing a major depressive episode (MDE), limited information exists on whether or not race and gender alters the predictive role of SLE on risk of MDE over a long-term period. The current study explored race and gender differences in the long-term predictive role of SLE at baseline (1986) on subsequent risk of MDE 25 years later (2011) in a nationally representative cohort in the United States.
Using a life course epidemiological approach, this longitudinal study borrowed data from the Americans’ Changing Lives (ACL) Study 1986–2011. Main predictor of interest was baseline SLE over the last 3 years measured at 1986. Main outcome was risk of MDE [Composite International Diagnostic Interview (CIDI)] 25 years later (2011). Covariates included demographics, socioeconomics, depressive symptoms [Center for Epidemiological Studies-Depression Scale (CES-D)], chronic medical conditions, and health behaviors measured at baseline (1986). Gender and race were the focal moderators. We employed logistic regressions in the pooled sample, and specific to race and gender, to test whether or not SLE × race and SLE × gender interactions are significant.
In the pooled sample, baseline SLE (1986) predicted risk of MDE 25 years later (2011). We also found a gender by SLE interaction, suggesting a stronger predictive role of SLE for subsequent clinical depression for men compared to women. Race did not modify the predictive role of SLE on subsequent risk of MDE 25 years later.
How SLE predicts MDE 25 years later differs for men and women, with a stronger predictive role for men compared to women. More research is needed to better understand the complex links between gender, sex, stress, and depression.
Regardless of the type of stressor (
There is a debate regarding whether or not stress response is independent of setting and context (
Race may alter the link between SLE and depression at each time point, and also over time. Despite higher levels of exposure to SLE (
Gender is also another main factor that may alter the cross-sectional and long-term associations between experiences of stress and the risk of MDD. Based on the psychosocial theory of depression, predominance of MDD in women is at least in part mediated by a higher exposure of women to SLE during childhood and adulthood (
We conducted this study to explore race and gender differences in the predictive role of SLE in 1986 on long-term risk of depression 25 years later in 2011. Similar to previous work (
Data were from wave 1 (1986) and wave 5 (2011) of the Americans’ Changing Lives (ACL) Study, a nationally representative longitudinal study in the United States (
The ACL study is the oldest ongoing nationally representative longitudinal study on the role of a broad range of psychosocial factors on health changes with aging over the life course from adulthood to early elderly (
The original study received approval from the institutional review board (IRB), University of Michigan. Informed consent was obtained from all individual participants included in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
The ACL used a stratified multistage probability sampling strategy. The ACL has oversampled African Americans and older adults (age 60 and above). In 1986, the study enrolled 3,617 community-dwelling adults age 25 or older who lived in the continental U.S. Wave 1 included 70% of sampled households and 68% of sampled individuals. Wave 5 included 81% of survivors in 2011. More information on participants, sampling, and recruitment is shown in Appendix 1 in Supplementary Material (
The current analysis is limited to 1,129 individuals who were followed for 25 years. The study is on the role of SLE in 1986 on MDE 25 years later. So, only survivors and those who participated in wave 1 and wave 5 could enter this study.
First, wave data were collected via face-to-face interviews. Wave 5 data were collected via either face-to-face or telephone interviews. Telephone interviews are accepted for Composite International Diagnostic (
Baseline data were collected on demographic characteristics, socioeconomic status, health behaviors, depressive symptoms, and health at wave 1 (1986). MDE was measured at wave 5 (2011).
We collected data on the number of major negative events in the past 3 years. Participants were asked about SLE at wave 1 (1986), using a measure that accords well with current standards of measurement of major/traumatic events (
Demographic variables included age (continuous measure), race (Black and White, with White as the reference group), and gender (dichotomous variable with male as the reference group). While age was a covariate, race and gender were moderators.
Socioeconomic status was measured using education (years of schooling) and income [an 11 – level categorical (rank) variable treated as a continuous measure].
We collected data on chronic medical conditions (CMC) by measuring self-reported data. Participants were asked whether or not health care providers have ever told them that they had any of the following seven conditions: hypertension, diabetes, chronic lung disease, heart disease, stroke, arthritis, and cancer. Participants were also asked if they were currently taking medication for these conditions. Based on dichotomous responses, we calculated a sum score, ranging from 0 to 7, with a higher score indicating more CMC (
Respondents were asked to classify their self-rated health (SRH) as excellent, very good, good, fair, or poor. SRH was operationalized in the following two ways: (1) as a dichotomous measure and (2) as a continuous score. For the first approach, we collapsed this five-category scale into two categories (fair/poor vs. excellent/very good/good), a cutoff point that is common in the literature. This measure has shown high test–retest reliability and validity, when considering its predictive power for mortality and other health outcomes (
We collected information on respondents’ functional health fusing several questions. A score of 1 represents confinement to a bed or chair and a score of 4 represents the ability to do heavy work inside or outside of the home. These scores were then transformed into a three-category variable: (1) no functional limitation (i.e., able to do heavy work around the house); (2) some limitation, meaning the respondent reported not being able to do such things as heavy physical labor or work around the house; or (3) moderate/severe limitation, meaning the respondent reported having great difficulty walking a few blocks or climbing stairs, or reported being confined to a bed or a chair (
Obesity was defined based on the body mass index (BMI) of larger than 30 kg/m2. The BMI level was calculated based on self-reported weights and heights. Weight and height were originally collected in pounds (1 pound = 0.453 kg) and feet (1 foot = 0.3048 m)/inches (1 inch = 0.0254 m), respectively. BMI calculated based on self-reported weight and height is known to be closely correlated with BMI based on direct measures of height and weight (
The study also used ACL measures on exercise (physical activity), smoking (i.e., tobacco use), and drinking (i.e., alcohol consumption). The first measure, the physical activity index, asked respondents how often they engaged in the following activities: working in the garden or yard, participating in active sports or exercise, and taking walks. A 4-point Likert scale response ranged from “often” to “never.” The index was scored by taking the mean of the three items (
Depressive symptoms were measured with a brief version of the Center for Epidemiological Studies-Depression scale (CES-D) which included 11 items (
The ACL survey has adopted the five-items of the Short Portable Mental Status Questionnaire (SPMSQ) to measure the cognitive impairment of the respondents. The SPMSQ assesses respondents’ memory, knowledge of current events, and ability to perform mathematical tasks and is designed to identify cognitive deficits among community and institutionalized settings (
The outcome variable was the 12-month MDE measured at 2011 using the World Mental Health Composite International Diagnostic Interview (CIDI). CIDI is a fully structured diagnostic interview and evaluates a wide range of Diagnostic and Statistical Manual-IV (DSM-IV) psychiatric disorders, including but not limited to MDE. CIDI has been used reliably on the World Mental Health project (
Due to the complex sample design used in the HRS, Stata 13.0 (Stata Corp., College Station, TX, USA) was used for data analysis. Taylor series linearization was used for estimation of SEs. Thus, the stratified and clustered data, as well as non-response patterns, were considered for data analysis. Using weights enabled us to provide rates that are generalizable to the U.S. population.
For univariate analyses, we reported means or frequencies (%) when appropriate. For multivariate analysis, we used logistic regression models in the pooled sample, and also stratified by race and gender. SLE was the main predictor of interest, and the outcome was risk of endorsement for MDE measured in 2011 using CIDI. Covariates included baseline demographics, socioeconomics, depressive symptoms (CES-D), physical health (hypertension, diabetes, chronic lung disease, heart disease, stroke, cancer, and arthritis), and health behaviors measured in 1986. Gender and race were the focal moderators.
We did not control for SLE in 2011. Controlling for SLE concurrent with outcome is needed when the focus is to know the residual effects of SLE in 1986 on MDE in 2011 net of SLE in 2011. Thus, the goal of this study is to study predictive (not residual) effect of SLE on MDE. With that goal, controlling for SLE in 2011 will be a case of over-adjustment, as higher SLE in 2011 may be in the causal path for the effect of SLE in 1986 on MDE in 2011. A significance level of
The current analysis included 1,129 individuals who were followed for 25 years and completed surveys in wave 1 and wave 5 of the ACL study. Participants were White men (
Table
Mean (SD) | Min–Max | Mean (SD) | Min–Max | Mean (SD) | Min–Max | Mean (SD) | Min–Max | Mean (SD) | Min–Max | |
---|---|---|---|---|---|---|---|---|---|---|
All | Whites | Blacks | Men | Women | ||||||
Age | 47.77 (0.53) | 46.69–48.84 | 47.96 (0.60) | 46.75–49.17 | 46.33 (0.72) | 44.89–47.78 | 46.44 (0.66) | 45.10–47.78 | 48.96 (0.59) | 47.77–50.15 |
Education |
12.53 (0.10) | 12.34–12.73 | 12.69 (0.11) | 12.48–12.90 | 11.37 (0.23) | 10.90–11.84 | 12.74 (0.13) | 12.47–13.00 | 12.35 (0.09) | 12.18–12.53 |
Income |
5.41 (0.09) | 5.22–5.60 | 5.57 (0.10) | 5.36–5.77 | 4.25 (0.18) | 3.88–4.62 | 5.78 (0.11) | 5.57–6.00 | 5.08 (0.10) | 4.88–5.27 |
CMC |
0.79 (0.03) | 0.74–0.85 | 0.78 (0.03) | 0.71–0.84 | 0.91 (0.05) | 0.81–1.02 | 0.68 (0.04) | 0.61–0.76 | 0.89 (0.03) | 0.83–0.96 |
Function |
3.72 (0.02) | 3.69–3.75 | 3.72 (0.02) | 3.69–3.76 | 3.69 (0.03) | 3.62–3.76 | 3.78 (0.02) | 3.73–3.82 | 3.67 (0.02) | 3.63–3.71 |
Cognition |
0.69 (0.03) | 0.62–0.76 | 0.65 (0.04) | 0.57–0.73 | 1.00 (0.05) | 0.90–1.10 | 0.67 (0.04) | 0.60–0.74 | 0.72 (0.04) | 0.63–0.80 |
SLE |
0.88 (0.02) | 0.84–0.92 | 0.88 (0.02) | 0.84–0.92 | 0.87 (0.03) | 0.81–0.94 | 0.85 (0.03) | 0.79–0.91 | 0.90 (0.02) | 0.86–0.95 |
Table
OR (SE) | 95% CI | OR (SE) | 95% CI | OR (SE) | 95% CI | OR (SE) | 95% CI | |
---|---|---|---|---|---|---|---|---|
Model 1 |
Model 2 |
Model 3 |
Model 4 |
|||||
Gender (females) | 1.12 (0.28) | 0.68–1.84 | 2.38 (1.28) | 0.81–7.03 | 1.12 (0.28) | 0.68–1.84 | 2.39 (1.29) | 0.81–7.09 |
Race (blacks) | 0.92 (0.23) | 0.55–1.54 | 0.88 (0.22) | 0.54–1.45 | 1.04 (0.51) | 0.39–2.77 | 1.05 (0.50) | 0.41–2.72 |
Age | 0.98 (0.01) | 0.96–1.01 | 0.98 (0.01) | 0.96–1.01 | 0.98 (0.01) | 0.96–1.01 | 0.98 (0.01) | 0.96–1.01 |
Education | 0.97 (0.08) | 0.83–1.13 | 0.97 (0.07) | 0.83–1.13 | 0.97 (0.08) | 0.83–1.13 | 0.97 (0.07) | 0.83–1.13 |
Income | 0.98 (0.06) | 0.86–1.11 | 0.98 (0.06) | 0.88–1.10 | 0.98 (0.06) | 0.86–1.11 | 0.98 (0.06) | 0.88–1.10 |
Chronic medical conditions | 1.18 (0.20) | 0.85–1.65 | 1.15 (0.19) | 0.82–1.61 | 1.18 (0.20) | 0.85–1.66 | 1.15 (0.19) | 0.82–1.61 |
Self-rated health (Poor) | 1.37 (0.79) | 0.43–4.40 | 1.46 (0.80) | 0.49–4.40 | 1.37 (0.79) | 0.43–4.41 | 1.47 (0.80) | 0.49–4.40 |
Obese | 1.36 (0.36) | 0.80–2.30 | 1.31 (0.38) | 0.73–2.35 | 1.36 (0.36) | 0.80–2.30 | 1.31 (0.38) | 0.73–2.36 |
Function | 0.86 (0.25) | 0.48–1.55 | 0.84 (0.23) | 0.48–1.46 | 0.86 (0.25) | 0.48–1.55 | 0.84 (0.23) | 0.48–1.46 |
Cognition | 0.94 (0.12) | 0.73–1.20 | 0.94 (0.11) | 0.74–1.20 | 0.94 (0.12) | 0.73–1.21 | 0.95 (0.11) | 0.75–1.20 |
Depressive symptoms (CES-D) | 2.58 (0.85) |
1.33–4.99 | 2.73 (0.83) |
1.47–5.05 | 2.58 (0.85) |
1.33–5.00 | 2.72 (0.84) |
1.47–5.05 |
Smoking | 1.61 (0.45) | 0.91–2.84 | 1.63 (0.46) |
0.92–2.89 | 1.60 (0.45) | 0.91–2.80 | 1.62 (0.45) |
0.92–2.85 |
Drink | 0.74 (0.16) | 0.48–1.13 | 0.74 (0.16) | 0.47–1.14 | 0.74 (0.16) | 0.48–1.13 | 0.73 (0.16) | 0.47–1.14 |
SLE | 1.41 (0.22) |
1.03–1.93 | 2.09 (0.60) |
1.17–3.74 | 1.58 (0.71) | 0.64–3.92 | 2.46 (1.37) | 0.80–7.55 |
SLE × gender (females) | 0.54 (0.16) |
0.29–1.00 | 0.53 (0.17) |
0.28–1.00 | ||||
SLE × race (blacks) | 0.90 (0.26) | 0.51–1.61 | 0.87 (0.25) | 0.49–1.54 |
Table
Men |
Women |
Whites |
Blacks |
|||||
---|---|---|---|---|---|---|---|---|
OR (SE) | 95% CI | OR (SE) | 95% CI | OR (SE) | 95% CI | OR (SE) | 95% CI | |
Gender (Females) | – | – | – | – | 1.47 (0.44) | 0.80–2.67 | 1.20 (0.52) | 0.49–2.91 |
Race (Blacks) | 1.29 (0.59) | 0.51–3.24 | 1.20 (0.39) | 0.63–2.30 | – | – | – | – |
Age | 0.97 (0.02) | 0.92–1.01 | 0.99 (0.01) | 0.96–1.02 | 0.98 (0.01) | 0.96–1.01 | 0.97 (0.02) | 0.93–1.03 |
SLE | 2.10 (0.58) |
1.20–3.66 | 1.31 (0.19) |
0.98–1.74 | 1.60 (0.30) |
1.10–2.32 | 1.30 (0.22) | 0.93–1.82 |
Gender (females) | – | – | – | 0.46–1.99 | 1.37 (0.39) | 0.77–2.44 | 1.07 (0.50) | 0.42–2.75 |
Race (Blacks) | 1.31 (0.54) | 0.57–2.99 | 0.96 (0.35) | – | – | – | ||
Age | 0.97 (0.02) | 0.93–1.01 | 0.99 (0.01) | 0.96–1.02 | 0.98 (0.01) | 0.96–1.01 | 0.97 (0.02) | 0.93–1.01 |
Education | 0.97 (0.13) | 0.74–1.27 | 0.87 (0.08) | 0.73–1.03 | 0.92 (0.08) | 0.76–1.10 | 0.88 (0.12) | 0.66–1.17 |
Income | 0.93 (0.12) | 0.72–1.21 | 0.94 (0.07) | 0.81–1.09 | 0.92 (0.06) | 0.80–1.06 | 0.98 (0.08) | 0.83–1.16 |
SLE | 2.09 (0.57) |
1.20–3.63 | 1.26 (0.18) | 0.93–1.69 | 1.52 (0.29) |
1.05–2.22 | 1.34 (0.24) | 0.94–1.92 |
Tables
OR (SE) | 95% CI | OR (SE) | 95% CI | OR (SE) | 95% CI | OR (SE) | 95% CI | |
---|---|---|---|---|---|---|---|---|
Men | Women | Whites | Blacks | |||||
Gender (females) | – | – | – | – | 1.13 (0.32) | 0.64–1.98 | 0.92 (0.47) | 0.33–2.58 |
Race (Blacks) | 1.17 (0.49) | 0.50–2.73 | 0.73 (0.27) | 0.35–1.54 | – | – | – | – |
Age | 0.95 (0.02) |
0.91–1.00 | 1.00 (0.02) | 0.96–1.04 | 0.98 (0.01) | 0.95–1.01 | 0.96 (0.02) | 0.92–1.01 |
Education | 1.00 (0.14) | 0.76–1.33 | 0.93 (0.08) | 0.77–1.11 | 0.97 (0.09) | 0.80–1.17 | 1.00 (0.12) | 0.79–1.27 |
Income | 0.99 (0.12) | 0.77–1.27 | 0.99 (0.07) | 0.87–1.14 | 0.97 (0.07) | 0.84–1.12 | 1.02 (0.08) | 0.87–1.19 |
Chronic Medical Conditions | 1.95 (0.57) |
1.09–3.51 | 0.81 (0.17) | 0.52–1.24 | 1.19 (0.23) | 0.81–1.76 | 1.07 (0.37) | 0.54–2.13 |
Self-rated health (Poor) | 1.39 (1.75) | 0.11–17.52 | 1.57 (0.83) | 0.54–4.53 | 1.45 (0.98) | 0.37–5.70 | 1.09 (0.68) | 0.31–3.85 |
Obese | 0.83 (0.52) | 0.24–2.91 | 1.81 (0.52) |
1.01–3.24 | 1.29 (0.41) | 0.68–2.45 | 1.90 (0.88) | 0.74–4.86 |
Function | 1.11 (1.00) | 0.18–6.79 | 0.78 (0.20) | 0.46–1.32 | 0.79 (0.26) | 0.40–1.54 | 1.22 (0.33) | 0.71–2.11 |
Cognition | 0.90 (0.19) | 0.58–1.38 | 0.98 (0.13) | 0.75–1.28 | 0.83 (0.14) | 0.59–1.17 | 1.63 (0.34) |
1.07–2.49 |
Depressive Symptoms (CES-D) | 1.80 (0.78) | 0.75–4.29 | 3.49 (1.23) |
1.72–7.08 | 2.45 (0.94) |
1.13–5.31 | 3.42 (1.31) |
1.58–7.40 |
Smoking | 1.62 (0.59) | 0.78–3.37 | 1.60 (0.53) | 0.82–3.11 | 1.51 (0.47) | 0.81–2.84 | 1.93 (0.67) |
0.96–3.90 |
Drink | 0.93 (0.50) | 0.32–2.72 | 0.69 (0.21) | 0.38–1.26 | 0.67 (0.15) |
0.42–1.07 | 1.67 (0.72) | 0.69–4.00 |
SLE | 1.94 (0.49) |
1.17–3.24 | 1.15 (0.15) | 0.87–1.50 | 1.43 (0.27) |
0.98–2.08 | 1.29 (0.21) | 0.93–1.79 |
In line with the
Our findings may be due to gender differences in the threshold of reporting stress. Our findings may also be due to the gender differences in risk perception (
Race and gender also determine the risk of exposure to stress (
Gender and race may change availability, access, use, and effects of stress buffers, such as family (
Literature has suggested that race, gender, and their interstations have implications for coping styles, including but not limited to use of problem-focused or emotional coping styles (
Although our study conceptualized gender not sex as the moderator of the stress–depression link, our findings are supported by a literature on the role of sex as a moderator of the interactions between stress, genetic predisposition, and depression. For instance, Kurrikoff et al., who did not find a main effect of the 5-HTTLPR genotype or the interaction between 5-HTTLPR and SLE on MDD documented the 5-HTTLPR × gender interaction on MDD in case of interpersonal SLE on MDE. The study showed the lowest prevalence of depression among female s′-allele carriers who had low levels of exposure to interpersonal adverse events. Authors concluded that the complex interplay between serotonin, social stress, and depression is sex dependent (
Our study had its own limitations. Reliability and validity of SLE and depression measures may depend on race and gender (
Our study did not consider type of stressors. First and foremost, because current SLEs were not included in the model, and as we know that individuals with higher levels of SLEs at one time point are more likely to continue to experience SLEs, we cannot rule out the possibility that the effects of SLE on MD are not due to continuity across time in the level of SLEs. Thus, the results should not be interpreted as the residual effect of SLE in 1986 over SLE in 2011 due to lack of controlling for concurrent SLE at the time of outcome (2011). Second, men and women experience different types of SLEs, such as unemployment, child-care, domestic violence, and caregiving. Such gender differences may explain why men and women differ in the link between count of stressors and risk of depression (
Despite the above limitations, our study makes a unique contribution to the literature on race and gender differences on the psychological response to stress, and disparities in development of depression over a long period of time. Based on our findings, even in the presence of the same level of stress exposure, long-term mental health consequences of stress may depend on gender (
The mechanism behind gendered response to stress is still unclear (
To conclude, gender, but not race, altered the longitudinal association between the baseline level of SLE (1986) and risk of MDE 25 years later (2011). Thus, each incremental increase in SLE may better predict risk of MDE 25 years later among men compared to women. The predictive role of SLE for long-term risk of MDE seems to be similar for Whites and Blacks. Additional research is needed on the complex links between gender, race, exposure to stress, and development of depression.
Informed consent was obtained from all individual participants included in the study. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
SA designed the work and analyzed the data. ML drafted the manuscript and revised the draft. Both authors approved the final draft.
SA and ML do not have any potential conflicts of interest to report.
SA is supported by the Heinz C. Prechter Bipolar Research Fund and the Richard Tam Foundation at the University of Michigan Comprehensive Depression Center.
The Americans’ Changing Lives (ACL) study was supported by Grant # AG018418 from the National Institute on Aging (DHHS/NIH), and per the NIH Public Access Policy requires that peer-reviewed research publications generated with NIH support are made available to the public through PubMed Central. NIH is not responsible for the data collection or analyses represented in this article. The ACL study was conducted by the Institute of Social Research, University of Michigan.
The Supplementary Material for this article can be found online at