Journal of Public Health | Vol. 37, No. 3, pp. 419 –426 | doi:10.1093/pubmed/fdu062 | Advance Access Publication August 30, 2014

Racial/ethnic and gender differences in the association between depressive symptoms and higher body mass index Gergana Kodjebacheva1,2, Daniel J. Kruger3, Greg Rybarczyk4, Suzanne Cupal5 1

Department of Public Health and Health Sciences, University of Michigan – Flint, Flint, MI 48502, USA International Institute, University of Michigan – Ann Arbor, Ann Arbor, MI 48109, USA School of Public Health, University of Michigan – Ann Arbor, Ann Arbor, MI 48109, USA 4 Department of Earth and Resource Science, University of Michigan – Flint, Flint, MI 48502, USA 5 Genesee County Health Department, Flint, MI 48502, USA Address correspondence to Gergana Kodjebacheva, E-mail: [email protected] 2 3

Aim The study investigated the socio-demographic differences in the association between depressive symptoms and higher body mass index (BMI). Subjects and methods In Genesee County, Michigan, random samples of households were drawn from all residential census tracts. The Speak to Your Health! Survey was administered among adults aged 18 years and older in these households. To conduct this cross-sectional study, data from three waves of survey data collection (2007, 2009 and 2011) were combined resulting in a sample of 3381 adults. Self-reported height and weight were used to calculate BMI. Depressive symptoms were assessed with Brief Symptoms Inventory items. Socio-demographic factors included age, race/ethnicity, gender and education. Results Using stepwise linear regression, gender (b ¼ 0.04, P ¼ 0.02) and the interaction terms of race/ethnicity  depressive symptoms (b ¼ 0.15, P , 0.001) and gender  depressive symptoms (b ¼ 0.05, P ¼ 0.01) uniquely predicted BMI. Conclusion Women had a higher BMI than men, and depressive symptoms were more strongly associated with BMI among African Americans and women than among non-Latino Whites and men. Tailored interventions to alleviate depressive symptoms in African Americans and females may help decrease racial/ethnic and gender differences in depressive symptoms and obesity. Keywords adults, mental health, obesity

Introduction According to meta-analysis of research studies, clinical depression and sub-clinical depressed mood were associated with higher body mass index (BMI) in adults.1 – 4 Several mechanisms explain how psychological distress influences obesity. First, depressive symptoms may promote fat storage in the body by increasing cortisol levels.5 Another explanation is that negative emotions may lead to the consumption of high-calorie meals and binge eating.6,7 In addition, people’s sadness and hopelessness might decrease their motivation to exercise, thus contributing to higher BMI.8 – 10 The influences of socio-demographic factors on the association between depressive symptoms and higher BMI are not well understood.1,2,4,10,11 Research on the influence of sociodemographic factors such as race/ethnicity may inform the

development of effective interventions. Mental health interventions that provided services to a specific racial/ethnic group were four times as likely to be effective in alleviating depressive symptoms compared with interventions that targeted people of different racial/ethnic groups in meta-analysis of 76 studies.12 Since weight gain was a late consequence of depressed mood in a meta-analysis of longitudinal studies,4 implementing timely strategies based on the cultural context of the participant to prevent and manage psychological

Gergana Kodjebacheva, Assistant Professor, Faculty Associate Daniel J. Kruger, Research Assistant Professor Greg Rybarczyk, Assistant Professor Suzanne Cupal, Public Health Supervisor

# The Author 2014. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: [email protected].

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A B S T R AC T

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Latina was a risk factor in the association between depressive symptoms and obesity.1 One limitation was that the study sample was not representative of the BRFSS because the particular question on depressive symptoms ‘During the past 30 days, for about how many days have you felt sad, blue, or depressed’ was administered in a limited number of states.1 Given these conflicting findings and the limited research on racial/ethnic influences, we investigated the sociodemographic differences in the association between depressive symptoms and BMI. We conducted the cross-sectional research in a demographically representative sample in Genesee County, Michigan, USA. The socio-demographic determinants included age, gender, race/ethnicity and education. The participants completed a survey, which included items on depressive symptoms.

Methods Setting

Genesee County and its most populous city, Flint have experienced significant economic and population declines in part due to the closure of automobile manufacturing plants.13 The unemployment rate in the county more than doubled from 4.1% in December, 2000 to 9.8% in December, 2011.14 The county’s population decreased by 10 351 people from 415 439 in 2000 to 425 790 individuals in 2010.15 Between 2000 and 2012, the rate of violent crime increased by 9% in Genesee County.16 Cross-sectional design

To monitor and assess residents’ health and health needs, a committee composed of academicians and community members developed the Prevention Research Center of Michigan’s (PRC/MI) Speak to Your Health! Survey.17 – 19 Previous manuscripts provided details on the Speak to Your Health! Survey.17 – 19 The survey was administered among residents aged 18 years and older across all residential Census tracts in Genesee County, MI. Random samples of households were drawn from these tracts to represent all areas of Genesee County. In this cross-sectional study, three waves of survey data (2007, 2009 and 2011) were combined into a sample of 3381 adults. A total of 4585 completed the survey in 2007, 2009 and 2011; these 4585 participants were part of the complete sample. Of them, 3381 had complete data on all variables; these 3381 participants were part of the analytic sample included in the present analysis. The complete and analytic samples were similar in terms of age, education in years, gender and BMI (results not shown). Participants were asked

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distress may help reduce depressive moods and subsequently obesity. Research on the influence of socio-demographic factors on the association between depressive symptoms and obesity had conflicting findings.1,2,4,10,11 Female gender either had no influence4 or was a greater risk factor1,2 in the relationship between depressed mood and obesity. Some reasons for the gender difference in the association between depressed mood and obesity may include disparities in genetic predisposition to both depressed mood and obesity; stigmatization; access to care and choice of providers.1 Educational attainment had no influence on the association between depressive symptoms and obesity in most1,4,10 but not all studies.11 One study on racial/ethnic differences reported a more pronounced association between depression and obesity among Latinas;1 two other studies found no racial/ethnic differences.10,11 People of lower educational attainment and Latinas may have reduced access to mental health care. The depressive symptoms of people of lower educational attainment and Latinas thus may remain untreated for longer periods of time, which subsequently could lead to reduced exercise and increased BMI. These prior studies with conflicting findings had important limitations. A meta-analysis of nine longitudinal studies found that depression increased the likelihood of becoming obese. It found no differences in the association by gender and age. Limitations of the meta-analysis included a small number of publications, a statistically significant trend of publication bias and the inclusion of only age and gender as co-variates.4 In another meta-analyses of 17 studies, which also only focused on gender and age differences, the association between depression and obesity was especially pronounced among females; the relationship did not differ by age.2 Three studies focusing on racial/ethnic differences in the association between depressive symptoms and obesity were identified. In an investigation of 4651 US middle-aged females in a health plan in Washington and Northern Idaho, race/ethnicity, age and educational levels were not risk factors in the association between depression and obesity; the study consisted primarily of middle class and White women.10 A study of 4162 US adults aged 65 years and older found that being African American was not associated with having comorbid depression/high BMI.11 Lower education was, however, related to having such comorbidity.11 The findings of this study, which was administered in five counties in North Carolina, may not be applicable to other parts of the US and to adults younger than 65.11 The third study focusing on racial/ethnic differences performed analysis in a sub-set of the 2001 Behavioral Risk Factor Surveillance Survey (BRFSS) participants in the USA.1 Among 44 800 subjects, being

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if they had previously taken the survey and if so, in what year they had completed the survey. No participant reported to have previously taken the survey. Self-reported measures and data analysis

Stepwise linear regression was used to determine the unique predictors of BMI. In stepwise regression, predictor variables are determined by an automatic procedure in the form of a sequence of t-tests.21 In this study, bidirectional elimination was used, in which a combination of forward selection and backward elimination was carried out to test for variable(s) to be included or excluded at each step.22 Forward selection begins with no variables in the model, tests the addition of each variable and adds the variable(s) that would improve the model the most. Backward elimination starts with all variables, tests the deletion of each variable and deletes variable(s) that would improve the model the most by being deleted. The standardized regression coefficients in the stepwise regression were calculated. Because the coefficients in the b column are all in the same standardized units, they can be compared to determine which one has a stronger effect. The ultimate goal of stepwise regression is to identify the regression model that best predicts the outcome.21,22 BMI was the dependent variable in stepwise linear regression. In Model 1, the step-wise linear regression identified the

Table 1. Speak to Your Health! Survey items used for the self-reported measurements in Genesee County, Michigan Age What is your month and year of birth? Gender What is your sex? Female; male Race/ethnicity How would you describe your racial/ethnic background? White; Black or African American; Hispanic or Latino/a, Asian, Native Hawaiian or Other Pacific Islander; American Indian or Alaska Native, Multiracial, Specify, Other, specify, Do not know Education What is the highest grade or degree you completed in school? Less than high school; HS graduate or GED; some college, no degree, technical school; associates degree; bachelor’s degree; masters, doctorate or post-doctoral studies Depressive symptoms During the past week, including today, please mark how often you felt or thought the following way. How often have you Felt lonely (1) Never, (2) Almost never, (3) Sometimes, (4) Fairly often or (5) Very often? Felt blue or sad (1) Never, (2) Almost never, (3) Sometimes, (4) Fairly often or (5) Very often? Felt no interest in things (1) Never, (2) Almost never, (3) Sometimes, (4) Fairly often or (5) Very often? Body mass index About how tall are you without shoes? Enter feet and inches. . . About how much do you weigh without shoes? Enter weight in pounds. . .

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BMI, a continuous variable, was calculated using the respondents’ reported height and weight (Table 1). Sociodemographic variables included age, gender, race/ethnicity and education. Ethnicity was categorized as ‘non-Latino White’ and ‘African American’. Participants were asked for their highest level of education completed (i.e. less than high school, high school graduate or GED, some college, associate’s degree, bachelor’s degree, master’s/doctoral/postdoctoral degree). Depressive symptoms were assessed with Brief Symptoms Inventory items.20 Composite scores were calculated using these Brief Symptoms Inventory items. A two independent samples t-test was conducted to compare the mean BMI between African Americans and non-Latino Whites. The bivariate Pearson’s correlation coefficients between variables were calculated.

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The Chronbach’s alpha of the depressive symptom items was 0.89. As depressive symptom scores increased, BMI increased as well (r ¼ 0.10, P , 0.01) (Table 3). In Model 1, gender (b ¼ 0.04, P ¼ 0.02) and the interaction terms of race/ethnicity  depressive symptoms (b ¼ 0.15, P , 0.001) and gender  depressive symptoms (b ¼ 0.05, P ¼ 0.01) uniquely predicted BMI (Table 4). Once these factors Table 3. Bivariate Pearson’s correlation coefficients, n ¼ 3381 Gender Race

Education Depressive

BMI

symptoms

Results

Age

Most participants were non-Latino White and female. The mean age (+standard deviation SD) of participants was 55 (+7) years. The mean years (+SD) of education among participants were 12 (+2) (Table 2). The mean BMI was higher in African Americans than in non-Latino Whites. Specifically, the mean BMI among African Americans was 29.82 and that among non-Latino Whites was 28.65 (t ¼ 4.77; P , 0.01).

0.03

Gender

20.07** 20.09** 20.04*

Race/

0.03

20.10**

20.03 0.04*

20.01 0.02

20.32**

0.08**

ethnicity Education

20.03*

20.01

Depressive

0.10**

symptoms *P , 0.05, **P , 0.01.

Table 2. Socio-demographic characteristics of the Speak to Your

Table 4. Results of stepwise linear regression predicting body mass

Health! Survey participants, n ¼ 3381

index among the Speak to Your Health! Survey participants, n ¼ 3381

Age: mean + SD

55 + 16

Predictor

T

b

18– 24 years

109 (3.2%)

(standardized

25– 44 years

715 (21.1%)

coefficient)

45– 64 years

1556 (46.0%)

65– 95 years Education, years: mean + SD (range, years)

1001 (29.6%)

Model 1

12 + 2 (10– 18)

Highest grade or degree completed in school

P-value

Race/ethnicity  Depressive

0.15

7.71 ,0.01

symptoms

Less than high school

1129 (33.4%)

Gender  Depressive symptoms

0.05

2.58

High school graduate or GED

956 (28.3%)

Gender

0.04

2.43

0.02

Some college

588 (17.4%)

Race/ethnicity

0.02

1.12

0.25

Technical school

63 (1.9%)

Age  Depressive symptoms

0.02

0.69

0.44

Associated degree

221 (6.5%)

Depressive symptoms

0.02

0.60

0.55

Bachelor’s degree

249 (7.4%)

Age

20.001

20.03

0.98

Master’s, doctoral or post-doctoral degree

175 (5.2%)

Education

20.005

20.27

0.81

0.01

Model 2a

Gender Female, n (%)

2173 (64.3%)

Year (survey wave)

0.04

2.17

0.03

Male, n (%)

1208 (35.7%)

Race/ethnicity  Depressive

0.14

7.55

0.01

Race/ethnicity

symptoms

African American, n (%)

1509 (44.6%)

Gender  Depressive symptoms

0.05

2.75

0.006

Non-Latino White, n (%)

1872 (55.4%)

Gender

0.04

2.43

0.02

Race/ethnicity

0.03

1.20

0.23

20.02

20.76

0.45

0.02

0.70

0.48

Year (survey wave) 2007

1244 (36.8%)

Age  Depressive symptoms

2009

1361 (40.3%)

Depressive symptoms

2011

776 (23.0%)

Age

20.001

20.07

0.95

Education

20.008

20.43

0.67

*Age, education and year (wave) were continuous predictors in the linear regression.

a

The variable year (survey wave) was added in Model 2.

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influence of age, gender, race/ethnicity, education, depressive symptoms and the interaction terms for demographic variables with depressive symptoms on BMI. Model 2 included all predictors as those in Model 1 in addition to the variable ‘year (survey wave)’. ‘Year (survey wave)’ was added as a predictor in Model 2 to account for including three waves of survey data (i.e. 2007, 2009 and 2011). Age (in years), education (i.e. years of education), year (survey wave) and depressive symptoms composite scores were continuous variables in the linear regression. Statistical significance was defined as P , 0.05. The statistical analyses were conducted using SPSS (IBM, 2012).

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Discussion Main findings of this study

A more pronounced relationship between depressive symptoms and obesity among African Americans existed. The presence of a gender difference in depressive symptoms and obesity is consistent with most prior research.2 The lack of age and education differences in the association between depressive symptoms and obesity in the present study also supports most prior research.1,4,10 The correlation between depressive symptoms and BMI was positive and statistically significant; however, the correlation was relatively weak. Such weak correlation may imply that factors other than depressive symptoms contribute to higher BMI. Increasing survey year was associated with higher BMI. What is already known on this topic

An African American individual may gain more weight than a non-Latino White individual suffering from the same depressive symptoms. The reasons for the greater weight gain in African Americans may be their stronger stigma related to having depression, reduced likelihood to seek mental health services and lower quality of received mental healthcare services compared with non-Latino Whites. Stigma, defined as the perception of having a ‘spoiled identity’23 and undesirable traits,24 is an obstacle to seeking mental health care.25 The US Department of Health and Human Services identified reducing stigma as a major goal in increasing mental health care.26 African American patients reported greater stigma related to depression than non-Latino Whites in prior research.27,28 As a result of such stigma, African Americans are less likely to seek mental health services than non-Latino Whites.29,30 Once African Americans do seek mental health services, they receive lower quality of care than non-Latino Whites.29,30 As a result of these disparities, African Americans’ depressive symptoms may remain untreated or undertreated, while

non-Latino Whites’ depressive symptoms may be successfully managed. African Americans’ experiences of stigma and lower access to adequate and quality mental health care may exacerbate their risk for having untreated/undertreated depressive symptoms and subsequently obesity. The gender difference in the association between depressive symptoms and obesity may be explained by the stronger genetic predisposition to depressed mood and obesity in women than in men. A significant increase in anxiety and depression scores for females homozygous for certain genes existed in one study.31 A statistically significant association between BMI and homozygosity for these genes for females but not males was present.31 The study concluded that genetic factors played significant roles for obesity and psychological distress, particularly in females.31 In addition, females’ depressed mood may persist over time due to social factors such as greater peer pressures during adolescence and lower wages and reduced career opportunities in adulthood compared with men.32 These social factors may contribute to the stronger association between depression and obesity among females. Future research should investigate the reasons for the racial/ethnic and gender differences in the association between depressive symptoms and obesity. What this study adds

The findings have implications for intervention research. Interventions to reduce obesity are much needed in areas such as Michigan. The rate of obesity increased from 20% in 2000 to 31.3% in 2012 in the state.33 Only four other states, specifically West Virginia, Alabama, Louisiana and Mississippi, had higher obesity rates than Michigan in 2012.33 The obesity rate in Genesee County was even higher than that in Michigan; the rate of obesity was 35.9% in Genesee County in 2012.34 Most interventions to decrease obesity rates in Michigan do not target the pathways from depressive symptoms to obesity. The Michigan Nutrition, physical activity and obesity program, for example, enhanced public parks and improved walking trails.35 It initiated the planting of neighborhood and school gardens and the creation of farmer’s markets. The Faith-Based Initiative, through partnership with African American churches, increased access to fresh fruits and vegetables and places for physical activity.35 Such programs are much needed but cannot fully succeed in decreasing obesity rates if people’s depressive symptoms prevent them from consuming healthy meals and engaging in exercise and outdoor activities. The findings on the racial/ethnic and gender difference in the association between depressive symptoms and obesity support the development of tailored interventions among African Americas and females. Compared with non-Latino Whites, African Americans have expressed lower acceptability

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were accounted for, no other demographic characteristic or interaction term explained a significant proportion of the variance in the association between depressive symptoms and BMI. In Model 2, increasing year (wave) was a significant unique predictor of higher BMI (b ¼ 0.04, P ¼ 0.03). Gender and the interaction terms of race/ethnicity  depressive symptoms, gender  depressive symptoms remained statistically significant in Model 2 (Table 4). In both models, therefore, women had a higher BMI than men, and depressive symptoms were more strongly associated with BMI among African Americans and women than among non-Latino Whites and men. The interaction term depressive symptoms  race had the largest standardized coefficient among all statistically significant predictors.

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Limitations of this study

The survey response rate was 25%. The results may not be generalized to all US areas. All measurements were selfreported. People tend to overestimate their height and underestimate their weight.42 No question on participants’ income was asked in the 2007, 2009 and 2011 surveys because there was a high refusal rate to the household income question in earlier survey waves. We used the education variable to assess socioeconomic status. Another limitation is that the results of this study cannot be generalized to clinical depression. They may be better generalized to individuals experiencing subclinical depressive mood who are at risk for depression. The full depressive symptoms scale was not used; however, the

four items used to assess depressive symptoms exhibited a high reliability with a Chronbach’s alpha of 0.89. Causal and temporal associations could not be assessed in this cross-sectional study. The direction of the association between depressive symptoms and obesity may be opposite to that reported in this study. Stigma is attached to obesity, particularly among non-Latino whites and people of higher socioeconomic status.43 – 46 Studies on the influence of obesity on depressive symptoms had mixed findings. In the Third National Health and Nutrition Examination Survey (NHANES), obesity was related to depression primarily among individuals with severe obesity.44 In the National Comorbidity Survey, obesity was associated with major depression; the association was more pronounced among non-Latino whites and college graduates.45 In a representative sample of 2020 adults, there was no influence of obesity on depression. However, being overweight increased the likelihood of depression among the more educated adults.46 Future studies should investigate socio-demographic differences in the bi-directional relationship between depressive symptoms and obesity. Interventions to reduce obesity rates in the USA as a whole and in Michigan in particular are much needed. Depressive symptoms were stronger predictors of BMI for African Americans and women than for non-Latino Whites and men. Interventions to prevent and manage physiological distress among African Americans and females may decrease obesity rates. In addition, clinicians may consider monitoring weight gain among patients with depressive symptoms over time.

Acknowledgement We thank the Speak to Your Health! Community Survey Committee.

Funding The Speak to Your Health Survey was supported by the Centers for Disease Control and Prevention (CDC) grants U48/CCU515775 and 1U48DP001901-01 through the Prevention Research Center of Michigan.

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of antidepressant medication,36 greater preference for professional counseling37 and increased interest in counseling from clergy.38 Future research should assess the effectiveness of quality improvement programs in physician offices, offering a choice of mental treatment options that consider preferences of African Americans. Interventions to prevent and treat mental health problems among females may be especially important in adolescence. The higher prevalence of depression in females compared with males first emerged in puberty in prior research.39 The most effective interventions to reduce depression in adolescent girls provided cognitive-behavioral therapy. Others were multi-faceted interventions targeting negative stress responses and family conflict.40 Yet different effective programs provided coping classes teaching adolescent girls how to overcome unconstructive thoughts and behaviors.40 Future research should assess the effectiveness of these interventions on healthy weight maintenance. Decreasing stigma related to having depressive symptoms may be another viable intervention among females. Women who had family/friends with depression felt less stigmatized than women without family/friends with the condition in a study of 3047 adults.41 In the same study, females who were completely in agreement with their physicians on the treatment for their depression reported less stigmatizing attitudes than women not in complete agreement. Therefore, programs seeking to increase social support and improve patient–physician communication on the appropriate treatment may decrease obesity rates by improving mental health care among women. Residents’ increases in weight over the years may be attributed to the worsening economic situation in Genesee County. Future studies should investigate pathways that may explain how people’s health may have changed over the years. One hypothesis is that people may be discouraged to exercise in their neighborhood because of the worsening crime, thus contributing to increased BMI over the years.

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ethnic and gender differences in the association between depressive symptoms and higher body mass index.

The study investigated the socio-demographic differences in the association between depressive symptoms and higher body mass index (BMI)...
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