1 Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD.
2 Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
3 Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
Received for publication September 11, 2002; accepted for publication June 18, 2003.
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ABSTRACT |
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body mass index; body weight; depression; obesity
Abbreviations: Abbreviations: BMI, body mass index; CI, confidence interval; DIS, Diagnostic Interview Schedule; DSM, Diagnostic and Statistical Manual of Mental Disorders; NHANES III, Third National Health and Nutritional Examination Survey; OR, odds ratio.
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INTRODUCTION |
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Methodological differences across studies have contributed to these inconsistent observations. Friedman and Brownell noted in their 1995 review (8) that most population-based studies had not defined depression according to established psychiatric diagnostic criteria. The definition of obesity also varied. Some investigators used body mass index (BMI), defined as weight in kilograms divided by the square of height in meters, as a continuous variable in their analyses; others used cutpoints to define BMI categories. More recent studies have used cutpoints recommended by the US Public Health Service (the Public Health Service defines obesity as a BMI at or above the 85th percentile) (20) or the National Heart, Lung, and Blood Institute (the Institute defines obesity as a BMI of 30 or higher) (1). The use of cutpoints defined by percentiles is problematic. BMI distributions vary across subpopulations defined by age, gender, race, geography, and time (1). Thus, cutpoints based on percentiles may yield obesity categories that are not comparable across studies.
Since the publication of Friedman and Brownells review, three population-based studies (9, 10, 13) have defined depression using criteria from the Diagnostic and Statistical Manual of Mental Disorders (DSM), Fourth Edition (DSM-IV) (21). Carpenter et al. (13) used data from the 1992 National Longitudinal Alcohol Epidemiologic Survey (22). Among adults aged 18 years or more, high BMI was inversely associated with past-year depression and suicide ideation in men; positive associations were observed in women. Low BMI was associated with past-year depression, suicide attempts, and suicide ideation in men but not in women. When BMI categories were used in the analyses, obesity (BMI 30) was associated with past-year depression in women and was inversely associated with it in men.
Roberts et al. (9), in older adults from the Alameda County Study, found that obesity in 1994 (as defined by the US Public Health Service criteria) was associated with past-year depression in 1995, after controlling for age, sex, education, marital status, social support, social isolation, life events, financial strain, chronic medical conditions, and functional disability. Health and functional disability were the most important indicators of risk for depression in that report. Roberts et al. examined whether the definition of obesity affected their results. There was an association between obesity and past-year depression in unadjusted analyses but not in multivariable analyses when obesity was defined using the National Heart, Lung, and Blood Institute criteria (9). These findings were replicated in a 5-year study of the same cohort (10).
Results from these studies are somewhat disparate with respect to the risk for depression when obesity is defined using National Heart, Lung, and Blood Institute criteria. This may be due to heterogeneity of the obesity-depression relation across obese persons, as has been suggested in recent reviews (7, 8). One approach to resolving this heterogeneity is to stratify obesity by severity (class 1, BMI 3034.9; class 2, BMI 3539.9; class 3, BMI 40); this approach has not previously been used. In addition, the first two studies (9, 13) reported associations for past-year depression, the third (10) for depression within the past 2 weeks; it is possible that the association between obesity and depression depends on the time frame used to measure depression.
The inconsistency of findings from previous research indicates that obesity and depression do not always co-occur. Therefore, it is necessary to ask: When does an association between these conditions occur? Understanding when obesity and depression co-occur in the population is important. First, obesity and depression are common and have important deleterious effects on a wide range of health outcomes (16). Second, a subgroup of people may exist in whom both conditions co-occur with a higher frequency than in the general population. Indeed, clinical studies have reported higher rates of depression and psychopathology among persons with severe obesity (23, 24); however, clinical samples represent a select population. It remains unclear whether severely obese persons represent a subgroup of the obese population that is at particular risk for depression.
Identifying which obese persons will also have depression is a useful approach to resolving the heterogeneity of findings from previous research. Finding this subpopulation will also help investigators focus future research on more informative samples. By specifying an "at-risk" population, researchers can use increasingly precise case definitions to investigate underlying mechanisms and to develop and evaluate more effective preventive and therapeutic interventions for both conditions.
In this study, we investigated whether there is any association between obesity and depression; whether the association between obesity and depression depends on the severity of obesity; and whether the definition of obesity and/or depression influences the occurrence of the association. Data from the Third National Health and Nutritional Examination Survey (NHANES III) (25) presented us with the opportunity to address these questions in a population sample, since a structured diagnostic interview was used to ascertain the presence of DSM major depression in the respondents. We assessed several hypotheses. First, we predicted that there would be no association between obesity (BMI 30) and depression in the NHANES III sample. Our rationale was that obesity is a heterogeneous condition (26), and inconsistent results from previous studies strongly suggested heterogeneity of relations (with depression) within the obesity category (7, 8). In addition, our population sample was young and healthy; chronic medical conditions and functional disability explain much of the association in older adults (9, 10). On the other hand, we hypothesized that severe obesity (BMI
40) would be associated with depression. Severe obesity has been associated with depression in clinical samples (23, 24, 27), and a population-based study of persons aged 2059 years found a higher prevalence of unhappiness (in men) and sadness (in women) in the highest tertile of relative body weight (28).
We expected the occurrence of an association between obesity and depression to depend on the time frame used to measure depression. The time frame used to measure depression influences the assignment of depression status. For example, many persons with past-year depression are excluded from the diagnosis when the past-month time frame is used to measure depression; this can lead to error when evaluating associations between obesity and depression. In addition, individuals recollection of past symptoms can change considerably over time (29); there may be differences in reliability when different time frames are used to diagnose depression.
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MATERIALS AND METHODS |
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A total of 39,695 respondents aged 2 months to 90 years were included in NHANES III. The response rates of 82 percent for the household interviews and 73 percent for the examinations (unpublished data from the National Center for Health Statistics) are typical of large surveys. In this study, we focused on the 8,773 persons aged 1539 years who had been randomly selected for the structured psychiatric interview. A total of 363 respondents (4.1 percent) were excluded from the study analyses: 28 of these (0.3 percent) were missing data on height or weight (precluding calculation of relative body weight), and 338 (3.8 percent) were missing data from the psychiatric interview (precluding ascertainment of depression status). The final sample size for this study was 8,410. Compared with study subjects, persons excluded from the study were more frequently underweight (BMI <18.5) and less frequently obese (
2 test: p > 0.05; data not shown). Those excluded more frequently had an education of eighth grade or less and had less frequently been educated beyond high school (
2 p < 0.01). Approximately 71 percent of participants were White, as compared with 44 percent of excluded persons (
2 p < 0.01); the participation of African-American and Hispanic respondents was comparable. There were no differences by gender, age, or marital status.
Measurements
Diagnostic Interview Schedule
The Diagnostic Interview Schedule (DIS) (31, 32) is a structured interview designed for use by trained lay interviewers. In the NHANES III, only the section required for diagnosis of depressive and bipolar disorders was administered. The DIS allowed diagnoses to be made according to operational criteria in the Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM-III) (33). The DIS has been well characterized (34) and widely used in epidemiologic field studies (35). The DIS/DSM-III diagnosis of major depression in NHANES III is equivalent to a diagnosis based on the DSM-IV.
Major depression
The diagnosis of DIS/DSM-III major depression requires the persistence of depressed mood or anhedonia for at least 2 weeks. An additional four out of eight other possible depressive symptom groups are required to have been clustered with depressed mood or anhedonia during those 2 weeks. The diagnosis is not made if the respondent attributes the symptoms to another illness, medicines, or bereavement or if there is no social or occupational impairment. In this study, the primary measure of depression was past-month DSM-III major depression. Respondents were also assigned a diagnosis of past-year and/or lifetime (ever having met the criteria) major depression. Respondents were assigned a diagnosis of recurrent major depression if they had ever had more than one episode of depression. All depression measures were binary (0 = no depression, 1 = depression).
Relative body weight
Body mass index was calculated from height and weight, which were measured by trained technicians. Participants were grouped into four or six BMI categories based on criteria from the National Heart, Lung, and Blood Institute (1). For the four-category definition, these groups were "normal weight" (BMI 18.524.9; the reference category), "underweight" (BMI <18.5), "overweight" (BMI 25.029.9), and "obese" (BMI 30). For the six-category definition, the obese category was subdivided into "obesity class 1" (BMI 30.034.9), "obesity class 2" (BMI 35.039.9), and "obesity class 3" (BMI
40). We also used BMI as a continuous variable to investigate associations over the entire range of relative body weight.
Covariates
Selection of covariates was based on the published literature (3644), and bivariable logistic regression analyses were performed to identify potentially confounding factors. The potential confounders considered were: age (1519 (referent), 2024, 2529, 3034, or 3539 years); race/ethnicity (non-Hispanic White (referent), non-Hispanic Black, Hispanic, or other); education (8 (referent), 911, 12, or >12 years); marital status (married (referent), divorced/widowed/separated, or never married); physicians rating of health (excellent, good, or fair/poor); dieting for medical reasons (0 = no, 1 = yes); use of psychiatric medicines in the past month (0 = no, 1 = yes); cigarette smoking (never, former, or current); use of alcohol (no use, former use, moderate use, or abuse); and ever use of marijuana (0 = no, 1 = yes) or cocaine (0 = no, 1 = yes).
Statistical analysis
Stata software (45) was used for all statistical analyses. Stata uses weights and sampling data to provide corrected standard error estimates and statistical tests. There was sufficient statistical power to test the study hypotheses (table 1). Most analyses were stratified by gender. The primary analytical method was estimation of the relative odds for depression in each obesity class. The multivariable logistic regression model included the potential confounders. Logistic regression analyses were performed for each definition of DSM-III major depression (past-month, past-year, lifetime, and recurrent) and for each measure of relative body weight (continuous BMI, four BMI categories, and six BMI categories).
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RESULTS |
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DISCUSSION |
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We found that the association between obesity and depression depends on the severity of the obesity. Obese persons had an approximately 1.5-fold higher prevalence of past-month depression than their normal-weight counterparts. Among women, obesity was associated with 82 percent higher odds of past-month depression; the estimate of 73 percent higher odds in men was not statistically significant. These data were inconsistent with our first hypothesis, which predicted null results. However, among the obese, there was heterogeneity in rates of the prevalence of past-month depression. The prevalence of depression was highest in persons with severe obesity (BMI 40). Consistent with our second hypothesis, there was a strong association between severe obesity and depression in logistic regression analyses; when we adjusted for potential confounders to assess whether obesity was independently associated with depression, the association remained strong.
The association between obesity and depression is sensitive to the definition of obesity. This is hardly surprising, since specific conditions exist for the association (severe obesity, in this study). The time frame used to define cases of DIS/DSM-III major depression had only a small effect on the presence of association, especially when obesity was stratified by severity. When depression is defined using DSM criteria, the presence of an association may not be sensitive to the time frame used to measure depression. This may be partly explained by depressions being a chronic condition, and it is of value to researchers in this field in that it suggests that DSM depression within the past year is a reliable measure. Thus, the definition of obesity is the more important determinant of the occurrence of an association with depression. We did not observe any associations when BMI was used as a continuous measure. BMI is an unsatisfactory measure when used as a continuous variablewhich requires the assumption that the relation between obesity and depression is linear across the entire range of relative body weights. Empirical research suggests that health risks are not linearly distributed across the entire range of relative body weights; health risks are dramatically higher in the obese (1, 3, 4), particularly the severely obese (1). As we noted above, when BMI was categorized, heterogeneity in depression risk was observed and severe obesity was associated with depression.
Our results complement findings from other population-based studies that investigated the relation between obesity and DSM major depression. Carpenter et al. (13) found an association between obesity and depression in women; their inverse association in men may correspond to our finding of a relatively low prevalence of depression in obesity class 2 men (which was not statistically significant in logistic regression analyses). Roberts et al. (9, 10) found associations between obesity and depression among older adults with a relatively high prevalence of chronic medical conditions and functional disabilitythe principal indicators of risk for depression in their studies. In contrast, we sampled young adults in whom chronic medical conditions and functional disability were of very low prevalence and were not associated with depression. Palinkas et al. (16) also studied older adults but did not find any association between obesity and depression (defined by scores on the Beck Depression Inventory (47)). These studies did not examine associations across levels of obesity. In another study, Britz et al. (27) compared a clinic sample of severely obese adolescents with obese and normal-weight adolescents from the population and found higher rates of DSM-IV psychiatric disorders in the clinic-based case adolescents. Since the clinic-based case children were considerably more obese than the population-based case children, the investigators could not determine whether the higher rates of psychiatric disorders were related to severe obesity or to treatment-seeking behavior.
This study had several strengths. First, the sample was drawn from the general household population of the United States, thereby minimizing the selection biases of clinical samples. Second, DSM-III diagnostic criteria were applied using data from a structured psychiatric lay interview method (the DIS); the DIS/DSM-III diagnosis of major depression was equivalent to a DSM-IV diagnosis. Third, we stratified the analyses by gender, which allowed us to identify gender-specific patterns of association. Fourth, we were able to examine the association between obesity and depression within subclasses of obesity. Finally, to our knowledge, this is the only study that has assessed the impact on the association between the two conditions of using different time frames to ascertain depression.
Our study also had limitations. First, the design was cross-sectional; a temporal relation between obesity and depression could not be inferred. Second, we had data only on persons aged 1539 years. Thus, the study was limited to that age group. Third, the size of the male subpopulation was too small for us to test for an independent association of severe obesity with depression. However, the sample size was adequate for our primary hypotheses. Fourth, lay interviewers may collect clinical data of limited quality, since they are not trained to probe responses; thus, the validity of diagnoses based on lay interviews can be questioned (48, 49). In addition, problems with the accuracy of the DIS for diagnosing depression (and other psychiatric disorders) have been reported (50, 51), and diagnostic agreement between the DIS and a psychiatrists interview is higher in clinical samples than in community samples (34). Furthermore, nonspecific symptoms such as change in appetite, fatigue, insomnia, and loss of libido are included in the DSM-III diagnostic criteria for depression. These symptoms may be more common in the severely obese (because of a higher prevalence of chronic medical conditions), making careful attribution of symptoms (which requires clinical training) a critical factor in the diagnostic process. However, use of the DIS is a tremendous improvement over use of continuous scales (such as the Beck Depression Inventory (47), the Center for Epidemiologic Studies Depression Scale (52), and the scale of Zung et al. (53)), and our results are consistent with findings from clinical studies. In addition, it is prohibitively expensive to use clinically trained interviewers to ascertain diagnoses in large community surveys.
Our findings indicate that informative approaches to the study of the association between obesity and psychiatric outcomes include the stratification of obesity by severity and the use of DSM definitions of psychiatric disorder. Persons with severe obesity may represent an "at-risk" population in which mechanisms linking obesity to depression can be profitably investigated. This association between severe obesity and depression is also of interest to clinicians, since depression is associated with poorer treatment outcomes. It is important to evaluate and treat depression in persons who seek medical treatment for severe obesity, and it may be that routine screening for depression should be formulated as the standard of care for these patients.
More research is needed to clarify the relation between severe obesity and depression. For instance, the association may be bidirectional (7). In addition, it remains unclear whether gender, age, race, and socioeconomic status influence this association. The use of DSM criteria for the diagnosis of depression in population-based studies has been an important step forward, but research measures will have enhanced construct validity when interviewers are clinically trained. Clinic-based samples will be useful for identifying other potential risk factors for depression in the obese, since they often represent the extreme of disease or syndrome presentations and thus may minimize ambiguity in case definitions and heterogeneity in research samples. Prospective studies will ultimately be required in order to clarify the temporal relation between obesity and depression, but these studies must await the identification of potential risk factors for depression in the obese. These studies will require active collaboration between investigators to surmount the challenges involved, which include high costs, the need for large study samples, lengthy follow-up, and repeated assessments, and the problem of censorship in studies of long duration.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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