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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Arch Gen Psychiatry. Author manuscript; available in PMC Feb 23, 2012.
Published in final edited form as:
PMCID: PMC3285453
NIHMSID: NIHMS354489

Depressive Symptoms and Change in Abdominal Obesity Among Older Persons

Nicole Vogelzangs, MSc,1 Stephen B Kritchevsky, PhD,2 Aartjan TF Beekman, MD, PhD,1 Anne B Newman, MD, MPh,3 Suzanne Satterfield, MD, DrPh,4 Eleanor M Simonsick, PhD,5 Kristine Yaffe, MD,6 Tamara B Harris, MD, MS,7 and Brenda WJH Penninx, PhD1, for the Health ABC study

Abstract

Context

Depression has been hypothesized to result in abdominal obesity through the accumulation of visceral fat. No large study has tested this hypothesis longitudinally.

Objective

To examine whether depressive symptoms predict an increase in abdominal obesity in a large population-based sample of well-functioning older persons.

Design

The Health, Aging, and Body Composition Study, an ongoing prospective cohort study, with 5 years of follow-up.

Setting

Community-dwelling older persons residing in the areas surrounding Pittsburgh, Pennsylvania, and Memphis, Tennessee.

Participants

2088 well-functioning white and black persons aged 70–79 years.

Main Outcome Measures

Baseline depression was defined as a Center for Epidemiological Studies Depression (CES-D) score of ≥ 16. At baseline and after 5 years, overall obesity measures included body mass index and percent body fat (measured by dual energy x-ray absorptiometry). Abdominal obesity measures included waist circumference, sagittal diameter, and visceral fat (measured by computed tomography).

Results

After adjustment for sociodemographics, lifestyle, diseases and overall obesity, baseline depression was associated with a 5-year increase in sagittal diameter (β=.054, p=.01) and visceral fat (β=.080, p=.001).

Conclusions

This study shows that depressive symptoms result in an increase in abdominal obesity, independent of overall obesity, suggesting that there may be specific pathophysiological mechanisms which link depression with visceral fat accumulation. These results might also help explain why depression increases risk of diabetes and cardiovascular disease.

INTRODUCTION

Depression is common in later life. Clinically relevant depressive symptoms are present in 10 to 15% of the older population1. According to the World Health Organization, depression is among the leading disorders causing disability and will be the second most important cause of disability worldwide in 20202. Depression has been associated with the onset of diabetes, cardiovascular disease (CVD) and cardiac mortality36. To better prevent occurrence of these major disabling and life-threatening diseases, more insight into underlying mechanisms relating depression to these disorders, is needed.

Neuroendocrine disturbances found in depressed persons include dysregulation of the hypothalamic-pituitary-adrenal (HPA)-axis and hypothalamic-pituitary-gonadal (HPG)-axis, indicated by high levels of cortisol7,8 and low levels of sex steroid hormones9, respectively. In addition, high levels of inflammatory markers have been observed in persons who report clinically relevant depressive symptoms10. Similar abnormalities have been identified in persons with abdominal obesity11,12. Consequently, Björntorp hypothesized that chronic stress and/or depression results in abdominal obesity, through long-term activation of the HPA-axis13. Björntorp argued that elevated cortisol, particularly when combined with low sex steroid hormones, causes fat to accumulate in visceral adipose tissue. This might be due to specific properties of visceral fat, such as a high density of glucocorticoid receptors14. Excess visceral fat, as indicated by abdominal obesity, subsequently has been found to predict diabetes, CVD, and mortality, to a greater degree than overall obesity1518.

Up until now, no large study has longitudinally tested the hypothesis that depressive symptoms lead to an increase in visceral fat. Some cross-sectional studies report an association between abdominal obesity and depression1924 independent of overall obesity. One prospective study found that 29 patients with major depression had a larger increase in visceral fat than 17 non-depressed persons25.

The present study investigates the longitudinal association between depressive symptoms at baseline and 5-year changes in abdominal obesity in a large community sample of older persons. We hypothesize that depressive symptoms at baseline will predict an increase in abdominal obesity over time and that this association is specific to abdominal obesity as compared to overall obesity.

METHODS

Study population

Data are from 3075 well-functioning white and black men and women, aged 70–79 years enrolled in the Health, Aging, and Body Composition (Health ABC) study, an ongoing prospective cohort study. Participants were recruited in 1997 and 1998, drawn from a sample of white and all black Medicare-eligible beneficiaries residing in the areas surrounding Pittsburgh, Pennsylvania, and Memphis, Tennessee. Race was self-identified and black persons were over-sampled to be able to examine race differences. Subjects were eligible if they reported no difficulty with walking for a quarter of a mile, walking up 10 steps, or performing activities of daily living. Subjects were ineligible if they had severe difficulty communicating, had active cancer treatment in the past three years, had plans to move out of the area, or were participating in a randomized trial of a lifestyle intervention. All participants signed an informed written consent, approved by the institutional review boards of the clinical sites. In the present study, persons with missing baseline data on depressive symptoms and/or obesity were excluded (N=26). In addition, persons without obesity data at the 5-year assessment in 2002–2003 were excluded (N=961; 375 persons had died, 13 were lost to follow-up, 63 did not participate that year, and 510 were assessed by phone interview only), leaving 2088 persons for the present analyses. Included persons (N=2088) were younger (73.4 years vs. 74.1 years at baseline; p<.001), more often women (52.7 vs. 48.9; p=.05), white (63.6% vs. 47.2%; p<.001), college educated (46.7% vs. 32.8%; p<.001) and had lower rates of depression at baseline (4.0% vs. 6.2%; p=.007) than excluded persons (N=987).

Depressive symptoms

During the baseline interview, depressive symptoms were measured with the 20-item Center for Epidemiologic Studies Depression (CES-D) scale assessing depressive symptoms in the previous week26. This scale, ranging from 0 to 60, has been widely used in older populations and has been shown to be a valid and reliable instrument among the elderly27. In our study the internal consistency was high: Cronbach’s alpha = 0.81. A score of 16 or higher, the usual cut-off, identified persons with clinically relevant depressive symptoms. Although this definition does not reflect a psychiatric diagnosis of depression, for convenience, in this paper we will refer to this cut-off measure as ‘depression’. In addition, the CES-D 10 item version, which has shown good predictive accuracy when compared with the 20-item CES-D scale28, was administered at follow-up after 2, 3, 4 and 5 years. For sensitivity analyses, depressed persons were subdivided into persons who were only depressed at baseline (single depression) and those who also had at least one follow-up assessment with depression (CES-D ≥ 10) (persistent/recurrent depression).

Obesity

All obesity measures were assessed at the clinic visit at baseline and 5 years later.

Overall obesity

Body weight was measured on a standard balance beam scale to the nearest 0.1 kg. Height was measured barefoot using a wall-mounted stadiometer to the nearest 0.1 cm. BMI was calculated as body weight (kg) divided by the square of height (m2). Total mass (gram) and total fat mass (gram) were determined via a whole body dual energy x-ray absorptiometry (DXA) scan performed using fan beam technology (QDR4500A; Hologic, Waltham, MA, USA). Total fat mass/total mass *100 defined total percent body fat; when total mass was missing, weight (gram) was used instead.

Abdominal obesity

Computed tomography (CT) scanning was performed at the level between the fourth and fifth lumbar vertebrae (L4–L5) to measure visceral fat (cm2), using a Somatom Plus 4 (Siemens, Erlangen, Germany) or a Picker PQ 2000S (Marconi Medical Systems, Cleveland, OH) scanner in Memphis and a 9800 Advantage scanner (General Electric, Milwaukee, WI) in Pittsburgh. The scans were conducted at 120 kVp, 200–250 mA/second, at a slice thickness of 10 mm. Areas were calculated by multiplying the number of pixels of a given tissue type by the pixel area using IDL development software (RSI Systems, Boulder, CO). Visceral fat was manually distinguished from abdominal subcutaneous fat by tracing along the fascial plane defining the internal abdominal wall. Quality of repositioning on CT scans between baseline and the 5-year assessment was rated, incorporating abdominal level and anatomical landmarks. In addition to the continuous measure of 5-year change in visceral fat, a categorical measure was constructed, defining loss, no change, or gain of visceral fat. A cut-off of 30% change in visceral fat was selected, because this approximated 1 SD in the visceral fat change score. Besides the direct CT measure of visceral fat, some anthropometric measures were assessed. Maximum sagittal diameter (cm), the distance between the abdomen and back, was derived from the CT scans. Waist circumference (cm) was measured at the largest abdominal circumference to the nearest 0.1 cm using a flexible plastic tape measure.

Baseline characteristics

Sociodemographic characteristics included age, sex, race (white, black), site (Pittsburgh, Memphis), and education (less than high school, high school, post-secondary). We also assessed lifestyle characteristics known to be related to both abdominal obesity and depression: smoking status (non-, former, or current), current alcohol use (0–1 vs. 2+ drinks/day) and physical activity (sum of weight training, high and medium intensity exercise, aerobic dance, (exercise) walking, and stair climbing (in kcal/week)). Presence of baseline diabetes and CVD (including stroke or transient ischemic attack, myocardial infarction, angina pectoris, percutaneous transluminal coronary angioplasty, or coronary artery bypass grafting) were adjudicated using standardized algorithms considering various sources of information: self-report, medication use, oral glucose tolerance testing, and medical claims data from the former Health Care Financing Administration. Number of other chronic diseases was mainly based on self-report and included congestive heart failure, peripheral arterial disease, cancer, lung disease, osteoarthritis, osteoporosis, gastrointestinal disease, prostate disease, thyroid disease, Parkinson’s disease, and kidney disease. In addition, all medications regularly taken in the past 2 weeks before baseline were recorded and coded according to the Iowa Drug Information System (IDIS)29. From this inventory, the total number of prescription medication taken was calculated. In addition, use of antidepressant medication was ascertained, which included monoamine oxidase inhibitors (281605), tri/tetracyclic antidepressants (281606), selective serotonin reuptake inhibitors (281607), and other antidepressants (281604), regardless of reason. Other psychoactive medication included antipsychotic (281609: phenothiazines, 282610: butyrophenones, 281608: other) and anxiolytic (2824: benzodiazepines, barbiturates, other) medication.

Statistical analyses

Sample characteristics were compared between depressed and non-depressed persons using chi-square statistics for dichotomous and categorical variables and independent t-test for continuous variables. Because some of the obesity measures differ greatly between men and women, sex-adjusted means were presented based on analyses of covariance. Paired-sample t-tests were performed to assess whether 5-year changes in obesity were statistically significant. To evaluate the association between depressive symptoms at baseline (both continuous as well as dichotomous) and 5-year change in abdominal obesity, linear regression analyses were conducted with abdominal obesity change scores as the outcome. For comparison, associations between depressive symptoms and overall obesity were also presented. Covariates were a priori selected and initial analyses were adjusted for the corresponding baseline obesity measure and sociodemographic variables (sex, age, race, site, and education). Next, to assess whether results were independent of baseline overall obesity, abdominal obesity analyses were additionally adjusted for BMI. Finally, because lifestyle, abdominal obesity-related diseases, and general health status might partly explain the association between abdominal obesity and depression, we examined their role by additionally adjusting analyses for smoking, alcohol use, physical activity, prevalent diabetes, prevalent CVD, number of other chronic diseases, and number of prescription medication taken.

Because depression has also been associated with weight loss30,31, it is possible that a u-shaped association exists between depression and change in visceral fat, with depression being associated with both gain and loss of visceral fat. Therefore, it was checked whether baseline depression was also associated with a decrease in visceral fat, distinct from a potential increase in visceral fat. For this purpose, an adjusted multinomial logistic regression analysis was performed using categories of visceral fat change (loss/no change/gain) as outcome. By choosing the no change group as the reference category, this analysis gives 2 OR’s: one assessing the risk of losing visceral fat when depressed at baseline, and one assessing the risk of gaining visceral fat when depressed at baseline. Furthermore, to verify that the association between depression and visceral fat was independent of change in BMI, a linear regression analysis was performed with change in visceral fat as the outcome, adjusted for change in BMI. In addition, it was tested whether an interaction existed with change in BMI, to assess whether the relationship between depression and change in visceral fat was consistent across the whole range from weight loss, weight stability to weight gain.

Because sex differences in the relationships between depression, abdominal obesity, and CVD have been observed3,18 and since fat distribution differs across sex and race, all analyses were repeated including sex- and sex-specific race- by depression interaction terms, to test whether findings were consistent across sex and race. For graphing purposes, adjusted mean 5-year changes in abdominal obesity were calculated using analysis of covariance. Finally, because a significant proportion of persons enrolled at baseline did not have a clinic visit after 5 years leaving the most healthy persons for analyses, missing values at follow-up were multiply imputed. Multiple imputation was established by Multivariate Imputation by Chained Equations32 using R statistical software. Obesity follow-up measures were only imputed if depression and the corresponding obesity measure at baseline were non-missing. Missing follow-up obesity values were 5 times imputed by predictive mean matching using information from all available covariates (sex, age, race, site, education, smoking, alcohol use, physical activity, prevalent diabetes, prevalent CVD, number of other chronic diseases, number of prescription medication taken, antidepressant medication, other psychoactive medication), predictors (CES-D score, yes/no depression, yes/no persistent depression), the corresponding baseline obesity measure, BMI and change in BMI for abdominal obesity measures, and visceral fat and change in visceral fat for overall obesity measures. Fully adjusted (including adjustment for yes/no imputed value) linear regression analyses that associated depression with change in obesity were conducted on each of the 5 newly created dataset and results were pooled.

RESULTS

Sample characteristics

At baseline, the mean age of the participants was 73.4 (SD=2.8) years, 52.7% were women, and 36.4% were black. Depression was present in 4.0% and the mean BMI was 27.3 (SD=4.7). Women had a greater percent body fat than men (40.5% vs. 29.5%), but had less visceral fat (130.7 cm2 vs. 157.4 cm2). Overall 5-year changes in obesity were small, although some increases in obesity were seen in men, while decreases in abdominal obesity were observed in women, especially in visceral fat (−11.4 cm2), consistent with earlier reported findings in this older sample33. Visceral fat correlated more strongly with waist circumference (Pearson’s r = 0.63) and sagittal diameter (Pearson’s r = 0.75), than with BMI (Pearson’s r = 0.54). Table 1 shows the sample characteristics for persons with and without depression. Persons with baseline depression were less educated, had more chronic diseases and were taking more prescription medication. Depressed persons had slightly higher sex-adjusted percent body fat at baseline (35.2% vs. 36.6%, p=.02) and showed a (larger) sex-adjusted 5-year increase in sagittal diameter (0.2 cm vs. 0.9 cm, p=.007) and visceral fat (−7.1 cm2 vs. 9.0 cm2, p=.001) than non-depressed persons.

Table 1
Sample characteristics

Baseline depressive symptoms and 5-year change in abdominal obesity

Table 2 describes the results of adjusted linear regression analyses assessing the association between baseline CES-D score (continuous) and depression (CES-D ≥ 16) with 5-year changes in obesity measures. No significant associations were found for the continuous CES-D score or the depression variable with 5-year changes in overall obesity (BMI or percent body fat). In contrast, after full adjustment for covariates, baseline depression was associated with increases in sagittal diameter (β=.054, p=.01), and visceral fat (β=.080, p=.001), with a trend for an increase in waist circumference (β=.031, p=.08). For the continuous CES-D score these associations were still consistent but somewhat attenuated (waist circumference: β=.026, p=.15; sagittal diameter: β=.037, p=.10; visceral fat: β=.042, p=.07).

Table 2
Baseline depressive symptoms and 5-year change in obesity

Role of weight change

To check whether depressive symptoms were not also associated with a loss in abdominal obesity, an adjusted multinomial logistic regression analysis was performed using visceral fat change categories (≥ 30% loss/no change/≥ 30% gain) as the outcome. Persons with baseline depression had an odds of 0.43 (95%CI=0.18–1.04, p=.06; i.e. a decreased risk) to lose visceral fat and an odds of 2.06 (95%CI=1.04–4.05, p=.04; i.e. an increased risk) to gain visceral fat compared to having no change in visceral fat, indicating a linear association between baseline depression and change in visceral fat. To verify that the association between depression and visceral fat was independent of change in BMI, the association between depression and visceral fat, as reported in Table 2, was additionally adjusted for change in BMI. The relationship between depression and change in visceral fat remained statistically significant (β=.050, p=.009). Furthermore, no interaction between depression and change in BMI in the association with visceral fat was found (p=.95).

Sex and race differences

To examine whether associations between depression and abdominal obesity were consistent across sex and race, sex by depression and sex-specific race by depression interaction terms were included in the fully adjusted models assessing the association between depression and change in abdominal obesity as described in Table 2. A significant sex (p=.03) by depression interaction was found for change in visceral fat only. No race interactions were found among men (all p>.20), but in women trends for race by depression interactions in predicting 5-year change in abdominal obesity were found for waist circumference (p=.06), sagittal diameter (p=.09), and visceral fat (p=.08). Because race interactions were found in women only, subsequent analyses were stratified by sex and race. Depression rates across sex by race groups were as follows: white men (N=683): 3.5%, white women (N=645): 4.3%, black men (N=304): 3.3%, and black women (N=456): 4.8%. Stratification showed that the association between depression and 5-year change in visceral fat was generally consistent across sex and race with the exception of black women: white men: β=.154, p<.001; white women: β=.078, p=.05; black men: β=.121, p=.06; black women: β=−.029, p=.54. To graph these findings for all abdominal obesity measures, adjusted mean 5-year changes in abdominal obesity were calculated for persons with and without baseline depression using analysis of covariance stratified by sex and race (Figure 1). The figure shows that baseline depression was associated with an increase in abdominal obesity, while persons without depression showed a much smaller increase or even a decrease in abdominal obesity over 5 years. This finding was consistent across all abdominal obesity measures and across sex and race, with the exception of black women.

Figure 1
Adjusted mean 5-year changes in abdominal obesity according to baseline depression across sex and race groups: waist circumference (A), sagittal diameter (B), and visceral fat (C); adjusted for corresponding baseline abdominal obesity measure, age, site, ...

Additional analyses

To assess the robustness of our findings a set of sensitivity analyses was conducted. First, the association between depression and change in abdominal obesity was assessed in persons with a single depression at baseline (N=17) and in those with persistent/recurrent depression (N=67). These analyses showed rather consistent associations for both depression groups (waist circumference: β=.016, p=.36 and β=.027, p=.13, sagittal diameter: β=.028, p=.21 and β=.047, p=.03, visceral fat: β=.070, p=.002 and β=.055, p=.02, respectively). Further, to assure that associations between depression and increases in abdominal fat were not due to antidepressant use, analyses such as described in Table 2 were additionally adjusted for antidepressant use which did not change the results in any meaningful way. Similar results were also found when adjusting for other psychoactive medication. Also, when persons with a low quality of repositioning on the CT scans (N=84) were excluded from the analyses, associations with increases in visceral fat were comparable. Finally, to include all persons with baseline obesity data and to check the potential effect of selective drop-out, analyses were conducted after multiple imputation for missing values. When repeating the fully adjusted analyses described in Table 2, associations between depression and change in abdominal obesity largely remained (waist circumference: N=3038, β=.021, p=.27; sagittal diameter: N=2998, β=.041, p=.03; visceral fat: N=2931, β=.073, p<.001).

DISCUSSION

This study examined whether depressive symptoms could predict an increase in abdominal obesity over time in a large community-based sample of older persons. As hypothesized, depressed persons showed a significantly greater increase in abdominal obesity over 5 years, especially in visceral fat, than non-depressed persons. Such an association was not found for an increase in overall obesity and also appeared to be independent of changes in overall obesity, suggesting that depressive symptoms are rather specifically associated with fat gain in the visceral region.

To our knowledge, this is the first study to examine the association between depressive symptoms and increases in abdominal obesity over time in a large cohort. Our results are consistent with a study by Weber-Hamann et al.25, which showed a larger accumulation of visceral fat mass over time in 29 depressed patients compared to 17 controls. Most studies so far have assessed the association between abdominal obesity and depression cross-sectionally, using either anthropometric measures alone, or CT measures in relatively small study samples1924. Most of these studies showed a positive relationship between depression and abdominal obesity, although one large epidemiological study could not demonstrate an association between waist circumference and depression34. In our study, associations with waist circumference were also weaker than those with visceral fat, possibly due to the fact that waist circumference is only an indirect measure of visceral fat and is determined by both abdominal subcutaneous and visceral fat mass. Also, measuring waist circumference might be less precise than CT scanning. Stronger associations were found for sagittal diameter, which is considered a better indicator of visceral fat than waist circumference in older persons35. Our results indeed show a higher correlation of sagittal diameter (r=0.75) than waist circumference (r=0.63) with visceral fat. Most pronounced, however, were the associations with visceral fat, which is in line with our hypothesis that depressive symptoms contribute to an accumulation of visceral fat specifically.

Although depression has been associated with weight loss30,31, our results show an increase in visceral fat in persons with depressive symptoms, even in this aging population where decreases in fat mass are common36. We found no evidence that depression would result in a loss of visceral fat. Even more, we found that depression was in fact negatively associated with a loss of visceral fat, indicating that depression is linearly linked with the accumulation of visceral fat and no u-shaped association exists. Furthermore, the results of this study show that depression appears to be specifically associated with abdominal obesity stronger than and independent of overall obesity. Associations between depressive symptoms and overall obesity were not found and adjusting abdominal obesity analyses for baseline BMI did not influence findings. Furthermore, we additionally adjusted for change in BMI which was partly an over-adjustment, because changes in BMI do also reflect changes in visceral fat. However, despite this relatively strict adjustment, the relationship between depression and change in visceral fat remained. Moreover, our results showed that across the whole range of weight change an association existed between depression and visceral fat suggesting that even in persons who lost weight, visceral fat was preferentially retained in those with depression. The finding that associations were specific for abdominal obesity, is in line with other studies showing that abdominal obesity, more than overall obesity, is associated with poor health outcomes, such as diabetes, CVD, and mortality1518. Because both depression and diabetes/CVD appear to be specifically associated with excess visceral fat, this could help explain the frequently found increased risk of diabetes and CVD among depressed persons.

Our results indicate that depression predicts increases in abdominal obesity in all but black women. Reasons for this exception are not entirely clear. One explanation may be that the black women in this older sample experienced a relatively large decrease in visceral fat, which might have obscured the association between depressive symptoms and the accumulation of visceral fat. Alternatively, this could have been a chance finding due to small sample sizes after stratification by sex and race. However, expected associations were found for the other 3 sex by race groups. Future research should explore sex and race differences further in younger samples.

What are the mechanisms by which depression may promote visceral fat accumulation? As suggested by Björntorp, stress activates the HPA-axis, which leads to an accumulation of visceral fat13. Different studies show that chronic stress and depression are, at least in a subset of patients, associated with a dysregulation of the HPA-axis and elevated concentrations of cortisol7,8. Visceral fat is highly sensitive to cortisol, due to a high density of glucocorticoid receptors14. Cortisol promotes the accumulation of visceral fat by activating lipoprotein lipase and inhibiting lipid mobilization13. Indeed, it has been shown that hypercortisolemic depression is associated with abdominal obesity20,37. Moreover, these effects might be most pronounced when levels of sex steroid hormones, which have been found to reduce visceral fat mass and have a lipid-mobilizing effect13,38, are low, as has been observed in late-life depression9. Further, depression has been linked with high levels of inflammatory markers10, which can activate the HPA-axis39 and therefore subsequently result in visceral obesity. Moreover, as described by Gold and Chrousos40, even in persons with non-hypercortisolemic atypical depression, due to overeating, a cycling of weight gain and loss occurring throughout recurrent episodes of depression could preferentially distribute weight to visceral fat areas. An alternative explanation for why depression may lead to abdominal obesity is that depressed persons have an unhealthier lifestyle. Although we adjusted our analyses for some lifestyle behaviors (smoking, alcohol use, and physical activity), it is possible that depressed persons have a poorer dietary pattern. However, a poor diet in itself would likely lead to an increase in both overall and abdominal obesity41. In combination with a hyperactive HPA-axis, however, it is possible that excess caloric intake is preponderantly stored into visceral fat depots42. In addition, somatic comorbidities of depressed persons could have led to the increase in visceral fat, although our results were little affected by adjustment for diabetes, CVD, and general health status. Furthermore, weight gain in depressed persons has been associated with the use of antidepressants43. However, in our study antidepressant use was not associated with increases in (abdominal) obesity, and therefore our findings can not be the result of antidepressant use.

Our results show that the link between depressive symptoms and increased abdominal obesity was stronger for the dichotomous indicator of depression than for the continuous CES-D score, suggesting that a certain amount of distress is needed before visceral fat starts to accumulate. On the other hand, we did not find evidence that the association between depression and an increase in abdominal obesity was specific for persons with persistent/recurrent depression compared to person with a single depression episode at baseline. However, most persons depressed at baseline did have an additional episode of depression during follow-up and it is very well possible that persons only depressed at baseline did experience additional depressive episodes in-between annual assessments.

Our study has some limitations. We did not have well-accepted criterion-based psychiatric diagnoses of depression. However, the CES-D is a commonly used scale to measure clinically relevant depressive symptoms. Our results might have been even stronger for persons with a diagnosis of major depressive disorder. Further, our sample showed low levels of depressive symptomatology at baseline and this aging population exhibited little change or even decrease in obesity, making it more difficult to detect associations with changes in obesity. Possibly, associations may be even stronger in a middle-aged population were visceral fat tends to increase over time. In addition, after 5 years of follow-up, there was drop-out due to mortality and non-response likely resulting in a relatively healthy sample, which could have led to an underestimation of the association between depression and change in abdominal obesity. On the other hand, studying the most healthy had the advantage that associations found were less likely confounded by somatic comorbidities. When missing values of persons without 5-year follow-up data were imputed, thereby including the less healthy, associations between depression and increase in abdominal obesity largely remained. Our study also has some important strengths, including use of a large community-based cohort followed for several years with repeated DXA and CT scans, which provide more direct assessments of total and visceral fat stores, as well as the more commonly used anthropometric measures.

In conclusion, our longitudinal results suggest that clinically relevant depressive symptoms give rise to an increase in abdominal obesity, in particular visceral fat, which seems to be stronger than and independent of overall obesity. Because of this specific accumulation of visceral fat, these results clearly suggest that there may be certain underlying pathophysiological mechanisms, plausibly involving the HPA-axis, which link depression with visceral fat. This could also help explain why depression is often followed by diabetes or CVD. Future research should further disentangle these mechanisms, since this will yield important information for prevention or treatment of depression-related health consequences.

Acknowledgments

Funding/Support: We thank David Vergouw for his help with the multiple imputation analyses. This work was supported by National Institute on Aging (NIA) contract numbers N01-AG-6-2101, N01-AG-6-2103, and N01-AG-6-2106 and in part by the Intramural Research Program of the National Institutes of Health, NIA. Data analyses were supported by grant R01-HL72972-01 from the National Heart, Lung, and Blood Institute (NHLBI). The work of NV was supported by a travel grant from the Young Academy of the Royal Netherlands Academy of Arts and Science.

Role of the Sponsor: The National Institute on Aging scientists had substantial involvement in the study design, data collection, analysis, interpretation, and manuscript preparation.

Footnotes

Financial disclosures: None reported.

Author contributions: Drs. Vogelzangs and Penninx had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Vogelzangs, Kritchevsky, Penninx.

Acquisition of data: Kritchevsky, Newman, Satterfield, Simonsick, Yaffe, Harris.

Analysis and interpretation of data: Vogelzangs, Beekman, Penninx.

Drafting of the manuscript: Vogelzangs, Penninx.

Critical revision of the manuscript for important intellectual content: Vogelzangs, Kritchevsky, Beekman, Newman, Satterfield, Simonsick, Yaffe, Harris, Penninx.

Statistical analysis: Vogelzangs, Beekman, Penninx.

Obtained funding: Kritchevsky, Newman, Harris, Penninx.

Administrative, technical, or material support: Newman, Satterfield, Simonsick, Yaffe, Harris.

Study supervision: Penninx.

References

1. Beekman AT, Copeland JR, Prince MJ. Review of community prevalence of depression in later life. Br J Psychiatry. 1999;174:307–311. [PubMed]
2. Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990–2020: Global Burden of Disease Study. Lancet. 1997;349(9064):1498–1504. [PubMed]
3. Penninx BW, Guralnik JM, Mendes de Leon CF, et al. Cardiovascular events and mortality in newly and chronically depressed persons > 70 years of age. Am J Cardiol. 1998;81(8):988–994. [PubMed]
4. Penninx BW, Beekman AT, Honig A, et al. Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry. 2001;58(3):221–227. [PubMed]
5. Knol MJ, Twisk JW, Beekman AT, Heine RJ, Snoek FJ, Pouwer F. Depression as a risk factor for the onset of type 2 diabetes mellitus. A meta-analysis. Diabetologia. 2006;49(5):837–845. [PubMed]
6. Whooley MA. Depression and cardiovascular disease: healing the broken-hearted. JAMA. 2006;295(24):2874–2881. [PMC free article] [PubMed]
7. Deuschle M, Weber B, Colla M, Depner M, Heuser I. Effects of major depression, aging and gender upon calculated diurnal free plasma cortisol concentrations: a re-evaluation study. Stress. 1998;2(4):281–287. [PubMed]
8. Chrousos GP, Gold PW. The concepts of stress and stress system disorders. Overview of physical and behavioral homeostasis. JAMA. 1992;267(9):1244–1252. [PubMed]
9. Morsink LF, Vogelzangs N, Nicklas BJ, et al. Associations between sex steroid hormone levels and depressive symptoms in elderly men and women: Results from the Health ABC study. Psychoneuroendocrinology. 2007;32(8):874–883. [PubMed]
10. Penninx BW, Kritchevsky SB, Yaffe K, et al. Inflammatory markers and depressed mood in older persons: results from the Health, Aging and Body Composition study. Biol Psychiatry. 2003;54(5):566–572. [PubMed]
11. Visser M, Bouter LM, McQuillan GM, Wener MH, Harris TB. Elevated C-reactive protein levels in overweight and obese adults. JAMA. 1999;282(22):2131–2135. [PubMed]
12. Bjorntorp P, Rosmond R. Neuroendocrine abnormalities in visceral obesity. Int J Obes Relat Metab Disord. 2000;24 (Suppl 2):S80–S85. [PubMed]
13. Bjorntorp P. Do stress reactions cause abdominal obesity and comorbidities? Obes Rev. 2001;2(2):73–86. [PubMed]
14. Bronnegard M, Arner P, Hellstrom L, Akner G, Gustafsson JA. Glucocorticoid receptor messenger ribonucleic acid in different regions of human adipose tissue. Endocrinology. 1990;127(4):1689–1696. [PubMed]
15. Ohlson LO, Larsson B, Svardsudd K, et al. The influence of body fat distribution on the incidence of diabetes mellitus. 13.5 years of follow-up of the participants in the study of men born in 1913. Diabetes. 1985;34(10):1055–1058. [PubMed]
16. Folsom AR, Kaye SA, Sellers TA, et al. Body fat distribution and 5-year risk of death in older women. JAMA. 1993;269(4):483–487. [PubMed]
17. Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. JAMA. 1998;280(21):1843–1848. [PubMed]
18. Nicklas BJ, Penninx BWJH, Cesari M, et al. Association of visceral adipose tissue with incident myocardial infarction in older men and women: the Health, Aging and Body Composition Study. Am J Epidemiol. 2004;160(8):741–749. [PubMed]
19. Thakore JH, Richards PJ, Reznek RH, Martin A, Dinan TG. Increased intra-abdominal fat deposition in patients with major depressive illness as measured by computed tomography. Biol Psychiatry. 1997;41(11):1140–1142. [PubMed]
20. Weber-Hamann B, Hentschel F, Kniest A, et al. Hypercortisolemic depression is associated with increased intra-abdominal fat. Psychosom Med. 2002;64(2):274–277. [PubMed]
21. Ahlberg AC, Ljung T, Rosmond R, et al. Depression and anxiety symptoms in relation to anthropometry and metabolism in men. Psychiatry Res. 2002;112(2):101–110. [PubMed]
22. Lee ES, Kim YH, Beck SH, Lee S, Oh SW. Depressive mood and abdominal fat distribution in overweight premenopausal women. Obes Res. 2005;13(2):320–325. [PubMed]
23. Kahl KG, Bester M, Greggersen W, et al. Visceral fat deposition and insulin sensitivity in depressed women with and without comorbid borderline personality disorder. Psychosom Med. 2005;67(3):407–412. [PubMed]
24. Eskandari F, Mistry S, Martinez PE, et al. Younger, premenopausal women with major depressive disorder have more abdominal fat and increased serum levels of prothrombotic factors: implications for greater cardiovascular risk. Metabolism. 2005;54(7):918–924. [PubMed]
25. Weber-Hamann B, Werner M, Hentschel F, et al. Metabolic changes in elderly patients with major depression: evidence for increased accumulation of visceral fat at follow-up. Psychoneuroendocrinology. 2006;31(3):347–354. [PubMed]
26. Radloff LS. The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement. 1977;1(3):385–401.
27. Beekman AT, Deeg DJ, van Limbeek J, Braam AW, De Vries MZ, van Tilburg W. Criterion validity of the Center for Epidemiologic Studies Depression scale (CES-D): results from a community-based sample of older subjects in The Netherlands. Psychol Med. 1997;27(1):231–235. [PubMed]
28. Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale) Am J Prev Med. 1994;10(2):77–84. [PubMed]
29. Pahor M, Chrischilles EA, Guralnik JM, Brown SL, Wallace RB, Carbonin P. Drug data coding and analysis in epidemiologic studies. Eur J Epidemiol. 1994;10(4):405–411. [PubMed]
30. Haukkala A, Uutela A, Salomaa V. Depressive symptoms, clinical hostility, and weight change: A 3-year follow-up among middle-aged men and women. Int J Behav Med. 2001;8(2):116–133.
31. Forman-Hoffman VL, Yankey JW, Hillis SL, Wallace RB, Wolinsky FD. Weight and depressive symptoms in older adults: direction of influence? J Gerontol B Psychol Sci Soc Sci. 2007;62(1):S43–S51. [PubMed]
32. Van Buuren S, Oudshoorn CGM. mice: Multivariate Imputation by Chained Equations. [Accessed 2008 April 1];R package version 1.16. 2007 http://web.inter.nl.net/users/S.van.Buuren/mi/hmtl/mice.htm.
33. Visser M, Pahor M, Tylavsky F, et al. One- and two-year change in body composition as measured by DXA in a population-based cohort of older men and women. J Appl Physiol. 2003;94(6):2368–2374. [PubMed]
34. Hach I, Ruhl UE, Klotsche J, Klose M, Jacobi F. Associations between waist circumference and depressive disorders. J Affect Disord. 2006;92(2–3):305–308. [PubMed]
35. Harris TB, Visser M, Everhart J, et al. Waist circumference and sagittal diameter reflect total body fat better than visceral fat in older men and women. The Health, Aging and Body Composition Study. Ann N Y Acad Sci. 2000;904:462–473. [PubMed]
36. Newman AB, Lee JS, Visser M, et al. Weight change and the conservation of lean mass in old age: the Health, Aging and Body Composition Study. Am J Clin Nutr. 2005;82(4):872–878. [PubMed]
37. Vogelzangs N, Suthers K, Ferrucci L, et al. Hypercortisolemic depression is associated with the metabolic syndrome in late-life. Psychoneuroendocrinology. 2007;32(2):151–159. [PMC free article] [PubMed]
38. Villareal DT, Holloszy JO. Effect of DHEA on abdominal fat and insulin action in elderly women and men: a randomized controlled trial. JAMA. 2004;292(18):2243–2248. [PubMed]
39. Kyrou I, Chrousos GP, Tsigos C. Stress, visceral obesity, and metabolic complications. Ann N Y Acad Sci. 2006;1083:77–110. [PubMed]
40. Gold PW, Chrousos GP. Organization of the stress system and its dysregulation in melancholic and atypical depression: high vs low CRH/NE states. Mol Psychiatry. 2002;7(3):254–275. [PubMed]
41. Newby PK, Muller D, Hallfrisch J, Qiao N, Andres R, Tucker KL. Dietary patterns and changes in body mass index and waist circumference in adults. Am J Clin Nutr. 2003;77(6):1417–1425. [PubMed]
42. Dallman MF, la Fleur SE, Pecoraro NC, Gomez F, Houshyar H, Akana SF. Minireview: glucocorticoids--food intake, abdominal obesity, and wealthy nations in 2004. Endocrinology. 2004;145(6):2633–2638. [PubMed]
43. Zimmermann U, Kraus T, Himmerich H, Schuld A, Pollmacher T. Epidemiology, implications and mechanisms underlying drug-induced weight gain in psychiatric patients. J Psychiatr Res. 2003;37(3):193–220. [PubMed]