Obesity and major depressive disorder (MDD)/anxiety disorders often co-occur and aggravate each other resulting in adverse health-related outcomes. As little is known about the potential effects of interaction between obesity and MDD and/or anxiety disorders on health-related quality of life (HR-QoL), this study was aimed at examining these combined effects.
We collected data among N = 89,332 participants from the LifeLines cohort study. We categorized body weight using body mass index (kg/m2) as normal weight (18.5–24.99), overweight (25–29.9), mild obesity (30–34.9) and moderate/severe obesity (≥ 35); we measured abdominal obesity using a waist circumference of ≥102 and ≥ 88 cm for males and females, respectively. MDD and anxiety disorders were diagnosed with the Mini-International Neuropsychiatric Interview. HR-QoL was assessed using the RAND-36 questionnaire to compute physical and mental quality of life scores. We used binary logistic and linear regression analyses.
The combined effect of obesity and MDD and/or anxiety disorders on physical QoL was larger than the sum of their separate effects; regression coefficients, B (95%-confidence interval, 95%-CI) were: - 1.32 (-1.75; -0.90). However, the combined effect of obesity and major depression alone on mental QoL was less than the additive effect. With increasing body weight participants report poorer physical QoL; when they also have MDD and/or anxiety disorders participants report even poorer physical QoL. In persons without MDD and/or anxiety disorders, obesity was associated with a better mental QoL.
Citation: Nigatu YT, Reijneveld SA, de Jonge P, van Rossum E, Bültmann U (2016) The Combined Effects of Obesity, Abdominal Obesity and Major Depression/Anxiety on Health-Related Quality of Life: the LifeLines Cohort Study. PLoS ONE 11(2): e0148871. doi:10.1371/journal.pone.0148871
Editor: Andreas Stengel, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, GERMANY
Received: April 24, 2015; Accepted: January 24, 2016; Published: February 11, 2016
Copyright: © 2016 Nigatu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data catalogue of LifeLines is publicly accessible on (http://www.lifelines.net/). The LifeLines system allows access for reproducibility of the study results.
Funding: The authors have no support or funding to report.
Competing interests: The authors have declared that no competing interests exist.
Obesity, major depressive disorder (MDD) and anxiety disorders are major public health problems, posing enormous challenges for the decades to come [1,2]. Obesity and MDD and/or anxiety disorders are associated with long-term disability, morbidity and mortality, and enormous economic costs [3–5]. Since the 1980s the prevalence of obesity has tripled in many countries of the World Health Organization (WHO) European Region, and continues to rise at an alarming rate. The rate of MDD and/or anxiety disorders has also increased in the past decade. For instance, in the UK, the incidence of depressive symptoms rose threefold from the baseline of 5.11/1000 person years in 1996 to 15.5/1000 person years in 2006 [4,6]. MDD is even expected to be one of the top leading causes of disability-adjusted life years in 2030 . Obesity and MDD and/or anxiety have become the most serious health risks today, and are associated with major chronic diseases such as cardiovascular diseases, type 2 diabetes, orthopedic problems and certain kinds of cancer [8,9].
Co-occurrence of chronic physical conditions with MDD and/or anxiety disorders may have even worse consequences, including a poorer health-related quality of life (HR-QoL) . HR-QoL has gained increasing interest as an outcome measure in clinical practice and public health settings . Alley et al showed that obesity is associated with poor QoL, especially due to its earlier age of onset and long-term exposure . MDD and/or anxiety disorders are also associated with significant reductions in HR-QoL . During a depressive episode, a patient’s level of HR-QoL is the same as that of as a patient with a severe stroke .
Several studies have reported that obesity and MDD and/or anxiety disorders often co-occur and are bidirectionally inter-related [14–16]. However, obesity and MDD and/or anxiety disorders have more often been considered separate conditions without taking into account their potential interaction on HR-QoL. For example, the effect of general and abdominal obesity on HR-QoL may further increase in persons with MDD and/or anxiety disorders compared to those without such disorders. Regarding this, the general obesity reflects excess total body fat whereas abdominal obesity in particular reflects excess visceral fat which has been suggested to be in particular deleterious . However, for both obesity and abdominal obesity little is known about the potential effects of their interaction with MDD and/or anxiety disorders on HR-QoL. The main reasons to examine their interaction or combined effect on HR-QoL are: 1) obesity and MDD are bidirectionally related and overlapping risk factors for major chronic diseases [14–16,18]; 2) patients with obesity and MDD share pleiotropic genes (12–20%) and have many common features that make them valuable to examine as a distinct population of interest [14–16,19,20]; and 3) both obesity and MDD and/or anxiety disorders lead to an enormous individual and global burden of disease and disability [1,2]. Therefore, obesity and MDD and/or anxiety disorders may interact thereby augmenting one another’s effect on HR-QoL, and substantially reducing the HR-QoL in people with both exposures.
The interaction between obesity and MDD and/or anxiety disorders on HR-QoL can best be measured by statistical interaction on the additive scale as opposed to conventional interaction . On the one hand, knowledge on interaction effects on the additive scale could provide empirical evidence for public health interventions in vulnerable groups; on the other hand, knowledge on interactions on the multiplicative scale is more relevant in disease etiology . The present study focuses essentially on interaction on the additive scale (i.e. comparing the sum of separate effects of obesity and MDD and/or anxiety versus the combined effect). It is very important to be aware of a slight arbitrariness of interaction on the additive scale from the conventional interaction in terms of defining, detecting and interpreting the interaction effect, particularly for continuous outcomes. In conventional interaction, for instance, it is assumed in advance that obesity modifies the effect of MDD and/or anxiety on poor HR-QoL (i.e. unidirectional). In contrast, the interaction on the additive scale concept considers the potential bidirectional interaction effect of obesity and MDD and/or anxiety on poor HR-QoL, because obesity and MDD and/or anxiety do not precede each other. For instance, if the combined effect of obesity and MDD and/or anxiety disorders surpasses the sum of their separate effects, then intervening on obesity might also reduce the effect of MDD and/or anxiety disorders on poor HR-QoL and vice versa.
Therefore, the aim of this study was to examine the combined effect of obesity and MDD and/or anxiety disorders on HR-QoL and to determine whether the effect of obesity on HR-QoL further increases in persons with and without MDD and/or anxiety disorders. Interaction on the additive scale was used as a measure to test the hypothesis that the combined effect of obesity and MDD and/or anxiety disorders on HR-QoL was larger than the sum of the separate effects.
Material and Methods
Study design and population
Data were collected in the ongoing LifeLines Cohort Study, a multi-disciplinary prospective population-based cohort study examining in a unique three-generation design the health and health-related behaviors of 167,729 persons living in the north of The Netherlands. The study employs a broad range of investigative procedures to assess the biomedical, socio-demographic, behavioral, physical and psychological factors which contribute to the health and disease of the general population, with a special focus on multi-morbidity and complex genetics. The design of the LifeLines cohort study has been described elsewhere . For the study, we included N = 89,332 persons, who were enrolled between November 2006 and June 2013. Inclusion criteria for the present study were: age 18 years and older, psychiatric diagnosis, anthropometric measurements, and complete data on HR-QoL.
The LifeLines study protocol was approved by the Ethical Review Board of the University Medical Center Groningen. After receiving full verbal and written information about the study, all participants gave written informed consent. The study was conducted in accordance with the Declaration of Helsinki.
General and abdominal obesity.
General obesity was assessed using the body mass index (BMI). The BMI was calculated from measured body weight (kg) and height (m). Participants were classified into four BMI classes according to the standard international classification of the World Health Organization (WHO): normal weight (BMI: 18.5–24.99 kg/m2), overweight (BMI 25.0–29.99 kg/m2), mild obesity (BMI 30.0–34.99 kg/m2) and moderate/severe obesity (BMI ≥ 35.0 kg/m2). Abdominal obesity was defined using objectively measured waist circumference (WC) of ≥102 cm and ≥88 cm for males and females, respectively . We included abdominal obesity because BMI has been criticized for its inadequate reflection of body composition and we wanted to make our analyses robust. Anthropometric measurements were conducted by nurses during a visit at the LifeLines test location.
Major depressive disorders (MDD) and anxiety disorders.
MDD and anxiety disorders (generalized anxiety disorder (GAD), social phobia, panic and agoraphobia) were assessed by using the Mini-International Neuropsychiatric Interview (MINI) . The MINI is a short structured diagnostic interview. It is compatible with international diagnostic criteria, including the International Classification of Diseases (ICD-10) and the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) . The MINI was designed to meet the need for a short (15 minutes) but accurate structured psychiatric interview for epidemiological studies. The MINI has an excellent inter-rater reliability (Kappa, k > 90), and high retest reliability (k = 0.87 for MDD, k = 0.78 for anxiety disorders) . The MINI interview was conducted by trained interviewers.
Health-related quality of Life (HR-QoL).
HR-QoL was assessed by the RAND-36 questionnaire. The RAND-36 is a generic and widely used measure of HR-QoL, designed for use in clinical practice and research, health policy evaluations, and general population surveys . It has been adapted for use in various countries, including the Netherlands [26,27]. The questionnaire covers eight dimensions: Physical Functioning, Role Limitations due to Physical Functioning (Role-Physical), Bodily Pain, General Health, Vitality, Social Functioning, Role Limitations due to Emotional Functioning (Role-Emotional), and Mental Health. Two summary scores of QoL can be calculated: the physical component summary (PCS) and the mental component summary (MCS) scores, reflecting physical and mental QoL, respectively. These summary scores provide information on the patient’s physical and mental QoL in just two values, thereby reducing the number of statistical analyses needed and offering easier interpretation of the data . The PCS- and MCS-scores have good discriminant validity for identifying differences between clinically meaningful groups . The eight domains and two summary scores range from 0 to 100, with higher scores indicating better HR-QoL. PCS- and MCS-scores were computed by using recommended scoring algorithms, and standardized by linear z-score transformation to have a mean of 50 and standard deviations of 10 in the US general population.
Covariates concerned sociodemographic characteristics (age, sex and educational status), lifestyle factors (smoking, alcohol consumption and physical exercise) and common chronic conditions (cardiovascular diseases, hypertension, diabetes, rheumatoid arthritis and cancer). Age was measured in years. Educational level was categorized into low (primary and lower secondary education), middle (higher secondary education) and high education (tertiary or higher education). Physical exercise was defined as the frequency per week in which the respondent typically engaged in moderate physical activities (e.g. walking, bicycling, gardening and household work) for at least half an hour, it was then categorized into high (twice or more per week), medium (once per week) and low (do not exercise/ hardly per week). Smoking status was dichotomized into current smokers and non-smokers. Alcohol intake was assessed based on intake frequency and the average number of units consumed on a drinking day. The number of alcoholic drinks per week was determined by multiplying the number of drinking days per week by the average number of units consumed on a drinking day. The number of alcoholic drinks/week was then divided by 7 to obtain the average number of alcoholic drinks per day. High alcohol consumption was defined as drinking more than an average of 2 drinks of alcohol per day . Common chronic illnesses were assessed by taking the current and/or past history of chronic physical conditions (i.e. cardiovascular diseases, hypertension, diabetes, rheumatoid arthritis and cancer) [26,32].
First, we described participants’ sociodemographics, lifestyle factors, psychopathology and chronic conditions as frequencies, means and standard deviations, using the four BMI categories and abdominal obesity status. The associations of BMI categories and abdominal obesity with MDD and/or anxiety disorders were assessed using binary logistic regression.
Second, we assessed the average deviation in HR-QoL scores for overweight, obese (mild to moderate or severe) persons compared to normal weight persons by MDD and/or anxiety disorders status using one-way analysis of variance (ANOVA). Third, we examined the combined effect of obesity and MDD and/or anxiety disorders on physical and mental QoL. We assessed the presence of interactions by testing the significance of the increment in squared multiple correlation (ΔR2) by including the product terms (overweight/obesity x MDD and/or anxiety disorders) in the model adjusted for obesity and MDD and/or anxiety disorders, and also by testing whether the coefficient for the product terms differs from 0 . The regression coefficient of the product term (β) reflects interaction as departure from additivity and is the absolute value difference between the combined effect and the separate effects of obesity and MDD and/or anxiety disorders on physical and mental QoL . The combined effect of obesity and MDD and/or anxiety disorders on physical or mental QoL as measured on a continuous scale is given by the sum of the separate effects of obesity, MDD and/or anxiety disorders and the product term. A synergistic effect of obesity and MD/anxiety on physical and mental QoL is reflected as B < 0, while B > 0 represents a negative interaction (antagonistic) of obesity and MDD and/or anxiety disorders on physical and mental QoL:B = 0 represents no interaction effect of obesity and MDD and/or anxiety disorders on physical and mental QoL.
Fourth, using linear regression models, we examined the association of BMI categories with physical and mental QoL in persons with and without MDD and/or anxiety disorders. In these analyses, we tested four different models of general and abdominal obesity to adjust for other variables potentially affecting the associations of obesity and/or MDD and/or anxiety disorders with physical and mental QoL. Model 1 tested the crude association of overweight and obesity categories with physical and mental QoL compared to normal weight category, and stratified by MDD and/or anxiety disorders status. Model 2 adjusted additionally for socio-demographic factors (i.e. age, sex and education). In Model 3, lifestyle factors (i.e. physical exercise, smoking and alcohol) were added, and Model 4 contained all variables from Model 3 plus major chronic conditions (i.e. cardiovascular diseases, hypertension, diabetes, rheumatoid arthritis and cancer).
All analyses were performed using SPSS statistical software (SPSS version 22.0), a two-sided p<0.05 was considered statistically significant.
Table 1 shows the characteristics of participants (N = 89,332) by BMI categories and abdominal obesity status. The prevalences of overweight, mild obesity, moderate/severe obesity and abdominal obesity were 40%, 12%, 4% and 36%, respectively, and of MDD and/or anxiety disorders was 11%. In addition, mild, moderate/severe and abdominal obesity were associated with MDD and/or anxiety disorders (odds ratio, OR (95% confidence interval, CI): = 1.20 (1.12; 1.28), 1.81 (1.65; 1.99) and 1.40 (1.34; 1.46)), respectively. Overweight was not associated with MDD/anxiety disorders OR = 0.96 (0.91; 1.01).
In Table 2 we present the average deviation in HR-QoL domains in participants with obesity and MDD and/or anxiety disorders compared with normal weight counterparts. On all physical health measures and health perceptions overweight and obese persons had a significantly poorer HR-QoL than normal weight persons (Table 2). However, overweight and normal weight participants showed no difference in psychosocial aspects of HR-QoL (social functioning and emotional role) (p<0.01).
The combined effect of obesity and MDD and/or anxiety disorders on HR-QoL
Table 3 shows the interaction of obesity and major depression/anxiety with physical and mental quality of life, which is the main finding of this study. We found that the combined effect of obesity and MDD and anxiety on physical QoL was (B = -1.32, 95%CI: -1.75; -0.90 and B = -1.27, 95%CI: -1.73; -0.81, respectively (Table 3). The interaction effect sizes of B = -1.32 indicated that the combined effect of obesity and MDD and/or anxiety disorders on physical QoL was greater than the additive effect. However, the combined effect of obesity and major depression alone on mental QoL was less than the additive effect (Table 3).
Furthermore, our stratified analysis revealed a significant association of physical QoL across BMI categories and abdominal obesity in depressed and anxious individuals (Table 4). However, the association of obesity and mental QoL was not statistically significant in depressed and anxious individuals in the general population. In non-depressed and anxious individuals, obesity was significantly associated with better mental QoL (Table 5).
In this large, representative cohort study, we found that the combined effects of obesity and MDD and/or anxiety disorders on physical and mental QoL were greater than the sum of their separate effects. Moreover, general and abdominal obesity were significantly associated with a poorer physical QoL in persons with and without MDD and/or anxiety disorders after adjustment for potential confounders. General and abdominal obesity were found to be associated with better mental QoL in persons without MDD/anxiety disorders. This association was not found in persons with MDD/anxiety disorders after adjustment for potential confounders.
The combined effect of obesity and MDD and/or anxiety disorders on physical QoL was significantly larger than the sum of their estimated separate effects. As indicated in the interaction model, the average physical QoL for obese persons (BMI≥30) with MDD was 4.46 points lower than that of non-obese non-depressed persons. With sufficient-cause interaction in mind, obesity and MDD and/or anxiety disorders are component causes that act in concert and are associated with poor physical QoL. Obesity may interact with MDD and/or anxiety disorders, whereby each augmenting the effect of the other on physical QoL. Although this finding is based on cross-sectional data, it seems plausible because obesity shares genetic and complex biologic etiologic substrates with MDD and/or anxiety disorders [14,20,34]. Although the presence of inflammatory responses and the crucial role of cytokines have been established more for depression than for anxiety , the joint presence of MDD/anxiety disorders and obesity can contribute to morbidity and poorer physical conditions [14,20,36]. In addition, subtypes of both obesity and MDD and/or anxiety disorders are assumed to be related to stress, which is characterized by endogenous overproduction of adrenocorticotrophin (ACTH) and cortisol  This chronic hypercortisolism induces (abdominal) obesity and depressive symptoms, and severely reduced HR-QoL, conditions which are all known to improve in the majority of patients after treating the disease by surgery or medication . Hence, the current study shows that joint exposure of obesity and MDD and/or anxiety disorders decreases physical QoL, and the joint association of obesity and MDD and/or anxiety disorders is greater than the additive effect.
The combined effect of obesity and MDD/anxiety disorders on mental QoL was also significantly greater than the sum of their separate effects. The interaction model indicates that mean mental QoL scores were 5.52 points lower in obese persons (BMI≥30) with MDD/anxiety disorders than in those without such disorders. This underlines the findings of Atlantis et al , who reported mean mental QoL scores of 39% to 43% points lower in all BMI groups with MDD compared to groups with normal weight and without MDD. Although the excess reduction of the mental QoL score is expected to be related to MDD/anxiety disorders, being obese may further decrease mental QoL. In Western societies, where being thin is considered attractive beauty, obesity might impact on an individual’s body image and self-esteem, and thus be a source of clinically significant distress or depression, thereby reducing the quality of life . Hilbert et al have also shown that obese persons taking part in social activities face more stigma and prejudice than do obese persons .
Furthermore, multivariate analyses showed that general and abdominal obesity were consistently associated with a poorer physical QoL in persons both with and without MDD and/or anxiety disorders. This finding is in line with a systematic review and several other studies [17, 41–50], which found a robust relationship between overweight, obesity and poorer HR-QoL. The severity of obesity and treatment-seeking behavior might be underlying factors linking obesity and poor physical QoL . Higher body weight and an excess of visceral fat are associated with higher rates of health care utilization . Persons who had sought treatment or tried to lose weight were significantly more impaired on physical measures (e.g. bodily pain, general health and vitality) of HR-QoL than those who did not try to lose weight . As presented in this study, the physical measures of HR-QoL showed significant linear reductions in obese persons, and the greatest decline (20 point lower) was observed in obese persons with MDD and/or anxiety disorders (Table 2). The effect of obesity on mental QoL seems reduced with increasing obesity in anxious individuals compared to depressed counterparts, but was not statically significant after adjustment of potential confounders (Table 2 and Table 5). Therefore, all forms of obesity are associated with poorer physical QoL, and the associations may even be stronger in obese persons who also have MDD and/or anxiety disorders.
We did not find associations of general and abdominal obesity with mental QoL in persons with MDD and/or anxiety disorders. The associations were explained by lifestyle factors and chronic conditions. However, in persons without MDD and/or anxiety disorders, both general and abdominal obesity were significantly associated with a better mental QoL after adjustment for potential confounders. This finding contradicts those of Cameron et al  and Vetter et al , who found that BMI change was associated with a decrease in mental QoL. Laaksonen et al and Renzaho et al reported no association between obesity and mental QoL and other mental health domains [43,45]. Possible explanations for these discrepancies are differences in the assessment of MDD and anxiety disorders, the study population and confounding factors. Most of the previous studies used self-reported measures of MDD and/or anxiety disorders [37,43], while the present study used a psychiatric interview. In the previous studies, the potential interactions between obesity and MDD and/or anxiety disorders were also not considered. Generally, mental health problems could be expected in obese persons because of the stigma associated with excess body weight, but some obese persons appear to have essentially normal psychosocial functioning. This might be due to several underlying factors, such as perceived body image, self-esteem, and the level of severity and persistence of depressive disorders in obese persons [39, 43]. It could also be due to the generic instrument used to assess mental Qol, where the generic versions may not reflect the impact of weight related stigma and discrimination issues on mental QoL in obese persons. Taken together, these results indicate that the joint exposures of obesity and MDD and/or anxiety disorders are associated with poorer physical and mental QoL; obesity alone has no effect on mental QoL in the general population.
Strengths and limitations
The major strength of our study is the nature of the study population, which is derived from the general population and both large and well characterized. The sample size of N = 89,332 participants allowed us to perform subgroup analysis with different BMI categories and MDD and/or anxiety disorders status. Moreover, a comprehensive assessment of chronic conditions, a psychiatric interview, and two anthropometry metrics, i.e. BMI and WC, were used. The similar results for BMI and WC suggest that our results are robust.
The main limitation of our study is its cross-sectional nature, i.e. inferences concerning the direction of the observed associations between obesity, MDD and/or anxiety disorders and HR-QoL cannot be made. Moreover, the use of the RAND-36 may be a limitation, as many researchers for its inadequate reflection of HR-QoL have criticized it. The RAND-36 may also not cover all essential health aspects pertinent to a particular disease. However, it does have the advantage of enabling HR-QoL comparisons across different diseases. It has been shown to have had a high degree of responsiveness to diseases, by which it discriminates between people in different categories of overweight and obesity, as presented here. Nevertheless, it is highly important to sue a multidimensional instrument embracing different health aspects that do not necessarily correlate to each other, such as obesity specific measures like the impact of weight on quality of life (IWQoL-Lite). Furthermore, misclassification may have occurred in the measurements of smoking and alcohol consumption, which were based on self-administered questionnaires. However, earlier studies have showed that self-reported smoking status and alcohol consumption can be used with notable confidence and provide an estimate comparable to the actual consumption [32, 49]. Finally, because data on the binge eating disorder (BED) was not available we were not able to analyse the potential role of this variable in the association of obesity and MDD and/or anxiety with poor HR-QoL. Further studies are needed to assess the potential role of BED.
Practical and policy implications
In this large, representative study, we showed that in the general population the combination of obesity and MDD and/or anxiety disorders is associated with a poor HR-QoL. This combined effect may have implications for prevention and public health measures if confirmed in prospective studies. The magnitude of the impact of obesity and MDD and/or anxiety disorders on a range of HR-QoL dimensions indicates that the successful management of depression in the primary care setting would result in a significant alleviation of suffering in obese adults. In light of this, the weight-increasing side effects of many commonly used antidepressants should also be considered. Where possible, a more restrained use of those antidepressants with the greatest weight stimulating effects would seem advisable, in particular for obese persons . Several studies have shown that a weight loss program can lead to a significant reduction in depression scores . Thus, monitoring depressive and anxiety symptoms is important in obese persons, and maintaining normal weight or reducing excess weight would be by far the best approach to improve the HR-QoL.
In conclusion, the combined effect of obesity and MDD and/or anxiety disorders on HR-QoL is greater than the sum of the separate effects of obesity and MDD and/or anxiety disorders on HR-QoL. Moreover, both general and abdominal obesity are associated with poor physical QoL. General and abdominal obesity without MDD and/or anxiety disorders are associated with better mental QoL. Longitudinal studies are needed to explore the causal pathways between obesity, MDD and/or anxiety disorders and HR-QoL.
The authors wish to acknowledge the services of the LifeLines Cohort Study, the contributing research centers delivering data to LifeLines, and all the study participants. The LifeLines Cohort Study (BRIF4568) is engaged in a Bioresource research impact factor (BRIF) policy pilot study, details of which can be found at https://www.bioshare.eu/content/bioresource-impact-factor. The data catalogue of LifeLines is publicly accessible on http://www.lifelines.net/. The LifeLines system allows access for reproducibility of the study results.
Conceived and designed the experiments: YTN SAR PD EVR UB. Performed the experiments: YTN SAR PD EV UB. Analyzed the data: YTN. Contributed reagents/materials/analysis tools: YTN SAR PD EVR UB. Wrote the paper: YTN SAR PD EVR UB. Approved the decision to publish: YTN SAR PD EVR UB.
- 1. Kelly T, Yang W, Chen CS, Reynolds K, He J. Global burden of obesity in 2005 and projections to 2030. Int J Obes (Lond) 2008; 32:1431–1437.
- 2. Kessler RC, Berglund P, Demler O, Jin R, Koretz D, Merikangas KR, et al. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 2003; 289:3095–3105. pmid:12813115
- 3. Pi-Sunyer X. The medical risks of obesity. Postgrad Med 2009; 121:21–33. doi: 10.3810/pgm.2009.11.2074. pmid:19940414
- 4. Sobocki P, Lekander I, Borgstrom F, Strom O, Runeson B. The economic burden of depression in Sweden from 1997 to 2005. Eur Psychiatry 2007; 22:146–152. pmid:17194573
- 5. Muller-Riemenschneider F, Reinhold T, Berghofer A, Willich SN. Health-economic burden of obesity in Europe. Eur J Epidemiol 2008; 23:499–509. doi: 10.1007/s10654-008-9239-1. pmid:18509729
- 6. Rait G, Walters K, Griffin M, Buszewicz M, Petersen I, Nazareth I. Recent trends in the incidence of recorded depression in primary care. Br J Psychiatry 2009; 195:520–524. doi: 10.1192/bjp.bp.108.058636. pmid:19949202
- 7. Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990–2020: Global Burden of Disease Study. Lancet 1997; 349:1498–1504. pmid:9167458
- 8. Ghoorah K, Campbell P, Kent A, Maznyczka A, Kunadian V. Obesity and cardiovascular outcomes: a review. Eur Heart J Acute Cardiovasc Care 2014. doi: 10.1177/2048872614523349.
- 9. Kabadi SM, Lee BK, Liu L. Joint effects of obesity and vitamin D insufficiency on insulin resistance and type 2 diabetes: results from the NHANES 2001–2006. Diabetes Care 2012; 35:2048–2054. pmid:22751957
- 10. Baune BT, Adrian I, Jacobi F. Medical disorders affect health outcome and general functioning depending on comorbid major depression in the general population. J Psychosom Res 2007; 62:109–118. pmid:17270568
- 11. Soto M, Failde I, Marquez S, Benitez E, Ramos I, Barba A, et al. Physical and mental component summaries score of the SF-36 in coronary patients. Qual Life Res 2005; 14:759–768. pmid:16022068
- 12. Alley DE, Chang VW. The changing relationship of obesity and disability, 1988–2004. JAMA 2007; 298:2020–2027. pmid:17986695
- 13. Sobocki P, Ekman M, Agren H, Krakau I, Runeson B, Martensson B, et al. Health-related quality of life measured with EQ-5D in patients treated for depression in primary care. Value Health 2007; 10:153–160. pmid:17391424
- 14. Afari N, Noonan C, Goldberg J, Roy-Byrne P, Schur E, Golnari G, et al. Depression and obesity: do shared genes explain the relationship? Depress Anxiety 2010; 27:799–806. doi: 10.1002/da.20704. pmid:20821799
- 15. de Wit LM, Fokkema M, van Straten A, Lamers F, Cuijpers P, Penninx BW. Depressive and anxiety disorders and the association with obesity, physical, and social activities. Depress Anxiety 2010; 27:1057–1065. doi: 10.1002/da.20738. pmid:20734363
- 16. Luppino FS, de Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BW, et al. Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Arch Gen Psychiatry 2010; 67:220–229. doi: 10.1001/archgenpsychiatry.2010.2. pmid:20194822
- 17. Fontaine KR, Bartlett SJ, Barofsky I. Health-related quality of life among obese persons seeking and not currently seeking treatment. Int J Eat Disord 2000; 27:101–105. pmid:10590455
- 18. Pan A, Sun Q, Czernichow S, Kivimaki M, Okereke OI, Lucas M, et al. Bidirectional association between depression and obesity in middle-aged and older women. Int J Obes (Lond) 2012; 36:595–602.
- 19. Pan A, Kawachi I, Luo N, Manson JE, Willett WC, Hu FB, et al. Changes in Body Weight and Health-Related Quality of Life: 2 Cohorts of US Women. Am J Epidemiol 2014; 180:254–62. doi: 10.1093/aje/kwu136. pmid:24966215
- 20. Penninx BW, Milaneschi Y, Lamers F, Vogelzangs N. Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile. BMC Med 2013 15; 11:129-7015-11-129.
- 21. Knol MJ, van der Tweel I, Grobbee DE, Numans ME, Geerlings MI. Estimating interaction on an additive scale between continuous determinants in a logistic regression model. Int J Epidemiol 2007; 36:1111–1118. pmid:17726040
- 22. Knol MJ, VanderWeele TJ. Recommendations for presenting analyses of effect modification and interaction. Int J Epidemiol 2012; 41:514–520. doi: 10.1093/ije/dyr218. pmid:22253321
- 23. Stolk RP, Rosmolen JG, Postma DS, de Boer RA, Davis G, Sleets JP, et al. Universal risk factors for multifactorial diseases: LifeLines: a three-generation population-based study. Eur J Epidemiology 2008; 23:67–74.
- 24. World Health Organization. Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation.Geneva. 2008.
- 25. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 1998; 59 (Suppl) 20:22–33.
- 26. Krueger RF, Eaton NR. Transdiagnostic factors of mental disorders. World Psychiatry 2015;14(1):27–29. doi: 10.1002/wps.20175. pmid:25655146
- 27. Barajas Gutierrez MA, Robledo Martin E, Tomas Garcia N, Sanz Cuesta T, Garcia Martin P, Cerrada Somolinos I. Quality of life in relation to health and obesity in a primary care center. Rev Esp Salud Publica 1998; 72:221–231. pmid:9810829
- 28. Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, et al. Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998; 51:1171–1178. pmid:9817135
- 29. Hays RD, Morales LS. The RAND-36 measure of health-related quality of life. Ann Med 2001; 33:350–357. pmid:11491194
- 30. Ware JE, Kosinski M, Keller SD. SF-36 Physical and mental summary scales: A user’s manual. Boston: The Health Institute 1994.
- 31. Ware JE Jr, Gandek B, Kosinski M, Aaronson NK, Apolone G, Brazier J, et al. The equivalence of SF-36 summary health scores estimated using standard and country-specific algorithms in 10 countries: results from the IQOLA Project. International Quality of Life Assessment. J Clin Epidemiol 1998;51: 1167–1170. pmid:9817134
- 32. Slagter SN, van Vliet-Ostaptchouk JV, Vonk JM, Boezen HM, Dullaart RP, Kobold AC, et al. Combined Effects of Smoking and Alcohol on Metabolic Syndrome: The LifeLines Cohort Study. PLoS One 2014; 9:e96406. doi: 10.1371/journal.pone.0096406. pmid:24781037
- 33. Egede LE. Major depression in persons with chronic medical disorders: prevalence, correlates and association with health resource utilization, lost productivity and functional disability. Gen Hosp Psychiatry 2007; 29:409–416. pmid:17888807
- 34. Thormann J, Chittka T, Minkwitz J, Kluge M, Himmerich H. Obesity and depression: an overview on the complex interactions of two diseases. Fortschr Neurol Psychiatr 2013; 81:145–153. doi: 10.1055/s-0032-1330351. pmid:23516104
- 35. Vogelzangs N, Beekman AT, de Jonge P, et al. Anxiety disorders and inflammation in a large adult cohort. Transl Psychiatry 2013; 3:e24.
- 36. Whisman MA, McClelland GH. Designing, testing, and interpreting interactions and moderator effects in family research. J Fam Psychol 2005; 19:111–120. pmid:15796657
- 37. Badia X, Valassi E, Roset M, Webb SM. Disease-specific quality of life evaluation and its determinants in Cushing's syndrome: what have we learnt? Pituitary 2014; 17:187–195. doi: 10.1007/s11102-013-0484-2. pmid:23564339
- 38. Atlantis E, Goldney RD, Eckert KA, Taylor AW. Trends in health-related quality of life and health service use associated with body mass index and comorbid major depression in South Australia, 1998–2008. Qual Life Res 2012; 21:1695–1704. doi: 10.1007/s11136-011-0101-7. pmid:22205135
- 39. Friedman KE, Reichmann SK, Costanzo PR, Musante GJ. Body image partially mediates the relationship between obesity and psychological distress. Obes Res 2002; 10:33–41. pmid:11786599
- 40. Hilbert A, Braehler E, Haeuser W, Zenger M. Weight bias internalization, core self-evaluation, and health in overweight and obese persons. Obesity (Silver Spring) 2014; 22: 79–85.
- 41. Cameron AJ, Magliano DJ, Dunstan DW, Zimmet PZ, Hesketh K, Peeters A, et al. A bi-directional relationship between obesity and health-related quality of life: evidence from the longitudinal AusDiab study. Int J Obes (Lond) 2012; 36:295–303.
- 42. Gariepy G, Wang J, Lesage AD, Schmitz N. The longitudinal association from obesity to depression: results from the 12-year National Population Health Survey. Obesity (Silver Spring) 2010; 18:1033–1038.
- 43. Renzaho A, Wooden M, Houng B. Associations between body mass index and health-related quality of life among Australian adults. Qual Life Res 2010; 19:515–520. doi: 10.1007/s11136-010-9610-z. pmid:20182918
- 44. Vetter ML, Wadden TA, Lavenberg J, Moore RH, Volger S, Perez JL, et al. Relation of health-related quality of life to metabolic syndrome, obesity, depression and comorbid illnesses. Int J Obes (Lond) 2011; 35:1087–1094.
- 45. Laaksonen M, Sarlio-Lahteenkorva S, Leino-Arjas P, Martikainen P, Lahelma E. Body weight and health status: importance of socioeconomic position and working conditions. Obes Res 2005; 13:2169–2177. pmid:16421352
- 46. Nigatu YT, Bultmann U, Reijneveld SA. The prospective association between obesity and major depression in the general population: does single or recurrent episode matter? BMC Public Health 2015;15(1):350.
- 47. Nigatu Y, Bültmann U, Reijneveld S. The prospective association between obesity and major depression: a longitudinal cohort study in the general population. The European Journal of Public Health 2013;23(suppl 1).
- 48. van Zutven K, Mond J, Latner J, Rodgers B. Obesity and psychosocial impairment: mediating roles of health status, weight/shape concerns and binge eating in a community sample of women and men. Int J Obes (Lond) 2015;39:346–352.
- 49. Giovannucci E, Colditz G, Stampfer MJ, Rimm EB, Litin L, et al. The assessment of alcohol consumption by a simple self-administered questionnaire. Am J Epidemiol 1991:133: 810–817. pmid:2021148
- 50. Blumenthal SR, Castro VM, Clements CC, Rosenfield HR, Murphy SN, Fava M, et al. An electronic health records study of long-term weight gain following antidepressant use. JAMA Psychiatry 2014; 71:889–896. doi: 10.1001/jamapsychiatry.2014.414. pmid:24898363
- 51. Barnes RD, White MA, Martino S, Grilo CM. A randomized controlled trial comparing scalable weight loss treatments in primary care. Obesity (Silver Spring) 2014; 22:2508–2516.