Literature DB >> 31879459

Is obesity a risk to depression? A cross-sectional study.

Rajat Garg1, Sachin Kumar Saxena2, Sabreen Bashir3.   

Abstract

BACKGROUND: Depression and obesity are disorders of stress with a dose dependent relationship between the both. The adverse health and social consequences are significant, when depression and obesity co-exist. This study aimed to examine the prevalence of depression among overweight and obese patients in a large station of Armed Forces and associate other risk factors of depression.
METHODS: This cross sectional descriptive study was conducted in the general OPD of large Station medicare centre (SMC) on overweight and obese personnel. Data was collected by self-administered Patient Health Questionnaire (PHQ-9) to assess the risk for depression over a period of one month.
RESULTS: In this study, out of 106 individuals, 71 (67%) were overweight and 35 (33%) were obese, as per WHO criteria. Of the individuals assessed, 13 (12%) individuals were found to have risk of moderate depression, 58 (54%) for mild depression and 35 (33%) individuals had no risk for clinically significant depression. The likelihood of depression was most strongly associated with BMI followed by age, status of living with family and habit of drinking alcohol.
CONCLUSION: Obesity and depressive disorders are common comorbidities with overlapping pathophysiology whose co-existence leads to exponential adverse health outcomes. The outcome of depression and obesity is to be managed comprehensively by psychological counseling and life style modification. Copyright:
© 2019 Industrial Psychiatry Journal.

Entities:  

Keywords:  Depression; Patient Health Questionnaire-9; obesity; overweight

Year:  2019        PMID: 31879459      PMCID: PMC6929221          DOI: 10.4103/ipj.ipj_59_19

Source DB:  PubMed          Journal:  Ind Psychiatry J        ISSN: 0972-6748


Globally, the prevalence of depression and obesity are important public health concerns, with an estimated 350 and 500 million people suffering, respectively.[12] A recent meta-analysis of 17 community-based cross-sectional studies among adults showed a positive overall association between depression and obesity.[3] Depression and obesity are disorders of stress with dysregulation of the stress management system [Figure 1].[4] Obesity is a systemic disorder, leading to increase in cortisol, leptin, insulin levels resulting in hypothalamic pituitary adrenal axis dysregulation, and insulin resistance, which can further induce inflammation and worsen depression.[5] There is a dose-dependent relationship between the both, that is, with higher body mass index (BMI) the risk of clinical depression increases.[3]
Figure 1

Pathoetiological connection between obesity and depression. ACTH – Adrenocorticotrophic hormone; CRH – Corticotropin-releasing hormone; CRP – C-reactive protein; HPA – Hypothalamic—pituitary—adrenal; IL – Interleukin; TNF – Tumour necrosis factor

Pathoetiological connection between obesity and depression. ACTH – Adrenocorticotrophic hormone; CRH – Corticotropin-releasing hormone; CRP – C-reactive protein; HPA – Hypothalamic—pituitary—adrenal; IL – Interleukin; TNF – Tumour necrosis factor Obesity and depression run in the vicious cycle [Figure 2]. When an individual is in a depressed mood state, it is also associated with anhedonia and sedentary lifestyle along with dietary changes. On the other hand, obese patients have higher levels of leptin hormone, which is known to cause clinical depression. Depression and obesity are both associated with social stigma and low self-esteem.[6] The adverse health and social consequences are significant when depression and obesity cooccur. Symptoms of depression in obese patients are strongly associated with poor quality of life, particularly social functioning and mental health.[7] Further, obesity coupled with depression has significant economic implications, owing to reduced participation in the labor force and absenteeism.[8]
Figure 2

Vicious cycle of obesity and depression

Vicious cycle of obesity and depression There are limited data on the prevalence of comorbid obesity and depression in the general practice setting. The frequency with which comorbid depression and obesity occur is important because of the implications for its detection and management. For example, some somatic criteria for the diagnosis of depression, such as sleep problems, fatigue, or changes in appetite, could be confounded with manifestations of obesity.[9] Depressed people with overweight are difficult to manage; however, little decrease in their body weight had remarkably helped improving their depression.[10] While interventions for weight management, such as exercise and lifestyle modification may also be helpful in managing depression, there are no set protocols for providing integrated treatment of these health conditions. This study aimed to examine the risk of depression among overweight and obese individuals in a large station of Armed Forces and associate depression with other risk factors.

MATERIALS AND METHODS

This is a cross-sectional (prospective) descriptive study conducted in the general outpatient department (OPD) of a large station of Armed Forces.

Sample

The study population was overweight and obese personnel registered in polyclinic (calculated according to the BMI) who were ≥18 years of age and who fulfilled both inclusion criteria. Inclusion criteria were all personnel whose BMI was ≥25 and who were willing to participate in the study. From a previous study, the prevalence of depression among obese participants was 23%,[11] which sample size was calculated to be 106 taking the absolute error of margin of 8% with 95% confidence interval (CI).

Instruments

After taking their informed consent, data were collected by self-administered/interviewer assisted (in case of insufficient ability) Patient Health Questionnaire (PHQ-9) to assess the risk of depression. The PHQ-9 has been extensively used by medical personnel in the primary care setting.[12] A total score of ≥10 to classify depression is considered the best balance between sensitivity (88%) and specificity (88%) compared to mental health professional assessment, and this cutoff value was used for this study.[13]

Measures

Social-demographic characteristics

Self-administered data were obtained for age category, rank, service years, education status, marital status, status of living with family, past field postings, and habit of drinking alcohol.

Body mass index

Participants were asked to report their weight to the nearest kilogram and their height to the nearest centimeter. BMI was calculated, and World Health Organization definitions applied to categories overweight (25–29.9 kg/m2) and obese (>30 kg/m2).[14] Overweight and obese individuals were included in the study.

Depression

The PHQ-9 was used to assess the risk of depression. It is scored on a 27-point scale. Severity of risk of depression was graded according to the following scores: (0–4) – no risk; score (5–10) – mild risk; score (10–14) – moderate risk; and score (>15) – severe risk of depression.[13]

Statistical analysis

Data entry and statistical analysis were conducted using the Statistical Package for the Social Sciences program version 21 (IBM Corporation, Chichago USA). Descriptive analysis was performed including frequencies, percentages, and confidence intervals. Binary logistic regression model was used to examine association between predictor variables (as captured by data capturing form) and risk of depression. The main model consists of the following predictor variables: demographic variables such as age, service years, rank, education, marital status, living status, and habit of drinking alcohol. Results were expressed as odds ratio (OR) and 95% CIs. In this study, the level of significance was set at P < 0.05 for all the analyses.

RESULTS

A total of 106 study population including 71 (67%) overweight, and 35 (33%) obese were evaluated. The mean age ± standard deviation of patients was 37.73 ± 9.3 years with a minimum age of 25 years and maximum age of 56 years. Among the study population, 82 (77.4%) were of the rank sergeant and below and 24 (22.6%) were warrant officers and above with mean service years of approximately 18 years. More than half of the study population was graduates (75.5%). Almost 80% of individuals were married, and 74.5% of them were living with family. A majority of the respondents (63%) had the habit of drinking alcohol. Among the study population, 67% of them were overweight, and 33% of them were obese with a mean BMI of 27.9 kg/m2 [Table 1].
Table 1

Demographic characteristics of the study population

Characteristicsn=106%
Age (yr)
 Upto 303331.1
 31 and above7368.9
Rank
 Sgt & below82774
 WO & Above2422.6
Service years
 Upto 206561.3
 21 & above4138.7
Education
 Primary School54.7
 Middle School32.8
 High School1817
 Graduate
Field postings8075.5
 Yes5350
 No
Marital Status5350
 Married9286.8
 Unmarried1413.2
Living Status
 With Family7974.5
 Alone2725.5
Habit of Drinking Alcohol
 Yes6763.2
 No3936.8
BMI
 Overweight7167
 Obese3533

BMI- Body mass index (kg/m2); SGT - Sergeant; WO- Warrant officer

Demographic characteristics of the study population BMI- Body mass index (kg/m2); SGT - Sergeant; WO- Warrant officer As per this study, of the individuals assessed, 13 (12%) individuals fulfilled the criteria for risk of moderate depression, 58 (54%) for mild depression, and 35 (33%) individuals had no risk for clinically significant depression. Thus almost half of individuals with overweight or obese were ailing from the risk of mild-to-moderate depression. There was no individual with risk of severe depression. This study is in concurrence with a previous study which found overweight increased the risk of onset of depression.[3] The prevalence of depression in overweight and obese individuals can be associated with factors such as stigmatization, low self-esteem, and body dissatisfaction[11] which can contribute to or exacerbate depressive illness. Conversely, features of depression may also cause or exacerbate weight problems and obesity. On assessing the individuals whether they had any difficulty in job, about 53% of individuals had some difficulty in job, about 20% of them had moderate difficulty in job, and about 25% of them had no difficulty in job [Table 2].
Table 2

Risk of depression in Study population

Likelihood of depressionn=106%
No risk3533
Mild risk5854.7
Moderate risk1312.3
Severe risk--

PHQ Score (0-4) - No risk; (5-10)- Moderate risk; (10-14) moderate risk, (>15)- severe risk

Risk of depression in Study population PHQ Score (0-4) - No risk; (5-10)- Moderate risk; (10-14) moderate risk, (>15)- severe risk The likelihood of depression was most strongly associated with BMI (OR: 6.33; 95% CI: 2.94–13.64; P < 0.001) followed by age (OR: 1.12; 95% CI: 1.08–3.7; P = 0.008), living single (OR: 1.31; 95% CI: 1.06–1.54; P = 0.004), and the habit of drinking alcohol (OR: 1.24; 95% CI: 1.04–1.64; P = 0.041). There was a positive association between weight gain and depression in a previous study also.[15] Advancing age was associated with depression which was also shown in earlier studies.[16]

DISCUSSION

Obesity and depressive disorders are common morbidities with overlapping pathophysiology whose coexistence is associated with adverse health outcomes. In fact, many overweight/obese patients exhibited weight loss after the treatment of depression.[10] This study found that large number (54%) of obese patients had a risk of mild depression, and few (12%) had a risk of moderate depression. As per recent literature,[9] the individuals with risk of mild depression to be treated in community setting itself with lifestyle modification, dietary advice, and involvement of pleasure-seeking activities. Whereas individuals with risk of moderate depression need to be referred to psychological counselor for further investigation and counseling sessions. The data regarding the prevalence of depression in patients with overweight and obese individuals from India are scarce. However, a previous study from the USA reported that obese were significantly more likely to be depressed than those who were either normal or underweight.[17] Regression analysis from the previous studies identified more educated, unmarried group of individuals with worse mental health.[1718] However, the likelihood of depression was not significant with education status and marital status in this study. This study also showed no significant association with service years, rank, and field postings. The most likely explanation for these disparate results relates to differences in the populations studied and the procedures used, particularly the measures of depression. Exploration into the most effective ways of discovering the potential comorbidity of obesity and depression will help to assist in developing interventional approaches to effectively target these conditions simultaneously or sequentially.

Limitation

The PHQ-9 has been shown to have high sensitivity and specificity in the general practice setting. However, it is a screening tool and does not provide a clinical diagnosis of depression. Therefore, there is likely to be some degree of measurement error in the rates of depression reported for each BMI category. Cross-sectional nature of this study precluded an examination of the alternate hypothesis that depression increases the risk for obesity.

RECOMMENDATIONS

It is recommended that every individual with overweight/obesity should once be screened by the PHQ-9 questionnaire by the authorized medical attendant at the OPD level and should be analyzed for the risk of depression. Individuals who are detected to have moderate-to-severe risk of depression should not only undergo lifestyle modifications but also be enrolled in a combined comprehensive obesity and depression control program, which will include the systemic series of counseling sessions by a trained psychological counselor and should be followed up till the individual is benefited. The benefit of interpersonal and psychotherapy may also be given by referring them to psychiatry centers. This will improve not only the overall functional status including mental, emotional, and social well-being but also their health perception and quality of life. It will also prevent cognitive dysfunction, increased days of work absence, early retirement, higher dependence on disability welfare and correspondingly, and improvement in depressive symptoms leading to increase in work productivity.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.
  12 in total

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Review 2.  Approaching the shared biology of obesity and depression: the stress axis as the locus of gene-environment interactions.

Authors:  S R Bornstein; A Schuppenies; M-L Wong; J Licinio
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Review 4.  Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies.

Authors:  Floriana S Luppino; Leonore M de Wit; Paul F Bouvy; Theo Stijnen; Pim Cuijpers; Brenda W J H Penninx; Frans G Zitman
Journal:  Arch Gen Psychiatry       Date:  2010-03

5.  Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis.

Authors:  Simon Gilbody; David Richards; Stephen Brealey; Catherine Hewitt
Journal:  J Gen Intern Med       Date:  2007-09-14       Impact factor: 5.128

6.  Management of depression in UK general practice in relation to scores on depression severity questionnaires: analysis of medical record data.

Authors:  Tony Kendrick; Christopher Dowrick; Anita McBride; Amanda Howe; Pamela Clarke; Sue Maisey; Michael Moore; Peter W Smith
Journal:  BMJ       Date:  2009-03-19

7.  Depression in association with severe obesity: changes with weight loss.

Authors:  John B Dixon; Maureen E Dixon; Paul E O'Brien
Journal:  Arch Intern Med       Date:  2003-09-22

8.  Major depression as a risk factor for chronic disease incidence: longitudinal analyses in a general population cohort.

Authors:  Scott B Patten; Jeanne V A Williams; Dina H Lavorato; Geeta Modgill; Nathalie Jetté; Michael Eliasziw
Journal:  Gen Hosp Psychiatry       Date:  2008-07-23       Impact factor: 3.238

9.  Prevalence of comorbid depression and obesity in general practice: a cross-sectional survey.

Authors:  Mariko Carey; Hannah Small; Sze Lin Yoong; Allison Boyes; Alessandra Bisquera; Rob Sanson-Fisher
Journal:  Br J Gen Pract       Date:  2014-03       Impact factor: 5.386

Review 10.  Metabolic disturbances connecting obesity and depression.

Authors:  Cecile Hryhorczuk; Sandeep Sharma; Stephanie E Fulton
Journal:  Front Neurosci       Date:  2013-10-07       Impact factor: 4.677

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