Emotional states of different obesity phenotypes: A sex-specific results in a west-Asian population

doi:10.21203/rs.3.rs-48797/v1

Download PDF

Research article

Emotional states of different obesity phenotypes: A sex-specific results in a west-Asian population

https://doi.org/10.21203/rs.3.rs-48797/v1

This work is licensed under a CC BY 4.0 License

Journal Publication

published 04 Mar, 2021

Read the published version in BMC Psychiatry →

You are reading this older preprint version

Read the latest preprint version →

Background

The present study aimed to investigate the relationship of obesity phenotypes with depression, anxiety, and stress of the adult participants in Tehran Lipid and Glucose Study (TLGS).

Methods

Depression, anxiety, and stress levels of 2469 adult participants aged > 19 (1158 men and 1311 women) from Tehran Lipid and Glucose Study were examined among different obesity phenotypes in the current study. Weight, height, and waist circumferences of participants were measured by trained personnel. Obesity was defined as BMI ≥ 30 kg/m², and metabolically unhealthy status based on having metabolic syndrome (MetS) or diabetes type 2. Finally, four obesity phenotypes were defined: 1) Metabolically Healthy Non-Obese (MHNO), 2) Metabolically Healthy Obese (MHO) 3) Metabolically Unhealthy Non-Obese (MUNO), and 4) Metabolically Unhealthy Obese (MUO). Ordinal logistic regression analysis was used to compare sex-specific odds ratios.

Results

The mean age of 2469 men and women was 46.2 ± 15.9 and 45.6 ± 14.7, respectively. In total, women were more likely to experience different levels of depression (30.5%), anxiety (44.2%), and stress (43.5%). After adjusting for potential confounders, the odds of experiencing higher levels of anxiety were significantly greater in metabolically unhealthy men whether they were obese (OR: 1.78, 95% CI: 1.25–2.54; P = < 0.001) or non-obese (OR: 1.61, 95% CI: 1.17–2.21; P = < 0.001), and also in MUO women (OR: 1.73, 95% CI: 1.28–2.34; P = < 0.001) comparing to their MHNO counterparts. Moreover, the odds of experiencing higher levels of stress were significantly greater in MUNO men (OR: 1.40, 95% CI: 1.02–1.90; P = 0.04), and in MUO women (OR: 1.45, 95% CI: 1.07–1.96; P = 0.02) comparing to their MHNO counterparts. No difference in having higher levels of depression was observed in both genders.

Conclusions

Compared to MHNO individuals, MUO women and all metabolically unhealthy men reported higher levels of anxiety and stress. The obesity phenotypes were by no means associated with depression in men and women.

Psychiatry

Psychology

metabolic syndrome

obesity

anxiety

depression

stress

metabolically healthy obesity

Obesity is a common health issue that has tripled over the last decades (1). Along with the global ascending rate of excessive weight gain, a range of 18.5% − 25% as an average prevalence for obesity among the Iranian adult population has also been reported (2). Although obesity has been identified as the leading cause of chronic disorders, such as cardiovascular diseases (CVDs), diabetes Mellitus, cancers, and premature death (3), according to some studies, metabolic syndrome (MetS) is a determining factor in evaluating the outcomes of obesity as well as body mass index (BMI) (4). In this regard, obesity phenotypes are represented as combinations of BMI and metabolic health components which may lead to different health outcomes (5).

Unlike the well-studied physical comorbidities of obesity and MetS, there are contradictory results in the realm of psychological consequences. Although it has been fairly indicated that the metabolic disturbances are partly responsible for increased mortality in schizophrenic and bipolar patients (6), there is no certain consensus about the predisposing impacts of obesity and MetS on common mental problems such as depression, anxiety, and stress. These disorders affect the mood or feelings of individuals, decline productivity, and cause a tremendous economic burden (7, 8). Considering the high prevalence of depression (44%), anxiety (42%), and stress (40%) in Iran and the existing mixed data in this area, it is crucial to recognize the influential factors on mentioned emotional states (9).

Obese individuals are believed to be more depressed and anxious, which is supported by a large body of evidence (10, 11), although, some studies did not confirm this relationship (12–14), and even others have established the "jolly fat" theory, which emphasizes an adverse association between obesity and mental health issues, including depression and anxiety (15, 16). In terms of MetS, similar conflicting results have been published of mentioned emotional states in relation to unfavorable metabolic profile (17–20). The previous studies also worked on the bi-directional relationship and existence of a vicious cycle of obesity and stress (21), which has been considered as a risk factor for some parameters of metabolic syndrome (22); however, stress was barely considered in those studies as an outcome. To the best of our knowledge, just a recent meta-analysis on four qualified studies indicated no relationship between MetS and stress levels in the adult population (22).

The remarkable point is that despite the often concurrence of obesity and MetS, most of the prior studies have not considered the heterogeneity of obesity phenotypes. Only were a few studies conducted to answer whether or not being a metabolically healthy obese (MHO) is a psychologically benign situation in comparison to other phenotypes. As the meta-analysis in 2014 revealed, although MHO individuals experience higher levels of depression than metabolically healthy non-obese (MHNO) ones, they were less likely to develop depressive symptoms compared to metabolically unhealthy obese (MUO) individuals (23). Since then, four similar studies were conducted, three of which only considered depression as a mental outcome. Two studies among Irish and French populations showed a higher risk of psychological health problems in MUO individuals (24, 25). In contrast, the recent English Longitudinal Study of Ageing (ELSA) revealed no association between obesity and MetS with depression (26); a study among a very small Iranian population indicated that MHO was a benign phenotype associated with depression (27). Examining the effects of two common somatic diseases on mental health problems could shed light on one aspect of these multifactorial disorders. The current study aimed to investigate the relationship of obesity phenotypes with depression, anxiety, and stress in adult participants of the Tehran Lipid and Glucose Study (TLGS). The obtained results could provide a comprehensive view regarding the emotional states of a large general population in West Asia.

Study design and participants

This study was conducted in the framework of the Tehran Lipid and Glucose Study (TLGS). The TLGS includes two major junctures: phase 1, a cross-sectional study designed to determine the prevalence of non-communicable diseases (NCDs) risk factors executed from 1999 to 2001, and five follow up re-exam have been implemented from 2002 to 2015. More study details have been reported previously (28).

Form all the individuals who participated in the TLGS during 2016-2018 (6^th phase), 2728 participants were recruited aged ≥20 years with complete data on depression, anxiety, and stress. After excluding those with missing data on BMI, MetS components, or covariates (sociodemographic factors, smoking status, and level of physical activity) (n=259), the final data of 2469 adults (1158 men and 1311 women) were analyzed. This study was approved by the ethics committee of the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences. All the participants signed the written informed consent before data collection.

Definition and measurements

Obesity phenotypes: The participants were categorized into four obesity phenotypes: 1) Metabolically healthy non-obese (MHNO), 2) Metabolically healthy obese (MHO) 3) Metabolically unhealthy non-obese (MUNO), and 4) Metabolically unhealthy obese (MUO). Metabolically unhealthy status was defined as having MetS or diabetes type 2 according to Joint Interim Statement (JIS) and American Diabetes Association (ADA) respectively. MetS was defined as having any three of the following abnormalities: 1) ethnic-based abdominal obesity which described as waist circumference ≥ 90 for men and women (29) ; 2) HDL-cholesterol < 40 mg/dl in men or 50 mg/dl in women; 3) triglyceride ≥ 150 mg/dl; 4) glucose FPG≥ 100 mg/dl or known treatment for diabetes; 5) blood pressure ≥ 130/85 mmHg or use of antihypertensive drugs (30).

Type 2 diabetes was defined as fasting blood sugar ≥ 126 mg/dl or 2-hour post-load glucose ≥ 200 mg/dl or taking medication for diagnosed diabetes. Obesity was defined as BMI≥30 kg/m².

Sociodemographic characteristics: The participants' age, gender, marital status, job status, and educational level were assessed via a pretest questionnaire. The educational level of participants defined as 1) Primary: including people with less than a high school diploma; 2) Secondary: including people with a high school diploma; and 3) Higher: including people with a college degree or higher.

Smoking and physical activity status: The smoking habit of participants was classified into two groups: 1) smokers (daily and occasionally smokers) and 2) non-smokers (ex-smokers or never smokers). Physical activity levels were evaluated by the validated Iranian version of the Modifiable Activity Questionnaire (MAQ). To calculate the energy expenditure for activates of sport, job, and travel during one week, the metabolic equivalent task (MET) of the particular act was multiplied by a weight and the sum of all acts considered as total energy expenditure in adults. After calculating total MET-value for adults, it was categorized into three groups of low (<600), moderate (600-3000), and high (≥3000) physical activity (31).

Clinical and anthropometric measurements: Trained personnel measured weight, height, and waist circumferences of participants while they wore light clothes and were barefoot. The weight was analzyed using an electronic digital scale that its accuracy was up to 100 g. The height was examined while participants were standing in a normal position. Waist circumference was measured via an unstretched measuring tape and recorded to the nearest 0.1. The blood pressure was measured after a 15-minute rest period in the seated position twice by qualified physicians via a standard mercury sphygmomanometer; the average of two measurements was considered for analysis.

Biochemical measurements: The blood sample was taken from the participants after a 12-14 hour overnight fast by trained personnel in the data collection center of the TLGS. All blood sample of fasting blood sugar (FBS) and serum lipids (total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG)) were analyzed in the TLGS research laboratory on the same day. Additional information has been previously published about the biochemical measurements (32).

Depression, anxiety, and stress: The Persian version of depression, anxiety, and stress scale-21 items (DASS-21) was used to assess the emotional distress of participants. The psychometric properties of the Persian version of DASS-21 have been previously studied among the Iranian population, and its reliability and validity were approved (33) . DASS-21 is a self-report questionnaire, including three scales, and each scale was composed of seven items divided into subscales with similar content. The participants completed this questionnaire by rating each item to reflect their emotional experiences from 0 (did not apply to me at all) to 3 (applied to me very much). The cut-off scores for conventional severity labels were used as follows: 1) Depression: normal: 0-9, mild: 10-13, moderate: 14-20, and severe: +21; 2) Anxiety: normal: 0-7, mild: 8-9, moderate: 10-14, and severe: +15; 3) Stress: normal: 0-14, mild: 15-18, moderate: 19-25, and severe: +26. The highest score for each scale was 42, multiplied by 2 (34).

Statistical analysis

Continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were expressed as frequency (percentage). The continuous and categorical variables among different obesity and MetS groups were cmpared via one way ANOVA and Chi-square test, respectively. Mean scores of depression, anxiety, and stress were compared across different obesity phenotypes via the analysis of covariance and age, marital status, education, job status, smoking status, and level of physical activity were considered as adjustments. Ordinal logistic regression was used to explore the associations between obesity/MetS groups and ordinal outcomes of depression, anxiety, and stress. Sex-specific ORs with 95% confidence intervals were calculated and reported for men and women separately; model 1 was unadjusted, while model 2 was adjusted for age, marital status (Ref.: Married), education (Ref.: Higher), job status (Ref.: Employed), smoking status (Ref.: Non-smoker), and level of physical activity (Ref: High). All tests were two-sided, and a p-value of less than 5% was considered statistically significant. Statistical analysis was conducted using the IBM SPSS 24 (SPSS Inc., Chicago, IL, USA).

The mean age of 2469 men and women was 46.2±15.9 and 45.6±14.7 years, respectively. The distribution of sociodemographic factors, smoking status, and level of physical activity among study groups are illustrated in Table1. The majority of participants in all groups were married (79.9% men and 75.1% women). Most dysmetabolic men subjects had a college degree (40% non-obese and 43.4% obese), while most dysmetabolic women had a high school diploma or less (45.6% non-obese and 51.1% obese). Most men in all groups (74%) were employed while most women (71.5%) were unemployed or housewife. The prevalence of type 2 diabetes among MUNO and MUO phenotypes was 20% and 16.6% among men, likewise 33.8% and 25.1% among women. The mean BMI of participants was 27.79±4.85. The descriptive statistics of BMI and MetS components in men and women are represented in Table 1-Appendix.

Table 2 illustrates the distribution of depression, anxiety, and stress levels among phenotypes for men and women. In total, women were more likely to experience different levels of depression (30.5%), anxiety (44.2%) and stress (43.5%), and the number of severe depression, anxiety, and stress in women (7.3%, 12.715.5%, and 11.616.6%) was higher than men (10.64.7%, 23.28.2%, and 17.9%). The highest and lowest frequency were MHNO women with normal levels of depression and MHO men with moderate and severe depression, respectively. The mean scores of depression, anxiety, and stress were compared among different obesity phenotypes after adjusting for age, marital status, level of education, job status, smoking status, and level of physical activity and were illustrated in (Figure 1). The results showed that mean anxiety scores in men and mean anxiety and stress scores in women were significantly different among obesity phenotypes (p= 0.044, p=0.02, and p=0.022, respectively). However, there was no significant difference in the depression scale in both genders.

Table 3 shows the odds ratios (95% CI) of reporting higher levels of depression, anxiety, and stress for different obesity phenotypes for men and women separately. After adjusting for potential confounders, including age, marital status, level of education, job status, smoking status, and level of physical activity, the odds of experiencing higher levels of anxiety were significantly greater in metabolically unhealthy men whether they were obese (OR: 1.78, 95% CI: 1.25-2.54; P=<0.001) or not obese (OR: 1.61, 95% CI: 1.17-2.21; P= <0.001), and also in MUO (OR: 1.73, 95% CI: 1.28-2.34; P=<0.001) comparing to their MHNO counterparts. Moreover, the odds of experiencing higher levels of stress were significantly greater in MUNO (OR: 1.40, 95% CI: 1.02-1.90; P=0.04), and in MUO (OR: 1.45, 95% CI: 1.07-1.96; P=0.02) comparing to their MHNO counterparts. The difference in having higher levels of depression only was observed in MUO women before adjustment (OR: 1.39, 95% CI: 1.04-1.84; P=0.02); no difference was observed after adjustments in both genders.

The present study was one of the first attempts to investigate the relation of obesity phenotypes with emotional distress among men and women in Tehran. In total, the current results indicated that women were more likely to experience anxiety and stress. More stratified analysis based on weight and metabolic status revealed an increased risk of anxiety and stress among MUO women compared to their MHNO counterparts. However, corresponding results for men showed that just metabolic disorders, regardless of weight status, could lead to higher levels of anxiety and stress. Interestingly, obesity phenotypes were not related to depression in both genders.

The current results indicated that women were more prone to experience mental problems, mainly in the form of anxiety and stress. Consistent with our findings, gender differences and higher prevalence of mood and anxiety disorders among women have been addressed in Iran (9) and other nations as well (35). Apart from genetic and other biological factors like more hormonal fluctuations in women (36), some essential psycho-socio-cultural determinants including more extended rumination and brooding (37), shame, interpersonal stressors, and experienced violence in women, in addition to gender inequality, traditional gender roles, and sex-based discrimination are considered to be the reason for this higher prevalence worldwide (38). In transitional societies, including most of the middle-Eastern countries, all developments in the economic and educational structure of the community in recent decades have been accompanied by the multiplicity of women’s expected roles, which could complicate the underlying causes of mentioned mental disorders (39).

In the current study, there were significant relationships among obesity phenptypes with anxiety and stress in both genders. The previous studies focused mainly on depression as a mental health regarding obesity phenotypes. Therefore, relevant knowledge about anxiety and stress is inadequate and conflicting. On the other hand, using different tools for measurement, investigating separate effects of obesity and cardiovascular risk factors, and various cultural contexts make the comparison difficult. To the best of our knowledge, only one study on the middle-aged Irish population revealed a higher risk of anxiety in MUO individuals than their MHNO counterparts (24). Other studies focused on weight and metabolic health status separately. In this regard, a meta-analysis has reported more frequent incidence of anxiety in obese individuals than normal-weight persons (11). Conversely, some evidence showed the lack of association between MetS and anxiety among Japanese men (17). Regarding stress, the findings of a recent meta-analysis on four studies indicated no association between MetS and stress (22). The interaction of anxiety and stress in our findings is perceived from the higher levels of anxiety and stress in the same definite phenotypes, since chronic stress leads to anxiety and anxeity makes individuals vulnerable to stress (40). Moreover, indisputable effects of local culture on these global experiences can be seen in the findings, as collectivism is one of the fundamental characteristics of Middle Eastern societies that protect individuals against depression but exposes them more to anxiety (41). In terms of gender differences, our findings indicated the importance of metabolic health status in increasing men's anxiety and stress levels, while neither obesity nor metabolic syndrome solely affects women's mental state. Despite the rising rate of female labor force participation in Iran, the responsibility for family expenses primarily is still on men (42). This situation highlighted the significance of men's health conditions, which could lead to more feelings of pressure.

The current findings revealed no significant association between obesity phenotypes and depression in both genders. These results are consistent with the findings of the English Longitudinal Study of Ageing (ELSA) which indicated that neither obesity nor poor metabolic status was associated with higher risks of depressive symptoms at over two years follow-up (26). Accordingly, another longitudinal survey suggested that obesity was not a predictor of depression in Canadian women (12), and the same results have been observed among Mexican men (14). Also, the lack of relationship between MetS and depression was already published among the Turkish population (18). However, two systematic reviews confirmed the positive relationship between obesity and depression in different communities (10) and an increased risk of depression for MUO individuals (43). Since the relation of obesity phenotypes with depression is multifactorial, the discrepancy in the outcomes could have many physical to psychosocial factors. Aside from gene-by-environment interaction (44), the underlying psychological factors seem to play a particular role in this regard. The increased prevalence of psychiatric morbidity, especially the depression in the treatment-seeking obese population, reflect the participant's mental differences (45). Needless to say, the treatment-seeking participants see obesity as a condition that needs to be changed. This point of view comes from perceived body weight (46), body dissatisfaction (47), and weight bias internalization (48), which are strongly influenced by media exposure and negative beliefs about obesity in these communities (49). In contrast, since higher socioeconomic groups in developing countries are more likely to be obese, obesity sometimes is regarded as well-being and wealth (50). Besides, living in a collectivist society and receiving social support are protective elements against depression (41). Another point in Muslim countries, including Iran, could be hijab and clothing rules, which lessened the importance of body shape and, consequently, its adverse psychological effects (13).

The current study faced some strengths and potential limitations. To the best of our knowledge, this is the first study to examine the synergic effects of weight and metabolic status on depression, anxiety, and stress among a large population of Tehranian adults. The current study compared the relationships between obesity phenotypes and emotional states in men and women. Nevertheless, due to the limitation of the cross-sectional design of the study, the causal relationship could not be established. Also, it was impracticable to adjust all the confounders due to the complicated essence of emotional distress so that the unmeasured variables could affect our findings. Besides, these results can only be generalized to the Tehranian urban population.

In conclusion, compared to MHNO individuals, MUO women and all dysmetabolic men reported higher levels of anxiety and stress. However, none of obesity phenotypes were not associated with depression. These valuable results on psychological effects of different obesity phenotypes would be valuable to recognize more realistic burden of the mentioned disorders and help devise new strategies to promote general health in the societies.

Ethics approval and consent to participate: This study was approved by the ethics committee of the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences. All the participants signed the written informed consent before data collection.

Consent for publication: Not applicable

Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests" in this section.

Funding: Not applicable

Authors' contributions:

Conceptualization: Parisa Amiri, Fahimeh Mehrabi

Data curation: Parisa Amiri, Fahimeh Mehrabi, Leila Cheraghi.

Formal analysis: Leila Cheraghi.

Funding acquisition: Fereidoun Azizi.

Investigation: Fahimeh Mehrabi, Parisa Amiri

Methodology: Parisa Amiri, Fahimeh Mehrabi, Leila Cheraghi.

Project administration: Parisa Amiri, Fereidoun Azizi.

Supervision: Parisa Amiri, Fereidoun Azizi, Farhad Hosseinpanah.

Writing – original draft: Fahimeh Mehrabi, Parisa Amiri.

Writing – review & editing: Fahimeh Mehrabi, Parisa Amiri, Leila Cheraghi , Farhad Hosseinpanah, Fereidoun Azizi

Acknowledgements: Not applicable

Organization WH. Obesity and overweight fact sheet. 2016. Department of Sustainable Development and Healthy Environments Available from: http://wwwsearowhoint/entity/noncommunicable_diseases/media/non_communicable_diseases_obesity_fspdf accessed June10. 2018.
Rahmani A, Sayehmiri K, Asadollahi K, Sarokhani D, Islami F, Sarokhani M. Investigation of the prevalence of obesity in Iran: a systematic review and meta-analysis study. Acta Medica Iranica. 2015:596–607.
Apovian CM. Obesity: definition, comorbidities, causes, and burden. Am J Manag Care. 2016;22(7 Suppl):s176-85.
O'Neill S, O'Driscoll L. Metabolic syndrome: a closer look at the growing epidemic and its associated pathologies. Obesity reviews. 2015;16(1):1–12.
Pajunen P, Kotronen A, Korpi-Hyövälti E, Keinänen-Kiukaanniemi S, Oksa H, Niskanen L, et al. Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey. BMC Public Health. 2011;11(1):754.
Penninx BW, Lange SM. Metabolic syndrome in psychiatric patients: overview, mechanisms, and implications. Dialog Clin Neurosci. 2018;20(1):63.
Baxter A, Vos T, Scott K, Ferrari A, Whiteford H. The global burden of anxiety disorders in 2010. Psychological medicine. 2014;44(11):2363–74.
Malhotra N, Kulhara P, Chakrabarti S, Grover S. Lifestyle related factors & impact of metabolic syndrome on quality of life, level of functioning & self-esteem in patients with bipolar disorder & schizophrenia. Indian J Med Res. 2016;143(4):434.
Valizadeh R, Sarokhani D, Sarokhani M, Sayehmiri K, Ostovar R, Angh P, et al. A study of prevalence of anxiety in Iran: Systematic review and meta-analysis. Der Pharma Chemica. 2016.
Rajan T, Menon V. Psychiatric disorders and obesity: a review of association studies. Journal of postgraduate medicine. 2017;63(3):182.
Amiri S, Behnezhad S. Obesity and anxiety symptoms: A systematic review and meta-analysis. neuropsychiatrie. 2019;33(2):72–89.
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. 2010;18(5):1033–8.
Askari J, Hassanbeigi A, Khosravi HM, Malek M, Hassanbeigi D, Pourmovahed Z, et al. The relationship between obesity and depression. Procedia-social behavioral sciences. 2013;84:796–800.
Zavala GA, Kolovos S, Chiarotto A, Bosmans JE, Campos-Ponce M, Rosado JL, et al. Association between obesity and depressive symptoms in Mexican population. Soc Psychiatry Psychiatr Epidemiol. 2018;53(6):639–46.
Rahmani J, Kord Varkaneh H, Dorosty A-R. The Relationship between General and Central Obesity with Anxiety among Iranian Young Men. Journal of Nutrition Food Security. 2018;3(1):4–12.
Minkwitz J, Scheipl F, Cartwright L, Campbell IC, Chittka T, Thormann J, et al. Why some obese people become depressed whilst others do not: exploring links between cognitive reactivity, depression and obesity. Psychology health medicine. 2019;24(3):362–73.
Takeuchi T, Nakao M, Nomura K, Yano E. Association of metabolic syndrome with depression and anxiety in Japanese men. Diabetes Metab. 2009;35(1):32–6.
Demirci H, Cinar Y, Bilgel N. Metabolic syndrome and depressive symptoms in a primary health care setting in Turkey. Klinik Psikofarmakoloji Bülteni-Bulletin of Clinical Psychopharmacology. 2011;21(1):49–57.
Gheshlagh RG, Parizad N, Sayehmiri K. The relationship between depression and metabolic syndrome: systematic review and meta-analysis study. Iranian Red Crescent Medical Journal. 2016;18(6).
Bagherniya M, Khayyatzadeh SS, Avan A, Safarian M, Nematy M, Ferns GA, et al. Metabolic syndrome and its components are related to psychological disorders: a population based study. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2017;11:S561-S6.
Tomiyama AJ. Stress and obesity. Ann Rev Psychol. 2019;70:703–18.
Tenk J, Mátrai P, Hegyi P, Rostás I, Garami A, Szabó I, et al. Perceived stress correlates with visceral obesity and lipid parameters of the metabolic syndrome: A systematic review and meta-analysis. Psychoneuroendocrinology. 2018;95:63–73.
Jokela M, Hamer M, Singh-Manoux A, Batty G, Kivimäki M. Association of metabolically healthy obesity with depressive symptoms: pooled analysis of eight studies. Molecular psychiatry. 2014;19(8):910–4.
Phillips CM, Perry IJ. Depressive symptoms, anxiety and well-being among metabolic health obese subtypes. Psychoneuroendocrinology. 2015;62:47–53.
Hinnouho G-M, Singh-Manoux A, Gueguen A, Matta J, Lemogne C, Goldberg M, et al. Metabolically healthy obesity and depressive symptoms: 16-year follow-up of the Gazel cohort study. PloS one. 2017;12(4):e0174678.
Slater N, Rowley C, Venables RH, White S, Frisher M. Evaluating associations between metabolic health, obesity and depressive symptoms: a prospective analysis of data from the English Longitudinal Study of Ageing (ELSA) with a 2–year follow–up. BMJ open. 2018;8(12).
Yosaee S, Djafarian K, Esteghamati A, Motevalian A, Shidfar F, Tehrani-Doost M, et al. Depressive symptoms among metabolically healthy and unhealthy overweight/obese individuals: a comparative study. Medical journal of the Islamic Republic of Iran. 2018;32:95.
Azizi F, Ghanbarian A, Momenan AA, Hadaegh F, Mirmiran P, Hedayati M, et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials. 2009;10(1):5.
Azizi F, Khalili D, Aghajani H, ESTEGHAMATI A, Hosseinpanah F, DELAVARI A, et al. Appropriate waist circumference cut-off points among Iranian adults: the first report of the Iranian National Committee of Obesity. 2010.
Azizi F, Hadaegh F, KHALILI D, Esteghamati A, HOSSEIN PF, Delavari A, et al. Appropriate definition of metabolic syndrome among Iranian adults: report of the Iranian National Committee of Obesity. 2010.
Momenan AA, Delshad M, Sarbazi N, REZAEI GN, Ghanbarian A, AZIZI F. Reliability and validity of the Modifiable Activity Questionnaire (MAQ) in an Iranian urban adult population. 2012.
Hadaegh F, Bozorgmanesh MR, Ghasemi A, Harati H, Saadat N, Azizi F. High prevalence of undiagnosed diabetes and abnormal glucose tolerance in the Iranian urban population: Tehran Lipid and Glucose Study. BMC Public Health. 2008;8(1):176.
Asghari A, Saed F, Dibajnia P. Psychometric properties of the Depression Anxiety Stress Scales-21 (DASS-21) in a non-clinical Iranian sample. Int J psychol. 2008;2(2):82–102.
Lovibond PF, Lovibond SH. The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behav Res Ther. 1995;33(3):335–43.
Boyd A, Van de Velde S, Vilagut G, De Graaf R, Florescu S, Alonso J, et al. Gender differences in mental disorders and suicidality in Europe: results from a large cross-sectional population-based study. J Affect Disord. 2015;173:245–54.
Li SH, Graham BM. Why are women so vulnerable to anxiety, trauma-related and stress-related disorders? The potential role of sex hormones. The Lancet Psychiatry. 2017;4(1):73–82.
Johnson DP, Whisman MA. Gender differences in rumination: A meta-analysis. Pers Indiv Differ. 2013;55(4):367–74.
Kuehner C. Why is depression more common among women than among men? The Lancet Psychiatry. 2017;4(2):146–58.
Küçük S. Being a woman in Turkey and in the Middle East. The Globalist. 2013.
Khan S, Khan RA. Chronic stress leads to anxiety and depression. Ann Psychiatry Ment Health. 2017;5(1):1091.
Chavira DA, Ponting C, Lewis-Fernández R. Cultural and Social Aspects of Anxiety Disorders. The American Psychiatric Association Publishing Textbook of Anxiety, Trauma, and OCD-Related Disorders. 2020:59.
Esfahani HS, Shajari P. Gender, education, family structure, and the allocation of labor in Iran. Middle East Development Journal. 2012;4(02):1250008.
Malmir H, Mirzababaei A, Moradi S, Rezaei S, Mirzaei K, Dadfarma A. Metabolically healthy status and BMI in relation to depression: A systematic review of observational studies. Diabetes & Metabolic Syndrome: Clinical Research & Reviews; 2019.
McCaffery JM, Doyle CY. 7 Gene × Environment Interaction in Obesity: The Contribution of Randomized Clinical Trials. Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes. 2016:117.
Vaidya V. Psychosocial aspects of obesity. Health and Treatment strategies in obesity. 27: Karger Publishers; 2006. p. 73–85.
Paulitsch RG, Demenech LM, Dumith SC. Association of depression and obesity is mediated by weight perception. Journal of health psychology. 2020:1359105319897778.
Richard A, Rohrmann S, Lohse T, Eichholzer M. Is body weight dissatisfaction a predictor of depression independent of body mass index, sex and age? Results of a cross-sectional study. BMC Public Health. 2016;16(1):863.
Durso LE, Latner JD, Ciao AC. Weight bias internalization in treatment-seeking overweight adults: Psychometric validation and associations with self-esteem, body image, and mood symptoms. Eat Behav. 2016;21:104–8.
Khaled SM, Shockley B, Qutteina Y, Kimmel L, Le KT. Testing Western Media Icons Influence on Arab Women’s Body Size and Shape Ideals: An Experimental Approach. Social Sciences. 2018;7(9):142.
Dinsa GD, Goryakin Y, Fumagalli E, Suhrcke M. Obesity and socioeconomic status in developing countries: a systematic review. Obesity reviews. 2012;13(11):1067–79.

Table 1. Distribution of participants’ characteristics in different obesity phenotypes (n=2469).

			Metabolically healthy		Metabolically unhealthy
	Variables	Total	Non-obese n=1133 (45.9)	Obese n=237 (9.6)	Non-obese n=583 (23.6)	Obese n=516 (20.9)	P-value
Men	Age (year)	46.2±15.9	41.36±15.8	48.5±12.9	54.1±15.2	40.9±11.6	<0.001
	Marital status n(%)						<0.001
	Single	233(20.1)	168(32.8)	16(18.6)	29(8.2)	20(9.8)
	Married	925(79.9)	344(67.2)	70(81.4)	326(91.8)	185(90.2)
	Level of education n(%)						<0.001
	Primary or illiterate	219(18.9)	62(12.1)	14(16.3)	101(28.5)	42(20.5)
	Secondary	481(41.5)	216(42.2)	34(39.5)	142(40.0)	89(43.4)
	Higher	458(39.6)	234(45.7)	38(44.2)	112(31.5)	74(36.1)
	Job status n(%)						<0.001
	Unemployed, but had other sources of income	212(18.3)	59(11.5)	4(4.7)	118(33.2)	31(15.1.8)
	Unemployed/housewife	89(7.7)	65(12.7)	4(4.7)	13(3.7)	7(3.4)
	Employed	857(74.0)	388(75.8)	78(90.7)	224(63.1)	167(81.5)
	Smoking status n(%)						0.21
	Smoker	498(43.0)	213(41.6)	33(38.4)	151(42.5)	101(49.3)
	Non-smoker	660(57.0)	299(58.4)	53(61.6)	204(57.5)	104(50.7)
	Level of Physical activity n(%)						0.02
	Low	451(38.9)	174(34.0)	36(41.9)	150(42.3)	91(44.4)
	Moderate or High	707(61.1)	338(66.0)	50(58.1)	205(57.7)	114(55.6)
Women	Age (year)	45.6±14.7	38.3±12.3	46.2±12.2	55.5±13.2	48.5±12.9	<0.001
	Marital status n(%)						<0.001
	Single	184(14.0)	148(23.8)	13(8.6)	12(5.3)	11(3.5)
	Divorced/Widowed	142(10.8)	28(4.5)	17(11.3)	39(17.1)	58(18.6)
	Married	985(75.1)	445(71.7)	121(80.1)	177(77.6)	242(77.8)
	Level of education n(%)						<0.001
	Primary or illiterate	372(28.4)	59(9.5)	50(33.1)	104(45.6)	159(51.1)
	Secondary	525(40.0)	273(44.0)	60(39.7)	84(36.8)	108(34.7)
	Higher	414(31.6)	289(46.5)	41(27.2)	40(17.5)	44(14.1)
	Job status n(%)						<0.001
	Unemployed, but had other sources of income	132(10.1)	26(4.2)	12(7.9)	42(18.4)	52(16.7)
	Unemployed/housewife	937(71.5)	431(69.4)	112(74.2)	153(67.1)	241(77.5)
	Employed	242(18.5)	164(26.4)	27(17.9)	33(14.5)	18(5.8)
	Smoking status n(%)						0.38
	Smoker	69(5.3)	38(6.1)	4(2.6)	11(4.8)	16(5.1)
	Non-smoker	1242(94.7)	583(93.9)	147(97.4)	217(95.2)	295(94.9)
	Level of Physical activity n(%)						0.71
	Low	383(29.2)	173(27.9)	44(29.1)	68(29.8)	98(31.5)
	Moderate or High	928(70.8)	448(72.1)	107(70.9)	160(70.2)	213(68.5)

Data are presented as mean ±SD and frequency (%).

Table 2. Sex-specific levels of depression, anxiety, and stress in different Obesity phenotypes (n=2469)

			Metabolically healthy		Metabolically unhealthy
	Variables	Total	Non-obese	Obese	Non-obese	Obese	P-value
Men	Depression						0.051
	Normal	925(79.9)	413(80.7)	66(76.7)	282(79.4)	164(80.0)
	Mild	89(7.7)	27(5.3)	8(9.3)	40(11.3)	14(6.8)
	Moderate	90(7.8)	43(8.4)	6(7.0)	24(6.8)	17(8.3)
	Severe	54(4.7)	29(5.7)	6(7.0)	9(2.5)	10(4.9)
	Anxiety						0.123
	Normal	810(69.9)	379(74.0)	61(70.9)	239(67.3)	131(63.9)
	Mild	106(9.2)	40(7.8)	6(7.0)	37(10.4)	23(11.2)
	Moderate	147(12.7)	58(11.3)	12(14.0)	52(14.6)	25(12.2)
	Severe	95(8.2)	35(6.8)	7(8.1)	27(7.6)	26(12.7)
	Stress						0.493
	Normal	774(66.8)	353(68.9)	54(62.8)	236(66.5)	131(63.9)
	Mild	129(11.1)	45(8.8)	13(15.1)	47(13.2)	24(11.7)
	Moderate	145(12.5)	65(12.7)	9(10.5)	40(11.3)	31(15.1)
	Severe	110(9.5)	49(9.6)	10(11.6)	32(9.0)	19(9.3)
Women	Depression						0.301
	Normal	911(69.5)	443(71.3)	103(68.2)	163(71.5)	202(65.0)
	Mild	142(10.8)	64(10.3)	21(13.9)	25(11.0)	32(10.3)
	Moderate	162(12.4)	72(11.6)	18(11.9)	28(12.3)	44(14.1)
	Severe	96(7.3)	42(6.8)	9(6.0)	12(5.3)	33(10.6)
	Anxiety						0.003
	Normal	732(55.8)	369(59.4)	86(57.0)	128(56.1)	149(47.9)
	Mild	113(8.6)	48(7.7)	13(8.6)	23(10.1)	29(9.3)
	Moderate	263(20.1)	128(20.6)	26(17.2)	48(21.1)	61(19.6)
	Severe	203(15.5)	76(12.2)	26(17.2)	29(12.7)	72(23.2)
	Stress						0.472
	Normal	741(56.5)	362(58.3)	79(52.3)	139(61.0)	161(51.8)
	Mild	167(12.7)	71(11.4)	25(16.6)	25(11.0)	46(14.8)
	Moderate	186(14.2)	87(14.0)	20(13.2)	30(13.2)	49(15.8)
	Severe	217(16.6)	101(16.3)	27(17.9)	34(14.9)	55(17.7)

Data are presented as frequency (%).

Table 3. Odds ratios and 95% confidence intervals for emotional states of different obesity phenotypes (n=2469)

			Depression		Anxiety		Stress
	Models	Status	OR(95%CI)	P-value	OR(95%CI)	P-value	OR(95%CI)	P-value
Men	Model 1*	MHNO	(Ref.)		(Ref.)		(Ref.)
		MUNO	1.01(0.72-1.40)	0.97	1.39(1.04-1.85)	0.03	1.08(0.82-1.43)	0.60
		MHO	1.22(0.71-2.10)	0.46	1.80(0.73-1.97)	0.48	1.26(0.79-1.99)	0.33
		MUO	1.08(0.73-1.61)	0.69	1.73(1.24-2.42)	<0.001	1.32(0.96-1.83)	0.09
	Model2	MHNO	(Ref.)		(Ref.)		(Ref.)
		MUNO	1.21(0.79-1.84)	0.31	1.61(1.17-2.22)	0.003	1.40(1.02-1.90)	0.04
		MHO	1.40(0.80-2.44)	0.24	1.22(0.74-2.04)	0.43	1.26(0.78-2.02)	0.34
		MUO	1.20(0.79-1.84)	0.39	1.78(1.25-2.54)	<0.001	1.34(0.95-1.90)	0.09
Women	Model 1	MHNO	(Ref.)		(Ref.)		(Ref.)
		MUNO	1.01(0.73-1.40)	0.95	1.14(0.86-1.52)	0.36	0.91(0.67-1.22)	0.51
		MHO	1.10(0.76-1.60)	0.60	1.15(0.82-1.62)	0.43	1.20(0.86-1.67)	0.28
		MUO	1.39(1.04-1.84)	0.02	1.65(1.27-2.13)	<0.001	1.21(0.94-1.57)	0.14
	Model 2	MHNO	(Ref.)		(Ref.)		(Ref.)
		MUNO	0.80(0.56-1.16)	0.24	1.16(0.84-1.61)	0.36	1.04(0.75-1.46)	0.80
		MHO	0.94(0.64-1.40)	0.77	1.13(0.80-1.61)	0.50	1.26(0.89-1.78)	0.20
		MUO	1.10(0.78-1.53)	0.60	1.73(1.28-2.34)	<0.001	1.45(1.07-1.96)	0.02

*Model 1: unadjusted. Model 2: Adjusted for age, marital status (ref=married), level of education (ref=higher), job status (ref=employed) and level of physical activity (ref=high).

Table 1-Appendix. Descriptive statistics of BMI and MetS components in men and women

Variables	Total n=2469	Men n=1158	Women n=1311	P-value**
BMI (Kg/m²)	27.79±4.85*	27.4±4.4	28.1±5.2	<0.001
Waist circumference (cm)	93.90±12.06	95.6±11.5	92.4±12.4	<0.001
FBS (mg/dl)	97.71±26.72	99.5±27.8	96.1±25.6	<0.001
2 hour blood sugar	108(91-131)	107(90-132.25)	109(93-130)	0.30
Total cholesterol (mg/dl)	186.21±39.21	183.9±38.5	188.2±39.7	0.023
HDL (mg/dl)	47.29±11.33	42.9±9.7	51.1±11.2	<0.001
TG (mg/dl)	122(86-173)	133.5(94-190)	112(80-157)	<0.001
SBP (mm Hg)	114.51±16.69	118.6±15.7	110.9±16.7	<0.001
DBP (mm Hg)	76±9.88	78.5±9.9	73.8±9.3	<0.001

*Mean±SD; BMI: Body mass index; FBS: fasting blood sugar; HDL: High-density lipoprotein; TG: Triglycerides; SBP: Systolic blood pressure; DBP: Diastolic blood pressure.

**P-value refers to the difference between males and females

Download PDF

Journal Publication

published 04 Mar, 2021

Read the published version in BMC Psychiatry →

Review #2 received at journal
26 Sep, 2020
Editorial decision: Major revision
26 Sep, 2020
Reviewer #2 agreed at journal
21 Sep, 2020
Review #1 received at journal
01 Sep, 2020
Reviewers invited by journal
12 Aug, 2020
Reviewer #1 agreed at journal
12 Aug, 2020
Editor assigned by journal
06 Aug, 2020
Submission checks completed at journal
05 Aug, 2020
Editor invited by journal
05 Aug, 2020
First submitted to journal
25 Jul, 2020

You are reading this older preprint version

Read the latest preprint version →

Emotional states of different obesity phenotypes: A sex-specific results in a west-Asian population

Status:

Journal Publication

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Results

Discussion

Conclusions

Declarations

References

Tables

Status:

Journal Publication

Version 1