Relationship between depression, stress and anxiety with anthropometric indices using Bio-Impedance Measure, among overweight/obese and normal subjects
Subject Areas :
Maryam Moussavi
1
,
Majid Karandish
2
,
Ariyo Movahedi
3
,
Behnood Abbasi
4
1 - Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Nutrition and Metabolic Diseases Research Centre, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
3 - Department of Nutrition, Science and Research Branch, Islamic Azad University, Tehran, Iran
4 - Department of Nutrition, Electronic Health and Statistics Surveillance Research Center, Science and Research Branch. Islamic Azad University, Tehran, Iran
Received: 2019-11-04
Accepted : 2020-02-25
Published : 2020-03-15
Keywords:
Obesity,
depression,
Stress,
anxiety,
Overweight,
Anthropometric indices,
Abstract :
Bioelectrical impedance analysis (BIA) is a simple, inexpensive, quick, and non-invasive technique for measuring body composition and its analysis is used as an alternative to examine muscle mass and body fat percentage Obesity and depression are two major public health problems among adolescents. Both obesity and depression are very prevalent and associated with numerous health complications, including hypertension, coronary heart disease, diabetes, and increased mortality. The present study was a cross-sectional study on 157 adult females and males from student and staff of Science and Research Branch of Islamic Azad University (SRBIAU) of Tehran that classified in two groups of normal weight and overweight or obese. The proportion of body tissues was determined according to the resistance created. The weight of the subjects was measured and recorded using BIA. Using the DASS-21 Questionnaire for Depression, Anxiety and Stress Based on the present findings, anthropometric indices such as weight, skeletal muscle mass, body mass index, waist to hip ratio, visceral fat level, whole-body water (L), body fat mass (kg), basal metabolic ratio (kcal), degree of obesity (%) ), fat percentage analysis (%), muscle weight analysis (kg), muscle percentage analysis were significantly different between the two groups (P <0.0001) and were higher in obese or overweight groups than the normal one. There were no significant differences in anxiety (p=0.496), stress (p=0.407), and mental health score (p=0.251) in both groups. Whereas, depression was significantly higher in the overweight or obese group (p=0.012). There was no meaningful relationship between BMI and stress (CC=0.04, P=0.612), anxiety (CC=0.052, P=0.519), whereas the positive correlation between BMI and depression (CC=0.932, P=0.035) was significant. There was a direct relationship between obesity and depression, anxiety, and stress. BMI correlates positively with mental health parameters.
References:
Walter-Kroker A, Kroker A, Mattiucci-Guehlke M, Glaab T. A practical guide to bioelectrical impedance analysis using the example of chronic obstructive pulmonary disease. Nutrition Journal. 2011;10,35.
No authors listed. Bioelectrical impedance analysis in body composition measurement. proceedings of a national institutes of health technology assessment conference. The American Journal of Clinical Nutrition. 1996;64(3 Suppl):387S-532S.
Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis - Part I: Review of principles and methods. Clinical Nutrition. 2004;23(5):1226–43.
WHO. Obesity and overweight. World Health Organization: Obesity and overweight. Available at: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.
Gómez-Hernández A, Beneit N, Díaz-Castroverde S, Escribano Ó. Differential role of adipose tissues in obesity and related metabolic and vascular complications. International Journal of Endocrinology. Hindawi Limited; 2016; Article ID 1216783.
Bastard JP, Maachi M, Lagathu C, Kim MJ, Caron M, Vidal H, et al. Recent advances in the relationship between obesity, inflammation, and insulin resistance. Vol. 17, European Cytokine Network. 2006, 4–12.
Pereira-Miranda E, Costa PRF, Queiroz VAO, Pereira-Santos M, Santana MLP. Overweight and Obesity Associated with Higher Depression Prevalence in Adults: A Systematic Review and Meta-Analysis. Vol. 36, Journal of the American College of Nutrition. Routledge; 2017, 223–33.
Luppino FS, De Wit LM, Bouvy PF, Stijnen T, Cuijpers P, Penninx BWJH, et al. Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry. 2010; 67,220–9.
Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJL, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLOS Medicine. 2013;10(11).
WHO. Depression. World Health Organization. 2020. Available at: https://www.who.int/news-room/fact-sheets/detail/depression.
WHO. Mental health action plan 2013-2020. 2020. Available at: https://www.who.int/mental_health/publications/action_plan/en.
Marina Marcus, M. Taghi Yasamy M, Van O. Depression: A Global Crisis. WHO Department of Mental Health and Substance Abuse. Available at: https://www.who.int/mental_health/management/depression/who_paper_depression_wfmh_2012.pdf.
Regier DA, Kuhl EA, Kupfer DJ. The DSM-5: Classification and criteria changes. World Psychiatry. 2013;12(2):92–8.
Melnyk BM, Small L, Morrison-Beedy D, Strasser A, Spath L, Kreipe R, et al. Mental health correlates of healthy lifestyle attitudes, beliefs, choices, and behaviors in overweight adolescents. Journal of Pediatric Health Care. 2006;20(6):401–6.
Osman A, Wong JL, Bagge CL, Freedenthal S, Gutierrez PM, Lozano G. The Depression Anxiety Stress Scales-21 (DASS-21): Further examination of dimensions, scale reliability, and correlates. Journal of Clinical Psychology. 2012;68(12):1322–38.
Murphy JM, Horton NJ, Burke JD, Monson RR, Laird NM, Lesage A, et al. Obesity and weight gain in relation to depression: Findings from the Stirling County Study. International Journal of Obesity. 2009;33(3):335–41.
Katon WJ. Epidemiology and treatment of depression in patients with chronic medical illness. Dialogues in Clinical Neuroscience. 2011;13(1):7–24.