Generalized Traditional Risk Factors of Being Overweight and Obesity among Ever Married Non-Pregnant Women in Bangladesh: An Application of Decision Tree Analysis

Authors

  • Mohammad Zahidul Islam Science Jatiya Kabi Kazi Nazrul Islam University

DOI:

https://doi.org/10.18034/ra.v6i2.331

Keywords:

Overweight, socio-demographic factors, decision tree approach, Bangladesh

Abstract

Background: As the prevalence of obesity increases, the co-existing underweight and increasing overweight has also become a public health problem in many developing countries like as Bangladesh. Therefore this study seeks to identify the major determinants factors of being overweight or obese.

Methods: This study used a cross-sectional analysis from the 2011 Bangladesh Demographic and Health Survey that include 2,740 maternal women. To assess the determinants factors of overweight and obese, a multivariate technique name as decision tree analysis was used in this study.

Results:  Around 68% of the maternal women were underweight and 32% were either overweight or obese. Women higher socio-economic status, women age ≥25 years, higher educational level and urban place of residence were found to be most dominant factors of being overweight and obese.

Conclusion: The findings suggest that, the major policy implications of this study are the importance of socio-economic status women, age ≥25 years with higher educational level and urban women to minimize its adverse effect on overweight and obese.

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Author Biography

  • Mohammad Zahidul Islam, Science Jatiya Kabi Kazi Nazrul Islam University

    Lecturer, Department of Population Science Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, Bangladesh

     

References

Kordas K, Centeno ZYF, Pachón H, Soto AZJ: Being overweight or obese is associated with lower prevalence of anemia among Colombian women of reproductive age. The Journal of nutrition 2013, 143(2):175-181.

Subramanian S, Perkins JM, Khan KT: Do burdens of underweight and overweight coexist among lower socioeconomic groups in India?The American journal of clinical nutrition 2009, 90(2):369-376.

Monteiro CA, Moura EC, Conde WL, Popkin BM: Socioeconomic status and obesity in adult populations of developing countries: a review. Bulletin of the World Health Organization 2004, 82(12):940-946.

Lee J, Houser RF, Must A, de Fulladolsa PP, Bermudez OI: Socioeconomic disparities and the familial coexistence of child stunting and maternal overweight in Guatemala. Economics & Human Biology 2012, 10(3):232-241.

Popkin BM: The nutrition transition in the developing world. Development Policy Review 2003, 21(5‐6):581-597.

Khan MN MM, Islam MR, MA A-M, M S: Trends in Body Mass Index and its Determinants among Ever-married Non-pregnant Women in Bangladesh. Mal J Nutr 2015, 21(2):191-205.

Khan M, Krämer A: Factors associated with being underweight, overweight and obese among ever-married non-pregnant urban women in Bangladesh. Singapore medical journal 2009, 50(8):804.

Corsi DJ, Finlay JE, Subramanian S: Weight of communities: A multilevel analysis of body mass index in 32,814 neighborhoods in 57 low-to middle-income countries (LMICs). Social Science & Medicine 2012, 75(2):311-322.

Hou X, Jia W, Bao Y, Lu H, Jiang S, Zuo Y, Gu H, Xiang K: Risk factors for overweight and obesity, and changes in body mass index of Chinese adults in Shanghai. BMC Public Health 2008, 8(1):389.

Fleischer NL, Roux AVD, Alazraqui M, Spinelli H: Social patterning of chronic disease risk factors in a Latin American city. Journal of Urban Health 2008, 85(6):923-937.

Parra DC, Lobelo F, Gómez LF, Rutt C, Schmid T, Brownson RC, Pratt M: Household motor vehicle use and weight status among Colombian adults: are we driving our way towards obesity?Preventive medicine 2009, 49(2):179-183.

Wen LM, Rissel C: Inverse associations between cycling to work, public transport, and overweight and obesity: findings from a population based study in Australia. Preventive medicine 2008, 46(1):29-32.

Bowman SA: PEER REVIEWED: Television-Viewing Characteristics of Adults: Correlations to Eating Practices and Overweight and Health Status. Preventing chronic disease 2006, 3(2).

Hu FB, Li TY, Colditz GA, Willett WC, Manson JE: Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women. Jama 2003, 289(14):1785-1791.

Fernald LC: Socio-economic status and body mass index in low-income Mexican adults. Social science & medicine 2007, 64(10):2030-2042.

Jacoby E, Goldstein J, López A, Núñez E, López T: Social class, family, and life-style factors associated with overweight and obesity among adults in Peruvian cities. Preventive medicine 2003, 37(5):396-405.

Bernabe‐Ortiz A, Gilman RH, Smeeth L, Miranda JJ: Migration Surrogates and Their Association With Obesity Among Within‐Country Migrants. Obesity 2010, 18(11):2199-2203.

Marshall RJ: The use of classification and regression trees in clinical epidemiology. Journal of clinical epidemiology 2001, 54(6):603-609.

Viikki K, Juhola M, Pyykkö I, Honkavaara P: Evaluating training data suitability for decision tree induction. Journal of medical systems 2001, 25(2):133-144.

Gandomi AH, Fridline MM, Roke DA: Decision tree approach for soil liquefaction assessment. The Scientific World Journal 2013, 2013.

Chevalier P, Cadi F, Scridon A, Girerd N, Bejan-Angoulvan T, Morel E, Hot IJ, Di Filippe S, Ganne C, Colin C: Prophylactic Radiofrequency Ablation in Asymptomatic Wolff-Parkinson-White Patients Is Not Yet a Good Strategy: A Decision Analysis. Circulation: Arrhythmia and Electrophysiology 2013:CIRCEP. 112.970459.

Rutstein S, Johnson K, Gwatkin D: Poverty, health inequality, and its health and demographic effects. In: Annual Meeting of the Population Association of America, Los Angeles, California: 2000; 2000.

Research NIoP, Training, Mitra, Associates, Demographic MIIfRD, Surveys H: Bangladesh Demographic and Health Survey: National Institute of Population Research and Training (NIPORT); 2011.

Rutstein S: Wealth versus expenditure: Comparison between the DHS wealth index and household expenditures in four departments of Guatemala. Calverton, Maryland: ORC Macro 1999.

Popkin BM: The nutrition transition and obesity in the developing world. The Journal of nutrition 2001, 131(3):871S-873S.

Abbas M, Paracha PI, Khan S, Iqbal Z, Iqbal M: socio-demographic and dietary determinants of overweight and obesity in male pakistani adults. European Scientific Journal 2013, 9(33).

Acharya B, Chauhan HS, Thapa SB, Kaphle HP, Malla D: Prevalence and socio-demographic factors associated with overweight and obesity among adolescents in Kaski district, Nepal. Indian Journal of Community Health 2014, 26(6):118-122.

Zienczuk N, Egeland GM: Association between socioeconomic status and overweight and obesity among Inuit adults: International Polar Year Inuit Health Survey, 2007–2008. International journal of circumpolar health 2012, 71.

Cohen AK, Rai M, Rehkopf DH, Abrams B: Educational attainment and obesity: a systematic review. Obesity Reviews 2013, 14(12):989-1005.

Krieger N, Williams DR, Moss NE: Measuring social class in US public health research: concepts, methodologies, and guidelines. Annual review of public health 1997, 18(1):341-378.

Chandola T, Clarke P, Morris J, Blane D: Pathways between education and health: a causal modelling approach. Journal of the Royal Statistical Society: Series A (Statistics in Society) 2006, 169(2):337-359.

Schnittker J: Education and the changing shape of the income gradient in health. Journal of Health and Social Behavior 2004, 45(3):286-305.

Al Nsour M, Al Kayyali G, Naffa S: Overweight and obesity among Jordanian women and their social determinants. EMHJ 2013, 19(12).

Batterham PJ, Christensen H, Mackinnon AJ: Modifiable risk factors predicting major depressive disorder at four year follow-up: a decision tree approach. BMC psychiatry 2009, 9(1):75.

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Published

31-08-2018

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Section

Research Paper

How to Cite

Islam, M. Z. (2018). Generalized Traditional Risk Factors of Being Overweight and Obesity among Ever Married Non-Pregnant Women in Bangladesh: An Application of Decision Tree Analysis. ABC Research Alert, 6(2), Bangladesh. https://doi.org/10.18034/ra.v6i2.331

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