Bangladesh
- Overview
- Obesity prevalence
- Trends over time
- Population breakdowns
- Drivers
- Comorbidities
- Health systems
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National obesity risk *7/10This is a composite ‘obesity risk’ score (out of 10, the highest risk) based on obesity prevalence, rate of increase, likelihood of meeting the 2025 target, treatment indicator and childhood stunting levels.Childhood obesity risk *3/11This is a ‘risk score’ for each country’s likelihood of having or acquiring a major childhood obesity problem during the 2020s, taking account of current prevalence levels and risk for future obesity (based on stunting among infants, maternal obesity, maternal smoking, and breastfeeding rates).
* Based on estimated data. For more information see Publications
Obesity prevalence
Trends over time
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The report card collates all the most-recent graphics for this country. If you would like to produce a custom report based on selected graphics, just tap the Add to custom PDF button below the graphics you would like to use.Population breakdowns
Drivers
Insufficient activity
Soft drink consumption
Fruit consumption
Vegetable consumption
Fast food consumption
Processed meat consumption
Grains consumption
Depression
Anxiety
Roots of obesity »
Like all chronic diseases, the root causes/drivers of obesity are complex. Select here to view 'other' root causes/drivers.Comorbidities
Health systems
Obesity prevalence
Adults, 2018
| Survey type: | Measured |
| Age: | 18-69 |
| Sample size: | 7985 |
| Area covered: | National |
| References: | National STEPS Survey for Non-communicable Diseases Risk Factors in Bangladesh 2018. National Institute of Preventive and Social Medicine (NIPSOM) Mohakhali, Dhaka1212 Available at https://extranet.who.int/ncdsmicrodata/index.php/catalog/770 (last accessed 05.10.200) |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 2017-2018
| Survey type: | Measured |
| Sample size: | 23861 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Notes: | 18328 (ever-married) women, 5533 Men. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 16478 |
| Area covered: | National |
| References: | Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm (last accessed 11th April 2016) |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 2011
| Survey type: | Measured |
| Sample size: | 17416 |
| Area covered: | National |
| References: | DHS 2011 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2007
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 10021 |
| Area covered: | National |
| References: | Demographics Health Survey 2007. |
| Notes: | Other married women 15 - 49 years. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 1995-1996
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 3997 |
| References: | Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Children, 2018-2019
| Survey type: | Measured |
| Age: | 10-19 |
| Sample size: | 9772 |
| Area covered: | National |
| References: | Urmy, N.J., Hossain, M.M., Shamim, A.A., Khan, M.S.A., Hanif, A.A.M., Hasan, M., Akter, F., Mitra, D.K., Hossaine, M., Ullah, M.A. and Sarker, S.K., 2020. Noncommunicable Disease Risk Factors Among Adolescent Boys and Girls in Bangladesh: Evidence From a National Survey. Osong Public Health and Research Perspectives, 11(6), pp.351-364. |
| Notes: | 4,907 boys and 4,865 girls NB. Combined child data estimated. These estimates were calculated by weighting male and female survey results. Weighting based on World Bank Population % total female 2019 (https://data.worldbank.org/indicator/SP.POP.TOTL.FE.ZS - accessed 21.10.20)' |
| Cutoffs: | WHO |
Children, 2014
| Survey type: | Self-reported |
| Age: | 13-17 |
| Sample size: | 2989 |
| Area covered: | National |
| References: | Global School-based Student Health Survey (GSHS), available at https://www.who.int/ncds/surveillance/gshs/2014-Bangladesh-fact-sheet.pdf?ua=1 (last accessed 24.11.20) |
| Notes: | WHO cutoffs. |
| Cutoffs: | WHO |
Children, 2009
| Survey type: | Measured |
| Age: | 6-15 |
| Sample size: | 10135 |
| Area covered: | National |
| References: | Bulbul T and Hoque M. 2014. Prevalence of childhood obesity and overweight in Bangladesh: findings from a countrywide epidemiological study. BMC Pediatr. 1;14:86. |
| Notes: | Z score BMI cut-offs used |
| Cutoffs: | WHO |
% Adults living with obesity in Bangladesh 1995-2017
| Survey type: | Measured |
| References: | 1995: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 2007: Demographics Health Survey 2007. 2011: DHS 2011 2014: Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm (last accessed 11th April 2016) 2017: National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
| Different methodologies may have been used to collect this data and so data from different surveys may not be strictly comparable. Please check with original data sources for methodologies used. | |
% Adults living with overweight or obesity in Bangladesh 1995-2017
| Survey type: | Measured |
| References: | 1995: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 2007: Demographics Health Survey 2007. 2011: DHS 2011 2014: Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm (last accessed 11th April 2016) 2017: National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
| Different methodologies may have been used to collect this data and so data from different surveys may not be strictly comparable. Please check with original data sources for methodologies used. | |
% Adults living with obesity in selected countries in the Asia/Oceania Region 1975-2019
Men
| References: | 1976, 1981, 1986: Yoshiike N, Seino F, Tajima S, Arai Y, Kawano M, Furuhata T, Inoue S. Twenty-year changes in the prevalence of overweight in Japanese adults: The National Nutrition Survey 1976-95. Obesity Reviews 2002;3:183-190 1993: Solon FS. Nutrition related chronic diseases in the Philippines. Makati city, Philippines: Nutrition Center of the Philippines Report Series, vol 2, No.1, cited in Reference 53 1995, 1996: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 1998: Data provided by the Philippean Depatment of Health, Dr C. Barbu, data reanalysed by Dr Charmaine Duante. 2000: Asia Pacific Cohort Studies Collaboration. The burden of overweight and obesity in the Asia-Pacific region. Obesity Reviews 2007;8:191-196. 2001: SCN (2004). 5th Report on the World Nutrition Situation. Nutrition for Improved Development Outcomes. Appendix 11 2002: Report of the 2002 China National Nutrition and Health Survey. 2004. (In Chinese). Chinese Ministry of Public Health (CMPH). 2003: http://www.fnri.dost.gov.ph/files/fnri%20files/nns/factsandfigures2003/anthropometric.pdf (last accessed June 14th 2011) 2004: Tonga STEPS Survey 2004 2005, 2013: Chang HC, Yang HC, Chang HY, et al. Morbid obesity in Taiwan: Prevalence, trends, associated social demographics, and lifestyle factors. PLoS One. 2017;12(2):e0169577. Published 2017 Feb 2. doi:10.1371/journal.pone.0169577 2006: Gerritsen S, Stefanogiannis N, Galloway Y, Devlin M, Templaton R and Yeh L. A portrait of health: key results of the 2006/07 New Zealand Health Survey. 2007: Mohamud WN, Musa KI, Khir AS, Ismail AA, Ismail IS, Kadir KA, Kamaruddin NA, Yaacob NA, Mustafa N, Ali O, Isa SH, Bebakar WM.Prevalence of overweight and obesity among adult Malaysians: an update. Asia Pac J Clin Nutr. 2011;20(1):35-41. 2009: Yan, S., Li, J., Li, S., Zhang, B., Du, S., Gordon-Larsen, P., Adair, L. and Popkin, B. (2012), The expanding burden of cardiometabolic risk in China: the China Health and Nutrition Survey. Obesity Reviews. doi: 10.1111/j.1467-789X.2012.01016.x 2011, 2012: New Zealand Health Survey. https://www.health.govt.nz/publication/annual-update-key-results-2018-19-new-zealand-health-survey (last accessed 14.07.20) 2014: New Zealand Health Survey 2014/15. https://www.health.govt.nz/publication/annual-update-key-results-2014-15-new-zealand-health-survey (last accessed 16.12.2015) 2015: 2015 Philippine Anthropometric Survey. http://enutrition.fnri.dost.gov.ph/site/preview.php?xx=%20uploads/2015_ANTHROPOMETRIC_SURVEY.pdf 2016: Ministry of Health. 2018. Annual Data Explorer 2017/18: New Zealand Health Survey [Data File]. URL: https://minhealthnz.shinyapps.io/nz-health-survey-2017-18-annual-data-explorer/(last accessed 14th December 2017) 2017: Tonga STEPS Survey 2017 https://extranet.who.int/ncdsmicrodata/index.php/catalog/713 (Last accessed 13.10.20) 2018: New Zealand Health Survey 2018-19. New Zealand Ministry of Health (https://minhealthnz.shinyapps.io/nz-health-survey-2018-19-annual-data-explorer/_w_b396d161/#!/key-indicators accessed 14.11.19) |
| Different methodologies may have been used to collect this data and so data from different surveys may not be strictly comparable. Please check with original data sources for methodologies used. | |
Women
| References: | 1976, 1981, 1986: Yoshiike N, Seino F, Tajima S, Arai Y, Kawano M, Furuhata T, Inoue S. Twenty-year changes in the prevalence of overweight in Japanese adults: The National Nutrition Survey 1976-95. Obesity Reviews 2002;3:183-190 1993: Solon FS. Nutrition related chronic diseases in the Philippines. Makati city, Philippines: Nutrition Center of the Philippines Report Series, vol 2, No.1, cited in Reference 53 1995, 1996: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 1998: Data provided by the Philippean Depatment of Health, Dr C. Barbu, data reanalysed by Dr Charmaine Duante. 2000: Asia Pacific Cohort Studies Collaboration. The burden of overweight and obesity in the Asia-Pacific region. Obesity Reviews 2007;8:191-196. 2001: SCN (2004). 5th Report on the World Nutrition Situation. Nutrition for Improved Development Outcomes. Appendix 11 2002: Report of the 2002 China National Nutrition and Health Survey. 2004. (In Chinese). Chinese Ministry of Public Health (CMPH). 2003: http://www.fnri.dost.gov.ph/files/fnri%20files/nns/factsandfigures2003/anthropometric.pdf (last accessed June 14th 2011) 2004: Tonga STEPS Survey 2004 2005, 2013: Chang HC, Yang HC, Chang HY, et al. Morbid obesity in Taiwan: Prevalence, trends, associated social demographics, and lifestyle factors. PLoS One. 2017;12(2):e0169577. Published 2017 Feb 2. doi:10.1371/journal.pone.0169577 2006: Gerritsen S, Stefanogiannis N, Galloway Y, Devlin M, Templaton R and Yeh L. A portrait of health: key results of the 2006/07 New Zealand Health Survey. 2007: Mohamud WN, Musa KI, Khir AS, Ismail AA, Ismail IS, Kadir KA, Kamaruddin NA, Yaacob NA, Mustafa N, Ali O, Isa SH, Bebakar WM.Prevalence of overweight and obesity among adult Malaysians: an update. Asia Pac J Clin Nutr. 2011;20(1):35-41. 2009: Yan, S., Li, J., Li, S., Zhang, B., Du, S., Gordon-Larsen, P., Adair, L. and Popkin, B. (2012), The expanding burden of cardiometabolic risk in China: the China Health and Nutrition Survey. Obesity Reviews. doi: 10.1111/j.1467-789X.2012.01016.x 2011, 2012: New Zealand Health Survey. https://www.health.govt.nz/publication/annual-update-key-results-2018-19-new-zealand-health-survey (last accessed 14.07.20) 2014: New Zealand Health Survey 2014/15. https://www.health.govt.nz/publication/annual-update-key-results-2014-15-new-zealand-health-survey (last accessed 16.12.2015) 2015: 2015 Philippine Anthropometric Survey. http://enutrition.fnri.dost.gov.ph/site/preview.php?xx=%20uploads/2015_ANTHROPOMETRIC_SURVEY.pdf 2016: Ministry of Health. 2018. Annual Data Explorer 2017/18: New Zealand Health Survey [Data File]. URL: https://minhealthnz.shinyapps.io/nz-health-survey-2017-18-annual-data-explorer/(last accessed 14th December 2017) 2017: Tonga STEPS Survey 2017 https://extranet.who.int/ncdsmicrodata/index.php/catalog/713 (Last accessed 13.10.20) 2018: New Zealand Health Survey 2018-19. New Zealand Ministry of Health (https://minhealthnz.shinyapps.io/nz-health-survey-2018-19-annual-data-explorer/_w_b396d161/#!/key-indicators accessed 14.11.19) |
| Different methodologies may have been used to collect this data and so data from different surveys may not be strictly comparable. Please check with original data sources for methodologies used. | |
Overweight/obesity by education
Adults, 2018
| Survey type: | Measured |
| Age: | 18-69 |
| Sample size: | 7985 |
| Area covered: | National |
| References: | National STEPS Survey for Non-communicable Diseases Risk Factors in Bangladesh 2018. National Institute of Preventive and Social Medicine (NIPSOM) Mohakhali, Dhaka1212 Available at https://extranet.who.int/ncdsmicrodata/index.php/catalog/770 (last accessed 05.10.20) |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2017-2018
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 18328 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Notes: | Ever-married women. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Men, 2017-2018
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 5533 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 16478 |
| Area covered: | National |
| References: | Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Overweight/obesity by age
Adults, 2018
| Survey type: | Measured |
| Sample size: | 7985 |
| Area covered: | National |
| References: | National STEPS Survey for Non-communicable Diseases Risk Factors in Bangladesh 2018. National Institute of Preventive and Social Medicine (NIPSOM) Mohakhali, Dhaka1212 Available at https://extranet.who.int/ncdsmicrodata/index.php/catalog/770 (last accessed 05.10.200) |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2017-2018
| Survey type: | Measured |
| Sample size: | 18328 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Notes: | Ever-married women. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Men, 2017-2018
| Survey type: | Measured |
| Sample size: | 5533 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Sample size: | 16478 |
| Area covered: | National |
| References: | Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Children, 2018-2019
| Survey type: | Measured |
| Sample size: | 9772 |
| Area covered: | National |
| References: | Urmy, N.J., Hossain, M.M., Shamim, A.A., Khan, M.S.A., Hanif, A.A.M., Hasan, M., Akter, F., Mitra, D.K., Hossaine, M., Ullah, M.A. and Sarker, S.K., 2020. Noncommunicable Disease Risk Factors Among Adolescent Boys and Girls in Bangladesh: Evidence From a National Survey. Osong Public Health and Research Perspectives, 11(6), pp.351-364. |
| Notes: | 4,907 boys and 4,865 girls |
| Cutoffs: | WHO |
Overweight/obesity by region
Adults, 2018
| Survey type: | Measured |
| Age: | 18-69 |
| Sample size: | 7985 |
| Area covered: | National |
| References: | National STEPS Survey for Non-communicable Diseases Risk Factors in Bangladesh 2018. National Institute of Preventive and Social Medicine (NIPSOM) Mohakhali, Dhaka1212 Available at https://extranet.who.int/ncdsmicrodata/index.php/catalog/770 (last accessed 05.10.20) |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2017-2018
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 18328 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Notes: | Ever-married women. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Men, 2017-2018
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 5533 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 16478 |
| Area covered: | National |
| References: | Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 16478 |
| Area covered: | National |
| References: | Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Boys, 2018-2019
| Survey type: | Measured |
| Age: | 10-19 |
| Sample size: | 9772 |
| Area covered: | National |
| References: | Urmy, N.J., Hossain, M.M., Shamim, A.A., Khan, M.S.A., Hanif, A.A.M., Hasan, M., Akter, F., Mitra, D.K., Hossaine, M., Ullah, M.A. and Sarker, S.K., 2020. Noncommunicable Disease Risk Factors Among Adolescent Boys and Girls in Bangladesh: Evidence From a National Survey. Osong Public Health and Research Perspectives, 11(6), pp.351-364. |
| Notes: | 4,907 boys and 4,865 girls |
| Cutoffs: | WHO |
Girls, 2018-2019
| Survey type: | Measured |
| Age: | 10-19 |
| Sample size: | 9772 |
| Area covered: | National |
| References: | Urmy, N.J., Hossain, M.M., Shamim, A.A., Khan, M.S.A., Hanif, A.A.M., Hasan, M., Akter, F., Mitra, D.K., Hossaine, M., Ullah, M.A. and Sarker, S.K., 2020. Noncommunicable Disease Risk Factors Among Adolescent Boys and Girls in Bangladesh: Evidence From a National Survey. Osong Public Health and Research Perspectives, 11(6), pp.351-364. |
| Notes: | 4,907 boys and 4,865 girls |
| Cutoffs: | WHO |
Boys, 2009
| Survey type: | Measured |
| Age: | 6-15 |
| Sample size: | 10135 |
| Area covered: | National |
| References: | Bulbul T and Hoque M. 2014. Prevalence of childhood obesity and overweight in Bangladesh: findings from a countrywide epidemiological study. BMC Pediatr. 1;14:86. |
| Notes: | Z score cut-offs used |
| Cutoffs: | Other |
Girls, 2009
| Survey type: | Measured |
| Age: | 6-15 |
| Sample size: | 10135 |
| Area covered: | National |
| References: | Bulbul T and Hoque M. 2014. Prevalence of childhood obesity and overweight in Bangladesh: findings from a countrywide epidemiological study. BMC Pediatr. 1;14:86. |
| Notes: | Z score cut-offs used |
| Cutoffs: | Other |
Overweight/obesity by socio-economic group
Adults, 2018
| Survey type: | Measured |
| Age: | 18-69 |
| Sample size: | 7985 |
| Area covered: | National |
| References: | National STEPS Survey for Non-communicable Diseases Risk Factors in Bangladesh 2018. National Institute of Preventive and Social Medicine (NIPSOM) Mohakhali, Dhaka1212 Available at https://extranet.who.int/ncdsmicrodata/index.php/catalog/770 (last accessed 05.10.20) |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2017-2018
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 18328 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Notes: | Ever-married women. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Men, 2017-2018
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 5533 |
| Area covered: | National |
| References: | National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 2014
| Survey type: | Measured |
| Age: | 15-49 |
| Sample size: | 16478 |
| Area covered: | National |
| References: | Demographic Health Survey Bangladesh 2014. http://www.dhsprogram.com/publications/publication-FR311-DHS-Final-Reports.cfm |
| Notes: | Demographic Health Survey data includes ever married women aged 15-49 years only and may include males aged 15-59. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Boys, 2018-2019
| Survey type: | Measured |
| Age: | 10-19 |
| Sample size: | 9772 |
| Area covered: | National |
| References: | Urmy, N.J., Hossain, M.M., Shamim, A.A., Khan, M.S.A., Hanif, A.A.M., Hasan, M., Akter, F., Mitra, D.K., Hossaine, M., Ullah, M.A. and Sarker, S.K., 2020. Noncommunicable Disease Risk Factors Among Adolescent Boys and Girls in Bangladesh: Evidence From a National Survey. Osong Public Health and Research Perspectives, 11(6), pp.351-364. |
| Notes: | 4,907 boys and 4,865 girls |
| Cutoffs: | WHO |
Girls, 2018-2019
| Survey type: | Measured |
| Age: | 10-19 |
| Sample size: | 9772 |
| Area covered: | National |
| References: | Urmy, N.J., Hossain, M.M., Shamim, A.A., Khan, M.S.A., Hanif, A.A.M., Hasan, M., Akter, F., Mitra, D.K., Hossaine, M., Ullah, M.A. and Sarker, S.K., 2020. Noncommunicable Disease Risk Factors Among Adolescent Boys and Girls in Bangladesh: Evidence From a National Survey. Osong Public Health and Research Perspectives, 11(6), pp.351-364. |
| Notes: | 4,907 boys and 4,865 girls |
| Cutoffs: | WHO |
Insufficient physical activity
Adults, 2016
| References: | Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet 2018 http://dx.doi.org/10.1016/S2214-109X(18)30357-7 |
Men, 2016
| References: | Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet 2018 http://dx.doi.org/10.1016/S2214-109X(18)30357-7 |
Women, 2016
| References: | Guthold R, Stevens GA, Riley LM, Bull FC. Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants. Lancet 2018 http://dx.doi.org/10.1016/S2214-109X(18)30357-7 |
Children, 2016
| Survey type: | Self-reported |
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, https://apps.who.int/gho/data/node.main.A893ADO?lang=en (last accessed 16.03.21) |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Boys, 2016
| Survey type: | Self-reported |
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, https://apps.who.int/gho/data/node.main.A893ADO?lang=en (last accessed 16.03.21) |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Girls, 2016
| Survey type: | Self-reported |
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, https://apps.who.int/gho/data/node.main.A893ADO?lang=en (last accessed 16.03.21) |
| Notes: | % of school going adolescents not meeting WHO recommendations on Physical Activity for Health, i.e. doing less than 60 minutes of moderate- to vigorous-intensity physical activity daily. |
| Definitions: | % Adolescents insufficiently active (age standardised estimate) |
Average daily frequency of carbonated soft drink consumption
Children, 2014-2015
| Survey type: | Measured |
| Age: | 12-17 |
| References: | Beal et al. (2019). Global Patterns of Adolescent Fruit, Vegetable, Carbonated Soft Drink, and Fast-food consumption: A meta-analysis of global school-based student health surveys. Food and Nutrition Bulletin. https://doi.org/10.1177/0379572119848287 sourced from Food Systems Dashboard http://www.foodsystemsdashboard.org/food-system |
Estimated per capita fruit intake
Adults, 2017
| Survey type: | Measured |
| Age: | 25+ |
| References: | Global Burden of Disease, the Institute for Health Metrics and Evaluation http://ghdx.healthdata.org/ |
| Definitions: | Estimated per-capita fruit intake (g/day) |
Prevalence of less than daily fruit consumption
Children, 2008-2015
| Survey type: | Measured |
| Age: | 12-17 |
| References: | Global School-based Student Health Surveys. Beal et al (2019). Global Patterns of Adolescent Fruit, Vegetable, Carbonated Soft Drink, and Fast-food consumption: A meta-analysis of global school-based student health surveys. Food and Nutrition Bulletin. https://doi.org/10.1177/0379572119848287. Sourced from Food Systems Dashboard http://www.foodsystemsdashboard.org/food-system |
| Definitions: | Prevalence of less-than-daily fruit consumption (% less-than-daily fruit consumption) |
Prevalence of less than daily vegetable consumption
Children, 2008-2015
| Survey type: | Measured |
| Age: | 12-17 |
| References: | Beal et al. (2019). Global Patterns of Adolescent Fruit, Vegetable, Carbonated Soft Drink, and Fast-food consumption: A meta-analysis of global school-based student health surveys. Food and Nutrition Bulletin. https://doi.org/10.1177/0379572119848287 sourced from Food Systems Dashboard http://www.foodsystemsdashboard.org/food-system |
| Definitions: | Prevalence of less-than-daily vegetable consumption (% less-than-daily vegetable consumption) |
Average weekly frequency of fast food consumption
Children, 2014-2015
| Age: | 12-17 |
| References: | Beal et al. (2019). Global Patterns of Adolescent Fruit, Vegetable, Carbonated Soft Drink, and Fast-food consumption: A meta-analysis of global school-based student health surveys. Food and Nutrition Bulletin. https://doi.org/10.1177/0379572119848287 sourced from Food Systems Dashboard http://www.foodsystemsdashboard.org/food-system |
Estimated per-capita processed meat intake
Adults, 2017
| Survey type: | Measured |
| Age: | 25+ |
| References: | Global Burden of Disease, the Institute for Health Metrics and Evaluation http://ghdx.healthdata.org/ |
| Definitions: | Estimated per-capita processed meat intake (g per day) |
Estimated per capita whole grains intake
Adults, 2017
| Survey type: | Measured |
| Age: | 25+ |
| References: | Global Burden of Disease, the Institute for Health Metrics and Evaluation http://ghdx.healthdata.org/ |
| Definitions: | Estimated per-capita whole grains intake (g/day) |
Mental health - depression disorders
Adults, 2015
| References: | Prevalence data from Global Burden of Disease study 2015 (http://ghdx.healthdata.org) published in: Depression and Other Common Mental Disorders: Global Health Estimates. Geneva:World Health Organization; 2017. Licence: CC BY-NC-SA 3.0 IGO. |
| Definitions: | % of population with depression disorders |
Mental health - anxiety disorders
Adults, 2015
| References: | Prevalence data from Global Burden of Disease study 2015 (http://ghdx.healthdata.org) published in: Depression and Other Common Mental Disorders: Global Health Estimates. Geneva:World Health Organization; 2017. Licence: CC BY-NC-SA 3.0 IGO. |
| Definitions: | % of population with anxiety disorders |
Oesophageal cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, oesophagus, adults ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, oesophagus, adults ages 20+. ASR (World) per 100,000 |
Breast cancer
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, breast, females, ages 20+. ASR (World) per 100,000 |
Colorectal cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, colorectum, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, colorectum, adults, ages 20+. ASR (World) per 100,000 |
Pancreatic cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, pancreas, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, pancreas, adults, ages 20+. ASR (World) per 100,000 |
Gallbladder cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, gallbladder, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, gallbladder, adults, ages 20+. ASR (World) per 100,000 |
Kidney cancer
Men, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, kidney, adults, ages 20+. ASR (World) per 100,000 |
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, kidney, adults, ages 20+. ASR (World) per 100,000 |
Cancer of the uterus
Women, 2018
| Age: | 20+ |
| References: | Global Cancer Observatory, Cancer incidence rates http://gco.iarc.fr/ (last accessed 30th June 2020) |
| Definitions: | Estimated age-standardized incidence rates (World) in 2018, cervix uteri, females, ages 20+. ASR (World) per 100,000 |
Raised blood pressure
Adults, 2015
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A875?lang=en |
| Definitions: | Age Standardised estimated % Raised blood pressure 2015 (SBP>=140 OR DBP>=90). |
Men, 2015
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A875?lang=en |
| Definitions: | Age Standardised estimated % Raised blood pressure 2015 (SBP>=140 OR DBP>=90). |
Women, 2015
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A875?lang=en |
| Definitions: | Age Standardised estimated % Raised blood pressure 2015 (SBP>=140 OR DBP>=90). |
Raised cholesterol
Adults, 2008
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A885 |
| Definitions: | % Raised total cholesterol (>= 5.0 mmol/L) (age-standardized estimate). |
Men, 2008
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A885 |
| Definitions: | % Raised total cholesterol (>= 5.0 mmol/L) (age-standardized estimate). |
Women, 2008
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A885 |
| Definitions: | % Raised total cholesterol (>= 5.0 mmol/L) (age-standardized estimate). |
Raised fasting blood glucose
Men, 2014
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A869?lang=en |
| Definitions: | Age Standardised % raised fasting blood glucose (>= 7.0 mmol/L or on medication). |
Women, 2014
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A869?lang=en |
| Definitions: | Age Standardised % raised fasting blood glucose (>= 7.0 mmol/L or on medication). |
Diabetes prevalence
Adults, 2017
| References: | Reproduced with kind permission of IDF, International Diabetes Federation. IDF Diabetes Atlas, 8th edition. Brussels, Belgium: International Diabetes Federation, 2017. http://www.diabetesatlas.org |
| Definitions: | Diabetes age-adjusted comparative prevalence (%). |
Health systems
Economic classification: Lower Middle Income
Health systems summary
Healthcare in Bangladesh is pluralistic, delivered by 4 providers: the government, non-governmental organisations, the private sector and donor agencies. Although care in the public sector is technically available to all Bangladeshi citizens and highly subsidised by the government, the quality of care is considered to be poor, a consequence of insufficient funding and governance. As a result, the private sector (made up of formal, traditional services and informal, less traditional services) has thrived, benefitting from limited regulation. Private care in Bangladesh is expensive, and so unaffordable for much of the population. Out of pocket payments are estimated to make up 63.3% of total health expenditure, with government expenditure making up just 26%. Insurance (social or private) is uncommon in Bangladesh.
The Bangladeshi health system is challenged by an insufficient health workforce, its inadequate public system, the high number of informal providers in rural areas, lack of effective risk-pooling and low financial investment. At the same time, Bangladesh is experiencing the double burden of communicable and non-communicable diseases and great demographic changes.
Indicators
| Where is the country’s government in the journey towards defining ‘Obesity as a disease’? | Some progress |
| Where is the country’s healthcare provider in the journey towards defining ‘Obesity as a disease’? | No |
| Is there specialist training available dedicated to the training of health professionals to prevent, diagnose, treat and manage obesity? | No |
| Have any taxes or subsidies been put in place to protect/assist/inform the population around obesity? | Yes |
| Are there adequate numbers of trained health professionals in specialties relevant to obesity in urban areas? | No |
| Are there adequate numbers of trained health professionals in specialties relevant to obesity in rural areas? | No |
| Are there any obesity-specific recommendations or guidelines published for adults? | No |
| Are there any obesity-specific recommendations or guidelines published for children? | Some progress |
| In practice, how is obesity treatment largely funded? | Out of pocket |
Summary of stakeholder feedback
Neither the government nor healthcare providers in Bangladesh are considered to act as if obesity is a disease. As obesity is not considered a disease by healthcare providers and patients, the stakeholder reported that people only enter the health system when they have a comorbidity related to obesity. Even then, they receive no treatment for their obesity unless they go private. This is because there is no funded obesity treatment within the public sector, leaving all obesity care to be provided by the private sector. There is said to be several private clinics and dietary care services available, but these are mostly situated in urban areas and so not accessible to those living in rural regions. When treatment is provided it is said to be as ‘beauty management’ rather than because obesity is a disease.
While there is an NCD strategy (that is accompanied by an implementation guide), it noted that there is no focus in it on obesity. There is also no obesity treatment guidelines or recommendations, or training for obesity specialists. This is despite recent research showing that obesity and its related diseases are increasing in Bangladesh. There is also a growing concern about childhood obesity.
Based on interviews/survey returns from 1 stakeholder
Last updated: June 2020
