Malaysia
- Overview
- Obesity prevalence
- Trends over time
- Population breakdowns
- Drivers
- Comorbidities
- Health systems
- Policies
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National obesity risk *8/10This 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 *7.5/11This 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.Breastfeeding
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Comorbidities
Health systems
Obesity prevalence
Adults, 2019
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 14965 |
| Area covered: | National |
| References: | NHMS 2019. Institute for Public Health (IKU) available at http://www.iku.gov.my/nhms-2019 (last accessed 17.09.20) |
| Notes: | Sample size includes approx 5000 children |
| Definitions: | Standard definitions. Malaysian Clinical Practice Guideline of Obesity (2004) cut offs are also available on MOH website |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 2015
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 29460 |
| Area covered: | National |
| References: | Institute for Public Health (IPH) 2015. National Health and Morbidity Survey 2015 (NHMS 2015). Vol. II: Non-Communicable Diseases, Risk Factors & Other Health Problems; 2015. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 2007-2008
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 4428 |
| Area covered: | National |
| References: | 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. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 2006
| Survey type: | Measured |
| Age: | 18+ |
| Sample size: | 33464 |
| Area covered: | National |
| References: | Khambalia AZ, Seen LS. Trends in overweight and obese adults in Malaysia (1996-2009): a systematic review. Obesity Reviews 2010; 11:403-412 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 1996
| Survey type: | Self-reported |
| Age: | 18+ |
| Sample size: | 30165 |
| References: | Ismail MN, Chee SS, Nawawi H, Yusoff K, Lim TO and James WPT. (2002). Obesity in Malaysia. Onesity Reviews, 3: 203 - 208. |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Adults, 1993-1994
| Survey type: | Measured |
| Age: | 18-64 |
| Sample size: | 4747 |
| References: | Ismail MN, Zawaih H, Chee SS, Ng KK. Prevalence of obesity and chronic energy deficiency (CED) in adult Malaysians. Malays J Nutrition. 1995; 1:1-9 |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Children, 2019
| Survey type: | Measured |
| Age: | 5-17 |
| Sample size: | ~ 3500 |
| Area covered: | National |
| References: | NHMS 2019. Institute for Public Health (IKU) available at http://www.iku.gov.my/nhms-2019 (last accessed 17.09.20) |
| Definitions: | WHO |
| Cutoffs: | WHO |
Children, 2012
| Survey type: | Self-reported |
| Age: | 13-17 |
| Sample size: | 25507 |
| Area covered: | National |
| References: | Global School-based Student Health Survey (GSHS), available at https://www.who.int/ncds/surveillance/gshs/Malaysia_2012_GSHS_FS_national.pdf?ua=1 (last accessed 14.12.20) |
| Notes: | WHO cutoffs. |
| Cutoffs: | WHO |
Children, 2006
| Survey type: | Measured |
| Age: | 7-12 |
| Sample size: | 7749 |
| Area covered: | National |
| References: | Third National Health and Morbidity Survey (NHMS III, 2006) published in Naidu BM, Mahmud SZ, Ambak R et al. Overweight among primary school-age children in Malaysia. Asia Pac J Clin Nutr 2013;22 (3):408-415 |
| Notes: | IOTF International Cut Off Used for Overweight and obesity |
| Cutoffs: | IOTF |
% Adults living with obesity, 1993-2015
| Survey type: | Measured |
| References: | 1993: Ismail MN, Zawaih H, Chee SS, Ng KK. Prevalence of obesity and chronic energy deficiency (CED) in adult Malaysians. Malays J Nutrition. 1995; 1:1-9 2006: Khambalia AZ, Seen LS. Trends in overweight and obese adults in Malaysia (1996-2009): a systematic review. Obesity Reviews 2010; 11:403-412 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. 2015: Institute for Public Health (IPH) 2015. National Health and Morbidity Survey 2015 (NHMS 2015). Vol. II: Non-Communicable Diseases, Risk Factors & Other Health Problems; 2015. |
| 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, 1993-2015
| Survey type: | Measured |
| References: | 1993: Ismail MN, Zawaih H, Chee SS, Ng KK. Prevalence of obesity and chronic energy deficiency (CED) in adult Malaysians. Malays J Nutrition. 1995; 1:1-9 2006: Khambalia AZ, Seen LS. Trends in overweight and obese adults in Malaysia (1996-2009): a systematic review. Obesity Reviews 2010; 11:403-412 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. 2015: Institute for Public Health (IPH) 2015. National Health and Morbidity Survey 2015 (NHMS 2015). Vol. II: Non-Communicable Diseases, Risk Factors & Other Health Problems; 2015. |
| 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, selected countries, 1976-2019
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
Children, 2006
| Survey type: | Measured |
| Age: | 7-12 |
| Sample size: | 7749 |
| Area covered: | National |
| References: | Third National Health and Morbidity Survey (NHMS III, 2006) published in Naidu BM, Mahmud SZ, Ambak R et al. Overweight among primary school-age children in Malaysia. Asia Pac J Clin Nutr 2013;22 (3):408-415 |
| Notes: | IOTF International Cut Off |
| Cutoffs: | IOTF |
Overweight/obesity by age
Children, 2012
| Survey type: | Self-reported |
| Sample size: | 25,507 |
| Area covered: | National |
| References: | Global School-Based Student Health Survey Factsheet Malaysia 2012. Available at: https://cdn.who.int/media/docs/default-source/ncds/ncd-surveillance/data-reporting/malaysia/gshs/malaysia-2012-gshs-fs-national.pdf?sfvrsn=56e59de7_3&download=true. Accessed 05.10.21. |
Overweight/obesity by region
Children, 2006
| Survey type: | Measured |
| Age: | 7-12 |
| Sample size: | 7749 |
| Area covered: | National |
| References: | Third National Health and Morbidity Survey (NHMS III, 2006) published in Naidu BM, Mahmud SZ, Ambak R et al. Overweight among primary school-age children in Malaysia. Asia Pac J Clin Nutr 2013;22 (3):408-415 |
| Notes: | IOTF International Cut Off |
| Cutoffs: | IOTF |
Overweight/obesity by socio-economic group
Children, 2006
| Survey type: | Measured |
| Age: | 7-12 |
| Sample size: | 7749 |
| Area covered: | National |
| References: | Third National Health and Morbidity Survey (NHMS III, 2006) published in Naidu BM, Mahmud SZ, Ambak R et al. Overweight among primary school-age children in Malaysia. Asia Pac J Clin Nutr 2013;22 (3):408-415 |
| Notes: | IOTF International Cut Off Parental Income (RM) |
| Cutoffs: | IOTF |
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) |
Children, 2010
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A893?lang=en |
| 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, 2010
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A893?lang=en |
| 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, 2010
| Age: | 11-17 |
| References: | Global Health Observatory data repository, World Health Organisation, http://apps.who.int/gho/data/node.main.A893?lang=en |
| 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, 2010-2015
| 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, 2010-2015
| 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, 2010-2015
| 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, 2010-2015
| 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 |
% Infants exclusively breastfed 0-5 months
Children, 2004-2020
| Area covered: | National |
| References: | Malaysia National Health and Morbidity Survey 2016 |
| Notes: | See UNICEF website for further survey information. Available at : https://data.unicef.org/resources/dataset/infant-young-child-feeding/ (last accessed 28.9.21) Citation: United Nations Children’s Fund, Division of Data, Analysis, Planning and Monitoring (2021). Global UNICEF Global Databases: Infant and Young Child Feeding: Exclusive breastfeeding, New York, September 2021. |
| Definitions: | % exclusively breastfed 0-5 months |
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, 2019
| Age: | 20-79 |
| References: | Reproduced with kind permission International Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels,Belgium: 2019. Available at: https://www.diabetesatlas.org |
| Definitions: | Diabetes age-adjusted comparative 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: Upper Middle Income
Health systems summary
Malaysia has a two-tier health system that is made up of a tax-funded public sector and a coexisting private sector. The public sector, which is led and funded primarily by the Malaysian government is available to all legal residents of Malaysia. Despite covering the bulk of the population, the public system is underserved by doctors and specialists compared to the private sector. The private sector, on the other hand, has thrived in recent years. Private care is mostly paid for with private health insurance and fee-for-service, out of pocket payments. The relatively high use of private care means that out of pocket expenditure is relatively high, making up approximately 34.5% of health financing in 2015.
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’? | Some progress |
| 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? | Some progress |
| 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? | Some progress |
| Are there any obesity-specific recommendations or guidelines published for children? | Some progress |
| In practice, how is obesity treatment largely funded? | Not known |
Summary of stakeholder feedback
There is reportedly no consensus on whether obesity is a disease in Malaysia, with differing views among clinicians and the general public. The government appears to have engaged in a few awareness campaigns but overall, there is much more to be done on obesity prevention.
Extent of treatment coverage and the availability of obesity treatment varies between the public and private sector. In the public sector, pharmacotherapy is covered as long as it was listed in the Ministry of Health Medicines Formulary, but it was noted that it currently contained few options for obesity. Bariatric surgery is partially covered but there is limited availability and treatment requires nominal out of pocket contributions to complement the government funding. Coverage in the private sector on the other hand was said to be dependent on clinical indication and type of insurance coverage. Behavioural modification, which was reported to be the most common type of treatment in Malaysia, is covered in both the public and private sector.
Stakeholders appreciated that Malaysia does have clinical practice guidelines for the management of obesity but noted that there was a disconnect between the guidelines and what happens in practice. It was said that people tended to enter primary care via community screening and if comorbidities are present, the person is referred onto hospital or tertiary care. One stakeholder raised concerns however that most do not enter the system and try out “fads” instead.
It was noted that there is no specialist obesity training in Malaysia, and so there are inadequate numbers of suitably qualified professionals to treat obesity in both urban and rural areas.
Based on interviews/survey returns from 5 stakeholders
Last updated: June 2020
