• Overview
  • Obesity prevalence
  • Trends over time
  • Population breakdowns
  • Drivers
  • Comorbidities
  • Health systems
  • Actions
Loading data – please wait …

Obesity prevalence

Women, 2014

Survey type:Measured
Age:15-49
Sample size:23495
Area covered:National
References:Demographic Health Survey Peru 2014
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, 2013

Survey type:Measured
Age:15-49
Sample size:21700
Area covered:National
References:DHS Peru 2013
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Women, 2012

Survey type:Measured
Age:15-49
Sample size:22866
Area covered:National
References:Demographic Health Survey Peru 2012
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Women, 2007-2008

Survey type:Measured
Age:15-49
Sample size:20192
Area covered:National
References:DHS 2007 - 2008
Notes:Other married women 15 to 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, 2000

Survey type:Measured
Age:15-49
Sample size:8372
References:Demographic Health Survey, Peru 2000
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Adults, 1998-2000

Survey type:Measured
Age:18-59
Sample size:2337
Area covered:National
References:Jacoby E, Goldstein J, Lopez A, Nunez E and Lopez T. (2003). Social class, family and life-style factors associated with overweight and obesity among adults in Peruvian cities. Reventative Medicine, 37: 396 - 405.
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Women, 1992

Survey type:Measured
Age:15-49
Sample size:5200
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, 2013-2014

Survey type:Measured
Age:5-13
Sample size:2801
Area covered:National
References:Carolina Tarqui-Mamani, Doris Alvarez-Dongo, Paula Espinoza-Oriundo. Prevalence and factors associated with overweight and obesity in Peruvian primary school children. Rev. salud pública 20 (2) Mar-Apr 2018 ¬ï https://doi.org/10.15446/rsap.V20n2.68082
Notes:WHO Cut off Used
Cutoffs:WHO

Children, 2010

Survey type:Self-reported
Age:13-15
References:Global School-based Student Health Survey (GSHS), available at https://www.cdc.gov/gshs/countries/index.htm (last accessed 28.04.20)
Notes:WHO cutoffs.
Cutoffs:WHO

Children, 2009

Survey type:Measured
Age:7-8
Sample size:1737
Area covered:National
References:Preston EC, Ariana P, Penny ME, Frost M, Plugge E. Prevalence of childhood overweight and obesity and associated factors in Peru. Rev Panam Salud Publica. 2015;38(6):472-8
Notes:Prevalence of overweight and obesity by Maternal Education. Prevalence of overweight and obesity was assessed using body mass index-for age Z-scores. The 2007 World Health Organization (WHO) international growth reference curves for children 5–19 years of age described by De Onis were used to compare children of the same age and gender. “Overweight” and “Obese” variables were defined as BMI-for-age Z-scores of ≥ 1 and ≥ 2, respectively.
Cutoffs:WHO

Children, 2002

Survey type:Measured
Age:7-8
Sample size:710
References:Carrillo-Larco RM, Miranda JJ, Bernabe-Ortiz A. Wealth index and risk of childhood overweight and obesity: evidence from four prospective cohorts in Peru and Vietnam. Int J Public Health, 2015 Nov 24.
Notes:IOTF Cut-off
Cutoffs:IOTF

Overweight/obesity by education

Women, 2014

Survey type:Measured
Age:15-49
Sample size:23497
Area covered:National
References:Demographic Health Survey 2014
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, 2008

Survey type:Measured
Age:15-49
Sample size:22151
Area covered:National
References:Poterico JA, Stanojevic S, Ruiz P, Bernabe-Ortiz A, Miranda JJ. The Association between Socioeconomic Status and Obesity in Peruvian Women. Obesity (Silver Spring, Md). 2012;20(11):2283-2289. doi:10.1038/oby.2011.288.
Notes:Education level, based on the number of years of education attained, was categorized separately into quartiles for rural and urban areas, and merged into a single variable.
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Children, 2013-2014

Survey type:Measured
Age:5-13
Sample size:2801
Area covered:National
References:Carolina Tarqui-Mamani, Doris Alvarez-Dongo, Paula Espinoza-Oriundo. Prevalence and factors associated with overweight and obesity in Peruvian primary school children. Rev. salud pública 20 (2) Mar-Apr 2018 ¬ï https://doi.org/10.15446/rsap.V20n2.68082
Notes:WHO Cut Off Points Used Education based on Parental educational status
Cutoffs:WHO

Children, 2009

Survey type:Measured
Age:7-8
Sample size:1737
Area covered:National
References:Preston EC, Ariana P, Penny ME, Frost M, Plugge E. Prevalence of childhood overweight and obesity and associated factors in Peru. Rev Panam Salud Publica. 2015;38(6):472-8
Notes:Prevalence of overweight and obesity by Maternal Education. Prevalence of overweight and obesity was assessed using body mass index-for age Z-scores. The 2007 World Health Organization (WHO) international growth reference curves for children 5–19 years of age described by De Onis were used to compare children of the same age and gender. “Overweight” and “Obese” variables were defined as BMI-for-age Z-scores of ≥ 1 and ≥ 2, respectively.
Cutoffs:WHO

Overweight/obesity by age

Women, 2014

Survey type:Measured
Sample size:23497
Area covered:National
References:Demographic Health Survey 2014
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, 2013-2014

Survey type:Measured
Sample size:2801
Area covered:National
References:Carolina Tarqui-Mamani, Doris Alvarez-Dongo, Paula Espinoza-Oriundo. Prevalence and factors associated with overweight and obesity in Peruvian primary school children. Rev. salud pública 20 (2) Mar-Apr 2018 ¬ï https://doi.org/10.15446/rsap.V20n2.68082
Notes:WHO Cut Off Points Used
Cutoffs:WHO

Overweight/obesity by region

Women, 2014

Survey type:Measured
Age:15-49
Sample size:23497
Area covered:National
References:Demographic Health Survey 2014
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:23497
Area covered:National
References:Demographic Health Survey 2014
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, 2008

Survey type:Measured
Age:15-49
Sample size:22151
Area covered:National
References:Poterico JA, Stanojevic S, Ruiz P, Bernabe-Ortiz A, Miranda JJ. The Association between Socioeconomic Status and Obesity in Peruvian Women. Obesity (Silver Spring, Md). 2012;20(11):2283-2289. doi:10.1038/oby.2011.288.
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Children, 2013-2014

Survey type:Measured
Age:5-13
Sample size:2801
Area covered:National
References:Carolina Tarqui-Mamani, Doris Alvarez-Dongo, Paula Espinoza-Oriundo. Prevalence and factors associated with overweight and obesity in Peruvian primary school children. Rev. salud pública 20 (2) Mar-Apr 2018 ¬ï https://doi.org/10.15446/rsap.V20n2.68082
Notes:WHO Cut Off Points Used
Cutoffs:WHO

Children, 2009

Survey type:Measured
Age:7-8
Sample size:1737
Area covered:National
References:Preston EC, Ariana P, Penny ME, Frost M, Plugge E. Prevalence of childhood overweight and obesity and associated factors in Peru. Rev Panam Salud Publica. 2015;38(6):472-8
Notes:Prevalence of overweight and obesity by Maternal Education. Prevalence of overweight and obesity was assessed using body mass index-for age Z-scores. The 2007 World Health Organization (WHO) international growth reference curves for children 5–19 years of age described by De Onis were used to compare children of the same age and gender. “Overweight” and “Obese” variables were defined as BMI-for-age Z-scores of ≥ 1 and ≥ 2, respectively.
Cutoffs:WHO

Overweight/obesity by socio-economic group

Women, 2014

Survey type:Measured
Age:15-49
Sample size:23497
Area covered:National
References:Demographic Health Survey 2014
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, 2008

Survey type:Measured
Age:15-49
Sample size:22151
Area covered:National
References:Poterico JA, Stanojevic S, Ruiz P, Bernabe-Ortiz A, Miranda JJ. The Association between Socioeconomic Status and Obesity in Peruvian Women. Obesity (Silver Spring, Md). 2012;20(11):2283-2289. doi:10.1038/oby.2011.288.
Notes:The possession assets index variable was constructed by the INEI using factor analysis. This variable was subsequently categorized into quartiles separately for rural and urban areas, and then combined into a single variable.
Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m².

Children, 2013-2014

Survey type:Measured
Age:5-13
Sample size:2801
Area covered:National
References:Carolina Tarqui-Mamani, Doris Alvarez-Dongo, Paula Espinoza-Oriundo. Prevalence and factors associated with overweight and obesity in Peruvian primary school children. Rev. salud pública 20 (2) Mar-Apr 2018 ¬ï https://doi.org/10.15446/rsap.V20n2.68082
Notes:WHO Cut Off Points Used
Cutoffs:WHO

Children, 2009

Survey type:Measured
Age:7-8
Sample size:1737
Area covered:National
References:Preston EC, Ariana P, Penny ME, Frost M, Plugge E. Prevalence of childhood overweight and obesity and associated factors in Peru. Rev Panam Salud Publica. 2015;38(6):472-8
Notes:Prevalence of overweight and obesity by Maternal Education. Prevalence of overweight and obesity was assessed using body mass index-for age Z-scores. The 2007 World Health Organization (WHO) international growth reference curves for children 5–19 years of age described by De Onis were used to compare children of the same age and gender. “Overweight” and “Obese” variables were defined as BMI-for-age Z-scores of ≥ 1 and ≥ 2, respectively.
Cutoffs:WHO

Insufficient physical activity

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, 2009-2015

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, 2009-2015

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, 2009-2015

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, 2009-2015

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, 2014-2019

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, 2014-2019

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: Upper Middle Income

Health systems summary

Peru’s health system is decentralised and complex, with healthcare provided by 5 separate entities (4 of which are public). Most of the population (60%) is served by the Ministry of Health (MINSA), but other providers include EsSalud (30%), the Armed Forces, the National Police and the private sector. MINSA provides the bulk of primary healthcare services and is mostly funded with tax revenues MINSA is free for the most vulnerable Peruvian citizens. EsSalud is a form of social insurance for workers where both the employers and employees contribute. In 2009, a universal health insurance law passed that made coverage by health insurance mandatory. As a result, those covered by MINSA’s scheme has been expanded to cover more Peruvians, and now 87% of the population have some form of insurance. Universal health coverage is expected to be reached by 2021.

One of the greatest challenges faced by the Peruvian health system is the persistent urban-rural disparities in access to healthcare services and professionals. The highly fragmented system results in an inefficient use of resources.

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
In practice, how is obesity treatment largely funded?Out of pocket
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?Not known
Are there any obesity-specific recommendations or guidelines published for children?Yes

Perceived barriers to treatment

  • Lack of financial investment and lack of funding for coverage
  • Poor health literacy and behaviour
  • Social determinants of health
  • Lack of training
  • Lack of treatment facilities
  • Fragmented and/or failing health system
  • Lack of multi-disciplinary teams
  • Lack of evidence, monitoring and research
  • Poor availability of pharmaceutical treatments

Summary of stakeholder feedback

There is limited government action around obesity, and it is not yet considered to be a disease. Stakeholders highlighted that there is notable inaction around prevention, with little economic and workforce resources dedicated to this. An exception to this is the recent introduction of front of package labelling.

Obesity is not considered to be a disease among healthcare providers either. Obesity treatment is only offered when comorbidities are present and/or the obesity is severe. When obesity treatment is provided, it is generally paid for out of pocket at great expense to the individual. Multi-disciplinary care is said to be rare. Those living in rural areas have great difficulty accessing the health system in general, and rarely receive obesity treatment as infectious diseases are a greater priority. People tend to leave the health system because of long waiting lists, a lack of obesity specialists to provide treatment and a failure to recognise that obesity needs to be treated.

There are inadequate numbers of obesity professionals in both urban and rural areas and there is limited to no specialist obesity training. Where there is training it seems to be only available for professionals such as endocrinologists, nutritionists and surgeons and it is general obesity training, not specialist.

Based on interviews/survey returns from 4 stakeholders

Last updated: June 2020

Download this information as a PDF

Actions

We are currently finalising our data for this section. It will be available from late 2020.

Loading