Peru
- Overview
- Obesity prevalence
- Trends over time
- Population breakdowns
- Drivers
- Comorbidities
- Health systems
- Policies
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National obesity risk *7.5/10This 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 *7/11This 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
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. | |
Adults, 2012-2013
| Survey type: | Measured |
| Age: | 20+ |
| Sample size: | 20535 |
| Area covered: | National |
| References: | Pajuelo, Jaime & Torres, Harold & Rebatta, Fernando & Zamora, Rosa. (2019). Obesidad no morbida y morbida del adulto en el Perú, 1975 - 2013. Anales de la Facultad de Medicina. 80. 317-21. 10.15381/anales.803.16851. |
| Notes: | NB. Combined adult 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)' |
| 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. |
| Notes: | NB. Combined adult 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 19.10.20)' |
| Unless otherwise noted, overweight refers to a BMI between 25kg and 29.9kg/m², obesity refers to a BMI greater than 30kg/m². | |
Women, 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 |
| Sample size: | 2882 |
| Area covered: | National |
| References: | Global School-based Student Health Survey (GSHS), available at https://www.who.int/ncds/surveillance/gshs/2010_GSHS_FS_Peru.pdf?ua=1 (last accessed 25.11.20) |
| 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 |
% Adults living with obesity, 1992-2014
| Survey type: | Measured |
| References: | 1992: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 2000: Demographic Health Survey, Peru 2000 2007: DHS 2007 - 2008 2013: DHS Peru 2013 2014: Demographic Health Survey Peru 2014 |
| 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, 1992-2014
| Survey type: | Measured |
| References: | 1992: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 2000: Demographic Health Survey, Peru 2000 2007: DHS 2007 - 2008 2013: DHS Peru 2013 2014: Demographic Health Survey Peru 2014 |
| 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, 1960-2020
Men
| References: | 1960, 1971, 1973, 1976, 1991: Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: prevalence and trends, 1960-1994. International Journal of Obesity (1998);22:39-47 1975: Monteiro CA, Conde WL, Popking BM. Is obesity replacing or adding to undernutrition? Evidence from different social classes in Brazil. 2002. Public Health Nutrition:51(1A), 105-112 1988: Berrios X, Jadue I, Zenteno J, Ross MI, Rodriguez H. Prevalencia de factores de riesgo para enfermedades cronicas. Estudio de la poblacion general de la region Metropolitana, 1986-1987. Rev. Med. Chile. 1990;118:597-604 1992, 1994, 1995: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 1997: Filozof C, Gonzales C, Sereday M, Mazza C, Braguinsky J. Obesity prevalence and trends in Latin American countries. Obesity Reviews, 2001;2:99-196 1998: http://www.unscn.org/layout/modules/resources/files/rwns5.pdf; MEAN BMI Data DHS Survey 1999: Centres for Disease Control and Prevention. http://www.cdc.gov/ 2000: Demographic Health Survey, Peru 2000 2001: Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of Overweight and Obesity in the United States, 1999-2004. JAMA 2006;295(13):1549-1555 2002: Monteiro CA, Conde WL and Popkin BA. (2007). Income-specific trends in obesity in Brazil: 1975 - 2003. American Journal of Public Health, 97 (10): 1808 - 1812. 2003: 2003 ENS Report. Final results on the National Health Survey. Http://epi.minsal.cl/epi/html/invest/ENS/informeFinalENS.pdf. 2005: Demographic Health Survey 2006. 2006: Olaiz-Fernández G, Rivera-Dommarco J, Shamah-Levy T, Rojas R, Villalpando-Hernández S, Hernández-Avila M, Sepúlveda-Amor J. Encuesta Nacional de Salud y Nutrición 2006. Cuernavaca, México: Instituto Nacional de Salud Pública, 2006. (National Health and Nutrition Survey 2006). 2007: DHS 2007 - 2008 2008: Ramirez-Zea M, Kroker-Lobos MF, Close-Fernandez R, Kanter R. The double burden of malnutrition in indigenous and nonindigenous Guatemalan populations. Am J Clin Nutr. 2014 Dec;100(6):1644S-51S. doi: 10.3945/ajcn.114.083857 2009: 1-4th Argentinian National Survey of Risk Factors (Encuesta Nacional de Factores de Riesgo). 4th (2018) Survey 2010: Demographic Health Survey 2010 2011: Ruopeng An, “Prevalence and Trends of Adult Obesity in the US, 1999–2012”, ISRN Obesity, vol. 2014, Article ID 185132, 6 pages, 2014. doi:10.1155/2014/185132 2012: Demographic Health Survey Haiti 2012 2013: DHS Peru 2013 2014: Demographic Health Survey, Guatemala 2014-15 2015: NHANES 2015/16. Analysis conducted by the World Obesity Federation, Caroline Litts, Fiona Montague & R Jackson-Leach 2017 2016: Encuesta Nacional de Salud. Chile. 2016-2017 https://www.minsal.cl/wp-content/uploads/2017/11/ENS-2016-17_PRIMEROS-RESULTADOS.pdf (Last accessed 04.08.20) 2017: Pickens, C. M., Flores-Ayala, R., Addo, O. Y., Whitehead, R. D., Jr, Palmieri, M., Ramirez-Zea, M., Hong, Y., & Jefferds, M. E. (2020). Prevalence and Predictors of High Blood Pressure Among Women of Reproductive Age and Children Aged 10 to 14 Years in Guatemala. Preventing chronic disease, 17, E66. https://doi.org/10.5888/pcd17.190403 2018: 4th National Survey, Full report available at http://www.msal.gob.ar/images/stories/bes/graficos/0000001622cnt-2019-10_4ta-encuesta-nacional-factores-riesgo.pdf (last accessed 29.04.20) 2019: Bahamas STEPS Survey (Preliminary results) https://www.bahamas.gov.bs/wps/wcm/connect/891fac39-ad7d-4aa8-ac54-39912a1afcea/Preliminary+Factsheet+v7+%28med+resl%27n%29.pdf?MOD=AJPERES (Accessed 03.11.2020) 2020: Shamah-Levy T, Romero-Martínez M, Barrientos-Gutiérrez T, Cuevas-Nasu L, Bautista-Arredondo S, Colchero MA, GaonaPineda EB, Lazcano-Ponce E, Martínez-Barnetche J, Alpuche-Arana C, Rivera-Dommarco J. Encuesta Nacional de Salud y Nutrición 2020 sobre Covid-19. Resultados nacionales. Cuernavaca, México: Instituto Nacional de Salud Pública, 2021. https://ensanut.insp.mx/encuestas/ensanutcontinua2020/doctos/informes/ensanutCovid19ResultadosNacionales.pdf (Accessed 11.01.2022) |
| 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: | 1960, 1971, 1973, 1976, 1991: Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: prevalence and trends, 1960-1994. International Journal of Obesity (1998);22:39-47 1975: Monteiro CA, Conde WL, Popking BM. Is obesity replacing or adding to undernutrition? Evidence from different social classes in Brazil. 2002. Public Health Nutrition:51(1A), 105-112 1988: Berrios X, Jadue I, Zenteno J, Ross MI, Rodriguez H. Prevalencia de factores de riesgo para enfermedades cronicas. Estudio de la poblacion general de la region Metropolitana, 1986-1987. Rev. Med. Chile. 1990;118:597-604 1992, 1994, 1995: Martorell R, Khan LK, Hughes ML, Grummer Strawn LM. Obesity in women from developing countries. EJCN (2000) 54;247-252 1997: Filozof C, Gonzales C, Sereday M, Mazza C, Braguinsky J. Obesity prevalence and trends in Latin American countries. Obesity Reviews, 2001;2:99-196 1998: http://www.unscn.org/layout/modules/resources/files/rwns5.pdf; MEAN BMI Data DHS Survey 1999: Centres for Disease Control and Prevention. http://www.cdc.gov/ 2000: Demographic Health Survey, Peru 2000 2001: Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of Overweight and Obesity in the United States, 1999-2004. JAMA 2006;295(13):1549-1555 2002: Monteiro CA, Conde WL and Popkin BA. (2007). Income-specific trends in obesity in Brazil: 1975 - 2003. American Journal of Public Health, 97 (10): 1808 - 1812. 2003: 2003 ENS Report. Final results on the National Health Survey. Http://epi.minsal.cl/epi/html/invest/ENS/informeFinalENS.pdf. 2005: Demographic Health Survey 2006. 2006: Olaiz-Fernández G, Rivera-Dommarco J, Shamah-Levy T, Rojas R, Villalpando-Hernández S, Hernández-Avila M, Sepúlveda-Amor J. Encuesta Nacional de Salud y Nutrición 2006. Cuernavaca, México: Instituto Nacional de Salud Pública, 2006. (National Health and Nutrition Survey 2006). 2007: DHS 2007 - 2008 2008: Ramirez-Zea M, Kroker-Lobos MF, Close-Fernandez R, Kanter R. The double burden of malnutrition in indigenous and nonindigenous Guatemalan populations. Am J Clin Nutr. 2014 Dec;100(6):1644S-51S. doi: 10.3945/ajcn.114.083857 2009: 1-4th Argentinian National Survey of Risk Factors (Encuesta Nacional de Factores de Riesgo). 4th (2018) Survey 2010: Demographic Health Survey 2010 2011: Ruopeng An, “Prevalence and Trends of Adult Obesity in the US, 1999–2012”, ISRN Obesity, vol. 2014, Article ID 185132, 6 pages, 2014. doi:10.1155/2014/185132 2012: Demographic Health Survey Haiti 2012 2013: DHS Peru 2013 2014: Demographic Health Survey, Guatemala 2014-15 2015: NHANES 2015/16. Analysis conducted by the World Obesity Federation, Caroline Litts, Fiona Montague & R Jackson-Leach 2017 2016: Encuesta Nacional de Salud. Chile. 2016-2017 https://www.minsal.cl/wp-content/uploads/2017/11/ENS-2016-17_PRIMEROS-RESULTADOS.pdf (Last accessed 04.08.20) 2017: Pickens, C. M., Flores-Ayala, R., Addo, O. Y., Whitehead, R. D., Jr, Palmieri, M., Ramirez-Zea, M., Hong, Y., & Jefferds, M. E. (2020). Prevalence and Predictors of High Blood Pressure Among Women of Reproductive Age and Children Aged 10 to 14 Years in Guatemala. Preventing chronic disease, 17, E66. https://doi.org/10.5888/pcd17.190403 2018: 4th National Survey, Full report available at http://www.msal.gob.ar/images/stories/bes/graficos/0000001622cnt-2019-10_4ta-encuesta-nacional-factores-riesgo.pdf (last accessed 29.04.20) 2019: Bahamas STEPS Survey (Preliminary results) https://www.bahamas.gov.bs/wps/wcm/connect/891fac39-ad7d-4aa8-ac54-39912a1afcea/Preliminary+Factsheet+v7+%28med+resl%27n%29.pdf?MOD=AJPERES (Accessed 03.11.2020) 2020: Shamah-Levy T, Romero-Martínez M, Barrientos-Gutiérrez T, Cuevas-Nasu L, Bautista-Arredondo S, Colchero MA, GaonaPineda EB, Lazcano-Ponce E, Martínez-Barnetche J, Alpuche-Arana C, Rivera-Dommarco J. Encuesta Nacional de Salud y Nutrición 2020 sobre Covid-19. Resultados nacionales. Cuernavaca, México: Instituto Nacional de Salud Pública, 2021. https://ensanut.insp.mx/encuestas/ensanutcontinua2020/doctos/informes/ensanutCovid19ResultadosNacionales.pdf (Accessed 11.01.2022) |
| 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
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. | |
Adults, 2012-2013
| Survey type: | Measured |
| Sample size: | 20535 |
| Area covered: | National |
| References: | Pajuelo, Jaime & Torres, Harold & Rebatta, Fernando & Zamora, Rosa. (2019). Obesidad no morbida y morbida del adulto en el Perú, 1975 - 2013. Anales de la Facultad de Medicina. 80. 317-21. 10.15381/anales.803.16851. |
| 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. | |
Adults, 2012-2013
| Survey type: | Measured |
| Age: | 20+ |
| Sample size: | 20535 |
| Area covered: | National |
| References: | Pajuelo, Jaime & Torres, Harold & Rebatta, Fernando & Zamora, Rosa. (2019). Obesidad no morbida y morbida del adulto en el Perú, 1975 - 2013. Anales de la Facultad de Medicina. 80. 317-21. 10.15381/anales.803.16851. |
| 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, 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, 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 |
% Infants exclusively breastfed 0-5 months
Children, 1998-2019
| Area covered: | National |
| References: | Encuesta Demográfica y de Salud Familiar-ENDES 2019 Nacional y Departamental |
| 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, 2021
| Age: | 20-79 |
| Area covered: | National |
| References: | Reproduced with kind permission International Diabetes Federation. IDF Diabetes Atlas, 10th edn. Brussels, Belgium:International Diabetes Federation, 2021. http://www.diabetesatlas.org |
| Definitions: | Age-adjusted comparative prevalence of diabetes, % |
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
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 |
| 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 |
| In practice, how is obesity treatment largely funded? | Out of pocket |
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
