Indicators on the cost and affordability of a healthy diet (CoAHD) are estimated in each country and show the population’s physical and economic access to least expensive locally available foods to meet requirements for a healthy diet, as defined in food-based dietary guidelines (FBDGs). The indicators use observed retail food consumer prices and income distributions to provide an operational measure of people’s access to locally available foods in the proportions needed for health. These indicators support efforts within the framework of the Sustainable Development Goals (SDGs) to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture by 2030 (SDG 2). They also support the monitoring of progress towards the objective of transforming agrifood systems by promoting “nutrition-sensitive agriculture”. FAO, in partnership with the Food Price for Nutrition of the World Bank, produces and reports the CoAHD indicators.

Indicators on the cost and affordability of a healthy diet (CoAHD) are estimated in each country and show the population’s physical and economic access to least expensive locally available foods to meet requirements for a healthy diet, as defined in food-based dietary guidelines (FBDGs). The indicators use observed retail food consumer prices and income distributions to provide an operational measure of people’s access to locally available foods in the proportions needed for health. These indicators support efforts within the framework of the Sustainable Development Goals (SDGs) to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture by 2030 (SDG 2). They also support the monitoring of progress towards the objective of transforming agrifood systems by promoting “nutrition-sensitive agriculture”. FAO, in partnership with the Food Price for Nutrition of the World Bank, produces and reports the CoAHD indicators.

The 2014 Global Nutrition Report Dataset contains data for all the indicators that were used in Global Nutrition Report 2014: Actions and Accountability to Accelerate the World's Progress on Nutrition . The data are compiled from secondary sources including United Nations Children's Fund (UNICEF), World Health Organization (WHO), and the World Bank among many others. The dataset broadly contains information on adult and child nutrition, economic demography, nutrition intervention coverage, and policy legislation in the nutrition sector. The data visualization based on a subset of this dataset can be accessed here.

Abstract

At the time of Appraisal of the Food Security Project, Ethiopia was a post-conflict state having just emerged from a two-year long armed conflict with Eritrea. Though the conflict resulted in a suspension of development assistance, an Interim Strategy Note (ISN) was put in place in November 2000 to guide the World Bank’s post-conflict recovery program. This ISN guided much of the strategy for the Food Security Project’s design. District governments, or woredas, were largely responsible for delivering services. Though the agricultural sector remained underemployed, it was still the largest sector of the economy, meaning there was little opportunity outside rural areas for non-farming activities. Poor rural households also lacked sufficient access to the microfinance sector. Droughts and food price escalation caused massive food insecurity for around 7-13 million people. The Food Security Project (FSP) wanted to shift assistance focus away from short term temporary fixes toward addressing long-term problems of food insecurity. The FSP was designed to comprise 5 components: (i) grants to communities and kebeles, including community-level assets building, household asset building and income generating activities, and child growth promotion; (ii) capacity building for woredas, regions, and federal ministries; (iii) food marketing initiatives, including improved management of food aid, establishment of a food market information system, development of a warehouse receipt and inventory credit system for traders, and development of a competitive and efficient market in warehousing services; (iv) communications and public education; and (v) project administration and impact evaluation. While these components were edited before the culmination of the project, they generally remained. The project development objective was to build the resource base of poorer rural households, increase their employment and incomes, and improve their nutrition levels, especially for children under five years of age, pregnant and lactating women. A major benefit of FSP participation is access to credit. Documented outcomes included: (i) small increase in the number of months FSP households were food secure and a small decrease in number of months of food consumption covered by own resources; (ii) positive effect on caregivers’ knowledge of and behavior regarding child nutrition; (iii) FSP households slightly less likely to have had at least one shock in the last five years and less likely to have used savings or a loan to buy food; and (iv) FSP households reported an increase of off-farm work.

Geographic coverage

Rural Areas

Analysis unit

Households Individuals

Universe

The Food Security Project's (FSP) primary target groups were poor rural households, children under age 5, and pregnant and lactating women.

Kind of data

Sample survey data [ssd]

Sampling procedure

The dataset is a product of survey data. The questionnaire was administered by the CSA to 6,000 households in 240 kebeles of which 120 FSP kebeles were selected at random and then the nearest neighboring kebele which was not participating in FSP was also selected.

Within the non-FSP kebeles, 25 households were selected at random to participate in the survey. In FSP kebeles, a list was compiled of all FSP beneficiaries using FSP program records. From this list 17 households were selected at random to participate in the survey. In addition, among the population of non-beneficiaries, 8 households were selected at random for interviews.

This sampling structure provides two potential comparison groups to compare to FSP participants: non-beneficiaries within FSP kebeles and those residing in non-FSP kebeles.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Module 1 - Basic Household Characteristics S1A: Household demographics, current household members S1B: Characteristics of the household and the household head S1C: Former household members S2: Children's education and activities

Module 2 - Land, Crop and Forestry Production, and Disposition S1: Land characteristics and tenure S2A: 2002 Meher crop production S2B: 2002 Belg crop production S2C: 2002 Perennial crops/forestry production S3: Household level supply and disposition of crops (annual and perennial), spices, and forestry prducts S4: Use of labor in agricultural production

Module 3 - Household Assets S1: Household assets (non-land): production equipment, consumer durables S2: Housing S3: Livestock ownership S4: Income from livestock S5: Distress asset sales

Module 4 - Income Apart from Own-Agricultural Activities and Credit S1: Wage employment S2: Own business activities S3: Transfers

Module 5 - Access to WB/CIDA/Italy Food Security Project and Related Programs S1: Access to productive safety nets program - public works S2: Participation in other food security programs (OFSP) S3: Perceptions of benefits of assets created by PSNP and other public works S4: Perceptions and participation of operations of the WB/CIDA/Italy FSP S5: Access to credit

Module 6 - Consumption S1: Non-food expenditure on durables and services S2: Non-food expenditure on household consumables S3: Food consumption S4: Food availability, access and coping strategies

Module 7 - Health, Illness, Shocks and Poverty Perceptions S1: Health status S2: Illness S3: Child Growth Promotion S4: Long term shocks and coping mechanisms S5: Shocks to crops and livestock S6: Perceptions of poverty and well-being

This is not a data deposit; it is a description of how interested parties can access the data from the original DHS and MICS repositories.

The DHS and MICS are household survey micro-data, made available to researchers, for free, to investigate a range of social, health, and other issues in low and middle-income countries. Surveys are usually run every 3-5 years and can be accessed from the DHS and MICS websites.

Between 1990 and 2014, sub-Saharan Africa saw a 23% increase in the number of children experiencing stunting, with around 58 million children under 5 affected. Many of these children also experienced wasting, and the co-occurrence of these anthropometric deficits ("multiple malnutrition", MM) entail heightened morbidity risks. At household and community level, MM can refer to the co-existence of under- and over-nutrition, a pattern observed across many low and middle income countries (LMICs), and which the 2015 and 2016 Global Nutrition Reports have noted to be "the new normal". This project focuses on MM in young children in one of the world's poorest regions, the countries of West and Central Africa (WCA). Utilising data from existing household surveys from the 24 countries of WCA, the project will conduct quantitative analyses on anthropometric and demographic data and variables to explore the prevalence and patterning of MM. It will bring together individual and household level data from the surveys (DHS, MICS), and combine this information with macro-level indicators, of national governance, of public expenditure on health and nutrition, and of food prices, to examine the underlying, intermediate and basic causes of MM, as set out in UNICEF's conceptual framework on (mal)nutrition. Malnutrition is associated with raised mortality risks, particularly in children; analysis of longitudinal survey data has shown that children experiencing multiple anthropometric deficits are 12.3 times more likely to die. Such children are likely to benefit most from nutrition and other child survival interventions (McDonald et al., 2013), as long as they can be indentified - which is not currently happening. Despite this, and the efforts and resources (national and international) which go to early child development programs in LMICs, a UNICEF/WHO/World Bank review of child malnutrition revealed that data on the prevalence and patterning of MM in young children are severely lacking, with no regional or global estimates of the number of children concurrently stunted and wasted. This knowledge gap is a real and ongoing problem for national governments and international agencies like UNICEF and the FAO. The analysis of existing household surveys, using advanced quantitative methods, will provide policy-relevant evidence on the determinants of MM for policy makers. We will also show how patterns of MM have changed over time, and identify key geographic and socio-demographic factors associated with MM. The project focuses on children under 5 years of age, since this is a crucial period of physical development, and also because anthropometric data (heights, weights) on this age group are most reliable and routinely collected in national surveys. The WCA region has some of the world's poorest countries, many with high rates of child malnutrition. These countries also face on-going challenges of food security not least with respect to unstable food production in the context of increasing desertification, political and economic instability, and violent conflict (e.g. in northern Nigeria, Niger and Mali). WCA has excellent coverage in terms of the number of countries with existing survey data, all of which contain detailed, comparable data with which to investigate drivers of disparities in MM. Importatnly, the evidence generated by this project will aid assessment of progress towards the first three Sustainable Development Goals (SDG) - of ending poverty, hunger and reducing child mortality.

This interactive map of Nepal, broken down into five development regions, highlights the Mid-Western and Far-Western regions as the priority area for the Nepal Food Security Enhancement Project (jointly financed by the Nepal Government and GAFSP). The project is being implemented in nineteen hill and mountain districts of these two regions. The interactive map shows sub-national poverty and malnutrition data, as well as information on irrigation in the various regions. The Mid-Western and Far-Western regions are the two regions where poverty and malnutrition are the highest in the country. The Nepal Living Standard Survey (NLSS III, 2010) showed that 37% of the people in the rural hills of these regions fall below the poverty line, compared to the national average of 25.16%. The proportion of underweight children under the age of 5 years in the Mid-Western region is the highest in the country (more than 10%). The project has been designed to enhance food security and nutrition in food insecure communities in these two regions. Data Sources: Nepal Agriculture and Food Security Project (NAFSP) LocationsSource: GAFSP and World Bank Documents. Poverty (Proportion of population below the poverty line) (2010/11): Proportion of the population living on less than Rs 19.261 per year, in average 2010/11 prices.Source: Nepal Central Bureau of Statistics. Poverty in Nepal 2010/11. Nepal Living Standard Survey III 2010/11 (NLSS III). Poverty (Proportion of population below the poverty line at district level) (2011): Proportion of the population living on less than Rs 19.261 per year, in average 2010/11 prices.Source: Nepal Central Bureau of Statistics - World Bank. “Nepal Small Area Estimation of Poverty, 2011 -Estimations based on Living Standards Survey 2010-11, Nepal Census 2011 and GIS information from the Vulnerability Analysis and Mapping Unit of World Food Program Nepal.” Malnutrition (Proportion of underweight children under 5 years) (2011): Prevalence of severely underweight children is the percentage of children aged 0-59 months whose weight for age is less than minus 3 standard deviations below the median weight-for-age of the international reference population.Source: Measure DHS - Nepal Ministry of Health and Population. "2011 Nepal Demographic and Health Survey." Population (Total population) (2011): Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship, except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Source: Nepal Central Bureau of Statistics. “2011 Census Preliminary Results.” Population Density (Persons per 1 square kilometer) (2011): Population divided by land area in square kilometers.Source: Nepal Central Bureau of Statistics. 2011 Census preliminary results. Irrigation (2009/10): Total Irrigated Area in Hectares.Source: Ministry of Agriculture and Co-operatives. Statistical Information on Nepalese Agriculture 2009/10. Irrigation (2011/12): Total irrigated area in hectares.Source: Ministry of Agriculture - Department of Irrigation - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012." Rice Area (2011-12): Area in hectares of agricultural land used for rice.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012."

Rice Production (2011-12): Rice harvested expressed in tons.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012." Rice Productivity (2011-12): Rice yield expressed in kilograms per hectare.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012." Rice Area (2013-14): Area in hectares of agriculture land used for rice.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014."

Rice Production (2013-14): Rice harvested expressed in tons.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014."
Rice Productivity (2013-14): Rice yield expressed in kilograms per hectare.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014." Wheat Area (2011-12): Area in hectares of agriculture land used for wheat.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012." Wheat Production (2011-12): Wheat harvested expressed in tons.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012."
Wheat Productivity (2011-12): Wheat yield expressed in kilograms per hectare.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012." Wheat Area (2013-14): Area in hectares of agriculture land used for wheat.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014." Wheat Production (2013-14): Wheat harvested expressed in tons.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014."
Wheat Productivity (2013-14): Rice yield expressed in kilograms per hectare.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014." Livestock Inventory (2011-12): Number of cattle, goat, and sheep by district.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2011/2012." Livestock Inventory (2013-14): Number of cattle, goat, and sheep by district.Source: Ministry of Agricultural Development - Agri-Business Promotion and Statistics Division Statistics Section. "Statistical Information on Nepalese Agriculture 2013/2014."

The maps displayed on the GAFSP website are for reference only. The boundaries, colors, denominations and any other information shown on these maps do not imply, on the part of GAFSP (and the World Bank Group), any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.

Thailand TH: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 8.200 % in 2016. This records a decrease from the previous number of 10.900 % for 2012. Thailand TH: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 8.000 % from Dec 1987 (Median) to 2016, with 5 observations. The data reached an all-time high of 10.900 % in 2012 and a record low of 1.300 % in 1987. Thailand TH: Prevalence of Overweight: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank.WDI: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues

Abstract

The MAHAY study uses a multi-arm randomized-controlled trial (RCT) to test the cost-effectiveness of combined interventions to address chronic malnutrition and poor child development. The arms of the trial are: (T0) existing community-based nutrition program with monthly growth monitoring and nutritional/hygiene education; (T1) is T0 + home visits for intensive nutrition counseling within a behavior change framework; (T2) is T1 + lipid-based supplementation (LNS) for children 6-18 months old; (T3) is T2 + LNS supplementation of pregnant/lactating women; and (T4) is T1 + intensive home visiting program to support child development.

Trial Registration: Current Controlled Trials ISRCTN14393738. Registered June 23, 2015.

Geographic coverage

The five regions of south and southeast Madagascar included in the study are Amoron’i Mania, Androy, Atsimo Atsinanana, Haute Matsiatra, and Vatovavy-Fitovinany.

Analysis unit

Pregnant women, children 0-11 months old and respective households at baseline (2014)

Universe

The target population is pregnant women and children eligible to attend the national community based nutrition program.

Kind of data

Sample survey data [ssd]

Sampling procedure

Our sampling frame is the universe of community nutrition project sites in the five target regions of the program. From this universe of project communities, we drew a sample of communities that was randomly assigned to five groups. The comparison group for our study is the program as currently designed (as opposed to no program in most of the evaluation literature). In the four randomized arms, we have sequentially added increasing levels of intensity and complexity to the current intervention, starting with the lowest cost option and incrementally adding layers of intensity (and cost) to test the value added of each layer in terms of their ability to reduce stunting/growth faltering and promote child development.

Sampling deviation

Our sample of interest is the cohort of children (and their households) sampled at baseline and followed longitudinally at midline and at endline surveys. The sample was drawn from the census of children enrolled in the community-based intervention in December 2013 and updated in May 2014 in preparation for the baseline fieldwork. A sample of 3,738 households with either pregnant women or with children aged 0-11 months old was selected at baseline. At midline and endline, tracking protocols were put in place with the objective to minimize attrition and preserve a sample that reflected the target population of children in the program site. The following tracking criteria were followed:

• if the pregnant woman had a miscarriage or died, or if the target child had died, the household was considered as lost
• if the target child had temporarily moved within the catchment area of the program sites, the child should be located and interviewed;
• if the target child had moved outside the catchment area (and therefore not eligible to receive the services), the household would be replaced with a household randomly chosen from within the same age group;
• if the target child returned to the original household after their temporary migration at endline, both the original household and its replacement household at midline were interviewed at endline.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The following questionnaires were used for data collection:

The Household Questionnaire includes detailed sections on demographics, housing/water and sanitation, education, household expenditures, food security, and shocks. The household questionnaire was administered to the household head, or in his/her absence to the most informed household member. Data on food security status was collected using the Household Food Insecurity Access Scale (HFIAS) developed by the USAID-funded Food and Nutrition Technical Assistance II project (FANTA) and on dietary diversity using the Household Dietary Diversity Score (HDDS).

The Female and Child Questionnaire were administered to all primary caregivers of the target children. At baseline, all primary caregivers were asked about fertility. Mothers were administered sections on knowledge about nutrition and child development, as well as a module on child appetite and responsive feeding. A child questionnaire was administered to all primary caregivers include delivery information, breastfeeding history and status, timing introduction of complementary feeding, morbidity, and a 24 hour dietary recall. Child weight, height, and mid upper-arm circumference were measured at baseline in duplicate using techniques described for the WHO Multicenter Growth Reference Study. Child development was assessed using The Ages and Stages Questionnaire Inventory (ASQI), which is a comprehensive self-report maternal assessment of child development. ASQ-I is a continuous version of child development and progress as opposed to the more widely used ASQ-3 screening tool. The subscales measure skills in Communication, Gross Motor, Fine Motor, Personal-Social and Problem-Solving domains. In addition, pregnant women and primary caregivers were also administered a module on depression, using the Center for Epidemiological Studies Depression Scale (CESD) and administered a test on receptive vocabulary, using the Peabody Picture Vocabulary Test (PPVT) already adapted for Madagascar.

The Community Health Worker Questionnaire was administered to both the community nutrition worker (ACN) and the added community nutrition worker (ACDN, if already identified at baseline). The questionnaire includes demographics and socio-economic information about the community worker (education, occupation, household assets) and a Motivation Scale. The community workers were administered the same test of receptive vocabulary, using the Peabody Picture Vocabulary Test (PPVT) administered to the primary caregiver. In addition, the questionnaire has specific sections about the site characteristics, the characteristics and composition of a volunteer support group, the referral to a health center and the training received.

A Community Questionnaire was administered to a group of informed leaders about the size and population of the village (Fokontany), accessibility and availability of local infrastructure, the presence of associations in the village, the occurrence of weather shocks and production shocks.

The questionnaires are provided in French and Malagasy and are available for download.

Abstract

The overall objective envisaged by the survey is to collect information to assess the food security of households, their level of vulnerability and to define the criteria for targeting beneficiaries for intervention in favor of food insecure people. Specifically, the survey will collect new field data for: - Analyze the current food situation prevailing in the regions and the different food economy zones; - Estimate the number of food insecure people by indicating their geographic location and their socio-economic profile; - Analyze the market situation through the review of secondary data (food availability, prices, supply, functioning of markets and terms of trade); - Determine the causes of food insecurity and analyze the current constraints facing households according to their socioeconomic status in relation to their means of access to food and income; - Determine the severity of food insecurity and analyze the cyclical / chronic risks and shocks to which households are most exposed and their adaptive capacity or survival strategies; - Develop scenarios over the next six months to forecast the evolution of the food and nutrition security situation; and - Define the types of food and non-food assistance to save lives and to strengthen the livelihoods and resilience capacity to shocks of vulnerable households and communities.

Geographic coverage

Regional coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The overall objective envisaged by the survey is to collect information to assess the food security of households, their level of vulnerability and to identify the beneficiaries targeting criteria for interventions. The full ENSA sample is composed of 8.921 households living in 61 departments. The present work is based on a sample of 6946 households located in rural areas only. Specifically, the sample is composed of those households interviewed just after the rainy season in October 2014. The sample is representative at the regional level. For the ENSA three different types of data collection have been applied: - A focus group with opinion leaders, traditional leaders, local officials, resource persons, NGOs to discuss the main priority to add into the questionnaire; - Household-level interviews with heads of households or their representatives getting all the possible information about household life; and food security. - Community levels interviews to assess price developments and market supply systems.

Mode of data collection

Face-to-face [f2f]

US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 6.000 % in 2012. This records a decrease from the previous number of 7.800 % for 2009. US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 7.000 % from Dec 1991 (Median) to 2012, with 5 observations. The data reached an all-time high of 8.100 % in 2005 and a record low of 5.400 % in 1991. US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues

Papua New Guinea PG: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data was reported at 18.500 % in 2024. This records a decrease from the previous number of 18.600 % for 2023. Papua New Guinea PG: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 11.700 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 18.600 % in 2023 and a record low of 4.500 % in 2000. Papua New Guinea PG: Prevalence of Overweight: Weight for Height: % of Children Under 5, Modeled Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Papua New Guinea – Table PG.World Bank.WDI: Social: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.