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This dataset includes malnutrition indicators and some of the features that might impact malnutrition. The detailed description of the dataset is given below:

• Percentage-of-underweight-children-data: Percentage of children aged 5 years or below who are underweight by country.

• Prevalence of Underweight among Female Adults (Age Standardized Estimate): Percentage of female adults whos BMI is less than 18.

• GDP per capita (constant 2015 US$): GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 U.S. dollars.

• Domestic general government health expenditure (% of GDP): Public expenditure on health from domestic sources as a share of the economy as measured by GDP.

• Maternal mortality ratio (modeled estimate, per 100,000 live births): Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs).

• Mean-age-at-first-birth-of-women-aged-20-50-data: Average age at which women of age 20-50 years have their first child.

• School enrollment, secondary, female (% gross): Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.

The Poverty Mapping Project: Global Subnational Prevalence of Child Malnutrition data set consists of estimates of the percentage of children with weight-for-age z-scores that are more than two standard deviations below the median of the NCHS/CDC/WHO International Reference Population. Data are reported for the most recent year with subnational information available at the time of development. The data products include a shapefile (vector data) of percentage rates, grids (raster data) of rates (per thousand in order to preserve precision in integer format), the number of children under five (the rate denominator), and the number of underweight children under five (the rate numerator), and a tabular data set of the same and associated data. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

The Global Hunger Index (GHI) is a tool designed to comprehensively measure and track hunger globally and by region and country. Calculated each year by the International Food Policy Research Institute (IFPRI), the GHI highlights successes and failures in hunger reduction and provide insights into the drivers of hunger, and food and nutrition security. The 2013 GHI has been calculated for 120 countries for which data on the three component indicators are available and for which measuring hung er is considered most relevant. The GHI calculation excludes some higher income countries because the prevalence of hunger there is very low. The GHI is only as current as the data for its three component indicators. This year's GHI reflects the most recent available country level data for the three component indicators spanning the period 2008 to 2012. Besides the most recent GHI scores, this dataset also contains the GHI scores for four other reference periods- 1990, 1995, 2000, and 2005. A country's GHI score is calculated by averaging the percentage of the population that is undernourished, the percentage of children youn ger than five years old who are underweight, and the percentage of children dying before the age of five. This calculation results in a 100 point scale on which zero is the best score (no hunger) and 100 the worst, although neither of these extremes is reached in practice. The three component indicators used to calculate the GHI scores draw upon data from the following sources: 1. Undernourishment: Updated data from the Food and Agriculture Organization of the United Nations (FAO) were used for the 1990, 1995, 2000, 2005, and 2013 GHI scores. Undernourishment data for the 2013 GHI are for 2010-2012. 2. Child underweight: The "child underweight" component indicator of the GHI scores includes the latest additions to the World Health Organization's (WHO) Global Database on Child Growth and Malnutrition, and additional data from the joint database by the United Nations Children's Fund (UNICEF), WHO and the World Bank; the most recent Demographic and Health Survey (DHS) and Multiple Indicator Cluster Survey reports; and statistical tables from UNICEF. For the 2013 GHI, data on child underweight are for the latest year for which data are available in the period 2008-2012. 3. Child mortality: Updated data from the UN Inter-agency Group for Child Mortality Estimation were used for the 1990, 1995, 2000, and 2005, and 2013 GHI scores. For the 2013 GHI, data on child mortality are for 2011.

The Poverty Mapping Project: Global Subnational Prevalence of Child Malnutrition data set consists of estimates of the percentage of children with weight-for-age z-scores that are more than two standard deviations below the median of the NCHS/CDC/WHO International Reference Population. Data are reported for the most recent year with subnational information available at the time of development. The data products include a shapefile (vector data) of percentage rates, grids (raster data) of rates (per thousand in order to preserve precision in integer format), the number of children under five (the rate denominator), and the number of underweight children under five (the rate numerator), and a tabular data set of the same and associated data. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN).

this graph was created in R:

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Having enough to eat is one of the fundamental basic human needs. Hunger – or, more formally, undernourishment – is defined as eating less than the energy required to maintain an active and healthy life.

The share of undernourished people is the leading indicator for food security and nutrition used by the Food and Agriculture Organization of the United Nations.

The fight against hunger focuses on a sufficient energy intake – enough calories per person per day. But it is not the only factor that matters for a healthy diet. Sufficient protein, fats, and micronutrients are also essential, and we cover this in our topic page on micronutrient deficiencies.

Undernourishment in mothers and children is a leading risk factor for death and other poor health outcomes.

The UN has set a global target as part of the Sustainable Development Goals to “end hunger by 2030“. While the world has progressed in past decades, we are far from reaching this target.

On this page, you can find our data, visualizations, and writing on hunger and undernourishment. It looks at how many people are undernourished, where they are, and other metrics used to track food security.

Hunger – also known as undernourishment – is defined as not consuming enough calories to maintain a normal, active, healthy life.

The world has made much progress in reducing global hunger in recent decades — we will see this in the following key insight. But we are still far away from an end to hunger. Tragically, nearly one-in-ten people still do not get enough food to eat.

The share of the undernourished population is shown globally and by region in the chart.

You can see that rates of hunger are highest in Sub-Saharan Africa. South Asia has much higher rates than the Americas and East Asia. Rates in North America and Europe are below 2.5%. However, the FAO shows this as “2.5%” rather than the specific point estimate.

Child malnutrition joint country dataset (UNICEF, WHO, World Bank Group)

Definitions:
Severe Wasting: Percentage of children aged 0–59 months who are below minus three standard deviations from median weight-for-height of the WHO Child Growth Standards.
Wasting – Moderate and severe: Percentage of children aged 0–59 months who are below minus two standard deviations from median weight-for-height of the WHO Child Growth Standards.
Overweight – Moderate and severe: Percentage of children aged 0-59 months who are above two standard deviations from median weight-for-height of the WHO Child Growth Standards.
Stunting – Moderate and severe: Percentage of children aged 0–59 months who are below minus two standard deviations from median height-for-age of the WHO Child Growth Standards.
Underweight – Moderate and severe: Percentage of children aged 0–59 months who are below minus two standard deviations from median weight-for-age of the World Health Organization (WHO) Child Growth Standards.

United States US: Prevalence of Underweight: Weight for Age: Female: % of Children Under 5 data was reported at 0.400 % in 2012. This records a decrease from the previous number of 0.700 % for 2009. United States US: Prevalence of Underweight: Weight for Age: Female: % of Children Under 5 data is updated yearly, averaging 0.800 % from Dec 1991 (Median) to 2012, with 6 observations. The data reached an all-time high of 1.200 % in 1991 and a record low of 0.400 % in 2012. United States US: Prevalence of Underweight: Weight for Age: Female: % 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 underweight, female, is the percentage of girls under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Philippines PH: Prevalence of Stunting: Height for Age: % of Children Under 5 data was reported at 33.400 % in 2015. This records an increase from the previous number of 30.300 % for 2013. Philippines PH: Prevalence of Stunting: Height for Age: % of Children Under 5 data is updated yearly, averaging 36.050 % from Dec 1987 (Median) to 2015, with 10 observations. The data reached an all-time high of 44.700 % in 1987 and a record low of 30.300 % in 2013. Philippines PH: Prevalence of Stunting: Height for Age: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on 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; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Analysis of ‘COVID-19 Healthy Diet Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mariaren/covid19-healthy-diet-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

“Health requires healthy food."

Roger Williams (1603 – 1683)

In the past couple months, we’ve witnessed doctors, nurses, paramedics and thousands of medical workers putting their lives on the frontline to save patients who are infected. And as the battle with COVID-19 continues, we should all ask ourselves – What should we do to help out? What can we do to protect our loved ones, those who sacrifice for us, and ourselves from this pandemic?
These questions all relate back to the CORD-19 Open Research Dataset Challenge Task Question: “What do we know about non-pharmaceutical interventions?”
And my simple answer is : We need to protect our families and our own healths by adapting to a healthy diet.

Inspiration and Research Objectives

The USDA Center for Nutrition Policy and Promotion recommends a very simple daily diet intake guideline: 30% grains, 40% vegetables, 10% fruits, and 20% protein, but are we really eating in the healthy eating style recommended by these food divisions and balances?
In this dataset, I have combined data of different types of food, world population obesity and undernourished rate, and global COVID-19 cases count from around the world in order to learn more about how a healthy eating style could help combat the Corona Virus. And from the dataset, we can gather information regarding diet patterns from countries with lower COVID infection rate, and adjust our own diet accordingly.
In each of the 4 datasets below, I have calculated fat quantity, energy intake (kcal), food supply quantity (kg), and protein for different categories of food (all calculated as percentage of total intake amount). I've also added on the obesity and undernourished rate (also in percentage) for comparison. The end of the datasets also included the most up to date confirmed/deaths/recovered/active cases (also in percentage of current population for each country).

Acknowledgements

• Data for different food group supply quantities, nutrition values, obesity, and undernourished percentages are obtained from Food and Agriculture Organization of the United Nations FAO website To see the specific types of food included in each category from the FAO data, take a look at the last dataset Supply_Food_Data_Description.csv.

• Data for population count for each country comes from Population Reference Bureau PRB website

• Data for COVID-19 confirmed, deaths, recovered and active cases are obtained from Johns Hopkins Center for Systems Science and Engineering CSSE website

• The USDA Center for Nutrition Policy and Promotion diet intake guideline information can be found in ChooseMyPlate.gov

Note: I will update and push new versions of the datasets weekly. (Current version include COVID data from the week of 02/06/2021) Click here to see my data cleaning/preprocessing code in R

If you like this dataset, please don't forget to give me an upvote! 👍

--- Original source retains full ownership of the source dataset ---

this graph was retired the OurDataWorld :

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Malnutrition is a multifaceted issue that extends far beyond the simple concept of hunger and caloric intake. While ensuring an adequate supply of calories is undoubtedly crucial, it is equally important to consider the nutritional quality of the foods consumed. The composition of our diets plays a pivotal role in determining our overall health and well-being.

When we discuss malnutrition, we must broaden our perspective to encompass not only the quantity but also the quality of food intake. It's not just about filling stomachs; it's about providing the body with essential nutrients such as proteins, fats, vitamins, and minerals. Even if individuals consume enough calories, they can still suffer from malnutrition if their diets lack diversity and fail to deliver the necessary array of nutrients for optimal health.

A significant concern associated with poor dietary choices is the prevalence of micronutrient deficiencies. These deficiencies arise when individuals consume diets that are inadequate in essential vitamins and minerals. A diet that lacks diversity and relies heavily on processed or refined foods often fails to meet the body's micronutrient requirements, leading to a range of health problems and complications.

Addressing malnutrition requires a comprehensive approach that considers not only individual dietary habits but also broader societal and environmental factors. The environmental impact of food production and consumption cannot be overstated. As the global population continues to grow, ensuring access to nutritious foods for everyone while minimizing the environmental footprint of agriculture has become an urgent priority.

One of the key challenges we face is finding sustainable solutions to ensure that nutritious diets are accessible and affordable for all. This necessitates a shift towards more sustainable food systems that prioritize nutrient-rich foods while minimizing environmental degradation. Sustainable agriculture practices, such as organic farming and regenerative agriculture, can play a crucial role in achieving this goal by promoting biodiversity, reducing chemical inputs, and enhancing soil health.

Furthermore, promoting dietary diversity and education about nutrition are essential components of any strategy aimed at combating malnutrition. Encouraging individuals to consume a wide variety of foods, including fruits, vegetables, whole grains, and lean proteins, can help ensure they receive a balanced intake of essential nutrients. Nutrition education programs can empower individuals to make healthier food choices and adopt sustainable eating habits that benefit both their health and the planet.

In addition to individual-level interventions, policymakers and stakeholders must work together to implement broader systemic changes that promote food security and sustainability. This includes investing in agricultural research and innovation, supporting smallholder farmers, and implementing policies that incentivize the production and consumption of nutritious, environmentally friendly foods.

Ultimately, addressing malnutrition requires a concerted effort from all sectors of society. By prioritizing nutritious diets, promoting sustainable food systems, and addressing the root causes of food insecurity and environmental degradation, we can work towards a future where everyone has access to healthy, sustainable food choices. Together, we can build a world where malnutrition is no longer a widespread concern, and all individuals can thrive and reach their full potential.

The “malnourishment index” relates to the degree of food insecurity of a certain region in 2010. A community characterized by scarce food quality supply and thus subject to malnutrition and starvation of large part of its members is prone to suffer from climate change impact on food production. The index results from the second cluster of the Principal Component Analysis preformed among 14 potential variables. The analysis identify four dominant variables, namely “percentage of underweighted children”, “percentage of stunted children”, “diet diversification index” and “animal protein supply”, assigning a weight of 0.25 to the “percentage of underweighted children” and the “percentage of stunted children”, 0.3 to the “animal protein supply” and 0.2 to the “diet diversification index”. Before to perform the analysis the variables were score-standardized (converted to distribution with average of 0 and standard deviation of 1; “diet diversification index” and “animal protein supply” with inverse method) in order to be comparable. The first administrative level data for “percentage of underweighted children” (more than two standard deviations below the mean weight-for-age score of the NCHS/CDC/WHO international reference population) and “percentage of stunted children” (more than two standard deviations below the mean height-for-age score of the NCHS/CDC/WHO international reference population) were derived from the Global Database on Child Growth and Malnutrition of WHO/UNICEF (data range from 1998 to 2012). When subnational data were not available, were used the national values from UNICEF database. Such national figures were used also to normalize to 2010 the values recorded by WHO/UNICEF. Tabular data were linked by first administrative unit to the first administrative boundaries shapefile (FAO/GAUL) and then converted into raster format (resolution 0.5 arc-minute). The country based values for the other two variables were collected from FAO statistics like the average of the period 2008-2012. Tabular data were linked by country to the national boundaries shapefile (FAO/GAUL) and then converted into raster format (resolution 0.5 arc-minute). Malnourishment illustrates the problems of food insecurity and hunger of a population, which has serious consequences on people's physical condition and very negative impacts on the mental and physical development of children. Countries which have worst diet parameters are more sensitive to the effects of the climate change. Indeed low animal protein consumption and low diet diversification (dominated by cereals) are indicators of the lack of alternative food source than local cereals production. This dataset has been produced in the framework of the “Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)” project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Data on the percentage of children under age 5 by nutritional status in Nigeria, reflecting the level of malnutrition in Nigeria.

Definition: Prevalence of severe wasting in children under 5 years refers to percentage of children under 5 years old who are considered severely wasted. Wasting is a condition characterized by a child being significantly underweight for their height. It's often a sign of acute malnutrition, typically caused by insufficient food intake or frequent infections. Unlike stunting, which is a chronic condition resulting from long-term malnutrition, wasting is more immediate and often reversible with appropriate interventions. However, if left untreated, it can lead to severe health complications and even death.

Percentage of children under age 5 by nutritional status according to three anthropometric indices: weight for age, height for age, and weight for height, Palestine.

The data set consists of human poverty index value with varaiables such as percentage of people not expected to survive to age 40, adult illiteracy rate, percentage without safe water, percentage of children under age five who are malnourished and deprivation in economic provisioning by disticts for 2011. The data is extracted from Nepal Human Developement Report (2014) by UNDP (http://www.npc.gov.np/new/uploadedFiles/allFiles/NHDR_Report_2014.pdf).

Thailand TH: Prevalence of Underweight: Weight for Age: % of Children Under 5 data was reported at 6.700 % in 2016. This records a decrease from the previous number of 9.200 % for 2012. Thailand TH: Prevalence of Underweight: Weight for Age: % of Children Under 5 data is updated yearly, averaging 12.300 % from Dec 1987 (Median) to 2016, with 6 observations. The data reached an all-time high of 20.200 % in 1987 and a record low of 6.700 % in 2016. Thailand TH: Prevalence of Underweight: Weight for Age: % 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: Health Statistics. Prevalence of underweight children is the percentage of children under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's 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; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

KIHBS Table 6.1: Percentage of Children (6 - 59 months) who are Severely or Moderately Undernourished, County estimates

Percentage of undernutrition in children under five in rural and urban areas based on homogamy/heterogamy in parental education, BDHS 2017–18.

Chad TD: Prevalence of Stunting: Height for Age: % of Children Under 5 data was reported at 31.900 % in 2022. This records an increase from the previous number of 31.100 % for 2021. Chad TD: Prevalence of Stunting: Height for Age: % of Children Under 5 data is updated yearly, averaging 32.100 % from Dec 1997 (Median) to 2022, with 11 observations. The data reached an all-time high of 44.500 % in 1997 and a record low of 30.500 % in 2020. Chad TD: Prevalence of Stunting: Height for Age: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Social: Health Statistics. Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.;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.;See SH.STA.STNT.ME.ZS for aggregation;Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF). Estimates are from national survey data. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

Myanmar MM: Prevalence of Stunting: Height for Age: % of Children Under 5 data was reported at 29.200 % in 2016. This records a decrease from the previous number of 35.100 % for 2009. Myanmar MM: Prevalence of Stunting: Height for Age: % of Children Under 5 data is updated yearly, averaging 40.800 % from Dec 1991 (Median) to 2016, with 7 observations. The data reached an all-time high of 58.700 % in 1994 and a record low of 29.200 % in 2016. Myanmar MM: Prevalence of Stunting: Height for Age: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Myanmar – Table MM.World Bank: Health Statistics. Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on 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; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.