Diet-related deaths by 2010 US Census tract in the state of Florida. This data should be paired with rural and urban high impact areas. Data for each cause of death was aggregated for the years 2007-2013. Diet-related causes include cancer, diabetes, heart, liver, and stroke (deaths by accident are included for comparison). For detailed information, refer to the technical addendum developed by Mari Gallagher Research & Consulting Group (MG).This service is intended for use at very large scales or for popups with tile cached services.This service is tile cached for scale levels L06-L14.

This data layer is part of Florida’s Roadmap to Living Healthy web map produced by the Florida Department of Agriculture and Consumer Services (FDACS), Division of Food, Nutrition and Wellness (DFNW).For technical assistance, contact the Florida's Roadmap to Healthy Living Administrator

BackgroundWith the rapid improvement in economy and lifestyle, dietary risk-related diseases have become a public health problem worldwide. However, the health effects of dietary risk over time have not been fully clarified in China. Here, we explored the temporal trends in the death burden of unhealthy dietary habits in China and benchmark dietary risk challenges in China to G20 member states.MethodSex–age-specific burdens due to dietary risk in China were extracted from the Global Burden of Disease (GBD) Study 2019, including annual numbers and age-standardized rates (ASRs) of death, disability-adjusted life years (DALYs), and summary exposure values (SEVs) during 1990–2019. The variation trend of ASRs was evaluated by estimated annual percentage changes (EAPCs).ResultBetween 1990 and 2019, the number of dietary risk-based death and DALYs increased significantly in China with an overall downward trend of ASDR and ASR-DALYs. Ischemic heart disease was the first cause of death from diet, followed by stroke and colon and rectum cancers. Chinese men were at greater risk than women for diet-related death and DALYs. Further analysis showed that a high sodium diet has always been the “No. 1 killer” that threatens the health of Chinese residents. The death burden of dietary risk demonstrated an increasing trend with age, and the peak was reached in people over 75 years. Compared with other G20 countries, Japan and South Korea have the most similar dietary patterns to China with the character of high sodium intake. Notably, decreased whole grain intake, as the primary dietary risk attributable to death and DALYs burden in the United States and European countries, had already ranked second in China's dietary risks.ConclusionChina's dietary burden cannot be ignored. Chinese residents should pay more attention to the collocation of dietary nutrients, especially men and 75+ years (elderly) people. Targeted dietary adjustments can significantly reduce deaths and DALYs in China.

BackgroundThe global burden of diet-related chronic diseases and their future projections remain unclear. To address this gap, we present the latest data on deaths and disability-adjusted life years attributable to dietary factors from 1990 to 2021, focusing on noncommunicable diseases worldwide. Additionally, we provide predictions of mortality rates across different age groups through 2030.MethodsData from the Global Burden of Disease Study 2021 were analyzed to evaluate correlations between dietary factors and trends in chronic disease burden over a 30-year period. Moreover, we predicted the burden of chronic dietary diseases up to 2030.ResultsFrom 1990 to 2021, global age-standardized mortality rates and disability-adjusted life year (DALY) rates associated with dietary factors decreased by approximately one-third for neoplasms and cardiovascular diseases (CVDs). In high sociodemographic index (SDI) regions, neoplasm-related deaths showed a stronger correlation with dietary factors, particularly high red meat intake. In cardiovascular diseases, the leading dietary factors are low-grain diets, whereas in diabetes, it is due to increased intake of processed meat. In low-SDI regions, diets low in vegetables showed the strongest association with neoplasm-related mortality, while diets low in fruits were significantly linked to CVD and diabetes burden. High-sodium diet was a significant risk factor for CVD in the middle-SDI regions. Moreover, the 2030 projections indicated a decline in mortality from neoplasms and CVDs, with a slight increase in mortality rates from diabetes.ConclusionThe global burden of chronic diseases linked to dietary factors shows varying trends across different countries and regions, particularly influenced by their economic development levels. This variation underscores the necessity of enhancing dietary structures to mitigate chronic disease prevalence and foster overall health.

In 2023, there were approximately 750.5 deaths by all causes per 100,000 inhabitants in the United States. This statistic shows the death rate for all causes in the United States between 1950 and 2023. Causes of death in the U.S. Over the past decades, chronic conditions and non-communicable diseases have come to the forefront of health concerns and have contributed to major causes of death all over the globe. In 2022, the leading cause of death in the U.S. was heart disease, followed by cancer. However, the death rates for both heart disease and cancer have decreased in the U.S. over the past two decades. On the other hand, the number of deaths due to Alzheimer’s disease – which is strongly linked to cardiovascular disease- has increased by almost 141 percent between 2000 and 2021. Risk and lifestyle factors Lifestyle factors play a major role in cardiovascular health and the development of various diseases and conditions. Modifiable lifestyle factors that are known to reduce risk of both cancer and cardiovascular disease among people of all ages include smoking cessation, maintaining a healthy diet, and exercising regularly. An estimated two million new cases of cancer in the U.S. are expected in 2025.

Laos LA: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data was reported at 31.400 % in 2016. This records a decrease from the previous number of 33.000 % for 2015. Laos LA: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data is updated yearly, averaging 36.250 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 53.300 % in 2000 and a record low of 31.400 % in 2016. Laos LA: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

Ghana GH: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data was reported at 47.500 % in 2016. This records a decrease from the previous number of 48.400 % for 2015. Ghana GH: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data is updated yearly, averaging 51.400 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 65.900 % in 2000 and a record low of 47.500 % in 2016. Ghana GH: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ghana – Table GH.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

From 2018 to 2019, around 3,110 individuals in the United States died due to binge eating disorder, while another 3,430 died due to other specified feeding and eating disorders. This statistic illustrates the total number of deaths in the United States due to eating disorders from 2018 to 2019, by condition.

Cambodia KH: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data was reported at 23.034 % in 2019. This records a decrease from the previous number of 27.078 % for 2015. Cambodia KH: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data is updated yearly, averaging 30.154 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 52.752 % in 2000 and a record low of 23.034 % in 2019. Cambodia KH: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cambodia – Table KH.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

this graph was created in R:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2F99ddcc7060665597ad9b1c263aa8174d%2Fgraph1.gif?generation=1717872782993200&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Ff7af5fc372d601a18645c41c37411157%2Fgraph2.gif?generation=1717872788516258&alt=media" alt="">

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fc85d9de1d5b88949298afa0bab1d9406%2Fgraph3.gif?generation=1717872793749722&alt=media" alt="">

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.

The leading causes of death in the United States are by far cardiovascular diseases and cancer. However, the death rates from these diseases, as well as other leading causes of death, have decreased over the past few decades. The one major exception are deaths caused by Alzheimer’s disease, which have increased significantly. Cardiovascular disease deaths Although cardiovascular diseases are currently the leading cause of death in the United States, the death rate of these diseases has dropped significantly. In the year 1950, there were around *** deaths per 100,000 population due to cardiovascular diseases. In the year 2022, this number was ***** per 100,000 population. Risk factors for heart disease include smoking, poor diet, diabetes, obesity, stress, family history, and age. Alzheimer’s disease deaths While the death rates for cardiovascular disease, cancer, diabetes, and chronic lower respiratory diseases have all decreased, the death rate for Alzheimer’s disease has increased. In fact, from the year 2000 to 2021, the death rate from Alzheimer’s disease rose an astonishing *** percent. This increase is in part due to a growing aging population.

The National Health and Nutrition Examination Survey I Epidemiologic Followup Study (NHEFS) originated as a joint project between the National Center for Health Statistics (NCHS) and the National Institute on Aging (NIA). The design of NHEFS, which contains follow-up data on the NHANES I cohort, consisted of five steps. The first step focused on tracing and locating all subjects in the cohort or their proxies and determining their vital status. The second step involved the obtaining of death certificates for subjects who were deceased. Interviews with the participants or their proxies constituted the third phase of the follow-up. The fourth phase of the follow-up included measurements of pulse, blood pressure, and weight for interviewed respondents, and the fifth step was the acquisition of relevant hospital and nursing home records, including pathology reports and electrocardiograms. The respondent interview was designed to gather information on selected aspects of the subject's health history since the time of the NHANES I exam. This information included a history of the occurrence or recurrence of selected medical conditions, an assessment of behavioral, social, nutritional, and medical risk factors believed to be associated with these conditions, and an assessment of various aspects of functional status. Whenever possible, the questionnaire was designed to retain item comparability between NHANES I and NHEFS in order to measure change over time. However, questionnaire items were modified, added, or deleted when necessary to take advantage of recent improvements in questionnaire methodology. The Vital and Tracing Status file is a master file containing tracing, vital status, and demographic data for all NHEFS respondents. In addition, it provides users with information on the availability of different survey components for each respondent. For example, variables have been created to indicate whether a death certificate was received for a deceased subject, hospital records were received, or a follow-up interview was completed. The Health Care Facility Record file offers data on respondents who had reported an overnight stay in a health care facility after 1970. Information on the name and address of the facility, the date of the stay, and the reason for the stay was recorded. The Mortality Data file contains death certificate information for 1,935 NHEFS decedents. The death certificate information is for deaths occurring from 1971 to 1983.

Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) in Japan was reported at 10.3 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Japan - Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

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 statistic depicts the number of direct deaths from eating disorders in the U.S. from 1990 to 2019. According to the data the yearly number of deaths has increased from 22 in 1990 to 41 in 2019.

Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) in World was reported at 18.41 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

BackgroundPrevious studies have shown that increasing the frequency of eating is beneficial in terms of cardiovascular metabolic risk factors; however, limited evidence is available for the association between daily eating frequency and mortality, especially in people with diabetes. Therefore, we aimed to explore the association between eating frequency and long-term mortality in populations with diabetes.MethodsWe selected 4,924 individuals suffering from diabetes (mean age: 57.77 years; 51.3% men) from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2014. Daily eating frequency was used as the exposure factor in this study. We extracted the mortality data from the National Death Index records and matched them with the population of NHANES. All participants were followed up from the date of getting enrolled in NHANES to 31 December 2015. Multivariate Cox proportional hazards regression, Kaplan–Meier survival curves, and restricted cubic spline were used to assess the associations between eating frequency and all-cause and cause-specific mortality among people with diabetes.ResultsDuring 34,950 person–years of follow-up, 1,121 deaths were documented, including 272 cardiovascular disease (CVD)-related deaths and 156 cancer-related deaths. After adjusting for confounding factors, the daily eating frequency was linearly inversely associated with all-cause and CVD-related mortality, and the HR (95% CIs) for per one-time increment of eating frequency was 0.88 (0.80–0.98) and 0.77 (0.63–0.93), respectively. Sensitivity analyses showed that the main results and statistical significance were still stable.ConclusionHigher eating frequency was independently related to lower all-cause and CVD-related mortality in people with diabetes, which can be used as a potential strategy for daily-diet management among populations suffering from diabetes.

2.1 Experimental insects A laboratory colony of T. castaneum maintained at the USDA Center for Grain and Animal Health Research for over 30 years free of exposure to insecticide was used for these studies. The colony was kept in 0.95-L glass jars with filter paper lids for air flow with a rearing diet consisting of 95% unbleached, organic flour with 5% brewer's yeast added. Jars were held in an environmental chamber set at a temperature of 30 °C, relative humidity (RH) of 65%, and a 16:8 h light/dark photoperiod. 2.2 Manipulating diet nutritional quality Unbleached, organic wheat flour was mixed with microcrystalline cellulose (Thermo Fisher Scientific, Waltham, MA, USA), a nonnutritive and nontoxic filler that has a similar particle size to wheat flour to produce three diet treatments that differed in nutritional quality: 0% flour (0 flour:100 cellulose), 25% flour (25:75), and 100% flour (100:0). A treatment with no flour or cellulose was also included, as a no-food control. 2.3 Long-lasting insecticide-incorporated polyethylene netting Two types of Long-lasting insecticide-incorporated nettings (LLINs), both commercially labeled in the USA, were used: CarifendTM (BASF, Ludwigshafen, Germany) and D-TerrenceTM (Vestergaard, Lausanne, Switzerland),. Carifend netting incorporated 0.34% (w/w) α-cypermethrin while D-Terrence netting incorporated 0.4% (w/w) deltamethrin. Control netting was physically identical to the Carifend netting or D-Terrence netting but lacked any insecticide. 2.4 Effects of diet on recovery of T. castaneum adults after exposure to LLIN The netting was cut into squares and secured to the bottoms of square Petri dishes (100 × 100 × 15 mm, L × W × H, VWRTM, Radnor, PA, USA) with double-sided tape and label tape. 20 mixed-sex adults (2- to 3-week-old) were exposed to one of the three netting types (Carifend, D-Terrence, and control) for 2, 24, 48, 72, 96, 120, 144, and 168 h, respectively, with a total of 24 combinations of netting and exposure time treatment. Immediately following exposure, 20 adults were examined for health condition (unaffected, affected and dead) and transferred from the netting arena to recovery arenas. Recovery arenas were Petri dishes (35 × 10 mm, D × H, FalconTM, Franklin Lakes, NJ, USA) with 0.5 g of one of the three flour:cellulose diets (0:100, 25:75, and 100:0)). In addition, arenas without any food were also included as controls. There were 4 replicates for each combination of netting × exposure time × diet. The condition of T. castaneum were assessed as number of unaffected, affected and dead at 0, 1, 2, 3, 4, 5, 6, and 7 d post-exposure to netting. Adults were recorded as unaffected if they were active and behaving normally with coordinated walking and species-specific movements; affected if they had uncoordinated walking and sluggish movements or were on their backs with legs twitching, and/or could not right themselves after being prodded (i.e., knocked down); finally, dead if they were completely motionless even after prodding. During exposure and recovery, insects were kept in an environmental chamber under the same conditions as described above. Because no T. castaneum adults were observed to be affected and the number of dead was very low after exposure to control netting (Fig. 1), recovery experiments on control netting were not included in rest of the study. 2.5 Effects of diet and netting exposure on mobility of T. castaneum adults Eighteen newly emerged (≤ 2-day-old), mixed-sex adults that had been reared on standard lab diet were transferred to 0.5 g of one of the assigned diets (0:100, 25:75, and 100:0 flour:cellulose) in Petri dishes (35 × 10 mm, D × H, FalconTM, Franklin Lakes, NJ, USA) for one week. As above, there was also a no food treatment as a control. After the one-week time period, 18 adults from each of the diet treatments were exposed to netting (Carifend, D-Terrence, or control) for 10, 30, 60, or 90 min. Only adults rated as unaffected or affected (e.g., not dead) were further evaluated for impacts on mobility. Immediately following the exposure, adults were recorded for a 30-min period using a video-tracking apparatus combined with Ethovision Software (v.16.0, Noldus, Inc., Leesburg, VA, USA). The equipment was set up to track 6 arenas simultaneously, within each arena a single adult was measured. A piece of white filter paper (85 mm, Ahlstrom-Munksjö, Mt. Holly Springs, PA, USA) was taped to the bottom of Petri dishes (100 × 15 mm, D × H, VWRTM, Radnor, PA, USA). The Petri dishes were affixed with white foamboard 80 cm below a network camera (GigE, Basler AG, Ahrenburg, Germany) and backlit with a LED light box (42 × 30 cm, W × L, LPB3, Litup, Shenzhen, China). The program calculated the total distance moved (cm), and the mean instantaneous velocity (cm/s) over the 30 min period for each adult. In total, there were 18 replicates for each of the treatment combinations (netting × exposure time × diet).

Finland FI: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data was reported at 1.300 % in 2016. This records an increase from the previous number of 1.200 % for 2015. Finland FI: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data is updated yearly, averaging 1.600 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 6.900 % in 2000 and a record low of 1.200 % in 2015. Finland FI: Cause of Death: by Communicable Diseases & Maternal, Prenatal & Nutrition Conditions: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Finland – Table FI.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

Death rate has been age-adjusted to the 2000 U.S. standard population. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Coronary heart disease is a type of heart disease in which the arteries of the heart cannot deliver enough oxygen-rich blood to the heart muscles. Over time, this can weaken the heart muscle and may lead to heart attack or heart failure. It is the most common type of heart disease in the US and has been the leading cause of death in Los Angeles County for the last two decades. Poor diet, sedentary lifestyle, tobacco exposure, and chronic stress are all important risk factors for coronary heart disease. Cities and communities can mitigate these risks by improving local food environments and encouraging physical activity by making communities safer and more walkable.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This thesis studies the effect of US wheat aid on infant mortality rates in developing countries. There is debate on the effectiveness of US food aid; some claim it disrupts local food production, while others discuss its role in prolonging conflict. This paper aims to address the intended impact of food aid, feeding people, rather than unintended impacts tackled by previous studies. Infant mortality rates serve as a measure of the health of pregnant woman and infants, who make up a vulnerable population that is susceptible to food crises. An instrumental variable approach is taken, which uses lagged US wheat production, a country’s tendency to receive any US food aid, a rainshock variable, population, and a measure of intrastate conflict, to determine the impact of wheat aid on infant mortality rates in recipient countries. As shown by the results, infant mortality rates decrease with more US wheat aid, which is conducive to the goals of food aid set out by USAID. Specifically, a 100% increase in US food aid, decreases infant mortality rates by 19.3 deaths per 1,000 live births. Furthermore, the effect of US wheat aid on infant mortality rates is strongest in countries that are more likely to receive aid compared to those with a below average propensity to receive US food aid.