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Food Stamps Are A "Stimulus. Households adopt coping strategies in response to food and income reductions and increased prices following climate shocks. We are not generic; one size does not fit all. Children from the poorest 20 per cent of the population have stunting rates that are double the rate in comparison with the richest quintile. An alternative interface to the PubMed medical literature database. National Institutes of Health and the U. It pools information mainly from national and regional surveys, and studies dealing specifically with the prevalence and duration of breastfeeding and complementary feeding.

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This association is further corroborated by a number of studies that show a strong link between drought and stunting in children. For example, drought events in Bangladesh are associated with a higher stunting rate around five and nine months after the beginning of the drought event.

In rural Zimbabwe, one- to two-year olds exposed to drought face significantly lower growth velocity compared to children of the same age living in areas with average rainfall. In sub-Saharan Africa, warmer and drier climates are related to declining food availability and increased prevalence estimates of childhood stunting. Climate variability and extremes are among the key drivers behind the rise in hunger.

Exposure of countries to climate variability and extremes is also a rising trend. In , the average of the PoU in countries with high exposure to climate shocks was 3. Even more striking is that countries with high exposure have more than doubled the number of undernourished people as those without high exposure. Prevalence unweighted and number of undernourished people in low- and middle-income countries with high and low exposure to climate extremes during the period of — Countries with high exposure are defined as being exposed to climate extremes heat, drought, floods and storms for more than 66 percent of the time, i.

See Annex 2 for the list of countries with high exposure to climate extremes and methodology. The impact of climate variability and extremes on agriculture and food security: Rome, FAO, for classification of countries with high and low exposure to climate extremes; FAO for data on prevalence of undernourishment. A high dependence on agriculture, as measured by the number of people employed in the sector, leaves the PoU 9.

For low-income countries, the increase is equal to The finding is different for middle-income countries where the rise in PoU is less pronounced and occurs later from — This tends to indicate that middle-income countries were able to absorb the impacts of increased exposure to climate extremes, but may not have been able to cope as well in the — period, possibly due to the severity of exposure to El Niño. While hunger is on the rise, it is equally alarming that the number of people facing crisis-level food insecurity continues to increase.

This represents an increase compared to and , when 80 and million people, respectively, faced crisis levels. In 34 of these 51 countries, more than 76 percent of the total populations facing crisis levels of acute food insecurity or worse — nearly 95 million people — were also affected by climate shocks and extremes.

Where conflict and climate shocks occur together, the impact on acute food insecurity is more severe. In , 14 out of the 34 food-crisis countries experienced the double impact of both conflict and climate shocks, which led to significant increases in the severity of acute food insecurity.

Floods cause more climate-related disasters globally than any other extreme climate event, with flood-related disasters seeing the highest increase — 65 percent — in occurrence over the last 25 years. The frequency of storms is not increasing as much as that of floods, but storms are the second most frequent driver of climate-related disasters.

Climate variability and extremes have the strongest direct impact on food availability, given the sensitivity of agriculture to climate and the primary role of the sector as a source of food and livelihoods for the rural poor. However, the overall fallout is far more complex and greater than the impacts on agricultural productivity alone. Climate variability and extremes are undermining all dimensions of food security: Climate variability puts all aspects of food security at risk: Direct and indirect climate-driven impacts have a cumulative effect, leading to a downward spiral of increased food insecurity and malnutrition.

As mentioned, an obvious impact is that climate variability and extremes negatively affect agricultural productivity, in terms of changes in crop yields the amount of agricultural production harvested per unit of land area , cropping areas area planted or harvested , or cropping intensity number of crops grown within a year. The sectors of fisheries, aquaculture and forestry often are under-reported.

Impact of disasters on forestry is generally acknowledged in assessments, although rarely quantified in monetary terms. The impact of disasters and crises on agriculture and food security In addition, climate variability and extremes also affect food imports as countries try to compensate for domestic production losses.

The impacts on production will inevitably translate into loss of income for people whose livelihoods depend on agriculture and natural resources, reducing their ability to access food. Another factor is spikes in food prices and volatility follow climate extremes. Climate anomalies, and in particular extreme events, alter agricultural yields, production and stocks.

Episodes of high food price volatility pose a major threat to food access , especially in low- and middle-income countries and among poorer groups in high-income countries. The impact of price spikes and volatility not only falls heaviest on the urban poor, but also of small-scale food producers, agriculture labourers and the rural poor who are net food buyers. Climate variability and extremes also lead to income loss for those whose livelihoods depend on agriculture and natural resources, which then negatively impact food access as households have less resources to purchase food.

Household studies provide evidence that access to food and income of small family agriculture households is negatively impacted by climate variability and extremes. There is also evidence that climate shocks not only affect the level of income, but affect also the variability of incomes.

Changes in climate also heavily impact nutrition through impaired nutrient quality and dietary diversity of foods produced and consumed; impacts on water and sanitation, with their implications for patterns of health risks and disease; and changes in maternal and child care and breastfeeding. Households adopt coping strategies in response to food and income reductions and increased prices following climate shocks. More erratic rainfall and higher temperatures along with other extreme events affect the quality and safety of food.

Changing climate conditions and extremes such as temperature and humidity can lead to increased contamination of water and food. Even increased contamination of water used for irrigation can affect the safety of crops and animals that consume them, as well as the resulting food output.

Unsafe water and food create a vicious cycle of diarrhoea and malnutrition, threatening the nutritional status of the most vulnerable. Furthermore, climate extremes often directly affect human health through changes in temperature and precipitation and natural hazards. These increase the risk of disease, which further compromises food security and nutrition. Climate-related disasters create and sustain poverty, contributing to increased food insecurity and malnutrition as well as current and future vulnerability to climate extremes.

They also have impacts on livelihoods and livelihoods assets — especially of the poor — contributing to greater risk of food insecurity and malnutrition. Prolonged or recurrent climate extremes lead to diminished coping capacity, loss of livelihoods, distress migration and destitution. Climate resilience is one solution. Addressing climate variability and extremes and their impact on food security and nutrition requires a focus on resilience.

Context-specific interventions aimed at anticipating, limiting, and adapting to the effects of climate variability and extremes and building the resilience of livelihoods, food systems and nutrition to climatic shocks and stresses.

Scaled-up actions across sectors are urgently needed to strengthen the resilience of livelihoods and food systems to climate variability and extremes. Also trafficking may indirectly increase costs by encouraging participants to stay in the program longer than intended, or by incentivizing new participants seeking to profit from trafficking. The FNS aggressively acts to control trafficking by using SNAP purchase data to identify suspicious transaction patterns, conducting undercover investigations, and collaborating with other investigative agencies.

Trafficking has declined over time from nearly 4 percent in the s. Although large stores accounted for Trafficking was much less likely to occur among publicly owned than privately owned stores and was much less likely among stores in areas with less poverty rather than more.

The total annual value of trafficked benefits increased at about the same rate as overall program growth. The current estimate of total SNAP dollars trafficked is higher than observed in the previous — period. This increase is consistent, however, with the almost 37 percent growths in average annual SNAP benefits from the — study periods to the most recent one.

The methodology used to generate these estimates has known limitations. However, given variable data and resources, it is the most practical approach available to FNS. Further improvements to SNAP trafficking estimates would require new resources to assess the prevalence of trafficking among a random sample of stores.

For larger stores supermarkets and large groceries , only 0. In terms of redemptions, about 17 percent of small groceries redemptions and 14 percent of convenience store redemptions were estimated to have been trafficked.

This compares with a rate of 0. These changes will include stiffer penalties for retailers who are caught participating in illegal or fraudulent activities.

SNAP benefit fraud, generally in the form of store employees buying EBT cards from recipients is widespread in urban areas, with one in seven corner stores engaging in such behavior, according to a recent government estimate. There are in excess of , stores, and we have agents spread across the country. According to the Government Accountability Office , at a count, there was a payment error rate of 4. In Maine, incidents of recycling fraud have occurred in the past where individuals once committed fraud by using their EBT cards to buy canned or bottled beverages requiring a deposit to be paid at the point of purchase for each beverage container , dump the contents out so the empty beverage container could be returned for deposit redemption, and thereby, allowed these individuals to eventually purchase non-EBT authorized products with cash from the beverage container deposits.

The State of Utah developed a system called "eFind" to monitor, evaluate and cross-examine qualifying and reporting data of recipients assets. Utah's eFind system is a "back end", web-based system that gathers, filters, and organizes information from various federal, state, and local databases.

This system was developed with federal funds and it is available to other states free of charge. HIP is designed to take place from August to April with the actual operation phase of the pilot program scheduled to last 15 months, from November to January Periodically, proposals have been raised to restrict SNAP benefits from being used to purchase various categories or types of food which have been criticized as "junk food" or "luxury items". However, Congress and the Department of Agriculture have repeatedly rejected such proposals on both administrative burden and personal freedom grounds.

The Food and Nutrition Service noted in that no federal standards exist to determine which foods should be considered "healthy" or not, that "vegetables, fruits, grain products, meat and meat alternatives account for nearly three-quarters of the money value of food used by food stamp households" and that "food stamp recipients are no more likely to consume soft drinks than are higher-income individuals, and are less likely to consume sweets and salty snacks.

They also noted that many urban food stores do a poor job of stocking healthy foods and instead favor high-profit processed items. From Wikipedia, the free encyclopedia. An effort to manage agricultural surpluses , the first food stamps came off the presses April 20, Orange stamps were good for any grocery item the purchaser chose, except drugs, liquor and items consumed on the premises.

Blue stamps bought only surplus foods—dairy products, eggs, citrus fruits, prunes and fresh vegetables. Department of Agriculture official website , March 3, last revised. Accessed March 4, April 1, to July 1, Report. United States Census Bureau. Retrieved 22 January Retrieved 15 December United States department of Agriculture. Retrieved 16 August Retrieved 5 January Dole Institute of Politics. Retrieved 30 October Brookings Institution, , p.

United States Department of Agriculture. To provide for the continuation of agricultural and other programs of the Department of Agriculture through fiscal year , and for other purposes. Library of Congress , undated. Accessed May 20, Retrieved 16 December Retrieved 5 May An Analysis of the Housing and Vacancy Survey". Archived from the original on 5 January Retrieved April 20, Retrieved 2 December Economists consider SNAP one of the most effective forms of economic stimulus.

Similarly, CBO rated an increase in SNAP benefits as one of the two most cost-effective of all spending and tax options it examined for boosting growth and jobs in a weak economy. Center for Budget and Policy Priorititys. Retrieved 12 August Fiscal Year " PDF. Archived from the original PDF on Archived from the original on 7 January Retrieved 18 September Food Policy in the US. Untangling the Self-Selection Effect".

Economic Research Report No. Archived from the original on Assessing Federal Food Aid. AEI Press, p. Archived from the original PDF on 22 June Retrieved 14 December Obama Ag Secretary Vilsack: Food Stamps Are A "Stimulus.

Department of Agriculture, Economic Research Service. Retailers Brace for Reduction in Food Stamps". More Americans selling their food stamps for cash". Detroit-area stores swipe millions from aid program". Department of Agriculture website".

In , more than half of all wasted children lived in South Asia and about one quarter in sub-Saharan Africa, with similar proportions for severely wasted children. Under-five wasting and severe wasting are highly sensitive to change. Thus, estimates for these indicators are only reported for current levels In almost all countries with available data, stunting rates are higher among boys than girls.

While analyses to determine underlying causes for this phenomenon are underway, an initial review of the literature suggests that the higher risk for preterm birth among boys which is inextricably linked with lower birth weight is a potential reason for this sex-based disparity in stunting.

Analysis is based on a subset of 92 countries with recent data by wealth quintile groupings covering 69 per cent of the global population. Children from the poorest 20 per cent of the population have stunting rates that are double the rate in comparison with the richest quintile. In South Asia, the absolute disparities between the richest and poorest children in regard to stunting are greater than in any other region. While the overall rates are lower, the relative disparities are greatest in Latin America and the Caribbean where the rate among the poorest is more than 4 times higher than among the richest.

An analysis of 54 countries with comparable trend data between around and around shows that gaps between the poorest 20 per cent and richest 20 per cent of children under five have closed by at least 20 per cent in the majority of upper-middle-income countries. However, in almost all low income countries, this gap has either remained the same or increased.

Blencowe H et al. Preterm birth—associated neurodevelopmental impairment estimates at regional and global levels for Pediatric Research Volume No s1, December Please note that some children can suffer from more than one form of malnutrition — such as stunting and overweight or stunting and wasting. There are currently no joint global or regional estimates for these combined conditions, but UNICEF has a country-level dataset with country level estimates, where re-analysis was possible.

Prevalence of stunting, wasting and overweight among children under 5 is estimated by comparing actual measurements to an international standard reference population. The new standards are the result of an intensive study project involving more than 8, children from Brazil, Ghana, India, Norway, Oman and the United States. Overcoming the technical and biological drawbacks of the old reference population, the new standards confirm that children born anywhere in the world and given the optimum start in life have the potential to reach the same range of height and weight.

The new standards should be used in future assessments of child nutritional status. It should be noted that because of the differences between the old reference population and the new standards, prevalence estimates of child anthropometry indicators based on these two references are not readily comparable.

It is essential that all estimates are based on the same reference population preferably the new standards when conducting trend analyses. Before conducting trend analyses of child nutritional status, it is important to ensure that estimates from various data sources are comparable over time.

For example, household surveys in some countries in the early s only collected child anthropometry information among children up to 47 months of age — or even up to only 35 months of age. Prevalence estimates based on such data only referred to children under 4 or under 3 years of age and are not comparable to prevalence estimates based on data collected from children up to 59 months of age.

Some age adjustment needs to be applied to make these estimates based on non-standard age groups comparable to those based on the standard age range.

For more information about age adjustment, please click here to read a technical note. In addition, prevalence estimates need to be calculated according to the same reference population. For more information about the difference between the two references and its implications, please click here to read a series of questions and answers.

When data collection begins in one calendar year and continues into the next, the survey year assigned is the one in which most of the fieldwork took place.

For example, if a survey was conducted between 1 September and 28 February , the year would be assigned, since the majority of data collection took place in that year i.

This method has been used since the edition prior to that, the latter year was used by default — e. As of the edition, the country-level dataset used to generate the global and regional joint malnutrition estimates is based only on final survey results.

Preliminary survey results are no longer included in the dataset since the data are sometimes retracted or change significantly when the final version is released.

Country-level progress in reducing undernutrition prevalence is evaluated by calculating the average annual rate of reduction AARR and comparing this to the AARR needed in order to achieve targets. Estimation of regional and global trends is based on a multilevel modelling method see de Onis et al. For the most recent trend analysis, a total of data points from countries over the period to were included in the model.

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