COVID-19 Pandemic, Determinants of Food Insecurity, and Household Mitigation Measures: A Case Study of Punjab, Pakistan.
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ABSTRACT:
SUBMITTER: Shahzad MA
PROVIDER: S-EPMC8224546 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Food insecurity is a major concern for the developing world and around 37% of the population of Pakistan is food insecure. This paper utilizes the Food Insecurity Experience Scale (FIES) to assess the population prevalence of food insecurity and to identify their risk factors and determinants at the household level in Pakistan. This study employs a multi-level random coefficient model, using the Pakistan Panel Household Survey (PPHS-2010) dataset; representative data from 4,130 households. Factors like; income of the household, gender, education, household size, land ownership, and shocks of food insecurity allow the incidence of idiosyncratic shocks (injuries and/or casualties) at the community level, which affects the food insecurity situation of the community, rather differently were included. The study confirms a statistically significant inverse relationship between household income, household size, and household head education with food insecurity and a positive association of shocks and inflation with food insecurity at the household level. Specifically, with increasing per capita income of the household, food insecurity declines (coefficient: -0.083, statistically significant at 1%) and food insecurity increases with shocks (coefficient: 0.058, statistically significant at 1% significance level). The study also reveals a significant heterogeneity at a one percent significance level in the determinants of food insecurity at the district, community, and household levels. The income of the household, household head gender and education level, household size, household assets, shocks, injuries, and inflationary pressure are important determinants of food insecurity in Pakistan.
| S-EPMC10553256 | biostudies-literature
Project description:Background: With millions of people experiencing malnutrition and inadequate water access, FI and WI remain topics of vital importance to global health. Existing unidimensional FI and WI metrics do not all capture similar multidimensional aspects, thus restricting our ability to assess and address food- and water-related issues. Methods: Using the Sanitation, Hygiene and Infant Nutrition Efficacy (SHINE) trial data, our study conceptualizes household FI (N = 3551) and WI (N = 3311) separately in a way that captures their key dimensions. We developed measures of FI and WI for rural Zimbabwean households based on multiple correspondence analysis (MCA) for categorical data. Results: Three FI dimensions were retained: 'poor food access', 'household shocks' and 'low food quality and availability', as were three WI dimensions: 'poor water access', 'poor water quality', and 'low water reliability'. Internal validity of the multidimensional models was assessed using confirmatory factor analysis (CFA) with test samples at baseline and 18 months. The dimension scores were associated with a group of exogenous variables (SES, HIV-status, season, depression, perceived health, food aid, water collection), additionally indicating predictive, convergent and discriminant validities. Conclusions: FI and WI dimensions are sufficiently distinct to be characterized via separate indicators. These indicators are critical for identifying specific problematic insecurity aspects and for finding new targets to improve health and nutrition interventions.
| S-EPMC8199942 | biostudies-literature
Project description:BackgroundIn England, the responsibility to address food insecurity lies with local government, yet the prevalence of this social inequality is unknown in small subnational areas. In 2018 an index of small-area household food insecurity risk was developed and utilised by public and third sector organisations to target interventions; this measure needed updating to better support decisions in different settings, such as urban and rural areas where pressures on food security differ.MethodsWe held interviews with stakeholders (n = 14) and completed a scoping review to identify appropriate variables to create an updated risk measure. We then sourced a range of open access secondary data to develop an indices of food insecurity risk in English neighbourhoods. Following a process of data transformation and normalisation, we tested combinations of variables and identified the most appropriate data to reflect household food insecurity risk in urban and rural areas.ResultsEight variables, reflecting both household circumstances and local service availability, were separated into two domains with equal weighting for a new index, the Complex Index, and a subset of these to make up the Simple Index. Within the Complex Index, the Compositional Domain includes population characteristics while the Structural Domain reflects small area access to resources such as grocery stores. The Compositional Domain correlated well with free school meal eligibility (rs = 0.705) and prevalence of childhood obesity (rs = 0.641). This domain was the preferred measure for use in most areas when shared with stakeholders, and when assessed alongside other configurations of the variables. Areas of highest risk were most often located in the North of England.ConclusionWe recommend the use of the Compositional Domain for all areas, with inclusion of the Structural Domain in rural areas where locational disadvantage makes it more difficult to access resources. These measures can aid local policy makers and planners when allocating resources and interventions to support households who may experience food insecurity.
| S-EPMC9733884 | biostudies-literature
Project description:ObjectiveThe objective was to examine risk and protective factors associated with pre- to early-pandemic changes in risk of household food insecurity (FI).DesignWe re-enrolled families from two statewide studies (2017-2020) in an observational cohort (May-August 2020). Caregivers reported on risk of household FI, demographics, pandemic-related hardships, and participation in safety net programs (e.g. CARES stimulus payment, school meals).SettingMaryland, United States.ParticipantsEconomically, geographically, and racially/ethnically diverse families with preschool to adolescent-age children. Eligibility included reported receipt or expected receipt of the CARES stimulus payment or a pandemic-related economic hardship (n=496).ResultsPrevalence of risk of FI was unchanged (pre-pandemic: 22%, early-pandemic: 25%, p=0.27). Risk of early-pandemic FI was elevated for non-Hispanic Black (aRR=2.1 [95% CI 1.1, 4.0]) and Other families (aRR=2.6 [1.3, 5.4]) and families earning ≤300% federal poverty level. Among pre-pandemic food secure families, decreased income, job loss, and reduced hours were associated with increased early-pandemic FI risk (aRR=2.1 [1.2, 3.6] to 2.5 [1.5, 4.1]); CARES stimulus payment (aRR=0.5 [0.3, 0.9]) and continued school meal participation (aRR=0.2 [0.1, 0.9]) were associated with decreased risk. Among families at risk of FI pre-pandemic, safety net program participation was not associated with early-pandemic FI risk.ConclusionsThe CARES stimulus payment and continued school meal participation protected pre-pandemic food secure families from early-pandemic FI risk but did not protect families who were at risk of FI pre-pandemic. Mitigating pre-pandemic FI risk and providing stimulus payments and school meals may support children's health and reduce disparities in response to pandemics.
| S-EPMC8943228 | biostudies-literature
Project description:Faisalabad is a major industrial area in Pakistan's Punjab province that discharges wastewater into the Chenab River. Industrial effluents in Faisalabad are predicted to pose a significant threat to the riparian vegetation of the Chenab River and nearby vegetation. Heavy metal pollution of plants, water, and soils is one of the biggest problems worldwide that needs to be addressed because heavy metals above normal levels are extremely dangerous to both riparian vegetation and wildlife. The results indicated high levels of pollution in the industrial effluents as well as in the river in terms of salinity, metal toxicity, TSS, TDS, SAR, the acidic and alkaline nature of the industrial effluents, and the spread of industrial effluents up to 15 square kilometres in the Chenab River. Despite the higher pollution, four plants were found at all sites: Calotropis procera, Phyla nodiflora, Eclipta alba and Ranunculus sceleratus. It was found that most of the selected plants were phytoaccumulators, making them best suited to survive in harsh environments such as those with industrial pollution. The Fe concentration in the plant constituents was the highest, along with Zn, Pb, Cd, and Cu, all of which were above the permissible limits of the WHO. The metal transfer factor (MTF) was higher in most of the plants studied, and even exceeded 10 at some severely affected sites. Calotropis procera proved to be the most suitable plant for growth on drainage systems and also at river sites, as it had the highest importance value across all sites and seasons.
| S-EPMC10314743 | biostudies-literature
Project description:The experience of a downward change in one's financial situation is so common that most consumers will experience it during their lifetime, and this prevalence has been compounded by the recent COVID-19 pandemic. Limited research, however, has examined the impact of economic hardship on consumers' food-related behavior. Using a sample of Canadians and Americans (n = 519; Mage = 38.4; SDage = 13.6; 46.2% female; 85% lived alone), we identify that economic hardship significantly and negatively predicts consumer food waste behavior, such that economic hardship leads consumers to waste less food. Conversely, we also identify a positive indirect effect wherein economic hardship positively predicts ontological insecurity (i.e., the aversive feeling of being overwhelmed and out of control), which in turn positively predicts overconsumption (e.g., overstocking one's fridge or pantry) and in turn predicts higher food waste. This preliminary work opens the door to future work exploring a potentially rich avenue of research on the implications of adverse economic events on consumer food choice, consumption, and disposal. Implications for research and practice are discussed.
| S-EPMC9759702 | biostudies-literature
Project description:IntroductionNumerous natural and man-made factors have afflicted Ethiopia, and millions of people have experienced food insecurity. The current cut-points of the WFP food consumption score (FCS) have limitations in measuring the food insecurity level of different feeding patterns due to the diversified culture of the society. The aim of this study is to adapt the WFP food security score cut-points corrected for the different feeding cultures of the society using effect-driven quantile clustering.MethodThe 2012, 2014, and 2016 Ethiopian socio-economic household-based panel data set with a sample size of 3,835 households and 42 variables were used. Longitudinal quantile regression with fixed individual-specific location-shift intercept of the free distribution covariance structure was adopted to identify major indicators that can cluster and level quantiles of the FCS.ResultHousehold food insecurity is reduced through time across the quintiles of food security score distribution, mainly in the upper quantiles. The leveling based on effect-driven quantile clustering brings 35.5 and 49 as the FCS cut-points corrected for cultural diversity. This corrected FCS brings wider interval for food insecure households with the same interval range for vulnerable households, where the WFP FCS cut-points under estimate it by 7 score. Education level, employment, fertilizer usage, farming type, agricultural package, infrastructure-related factors, and environmental factors are found to be the significant contributing factors to food security. On the other hand, the age of the head of the household, dependency ratio, shock, and no irrigation in households make significant contributions to food insecurity. Moreover, households living in rural areas and farming crops on small lands are comparatively vulnerable and food insecure.ConclusionMeasuring food insecurity in Ethiopia using the WFP FCS cut-off points underestimates households' food insecurity levels. Since the WFP FCS cut-points have universality and comparability limitations, there is a need for a universally accepted local threshold, corrected for local factors those resulted in different consumption patterns in the standardization of food security score. Accordingly, the quantile regression approach adjusts the WFP-FCS cut points by adjusting for local situations. Applying WFP cut-points will wrongly assign households on each level, so the proportion of households will be inflated for the security level and underestimated for the insecure level, and the influence of factors can also be wrongly recommended the food security score for the levels. The quantile clustering approach showed that cropping on a small land size would not bring about food security in Ethiopia. This favors the Ethiopian government initiative called integrated farming "ኩታ ገጠም እርሻ" which Ethiopia needs to develop and implement a system that fits and responds to this technology and infrastructure.
| S-EPMC10365274 | biostudies-literature
Project description:This study examined the burden of food insecurity in India's un-notified slums, using an SDG framework to identify correlates of food insecurity. A convenience sampling approach was employed in selecting 38 slums from 675 un-notified slums across four geographic zones. Ten percent of the households in each slum site were selected from each zone, and one household member was interviewed, based on their availability and fulfilment of the eligibility criteria. Eligible individuals included those aged 18 years and above, who were resident in the selected slums and provided consent. Individuals with mental or physical challenges were excluded. A total sample of 907 study participants were included. Results showed that 43% (n = 393) of the participants were food insecure. More than half were females (73%, n = 285), who had not completed any schooling (51%, n = 202). One-third (n = 128) resided in the Northern Region of Delhi. SDG-related predictors of food insecurity included: household educational level (SDG 4 Quality education) (p = 0.03), coverage of health service needs (SDG 3 Good health and well-being) (p = 0.0002), electricity needs (SDG 7 affordable and clean energy) (p<0.0001), and employment needs (SDG 8 Decent and economic growth) (p = 0.003). Having healthcare needs that were partially or fully met was equally associated with higher food insecurity: this could be attributed to high healthcare costs and the lack of federal subsidies in un-notified slums, collectively contributing to high out-of-pocket health costs. Failure to fully meet employment needs was also significantly associated with higher food insecurity. However, met needs for electricity, finance, women's safety and satisfactory family relationships, were associated with lower food insecurity. Household predictors of food insecurity included: number of household members, and the presence of physically disabled household members. Necessary interventions should include connecting food insecure households to existing social services such as India's Public Distribution System, and multi-sector partnerships to address the existing challenges.
| S-EPMC6445475 | biostudies-literature
Project description:The coronavirus disease (COVID-19) pandemic has increased unemployment and food insecurity in the United States (US). Prior to the pandemic, college students exhibited higher rates of food insecurity than nonstudent households. The objectives of this study were to assess the prevalence and determinants of food insecurity among college students during the COVID-19 pandemic. We administered an online survey to 651 students on three diverse campuses at a state-funded university in Texas, US, in May 2020. Food security was assessed using a multistep approach that included the 2-item Food Sufficiency Screener and 6-Item USDA Food Security Survey Module (FSSM). Overall, 34.5% of respondents were classified as food insecure within the last 30 days. The strongest predictors of food insecurity were change in current living arrangement (OR = 2.70, 95% CI: 2.47, 2.95), being furloughed (OR = 3.22, 95% CI: 2.86, 3.64), laid off (OR = 4.07, 95% CI: 3.55, 4.66), or losing part-time work (OR = 5.73, 95% CI: 5.09, 6.46) due to the COVID-19 pandemic. These findings highlight the high prevalence of food insecurity among college students during the COVID-19 pandemic, with students who experienced housing insecurity and/or loss of income due to the pandemic being impacted the most.
| S-EPMC7551032 | biostudies-literature
Project description:We aimed to explore experiences of government-led actions on the social determinants of food insecurity during Australia's COVID-19 pandemic response (which included novel, yet temporary, social protection measures to support Australians facing hardship during state-wide lockdowns). During November-December 2020, we conducted in-depth interviews with 24 Victorians who received government income support (prior to COVID-19) and the temporary COVID-19 specific payments. Interviews were guided by a theoretical understanding of the social determinants of health and health inequities, which we aligned to the social policy context. Data were audio-recorded, transcribed, inductively coded, categorised and thematically analysed. Our sample included mostly women (n = 19) and single parents (n = 13). Interviews reflected four key themes. Firstly, participants described 'battles all around them' (i.e., competing financial, health and social stressors) that were not alleviated by temporary social policy changes and made healthy eating difficult to prioritise during the pandemic. Secondly, housing, income, job, and education priorities rendered food a lower and more flexible financial priority - even with 18 participants receiving temporary income increases from COVID-19 Supplements. Thirdly, given that food remained a lower and more flexible financial priority, families continued to purchase the cheapest and most affordable options (typically less healthful, more markedly price discounted). Finally, participants perceived the dominant public and policy rhetoric around income support policies and healthy eating to be inaccurate and shaming - often misrepresenting their lived experiences, both prior to and during COVID-19. Participants reported entrenched struggles with being able to afford basic living costs in a dignified manner during COVID-19, despite temporary social protection policy changes. To reduce inequities in population diets, a pre-requisite to health, all stakeholders must recognise an ongoing responsibility for adopting long-term food and social policies that genuinely improve lived experiences of food insecurity and poverty.Supplementary informationThe online version contains supplementary material available at 10.1007/s12571-022-01318-4.
| S-EPMC9483265 | biostudies-literature