An Analysis of Food Insecurity in Pakistan: Prevalence of Undernourishment (PoU) and Food Insecurity Experience Scale (FIES)

Abstract

This study covers only SDG target 2.1 (2.1.1-Prevalance of Undernourishment and 2.1.2-Food Insecurity Experience Scale). Though FAO is the custodian organization for estimating these targets across the globe, however, it is the first ever attempt for estimating these targets by PARC-MNFS&R. HIES data for the year 2018-19 has been used for estimation of these targets and compared with the results of HIES-2015-16 estimated by FAO. According to the results 18.38 percent households are undernourished in Pakistan and this situation is worse in urban areas (23.43%) compared with rural areas (16.61%). Punjab has highest proportion of undernourished individuals/households with 21.48 percent followed by Sindh province with 17.40 percent households. Khyber Pakhtunkhwa has the lowest proportion of 12.67 percent and Baluchistan with 16.95 percent households. National level results of FIES supports the results of PoU except urban/rural order. According to FIES results, about 16 percent of the households (individuals) are moderate and/or severe food insecure with more than 02 percent as severe food insecure in Pakistan. Sindh province shows highest proportion with more than 19 percent followed by KP province with nearly 17 percent households as moderate and severe food insecure. However, highest proportions of more than 03 percent households were found as severe food insecure in Punjab province. In conclusion Pakistan has shown tremendous achievements towards the Zero Hunger Targets by 2030, however, more efforts are needed for sustainable agriculture and food system in order to address the food insecurity level through better access and availability of food. Awareness campaign about healthy and nutritious food intake, and measures for adoption of dietary guidelines are recommended for preventing undernourishment.

Optimizing spatio-temporal correlation structures for modeling food security in Africa: a simulation-based investigation

“…In order to maintain consistency and facilitate comparisons between countries, the FIES Survey Module is implemented among nationally representative samples of the adult population. This standardized approach ensures that data on food insecurity is collected in a uniform manner across different nations [ 16 ].…”

“…Afridi, Jabbar [ 16 ] highlighted the significance of utilizing a convergence of evidence strategy, which involves the use of multiple metrics, to identify the key factors associated with food security and nutrition. The initial set of 40 variables sourced from the FAO dataset underwent Principal Components Analysis (PCA).…”

A bayesian spatio-temporal dynamic analysis of food security in Africa

“…Using adult samples within each country, FAO then calibrates the national FIES findings to a single standardized global scale. This calibration process ensures that food insecurity metrics can be comparatively evaluated at an international level 27 . To address missing values in the dataset, we employed missForest, a random forest technique, detailed in our previous work 28 .…”

Adaptation Implications of Climate-Smart Agriculture in Rural Pakistan

“…Climate change and extreme weather events are major threats to agriculture around the world, especially in South Asian countries. Climate variability induces challenges to achieving food security, poverty reduction, and rural development in these countries due to the vagaries of weather [6,7] and other natural disasters such as extreme temperatures, extremely erratic rainfall, floods and droughts, dust cyclones, pest infestation, and crop diseases coupled with low adoption rates of new technologies [8]. Variations in climate have a significant impact on water resources, agriculture production, food supply, farmers' wellbeing, and finally the global economy [9].…”