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The COVID-19 crisis has not only increased socio-economic inequalities globally but it also severely affected people's everyday lives. This study explores the impacts of COVID-19 on household income, food security, and food consumption patterns in the urban slums of Punjab, Pakistan. Using a multistage random sampling method, cross-sectional data was collected from 257 households through face-to-face interviews. Respondents were chosen randomly applying the random walk method. The data were analysed using Probit regression models. The household food security situation was estimated using the food insecurity experience scale (HFIES) developed by the Food and Agriculture Organization (FAO). Results show that household income and food security situations during the COVID-19 pandemic were significantly affected by education level, household size, daily-wage earnings, salaried employment, and household income slot-I. Household participation in social safety programs appears to help mitigate income shocks and decrease food insecurity. Due to the COVID-19 crisis, 73.92% and 54.86% of the surveyed households faced income shocks and worsened food security, respectively. The consumption of meat, poultry products, and seafood decreased by 21.01%, 17.50%, and 14.39%, respectively, during the pandemic, in comparison to the pre-pandemic period. The study recommends that authorities should consider continuously focusing on supporting existing national social safety programs and designing new ones by providing responsive packages during such adversities. Further, structuring robust financial institutions to aid business recovery and to ensure the availability of food to marginalised communities, particularly in urban slums, could sustain the masses. [ABSTRACT FROM AUTHOR]

Agricultural credit is an important tool that can improve farm production, ensure food security, increase household income, and ultimately catalyse rural development. This study examined the factors affecting the credit constraints on farm households in Punjab, Pakistan. A questionnaire was administered, and 519 farm households were recruited from five randomly selected districts of Punjab province. The data were analyzed using a two-step methodology. In the first step, direct elicitation was used to identify the credit constraints of farm households. In the second step, the Probit model was employed to analyze the factors that affect the likelihood of farm households facing credit constraints. The results showed that household head education, farm size, and farm capital had significant negative effects on the presence of credit constraints. The dependency ratio and household consumption expenditures had significant positive effects on farm households' likelihood of being credit constrained. These findings may help to mitigate the removal of farm household credit constraints and improve access to institutional credit, as well as reducing food insecurity and income inequality. The Central Bank of Pakistan should strictly monitor the lending procedures of commercial banks and introduce relaxed policies for new applicants and small landholders. Driving down the interest rate for agricultural businesses and offering loans for improved farm technologies at subsidized rates could be another important policy option. Awareness sessions about lending and repayment procedures should be conducted at the village level. [ABSTRACT FROM AUTHOR]

While individual and family risk factors that contribute to health disparities in children with type 1 diabetes have been identified, studies on the effects of neighborhood risk factors on glycemic control are limited, particularly in minority samples. This cross‐sectional study tested associations between family conflict, neighborhood adversity and glycemic outcomes (HbA1c) in a sample of urban, young Black adolescents with type 1 diabetes(mean age = 13.4 ± 1.7), as well as whether neighborhood adversity moderated the relationship between family conflict and HbA1c. Participants (N = 128) were recruited from five pediatric diabetes clinics in two major metropolitan US cities. Diabetes‐related family conflict was measured via self‐report questionnaire (Diabetes Family Conflict Scale; DFCS). Neighborhood adversity was calculated at the census block group level based on US census data. Indictors of adversity were used to calculate a neighborhood adversity index (NAI) for each participant. Median family income was $25,000, suggesting a low SES sample. In multiple regression analyses, DFCS and NAI both had significant, independent effects on glycemic control (β = 0.174, P = 0.034 and β = 0.226 P = 0.013, respectively) after controlling for child age, family socioeconomic status and insulin management regimen. Tests of effects of the NAI and DFCS interaction on HbA1c found no significant moderating effects of neighborhood adversity. Even within contexts of significant socioeconomic disadvantage, variability in degree of neighborhood adversity predicts diabetes‐related health outcomes in young Black adolescents with type 1 diabetes. Providers should assess social determinants of health such as neighborhood resources that may impact adolescents' ability to maintain optimal glycemic control. [ABSTRACT FROM AUTHOR]