This study examined access to water, food, and nutrition programs among marginalized communities in Southern Punjab, Pakistan, and their effects on nutrition. Both qualitative and quantitative data were used in this study. We held two focus group discussions (one with 10 males and one with 10 females) and conducted in-depth interviews with 15 key stakeholders, including 20 mothers and 10 healthcare providers. A survey of 235 households was carried out to evaluate water and food insecurity, with the data analyzed using Wilcoxon’s rank-sum test, t-test, and Pearson’s chi-square test. The results revealed that 90% of households experienced moderate-to-severe water insecurity, and 73% faced moderate-to-severe food insecurity. Household water and food insecurity were positively correlated with each other (correlation coefficient = 0.205; p = 0.004). Greater household water (p = 0.028) and food insecurity (p < 0.001) were both associated with higher perceived stress. Furthermore, lower socioeconomic status was strongly related to higher levels of water (p < 0.001) and food insecurity (p < 0.001). Qualitative findings highlight the impact of colonial and post-colonial policies, which have resulted in water injustice, supply issues, and corruption in water administration. Women face significant challenges in fetching water, including stigma, harassment, and gender vulnerabilities, leading to conflicts and injuries. Water scarcity and poor quality adversely affect sanitation, hygiene, and breastfeeding practices among lactating mothers. Structural adjustment policies have exacerbated inflation and reduced purchasing power. Respondents reported a widespread lack of dietary diversity and food quality. Nutrition programs face obstacles such as the exclusion of people with low social and cultural capital, underfunding, weak monitoring, health sector corruption, and the influence of formula milk companies allied with the medical community and bureaucracy. This study concludes that addressing the macro-political and economic causes of undernutrition should be prioritized to improve nutrition security in Pakistan.

Background: There is an abundance of studies explaining the separate impact of female employment and household wealth status in reducing malnutrition. However, our study has unraveled the combined impact of maternal employment and household wealth on undernutrition among children under three in Pakistan. Methods: Using a sample of 1093 children under three years of age from the Pakistan Demographic and Health Survey 2017–2018, a binary logistic model was employed to gauge factors influencing the children’s undernutrition. Results: Our results indicated that children up to a certain age (three years old) with residence in certain regions (Pakistan) and recent episodes of diarrhea had an increased risk of undernutrition. Conversely, secondary and higher maternal education, access to improved water sources, and sanitation facilities lowered the chances of undernutrition in children under three in Pakistan. The interaction between maternal employment and household wealth showed that maternal employment significantly lowered the risk of stunting, being underweight, and wasting among the average, rich, and richest households; however, it did not contribute to child nutrition among the poorer and poor households. Notably, regardless of whether the mother was employed, the wealth status of being rich and richest reduced the risk of stunting, being underweight, and wasting. Conclusions: In overcoming undernutrition, maternal employment significantly contributed to middle-income households. However, in the richer and richest households, the wealth status played a more crucial role compared to the maternal employment. This indicates that while employment plays a supportive role in household resources, the wealth status is overall more influential in reducing undernutrition.

The present study has been carried out using the theoretical framework of Berry's Model of Acculturation developed. This study was planned to explore the effects of acculturative stress on social interaction anxiety as well as the moderating role of perception of teasing among students of other provinces. To carry out this study, a correlational research design was adopted. The data was collected using purposive sampling technique. A sample of 346 university residents from different provinces, aged between 17-27 years (M = 22.31, SD= 1.38) were selected for this study. acculturative stress was measured using acculturative stress scale for international students, social interaction anxiety was measured using social interaction anxiety scale, and perception of teasing was measured using perception of teasing scale. SPSS version 24 and Process by Hayes were used for analysis. The results of correlation analysis show that there is a positive association between acculturative stress and social interaction anxiety. Results of regression analysis reveal that social interaction anxiety significantly predicts acculturative stress among students of other provinces. Results of moderation analysis indicate that perception of teasing acts as moderator between acculturative stress and social interaction anxiety.

The rapid development of artificial intelligence has had a major impact on the creation and consumption of digital content and especially with the advent of AI-created media. This change is affecting the way youth consumers perceive online information and form their opinion of the artificial intelligence technologies. The current research sought to explore how the world of perception of AI-generated media and the attitude to artificial intelligence among Generation Z are connected. The paper also investigated whether digital literacy mediates this relationship. In particular, the study examined the hypotheses that the capacity of the individuals to critically interpret digital content can be viewed as the reason why their attitudes to AI-generated media shape their attitude towards artificial intelligence. This study incorporated a quantitative correlational research design. The research was performed among 300 Generation Z students of public and private universities in Lahore, Pakistan (M = 21.95, SD = 2.41). The perception AI-generated media, digital literacy and attitudes towards artificial intelligence were measured using standardized and reliable measure scales. The data were broken down in SPSS version 26 and PROCESS macro by Hayes. Some of the statistical methods used were descriptive statistics, Pearson correlation, mediation analysis, independent samples t-tests, and one-way ANOVA to test the relationships between variables and demographic differences. The findings revealed that the attitude towards artificial intelligence among the participants of Generation Z depended on perceptions of AI-generated media significantly. Also, digital literacy was positively related to attitudes toward artificial intelligence statistically significantly. The mediation analysis however showed that media perception as generated by AI did not significantly predict digital literacy. Therefore, the mediating effect of digital literacy was not found in the correlation between AI-generated media perception and opinions about artificial intelligence. According to these findings, despite the fact that digital literacy plays a role in developing positive attitudes towards artificial intelligence, the impact of artificial intelligence media perception on artificial intelligence attitudes is more of a direct relationship and not of an indirect relationship of mediating process. The relevance of this research in practice is found in the fact that, in order to teach young people how to find a critical approach toward emerging AI technologies, it is necessary to reinforce the digital literacy education. The originality of this study will be to investigate the direct correlation between media perception of AI-generated media and attitudes towards artificial intelligence as well as the possibility that digital literacy serves as the mediating variable between Generation Z, which has a high exposure to fast-evolving AI-driven media settings.