Interest in Receiving Nutrition Information Through Social Media Among Food-Security Program Participants in Washington, DC

Nutrition knowledge and health vulnerability of mothers of pre-school children in north-central, Nigeria

OBJECTIVE

This study explores the contribution of nutrition knowledge to the health status of pre-school children's mothers in Niger State, North-Central, Nigeria.

DESIGN

The study is a descriptive cross-sectional design using a quantitative data collection method.

SETTING/PARTICIPANTS

A multi-stage sampling technique was used to recruit 450 mothers of pre-school children across Niger state, Nigeria. Chi-square and linear regression were used to test the level of statistical significance (at p < 0.05). Socioeconomic and demographic information, anthropometric indices and nutrition knowledge were obtained using semi-structured questionnaires. Feeding patterns were also assessed using a qualitative 7-day dietary recall.

RESULT

The results showed that the majority (63.8%) of the mothers were within 26-35 years, and more than half (51.6%) of the mothers lacked knowledge of a "balanced diet". Fruits, vegetables, and dairy products were the least consumed food group among the mothers (7.1% and 9.1%, respectively). Place of residence, occupation, and method of waste disposal were significantly associated with maternal minimum dietary diversity adequacy (p<0.05). Over half (57.6%) of the mothers were within the normal BMI range, and the mean waist/hip ratio was 0.82± 0.08. Social media/online was the most (36.4%) explored source of nutrition information among the mothers. This study shows no significant association between nutrition knowledge and adequacy of minimum dietary diversity among the mothers of preschool children (p = 0.09, χ2 = 13.682).

CONCLUSION

Dietary diversity among mothers was associated with the socioeconomic status and BMI of the mothers, which were strong determinants of meal quality and health outcomes in Nigeria and other developing countries experiencing food insecurity.

Developing an analytical framework for estimating food security indicators in the United Arab Emirates: A review

Rapid population growth, climate change, limited natural resources, and the COVID-19 pandemic contribute to increased global hunger, necessitating intensive efforts to ensure food security and nutrition (FSN). Previous FSN approaches covered some dimensions, but not all, resulting in significant gaps in food security indicators. The Gulf Cooperation Council (GCC) and the Middle East and North Africa (MENA) regions have received less attention in food security studies, thus far necessitating considerable effort to develop an appropriate analytical framework. This study reviewed articles and international reports of FSN indicators, drivers and policies, methods, and models and extracted the challenges and gaps from the global and UAE contexts. The UAE and the world have gaps in FSN drivers, indicators, and methods, necessitating potential solutions to meet future challenges such as rapid population growth, pandemics, and limited natural resources. As a result, we created a newly developed analytical framework that addresses the shortcomings of previous approaches such as sustainable food systems developed by FAO and the Global Food Security Index (GFSI) and covers all aspects of food security. Gaps in knowledge in FSN drivers and policies, indicators, big data, methods, and models were considered in the developed framework, which has specific advantages. The novel developed framework addresses all food security dimensions (access, availability, stability, and utilization), ensuring poverty reduction, food security, and nutrition security while outperforming previous approaches (i.e., FAO and GFSI). The developed framework could be used successfully not only in the UAE and MENA, but also, globally, helping to solve food insecurity and malnutrition for future generations. The scientific community and policymakers should disseminate such solutions to address global food insecurity and ensure nutrition for future generations in the face of rapid population growth, limited natural resources, climate change, and spreading pandemics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10668-023-03032-3.

Food Security Challenges and Resilience during the COVID-19 Pandemic: Corner Store Communities in Washington, D.C

The COVID-19 pandemic exacerbates the complexities of food inequity. As one of the social determinants of health, food insecurity significantly impacts overall health across the life course. Guided by the Getting to Equity Framework, this qualitative community-engaged participatory project examines the impact of the pandemic on food security among adults in Washington, DC. Semi-structured interviews (n = 79) were conducted by trained community health workers between November 2020 and December 2021 at corner stores. Data analysis was performed using thematic network analysis in NVivo. Results are grouped into four key themes: (1) impact of the pandemic on food access, including expanded services and innovative solutions to meet needs; (2) coping and asset-based strategies at the individual and community level; (3) sources of information and support, and (4) impact of the pandemic on health and well-being. The importance of lived experience research in public health is increasingly recognized as an innovative approach that offers benefits through community engagement and empowerment.

Agricultural big data and methods and models for food security analysis-a mini-review

Background

Big data and data analysis methods and models are important tools in food security (FS) studies for gap analysis and preparation of appropriate analytical frameworks. These innovations necessitate the development of novel methods for collecting, storing, processing, and extracting data.

Methodology

The primary goal of this study was to conduct a critical review of agricultural big data and methods and models used for FS studies published in peer-reviewed journals since 2010. Approximately 130 articles were selected for full content review after the pre-screening process.

Results

There are different sources of data collection, including but not limited to online databases, the internet, omics, Internet of Things, social media, survey rounds, remote sensing, and the Food and Agriculture Organization Corporate Statistical Database. The collected data require analysis (i.e., mining, neural networks, Bayesian networks, and other ML algorithms) before data visualization using Python, R, Circos, Gephi, Tableau, or Cytoscape. Approximately 122 models, all of which were used in FS studies worldwide, were selected from 130 articles. However, most of these models addressed only one or two dimensions of FS (i.e., availability and access) and ignored the other dimensions (i.e., stability and utilization), creating a gap in the global context.

Conclusions

There are certain FS gaps both worldwide and in the United Arab Emirates that need to be addressed by scientists and policymakers. Following the identification of the drivers, policies, and indicators, the findings of this review could be used to develop an appropriate analytical framework for FS and nutrition.

Moving Food Assistance into the Digital Age: A Scoping Review

One of the most basic needs globally, food assistance refers to the multitude of programs, both governmental and non-governmental, to improve food access and consumption by food-insecure individuals and families. Despite the importance of digital and mobile Health (mHealth) strategies in food insecurity contexts, little is known about their specific use in food assistance programs. Therefore, the purpose of this study was to address that gap by conducting a scoping review of the literature. Keywords were defined within the concepts of food assistance and digital technology. The search included relevant peer-reviewed and grey literature from 2011 to 2021. Excluded articles related to agriculture and non-digital strategies. PRISMA guidelines were followed to perform a partnered, two-round scoping literature review. The final synthesis included 39 studies of which most (84.6%) were from the last five years and United States-based (93.2%). The top three types of articles or studies included text and opinion, qualitative research, and website, application, or model development (17.9%). The top three types of digital tools were websites (56.4%), smartphone applications (20.5%), and chatbots (5.1%). Nineteen digital features were identified as desirable. Most tools included just one or two features. The most popular feature to include was online shopping (n = 14), followed by inventory management, and client tracking. Digital tools for individual food assistance represent an opportunity for equitable and stable access to programs that can enhance or replace in-person services. While this review identified 39 tools, all are in early development and/or implementation stages. Review findings highlight an overall lack of these tools, an absence of user-centered design in their development, and a critical need for research on their effectiveness globally. Further analysis and testing of current digital tool usage and interventions examining the health and food security impacts of such tools should be explored in future studies, including in the context of pandemics, where digital tools allow for help from a distance.