Revolutionizing the food industry: The transformative power of artificial intelligence-a review.

Artificial Intelligence (AI) is revolutionizing the food industry by optimizing processes, improving food quality and safety, and fostering innovation. This review examines AI's applications in food science, including supply chain management, production, sensory science, and personalized nutrition. It discusses techniques like knowledge-based expert systems, fuzzy logic, artificial neural networks, and machine learning, highlighting their roles in predictive maintenance, quality control, product development, and waste management. The integration of AI with sophisticated sensors enhances real-time monitoring and decision-making in food safety and packaging. However, challenges such as ethical concerns, data security, transparency, and high costs persist. AI is poised to advance sustainability by optimizing resource use, enhance food security through predictive analytics of crop yields, and drive innovation in personalized nutrition and supply chain automation, ensuring tailored products and efficient delivery. This paper underscores AI's transformative potential in the food industry while addressing the obstacles to its widespread adoption.

Association Between Household Food Insecurity and Low Birth Weight: A Population-Based Case-Control Study.

BACKGROUND: Low birth weight (LBW) is a major public health issue associated with increased neonatal morbidity and mortality. This study aimed to examine the association between household food insecurity and LBW in Mashhad, Iran. Study Design: A population-based case-control study. METHODS: This study involved 6294 mothers (3247 cases and 3247 controls) who visited healthcare centers affiliated with Mashhad University of Medical Sciences for term births between March 2019 and March 2022. Cases included women who delivered neonates weighing<2500 g, while controls delivered babies≥2500 g. Food security was measured using the validated Household Food Insecurity Access Scale. Logistic regression models examined the associations between food insecurity and LBW. Geographic information system techniques mapped LBW distribution in Mashhad. RESULTS: Household food insecurity was significantly associated with higher odds of LBW (adjusted odds ratio [AOR]=1.25, 95% confidence interval [CI]: 1.03, 1.53). Other risk factors included younger maternal age (AOR=1.03, 95% CI: 1.01, 1.04), lower maternal education (AOR=0.55, 95% CI: 0.43, 0.71), cesarean delivery (AOR=1.70, 95% CI: 1.40, 2.06), and exposure to secondhand smoke (AOR=1.68, 95% CI: 1.02, 2.75). Gestational diabetes demonstrated a protective effect (AOR=0.37, 95% CI: 0.15, 0.91). Geographic mapping revealed that regions with higher food insecurity had elevated LBW prevalence. CONCLUSION: These findings underscore the importance of addressing food insecurity among pregnant women to reduce the risk of LBW and improve newborn outcomes.

Monitoring the Cost and Affordability of a Healthy Diet within Countries: Building Systems in Ethiopia, Ghana, Malawi, Nigeria, Pakistan, Tanzania, and Viet Nam.

Background: Governments around the world collect food price data on a frequent basis, often monthly, for the purpose of monitoring inflation. These routine economic data can be used with a nutrition-sensitive lens for understanding economic access to a healthy diet. The Food and Agriculture Organization of the United Nations has adopted the cost and affordability of a healthy diet (CoAHD) for annual tracking alongside other food security indicators. This indicator is relevant in many countries for informed decision-making and accountability toward Food Systems Summit pathways. National governments may wish to include this indicator in their own monitoring systems, using existing subnational price and income data. Objectives: We describe emerging systems in several countries for monitoring CoAHD and analytical tools that facilitate the calculation of CoAHD. We discuss reasons why the indicator may differ when calculated using subnational data compared with the global monitoring system and how to interpret differences. Methods: Between June 2016 and February 2024, 19 workshops were held in 7 countries (Ethiopia, Ghana, Malawi, Nigeria, Pakistan, Tanzania, and Viet Nam), where stakeholder discussions covered sources of food price data, institutions involved, policy uses, and direct training in calculation of CoAHD. Food price data collected by national organizations were used to calculate CoAHD in partnership with government agencies. Results: Calculating CoAHD using subnational data uses the same methods across settings, but the mechanisms for monitoring and dissemination are different in each country, illustrating heterogeneity in how the metric can most effectively be incorporated within existing structures. Results from national and global monitoring systems have expected differences based on data sources, healthy diet standards, and affordability standards. Conclusions: CoAHD can be calculated with existing data and resources, facilitated by new software tools and user tutorials. In the future, it can be further streamlined, leveraging technical assistance from global institutions and aligning national and global monitoring systems.

A new framework on climate-induced food-security risk for small-scale fishing communities in Tanzania.

Food insecurity is a pressing issue facing our world, particularly affecting coastal communities who rely on marine resources. The problem is further compounded by the rapidly changing climate, a deteriorating environment and growing human populations. It is essential to evaluate this issue accurately to reduce risk and improve the situation of coastal communities, especially in countries with less socioeconomic development. To this end, we develop a food security social-ecological risk assessment framework for developing communities in coastal areas of the Western Indian Ocean facing a changing environment. The framework integrates local ecological knowledge, expert scientific opinion, survey data, and satellite sea surface temperature (SST) and chlorophyll-a observation. We conducted a local-scale case study in four regions in Tanzania; Mafia, Pemba, Tanga, and Unguja, revealing that they face moderate to high risk levels of food insecurity. The highest risk was observed in the island communities of Pemba and Unguja, while the communities of Mafia and Tanga had the lowest risk due to lower exposure and sensitivity to climate change. Our results show that recognizing the key differences across risk components is crucial in identifying effective intervention strategies for local practitioners. This study highlights the need for detailed assessments to provide accurate information on local-scale food security dynamics, specifically when assessing impacts induced by environmental and climatic changes. Supplementary Information: The online version contains supplementary material available at 10.1007/s12571-024-01472-x.

What do you want to eat? Cuisine and nutrition intervention preferences among people using a large food pantry in Texas.

Objective: Nutrition interventions delivered through food pantries could reduce health disparities for people experiencing food insecurity. We identified clients' preferences for cuisines, nutrition interventions, and outcomes and whether preferences differ for subpopulations. Methods: Cross-sectional study at a large pantry in Dallas, Texas (N = 200). Survey collected from February-May 2023 on demographics, cuisine preferences, nutrition intervention preferences, and outcomes clients hope to achieve when changing lifestyle (weight loss, feeling comfortable in clothes, feeling good about diet, wellbeing). A subsample (N = 130) had height and weight measured. We tested whether food security and BMI (categorical) were associated with intervention or outcome preferences using IBM SPSS Statistics (Version 29) to conduct analysis of variance. Results: Top-rated cuisines were Mexican, Chinese, Italian. Participants reported a desire for interventions implemented through the pantry reflected by high Nutrition Intervention Index scores. The highest rated intervention was bringing more healthy food into the pantry and lowest rated was restricting unhealthy donations.Overall wellbeing was the most important outcome and weight loss the least important.Neither food security nor BMI were associated with desire for interventions. All outcomes were rated in a similar pattern, though people with obesity and overweight rated weight loss as more important than people with normal weight. Conclusions: Most participants demonstrated a strong desire for healthier, ethnically diverse options, and nutrition interventions delivered through the pantry. Our findings explore cuisines and outcomes preferred by people that use food pantries which can guide researchers, clinicians, and non-profit organizations in planning and promotion of nutrition programs for pantry clients.

CRISPR/Cas: a powerful tool for designing and improving oil crops.

Improving oil yield and quality is a major goal for crop breeding, and CRISPR/Cas-mediated genome editing has opened a new era for designing oil crops with enhanced yield and quality. CRISPR/Cas technology can not only increase oil production but also enhance oil quality, including enhancing pharmaceutical and health components, improving oil nutrients, and removing allergic and toxic components. As new molecular targets for oil biosynthesis are discovered and the CRISPR/Cas system is further improved, CRISPR/Cas will become a better molecular tool for designing new oil crops with higher oil production, enhanced nutrients, and improved health components. 'CRISPRized' oil crops will have broad applications both in industry (e.g., as biofuels) and in daily human life.

A systematic literature review on the impact of climate change on the livelihoods of smallholder farmers in South Africa.

Smallholder farmers in South Africa are increasingly vulnerable to the adverse effects of climate change, posing significant threats to their livelihoods and food security. This systematic literature review investigates the several impacts of climate change on smallholder farmers across the country. The literature review used a systematic approach to search for relevant research across three academic databases such as Google scholar, Consensus, and Zendy. Based on the inclusion criteria for the literature review, 261 articles were initially screened, and 35 articles were included in the systematic review. This process helped to identify the most relevant and high-quality studies on the topic. The data extracted from the 35 articles were analyzed and synthesized to identify the impact of climate change on the livelihoods of smallholder farmers. This helped to identify commonalities and differences across the literature, and to draw conclusions about the impact of climate change on the livelihoods of smallholder farmers. The study identified and examined the specific challenges faced by smallholder farmers, including the loss of livestock, reduced crop yields and heightened economic hardship. Additionally, the review explores the coping strategies employed by farmers to mitigate these challenges and adapt to the evolving climatic conditions. The findings highlight the urgent need for targeted interventions and support mechanisms aimed at enhancing the resilience of smallholder farmers and ensuring the long-term sustainability of agricultural practices amidst the challenges posed by climate change. Furthermore, the study provides valuable recommendations for policymakers, agriculturalists, and other stakeholders to address the identified issues and support smallholder farmers in adapting to climate change.

Recent advances of CRISPR-based genome editing for enhancing staple crops.

An increasing population, climate change, and diminishing natural resources present severe threats to global food security, with traditional breeding and genetic engineering methods often falling short in addressing these rapidly evolving challenges. CRISPR/Cas systems have emerged as revolutionary tools for precise genetic modifications in crops, offering significant advancements in resilience, yield, and nutritional value, particularly in staple crops like rice and maize. This review highlights the transformative potential of CRISPR/Cas technology, emphasizing recent innovations such as prime and base editing, and the development of novel CRISPR-associated proteins, which have significantly improved the specificity, efficiency, and scope of genome editing in agriculture. These advancements enable targeted genetic modifications that enhance tolerance to abiotic stresses as well as biotic stresses. Additionally, CRISPR/Cas plays a crucial role in improving crop yield and quality by enhancing photosynthetic efficiency, nutrient uptake, and resistance to lodging, while also improving taste, texture, shelf life, and nutritional content through biofortification. Despite challenges such as off-target effects, the need for more efficient delivery methods, and ethical and regulatory concerns, the review underscores the importance of CRISPR/Cas in addressing global food security and sustainability challenges. It calls for continued research and integration of CRISPR with other emerging technologies like nanotechnology, synthetic biology, and machine learning to fully realize its potential in developing resilient, productive, and sustainable agricultural systems.

Nutrition Knowledge, English Adequacy, Women's Education, and Food Insecurity Among Syrian Refugees in Florida.

Objectives The objective of the study was to measure food security among Syrian refugees residing in urban and rural areas in Florida. Women's education, English proficiency, and nutrition knowledge were assessed to indicate their effects on food security in this population. Methods One-on-one interview questionnaires were administered to Syrian refugee households residing in Florida (n=80: n=43 in rural areas and n=37 in urban areas). The main outcomes were food insecurity, nutrition knowledge, English adequacy, and women's education. Results The main outcome of this study was the food security status among Syrian refugees residing in Florida. Among the total households, 80% were food insecure, and food insecurity was greater in rural areas (60.9%) than in urban areas (39.1%). The majority (57.5%) of participants scored fair nutrition knowledge. One-way frequency analysis showed that 75% of households had inadequate English. Around 23.7% of Syrian refugee women had a high school diploma or higher. Among these women, 68.4% were residing in urban areas. The chi-squared test showed significant differences in women's education in rural and urban areas (p=0.03). Nutrition knowledge was higher in urban areas compared to rural areas. The chi-squared test showed a significant difference in nutrition knowledge in urban and rural areas (p=0.04). The result of the multivariate logistic regression model indicated that the type of residence, rural vs urban areas, had an inverse significant effect on food security after controlling for our variables. Syrian refugees in rural areas had 79.9 greater odds of being food insecure compared with urban areas (odds ratio: 0.201, 95% CI: 0.053-0.758, p=0.01). Conclusions Nutrition knowledge, English adequacy, and women's education may be less important than types of residence. The type of residence is a contributing factor to food insecurity in Syrian refugees residing in Florida. A larger sample size would allow a clearer understanding of the relation of our variables with food insecurity.

The association between food insecurity and obesity, a body shape index and body roundness index among US adults.

Research has established a positive association between food insecurity and obesity, typically assessed by body mass index (BMI); However, studies examining the relationship between food insecurity and measures of body fat content and distribution are lacking. The aim of this study was to examine the association between food insecurity and obesity ([BMI] ≥ 30 kg/m2) and body fat indicators assessed by body roundness index ([BRI] > 6.72) and a body shape index ([ABSI] > 0.08). This is a cross-sectional study using NHANES data 2007-2020. Household food security was assessed by U.S. Food Security Survey Module questionnaire. Multivariable-adjusted binary logistic regression analyses were used to calculate odds ratios and 95% CIs. Compared to those with full food security, the adjusted ORs for obesity were 1.28 (95% CI:1.18, 1.39), 1.40 (95% CI:1.28, 1.53), and 1.43 (95% CI:1.30, 1.57) for those with marginal, low and very low food security, respectively. The corresponding ORs for high BRI were, respectively, 1.39 (95% CI:1.26, 1.52), 1.50 (95% CI:1.36, 1.66), and 1.60 (95% CI:1.43, 1.78). Similar results were observed for ABSI. The analyses of BMI suggested a potential sex difference, as significant associations were found in women, but not in men. This study confirms previous evidence of the positive association between food insecurity and obesity among US adults.

Trends in household food insecurity from the Canadian Community Health Survey, 2017 to 2022.

Background: Income-related food insecurity is an important determinant of health. This study aimed to provide an update on the food security status of Canadian households using the most recent available data from a health-oriented national-level survey. This study also examined trends in food insecurity since 2017, and how these have tracked with changes in price inflation. Data and methods: Data on household food security status in the 10 Canadian provinces came from five annual cycles of the population-representative cross-sectional Canadian Community Health Survey (CCHS): 2017, 2018, 2020 (September to December), 2021, and 2022. The Household Food Security Survey Module was used to categorize household food security status during the previous 12 months as food secure or marginally, moderately, or severely insecure. Results: Before 2019, approximately 1 in 10 households had experienced some level of food insecurity in the previous 12 months (9.6% in 2017 and 11.6% in 2018). Household food insecurity prevalence was slightly lower and stable during the COVID-19 pandemic years (8.5% in fall 2020 and 9.1% in 2021) and increased to 15.6% in 2022. Levels of household food insecurity generally tracked with changes in consumer price inflation. Compared with 2021, there were notable increases in levels of moderate and severe food insecurity in 2022 among one-parent households with children, renters, and those reliant on government financial assistance. Interpretation: The prevalence of household food insecurity in the CCHS was relatively stable from 2017 to 2021, increased in 2022, and generally tracked with changes in price inflation. Monitoring levels of household food insecurity will continue to be important as price inflation eases but the cost of living remains high.

Edited eukaryotic translation initiation factors confer resistance against maize lethal necrosis.

Maize lethal necrosis (MLN), which is caused by maize chlorotic mottle virus along with a potyvirus, has threatened the food security of smallholders in sub-Saharan Africa. Mutations in eukaryotic translation initiation factors (eIFs), which also facilitate virus genome translation, are known to confer variable resistance against viruses. Following phylogenetic analysis, we selected two eIF4E proteins from maize as the most likely candidates to facilitate MLN infection. A knockout (KO) of each of the corresponding genes in elite but MLN-susceptible maize lines conferred only partial protection. Our inability to knockout both the genes together suggested that at least one was required for survival. When we edited (ED) the eIF4E genes in Mini Maize, however, the plants with the eif4e1-KO became highly resistant, whereas those with the eif4e2-KO remained susceptible. Neither of the causal viruses could be detected in the MLN-inoculated eif4e1-KO plants. The eIF4E2 cDNA in Mini Maize lacked the entire 4th exon, causing a 22-amino acid in-frame deletion, which shortened the protein to 198 amino acids. When we introduced mutations in the 4th exon of the eIF4E2 gene in two elite, MLN-susceptible lines pre-edited for an eif4e1-KO, we obtained as strong resistance against MLN as in eif4e1-KO Mini Maize. The MLN-inoculated lines with eif4e1-KO/eIF4E2-exon-4ED performed as well as the uninoculated wild-type lines. We demonstrate that the C-terminal 38 amino acids of eIF4E2 are dispensable for normal plant growth but are required for the multiplication of MLN viruses. Our discovery has wide applications across plant species for developing virus-resistant varieties.

Women's Knowledge of Local Plants and Their Gastronomic Heritage in Chitral, NW Pakistan.

Women are the "guardians of the kitchen" and central to household food security, yet their role has never been studied across the Hindukush region or Pamiri Knot. This study explores the women's knowledge (specifically from the Khowar (Kho) and Wakhi linguistic groups) of local food systems and determines their role in ensuring household food security and sustainability in the mountain regions of northern Pakistan. Based on in-depth semi-structured interviews with female informants in the Rech and Broghil valleys of upper Chitral, 91 different types of food products were recorded, including wild and cultivated species. Eremurus stenophyllus and Allium barsczewskii were the commonly utilized plant species, though distinct preferences between the Kho and Wakhi groups were noted. Prominent differences were perceived in using certain cultivated plants among the two ethnic groups. For instance, Kho preferred plants like Beta vulgaris, Zea mays, and Brassica napus as indicated by the use reports, while Wakhi concentrated on Thymus serpyllum, Zygophyllum obliquum and Papaver involucratum. Both groups had shared dairy practices, but cottage cheese and curd were highly cited among Kho, while double-fermented curd and Qurut for Wakhi. The study recorded some new food uses for specific plants, such as Atriplex hortensis, Carthamus tinctorius, Hylotelephium spp., and Saxifraga sibirica. Cross-culture analyses revealed a mosaic pattern of homogenous and heterogenous trends based on reported food species of plants/animals and their use reports. Our findings emphasize the significant role of women in sustaining local food diversity, food sustainability, and the preservation and security of the local food systems, cultural legacy, and household food management. Therefore, inclusive research addressing their social, economic, and environmental issues must be conducted. Furthermore, policies must incorporate women's traditional knowledge to build resilient food systems.

Geminiviruses and Food Security: A Molecular Genetics Perspective for Sustainable Agriculture in Africa.

The African continent is vulnerable to food insecurity. Increased food costs, job losses, and climate change force Africans to chronic hunger. Biotechnology can be used to mitigate this by using techniques such as CRISPR/Cas9 systems, TALENs, and ZFNs. Biotechnology can utilize geminiviruses to deliver the necessary reagents for precise genome alteration. Additionally, plants infected with geminiviruses can withstand harsher weather conditions such as drought. Therefore, this article discusses geminivirus replication and its use as beneficial plant DNA viruses. It focuses explicitly on genome editing to increase plant resistance by manipulating plants' salicylic acid and jasmonic acid pathways.

Internal Drive or External Pull: Independent Innovation and Sustainable Growth of Chinese Agricultural Enterprises.

The independent innovation of agricultural enterprises ensures national food security through enhancing food production efficiency and optimizing food nutritional quality. Independent innovation is an important way for the sustainable growth of agricultural enterprises. However, in this process, there are issues such as long cycles and high risks. Based on this, using the panel data of China's listed agricultural enterprises from 2007 to 2021, this study empirically examined the impact of independent innovation on the sustainable growth of agricultural enterprises, as well as the moderating effects of internal drivers (digital transformation) and external pull factors (government subsidies) through a two-way fixed effects model. The findings are the following: (1) The impact of independent innovation on the sustainable growth of agricultural enterprises exhibits an "inverted U-pattern". When the R&D investment of agricultural enterprises accounts for 77.85% of operating income, the sustainable growth ability of agricultural enterprises is the highest. (2) Compared with large agricultural enterprises, small and medium-sized agricultural enterprises reach the threshold of independent innovation ability later, and the incentive effect range of independent innovation is longer. (3) Independent innovation exerts a more significant "inverted U" effect on the sustainable growth of non-state-owned agricultural enterprises and agricultural enterprises in the mature stage, while its impact on the sustainable growth of state-owned agricultural enterprises and agricultural enterprises in the growth and decline stages is not significant. (4) Government subsidies can help enhance the positive impact of independent innovation on the sustainable growth of agricultural enterprises when it does not exceed the threshold but cannot alleviate the negative impact of independent innovation on the sustainable growth of agricultural enterprises when it exceeds the threshold; investment in digital transformation not only helps to enhance the positive impact of independent innovation on the sustainable growth of agricultural enterprises when it does not exceed the threshold but also helps to alleviate the negative impact of independent innovation on the sustainable growth of agricultural enterprises when it exceeds the threshold. The research results provide data support for agricultural enterprises to carry out innovation activities under internal drive and external pull. At the same time, it is of great significance for the national implementation of the strategy of storing food in technology and food security strategy.

Leveraging multi-omics tools to comprehend responses and tolerance mechanisms of heavy metals in crop plants.

Extreme anthropogenic activities and current farming techniques exacerbate the effects of water and soil impurity by hazardous heavy metals (HMs), severely reducing agricultural output and threatening food safety. In the upcoming years, plants that undergo exposure to HM might cause a considerable decline in the development as well as production. Hence, plants have developed sophisticated defensive systems to evade or withstand the harmful consequences of HM. These mechanisms comprise the uptake as well as storage of HMs in organelles, their immobilization via chemical formation by organic chelates, and their removal using many ion channels, transporters, signaling networks, and TFs, amid other approaches. Among various cutting-edge methodologies, omics, most notably genomics, transcriptomics, proteomics, metabolomics, miRNAomics, phenomics, and epigenomics have become game-changing approaches, revealing information about the genes, proteins, critical metabolites as well as microRNAs that govern HM responses and resistance systems. With the help of integrated omics approaches, we will be able to fully understand the molecular processes behind plant defense, enabling the development of more effective crop protection techniques in the face of climate change. Therefore, this review comprehensively presented omics advancements that will allow resilient and sustainable crop plants to flourish in areas contaminated with HMs.

The Present State and Impact of AI-Driven Computational Tools for Predicting Plant Protein Structures.

Several key functions of plants, such as photosynthesis, nutrient transport, disease resistance, and abiotic tolerance, are manifested by several classes of proteins. Prediction of 3- dimensional (3-D) structures of proteins and their working mechanisms can have a profound impact on plant proteomics research and could help improve key agricultural traits in crop plants. This review aims to present the current status of plant protein structure determination and discuss the way forward. Most experimentally proven protein structures are available only for the model plant Arabidopsis thaliana. Most of the key crop plants have only a few hundred or fewer experimentally proven 3-D structures. Fewer than 1% of the protein sequences in the majority of plants have had their 3D structures experimentally determined, and A. thaliana is the sole plant with the highest percentage of 1.4 % of protein sequences with experimentally determined structures. AI-based protein structure prediction tool AlphaFold has predicted models of several thousand proteins for many crop plants. In AlphaFold predicted protein models, soybean has the highest percentage (65%) of its UniProt protein sequences with predicted models, and a few other crop plants have also a considerable percentage of its UniProt sequences with AlphaFold predicted models. AlphaFold might help predict models and bridge the gap in plant structure determination studies. Protein structure information might lead to engineering key residues to improve the agronomical performance of crop plants.

The impact of ethical commitments on the intention to adopt digital agricultural technologies.

Sustainable food security is a critical global concern and an urgent priority in developing countries such as Iran. Digital agricultural technologies (DAT) represent significant solutions in this regard, yet their adoptions and development in Iran face limitations. Theoretical studies have underscored the importance of ethical commitments in the adoption process. This study aims to investigate whether ethical commitments regarding food security can influence the intention to adopt digital technologies by farmers. The study employed the Norm Activation Model and integrated two additional components, namely perceived risk and social capital. We applied this framework to examine research works on farmers of Kermanshah Province in the west of Iran, using survey data (sample n = 384). Data analyses were done through structural equation modeling (SEM). Based on the results, the developed Norm Activation Model can be used to predict the adoption intention of DAT by farmers; with the model explaining 65% of total variance. Feeling guilt exhibited the highest direct effect, followed by feeling proud. Furthermore, ethical norms had a direct and indirect impact on intention through the mediating variables of feeling proud and Feeling guilt. The findings of this study contribute to facilitating innovation adoption strategies. It is recommended that, in order to facilitate and stabilize farmers' adoption of innovation, their sense of guilt should first be aroused. After stimulating the farmers' sense of pride toward the adoption; emphasis should be placed on ethical commitments. Ultimately, the introduction of technology and the facilitation of infrastructure should be pursued.

Exploring the association of social connections and food security among adults with uncontrolled type 2 diabetes: a population-based study.

BACKGROUND: Primary health care professionals are held accountable for various quality measures in the treatment of patients with chronic diseases such as diabetes. Uncontrolled type 2 diabetes (T2D) remains a considerable health problem; thus, further studying patients with this condition is important for delivering effective interventions. Social determinants of health (SDoH) have been shown to affect various aspects of diabetes care in different subpopulations. We studied the association of SDoH with uncontrolled T2D in a population of adult primary care patients. METHODS: We retrospectively searched our electronic health record for adult patients (≥18 years) with a diagnosis of T2D and a hemoglobin A1c (HbA1c) level of 8% or higher. Patients were empaneled to 2 primary care clinic sites between January 1, 2021, and January 31, 2022. Patients were grouped by HbA1c level to stratify patients according to the extent of uncontrolled T2D. Patient characteristics were compared among groups. Unadjusted and adjusted multinomial logistic regression analysis was used to estimate the odds of various SDoH factors among patient groups with different levels of uncontrolled T2D. RESULTS: The study cohort included 1,596 patients. Most patients were White (79%), and the median age was 58.8 years. The median HbA1c level was 8.9%, and approximately 68% of patients were obese (body mass index [BMI] ≥30). When the study population was grouped by HbA1c level (8% to < 9% [n = 806], ≥9% to < 12% [n = 684], and ≥12% [n = 106]), significant differences among groups were observed in age group (P < .001), marital status (P < .001), race (P < .001), ethnicity (P = .001), and BMI category (P = .01). In groups with higher HbA1c levels, we noticed a higher percentage of patients who were aged 51 to 65 years or single. Among patients with uncontrolled HbA1c levels, more patients were obese than overweight. Patients in the intermediate HbA1c group had increased odds of food insecurity and some decreased social connections, even after adjusting for age, sex, race, ethnicity, and marital status. CONCLUSIONS: Among patients with uncontrolled T2D, higher HbA1c levels were associated with decreased social connections and increased food insecurity. Our findings provide insight into the role of these SDoH in managing T2D and have important implications for primary care practice.

Advancing irrigation management: integrating technology and sustainability to address global food security.

Irrigation management is essential for addressing global food security challenges under changing climate. This review discusses the integration of advanced irrigation technologies and their roles in enhancing water use efficiency and managing energy demands within agricultural systems. High-efficiency irrigation systems, such as drip and sprinkler systems, have significant potential to reduce water use and increase crop yields. However, their adoption varies worldwide, and the efficiency of existing irrigation practices often remains inadequate, resulting in substantial water losses due to outdated management practices. Emerging technologies and innovative irrigation strategies, including precision agriculture and advanced crop models, provide promising pathways for improving irrigation efficiency. Nonetheless, the widespread integration of these technologies is hindered by high costs, the need for technical expertise, and challenges in adapting existing agricultural systems to new methodologies. Irrigation systems can have substantial energy requirements, particularly those dependent on groundwater. The exploration of the water-environment-energy-food (WEEF) nexus illustrates the importance of a balanced approach to resource management, which is crucial for achieving sustainable agricultural outcomes. Future research should include lowering barriers to technology adoption, enhancing data utilization for precision irrigation, promoting integrated management strategies within the WEEF framework, and strengthening policy support for sustainable practices. This review proposes a multidisciplinary approach to irrigation management that includes technological innovation, strategic policy development, and global cooperation to secure sustainable agricultural practices and ensure global food supply resilience in the face of climate change.