United States Department Of Agriculture Research Articles

Development of Omani-branded food composition database for an electronic dietary assessment tool

Background: The food composition database provides a comprehensive information on the various nutrients present in the foods. At present, Oman lacks a food composition database (FCDB) of locally produced branded foods, which necessitates the development of such a database. Objectives: The aim of this study is to develop an FCDB for Omani-branded foods available for local consumption for an electronic dietary assessment tool. Methods: Back-of-pack (BOP) nutritional information of these branded foods available in our markets was gathered from manufacturer data. Food mapping was used to match the branded foods according to the BOP macronutrient data and food description to the appropriate generic food item from United States Department of Agriculture (USDA) or Canadian FCDBs. Results: The developed database is composed of 571 food items with associated 60 nutrients. The majority of food items (91%) were mapped to a single generic food item. The rest (9%) was mapped to multiple generic food items. Overall, 96% of food items were mapped to a single generic food, which was matched based on BOP macronutrients and item descriptions. However, the minority (4%) were mapped based on item description alone as either the BOP nutrients were implausible. Moreover, 91% of food items were individually mapped to within 10% agreement with the generic food item for energy. The fish and fish group has the largest mean of absolute percentage difference in energy between BOP and generic items (16%). Conclusion: This currently developed database would critically help to accurately assess the dietary intake of the Omani population once incorporated into an electronic dietary assessment tool, and it can be updated in the future on a regular basis.

Potassium Food Additives and Dietary Management of Serum Potassium: Proposed Best-Practice Recommendations

The contribution of potassium food additives to total dietary potassium intake is unknown. This poses challenges for individuals living with kidney disease who may need to monitor their potassium intake. Additionally, different countries have varying regulations regarding the reporting of dietary potassium content in foods. This article examines the potential of published food databases in assisting clinicians to help individuals with kidney disease manage their serum potassium levels. It uses the United States Department of Agriculture's Branded Food Products Database as an example. Evidence for potassium additive content in database entries, along with their bioavailability, is discussed, and best-practice recommendations are made based on current evidence. Clinical practice and future research priorities are suggested.

Federal economic data on local and regional food producers

AbstractUS local and regional food systems (LRFS) garner significant support from the federal government. Congress has directed the US Department of Agriculture to collect data on farmers and ranchers that use these markets, but challenges remain. We provide information about the three national surveys that provide farm‐level data on sales through LRFS, including how questions have changed over time. We highlight the benefits and challenges of using each survey from scale/scope and producer implication perspectives and offer recommendations to improve the existing survey instruments to support enhanced economic understanding of the implications of local and regional food markets.

Sialic Acid Receptor Specificity in Mammary Gland of Dairy Cattle Infected with Highly Pathogenic Avian Influenza A(H5N1) Virus.

In March 2024, the US Department of Agriculture's Animal and Plant Health Inspection Service reported detection of highly pathogenic avian influenza (HPAI) A(H5N1) virus in dairy cattle in the United States for the first time. One factor that determines susceptibility to HPAI H5N1 infection is the presence of specific virus receptors on host cells; however, little is known about the distribution of the sialic acid (SA) receptors in dairy cattle, particularly in mammary glands. We compared the distribution of SA receptors in the respiratory tract and mammary gland of dairy cattle naturally infected with HPAI H5N1. The respiratory and mammary glands of HPAI H5N1-infected dairy cattle are rich in SA, particularly avian influenza virus-specific SA α2,3-gal. Mammary gland tissues co-stained with sialic acids and influenza A virus nucleoprotein showed predominant co-localization with the virus and SA α2,3-gal. HPAI H5N1 exhibited epitheliotropism within the mammary gland, and we observed rare immunolabeling within macrophages.

Application of a Standardized Impact Monitoring Protocol (SIMP) to assess biological weed control projects in the State of Idaho, USA

In the USA, the lack of systematic post-release assessments of weed biological control projects demonstrating quantitative effects of biological control agents on target weed densities, population biology, and/or vegetation responses remain a concern. While there are numerous quantitative assessments, overall conclusions are limited in scope by the spatial scale covered, duration of study, potentially confounding factors, or weed parameters measured. The United States Department of Agriculture’s Animal Plant Health Inspection Service is the regulatory agency responsible for biological control agent releases. USDA APHIS requires post-release impact monitoring of target weed populations as part of release permits issued for new biological control agents. However, large scale, long-term impact assessments are rarely conducted for a variety of reasons. To address this problem, biocontrol practitioners developed a standardized impact monitoring protocol (SIMP) for the State of Idaho in 2007. The intent was to collect ecological data which are sufficiently robust for quantitative analysis, while minimizing time spent in the field to make data collection appealing to citizen scientists and land managers. SIMP has since been implemented for ten weed biocontrol systems, with more than fifteen years of monitoring data for some systems. SIMP data are collected along permanent transects and include weed density and size parameters, categorical vegetation community and biocontrol agent abundance data. Data are repeated measures, which are well suited for dynamic population modeling and can be coupled with environmental factors (e.g., climate or soil data) to analyze how processes like climate (and climate change) can drive variation in weed biocontrol agent interactions. SIMP data can be combined with detailed weed, nontarget plant and/or biocontrol agent surveys to add analytical data. Finally, SIMP has also been implemented for two weeds for which biological control agents have not yet been introduced to provide weed and community vegetation data prior to releases.

Is US farm sector debt underestimated? Evidence from equipment lending

PurposeThe growth of lending from nontraditional lenders may pose challenges for official US Department of Agriculture (USDA) farm sector debt estimates, but it is difficult to find data to assess official estimates. The purpose of this study is to examine whether debt provided by nontraditional lenders is accurately accounted for in official estimates.Design/methodology/approachWe compare traditional and nontraditional lending data from farm equipment lien collateral values and the USDA Agricultural Resource Management Survey (ARMS). After analyzing trends in equipment lending implied by farm equipment lien data and ARMS, we estimate whether changes in farm equipment lien values predict changes in equipment debt reported in ARMS and whether lender type influences that relationship.FindingsWe find that credit provided by nontraditional lenders is likely underreported in ARMS. Our econometric model shows that equipment debt volumes for nontraditional lenders are consistently lower than traditional loan volumes in ARMS across a variety of model specifications. We also find that an increase in lien values for nontraditional lenders is less likely to predict an increase in ARMS equipment debt volumes than an increase for traditional lenders.Practical implicationsOfficial farm sector debt estimates may not fully account for nontraditional lenders.Originality/valueThis study demonstrates how the growth of nontraditional lending poses challenges for estimating US farm sector debt. We evaluate farm sector debt estimates and advance knowledge of the role of nontraditional lenders in farm equipment credit provision. The farm equipment lien dataset provides a rich source of novel data for research on local and national equipment debt and investment.

Dietary Patterns among Smokers and Non-Smokers: Findings from the National Health and Nutritional Examination Survey (NHANES) 2017-2018.

Diet behavior and nutrition are critical for maintaining health and improving quality of life. Cigarette smoking remains the leading cause of preventable death in the United States. Poor dietary choices, such as excessively frequenting restaurants, consuming ready-to-eat foods from grocery stores, and ingesting ultra-processed foods (like frozen meals and pizzas), can adversely impact health. Despite this, research comparing dietary behaviors between smokers and non-smokers is limited. Using data from the National Health and Nutritional Examination Survey 2017-2018, we analyzed diet behavior based on smoking status. Our findings reveal that smokers had a significant increase (90%) in the frequency of consuming frozen meals/pizzas in the past 30 days compared to non-smokers (coefficient: 1.9; 95% CI: 1.4, 2.6; p-value < 0.001). Additionally, over 70% of participants, regardless of their smoking status, were unaware of MyPlate, a nutritional guide created by the United States Department of Agriculture (USDA) to encourage Americans to make healthier food choices. There is an urgent need to increase public awareness of MyPlate and promote a better understanding of healthy dietary behaviors.

Barriers to Fresh Fruit and Vegetable Access in Adult Patients in the Mayo-La Crosse Family Medicine Residency Clinic.

Food insecurity remains a pressing issue in the United States, with approximately 12.8% of American households experiencing this challenge in 2023, as reported by the USDepartment of Agriculture (USDA). In Wisconsin, a state with a notable agricultural heritage, the prevalence of food insecurity averaged 9.9% between 2019 and 2023. A growing body of research underscores the importance of consuming diets rich in fruits and vegetables for maintaining optimal health and mitigating the risk of various chronic diseases, including cardiovascular disease (CVD) and obesity. Fruits and vegetables are reservoirs of essential nutrients such as vitamins, minerals, antioxidants, and dietary fiber, which collectively contribute to overall well-being.Despite the well-documented health benefits of fruits and vegetables, a considerable proportion of the population fails to meet the recommended daily intake of at least five servings. This disparity underscores the importance of exploring factors influencing dietary behaviors and identifying strategies to promote adherence to dietary guidelines. Surveys were distributed by staff at the family medicine residency clinic in La Crosse, Wisconsin, during routine visits in April and May 2023. Any patients ≥18 years old presenting to the Family Health Clinic (FHC) were eligible for inclusion. Patients were excluded if they were unable to read/answer survey questions due to intellectual/language/other barriers. Surveys included demographic data such as the participant's age, gender, race, income bracket, and primary mode of transportation. A total of 122 participants were then asked how many servings in a day they ate of 100% juice, fruits, beans, green vegetables, yellow/orange vegetables, and other vegetables, as well as about barriers to more fruit and vegetable consumption and a Likert scale about their attitudes toward fruit and vegetable consumption and interest in discussing it with a healthcare provider. Demographic characteristics were analyzed through graphical representation to elucidate trends and patterns among the surveyed population. We compared different demographics with the barriers to fruits and vegetables using bar graphs. The primary barrier to fruit and vegetable intake varied by age group: "cost" for 18-30, "other" for 31-50, "cost" and "none" for 51-70, and "none" for over 70. For gender, "none" was most frequent for maleswhile "cost" was for females. By income, "cost" was common for $0-20k and $20-50k, "none" for $50-100k, and "other" for >$100k. A Likert scale assessed interest in discussing healthy foods with healthcare providers. Most responses were "neutral,"with "strongly agree" highest in 18-30 and "agree" in 31-50, 51-70, and over 70 age groups. The purpose of this study was to ascertain barriers to fruit and vegetable access and identify patients' attitudes toward discussing healthy food choices with healthcare providers. There appears to be a correlation between decreasing income and increasing age and the likelihood of identifying cost as a barrier to fruit/vegetable intake. Barriers identified in our clinic included convenience/time constraints and cost. Many people in our survey also identified the lack of quality or good variety of fruits and vegetables at the store (availability) as a significant barrier to eating them.

Association of Household Food Insecurity with Stunting and Underweight Among Iranian Children Aged 2 - 5 Years old

Background: Although previous literature has assessed the association of household food insecurity with nutritional outcomes among children, the findings are inconsistent across different study populations. Objectives: We aimed to evaluate the association of household food insecurity with nutritional outcomes among children residing in Khalkhal city, Iran. Methods: The present cross-sectional study was conducted on 300 Iranian children aged 2 - 5 years who visited urban and rural health care centers between November 2021 and March 2022. Subjects were included in the survey using multi-stage cluster sampling. Household food security status was assessed using the United States Department of Agriculture (USDA) 18-item food security questionnaire. Odds ratios (95% confidence interval) for stunting according to the food insecurity score were estimated using multivariable logistic regression in three models. Results: In the present study, 39% of participants had food security, while the prevalence of food insecurity without hunger, food insecurity with moderate hunger, and food insecurity with severe hunger were 22.3%, 23%, and 15.7%, respectively. In all models, both categorized and continuous food insecurity scores correlated negatively with weight (P for all &lt; 0.001). Food insecurity did not predict the risk of stunting in all subjects before and after adjustment (Model 1: OR (CI) = 1.008 (0.96-1.05), P = 0.72; Model 2: OR (CI) = 1.01 (0.96 - 1.05), P = 0.65; Model 3: OR (CI) = 0.98 (0.92-1.04), P = 0.53). Conclusions: In the current study, we found that Iranian families with the lowest income had the highest food insecurity scores. Household food insecurity was negatively correlated with weight status among children aged 2 - 5 years.

Thirty Years of SNAP-Ed: The Transition of the Nation's Largest Nutrition Education Program Into a Pillar of the Public Health Infrastructure

This paper describes the 30-year evolution of Supplemental Nutrition Assistance Program-Education (SNAP-Ed) to provide evidence to support our perspective that SNAP-Ed has earned its position as a pillar of the public health infrastructure in the US. Legislatively designated as a nutrition education and obesity prevention program, its focus is the nearly 90 million Americans with limited income. This audience experiences ongoing health disparities and is disproportionately affected by public health crises. The SNAP-Ed program works to reduce nutrition-related health disparities at all levels of the Social-Ecological Model, follows a robust evaluation framework, and leverages strong partnerships between state-based practitioners, state agencies, and the US Department of Agriculture. The expansion of SNAP-Ed would enable the program to reach more Americans so that our nation can end hunger and reduce diet-related health disparities.

Similarities in the US Department of Agriculture international baseline projections

AbstractThe US Department of Agriculture (USDA) international baseline projections are crucial for US agricultural policy. Using a dynamic time warping algorithm, we examine whether corn, soybean, and wheat baselines exhibit a lack of significant distance indicating similarity in projections across countries. We then examine whether projections for countries with more similarity with the United States projections exhibit higher projection errors. We discover evidence of projections being similar to the United States, which is associated with lower errors for corn yield, harvested area, and exports and wheat import projections, but not for other variables. These findings offer valuable insights for USDA and stakeholders.

Sustainable Food Supply: The Interplay between Population Growth and Land Productivity Changes as a Pathway to 2030 and Beyond for Nigeria

Context and Background: Sustainable food supply is a critical global challenge, particularly in developing countries like Nigeria, where rapid population growth and limited land resources create a complex interplay with far-reaching implications. Thus, there will be a need to increase food production to keep pace with the population increase. Goal and Objectives: This study seeks to analyse the interplay between population growth and land productivity changes in Nigeria as a pathway towards achieving sustainable food supply by 2030 and beyond, in line with Goal 2 of the 2030 Sustainable Development Goals (SDGs) which is aimed at “ending hunger, achieving food security, improving nutrition, and promoting sustainable agriculture. Methodology: Data on land productivity and Nigeria's population and Population growth for 1961-2022 was sourced from the Economic Research Service of the United States Department of Agriculture (ERS-USDA, 2023). The data was analysed using descriptive statistics such as mean; standard errors and graphs; the Autoregressive Integrated Moving Average (ARIMA) was used to explain the interplay between population growth and land productivity changes in Nigeria. Results: The results of the population estimates revealed that the model successfully converged and significantly (p&lt;0) explained 98.3% of the variance of the endogenous variable that is, the population at an intercept of -2500.7. Of the hypothesized variables, year (1.212), cropland (9.14E-4), irrigated (0.283), and pasture (0.003). These findings imply that the future population would increase in each period until the series becomes explosive because, the coefficient of the lagged variable of population is positive and greater than 1, which is in contrast with the assumptions of the ARIMA model which should be less than 1. Thus, the study recommends adopting precision agriculture techniques such as GPS mapping, soil analysis, crop health monitoring, and automated irrigation to maximize crop yields, reduce costs, and transform farming practices in Nigeria.

Food Insecurity is Increasing and is More Common Among Persons with Chronic Liver Disease.

Effective interventions for metabolic liver disease include optimized nutritional intake. It is increasingly clear, however, that many patients with metabolic liver disease lack the resources to execute nutritional advice. Data on the trends of food insecurity are needed to prioritize public health strategies to address the burden of liver disease. Cross-sectional analysis of six waves of data from the 2007-2018, 24,847 subjects aged ≥20 years from the 2017-2018 National Health and Nutrition Examination Survey. Food security was measured using the US Department of Agriculture's Core Food Security Module. Liver disease was defined as elevated liver enzymes and a risk factor: elevated BMI, diabetes, and/or excess alcohol consumption. Models were adjusted using age, sex, race/ethnicity, education, poverty-income ratio, smoking, physical activity, alcohol intake, sugary beverage intake, Healthy Eating Inex-2015 score. Advanced liver disease was estimated using FIB-4 >2.67. The overall prevalence of liver disease was 24.6%, ranging from 21.1% (2017-2018) to 28.3% (2015-2016) (P-trend=0.85). 3.4% of participants had possible advanced liver disease, ranging from 1.9% (2007-2008) to 4.2% (2015-2016)(P-trend=0.07). Among those with liver disease, the prevalence of food insecurity was 13.6% in 2007-2008, which rose steadily to 21.6% in 2015-2016, before declining to 18.0% in 2017-2018 (P-trend=0.0004). Food insecurity rose more sharply for adults aged <50 years (2007-2008: 17.6%, 2015-2016: 28.0%, P-trend=0.004) compared to adults aged ≥50 years (2007-2008: 9.5%, 2015-2016: 16.5%, P-trend<0.0001). Food insecurity was more common among women, those with high BMI, and those with diabetes. Food insecurity is increasingly common among those with liver disease.

Promoting equity in the Conservation Reserve Program across the southeastern US

Black and female landowners, two of the largest groups of underserved landowners in the southeastern US, have considerably less land enrolled in the US Department of Agriculture's Conservation Reserve Program (CRP) than White and male landowners. The reasons for this discrepancy are complex and interrelated. Previous studies approached different facets of this problem using a variety of methods and analyses. Here, we conducted a synthetic literature review that demonstrates how the intertwined ecological, economic, and cultural concerns of underserved landowners influence their decisions about potential land conversion in the context of CRP requirements. Other studies have rarely considered such relevant factors as the sociocultural importance of land to underserved populations or the links between the limited participation of these groups in the CRP and historical racism and sexism in land management industries and agencies. Explicitly addressing these issues will help promote conservation equity in the CRP and other conservation programs.

Blow flies (Diptera: Calliphoridae) of the Baja California Peninsula

The blow fly fauna of the Baja California peninsula, Mexico has been sparsely documented. This study incorporates and lists recent and historical records of blow flies from collecting trips throughout the peninsula, visits to major southern California museums for historical collection records, and a literature search. Seven genera and 16 species are reported from the two peninsular Mexican States, Baja California, and Baja California Sur. Three species are recorded that are not included in the 2020 Catalog of Mexican Calliphoridae by Jaume-Schinkel, &amp; Ibanez-Bernal (2020), they are: Calliphora livida, Calliphora terraenovae, and Calliphora vomitoria. One blow fly species, Cochliomyia hominivorax (the primary Screw-Worm Fly) is not included here but is found in museum collections. Once present in Baja, it is considered eradicated from continental North America as far south as the Panama Canal by the U.S. Department of Agriculture (USDA) however, it is occasionally reintroduced (Skoda et al. 2018) and is still present in some Caribbean islands. It is noteworthy that all calliphorid species from this mountainous desert peninsula are also found in the State of California, USA which supports 11 genera and 47 species in this family (Whitworth 2006) primarily because of its more varied climate and terrain. The Baja peninsula can be considered a southern extension of the State of California, with reduced species representation due to reduced climate and terrain variation, so no separate identification keys are necessary. Forensic entomologists and taxonomists can use the blow fly keys for North America by Whitworth, 2006, and 2017 for this region. The latest key by Jones, Whitworth, and Marshall (2019) is revolutionary and much welcome in taxonomy in that it is an online computer-aided key that has actual macro-photos of species identification characters and is intended to be used with a computer screen next to your microscope for identifications in place of printed material.

Data blanks by design: Intellectual property and restrictions on genetic diversity assessments of the maize standing crop in the USA Upper Midwest

Societal Impact StatementAll US commercial maize (Zea mays) is a single race, “Corn Belt Dent,” and its genetic base has been in decline for at least 40 years. Independent genotyping can only be conducted after patent and licensing restrictions have expired, a period of 20 years. These restrictions also impede a molecular based assessment of the standing crop by the United States Department of Agriculture (USDA) as recommended by experts. Data blanks about landscape vulnerability put farmers at risk of crop failure and the public at risk of food insecurity. Understanding maize diversity experts' perspectives and analysis helps describe the contours of these data blanks and inform policy recommendations.Summary Recommendations by the Maize Crop Germplasm Committee to the United States Department of Agriculture (USDA) for a molecular based vulnerability assessment on the US standing maize (Zea mays) crop have not been acted on because of intellectual property and licensing restrictions. This research explores maize diversity experts' access to data and perceptions and analysis of the standing crop. The data come from semi‐structured interviews conducted with 44 maize diversity experts in the public and private sectors. Experts explain that genetic data blanks restrict non‐industry research, describe public sector concerns that standing diversity is narrow(ing), and find historic sources of pedigree data in Plant Variety Protection and patent records are no longer reliable. Some interviewees perceive that industry monitoring of standing diversity is in their best financial interest. Industry participants describe concentration in US maize allows them to control diversity over time, while public researchers discuss efficiency of scale narrowing genetic diversity and global concentration spreading this trend. Knowledge gaps about genetic diversity in US commercial maize are designed through patents, contracts, non‐disclosure agreements, and confidentiality agreements by patent holders who do not want their inbred lines genotyped by competitors. This restricts research and knowledge flow about genetic information into public networks. The Maize Crop Germplasm Committee is a node for knowledge flow; however, the lack of mechanisms for action suggests it is performative. We recommend all protections used on seed include exemptions for research, breeding, and seed saving; an independent assessment of how industry monitors standing diversity; and a molecular analysis of the standing crop conducted by the USDA.

Using machine learning algorithms to identify farms on the 2022 Census of Agriculture

As is the case for many National Statistics Institutes, the United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) has observed dwindling survey response rates, and the requests for more information at finer temporal and spatial scales have led to increased response burdens. Non-survey data are becoming increasingly abundant and accessible. Consequently, NASS is exploring the potential to complete some or all of a survey record using non-survey data, which would reduce respondent burden and potentially lead to increased response rates. In this paper, the focus is on a large set of records associated with potential farms, which are operations with undetermined farm status (farm/non-farm) and are referred to here as operations with unknown status (OUS). Although they usually have some agriculture, most OUS records are eventually classified as non-farms. Those OUS that are classified as farms tend to have higher proportions of producers from under-represented groups compared to other records. Determining the probability that an OUS record is a farm is an important step in the imputation process. The OUS records that responded to the 2017 U.S. Census of Agriculture were used to develop models to predict farm status using multiple data sources. Evaluated models include bootstrap random forest (RF), logistic regression (LR), neural network (NN), and support vector machine (SVM). Although the SVM had the best outcomes for three of the five metrics, the sensitivity for identifying farms was the lowest (13.8%). The NN model had a sensitivity of 80.5%, which was substantially higher than the other models, and its specificity of 45.3% was the lowest of all models. Because sensitivity was the primary metric of interest and the NN performed reasonably well on the other metrics, the NN was selected as the preferred model.

Genetic diversity of the Turkish accessions of two progenitor species, Triticum baeoticum Boiss. and Triticum urartu Thum. ex Gandil., using DArTSeq markers

AbstractThe aim of this study was to reveal the intra and interspecies differences between Triticum baeoticum and Triticum urartu using Diversity Arrays Technology sequencing (DArTseq) on 94 accessions representing Turkish populations. Seeds were gathered from the US Department of Agriculture, and from the Turkish Seed Gene Bank. Isolated and purified DNA samples were sent to Diversity Arrays Technologies for DArTseq. After the necessary quality filtering, a total of 16,898 and 100,103 loci were obtained respectively from the single nucleotide polymorphism (SNP) and SilicoDArT datasets. ADMIXTURE software was used to reveal the intra and interspecies population structures. Analysis of molecular variance was carried out to reveal the variance between the populations of the T. urartu and T. baeoticum species. Principal coordinate analysis was conducted to visualize the main sources of variation between the populations on a 2-dimensional plane. To reveal the evolutionary relationship, SNP dataset was used to reconstruct the phylogenetic dendrograms by using the maximum likelihood statistical method and the unweighted pair group method with arithmetic mean clustering algorithm. As a result of this study, the accessions of T. urartu and T. baeoticum species formed separate clusters and revealed as two different species. In line with the results obtained, it is obvious that the identification of some accessions should be re-evaluated. The results demonstrated that DArTseq, is a fast, low-cost, and high-accuracy method that can be used in species and population discrimination and an effective tool for Gene Bank management.

Association between flavonoid intake and rheumatoid arthritis among US adults

Basic research shows that flavonoids have anti-inflammatory effects that influence rheumatoid arthritis (RA) in rats. Investigating potential dietary interventions for RA helps prevent the onset and progression of the disease. Clinical evidence on the association of flavonoid and subclass intake with RA is lacking. Using three survey cycles of 2007–2008, 2009–2010, and 2017–2018 from the National Health and Nutrition Survey and the United States Department of Agriculture's Food and Nutrient Database for Dietary Studies (FNDDS), we analyzed 7,419 American adults (≥20 years old). The values of flavonoid and subclass intake were calculated using FNDDS. The status questions for self-reported RA were from the NHANES codebook. Weighted analyses, revealed that among the 7,419 participants included in this study (mean age of 44.69 years [standard error, 0.40] and 3,584 [48.31%] were female), 408 met the classification criteria for RA. According to the multivariable logistic regression model, compared with the risk of RA in the first quartile (Q1), the risks of RA in the second quartile (Q2), the third quartile (Q3) and the fourth quartile (Q4) were lower (Q2: OR=0.55, 95% CI: 0.38–0.80; Q3: OR=0.66, 95% CI: 0.44–0.97; Q4: OR=0.64, 95% CI: 0.46–0.89; trend: P=.03). The association between total flavonoids and RA remained significant after full consideration of confounding factors. With regard to the subclasses of flavonoids, high flavanones intake was associated with low RA prevalence in Model 3 (Q3: OR= 0.60, 95% CI:0.39–0.92; Q4: OR = 0.56, 95% CI: 0.32–0.99, trend: P=.02), but no such association was found in the other subclasses. Total flavonoids intake protected against RA, and the risk of developing RA decreased significantly with increasing intake of total flavonoids. Total flavonoids and flavanones were significantly associated with reduced RA risk for the American adult population. We highlighted the importance of employing diverse methodologies to assess the health effects of flavonoids.

Debate on Rice Import Policy in Indonesia: Discourse Network Analysis in Online Media

This research maps the discourses on agreements and disagreements of each actor regarding the rice import policy in Indonesia. In 2023, the Indonesian government took a policy to increase the quota of rice imports Indonesia, according to the United States Department of Agriculture, is the world’s fifth largest country in terms of rice imports. The policy was opposed and supported by a number of actors since Indonesia is also the fourth largest rice producer in the world. Actors who oppose and approve of the rice import policy in Indonesia present their respective arguments to influence the public. This research uses the Discourse Network Analysis (DNA) method to map the discourse coalition and actors based on the actors' arguments in Kompas.id media. The results show that the discourses of each actor are connected to each other. The discourses include: stabilizing rice reserves, international cooperation, reducing rice prices, anticipating climate change, importing rice during harvest, contradicting the food law, rising rice prices, rice stock alert, law enforcement against rice fraud, and rice procurement which is impossible.