The correlation between food insecurity and infant mortality in North Carolina.
Ontology highlight
ABSTRACT: Objective
Food insecurity (FI) affects approximately 11·1 % of US households and is related to worsened infant outcomes. Evidence in lower income countries links FI and infant mortality rates (IMR), but there are limited data in the USA. This study examines the relationship between FI and IMR in North Carolina (NC).Design
NC county-level health data were used from the 2019 Robert Woods Johnson Foundation County Health Rankings. The dependent variable was county-level IMR. Eighteen county-level independent variables were selected and a multivariable linear regression was performed. The independent variable, FI, was based on the United States Department of Agriculture's Food Security Supplement to the Current Population Survey.Setting
NC counties.Participants
Residents of NC, county-level data.Results
The mean NC county-level IMR was 7·9 per 1000 live births compared with 5·8 nationally. The average percentage of county population reporting FI was 15·4 % in the state v. 11·8 % nationally. Three variables statistically significantly predicted county IMR: percent of county population reporting FI; county population and percent population with diabetes (P values, respectively, < 0·04; < 0·05; < 0·03). These variables explained 42·4 % of the variance of county-level IMR. With the largest standardised coefficient (0·247), FI was the strongest predictor of IMR.Conclusions
FI, low birth weight and diabetes are positively correlated with infant mortality. While correlation is not causation, addressing FI as part of multifaceted social determinants of health might improve county-level IMR in NC.
SUBMITTER: Cassidy-Vu L
PROVIDER: S-EPMC9991794 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
The correlation between food insecurity and infant mortality in North Carolina.
Cassidy-Vu Lisa L Way Victoria V Spangler John J
Public health nutrition 20220131 4
<h4>Objective</h4>Food insecurity (FI) affects approximately 11·1 % of US households and is related to worsened infant outcomes. Evidence in lower income countries links FI and infant mortality rates (IMR), but there are limited data in the USA. This study examines the relationship between FI and IMR in North Carolina (NC).<h4>Design</h4>NC county-level health data were used from the 2019 Robert Woods Johnson Foundation County Health Rankings. The dependent variable was county-level IMR. Eightee ...[more]
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Project description:IntroductionSocial insecurity, a form of deprivation of social amenities, if present among patients presenting in a rural emergency department (ED) can be a source of medical burden and poor health outcomes. Although knowledge and understanding of the insecurity profile of such patients is necessary for targeted care that improves their health outcomes, the concept has not been comprehensively quantified. In this study we explored, characterized, and quantified the social insecurity profile of ED patients at a rural teaching hospital in southeastern North Carolina with a large Native American population.MethodsA paper survey questionnaire was administered by trained research assistants between May-June 2018 to patients who presented to the ED and consented to participate in this cross-sectional, single-center study. The survey was anonymous with no identifying information collected on the respondents. A general demographic section and questions derived from the literature capturing sub-constructs of social insecurity-communication access, access to transportation, housing insecurity and home environment, food insecurity, and exposure to violence-were captured in the survey. We assessed the factors included in the index of social insecurity based on a rank ordering using the magnitude of their coefficient of variation and the Cronbach's alpha reliability index of the constituent items.ResultsOverall, we collected 312 surveys from the approximately 445 administered and included them in the analysis, representing a response rate of about 70%. The average age of the 312 respondents was 45.1 (±17.7) years with a range of 18.0-96.0. More females (54.2%) than males participated in the survey. Native Americans (34.3%), Blacks (33.7%), and Whites (27.6%) comprised the three major racial/ethnicity groups of the sample, which are representative of the study area's population distribution. Social insecurity was observed among this population regarding all the subdomains and an overall measure (P <.001). We identified three key determinants of social insecurity-food insecurity, transportation insecurity, and exposure to violence. Social insecurity significantly differed overall and among the three of its key constituent domains by patients' race/ethnicity and gender (P <.05).ConclusionEmergency department visits in a rural North Carolina teaching hospital are characterized by a diverse patient population, including patients with some degree of social insecurity. Historically marginalized and minoritized groups including Native Americans and Blacks demonstrated overall higher rates of social insecurity and higher indexes on exposure to violence than their White counterparts. Such patients struggle with basic needs such as food, transportation, and safety. As social factors play a critical role in health outcomes, supporting the social well-being of a historically marginalized and minoritized rural community would likely help build the foundation for safe livelihood with improved and sustainable health outcomes. The need for a more valid and psychometrically desirable measurement tool of social insecurity among ED populations is compelling.
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Project description:Background: Sudden infant death syndrome (SIDS) is the sudden, unexplained death of infants <1 year old. SIDS remains a leading cause of death in US infants. We aim to identify associations between SIDS and race/ethnicity, birth weight/gestational age, and socioeconomic/environmental factors in North Carolina (NC) to help identify infants at risk for SIDS. Methods and Results: In this IRB-approved study, infant mortality 2007-2016 and death certificate-linked natality 2007-2014 were obtained from the NC Department of Health and Human Services. General, NC natality statistics 2007-2016 were obtained from CDC Wonder. Association between SIDS/total infant death and covariates (below) were calculated. Total infant mortality decreased 2007-2016 by an average of 14 deaths/100,000 live births per year, while SIDS incidence remained constant. Risk ratios of SIDS/total infant deaths, standardized to Non-Hispanic White, were 1.76/2.41 for Non-Hispanic Black and 0.49/0.97 for Hispanic infants. Increased SIDS risk was significantly and independently associated with male infant sex, Non-Hispanic Black maternal race/ethnicity, young maternal age, low prenatal care, gestational age <39 weeks, birthweight <2500 g, low maternal education, and maternal tobacco use (p < 0.01). Maternal previous children now deceased also trended toward association with increased SIDS risk. Conclusions: A thorough SIDS risk assessment should include maternal, socioeconomic, and environmental risk factors as these are associated with SIDS in our population.
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Project description:The obesity epidemic continues to challenge global health, driven by multifaceted environmental and biological factors. Here, we investigate the impact of food insecurity, characterized by unpredictable food access, on body weight, food intake, and body composition in mice. Male and female C57BL/6J mice were subjected to a combination of intermittent fasting and 5% calorie restriction to resemble food insecurity situations. Our results reveal that this novel food insecurity model promotes fat accumulation and decreases lean mass in both sexes on a standard chow diet. While food insecurity did not exacerbate fat gain in male mice fed a high-fat diet, it further reduced lean mass. RNA sequencing of epididymal white adipose tissue from food-insecure male mice identified upregulated lipid metabolism genes and downregulated immune response genes, suggesting adipocyte expansion and potential immunity dysfunction. These results challenge the traditional view that obesity is solely driven by positive energy balance. Instead, our findings highlight the role of food insecurity in promoting metabolic adaptations favouring fat storage. Our data provide biological mechanisms that may explain the dramatic rise in obesity, underscoring the importance of socio-economic factors, beyond diet composition and energy balance, in understanding the complex etiology of obesity.
2025-06-04 | GSE274149 | GEO
Project description:OBJECTIVE:Obtaining valid, reliable measures of food environments that serve Latino communities is important for understanding barriers to healthy eating in this at-risk population. DESIGN:The primary aim of the study was to examine agreement between retail food outlet data from two commercial databases, Nielsen TDLinx (TDLinx) for food stores and Dun & Bradstreet (D&B) for food stores and restaurants, relative to field observations of food stores and restaurants in thirty-one census tracts in Durham County, NC, USA. We also examined differences by proportion of Hispanic population (</?23·4 % Hispanic population) in the census tract and for outlets classified in the field as 'Latino' on the basis of signage and use of Spanish language. SETTING:One hundred and seventy-four food stores and 337 restaurants in Durham County, NC, USA. RESULTS:We found that overall sensitivity of food store listings in TDLinx was higher (64 %) than listings in D&B (55 %). Twenty-five food stores were characterized by auditors as Latino food stores, with 20 % identified in TDLinx, 52 % in D&B and 56 % in both sources. Overall sensitivity of restaurants (68 %) was higher than sensitivity of Latino restaurants (38 %) listed in D&B. Sensitivity did not differ substantially by Hispanic composition of neighbourhoods. CONCLUSIONS:Our findings suggest that while TDLinx and D&B commercial data sources perform well for total food stores, they perform less well in identifying small and independent food outlets, including many Latino food stores and restaurants.
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Project description:BackgroundMany studies have explored the heat-mortality relationship; however, comparability of results is hindered by the studies' use of different exposure methods.ObjectiveThis study evaluated different methods for estimating exposure to temperature using individual-level data and examined the impacts on the heat-mortality relationship.MethodsWe calculated different temperature exposures for each individual death by using a modeled, gridded temperature dataset and a monitoring station dataset in North Carolina for 2000-2016. We considered individual-level vs. county-level averages and measured vs. modeled temperature data. A case-crossover analysis was conducted to examine the heat-mortality risk under different exposure methods.ResultsThe minimum mortality temperature (MMT) (i.e., the temperature with the lowest mortality rate) for the monitoring station dataset was 23.87 °C and 22.67 °C (individual monitor and county average, respectively), whereas for the modeled temperature dataset the MMT was 19.46 °C and 19.61 °C (individual and county, respectively). We found higher heat-mortality risk while using temperature exposure estimated from monitoring stations compared to risk based on exposure using the modeled temperature dataset. Individual-aggregated monitoring station temperature exposure resulted in higher heat mortality risk (odds ratio (95% CI): 2.24 (95% CI: 2.21, 2.27)) for a relative temperature change comparing the 99th and 90th temperature percentiles, while modeled temperature exposure resulted in lower odds ratio of 1.27 (95% CI: 1.25, 1.29).SignificanceOur findings indicate that using different temperature exposure methods can result in different temperature-mortality risk. The impact of using various exposure methods should be considered in planning health policies related to high temperatures, including under climate change. IMPACT STATEMENT: (1) We estimated the heat-mortality association using different methods to estimate exposure to temperature. (2) The mean temperature value among different exposure methods were similar although lower for the modeled data, however, use of the monitoring station temperature dataset resulted in higher heat-mortality risk than the modeled temperature dataset. (3) Differences in mortality risk from heat by urbanicity varies depending on the method used to estimate temperature exposure.
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Project description:Food insecurity is a major public health problem worldwide. In India, there are limited food insecurity assessment studies using a conventionally accepted method like the Food Insecurity Experience Scale (FIES), developed by the Food and Agricultural Organization (FAO). This study aims to measure food insecurity using the FIES and explore its determinants and association with body mass index (BMI) among Indian adults. METHODS: In a cross-sectional study, we used FIES to measure food security in a sample of 9005 adults residing in North and South India. Using questionnaires, socio-demographic factors, dietary intake and food security data were collected. The dietary diversity scores (FAO-IDDS) and food insecurity scores (FAO-FIES) were calculated. Body size was measured and BMI was calculated. RESULTS: The mean age of the study participants was 52.4 years (± 11.7); half were women and half resided in rural areas. Around 10% of the participants reported having experienced (mild or moderate or severe) food insecurity between October 2018 and February 2019. Dietary diversity (measured by FAO's Individual Dietary Diversity Scores, IDDS) was low and half of the participants consumed ≤ 3 food groups/day. The mean BMI was 24.7 kg/m2. In the multivariate analysis, a lower IDDS and BMI were associated with a higher FIES. The place of residence, gender and wealth index were important determinants of FIES, with those residing in South India, women and those belonging to the poorest wealth index reporting higher food insecurity. Food security is understudied in India. Our study adds important evidence to the literature. Despite having marginal food insecurity, high prevalence of low diet quality, especially among women, is disconcerting. Similar studies at the national level are warranted to determine the food insecurity situation comprehensively in India and plan appropriate policy actions to address it effectively, to attain the key Sustainable Development Goals (SDG).
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Project description:BackgroundHealth disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial.ObjectiveWe examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers.MethodsWe applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures).ResultsWe found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM2.5, lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education).ConclusionResults indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.
| S-EPMC8214419 | biostudies-literature
Project description:BackgroundFood insecurity is associated with a wide array of negative health outcomes and higher health care costs but there has been no population-based study of the association of food insecurity and mortality in high-income countries.MethodsWe use cross-sectional population surveys linked to encoded health administrative data. The sample is 90,368 adults, living in Ontario and respondents in the Canadian Community Health Survey (CCHS). The outcome of interest is all-cause mortality at any time after the interview and within four years of the interview. The primary variable of interest is food insecurity status, with individuals classed as "food secure", "marginally food insecure", "moderately food insecure", or "severely food insecure". We use logistic regression models to determine the association of mortality with food insecurity status, adjusting for other social determinants of health.ResultsUsing a full set of covariates, in comparison to food secure individuals, the odds of death at any point after the interview are 1.28 (CI = 1.08, 1.52) for marginally food insecure individuals, 1.49 (CI = 1.29, 1.73) for moderately food insecure individuals, and 2.60 (CI = 2.17, 3.12) for severely food insecure individuals. When mortality within four years of the interview is considered, the odds are, respectively, 1.19 (CI = 0.95, 1.50), 1.65 (CI = 1.37, 1.98), and 2.31 (CI = 1.81, 2.93).InterpretationThese findings demonstrate that food insecurity is associated with higher mortality rates and these higher rates are especially large for the most severe food insecurity category. Efforts to reduce food insecurity should be incorporated into broader public health initiatives to reduce mortality.
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Project description:BackgroundLittle is known about patterns of household food insecurity (HFI) across more than two time points in adults in the United States, the frequency predictors of different trajectories. The distinctions between persistent and transient food insecurity trajectories may be crucial to developing effective interventions.ObjectiveTo characterize dominant trajectories of food security status over three time points between 2013 and 2016 and identify demographic, socioeconomic and health-related predictors of persistent and transient HFI.DesignCohort study in disadvantaged communities in South Carolina.Settingand subjects: 397 middle-aged participants, predominantly female, African American, living in USDA-designated food deserts.Main outcome measureHousehold food insecurity over time using the 18-item USDA's Household Food Security Survey Module.Statistical analyses performedDescriptive analyses of food security trajectories and multinomial regression analyses.ResultsAt baseline (2013-2014), 61% of households reported HFI during the previous 12 months, which decreased to 54% in 2015 and to 51% in 2016. Only 27% of households were persistently food secure, 36% experienced transient and 37% persistent food insecurity. Female sex (OR 2.7, 95%CI 1.2-5.9), being married or living with a partner (OR 2.4, 95CI% 1.1-5.3) and fair health status (OR 4.4, 95%CI 2.2-8.8) were associated with increased odds of persistent food insecurity. Fair health was also a significant predictor of transient food insecurity.ConclusionsThese findings suggest that future research should focus on persistent versus transient trajectories separately and that tailored interventions may be needed to make progress on alleviating food insecurity among disadvantaged communities.
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Project description:The residents of southeastern North Carolina (NC) are exposed to multiple socioeconomic and environmental risk factors and have higher mortality rates for a number of diseases. Uterine cancer mortality is known to vary dramatically by race, so we analyzed uterine cancer mortality in populations defined by zip codes in this area to investigate the contributions of various environmental risk factors to race-specific disease patterns. Methods. Zip code specific mortality and hospital admissions for uterine cancer from 2007 to 2013 were analyzed using the NC State Center for Health Statistics data and the Inpatient Database of the Healthcare Cost and Utilization Project datafiles, respectively. Results were adjusted for age, income, education, health insurance coverage, prevalence of current smokers, and density of primary care providers. Results. Uterine cancer mortality rates were generally higher in African American (32.5/100,000, 95% CI = 18.9-46.1) compared to White (19.6/100,000, 95% CI = 12.3-26.9) females. Odds ratios (ORs) of uterine cancer death were higher in White females (OR = 2.27, p < 0.0001) residing within zip codes with hog concentrated animal feeding operations (CAFOs) (hog density >215 hogs/km2) than in White females residing in non-CAFO communities. African American females living near CAFOs had less pronounced increase of uterine cancer death (OR = 1.08, p=0.7657). Conclusion. White females living in adjacent to hog CAFOs areas of southeastern NC have lower rates of mortality from uterine cancer than African American females, but they have higher odds of death compared to their counterparts living in other NC areas. African American females living near CAFOs also have modest increases from their high baseline mortality. While the observed associations do not prove a causation, improving access to screening and medical care is important to mitigate this health issues in southeastern NC.
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