Family Consumer Behaviors, Adolescent Prediabetes and Diabetes in the National Health and Nutrition Examination Survey (2007-2010)

Adapting the NIMHD Research Framework for Type 2 Diabetes-Related Disparities

PURPOSE OF REVIEW

Type 2 diabetes (T2D) disproportionately impacts minority populations. The National Institute on Minority Health and Health Disparities (NIMHD) developed a research framework to encourage health disparities research that considers a multi-level, multi-domain perspective. The purpose of this review was to describe evidence on the levels and domains that influence T2D disparities among minority populations and use this information to adapt the NIMHD Research Framework for T2D.

RECENT FINDINGS

Screening identified 108 articles published between 2017 and 2023 covering 74,354,597 participants. Articles were classified under the following domains, Biological (18), Behavioral (22), Physical/Built Environment (19), Sociocultural Environment (42), and Health Care System (31). Article levels of influence included Individual (73), Interpersonal (18), Community (36), and Societal (10). Findings were used to adapt the NIMHD Research Framework with an eye towards advancing T2D-related health equity. The results of this review confirm the complex nature of T2D-related disparities and support the notion that drivers operate within and between multiple levels and multiple domains to influence T2D-related outcomes across the lifespan.

A Comprehensive Youth Diabetes Epidemiological Data Set and Web Portal: Resource Development and Case Studies

BACKGROUND

The prevalence of type 2 diabetes mellitus (DM) and pre-diabetes mellitus (pre-DM) has been increasing among youth in recent decades in the United States, prompting an urgent need for understanding and identifying their associated risk factors. Such efforts, however, have been hindered by the lack of easily accessible youth pre-DM/DM data.

OBJECTIVE

We aimed to first build a high-quality, comprehensive epidemiological data set focused on youth pre-DM/DM. Subsequently, we aimed to make these data accessible by creating a user-friendly web portal to share them and the corresponding codes. Through this, we hope to address this significant gap and facilitate youth pre-DM/DM research.

METHODS

Building on data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we cleaned and harmonized hundreds of variables relevant to pre-DM/DM (fasting plasma glucose level ≥100 mg/dL or glycated hemoglobin  ≥5.7%) for youth aged 12-19 years (N=15,149). We identified individual factors associated with pre-DM/DM risk using bivariate statistical analyses and predicted pre-DM/DM status using our Ensemble Integration (EI) framework for multidomain machine learning. We then developed a user-friendly web portal named Prediabetes/diabetes in youth Online Dashboard (POND) to share the data and codes.

RESULTS

We extracted 95 variables potentially relevant to pre-DM/DM risk organized into 4 domains (sociodemographic, health status, diet, and other lifestyle behaviors). The bivariate analyses identified 27 significant correlates of pre-DM/DM (P<.001, Bonferroni adjusted), including race or ethnicity, health insurance, BMI, added sugar intake, and screen time. Among these factors, 16 factors were also identified based on the EI methodology (Fisher P of overlap=7.06×10-6). In addition to those, the EI approach identified 11 additional predictive variables, including some known (eg, meat and fruit intake and family income) and less recognized factors (eg, number of rooms in homes). The factors identified in both analyses spanned across all 4 of the domains mentioned. These data and results, as well as other exploratory tools, can be accessed on POND.

CONCLUSIONS

Using NHANES data, we built one of the largest public epidemiological data sets for studying youth pre-DM/DM and identified potential risk factors using complementary analytical approaches. Our results align with the multifactorial nature of pre-DM/DM with correlates across several domains. Also, our data-sharing platform, POND, facilitates a wide range of applications to inform future youth pre-DM/DM studies.

Facilitating youth diabetes studies with the most comprehensive epidemiological dataset available through a public web portal

The prevalence of type 2 diabetes mellitus (DM) and prediabetes (preDM) is rapidly increasing among youth, posing significant health and economic consequences. To address this growing concern, we created the most comprehensive youth-focused diabetes dataset to date derived from National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018. The dataset, consisting of 15,149 youth aged 12 to 19 years, encompasses preDM/DM relevant variables from sociodemographic, health status, diet, and other lifestyle behavior domains. An interactive web portal, POND (Prediabetes/diabetes in youth ONline Dashboard), was developed to provide public access to the dataset, allowing users to explore variables potentially associated with youth preDM/DM. Leveraging statistical and machine learning methods, we conducted two case studies, revealing established and lesser-known variables linked to youth preDM/DM. This dataset and portal can facilitate future studies to inform prevention and management strategies for youth prediabetes and diabetes.

Shiftwork Is Associated with Higher Food Insecurity in U.S. Workers: Findings from a Cross-Sectional Study (NHANES)

The number of shift workers has increased substantially within the last decades to keep pace with the increasingly complex societal need for 24 h services. Shift work has been associated with unhealthy lifestyles and a lower overall diet quality. Little is known, however, with regard to food security and consumer behavior in shift workers. The present study sought to address this gap in the literature, exploring a sample of n = 4418 day workers and n = 1065 shift workers in the United States. Using cross-sectional data from the National Health and Nutrition Examination Surveys (NHANES, 2007−2010), we found that shiftwork was associated with a lower amount of money spent on eating out and higher food insecurity issues. Compared to day workers, a higher proportion of shift workers reported receipt of food stamps (12.5% vs. 23.4%, p < 0.001) and worried about running out of food (3.95% vs. 8.05%, p < 0.001). These associations remained significant after adjustment for confounders when using multivariate logistic regression. The number of not-home-prepared meals did not differ between both groups. In light of the population health disparities and adverse health outcomes associated with food insecurity, novel strategies are urgently warranted to improve the situation of shift workers.

Fiber-rich foods delivered to Low-Income Households: A feasibility study of children with prediabetes and spillover effect on their caregivers

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Vegetables and whole grains delivered weekly to households with diabetes risk.

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Children with prediabetes increased liking of whole grains and vegetables.

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Children with prediabetes increased consumption of whole grains but not vegetables.

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Adults improved health outcomes but children did not, despite being study target.

Introduction

The incidence of pediatric prediabetes and type 2 diabetes mellitus (T2DM) is increasing, with those from low socioeconomic status (SES) households at increased risk. Dietary fiber (e.g., whole grains) is shown to improve glucose control and there is need for innovative strategies that address barriers to consumption (e.g., limited availability).

Methods

Food Overcoming our Diabetes Risk (FoodRx) was a pre-post study (N = 47) that provided 16 weeks of home-delivered whole grains, vegetables, and beans/legumes to households of low-income children in [blinded for submission] who had obesity and prediabetes. Child liking and intake (24-hour diet recalls) was evaluated. Anthropometrics and T2DM-related laboratory measurements (e.g. glycated hemoglobin) were measured for children, and for caregivers to evaluate potential spillover effect.

Results

Post-intervention, children increased liking of whole grains, vegetables, and beans/legumes (P < 0.05 for all). Child whole grain intake increased from 1.7 to 2.5 oz-equivalent servings/day (P < 0.001), and the percent of total grain intake that were whole increased from 30% to 44% (P < 0.001). Children’s body mass index, blood pressure, and serum triglyceride levels increased (+14.6 mg/dl, P = 0.04). Caregivers fasting glucose (-7.5 mg/dl; P = 0.03), fasting insulin (-2.5 μIU/ml, P = 0.0009) and homeostatic model assessment for insulin resistance (HOMA-IR) decreased (-0.8, P = 0.01).

Conclusions

Home deliveries of fiber rich foods improved liking and intake among children at risk for T2DM. There was spillover effect on caregivers, who demonstrated improvement in T2DM-related laboratory measurements instead of the children.

Association of Home Food Availability with Prediabetes and Diabetes among Adults in the United States

This study examined associations of home food availabilities with prediabetes and diabetes among 8929 adults (20–70 years) participating in 2007–2010 National Health and Nutrition Examination Surveys. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated by logistic regression. Relative to non-diabetic participants (individuals without diabetes or prediabetes), prediabetes participants were associated with lower availabilities of green vegetables (OR = 0.82; 95% CI = 0.73–0.91; p = 0.0006) and fat-free/low-fat milk (OR = 0.80, 95% CI = 0.65–0.89; p = 0.001) and higher sugary drink availability (OR = 1.24, 95% CI = 1.04–1.48; p = 0.02), adjusting for age, sex, and ethnicity (Model 1). The associations remained significant for vegetables (p = 0.005) and fat-free/low-fat milk (p = 0.02) adjusting for additional confounders (body mass index, education, Model 2). Adjusting for dietary components did not change the above results (in model 2) significantly. Participants with high healthy food availability scores had approximately 31% reduction (p = 0.003) in odds of prediabetes compared to those with low scores in Model 1. No associations were detected for diabetes except for fat-free/low-fat milk availability, for which an inverse association was observed in Model 1 (OR = 0.80, 95% CI = 0.65–0.99; p = 0.04). The results show prediabetes participants had lower availability of healthy foods and higher availability of unhealthy foods, suggesting the need to improve healthy food availability at home for this population.