Household food insecurity and associations with hemoglobin A1c and acute diabetes-related complications in youth and young adults with type 1 diabetes: The SEARCH for Diabetes in Youth study.

AIMS: To examine, among youth and young adults (YYA) with type 1 diabetes (T1D), the association of household food insecurity (HFI) with: 1) HbA1c and 2) episodes of diabetic ketoacidosis (DKA) and severe hypoglycemia. METHODS: HFI was assessed using the U.S. Household Food Security Survey Module in SEARCH for Diabetes in Youth participants with T1D between 2016 and 2019. Linear and logistic regression models adjusted for age, diabetes duration, sex, race, ethnicity, clinic site, parent/participant education, household income, health insurance, and diabetes technology use. RESULTS: Of 1830 participants (mean age 20.8 ± 5.0 years, 70.0 % non-Hispanic White), HbA1c was collected for 1060 individuals (mean HbA1c 9.2 % ± 2.0 %). The prevalence of HFI was 16.4 %. In the past 12 months, 18.2 % and 9.9 % reported an episode of DKA or severe hypoglycemia, respectively. Compared to participants who were food secure, HFI was associated with a 0.33 % (95 % CI 0.003, 0.657) higher HbA1c level. Those with HFI had 1.58 (95 % CI 1.13, 2.21) times the adjusted odds of an episode of DKA and 1.53 (95 % CI 0.99, 2.37) times the adjusted odds of an episode of severe hypoglycemia as those without HFI. CONCLUSIONS: HFI is associated with higher HbA1c levels and increased odds of DKA in YYA with T1D.

Diabetes Stigma and Clinical Outcomes in Adolescents and Young Adults: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To examine the association between diabetes stigma and HbA1c, treatment plan and acute and chronic complications in adolescents and young adults (AYAs) with type 1 or type 2 diabetes. RESEARCH DESIGN AND METHODS: The SEARCH for Diabetes in Youth study is a multicenter cohort study that collected questionnaire, laboratory, and physical examination data about AYAs with diabetes diagnosed in childhood. A five-question survey assessed frequency of perceived diabetes-related stigma, generating a total diabetes stigma score. We used multivariable linear modeling, stratified by diabetes type, to examine the association of diabetes stigma with clinical factors, adjusting for sociodemographic characteristics, clinic site, diabetes duration, health insurance, treatment plan, and HbA1c. RESULTS: Of 1,608 respondents, 78% had type 1 diabetes, 56% were female, and 48% were non-Hispanic White. The mean (SD) age at study visit was 21.7 (5.1) years (range, 10-24.9). The mean (SD) HbA1c was 9.2% (2.3%; 77 mmol/mol [2.0 mmol/mol]). Higher diabetes stigma scores were associated with female sex and higher HbA1c (P < 0.01) for all participants. No significant association between diabetes stigma score and technology use was observed. In participants with type 2 diabetes, higher diabetes stigma scores were associated with insulin use (P = 0.04). Independent of HbA1c, higher diabetes stigma scores were associated with some acute complications for AYAs with type 1 diabetes and some chronic complications for AYAs with type 1 or type 2 diabetes. CONCLUSIONS: Diabetes stigma in AYAs is associated with worse diabetes outcomes and is important to address when providing comprehensive diabetes care.

Prevalence and Predictors of Household Food Insecurity and Supplemental Nutrition Assistance Program Use in Youth and Young Adults With Diabetes: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To assess the prevalence of household food insecurity (HFI) and Supplemental Nutrition Assistance Program (SNAP) participation among youth and young adults (YYA) with diabetes overall and by type, and sociodemographic characteristics. RESEARCH DESIGN AND METHODS: The study included participants with youth-onset type 1 diabetes and type 2 diabetes from the SEARCH for Diabetes in Youth study. HFI was assessed using the 18-item U.S. Household Food Security Survey Module (HFSSM) administered from 2016 to 2019; three or more affirmations on the HFSSM were considered indicative of HFI. Participants were asked about SNAP participation. We used χ2 tests to assess whether the prevalence of HFI and SNAP participation differed by diabetes type. Multivariable logistic regression models were used to examine differences in HFI by participant characteristics. RESULTS: Of 2,561 respondents (age range, 10-35 years; 79.6% ≤25 years), 2,177 had type 1 diabetes (mean age, 21.0 years; 71.8% non-Hispanic White, 11.8% non-Hispanic Black, 13.3% Hispanic, and 3.1% other) and 384 had type 2 diabetes (mean age, 24.7 years; 18.8% non-Hispanic White, 45.8% non-Hispanic Black, 23.7% Hispanic, and 18.7% other). The overall prevalence of HFI was 19.7% (95% CI 18.1, 21.2). HFI was more prevalent in type 2 diabetes than type 1 diabetes (30.7% vs. 17.7%; P < 0.01). In multivariable regression models, YYA receiving Medicaid or Medicare or without insurance, whose parents had lower levels of education, and with lower household income had greater odds of experiencing HFI. SNAP participation was 14.1% (95% CI 12.7, 15.5), with greater participation among those with type 2 diabetes compared with those with type 1 diabetes (34.8% vs. 10.7%; P < 0.001). CONCLUSIONS: Almost one in three YYA with type 2 diabetes and more than one in six with type 1 diabetes reported HFI in the past year-a significantly higher prevalence than in the general U.S. population.

Inequalities in Glycemic Control in Youth with Type 1 Diabetes Over Time: Intersectionality Between Socioeconomic Position and Race and Ethnicity.

BACKGROUND: Racial/ethnic health inequities have been well-documented among youth and young adults with type 1 diabetes (T1D), yet little is known about how socioeconomic position (SEP) intersects with the risk marker of race/ethnicity to predict inequities in longitudinal glycemic control. PURPOSE: To identify patterns of SEP, race/ethnicity, and clinical characteristics that differentiate hemoglobin A1c (HbA1c) trajectories among youth and young adults after T1D diagnosis. METHODS: The SEARCH for Diabetes in Youth cohort includes youth with diabetes diagnosed from 2002 to 2006 and 2008 who were followed through 2015. We analyzed data from 1,313 youth and young adults with T1D with ≥3 HbA1c measures. Classification tree analysis identified patterns of baseline demographic, SEP, and clinical characteristic that best predicted HbA1c trajectories over an average of 8.3 years using group-based trajectory modeling. RESULTS: Two HbA1c trajectories were identified: Trajectory 1 (77%) with lower baseline HbA1c and mild increases (from mean 7.4% to 8.4%) and Trajectory 2 (23%) with higher baseline HbA1c and major increases (from 8.5% to 11.2%). Race/ethnicity intersected with different SEP characteristics among non-Hispanic white (NHW) than in non-whites. Public health insurance predicted high-risk Trajectory 2 membership in non-whites, whereas parental education, household structure, diagnosis age and glucose checking frequency predicted membership for NHW youth and young adults. Two characteristics, race/ethnicity and parental education alone identified 80% of the Trajectory 2 members. CONCLUSIONS: Race/ethnicity intersects with multiple SEP and clinical characteristics among youth and young adults with T1D, which is associated with particularly high risk of poor long-term glycemic control.

Exploring Disparities in Youth Physical Activity Environments by Income and Non-Hispanic White Population Across the United States.

This study investigated relationships between youth physical activity (PA) environments and income and non-Hispanic White population across the United States, stratified by US Census region and urban-rural designation. For all counties (n = 3142), publicly accessible data were used for sociodemographic indicators (ie, median household income and percent non-Hispanic White population) and a composite PA environment index (including exercise opportunities, violent crime incidence, walkability, and access to public schools). One-way analysis of variance was used to examine differences in PA environment index values according to income and non-Hispanic White population tertiles. There were significant differences in PA environments according to tertiles of income (F = 493.5, P < .001) and non-Hispanic White population (F = 58.6, P < .001), including variations by region and urban-rural designation. Public health practice and policy initiatives, such as joint use agreements, Safe Routes to School programs, and targeted funding allocations, should be used to address more pronounced income-based disparities in Southern and metropolitan counties and race-based disparities in rural and micropolitan counties.

Disparities in Hemoglobin A1c Testing During the Transition to Adulthood and Association With Diabetes Outcomes in Youth-Onset Type 1 and Type 2 Diabetes: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To identify correlates of hemoglobin A1c (HbA1c) testing frequency and associations with HbA1c levels and microvascular complications in youth-onset diabetes. RESEARCH DESIGN AND METHODS: The SEARCH for Diabetes in Youth study collected data from individuals diagnosed with diabetes before age 20 at 8 years (n=1,885 type 1, n=230 type 2) and 13 years (n=649 type 1, n = 84 type 2) diabetes duration. We identified correlates of reporting ≥3 HbA1c tests/year using logistic regression. We examined associations of HbA1c testing with HbA1c levels and microvascular complications (retinopathy, neuropathy, or nephropathy) using sequentially adjusted linear and logistic regression. RESULTS: For type 1 diabetes, odds of reporting ≥3 HbA1c tests/year at 8 and 13 years diabetes duration decreased with older age at diagnosis (odds ratio [OR] 0.91 [95% CI 0.88-0.95]), longer duration of diabetes (OR 0.90 [0.82-0.99]), not having a personal doctor (OR 0.44 [0.30-0.65]), and lapses in health insurance (OR 0.51 [0.27-0.96]). HbA1c testing ≥3 times/year over time was associated with lower HbA1c levels (OR -0.36% [-0.65 to -0.06]) and lower odds of microvascular complications (OR 0.64 [0.43-0.97]) at 13 years duration, but associations were attenuated after adjustment for HbA1c testing correlates (OR -0.17 [-0.46 to 0.13] and 0.70 [0.46-1.07], respectively). For type 2 diabetes, not seeing an endocrinologist decreased the odds of reporting ≥3 HbA1c tests/year over time (OR 0.19 [0.06-0.63]), but HbA1c testing frequency was not associated with HbA1c levels or microvascular complications. CONCLUSIONS: We observed disparities in HbA1c testing frequency predominately by health care-related factors, which were associated with diabetes outcomes in type 1 diabetes.

Incongruency of youth food and physical activity environments in the United States: Variations by region, rurality, and income.

Local environments are increasingly the focus of health behavior research and practice to reduce gaps between fruit/vegetable intake, physical activity (PA), and related guidelines. This study examined the congruency between youth food and PA environments and differences by region, rurality, and income across the United States. Food and PA environment data were obtained for all U.S. counties (N = 3142) using publicly available, secondary sources. Relationships between the food and PA environment tertiles was represented using five categories: 1) congruent-low (county falls in both the low food and PA tertiles), 2) congruent-high (county falls in both the high food and PA tertiles), 3) incongruent-food high/PA low (county falls in high food and low PA tertiles), 4) incongruent-food low/PA high (county falls in low food and high PA tertiles), and 5) intermediate food or PA (county falls in the intermediate tertile for food and/or PA). Results showed disparities in food and PA environment congruency according to region, rurality, and income (p < .0001 for each). Nearly 25% of counties had incongruent food and PA environments, with food high/PA low counties mostly in rural and low-income areas, and food low/PA high counties mostly in metropolitan and high-income areas. Approximately 8.7% of counties were considered congruent-high and were mostly located in the Northeast, metropolitan, and high-income areas. Congruent-low counties made up 10.0% of counties and were mostly in the South, rural, and low-income areas. National and regional disparities in environmental obesity determinants were identified that can inform targeted public health interventions.

Persistence and transience of food insecurity and predictors among residents of two disadvantaged communities in South Carolina.

BACKGROUND: Little 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. OBJECTIVE: To 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. DESIGN: Cohort study in disadvantaged communities in South Carolina. SETTING: and subjects: 397 middle-aged participants, predominantly female, African American, living in USDA-designated food deserts. MAIN OUTCOME MEASURE: Household food insecurity over time using the 18-item USDA's Household Food Security Survey Module. STATISTICAL ANALYSES PERFORMED: Descriptive analyses of food security trajectories and multinomial regression analyses. RESULTS: At 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. CONCLUSIONS: These 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.

Recruitment and Retention for the Evaluation of a Healthy Food Initiative in Economically Disadvantaged, Majority African American Communities.

Effective recruitment and retention supports equitable participation in research. The aim of this article is to describe recruitment and retention methods among residents of highly disadvantaged, predominantly African American communities in the southeastern United States during the evaluation of a healthy food access initiative. We proposed that active and passive recruitment methods, intensive retention strategies, community outreach and involvement, over-enrollment to anticipate attrition, and applied principles of community participation would achieve the study's recruitment and retention goals. The enrollment goal of 560 was met at 94% (n = 527), and the retention goal of 400 was achieved (n = 408).

Socioeconomic position is associated with glycemic control in youth and young adults with type 1 diabetes.

OBJECTIVE: Health inequities persist in youth and young adults (YYA) with type 1diabetes in achieving optimal glycemic control. The purpose of this study was to assess the contribution of multiple indicators of social need to these inequities. RESEARCH DESIGN AND METHODS: Two hundred and twenty two YYA withtype 1 diabetes enrolled in the SEARCH Food Insecurity Study in South Carolina and Washington between the years 2013 and 2015 were included. Latent class analysis was used to identify socioeconomic profiles based on household income, parental education, health insurance, household food insecurity, and food assistance. Profiles were evaluated in relation to glycemic control using multivariable linear and logistic regression, with HbA1c > 9%(75 mmol/mol) defined as high-risk glycemic control. RESULTS: Two profiles were identified: a lower socioeconomic profile included YYA whose parents had lower income and/or education, and were more likely to be uninsured, receive food assistance, and be food insecure. A higher socioeconomic profile included YYA whose circumstances were opposite to those in the lower socioeconomic profile. Those with a lower socioeconomic profile were more likely to have high-risk glycemic control relative to those with a higher socioeconomic profile (OR = 2.24, 95%CI = 1.16-4.33). CONCLUSIONS: Lower socioeconomic profiles are associated with high-risk glycemic control among YYA with type 1 diabetes. This supports recommendations that care providers of YYA with type 1 diabetes assess individual social needs in tailoring diabetes management plans to the social context of the patient.

Socioeconomic factors associated with diet quality and meeting dietary guidelines in disadvantaged neighborhoods in the Southeast United States.

Objective: To examine diet quality and dietary intake among residents of disadvantaged neighborhoods in the Southeast United States (U.S.) and to examine associations between dietary and socioeconomic factors. Design: We examined baseline data from an evaluation study of a healthy food access initiative. Participants were recruited from two urban settings comprising seven neighborhoods of high household poverty (17% to 62%). Participants completed in-person interviews with measures of education, household income, and food security and one unannounced 24-hour dietary recall by telephone with trained registered dietitians. Food desert residence was coded based on U.S. Census data. Proportions meeting 2010 Dietary Guidelines for Americans and Healthy Eating Index 2010 (HEI-2010) scores were computed. Associations between dietary variables and participant's education, household income, food security, and food desert residence were tested. Results: Participants (n = 465) were predominantly African American (92%), women (80%), and overweight or obese (79%), and 52 ± 14 years of age. Sixty-three percent had low or very low food security, and 82% lived in census tracts of low income and low access to supermarkets (urban food desert). HEI-2010 scores averaged 48.8 ± 13.1. A minority of participants met dietary guidelines. Diet quality was lower among participants with lower education and among those from food insecure households (p < .05). Household income and food security were positively associated with meeting several dietary guidelines (p < .05). Food desert residence was unrelated to diet variables. Conclusions: In this disadvantaged population, significant nutritional concerns were observed, and socioeconomic factors were associated with diet quality and meeting dietary guidelines. Interventions must address broader economic, social, and policy issues such as access to affordable healthy foods.

Health care access and glycemic control in youth and young adults with type 1 and type 2 diabetes in South Carolina.

Affordability and geographic accessibility are key health care access characteristics. We used data from 481 youth and young adults (YYA) with diabetes (389 type 1, 92 type 2) to understand the association between health care access and glycemic control as measured by HbA1c values. In multivariate models, YYA with state or federal health insurance had HbA1c percentage values 0.68 higher (P = 0.0025) than the privately insured, and those without insurance 1.34 higher (P < 0.0001). Not having a routine diabetes care provider was associated with a 0.51 higher HbA1c (P = 0.048) compared to having specialist care, but HbA1c did not differ significantly (P = 0.069) between primary vs specialty care. Distance to utilized provider was not associated with HbA1c among YYA with a provider (P = 0.11). These findings underscore the central role of health insurance and indicate a need to better understand the root causes of poorer glycemic control in YYA with state/federal insurance.

Association of Race and Ethnicity With Glycemic Control and Hemoglobin A1c Levels in Youth With Type 1 Diabetes.

IMPORTANCE: Health disparities in the clinical presentation and outcomes among youth with type 1 diabetes exist. Long-term glycemic control patterns in racially/ethnically diverse youth are not well described. OBJECTIVES: To model common trajectories of hemoglobin A1c (HbA1c) among youth with type 1 diabetes and test how trajectory group membership varies by race/ethnicity. DESIGN SETTING AND PARTICIPANTS: Longitudinal cohort study conducted in 5 US locations. The analysis included data from 1313 youths (aged <20 years) newly diagnosed in 2002 through 2005 with type 1 diabetes in the SEARCH for Diabetes in Youth study (mean [SD] age at diabetes onset, 8.9 [4.2] years) who had 3 or more HbA1c study measures during 6.1 to 13.3 years of follow-up. Data were analyzed in 2017. EXPOSURES: Self-reported race/ethnicity. MAIN OUTCOMES AND MEASURES: Hemoglobin A1c trajectories identified through group-based trajectory modeling over a mean (SD) of 9.0 (1.4) years of diabetes duration. Multinomial models studied the association of race/ethnicity with HbA1c trajectory group membership, adjusting for demographic characteristics, clinical factors, and socioeconomic position. RESULTS: The final study sample of 1313 patients was 49.3% female (647 patients) with mean (SD) age 9.7 (4.3) years and mean (SD) disease duration of 9.2 (6.3) months at baseline. The racial/ethnic composition was 77.0% non-Hispanic white (1011 patients), 10.7% Hispanic (140 patients), 9.8% non-Hispanic black (128 patients), and 2.6% other race/ethnicity (34 patients). Three HbA1c trajectories were identified: group 1, low baseline and mild increases (50.7% [666 patients]); group 2, moderate baseline and moderate increases (41.7% [548 patients]); and group 3, moderate baseline and major increases (7.5% [99 patients]). Group 3 was composed of 47.5% nonwhite youths (47 patients). Non-Hispanic black youth had 7.98 higher unadjusted odds (95% CI, 4.42-14.38) than non-Hispanic white youth of being in the highest HbA1c trajectory group relative to the lowest HbA1c trajectory group; the association remained significant after full adjustment (adjusted odds ratio of non-Hispanic black race in group 3 vs group 1, 4.54; 95% CI, 2.08-9.89). Hispanic youth had 3.29 higher unadjusted odds (95% CI, 1.78-6.08) than non-Hispanic white youth of being in the highest HbA1c trajectory group relative to the lowest HbA1c trajectory group; the association remained significant after adjustment (adjusted odds ratio of Hispanic ethnicity in group 3 vs group 1, 2.24; 95% CI, 1.02-4.92). In stratified analyses, the adjusted odds of nonwhite membership in the highest HbA1c trajectory remained significant among male patients and youth diagnosed at age 9 years or younger, but not female patients and youth who were older than 9 years when they were diagnosed (P for interaction = .04 [sex] and .02 [age at diagnosis]). CONCLUSIONS AND RELEVANCE: There are racial/ethnic differences in long-term glycemic control among youth with type 1 diabetes, particularly among nonwhite male patients and nonwhite youth diagnosed earlier in life.

Food Acquisition and Shopping Patterns among Residents of Low-Income and Low-Access Communities in South Carolina.

BACKGROUND: Little is known about the food acquisition and shopping habits of residents living in food deserts. OBJECTIVE: To identify distinct food acquisition and shopping patterns among residents, most of whom (81%) live in food desert (low income and low access) census tracts, and characterize these patterns with respect to the residents' socioeconomic status, nutrition knowledge, and perceptions of their food environment. DESIGN: This is a cross-sectional study. PARTICIPANTS/SETTING: Four hundred sixty-six primary food shoppers were included from two counties in South Carolina during 2013-2014. MAIN OUTCOME MEASURES: Participants' self-reported food acquisition and shopping habits, including shopping distance; frequency; store type; transportation mode; use of farmers' markets, food banks/pantries, and church/social service organizations, were used to develop shopping patterns and group residents. Supplemental Nutrition Assistance Program participation, food security, income, and education, nutrition knowledge, and perceptions of the food environment were used to characterize these groups. STATISTICAL ANALYSES PERFORMED: Latent class analysis and multinomial logistic regression were used to identify and characterize patterns, respectively. RESULTS: Three patterns were identified, including those who use community food resources, are infrequent grocery shoppers, and use someone else's car or public transportation when shopping (Class 1) (35%), those who use community food resources and are more frequent and proximal shoppers (Class 2) (41%), and those who do not use community food resources and are distal shoppers (Class 3) (24%). Compared with Class 3, Class 1 had comparatively lower socioeconomic status. Class 2 also had comparatively lower socioeconomic attributes except for income. Class 2 was not significantly different from Class 1 except that a higher proportion in Class 1 saw food access as a problem. No significant differences across classes were found regarding fruit and vegetable recommendation knowledge. CONCLUSIONS: Shopping frequency, use of community food resources, transportation methods, and shopping distance were the key factors that defined distinct patterns among residents living in low-income areas. Future interventions to increase healthy food access in underserved areas should not only consider accessibility but also community food resource use.

What does a person's eating identity add to environmental influences on fruit and vegetable intake?

OBJECTIVE: To evaluate whether knowledge of a person's eating identity (EI) can explain any additional variation in fruit and vegetable intake above and beyond that explained by food environment characteristics, perceptions of the food environment, and shopping behaviors. DESIGN: Cross-sectional study. SETTING: A total of 968 adults were recruited for a telephone survey by the Survey Research Laboratory in an eight-county region in South Carolina. SUBJECTS: The survey queried information on shopping behaviors, perceptions of the food environment, demographic and address information, fruit and vegetable intake, and EI. EI was assessed using the Eating Identity Type Inventory, a 12-item instrument that differentiates four eating identity types: healthy, emotional, meat, and picky. Statistical analyses were restricted to 819 participants with complete data. RESULTS: Healthy EI and picky EI were significantly and directly related to fruit and vegetable intake, with coefficients of 0.31 (p-value<0.001) for healthy EI and -0.16 (p-value<0.001) for picky EI, whereas emotional EI (ß = 0.00, p-value = 0.905) and meat EI (ß = -0.04, p-value = 0.258) showed no association. Shopping frequency also directly and significantly influenced fruit and vegetable intake (ß = 0.13, p-value = 0.033). With the inclusion of EI, 16.3% of the variation in fruit and vegetable intake was explained. CONCLUSIONS: Perceptions and GIS-based measures of environmental factors alone do not explain a substantial amount of variation in fruit and vegetable intake. EI, especially healthy EI and picky EI, is an important, independent predictor of fruit and vegetable intake and contributes significantly to explaining the variation in fruit and vegetable intake.

Stretching Food and Being Creative: Caregiver Responses to Child Food Insecurity.

OBJECTIVE: To examine the strategies and behaviors caregivers use to manage the household food supply when their children experience food insecurity as measured by the US Department of Agriculture's Household Food Security Survey Module. DESIGN: Cross-sectional survey with open-ended questions collected in person. SETTING: Urban and nonurban areas, South Carolina, US. PARTICIPANTS: Caregivers who reported food insecurity among their children (n = 746). PHENOMENON OF INTEREST: Strategies and behaviors used to manage the household food supply. ANALYSIS: Emergent and thematic qualitative coding of open-ended responses. RESULTS: The top 3 strategies and behaviors to change meals were (1) changes in foods purchased or obtained for the household, (2) monetary and shopping strategies, and (3) adaptations in home preparation. The most frequently mentioned foods that were decreased were protein foods (eg, meat, eggs, beans), fruits, and vegetables. The most frequently mentioned foods that were increased were grains and starches (eg, noodles), protein foods (eg, beans, hot dogs), and mixed foods (eg, sandwiches). CONCLUSIONS AND IMPLICATIONS: Caregivers use a wide variety of strategies and behaviors to manage the household food supply when their children are food insecure. Future work should examine how these strategies might affect dietary quality and well-being of food-insecure children.

Do GIS-derived measures of fast food retailers convey perceived fast food opportunities? Implications for food environment assessment.

PURPOSE: Geographic information systems (GISs) have been used to define fast food availability, with higher availability perhaps promoting poorer quality diets. Alternative measures involve perceptions; however, few studies have examined associations between GIS-derived and perceived measures of the food environment. METHODS: Telephone surveys of 705 participants within an eight-county region in South Carolina were analyzed using logistic regression to examine relationships between geographic presence of and distance to various types of food retailers and perceived fast food availability. RESULTS: The mean distance to the nearest fast food restaurant was 6.1 miles, with 16% of participants having a fast food restaurant within 1 mile of home. The geographic presence of and distance to all food retailer types were significantly associated with perceived availability of fast food in unadjusted models. After adjustment, only the presence of a fast food restaurant or pharmacy was significantly associated with greater odds of higher perceived availability of fast food. Greater odds of lower perceived availability of fast food were observed with the presence of a dollar store and increasing distance to the nearest supermarket or pharmacy. CONCLUSIONS: Measures of fast food availability, whether objective or perceived, may not be interchangeable. Researchers should carefully decide on the appropriate measurement tool-GIS-derived or perceived-in food environment studies.

Disparities in Diabetes by Education and Race/Ethnicity in the U.S., 1973-2012.

INTRODUCTION: Diabetes mellitus incidence has more than doubled in the U.S. over the past 2 decades. Not all sectors of the population have experienced the increase proportionally. The goal of this study was to determine if disparities in diabetes by education and race/ethnicity have increased over time, and if there are differences by gender and birth cohort. METHODS: Repeated cross-sectional data were used from the 1973-2012 National Health Interview Survey of adults aged 25-84 years. Logistic regression models were run and predicted probabilities were calculated to determine if disparities in self-reported diabetes by education and race/ethnicity changed over time, by gender and birth cohort (birth before 1946, 1946-1970, 1971 or after). Analyses were conducted in 2014-2015. RESULTS: Relationships between education or race/ethnicity and diabetes were modified by time for people born before 1971, with stronger effect modification for women than men. Inequalities in diabetes prevalence grew over time, although the magnitude of disparities was smaller for the 1946-1970 cohort. For example, in 2005-2012, the gap in diabetes prevalence for women with the highest and lowest levels of education was 12.7% for pre-1946 versus 7.9% for 1946-1970. Similar trends were seen for differences between non-Hispanic whites and non-Hispanic blacks or Hispanics. Results were inconclusive for the youngest cohort. CONCLUSIONS: Diabetes disparities are evident. Smaller differences in later cohorts may indicate that large structural changes in society (e.g., Civil Rights movement, increased educational and economic opportunities) have benefited later generations.

Household food insecurity and medication "scrimping" among US adults with diabetes.

OBJECTIVE: Our research examined the prevalence of food insecurity among adults with self-reported diabetes and whether food insecurity was associated with cutting back ("scrimping") on prescribed medications because of financial constraints. METHODS: We conducted a cross-sectional analysis of data from the 2011 National Health Interview Survey (NHIS). Adults completing this survey were considered to have diabetes if they reported current use of insulin or "diabetic pills" (n=3,242). Food insecurity was determined with a 10-item scale; respondents were categorized as food secure (FS), marginally food secure (MFS) or food insecure (FI). RESULTS: Approximately one in six adults in NHIS with diabetes reported food insecurity (17.0%), and an additional 8.8% were marginally FS. An individual was considered to be scrimping on medications if he/she gave a "yes" response to at least one of four questions pertaining to reduced, delayed or avoided medication use. Overall, 18.9% of respondents with diabetes reported one or more type of medication scrimping: 11.7% of FS individuals, 27.7% of MFS individuals and 45.6% of FI individuals. In adjusted analyses, marginal food security and food insecurity remained strongly associated with scrimping. CONCLUSIONS: One-quarter of adults with diabetes may have difficulty obtaining foods appropriate for a diabetic diet; a substantial number of these individuals also fail to obtain or take medications. Practitioners may miss either problem unless targeted questions are included in clinical encounters. Clinicians should consider referring FI and MFS diabetic patients to community food resources.

Do people really know what food retailers exist in their neighborhood? Examining GIS-based and perceived presence of retail food outlets in an eight-county region of South Carolina.

Measures of neighborhood food environments have been linked to diet and obesity. However, the appropriate measurement methods and how people actually perceive their food environments are still unclear. In a cross-sectional study of 939 adults, the perceived presence of food outlets was compared to the geographic-based presence of outlets within a participant's neighborhood, utilizing percent agreement and Kappa statistics. Perceived presence was based on survey-administered questions, and geographic-based presence was characterized using 1-, 2-, 3- and 5-mile (1-mile=1.6km) Euclidean- and network-based buffers centered on each participant's residence. Analyses were also stratified by urban and non-urban designations. Overall, an individual's perceived neighborhood food environment was moderately correlated with the geographic-based presence of outlets. The performance of an individual's perception was most optimal using a 2- or 3-mile geographic-based neighborhood boundary and/or when the participant lived in a non-urban neighborhood. This study has implications for how researchers measure the food environment.