Neighborhood level risk factors for type 1 diabetes in youth: the SEARCH case-control study.

BACKGROUND: European ecologic studies suggest higher socioeconomic status is associated with higher incidence of type 1 diabetes. Using data from a case-control study of diabetes among racially/ethnically diverse youth in the United States (U.S.), we aimed to evaluate the independent impact of neighborhood characteristics on type 1 diabetes risk. Data were available for 507 youth with type 1 diabetes and 208 healthy controls aged 10-22 years recruited in South Carolina and Colorado in 2003-2006. Home addresses were used to identify Census tracts of residence. Neighborhood-level variables were obtained from 2000 U.S. Census. Multivariate generalized linear mixed models were applied. RESULTS: Controlling for individual risk factors (age, gender, race/ethnicity, infant feeding, birth weight, maternal age, number of household residents, parental education, income, state), higher neighborhood household income (p = 0.005), proportion of population in managerial jobs (p = 0.02), with at least high school education (p = 0.005), working outside the county (p = 0.04) and vehicle ownership (p = 0.03) were each independently associated with increased odds of type 1 diabetes. Conversely, higher percent minority population (p = 0.0003), income from social security (p = 0.002), proportion of crowded households (0.0497) and poverty (p = 0.008) were associated with a decreased odds. CONCLUSIONS: Our study suggests that neighborhood characteristics related to greater affluence, occupation, and education are associated with higher type 1 diabetes risk. Further research is needed to understand mechanisms underlying the influence of neighborhood context.

Validation of 3 food outlet databases: completeness and geospatial accuracy in rural and urban food environments.

Despite interest in the built food environment, little is known about the validity of commonly used secondary data. The authors conducted a comprehensive field census identifying the locations of all food outlets using a handheld global positioning system in 8 counties in South Carolina (2008-2009). Secondary data were obtained from 2 commercial companies, Dun & Bradstreet, Inc. (D&B) (Short Hills, New Jersey) and InfoUSA, Inc. (Omaha, Nebraska), and the South Carolina Department of Health and Environmental Control (DHEC). Sensitivity, positive predictive value, and geospatial accuracy were compared. The field census identified 2,208 food outlets, significantly more than the DHEC (n = 1,694), InfoUSA (n = 1,657), or D&B (n = 1,573). Sensitivities were moderate for DHEC (68%) and InfoUSA (65%) and fair for D&B (55%). Combining InfoUSA and D&B data would have increased sensitivity to 78%. Positive predictive values were very good for DHEC (89%) and InfoUSA (86%) and good for D&B (78%). Geospatial accuracy varied, depending on the scale: More than 80% of outlets were geocoded to the correct US Census tract, but only 29%-39% were correctly allocated within 100 m. This study suggests that the validity of common data sources used to characterize the food environment is limited. The marked undercount of food outlets and the geospatial inaccuracies observed have the potential to introduce bias into studies evaluating the impact of the built food environment.

Conventional analyses of data from dietary validation studies may misestimate reporting accuracy: illustration from a study of the effect of interview modality on children's reporting accuracy.

OBJECTIVE: To compare two approaches to analysing energy- and nutrient-converted data from dietary validation (and relative validation) studies - conventional analyses, in which the accuracy of reported items is not ascertained, and reporting-error-sensitive analyses, in which reported items are classified as matches (items actually eaten) or intrusions (items not actually eaten), and reported amounts are classified as corresponding or overreported. DESIGN: Subjects were observed eating school breakfast and lunch, and interviewed that evening about that day's intake. For conventional analyses, reference and reported information were converted to energy and macronutrients; then t-tests, correlation coefficients and report rates (reported/reference) were calculated. For reporting error-sensitive analyses, reported items were classified as matches or intrusions, reported amounts were classified as corresponding or overreported, and correspondence rates (corresponding amount/reference amount) and inflation ratios (overreported amount/reference amount) were calculated. SUBJECTS: Sixty-nine fourth-grade children (35 girls) from 10 elementary schools in Georgia (USA). RESULTS: For energy and each macronutrient, conventional analyses found that reported amounts were significantly less than reference amounts (every P < 0.021; paired t-tests); correlations between reported and reference amounts exceeded 0.52 (every P < 0.001); and median report rates ranged from 76% to 95%. Analyses sensitive to reporting errors found median correspondence rates between 67% and 79%, and that median inflation ratios, which ranged from 7% to 17%, differed significantly from 0 (every P < 0.0001; sign tests). CONCLUSIONS: Conventional analyses of energy and nutrient data from dietary reporting validation (and relative validation) studies may overestimate accuracy and mask the complexity of dietary reporting error.

Conclusions about children's reporting accuracy for energy and macronutrients over multiple interviews depend on the analytic approach for comparing reported information to reference information.

OBJECTIVE: Validation study data are used to illustrate that conclusions about children's reporting accuracy for energy and macronutrients over multiple interviews (ie, time) depend on the analytic approach for comparing reported and reference information-conventional, which disregards accuracy of reported items and amounts, or reporting-error-sensitive, which classifies reported items as matches (eaten) or intrusions (not eaten), and amounts as corresponding or overreported. SUBJECTS AND DESIGN: Children were observed eating school meals on 1 day (n=12), or 2 (n=13) or 3 (n=79) nonconsecutive days separated by >or=25 days, and interviewed in the morning after each observation day about intake the previous day. Reference (observed) and reported information were transformed to energy and macronutrients (ie, protein, carbohydrate, and fat), and compared. MAIN OUTCOME MEASURES: For energy and each macronutrient: report rates (reported/reference), correspondence rates (genuine accuracy measures), and inflation ratios (error measures). STATISTICAL ANALYSES: Mixed-model analyses. RESULTS: Using the conventional approach for analyzing energy and macronutrients, report rates did not vary systematically over interviews (all four P values >0.61). Using the reporting-error-sensitive approach for analyzing energy and macronutrients, correspondence rates increased over interviews (all four P values <0.04), indicating that reporting accuracy improved over time; inflation ratios decreased, although not significantly, over interviews, also suggesting that reporting accuracy improved over time. Correspondence rates were lower than report rates, indicating that reporting accuracy was worse than implied by conventional measures. CONCLUSIONS: When analyzed using the reporting-error-sensitive approach, children's dietary reporting accuracy for energy and macronutrients improved over time, but the conventional approach masked improvements and overestimated accuracy. The reporting-error-sensitive approach is recommended when analyzing data from validation studies of dietary reporting accuracy for energy and macronutrients.

Conventional energy and macronutrient variables distort the accuracy of children's dietary reports: illustrative data from a validation study of effect of order prompts.

OBJECTIVE: Validation-study data are used to illustrate that conventional energy and macronutrient (protein, carbohydrate, fat) variables, which disregard accuracy of reported items and amounts, misrepresent reporting accuracy. Reporting-error-sensitive variables are proposed which classify reported items as matches or intrusions, and reported amounts as corresponding or overreported. METHODS: 58 girls and 63 boys were each observed eating school meals on 2 days separated by > or =4 weeks, and interviewed the morning after each observation day. One interview per child had forward-order (morning-to-evening) prompts; one had reverse-order prompts. Original food-item-level analyses found a sex-x-order prompt interaction for omission rates. Current analyses compared reference (observed) and reported information transformed to energy and macronutrients. RESULTS: Using conventional variables, reported amounts were less than reference amounts (ps<0.001; paired t-tests); report rates were higher for the first than second interview for energy, protein, and carbohydrate (ps< or =0.049; mixed models). Using reporting-error-sensitive variables, correspondence rates were higher for girls with forward- but boys with reverse-order prompts (ps< or =0.041; mixed models); inflation ratios were lower with reverse- than forward-order prompts for energy, carbohydrate, and fat (ps< or =0.045; mixed models). CONCLUSIONS: Conventional variables overestimated reporting accuracy and masked order prompt and sex effects. Reporting-error-sensitive variables are recommended when assessing accuracy for energy and macronutrients in validation studies.

Body mass index, sex, interview protocol, and children's accuracy for reporting kilocalories observed eaten at school meals.

This pilot study investigated body mass index (BMI; calculated as kg/m(2)), sex, interview protocol, and children's accuracy for reporting kilocalories. Forty 4th-grade children (20 low-BMI: >or=5th and <50th percentiles, 10 boys, 15 African American; 20 high-BMI: >or=85th percentile, 10 boys, 15 African American) were observed eating school meals (breakfast, lunch) and interviewed either that evening about the prior 24 hours or the next morning about the previous day, with 10 low-BMI (5 boys) and 10 high-BMI (5 boys) children per interview protocol. Five kilocalorie variables were analyzed using separate four-factor (BMI group, sex, race, interview protocol) analyses of variance. No effects were found for reported or matched kilocalories. More kilocalories were observed (P<0.02) and omitted (P<0.05) by high-BMI than low-BMI children. For intruded kilocalories, means were smaller (better) for high-BMI girls than high-BMI boys, but larger for low-BMI girls than low-BMI boys (interaction P<0.04); low-BMI girls intruded the most while high-BMI girls intruded the least. For interview protocol, omitted and intruded kilocalories were higher (worse), although not significantly so (P values <0.11), for interviews about the previous day than the prior 24 hours. These results illuminate relations of BMI, sex, interview protocol, and children's reporting accuracy, and are consistent with results concerning BMI and sex from studies with adults.

Children's dietary reporting accuracy over multiple 24-hour recalls varies by body mass index category.

This secondary analysis investigated the influence of body mass index (BMI) category and sex on reporting accuracy during multiple 24-hour dietary recalls. On three occasions, each of 79 children (40 girls) was observed eating school meals and interviewed the next morning about the previous day's intake, with ≥ 25 days between any two consecutive occasions for a child. Using age/sex BMI percentiles, we categorized 48 children as healthy weight (≥ 5(th) percentile <85(th)), 14 as at risk of overweight (≥ 85(th) percentile <95(th)), and 17 as overweight (≥95(th) percentile). A repeated-measures analysis was conducted for each of five outcomes (number of items observed eaten, number of items reported eaten, omission rate, intrusion rate, total inaccuracy). For items observed, BMI category x trial was marginally significant (P=0.079); over trials, this outcome was stable for healthy-weight children, decreased and stabilized for at-risk-of-overweight children, and was stable and decreased for overweight children. This outcome was greatest for overweight children and least for healthy-weight children (P=0.015). For items reported, no significant effects were found. For omission rate (P=0.028) and intrusion rate (P=0.083), BMI category x trial was significant and marginally significant; over trials, both decreased for healthy-weight children, decreased and stabilized for at-risk-of-overweight children, and increased and stabilized for overweight children. Total inaccuracy decreased slightly over trials (P=0.076); this outcome was greater for boys than for girls (P=0.049). Results suggest that children's dietary reporting accuracy over multiple recalls varies by BMI category. Validation studies with adequate samples for each BMI category, sex, and race are needed.