Faculty Bibliography

BACKGROUND:Low-income Hispanic women are at-risk of poor prenatal diet quality. Correlates associated with prenatal diet quality in this group of women are understudied. OBJECTIVE:The objective of this study was to examine the associations between financial, cultural, psychosocial, and lifestyle correlates and prenatal diet quality in low-income Hispanic women. DESIGN/METHODS:This cross-sectional analysis used data from pregnant women enrolled in the Starting Early Trial, a randomized-controlled trial of a primary-care based child obesity prevention program beginning in pregnancy. The trial enrolled women from clinics affiliated with a large urban medical center in New York City from 2012 to 2014. Financial, cultural, psychosocial, and lifestyle variables were collected using a comprehensive baseline questionnaire. Usual dietary intakes over the past year were assessed using the Block Food Frequency Questionnaire 2005 bilingual version. PARTICIPANTS/METHODS:The study enrolled low-income Hispanic women between 28 and 32 gestational weeks (N=519). MAIN OUTCOME MEASURES/METHODS:Prenatal diet quality was measured by the Healthy Eating Index 2015. STATISTICAL ANALYSES PERFORMED/METHODS:Unadjusted and adjusted multivariable linear regression analyses were performed to determine independent associations between financial, cultural, psychosocial, and lifestyle correlates and Healthy Eating Index 2015 total score. RESULTS:Overall prenatal diet quality was poor (mean Healthy Eating Index 2015 total score=69.0±9.4). Most women did not meet the maximum score for total vegetables (65.3%), whole grains (97.1%), dairy (74.8%), fatty acids (84.4%), refined grains (79.8%), sodium (97.5%), saturated fats (92.9%), and added sugars (66.5%). Women who reported screen time ≤2 hours/day, physical activity before and/or during pregnancy, and being born outside the United States had higher mean Healthy Eating Index 2015 total score than women with screen time >2 hours/day, no physical activity, and those born in the United States. CONCLUSIONS:Prenatal diet quality of low-income pregnant Hispanic women was suboptimal. This cross-sectional study revealed associations between cultural and lifestyle factors and prenatal diet quality in low-income Hispanic women. Longitudinal studies are needed to determine long-term influences and specific behaviors to target for effective intervention studies.

Nutrition is fundamental to maintaining health, managing chronic diseases, and preventing illness, but unlike physical activity there is not yet a way to unobtrusively and automatically measure nutrition. While recent work has shown that body-worn sensors can be used to identify meal times, to have an impact on health and fully replace manual food logs, we need to identify not only when someone is eating, but what they are consuming. However, it is challenging to collect labeled data in daily life, while lab data does not always generalize to reality. To address this, we develop new algorithms for semi-supervised hierarchical classification that enable higher accuracy when training on data with weak labels. Using this approach, we present the first results on automated classification of foods consumed in data collected from body-worn audio and motion sensors in free-living environments. We show that by exploiting a mix of lab and free-living data, we can achieve a classification accuracy of 88% on unrestricted meals (e.g. stir fry, pizza, salad) in unrestricted environments such as home and restaurants. Ultimately, this lays the foundation for body-worn devices that can calculate calories and macronutrients by identifying food type and quantity.

OBJECTIVE:Prepregnancy weight may not always be known to women. A model was developed to estimate prepregnancy weight from measured pregnancy weight. METHODS:The model was developed and validated using participants from two studies (Project Viva, n = 301, model development; and Fit for Delivery [FFD], n = 401, model validation). Data from the third study (Programming Research in Obesity, Growth, Environment and Social Stressors [PROGRESS]), which included women from Mexico City, were used to demonstrate the utility of the newly developed model to objectively quantify prepregnancy weight. RESULTS: = 0.81; y = 0.89x + 9.61; bias = 2.83 kg; 95% CI: -7.70 to 12.31; error range = -39.17 kg to 25.73 kg). The model was programmed into software (https://www.pbrc.edu/research-and-faculty/calculators/prepregnancy/). CONCLUSIONS:The developed model provides an alternative to determine prepregnancy weight in populations receiving routine health care that may not have accurate knowledge of prepregnancy weight. The software can identify misreporting and classification into incorrect gestational weight gain categories.

OBJECTIVE:The majority of groceries purchased by US households are industrially processed, yet it is unclear how processing level influences diet quality. We sought to determine if processing level is associated with diet quality of grocery purchases. DESIGN/METHODS:We analysed grocery purchasing data from the National Household Food Acquisition and Purchase Survey 2012-2013. Household grocery purchases were categorized by the NOVA framework as minimally processed, processed culinary ingredients, processed foods or ultra-processed foods. The energy share of each processing level (percentage of energy; %E) and Healthy Eating Index-2015 (HEI-2015) component and total scores were calculated for each household's purchases. The association between %E from processed foods and ultra-processed foods, respectively, and HEI-2015 total score was determined by multivariable linear regression. Foods purchased by households with the highest v. lowest ultra-processed food purchases and HEI-2015 total score <40 v. ≥60 were compared using linear regression. SETTING/METHODS:USA. PARTICIPANTS/METHODS:Nationally representative sample of 3961 households. RESULTS:Processed foods and ultra-processed foods provided 9·2 (se 0·3) % and 55·8 (se 0·6) % of purchased energy, respectively. Mean HEI-2015 score was 54·7 (se 0·4). Substituting 10 %E from minimally processed foods and processed culinary ingredients for ultra-processed foods decreased total HEI-2015 score by 1·8 points (β = -1·8; 95 % CI -2·0, -1·5). Processed food purchases were not associated with diet quality. Among households with high ultra-processed food purchases, those with HEI-2015 score <40 purchased less minimally processed plant-foods than households with HEI-2015 score ≥60. CONCLUSIONS:Increasing purchases of minimally processed foods, decreasing purchases of ultra-processed foods and selecting healthier foods at each processing level may improve diet quality.

BACKGROUND:This pilot study collected preliminary data for the modification of the VioScreen Food Frequency Questionnaire (FFQ), an adult-validated, self-administered, web-based dietary assessment tool for use in older children. METHODS:A convenience sample of 55 children, aged 6-14 years, completed the VioScreen FFQ and 3-day diet record (reference standard). Caregivers completed a short sociodemographic questionnaire. Reported dietary intakes from the VioScreen FFQ and 3-day diet record were calculated using standard nutrient databases, and descriptive statistics were used to examine differences in food/beverage items and portion sizes between the two methods. Informal focus groups obtained user feedback and identified components of the VioScreen FFQ that required modifications. RESULTS:The highest de-attenuated Pearson correlation coefficients between the VioScreen FFQ and 3-day diet record were observed for iron (r = 0.69), saturated fat (r = 0.59), and vegetables (r = 0.56), and the lowest were for whole grains (r = 0.11) and vitamin C (r = 0.16). Qualitative feedback was overall positive, and six technological modifications were identified. CONCLUSION/CONCLUSIONS:Findings from this pilot study provided valuable information on the process of evaluating the use of the VioScreen FFQ among older children, and will inform the future development of a modified version for this population.

BACKGROUND:To examine associations of adolescents' weight status perception and weight control intentions with dietary intakes. METHODS:Cross-sectional data from adolescents aged 10⁻15 in the National Health and Nutrition Examination Surveys, 2005⁻2014 (n = 4940). Adolescents responded to questions regarding weight perception and if they were trying to change their weight. Intakes of calories, protein, carbohydrate, fat, saturated fat, sugar, and fiber were assessed using 24-h dietary recalls. Multivariable linear regression estimated associations of intakes with weight perception and weight control intentions. RESULTS:The majority of adolescents perceived their weight as "about right"; however, 45% and 46% of boys and girls, respectively, reported trying to change their weight. Weight perception was not associated with intakes, with the exception of lower sugar (-13.65 g, 95% CI: -23.06, -4.23) and higher percent calories from protein (1.01%, 95% CI: 0.16, 1.87) in boys with overweight/obesity who perceived themselves as overweight, as well as lower percent calories from saturated fat (-1.04%, 95% CI: -2.24, -0.17) among girls with normal weight who perceived themselves as overweight. Weight control intentions were associated with intakes in boys only. Compared to boys who never tried to lose weight, boys who tried to lose weight consumed fewer calories (-188.34 kcal, 95% CI: -357.67, -19.01), a lower percent of calories from fat (-1.41%, 95% CI: -2.80, -0.02), and a greater percent of calories from protein (1.48%, 95% CI: 0.41, 2.55). CONCLUSIONS:Despite perceiving weight as "about right", many adolescents reported trying to change their weight, which was associated with some dietary intakes. Efforts may be necessary to educate adolescents on healthy nutrition and weight management behaviors.

INTRODUCTION/BACKGROUND:Cross-sectional studies suggest that postnatal blood lead (PbB) concentrations are negatively associated with child growth. Few studies prospectively examined this association in populations with lower PbB concentrations. We investigated longitudinal associations of childhood PbB concentrations and subsequent anthropometric measurements in a multi-ethnic cohort of girls. METHODS:Data were from The Breast Cancer and the Environment Research Program at three sites in the United States (U.S.): New York City, Cincinnati, and San Francisco Bay Area. Girls were enrolled at ages 6-8 years in 2004-2007. Girls with PbB concentrations collected at ≤10 years old (mean 7.8 years, standard deviation (SD) 0.82) and anthropometry collected at ≥3 follow-up visits were included (n = 683). The median PbB concentration was 0.99 μg/d (10th percentile = 0.59 μg/dL and 90th percentile = 2.00 μg/dL) and the geometric mean was 1.03 μg/dL (95% Confidence Interval (CI): 0.99, 1.06). For analyses, PbB concentrations were dichotomized as <1 μg/dL (n = 342) and ≥1 μg/dL (n = 341). Anthropometric measurements of height, body mass index (BMI), waist circumference (WC), and percent body fat (%BF) were collected at enrollment and follow-up visits through 2015. Linear mixed effects regression estimated how PbB concentrations related to changes in girls' measurements from ages 7-14 years. RESULTS:(95% CI: -1.5, -0.02), -2.9 cm (95% CI: -4.8, -0.9), and -1.7% (95% CI: -3.1, -0.4) for BMI, WC, and BF%, respectively. CONCLUSIONS:These findings suggest that higher concentrations of PbB during childhood, even though relatively low by screening standards, may be inversely associated with anthropometric measurements in girls.