Person:

Gillman, Matthew

Background: Parents are integral to the implementation of obesity prevention and management recommendations for children. Exploration of barriers to and facilitators of parental decisions to adopt obesity prevention recommendations will inform future efforts to reduce childhood obesity.Methods We conducted 4 focus groups (2 English, 2 Spanish) among a total of 19 parents of overweight (BMI ≥ 85th percentile) children aged 5-17 years. The main discussion focused on 7 common obesity prevention recommendations: reducing television (TV) watching, removing TV from child's bedroom, increasing physically active games, participating in community or school-based athletics, walking to school, walking more in general, and eating less fast food. Parents were asked to discuss what factors would make each recommendation more difficult (barriers) or easier (facilitators) to follow. Participants were also asked about the relative importance of economic (time and dollar costs/savings) barriers and facilitators if these were not brought into the discussion unprompted. Results: Parents identified many barriers but few facilitators to adopting obesity prevention recommendations for their children. Members of all groups identified economic barriers (time and dollar costs) among a variety of pertinent barriers, although the discussion of dollar costs often required prompting. Parents cited other barriers including child preference, difficulty with changing habits, lack of information, lack of transportation, difficulty with monitoring child behavior, need for assistance from family members, parity with other family members, and neighborhood walking safety. Facilitators identified included access to physical activity programs, availability of alternatives to fast food and TV which are acceptable to the child, enlisting outside support, dietary information, involving the child, setting limits, making behavior changes gradually, and parental change in shopping behaviors and own eating behaviors. Conclusions: Parents identify numerous barriers to adopting obesity prevention recommendations, most notably child and family preferences and resistance to change, but also economic barriers. Intervention programs should consider the context of family priorities and how to overcome barriers and make use of relevant facilitators during program development.

Background: Modeling childhood body mass index (BMI) trajectories, versus estimating change in BMI between specific ages, may improve prediction of later body-size-related outcomes. Prior studies of BMI trajectories are limited by restricted age periods and insufficient use of trajectory information. Methods: Among 3,289 children seen at 81,550 pediatric well-child visits from infancy to 18 years between 1980 and 2008, we fit individual BMI trajectories using mixed effect models with fractional polynomial functions. From each child's fitted trajectory, we estimated age and BMI at infancy peak and adiposity rebound, and velocity and area under curve between 1 week, infancy peak, adiposity rebound, and 18 years. Results: Among boys, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.2 (0.9) and 49.2 (11.9) months, respectively. Among girls, mean (SD) ages at infancy BMI peak and adiposity rebound were 7.4 (1.1) and 46.8 (11.0) months, respectively. Ages at infancy peak and adiposity rebound were weakly inversely correlated (r = -0.09). BMI at infancy peak and adiposity rebound were positively correlated (r = 0.76). Blacks had earlier adiposity rebound and greater velocity from adiposity rebound to 18 years of age than whites. Higher birth weight z-score predicted earlier adiposity rebound and higher BMI at infancy peak and adiposity rebound. BMI trajectories did not differ by birth year or type of health insurance, after adjusting for other socio-demographics and birth weight z-score. Conclusions: Childhood BMI trajectory characteristics are informative in describing childhood body mass changes and can be estimated conveniently. Future research should evaluate associations of these novel BMI trajectory characteristics with adult outcomes.

Background: The role of fathers in the development of obesity in their offspring remains poorly understood. We evaluated associations of missing paternal demographic information on birth certificates with perinatal risk factors for childhood obesity. Methods: Data were from the Linked CENTURY Study, a database linking birth certificate and well-child visit data for 200,258 Massachusetts children from 1980–2008. We categorized participants based on the availability of paternal age, education, or race/ethnicity and maternal marital status on the birth certificate: (1) pregnancies missing paternal data; (2) pregnancies involving unmarried women with paternal data; and (3) pregnancies involving married women with paternal data. Using linear and logistic regression, we compared differences in smoking during pregnancy, gestational diabetes, birthweight, breastfeeding initiation, and ever recording a weight for length (WFL) ≥ the 95th percentile or crossing upwards ≥2 WFL percentiles between 0–24 months among the study groups. Results: 11,989 (6.0 %) birth certificates were missing paternal data; 31,323 (15.6 %) mothers were unmarried. In adjusted analyses, missing paternal data was associated with lower birthweight (β -0.07 kg; 95 % CI: −0.08, −0.05), smoking during pregnancy (AOR 4.40; 95 % CI: 3.97, 4.87), non-initiation of breastfeeding (AOR 0.39; 95 % CI: 0.36, 0.42), and with ever having a WFL ≥ 95th percentile (AOR 1.10; 95 % CI: 1.01, 1.20). Similar associations were noted for pregnancies involving unmarried women with paternal data, but differences were less pronounced. Conclusions: Missing paternal data on the birth certificate is associated with perinatal risk factors for childhood obesity. Efforts to understand and reduce obesity risk factors in early life may need to consider paternal factors.

Background: United States pediatric guidelines recommend that childhood obesity counseling be conducted in the primary care setting. Primary care-based interventions can be effective in improving health behaviors, but also costly. The purpose of this study was to evaluate the cost of a primary care-based obesity prevention intervention targeting children between the ages of two and six years who are at elevated risk for obesity, measured against usual care. Methods: High Five for Kids was a cluster-randomized controlled clinical trial that aimed to modify children’s nutrition and TV viewing habits through a motivational interviewing intervention. We assessed visit-related costs from a societal perspective, including provider-incurred direct medical costs, provider-incurred equipment costs, parent time costs and parent out-of-pocket costs, in 2011 dollars for the intervention (n = 253) and usual care (n = 192) groups. We conducted a net cost analysis using both societal and health plan costing perspectives and conducted one-way sensitivity and uncertainty analyses on results. Results: The total costs for the intervention group and usual care groups in the first year of the intervention were $65,643 (95% CI [$64,522, $66,842]) and $12,192 (95% CI [$11,393, $13,174]). The mean costs for the intervention and usual care groups were $259 (95% CI [$255, $264]) and $63 (95% CI [$59, $69]) per child, respectively, for a incremental difference of $196 (95% CI [$191, $202]) per child. Children in the intervention group attended a mean of 2.4 of a possible 4 in-person visits and received 0.45 of a possible 2 counseling phone calls. Provider-incurred costs were the primary driver of cost estimates in sensitivity analyses. Conclusions: High Five for Kids was a resource-intensive intervention. Further studies are needed to assess the cost-effectiveness of the intervention relative to other pediatric obesity interventions. Trial registration ClinicalTrials.gov Identifier: NCT00377767.

Background: Given that it is not feasible to use dual x-ray absorptiometry (DXA) or other reference methods to measure adiposity in all pediatric clinical and research settings, it is important to identify reasonable alternatives. Therefore, we sought to determine the extent to which other adiposity measures were correlated with DXA fat mass in school-aged children. Methods: In 1110 children aged 6.5-10.9 years in the pre-birth cohort Project Viva, we calculated Spearman correlation coefficients between DXA (n=875) and other adiposity measures including body mass index (BMI), skinfold thickness, circumferences, and bioimpedance. We also computed correlations between lean body mass measures. Results: 50.0% of the children were female and 36.5% were non-white. Mean (SD) BMI was 17.2 (3.1) and total fat mass by DXA was 7.5 (3.9) kg. DXA total fat mass was highly correlated with BMI (rs=0.83), bioimpedance total fat (rs=0.87), and sum of skinfolds (rs=0.90), and DXA trunk fat was highly correlated with waist circumference (rs=0.79). Correlations of BMI with other adiposity indices were high, e.g., with waist circumference (rs=0.86) and sum of subscapular plus triceps skinfolds (rs=0.79). DXA fat-free mass and bioimpedance fat-free mass were highly correlated (rs=0.94). Conclusions: In school-aged children, BMI, sum of skinfolds, and other adiposity measures were strongly correlated with DXA fat mass. Although these measurement methods have limitations, BMI and skinfolds are adequate surrogate measures of relative adiposity in children when DXA is not practical.

Background: Mexico has the highest adult overweight and obesity prevalence in the Americas; 23.8% of children <5 years old are at risk for overweight and 9.7% are already overweight or obese. Creciendo Sanos was a pilot intervention to prevent obesity among preschoolers in Instituto Mexicano del Seguro Social (IMSS) clinics. Methods: We randomized 4 IMSS primary care clinics to either 6 weekly educational sessions promoting healthful nutrition and physical activity or usual care. We recruited 306 parent-child pairs: 168 intervention, 138 usual care. Children were 2-5 years old with WHO body mass index (BMI) z-score 0-3. We measured children’s height and weight and parents reported children’s diet and physical activity at baseline and 3 and 6-month follow-up. We analyzed behavioral and BMI outcomes with generalized mixed models incorporating multiple imputation for missing values. Results: 93 (55%) intervention and 96 (70%) usual care families completed 3 and 6-month follow-up. At 3 months, intervention v. usual care children increased vegetables by 6.3 servings/week (95% CI, 1.8, 10.8). In stratified analyses, intervention participants with high program adherence (5-6 sessions) decreased snacks and screen time and increased vegetables v. usual care. No further effects on behavioral outcomes or BMI were observed. Transportation time and expenses were barriers to adherence. 90% of parents who completed the post-intervention survey were satisfied with the program. Conclusions: Although satisfaction was high among participants, barriers to participation and retention included transportation cost and time. In intention to treat analyses, we found intervention effects on vegetable intake, but not other behaviors or BMI. Trial registration ClinicalTrials.gov NCT01539070. Comisión Nacional de Investigación Científica del IMSS: 2009-785-120.

Background: Despite the need to identify the causes of disparities in childhood obesity, the existing epidemiologic studies of early life risk factors have several limitations. We report on the construction of the Linked CENTURY database, incorporating CENTURY (Collecting Electronic Nutrition Trajectory Data Using Records of Youth) Study data with birth certificates; and discuss the potential implications of combining clinical and public health data sources in examining the etiology of disparities in childhood obesity. Methods: We linked the existing CENTURY Study, a database of 269,959 singleton children from birth to age 18 years with measured heights and weights, with each child’s Massachusetts birth certificate, which captures information on their mothers’ pregnancy history and detailed socio-demographic information of both mothers and fathers. Results: Overall, 74.2 % were matched, resulting in 200,343 children in the Linked CENTURY Study with 1,580,597 well child visits. Among this cohort, 94.0 % (188,334) of children have some father information available on the birth certificate and 60.9 % (121,917) of children have at least one other sibling in the dataset. Using maternal race/ethnicity from the birth certificate as an indicator of children’s race/ethnicity, 75.7 % of children were white, 11.6 % black, 4.6 % Hispanic, and 5.7 % Asian. Based on socio-demographic information from the birth certificate, 20.0 % of mothers were non-US born, 5.9 % smoked during pregnancy, 76.3 % initiated breastfeeding, and 11.0 % of mothers had their delivery paid for by public health insurance. Using clinical data from the CENTURY Study, 22.7 % of children had a weight-for-length ≥ 95th percentile between 1 and 24 months and 12.0 % of children had a body mass index ≥ 95th percentile at ages 5 and 17 years. Conclusions: By linking routinely-collected data sources, it is possible to address research questions that could not be answered with either source alone. Linkage between a clinical database and each child’s birth certificate has created a unique dataset with nearly complete racial/ethnic and socio-demographic information from both parents, which has the potential to examine the etiology of racial/ethnic and socioeconomic disparities in childhood obesity.

Among US racial/ethnic minority women, we examined associations between maternal experiences of racial discrimination and child growth in the first 3 years of life. We analyzed data from Project Viva, a pre-birth cohort study. We restricted analyses to 539 mother–infant pairs; 294 were Black, 127 Hispanic, 110 Asian and 8 from additional racial/ethnic groups. During pregnancy, mothers completed the Experiences of Discrimination survey that measured lifetime experiences of racial discrimination in diverse domains. We categorized responses as 0, 1–2 or >3 domains. Main outcomes were birth weight for gestational age z-score; weight for age (WFA) z-score at 6 months of age; and at 3 years of age, body mass index (BMI) z-score. In multivariable analyses, we adjusted for maternal race/ethnicity, nativity, education, age, pre-pregnancy BMI, household income and child sex and age. Among this cohort of mostly (58.2%) US born and economically non-impoverished mothers, 33% reported 0 domains of discrimination, 33% reported discrimination in 1–2 domains and 35% reported discrimination in >3 domains. Compared with children whose mothers reported no discrimination, those whose mother reported >3 domains had lower birth weight for gestational age z-score (b 20.25; 95% CI: 20.45, 20.04), lower 6 month WFA z-score (b 20.34; 95% CI: 20.65, 20.03) and lower 3-year BMI z-score (b 20.33; 95% CI: 20.66, 0.00). In conclusion, we found that among this cohort of US racial/ethnic minority women, mothers’ report of experiencing lifetime discrimination in > 3 domains was associated with lower fetal growth, weight at 6 months and 3-year BMI among their offspring.

Objective: To examine associations of chronic insufficient sleep with diet, and whether diet explains the sleep-adiposity relationship. Methods: In Project Viva, 1,046 parents reported children’s sleep duration at 6m and annually until mid-childhood (7y). The main exposure was a sleep curtailment score (6m–7y) ranging from 0 (maximal curtailment) to 13 (adequate sleep). In mid-childhood, parents reported children’s diet; researchers measured height/weight. Multivariable linear regression assessed associations of sleep with diet (Youth Healthy Eating Index [YHEI]); sleep with BMI z-score adjusting for YHEI; and, secondarily, joint associations of sleep and YHEI with BMI. Results: Mean (SD) sleep and YHEI scores were 10.21 (2.71) and 58.76 (10.37). Longer sleep duration was associated with higher YHEI in mid-childhood (0.59 points/unit sleep score; 95%CI: 0.32, 0.86). Though higher YHEI was associated with lower BMI z-score (−0.07 units/10-point increase; 95%CI: −0.13, −0.01), adjustment for YHEI did not attenuate sleep-BMI associations. Children with sleep and YHEI scores below the median (<11 and <60) had BMI z-scores 0.34 units higher (95%CI: 0.16, 0.51) than children with sleep and YHEI scores above the median. Conclusions: While parent-reported diet did not explain inverse associations of sleep with adiposity, both sufficient sleep and high-quality diets are important to obesity prevention.