Obesity最新文献

Objective

The objective of this study is to use a machine learning approach to identify predictors of BMI percentile among Hispanic/Latino youth in the United States.

Methods

Participants were Hispanic/Latino 8– to 16-year-olds from the cross-sectional Study of Latino Youth (SOL Youth; n = 1466). A supervised machine learning approach, LASSO regression, was used with BMI percentile as the outcome. A total of 102 predictor variables were examined spanning parent and child demographics; health behaviors; and psychological, sociocultural, and environmental measures.

Results

Mean age of participants was 12 years, 50% were female, and 44.2% were of Mexican heritage. A 36-variable LASSO model yielded the optimum mean squared error (R ² = 0.42), but a 10-variable solution was selected for parsimony. Six associations were significant. Dieting 1–4 or ≥ 5 times/year (β = 8.69 [95% CI: 10.25 to 14.52] or 10.86 [95% CI: 13.14 to 18.33], respectively) and having a parent of Dominican heritage (β = 3.48 [95% CI: 4.05 to 9.90]) or with obesity (β = 2.96 [95% CI: 2.99 to 6.85]) were associated with a higher BMI percentile. Perception of being smaller than the “ideal” body size (β = −1.65 [95% CI: −6.84 to −1.35]) and use of the food/activity parenting practice Control (β = −1.17 [95% CI: −3.63 to −1.69]) were associated with a lower BMI percentile.

Conclusions

Family-based approaches and focusing on dieting and body image satisfaction may be important for weight management in Hispanic/Latino youth.

Objective

This study aimed to quantify associations between newborn social risk factors and high infant weight-for-length (WFL) at 6 months.

Methods

We conducted a longitudinal, observational study using electronic health record data among infants in New York City. We included newborns with a primary care screening questionnaire for social risk factors (food insecurity, housing instability, transportation problems, and utility hardship) measured using the Accountable Health Communities Screening Tool. We conducted regression analyses to assess associations between social risk factors and high WFL, or the 97.7th percentile at 6 months. Secondary analyses included additional single-time-point and longitudinal weight outcomes (continuous and dichotomous).

Results

Among 1876 newborns, 77.3% identified as Hispanic/Latino, almost all had Medicaid insurance (96.6%), 355 (23.3%) had food insecurity risk, 149 (7.9%) had housing instability, 132 (7.0%) had transportation problems, and 110 (5.9%) had utility hardship. Newborns with utility hardship had higher odds of high WFL in unadjusted (OR 3.0, 95% CI: 1.8–5.2) and adjusted models (aOR 3.1, 95% CI: 1.7–5.6) accounting for infant, parent, and social risk factors.

Conclusions

Newborn utility hardship was associated with obesity risk at age 6 months. Interventions to address newborn social risk factors should examine the effectiveness of utility shutoff protection to reduce excess infant weight gain.

Objective

We evaluated whether sleep disturbance moderates weight loss in breast cancer survivors. We hypothesized that poor sleep prior to behavioral weight loss (BWL) would be associated with less weight reduction than better sleep.

Methods

Women with prior stage 0-III breast cancer with BMI ≥ 25 kg/m² were randomized to BWL (n = 47) or self-directed approach (n = 46). Weight and self-reported sleep (NIH PROMIS Adult Sleep Disturbance Short Form) were collected at baseline and at 6 and 12 months. In the full sample and cohorts stratified by baseline sleep, multiple regression analyses evaluated associations of study arm, age, baseline sleep, and BMI with weight loss.

Results

There was significant interaction between baseline sleep and treatment (BWL vs. self-directed) for weight loss at 6 (p = 0.024) and 12 months (p = 0.019). Weight loss among better sleepers was −6.16% (SE 1.42%) in BWL versus self-directed arms and −7.53% (SE 2.02%) at 6 (p < 0.001) and 12 months (p = 0.001), respectively. Among poor sleepers, weight loss was −3.15% (SE: 1.58%) and −2.44% (SE: 2.40%) at 6 (p = 0.056) and 12 months (p = 0.321), respectively. BWL had a greater effect among better sleepers but minimal effect among poor sleepers.

Conclusions

BWL has greater effects in breast cancer survivors with better versus worse sleep. Studies should evaluate whether sleep disturbance treatment augments weight loss.

Trial Registration: ClinicalTrials.gov identifier NCT01871116