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1.
Child Obes ; 16(1): 44-52, 2020 01.
Article in English | MEDLINE | ID: mdl-31556701

ABSTRACT

Background: Failure to recognize children's overweight status by parents may contribute to children's risk for obesity. We examined two methods of measuring mothers' perceptions of children's weight and factors associated with weight perception inaccuracy. Methods: Cross-sectional analyses of clinical and self-report data from 287 Mexican-heritage mother-child dyads. Mothers identified their child's weight category using a scale (e.g., "normal/overweight/obese") and a visual silhouette scale (11 child gender-specific weight-varying images). Children's height and weight were measured to calculate body mass index (BMI). Chi-square tests examined associations between categorical, silhouette, and BMI percentile categories of children's weight. Bivariate logistic regression analyses examined factors associated with mothers' inaccuracy of their children's weight. Results: Only 13% of mothers accurately classified their child as obese using the categorical scale, while 78% accurately classified their child as obese using the silhouette scale. Mothers were more likely to underestimate their child's weight using BMI categories (62%) compared to using the silhouette scale (23%). Predictors of mothers' underestimation using the categorical method were child sex [female] (adjusted odds ratio [AOR] = 1.99; 95% CI: 1.02-3.86), child age [younger age] (AOR = 10.39; 95% CI: 4.16-25.92 for ages 5-6 years), and mother's weight status (overweight AOR = 2.99; 95% CI: 1.05-8.51; obese AOR = 5.19; 95% CI: 1.89-14.18). Child BMI was the only predictor of mothers' overestimation (AOR = 0.89; 95% CI: 0.85-0.94) using the silhouette method. Conclusions: Using silhouette scales to identify children's body weight may be a more accurate tool for clinicians and interventionists to activate parents' awareness of unhealthy weight in children compared to using traditional categorical weight-labeling methods.


Subject(s)
Body Weight/physiology , Hispanic or Latino/psychology , Mothers/psychology , Pediatric Obesity/psychology , Body Mass Index , Child , Child, Preschool , Cross-Sectional Studies , Female , Humans , Male , Mexico/ethnology , United States
2.
J Nutr Educ Behav ; 50(4): 372-378.e1, 2018 04.
Article in English | MEDLINE | ID: mdl-29031582

ABSTRACT

OBJECTIVE: To examine the validity of the Children's Eating Behavior Questionnaire (CEBQ) through the associations of its 3 subscale scores (food responsiveness, slowness in eating, and satiety responsiveness) with body mass index (BMI). DESIGN: Cross-sectional study of baseline data from a clinic-based obesity prevention and control randomized controlled trial. PARTICIPANTS: Latino pediatric patients (n = 295) aged 5-11 years from a federally qualified health center in San Diego County, CA, with BMI percentiles ranging from 75.5 to 99.0. MAIN OUTCOME MEASURE: Child BMI-for-age percentile computed using the standardized program for the 2000 Centers for Disease Control and Prevention growth charts. ANALYSIS: Principal components analysis and multivariate linear regressions. RESULTS: Principal components analysis showed a factor structure relatively similar to that of the original 3 CEBQ subscales, with acceptable internal consistency and between-subscale correlations. Analyses demonstrated the validity of the 3 subscales: child BMI was positively associated with food responsiveness (ß = .336; P ≤ .001) and negatively associated with slowness in eating (ß = -.209; P ≤ .001) and satiety responsiveness (ß = -.211; P ≤ .001). CONCLUSIONS AND IMPLICATIONS: The 14-item CEBQ scale may be useful for assessing obesogenic eating behaviors of Latino children. Further study is needed to replicate these findings.


Subject(s)
Child Behavior/psychology , Feeding Behavior/psychology , Surveys and Questionnaires/standards , Body Mass Index , California , Child , Child, Preschool , Cross-Sectional Studies , Female , Hispanic or Latino , Humans , Linear Models , Male , Obesity/prevention & control , Parents
3.
Br J Sports Med ; 46(9): 684-8, 2012 Jul.
Article in English | MEDLINE | ID: mdl-21903618

ABSTRACT

BACKGROUND: Few prospective studies have examined predictors of change in specific physical activity (PA) behaviours in different ethnic groups. PURPOSE: To assess predictors of change in sports participation in Latino and non-Latino 5-8 year-old children in San Diego, California. METHODS: Average sports participation frequency (days/week) was assessed by validated parent-report at baseline (Nov 2006-May 2008) and 1 year later in 541 children (45.0% male, 41.1% Latino; mean ± SD age: 6.6 ± 0.7 years) taking part in an obesity prevention study (Project MOVE). Biological (sex, age, Body Mass Index z-score), socio-cultural (ethnicity, income, care giver education), parental (PA rules, PA encouragement) and environmental factors (home PA equipment, PA location) were assessed at baseline. Associations between change in sports participation and potential predictors were studied using multilevel linear regression stratified by Latino ethnicity, adjusted for sex, baseline sport participation, study condition and recruitment area. RESULTS: Sports participation increased over 1 year (mean change: +0.5 days; p<0.001) and change was similar for boys and girls (p=0.95), but Latino children showed a greater increase (p=0.03). The number of locations used for PA (p=0.024) and the total frequency of PA location use (p=0.018) were positively associated with increased sports participation among Latinos. No predictors were identified for non-Latino children. CONCLUSIONS: Only factors relating to PA location were identified as predictors of change in sports participation for Latino children. Interventions targeting specific PA behaviours such as sports participation may need to consider PA locations for Latino children and be tailored for specific ethnic groups.


Subject(s)
Hispanic or Latino/psychology , Sports/psychology , Age Factors , California/epidemiology , Child , Child, Preschool , Female , Hispanic or Latino/statistics & numerical data , Humans , Male , Sedentary Behavior/ethnology , Sex Factors , Socioeconomic Factors , Sports/statistics & numerical data
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