RESUMO
OBJECTIVE: The objective of this study was to describe anthropometric measures from internationally adopted children. Internationally adopted children are at risk for poor growth and development and there is no standardized growth chart evaluation for internationally adopted children due to variations in growth, genetics, and environmental exposures. METHODS: This is a retrospective chart review of 882 patients seen in an international adoption clinic between 2010 and 2017. Anthropometric measurements were converted to Z scores for weight, height, head circumference, and body mass index. RESULTS: A total of 41 countries and 16 subregions were represented. Central America, northern Africa, southern Africa, and southern Europe were the only subregions that had positive mean Z scores for weight, and southeast Asia had the lowest mean Z score for weight (n = 40, -1.76). No subregion had a positive mean Z score for height, and western Asia had the lowest overall mean Z score for height (n = 2, -2.44). Mean Z score for body mass index was positive in several subregions. CONCLUSIONS: Growth is an important predictor of health and development, and this study adds to the literature on growth patterns of internationally adopted children.
Assuntos
Criança Adotada , Criança , Humanos , Estudos Retrospectivos , Índice de Massa Corporal , Europa (Continente) , América CentralRESUMO
BACKGROUND AND OBJECTIVES: Food insecurity (FI) has increasingly become a focus for hospitalized patients. The best methods for screening practices, particularly in hospitalized children, are unknown. The purpose of the study was to evaluate results of an electronic medical record (EMR) embedded, brief screening tool for FI among inpatients. METHODS: This was a cross-sectional study from August 2020 to September 2022 for all children admitted to a quaternary children's hospital. Primary outcomes were proportion of those screened for FI and those identified to have a positive screen. FI was evaluated by The Hunger Vital Sign, a validated 2-question screen verbally obtained in the nursing intake form in the EMR. Covariates include demographic variables of age, sex, race, ethnicity, primary language, and insurance. Statistical analyses including all univariate outcome and bivariate comparisons were performed with SAS 9.4. RESULTS: There were 31 553 patient encounters with 81.7% screened for FI. Patients had a median age of 6.3 years, were mostly male (54.2%), White (60.6%), non-Hispanic (92.7%), English-speaking (94.3%), and had government insurance (79.8%). Younger (0-2 years), non-White, and noninsured patients were all screened significantly less often for FI (all P < .001). A total of 3.4% were identified as having FI. Patients who were older, non-White, Hispanic, non-English speaking, and had nonprivate insurance had higher FI (all P < .001). CONCLUSIONS: Despite the use of an EMR screening tool intended to be universal, we found variation in how we screen for FI. At times, we missed those who would benefit the most from intervention, and thus it may be subject to implementation bias.