Sex non-specific growth charts and potential clinical implications in the care of transgender youth.

Introduction: The Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) created separate growth charts for girls and boys because growth patterns and rates differ between sexes. However, scenarios exist in which this dichotomizing "girls versus boys" approach may not be ideal, including the care of non-binary youth or transgender youth undergoing transitions consistent with their gender identity. There is therefore a need for growth charts that age smooth differences in pubertal timing between sexes to determine how youth are growing as "children" versus "girls or boys" (e.g., age- and sex-neutral, compared to age- and sex-specific, growth charts). Methods: Employing similar statistical techniques and datasets used to create the CDC 2000 growth charts, we developed age-adjusted, sex non-specific growth charts for height, weight, and body mass index (BMI), and z-score calculators for these parameters. Specifically, these were created using anthropometric data from five US cross-sectional studies including National Health Examination Surveys II-III and National Health and Nutrition Examination Surveys I-III. To illustrate contemporary clinical practice, we overlaid our charts on CDC 2000 girls and boys growth charts. Results: 39,119 youth 2-20 years old (49.5% female; 66.7% non-Hispanic White; 21.7% non-Hispanic Black) were included in the development of our growth charts, reference ranges, and z-score calculators. Respective curves were largely superimposable through around 10 years of age after which, coinciding with pubertal onset timing, differences became more apparent. Discussion: We conclude that age-adjusted, sex non-specific growth charts may be used in clinical situations such as transgender youth in which standard "girls versus boys" growth charts are not ideal. Until longitudinal auxological data are available in these populations, our growth charts may help to assess a transgender youth's growth trajectory and weight classification, and expectations surrounding these.

Association between Hunger and Truancy among Students in Liberia: Analysis of 2017 Global School-Based Student Health Survey.

BACKGROUND: About 83% and 49% of Liberians live beneath the poverty line of US$1.25/day and experience hunger, respectively. Studies have established that hunger has long-term adverse consequence on truancy among students. However, no national level study has investigated contribution of hunger on truancy among in-school students in Liberia. This paper therefore seeks to examine the association between hunger and truancy among students in Liberia. The study hypothesises that there exists a positive association between hunger and truancy. METHODS: This study used the 2017 Liberia Global School-Based Student Health Survey (LGSSHS) and sampled 2,744 students. However, the present study was restricted to 1,613 respondents who had complete information about variable of interest analysed in the study. Hunger and truancy are the main explanatory and outcome variables for this study. At 95% confidence interval, two binary logistic regression models were built with Model I examining relationship between hunger and truancy and Model II controlled for the influence of covariates on truancy. Our findings were reported in odds ratio (OR) and adjusted odds ratio (AOR). All the analysis was done using STATA version 14.0. RESULTS: Descriptively, 46% were truant, and 65% of students ever experienced hunger. Inferentially, students that ever-encountered hunger had higher odds to truancy (AOR = 1.32, CI = 1.06-1.65). The odds to be truant also increased among those at 15 years and above (AOR = 2.00, CI = 1.46-2.72), who witnessed bullying (AOR = 1.36, CI = 1.10-1.68), that felt lonely (AOR = 1.35, CI = 1.06-1.71), that currently smoke cigarette (AOR = 2.58, CI = 1.64-4.06), and wards whose parents go through their things (AOR = 1.26, CI = 1.03-1.55). CONCLUSIONS: The study concluded that hunger was associated with truancy among students in Liberia. Additionally, students' age, bullying, feeling lonely, cigarette use, and parental concern also determined truancy. Governments, policy makers, and other partners in education should therefore roll out some school-based interventions, such as the school feeding program, which will help minimise the incidence of hunger among students. Such programs should consider the variations in students' background characteristics in its design.

Adjusting for Pubertal Status Reduces Overweight and Obesity Prevalence in the United States.

OBJECTIVE: To compare pediatric overweight and obesity prevalence among non-Hispanic white, Mexican American, and non-Hispanic black US youths before and after adjusting body mass index (BMI) for pubertal status, as assessed by Tanner stage. STUDY DESIGN: We analyzed cross-sectional anthropometric and pubertal data from non-Hispanic white, Mexican American, and non-Hispanic black youths in the National Health and Nutrition Examination Survey (NHANES) III. We developed specialized Tanner stage and chronological age-adjusted models to establish Tanner-stage adjusted BMI z-scores, which were then used to determine adjusted overweight/obesity prevalence. We compared pediatric overweight/obesity prevalence before and after pubertal status adjustment. RESULTS: Among 3206 youths aged 8-18 years (50% male; 26% non-Hispanic white, 35% Mexican American, 39% non-Hispanic black), adjusting BMI for Tanner stage significantly reduced overweight (males, from 29% to 21%; females, from 29% to 17%) and obesity (males, from 14% to 7%; females, from 11% to 5%) prevalence across all races/ethnicities. The obesity prevalence reduction was more pronounced in Mexican Americans (males, 11% reduction; females, 9% reduction) and non-Hispanic blacks (males and females, 10% reduction) compared with non-Hispanic whites (males, 6% reduction; females, 5% reduction). Similar patterns were seen in overweight prevalence. CONCLUSIONS: Adjusting for pubertal status reduced the prevalence of overweight/obesity in non-Hispanic white, Mexican American, and non-Hispanic black youth. This suggests that adjusting for puberty incorporates changes otherwise not captured when only considering the age of a child. Adjusting BMI for pubertal status may be important when interpreting a youth's weight status and consideration for obesity management, as well as when interpreting pediatric overweight/obesity prevalence data.