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Objectives Vitamin K deficiency bleeding (VKDB) in infants is a coagulopathy preventable with a single dose of injectable vitamin K at birth. The Tennessee Department of Health (TDH) and Centers for Disease Control and Prevention (CDC) investigated vitamin K refusal among parents in 2013 after learning of four cases of VKDB associated with prophylaxis refusal. Methods Chart reviews were conducted at Nashville-area hospitals for 2011-2013 and Tennessee birthing centers for 2013 to identify parents who had refused injectable vitamin K for their infants. Contact information was obtained for parents, and they were surveyed regarding their reasons for refusing. Results At hospitals, 3.0% of infants did not receive injectable vitamin K due to parental refusal in 2013, a frequency higher than in 2011 and 2012. This percentage was much higher at birthing centers, where 31% of infants did not receive injectable vitamin K. The most common responses for refusal were a belief that the injection was unnecessary (53%) and a desire for a natural birthing process (36%). Refusal of other preventive services was common, with 66% of families refusing vitamin K, newborn eye care with erythromycin, and the neonatal dose of hepatitis B vaccine. Conclusions for Practice Refusal of injectable vitamin K was more common among families choosing to give birth at birthing centers than at hospitals, and was related to refusal of other preventive services in our study. Surveillance of vitamin K refusal rates could assist in further understanding this occurrence and tailoring effective strategies for mitigation., Author(s): Lauren H. Marcewicz [sup.1] [sup.2] [sup.6] , Joshua Clayton [sup.1] [sup.3] , Matthew Maenner [sup.1] [sup.4] , Erika Odom [sup.2] , Ekwutosi Okoroh [sup.2] , Deborah Christensen [sup.4] , [...]

Neurofibromatosis type 1 (NF1) is an inherited neurocutaneous disorder associated with neurodevelopmental disorders including autism spectrum disorder (ASD). The frequency of ASD/NF1 co-occurrence has been subject to debate since the 1980s. This relationship was investigated in a large population-based sample of 8-year-old children identified with ASD (N = 12,271) by the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring (ADDM) Network. Twenty-two (1-in-558) children with ASD had diagnosed NF1, exceeding NF1 general population estimates by four to five fold. Children with ASD/NF1 versus ASD without NF1 were significantly less likely to receive a community-based ASD diagnosis (p = 0.04) and understand non-verbal communication (p = 0.001). These findings underscore the importance of including social-communication ability among relevant developmental concerns in children with NF1., Author(s): Deborah A. Bilder[sup.1] , Amanda V. Bakian[sup.1] , David A. Stevenson[sup.2] [sup.7] , Paul S. Carbone[sup.3] , Christopher Cunniff[sup.4] [sup.8] , Alyson B. Goodman[sup.5] , William M. McMahon[sup.6] , [...]

Objective: Many US youth experienced accelerated weight gain during the early COVID‐19 pandemic. Using an ambulatory electronic health record data set, the authors compared children's rates of BMI change in three periods: pre‐pandemic (January 2018‐February 2020), early pandemic (March‐December 2020), and later pandemic (January‐November 2021). Methods: This study used mixed‐effects models to examine differences in rates of change in BMI, weight, and obesity prevalence among the three periods. Covariates included time as a continuous variable, a variable indicating in which period each BMI was taken, sex, age, and initial BMI category. Results: In a longitudinal cohort of 241,600 children aged 2 through 19 years with ≥4 BMI measurements, the monthly rates of BMI change (kilograms per meters squared) were 0.056 (95% CI: 0.056‐0.057) in the pre‐pandemic period, 0.104 (95% CI: 0.102‐0.106) in the early pandemic, and 0.035 (95% CI: 0.033‐0.036) in the later pandemic. The estimated prevalence of obesity in this cohort was 22.5% by November 2021. Conclusions: In this large, geographically diverse cohort of US youth, accelerated rates of BMI change observed during 2020 were largely attenuated in 2021. Positive rates indicate continued weight gain rather than loss, albeit at a slower rate. Childhood obesity prevalence remained high, which raises concern about long‐term consequences of excess weight and underscores the importance of healthy lifestyle interventions. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to assess the association of BMI with inpatient care cost, duration, and acute complications among patients hospitalized for COVID‐19 at 273 US hospitals. Methods: Children (aged 2–17 years) and adults (aged ≥18 years) hospitalized for COVID‐19 during March 2020–July 2021 and with measured BMI in a large electronic administrative health care database were included. Generalized linear models were used to assess the association of BMI categories with the cost and duration of inpatient care. Results: Among 108,986 adults and 409 children hospitalized for COVID‐19, obesity prevalence was 53.4% and 45.0%, respectively. Among adults, overweight and obesity were associated with higher cost of care, and obesity was associated with longer hospital stays. Children with severe obesity had higher cost of care but not significantly longer hospital stays, compared with those with healthy weight. Children with severe obesity were 3.7 times (95% CI: 1.4–9.5) as likely to have invasive mechanical ventilation and 62% more likely to have an acute complication (95% CI: 39%–90%), compared with children with healthy weight. Conclusions: These findings show that patients with a high BMI experience significant health care burden during inpatient COVID‐19 care. [ABSTRACT FROM AUTHOR]

Objective: This study compared the importance of age at adiposity rebound versus childhood BMI to subsequent BMI levels in a longitudinal analysis.Methods: From the electronic health records of 4.35 million children, a total of 12,228 children were selected who were examined at least once each year between ages 2 and 7 years and reexamined after age 14 years. The minimum number of examinations per child was six. Each child's rebound age was estimated using locally weighted regression (lowess), a smoothing technique.Results: Children who had a rebound age < 3 years were, on average, 7 kg/m2 heavier after age 14 years than were children with a rebound age ≥ 7 years. However, BMI after age 14 years was more strongly associated with BMI at the rebound than with rebound age (r = 0.57 vs. -0.44). Furthermore, a child's BMI at age 3 years provided more information on BMI after age 14 years than did rebound age. In addition, rebound age provided no information on subsequent BMI if a child's BMI at age 6 years was known.Conclusions: Although rebound age is related to BMI after age 14 years, a child's BMI at age 3 years provides more information and is easier to obtain. [ABSTRACT FROM AUTHOR]

Background Late sequelae of COVID-19 have been reported; however, few studies have investigated the time course or incidence of late new COVID-19–related health conditions (post-COVID conditions) after COVID-19 diagnosis. Studies distinguishing post-COVID conditions from late conditions caused by other etiologies are lacking. Using data from a large administrative all-payer database, we assessed type, association, and timing of post-COVID conditions following COVID-19 diagnosis. Methods Using the Premier Healthcare Database Special COVID-19 Release (release date, 20 October 2020) data, during March–June 2020, 27 589 inpatients and 46 857 outpatients diagnosed with COVID-19 (case-patients) were 1:1 matched with patients without COVID-19 through the 4-month follow-up period (control-patients) by using propensity score matching. In this matched-cohort study, adjusted ORs were calculated to assess for late conditions that were more common in case-patients than control-patients. Incidence proportion was calculated for conditions that were more common in case-patients than control-patients during 31–120 days following a COVID-19 encounter. Results During 31–120 days after an initial COVID-19 inpatient hospitalization, 7.0% of adults experienced ≥1 of 5 post-COVID conditions. Among adult outpatients with COVID-19, 7.7% experienced ≥1 of 10 post-COVID conditions. During 31–60 days after an initial outpatient encounter, adults with COVID-19 were 2.8 times as likely to experience acute pulmonary embolism as outpatient control-patients and also more likely to experience a range of conditions affecting multiple body systems (eg, nonspecific chest pain, fatigue, headache, and respiratory, nervous, circulatory, and gastrointestinal symptoms) than outpatient control-patients. Conclusions These findings add to the evidence of late health conditions possibly related to COVID-19 in adults following COVID-19 diagnosis and can inform healthcare practice and resource planning for follow-up COVID-19 care. [ABSTRACT FROM AUTHOR]

The Mind, Exercise, Nutrition, Do It! 7–13 (MEND 7–13) program was adapted in 2016 by 5 Denver Health federally qualified health centers (DH FQHC) into MEND+, integrating clinician medical visits into the curriculum and tracking health measures within an electronic health record (EHR). We examined trajectories of body mass index (BMI, kg/m2) percentile, and systolic and diastolic blood pressures (SBP and DBP) among MEND+ attendees in an expanded age range of 4 to 17 years, and comparable nonattendees. Data from April 2015 to May 2018 were extracted from DH FQHC EHR for children eligible for MEND+ referral (BMI ≥85th percentile). The sample included 347 MEND+ attendees and 21,061 nonattendees. Mixed-effects models examined average rate of change for BMI percent of the 95th percentile (%BMIp95), SBP and DBP (mm Hg), after completion of the study period. Most children were ages 7 to 13 years, half were male, and most were Hispanic. An average of 4.2 MEND+ clinical sessions were attended. Before MEND+, %BMIp95 increased by 0.247 units/month among MEND+ attendees. After attending, %BMIp95 decreased by 0.087 units/month (P <.001). Eligible nonattendees had an increase of 0.084/month in %BMIp95. Before MEND+ attendance, SBP and DBP increased by 0.041 and 0.022/month, respectively. After MEND+ attendance, SBP and DBP decreased by 0.254/month (P <.001) and 0.114/month (P <.01), respectively. SBP and DBP increased by 0.033 and 0.032/month in eligible nonattendees, respectively. %BMIp95, SBP, and DBP significantly decreased among MEND+ attendees when implemented in community-based clinical practice settings at DH FQHC. [ABSTRACT FROM AUTHOR]

Background Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. Methods Using data from the Premier Healthcare Database on 181 813 hospitalized adults diagnosed with COVID-19 during March–September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. Results Overall, 84 497 (47%) patients were admitted to the ICU, 29 078 (16%) received IMV, and 27 864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92–0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09–1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09–1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06–1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. Conclusions These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes. [ABSTRACT FROM AUTHOR]

Keywords: acute lung injury; e-cigarette; EVALI; toxicology; vitamin E acetate EN acute lung injury e-cigarette EVALI toxicology vitamin E acetate 426 431 6 12/26/20 20210101 NES 210101 The Centers for Disease Control and Prevention (CDC), the US Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders have investigated a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). However, evidence is not sufficient to rule out the contribution of other chemicals of concern, including chemicals in either tetrahydrocannabinol (THC) or non-THC products, in some of the reported EVALI cases. Evidence is not sufficient to rule out the contribution of other chemicals of concern, including chemicals in either THC or non-THC products, in some of the reported EVALI cases.[4] SP , sp [7] SP , sp [10] What Is VEA, and Does It Differ From Vitamin E? None of the products seized in 2018 contained VEA; however, the 20 products seized in 2019 and the 24 products submitted by 12 patients with EVALI in 2019 contained VEA. [Extracted from the article]

Objective: Several cross-sectional studies have shown that height in childhood is correlated with BMI and with body fatness, and two longitudinal studies have reported that childhood height is associated with adult BMI. This study explored this longitudinal association in an electronic health record database of 2.8 million children.Methods: Children were initially examined between the ages of 2 and 13.9 years and, on average, were reexamined 4 years later.Results: As expected, there was a cross-sectional correlation between height-for-age z score and BMI that increased from r = -0.06 (age of 2 years) to r = 0.37 (age of 9-10 years). In addition, height-for-age at the first visit was related to subsequent BMI and obesity, with the prevalence of subsequent obesity increasing about fourfold over six categories of height-for-age at the first visit. About 40% of this longitudinal association was independent of initial BMI, but its magnitude decreased with initial age. For example, the initial height-for-age of children who were 12 years of age or older was only weakly associated with subsequent BMI.Conclusions: Health professionals should recognize that greater childhood height-for-age before 12 years of age may be a marker for increased risk of subsequent obesity. [ABSTRACT FROM AUTHOR]

Summary: Background and Objective: As obesity among children and adolescents is associated with major health risks, including the persistence of obesity into adulthood, there has been interest in targeting prevention efforts at children and adolescent. The longitudinal tracking of BMI and obesity, as well as the effects of initial age and duration of follow‐up on this tracking, were examined in a large electronic health record (EHR) database. Methods: The data consisted of 2.04 million children who were examined from 2006 through 2018. These children were initially examined between ages 2 and 9 years and had a final examination, on average, 4 years later. Results: Overall, children with obesity at one examination were 7.7 times more likely to have obesity at a subsequent examination than children with a BMI ≤ 95th percentile. Further, 71% of children with obesity at one examination continued to have obesity at re‐examination. Although 2‐year‐olds had a relative risk of 5.5 and a positive predictive value of 54%, then sensitivity of obesity at younger ages was low. Of the children who were re‐examined after age 10 y and found to have obesity, only 22% had a BMI ≥ 95th percentile at age 2 years. Conclusions: Despite the tracking of obesity at all ages, these results agree with previous reports that have found that an elevated BMI at a very young age will identify only a small proportion of older children with obesity. [ABSTRACT FROM AUTHOR]

Introduction: The U.S. Preventive Services Task Force recommends clinicians screen children aged 6 years or older for obesity and offer or refer children with obesity to intensive weight management programs. This study explores clinician awareness of weight management programs meeting the recommendation, adherence to the recommendation of screening and referral, and associations between provider and practice characteristics and weight management program referrals.Methods: This cross-sectional study used data from the DocStyles survey 2017, a web-based panel survey, analyzed in 2017. Among 1,023 clinicians who see pediatric patients, this study examined clinician awareness of weight management programs in their communities that met the recommendation, practice of screening for childhood obesity, and referral to weight management programs. Multivariable logistic regression estimated associations between the demographic and practice characteristics of clinicians and weight management program referrals.Results: Only 24.6% of surveyed clinicians were aware of a weight management program that met the U.S. Preventive Services Task Force recommendation in their community; of those aware, 88.9% referred patients to these weight management programs. Most (83.6%) clinicians screened children for obesity in ≥75% of visits. Overall, 53.5% of clinicians provided referrals to weight management programs. Referral was higher among female clinicians and clinicians serving mostly middle-income patients. Providers without teaching hospital privileges had lower odds of referral.Conclusions: Adherence to clinical recommendations is essential to curbing the childhood obesity epidemic. Only one in four surveyed clinicians were aware of weight management programs in their community meeting U.S. Preventive Services Task Force criteria. Half of clinicians referred pediatric patients with obesity to a weight management program. Results suggest efforts are needed to increase awareness of, and referral to, weight management programs meeting the recommendation. [ABSTRACT FROM AUTHOR]

Objective: Although the tracking of BMI levels from childhood to adulthood has been examined, there is little information on the within-person variability of BMI.Methods: Longitudinal data from 11,591 schoolchildren, 3,096 of whom were reexamined as adults, were used to explore the tracking and variability of BMI levels. This article focuses on changes in age-adjusted levels of BMI.Results: There was strong tracking of BMI levels. The correlation of adjusted BMI levels was r = 0.88, and 78% of children with severe obesity at one examination had severe obesity at the next examination (mean interval, 2.7 years). Further, an increase in adjusted BMI from +5 kg/m2 (above the median) to + 10 increased the risk for adult BMI ≥ 40 by 2.7-fold. However, BMI levels among children and adolescents were variable. Over a 9- to 15-month interval, the SD of adjusted BMI change was 0.9 kg/m2 , and 0.7% of children had an absolute change ≥ 3.5. This variability was associated with the interval between examinations and with the initial BMI.Conclusions: Despite the high degree of tracking of BMI, annual changes of 3.5 kg/m2 or more are plausible. Knowledge of this variability is important when following a child over time. [ABSTRACT FROM AUTHOR]

Background:BMIz-scores (BMIz) based on the Centers for Disease Control and Prevention (CDC) growth charts among children do not accurately characterise BMI levels among children with very high BMIs. These limitations may be particularly relevant in longitudinal and intervention studies, as the large changes in the L (normality) and S (dispersion) parameters with age can influence BMIz. Aim:To compare longitudinal changes in BMIzwith BMI expressed as a percentage of the 95th percentile (%BMIp95) and a modifiedz-score calculated as log(BMI/M)/S. Subjects and methods:A total of 45 414 2–4-year-olds with severe obesity (%BMIp95 ≥ 120). Results:Changes in very high BMIzlevels differed from the other metrics. Among severely obese 2-year-old girls, for example, the mean BMIzdecreased by 0.6 SD between examinations, but there were only small changes in BMIp95 and modified BMIz. Some 2-year-old girls had BMIzdecreases of >1 SD, even though they had large increases in BMI, %BMIp95 and modified BMIz. Conclusions:Among children with severe obesity, BMIzchanges may be due to differences in the transformations used to estimate levels of BMIzrather than to changes in body size. The BMIs of these children could be expressed relative to the 95th percentile or as modifiedz-scores. [ABSTRACT FROM AUTHOR]

Objective: Although the Centers for Disease Control and Prevention (CDC) growth charts are widely used, BMI-for-age z-Scores (BMIz) are known to be uninformative above the 97th percentile. This study compared the relations of BMIz and other BMI metrics (%BMIp95 , percent of 95th percentile, and ΔBMIp95 , BMI minus 95th percentile) to circumferences, skinfolds, and fat mass. We were particularly interested in the differences among children with severe obesity (%BMIp95  ≥ 120).Methods: Data was used from 30,003 2- to 19-year-olds who were examined from 1999-2000 through 2013-2014 in the National Health and Nutrition Examination Survey (NHANES).Results: The theoretical maximum BMIz based on the growth charts varied by more than threefold across ages. The BMI metrics were strongly intercorrelated, but BMIz was less strongly related to the adiposity measures than were ΔBMIp95 and %BMIp95 . Among children with severe obesity, circumferences and triceps skinfold showed almost no association with BMIz (r ≤ 0.10), whereas associations with %BMIp95 and ΔBMIp95 ranged from r = 0.32 to 0.79. Corresponding associations with fat mass ÷ height2 ranged from r = 0.40 (BMIz) to r =0.82 (%BMIp95 ) among 8- to 19-year-olds.Conclusions: Among children with severe obesity, BMIz is only weakly associated with other measures of body fatness. Very high BMIs should be expressed relative to the CDC 95th percentile, particularly in studies that evaluate obesity interventions. [ABSTRACT FROM AUTHOR]