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Background: During summer, children may meet fewer 24 hours Movement Guidelines (24 hr-MGs) [moderate-vigorous physical activity (PA): ≥60 minutes/day, screen time: ≤2 hours/day, sleep: 9-11 hours/day) compared with the school year. Structured environments within community settings ( e.g. , summer programs) support guideline adherence. Information about the relationship between structured home environments and 24 hr-MGs is needed. This mixed-methods study examined which features of the family, home, and community environment supported children in meeting 24 hr-MGs during the school year and summer. Methods: Children's PA and sleep data were estimated from wrist-worn accelerometry, and screen time was assessed via parent-reported nightly surveys (14 days) at two time points [school year: (March-April) and summer (July-August) of 2021]. Parents completed a survey at each time point with 13 measures of the family ( e.g. , screen time rules), home ( e.g. , bed sharing), and community ( e.g. , summer program enrollment) environment. Multilevel mixed effect logistic regression estimated the odds of meeting 24 hr-MGs at each time point. Parents ( n = 20) completed a qualitative interview and thematic analysis revealed parents perceived facilitators and barriers to guideline adherence. Results: Summer program enrollment and bedtime rules were associated with greater odds of meeting the PA [odds ratios (ORs): 4.9, 95% confidence intervals (CIs): (1.4, 17.1)] and ≥two 24 hr-MGs [OR: 2.2, 95 CI: (1.2, 4.0)] during summer, respectively. Parents perceived family rules/routines supported guideline adherence and lack of access to summer programs was a barrier. Conclusions: Structured environments at home and in the community can support children in meeting 24 hr-MGs guidelines. Interventions that expand access to summer programming and encourage implementation of structured home routines may support meeting multiple 24 hr-MGs during summer.

Objective: To describe the developmental pattern for physical activity (PA) in children 6-36 months of age and to identify factors that are longitudinally associated with PA as children transition from infancy to preschool age., Study Design: The study employed a prospective longitudinal design with baseline data collected when children were approximately 6 months of age. Mothers and infants (n = 124) were recruited through community and educational settings in South Carolina. Data were collected at 6-month intervals from 6 to 36 months. PA was measured via accelerometry. Mothers completed questionnaires that assessed independent variables, including parent characteristics, the child's sex, race, and ethnicity, birth/delivery type, motor milestones, sleep habits, dietary practices, childcare setting, and home environmental factors. Trained research staff administered anthropometric measures and assessed motor developmental status. Growth curve models described the age-related pattern for PA and evaluated relationships between independent variables and change in PA., Results: PA increased by approximately 45% between 6 and 36 months of age and followed a curvilinear pattern, with most of the increase occurring between 6 and 24 months. The child's exposure to television/electronic media was negatively associated with change in PA, and the presence of older siblings in the home was positively associated with change in PA., Conclusions: As children develop from infancy to early childhood, their PA increases substantially, with most of the increase occurring by 24 months of age., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose. This study was supported by a grant from the National Institutes of Health, R01HD091483., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Study Question: Does the prevalence of 12-month infertility in Burkina Faso, Côte d'Ivoire, Kenya, and Uganda differ between women trying to conceive and the broader population of women exposed to unprotected sex, and how are prevalence estimates affected by model assumptions and adjustments?, Summary Answer: Estimates of 12-month infertility among tryers ranged from 8% in Burkina Faso to 30% in Côte d'Ivoire, increasing substantially among a larger population of women exposed to unprotected intercourse., What Is Known Already: While having a child is a fundamental human experience, the extent to which women and couples experience infertility is a neglected area of research, particularly in sub-Saharan Africa. Existing estimates of infertility in this region vary widely from 2% to 32%, however, potential impacts of variability in study populations and model assumptions have not been well-examined., Study Design, Size, Duration: We used cross-sectional nationally representative survey data from Burkina Faso, Côte d'Ivoire, Kenya, and Uganda. We employed a multi-stage cluster random sampling design with probability proportional to the size selection of clusters within each country to produce representative samples of women aged 15-49. Samples ranged from 3864 in Côte d'Ivoire to 9489 in Kenya., Participants/materials, Setting, Methods: We created two analytic samples in each country-tryers and a broader sample of women exposed to unprotected sex-exploring differences in population characteristics and estimating the period prevalence of 12-month infertility using the current duration (CD) approach. We also examined the impact of several model assumptions within each of the two analytic samples, including adjustments for recent injectable contraceptive use, unrecognized pregnancy, infertility treatment, underreported contraceptive use, and sexual activity., Main Results and the Role of Chance: Employing the CD approach among tryers produced an overall 12-month infertility prevalence of 7.9% (95% CI 6.6-12.7) in Burkina Faso, 29.6% (95% CI 15.3-100.0) in Côte d'Ivoire, 24.5% (95% CI 16.5-34.6) in Kenya, and 14.7% (95% CI 8.1-22.4) in Uganda. Results among women exposed to unprotected intercourse indicated much higher levels of infertility, ranging from 22.4% (95% CI 18.6-30.8) in Uganda to 63.7% (95% CI 48.8-87.9) in Côte d'Ivoire. Sensitivity analyses suggest infertility estimates are particularly sensitive to adjustments around pregnancy recognition timing and sexual activity, with little impact of adjustments for recent injectable contraceptive use, infertility treatment, and underreporting of traditional and coital dependent contraceptive use., Limitations, Reasons for Caution: There was substantial digit preference in responses at 12 months, particularly among the tryers, which could introduce bias. Data quality concerns in the reproductive calendar may impact the accuracy of the CD approach among the broader sample of women exposed to unprotected sex, particularly with regard to underreported contraceptive use, induced and spontaneous abortions, and unrecognized pregnancies. Lastly, we lacked information on postpartum amenorrhea or abstinence., Wider Implications of the Findings: Understanding the inconsistencies in definition and analytic approach and their implications for infertility estimation is important for reliably monitoring population-level infertility trends, identifying factors influencing infertility, improving prevention programs, and ensuring access to quality treatment and services., Study Funding/competing Interest(s): This study was supported by grants from the Bill & Melinda Gates Foundation (INV009639) and the National Institute of Child Health and Human Development (K01HD107172). The funders were not involved in the study design, analyses, manuscript writing, or the decision to publish. The authors have no conflicts of interest to declare., Trial Registration Number: N/A., (© The Author(s) 2024. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

General pediatricians and those specialized in developmental-behavioral and neurodevelopmental disabilities support children with neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We identified substantial geographic disparities in pediatrician availability (eg, urban > rural areas), as well as regions with low pediatrician access but high ASD/ADHD prevalence estimates (eg, the US Southeast)., Competing Interests: Declaration of Competing Interest This publication was made possible in part by Grant Number T32-GM081740 from NIH-NIGMS. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIGMS or NIH. This project was supported in part by the Health Resources and Services Administration (HRSA) of the US Department of Health and Human Services (HHS) under grant number U1CRH30539 Rural Health Research Grant Program Cooperative Agreement. This information or content and conclusions are those of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS or the US Government. This work was also supported by the Centers for Disease Control and Prevention (CDC), National Center on Birth Defects and Developmental Disabilities (Cooperative Agreement #5U19DD001218)., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This study examined individual variation in change over time in sedentary behaviour and factors associated with higher or lower sedentary behaviour and change in sedentary behaviour in 110 toddlers from 18 to 36 months of age. Mother/child dyads were recruited into the study when children were 6 months of age. Mothers completed surveys, and children were measured at 6-month intervals to 36 months. Children wore accelerometers for one week at each time point, and height and weight were measured. Growth curve modelling examined relationships between demographic, early life, and environmental factors and sedentary behaviour from 18 to 36 months. Fifty-one percent of the children were boys. The trajectory of sedentary behaviour increased from 18 to 24 months then declined. Children with higher sedentary behaviour were less likely to be enrolled in daycare ( p  < 0.05), and they engaged in higher TV/electronic media use ( p  < 0.05). Children with lower sedentary behaviour were more likely to have been breastfed ( p  < 0.05). Children with higher locomotion scores at 6 months were less sedentary at 18 months ( p  < 0.05), but this difference diminished over time. Mothers should be encouraged to breastfeed, limit their child's TV/electronic media use, and provide opportunities for their young children to be physically active.

Background: Maternal opioid use (MOU) remains a public health concern. Studies have demonstrated significant increases in MOU, but estimates using ICD-10-CM or stratified by sociodemographic variables are limited., Objectives: Using a statewide, population-based dataset of Florida resident deliveries from 2000 to 2019, we examined the trend of MOU by age, race/ethnicity, education level, and insurance., Methods: Florida administrative data was used to conduct a retrospective cohort study. MOU was identified using opioid-related hospital discharge diagnoses documented prenatally or at delivery. Maternal sociodemographic variables were obtained from Florida vital statistics. Joinpoint regression was used to identify statistically significant changes in the trends overall and stratified by sociodemographic variables. Results are presented as annual percentage changes (APC) and 95% confidence intervals., Results: Our sample included over 3.6 million Florida resident mothers; of which, MOU was identified in 1% ( n  = 22,828) of the sample. From 2000 to 2019, MOU increased over ten-fold from 8.7 to 94.7 per 10,000 live birth deliveries. MOU increased significantly from 2000 to 2011 (APC: 32.8; 95% CI: 29.4, 36.2), remained stable from 2011 to 2016, and decreased significantly from 2016 to 2019 (APC: 3.9; 95% CI: -6.6, -1.0). However, from 2016 to 2019, MOU increased among non-Hispanic Black mothers (APC: 9.2; 95% CI: 7.5, 11.0), and those ages 30-34 (APC: 2.9; 95% CI: 1.2, 4.6) and 35-39 (APC: 6.4; 95% CI: 4.3, 8.4)., Conclusions: Accurate prevalence estimates of MOU by sociodemographic factors are necessary to fully understand prevalence trends, describe the burden among sub-populations, and develop targeted interventions.

Purpose: This study examined longitudinal associations between average physical activity (PA) levels in children and their sleep duration, and whether changes in PA levels are associated with their sleep duration., Methods: Data were collected on 108 children at 4 time points: when children were 6, 12, 18, and 24 months of age (44% female, 50% Non-Hispanic White). PA was assessed using accelerometry. Children's daytime, nighttime, and 24-hour sleep duration were measured with actigraphy. Linear mixed model analyses estimated the associations between average PA levels over time and changes in PA over time, treating each sleep duration variable as an outcome in separate linear mixed model analyses., Results: Children with higher total PA levels slept less during the day compared with children with lower total PA levels over the 2-year period. The strength of the relationship between a child's PA levels and their 24-hour sleep duration decreased as they approached 24 months of age., Conclusions: The results suggest that while PA may be developmentally beneficial overall, it appears that its relationship with sleep duration is not clinically relevant in very young children.

Purpose: In 2021, the United States Preventive Services Task Force (USPSTF) revised their 2013 recommendations for lung cancer screening eligibility by lowering the pack-year history from 30+ to 20+ pack-years and the recommended age from 55 to 50 years. Simulation studies suggest that Black persons and females will benefit most from these changes, but it is unclear how the revised USPSTF recommendations will impact geographic, health-related, and other sociodemographic characteristics of those eligible., Methods: This cross-sectional study employed data from the 2017-2020 Behavioral Risk Factor Surveillance System surveys from 23 states to compare age, gender, race, marital, sexual orientation, education, employment, comorbidity, vaccination, region, and rurality characteristics of the eligible population according to the original 2013 USPSTF recommendations with the revised 2021 USPSTF recommendations using chi-squared tests. This study compared those originally eligible to those newly eligible using the BRFSS raking-dervived weighting variable., Results: There were 30,190 study participants. The results of this study found that eligibility increased by 62.4% due to the revised recommendations. We found that the recommendation changes increased the proportion of eligible females (50.1% vs 44.1%), Black persons (9.2% vs 6.6%), Hispanic persons (4.4% vs 2.7%), persons aged 55-64 (55.8% vs 52.6%), urban-dwellers(88.3% vs 85.9%), unmarried (3.4% vs 2.5%) and never married (10.4% vs 6.6%) persons, as well as non-retirees (76.5% vs 56.1%) Respondents without comorbidities and COPD also increased., Conclusion: It is estimated that the revision of the lung cancer screening recommendations decreased eligibility disparities in sex, race, ethnicity, marital status, respiratory comorbidities, and vaccination status. Research will be necessary to estimate whether uptake patterns subsequently follow the expanded eligibility patterns., (© 2024. The Author(s).)

Lesion-symptom mapping studies provide insight into what areas of the brain are involved in different aspects of cognition. This is commonly done via behavioral testing in patients with a naturally occurring brain injury or lesions (e.g., strokes or brain tumors). This results in high-dimensional observational data where lesion status (present/absent) is nonuniformly distributed, with some voxels having lesions in very few (or no) subjects. In this situation, mass univariate hypothesis tests have severe power heterogeneity where many tests are known a priori to have little to no power. Recent advancements in multiple testing methodologies allow researchers to weigh hypotheses according to side information (e.g., information on power heterogeneity). In this paper, we propose the use of p-value weighting for voxel-based lesion-symptom mapping studies. The weights are created using the distribution of lesion status and spatial information to estimate different non-null prior probabilities for each hypothesis test through some common approaches. We provide a monotone minimum weight criterion, which requires minimum a priori power information. Our methods are demonstrated on dependent simulated data and an aphasia study investigating which regions of the brain are associated with the severity of language impairment among stroke survivors. The results demonstrate that the proposed methods have robust error control and can increase power. Further, we showcase how weights can be used to identify regions that are inconclusive due to lack of power., (© 2024 The Author(s). Biometrical Journal published by Wiley‐VCH GmbH.)

The motivation for this paper is to determine factors associated with time-to-fertility treatment (TTFT) among women currently attempting pregnancy in a cross-sectional sample. Challenges arise due to dependence between time-to-pregnancy (TTP) and TTFT. We propose appending a marginal accelerated failure time model to identify risk factors of TTFT with a model for TTP where fertility treatment is included as a time-varying treatment to account for their dependence. The latter requires extending backwards recurrence survival methods to incorporate time-varying covariates with time-varying coefficients. Since backwards recurrence survival methods are a function of mean survival, computational difficulties arise in formulating mean survival when fertility treatment is unobserved, i.e. when TTFT is censored. We address these challenges by developing computationally friendly forms for the double expectation of TTP and TTFT. The performance is validated via comprehensive simulation studies. We apply our approach to the National Survey of Family Growth and explore factors related to prolonged TTFT in the U.S., Competing Interests: Conflicts of interest: None declared., (© The Royal Statistical Society 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Spatial patterns are common in infectious disease epidemiology. Disease mapping is essential to infectious disease surveillance. Under a group testing protocol, biomaterial from multiple individuals is physically combined into a pooled specimen, which is then tested for infection. If the pool tests negative, all contributing individuals are generally assumed to be uninfected. If the pool tests positive, the individuals are usually retested to determine who is infected. When the prevalence of infection is low, group testing provides significant cost savings over traditional individual testing by reducing the number of tests required. However, the lack of statistical methods capable of producing maps from group testing data has limited the use of group testing in disease mapping. We develop a Bayesian methodology that can simultaneously map disease prevalence using group testing data and identify risk factors for infection. We illustrate its real-world utility using two datasets from vector-borne disease surveillance., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Stella Self reports financial support was provided by National Institute of Allergy and Infectious Diseases. Brian Herrin reports financial support was provided by National Institute of Allergy and Infectious Diseases. Melissa Nolan reports financial support was provided by University of South Carolina Office of the Vice President for Research. Rongjie Huang reports financial support was provided by Companion Animal Parasite Council. Stella Self reports financial support was provided by National Institute of General Medical Sciences. Alexander McLain reports financial support was provided by National Institute of General Medical Sciences. Melissa Nolan reports financial support was provided by National Institute of Allergy and Infectious Diseases. Stella Self reports a relationship with Companion Animal Parasite Council that includes: consulting or advisory, funding grants, and travel reimbursement. Brian Herrin reports a relationship with Companion Animal Parasite Council that includes: board membership and travel reimbursement. Stella Self reports a relationship with Merck & Co Inc that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Motivated by improving the prediction of the human immunodeficiency virus (HIV) suppression status using electronic health records (EHR) data, we propose a functional multivariable logistic regression model, which accounts for the longitudinal binary process and continuous process simultaneously. Specifically, the longitudinal measurements for either binary or continuous variables are modeled by functional principal components analysis, and their corresponding functional principal component scores are used to build a logistic regression model for prediction. The longitudinal binary data are linked to underlying Gaussian processes. The estimation is done using penalized spline for the longitudinal continuous and binary data. Group-lasso is used to select longitudinal processes, and the multivariate functional principal components analysis is proposed to revise functional principal component scores with the correlation. The method is evaluated via comprehensive simulation studies and then applied to predict viral suppression using EHR data for people living with HIV in South Carolina., (© 2024 The Author(s). Biometrical Journal published by Wiley‐VCH GmbH.)

Prevalence estimates of autism spectrum disorder (ASD) point to geographic and socioeconomic disparities in identification and diagnosis. Estimating national prevalence rates can limit understanding of local disparities, especially in rural areas where disproportionately higher rates of poverty and decreased healthcare access exist. Using a small area estimation approach from the 2016-2018 National Survey of Children's Health (N = 70,913), we identified geographic differences in ASD prevalence, ranging from 4.38% in the Mid-Atlantic to 2.71% in the West South-Central region. Cluster analyses revealed "hot spots" in parts of the Southeast, East coast, and Northeast. This geographic clustering of prevalence estimates suggests that local or state-level differences in policies, service accessibility, and sociodemographics may play an important role in identification and diagnosis of ASD.County-Level Prevalence Estimates of Autism Spectrum Disorder in Children in the United States., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose : To identify practice and social contextual factors that associate with physical activity (PA) levels of children during their participation in a youth soccer program. Methods : Twenty-seven youth soccer teams serving children ages 6-11 years participated. Research staff directly observed and recorded PA intensity and practice and social contextual factors using momentary time-sampling procedures. Each team was observed for 1 practice, during which approximately 6 children were each observed for twenty 30-s observation blocks (10-s observation, 20-s recording). In total, children were observed for 3,102 intervals. Multilevel logistic regression analyses were conducted to describe associations between PA intensity and practice and social contexts. Interaction terms were introduced into the models to determine if the associations differed across girls-only, boys-only, and coed teams. Results : A total of 158 children were observed across the 27 teams. Children were more likely to engage in moderate or vigorous PA while performing fitness (Odds Ratio [OR], 9.9, 95% CI = 5.34-18.04), game (OR, 4.0, 95% CI = 2.88-5.66), warm-up (OR, 2.8, 95% CI = 1.85-4.11), and drill (OR, 1.9, 95% CI = 1.41-2.67) activities compared to tactic/instructional activities. The associations between PA intensity levels and practice and social contexts did not differ across girls-only, boys-only, and coed teams. Conclusions : Fitness activities and full-team game play were associated with higher PA intensity levels during children's participation in youth soccer practices. Youth sport practice protocols can be modified to increase children's physical activity.

The vast growth of spatial datasets in recent decades has fueled the development of many statistical methods for detecting spatial patterns. Two of the most commonly studied spatial patterns are clustering, loosely defined as datapoints with similar attributes existing close together, and dispersion, loosely defined as the semi-regular placement of datapoints with similar attributes. In this work, we develop a hypothesis test to detect spatial clustering or dispersion at specific distances in categorical areal data. Such data consists of a set of spatial regions whose boundaries are fixed and known (e.g., counties) associated with a categorical random variable (e.g. whether the county is rural, micropolitan, or metropolitan). We propose a method to extend the positive area proportion function (developed for detecting spatial clustering in binary areal data) to the categorical case. This proposal, referred to as the categorical positive areal proportion function test, can detect various spatial patterns, including homogeneous clusters, heterogeneous clusters, and dispersion. Our approach is the first method capable of distinguishing between different types of clustering in categorical areal data. After validating our method using an extensive simulation study, we use the categorical positive area proportion function test to detect spatial patterns in Boulder County, Colorado USA biological, agricultural, built and open conservation easements., Competing Interests: Competing Interests Declarations of interest: none

This study compared marginal and conditional modeling approaches for identifying individual, park and neighborhood park use predictors. Data were derived from the ParkIndex study, which occurred in 128 block groups in Brooklyn (New York), Seattle (Washington), Raleigh (North Carolina), and Greenville (South Carolina). Survey respondents (n = 320) indicated parks within one half-mile of their block group used within the past month. Parks (n = 263) were audited using the Community Park Audit Tool. Measures were collected at the individual (park visitation, physical activity, sociodemographic characteristics), park (distance, quality, size), and block group (park count, population density, age structure, racial composition, walkability) levels. Generalized linear mixed models and generalized estimating equations were used. Ten-fold cross validation compared predictive performance of models. Conditional and marginal models identified common park use predictors: participant race, participant education, distance to parks, park quality, and population >65yrs. Additionally, the conditional mode identified park size as a park use predictor. The conditional model exhibited superior predictive value compared to the marginal model, and they exhibited similar generalizability. Future research should consider conditional and marginal approaches for analyzing health behavior data and employ cross-validation techniques to identify instances where marginal models display superior or comparable performance., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wende et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: Sleep disruption affects biological processes that facilitate carcinogenesis. This retrospective cohort study used de-identified data from the Veterans Administration (VA) electronic medical record system to test the hypothesis that patients with diagnosed sleep disorders had an increased risk of prostate, breast, colorectal, or other cancers (1999-2010, N=663,869). This study builds upon existing evidence by examining whether patients with more severe or longer-duration diagnoses were at a greater risk of these cancers relative to those with a less severe or shorter duration sleep disorder., Methods: Incident cancer cases were identified in the VA Tumor Registry and sleep disorders were defined by International Classification of Sleep Disorder codes. Analyses were performed using extended Cox regression with sleep disorder diagnosis as a time-varying covariate., Results: Sleep disorders were present among 56,055 eligible patients (8% of the study population); sleep apnea (46%) and insomnia (40%) were the most common diagnoses. There were 18,181 cancer diagnoses (41% prostate, 12% colorectal, 1% female breast, 46% other). The hazard ratio (HR) for a cancer diagnosis was 1.45 (95% confidence interval [CI]: 1.37, 1.54) among those with any sleep disorder, after adjustment for age, sex, state of residence, and marital status. Risks increased with increasing sleep disorder duration (short [<1-2 years] HR: 1.04 [CI: 1.03-1.06], medium [>2-5 years] 1.23 [1.16-1.32]; long [>5-12 years] 1.52 [1.34-1.73]). Risks also increased with increasing sleep disorder severity using cumulative sleep disorder treatments as a surrogate exposure; African Americans with more severe disorders had greater risks relative to those with fewer treatments and other race groups. Results among patients with only sleep apnea, insomnia, or another sleep disorder were similar to those for all sleep disorders combined., Discussion: The findings are consistent with other studies indicating that sleep disruption is a cancer risk factor. Optimal sleep and appropriate sleep disorder management are modifiable risk factors that may facilitate cancer prevention., Competing Interests: Author AD is currently employed by Palmetto GBA, LLC. When the study was conducted, she was employed by the University of South Carolina. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Burch, Delage, Zhang, McLain, Ray, Miller, Adams and Hébert.)

Purpose: To determine 24-hour physical activity (PA) clusters in children 6-36 months of age, factors associated with the clusters, and their agreement across time., Method: A longitudinal study followed 150 infants from South Carolina up to 36 months of age. Measures included 24-hour PA and demographic data. Functional clustering was used to obtain the clusters. The association between cluster membership and infant/parent characteristics was examined by Kruskal-Wallis and chi-squared tests. Concordance was measured with the kappa coefficient and percent agreement., Results: At each follow-up, 3 clusters were optimal, identified as late activity (cluster 1), high activity (cluster 2), and medium activity (cluster 3). The defining feature of the late activity cluster was that their physical activity (PA) activity was shifted to later in the day versus children in clusters 2 and 3. At 6 months, the clusters were associated with race (<0.001), crawling (0.043), other children in the household (0.043), and mother's education (0.004); at 12 months with race (0.029), childcare (<0.001), and education (<0.001); and at 36 months with other children in the household (0.019). Clusters showed moderate agreement (kappa = .41 [.25 to .57], agreement = 61% [49% to 72%]) between 6 and 12 months and, at 36 months, showed no agreement with either 6 or 12 months., Conclusion: Twenty-four-hour PA can be clustered into medium, high, and late PA. Further research is needed into the consequences of late sleeping in children at this age. Clusters are associated with household and childcare factors, and cluster membership is dynamic across time.

Background: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are two of the most common neurodevelopmental disorders with comorbidity rates of up to 70%. Population-based studies show differential rates of ADHD and ASD diagnosis based on sociodemographic variables. However, no studies to date have examined the role of sociodemographic factors on the likelihood of receiving an ADHD, ASD, or comorbid ASD + ADHD diagnosis in a large, nationally representative sample., Objective: This study aims to examine the impact of sociodemographic factors on the odds of experiencing ASD-only, ADHD-only, or both diagnoses for children in the United States., Methods: Using a mixed effects multinomial logistic modeling approach and data from the 2016-2018 National Survey of Children's Health, we estimated the association between sociodemographic variables and the log odds of being in each diagnostic group., Results: Sociodemographic variables were differentially related to the three diagnostic groups: ASD-only, ADHD-only, and ASD + ADHD. Compared to girls, boys experienced higher odds of all three diagnosis categories. White children had higher odds of having an ADHD-only or ASD + ADHD diagnosis compared to non-Hispanic (NH) Black, NH multiple/other race, and Hispanic children. Odds ratios for levels of parent education, household income, and birth characteristics showed varying trends across diagnostic groups., Conclusions: Overall, our findings point to unique sets of risk factors differentially associated ASD and ADHD, with lower income standing out as an important factor associated with receiving a diagnosis of ASD + ADHD., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The limited research assessing relationships between sleep duration and weight status in infants and toddlers relies primarily on parent-reported sleep and cross-sectional studies., Objectives: Examine whether average sleep duration and changes in sleep duration among 6-24-month-old children were associated with weight-for-length z-scores, and whether these associations varied by race/ethnicity, socioeconomic status and sex., Methods: Data were collected when children were approximately 6, 12, 18 and 24 months old (N = 116). Sleep duration was measured using actigraphy. Weight-for-length z-scores were calculated using children's height and weight. Physical activity was assessed using accelerometry. Diet was assessed using a feeding frequency questionnaire. Demographic characteristics included sex, race/ethnicity and socioeconomic status. Separate associations of between- and within-person changes in sleep duration were estimated with weight-for-length z-score treated as the outcome variable in linear mixed model analyses. Additional models were assessed that included interactions between sleep and demographic characteristics., Results: At time points where children slept longer at night compared to their own average, their weight-for-length z-score was lower. This relationship was attenuated by physical activity levels., Conclusions: Increasing sleep duration can improve weight status outcomes in very young children who have low physical activity levels., (© 2023 The Authors. Pediatric Obesity published by John Wiley & Sons Ltd on behalf of World Obesity Federation.)

Purpose: This study estimated associations between neighborhood socioeconomic status (NSES), walkability, green space, and incident falls among postmenopausal women and evaluated modifiers of these associations, including study arm, race and ethnicity, baseline household income, baseline walking, age at enrollment, baseline low physical functioning, baseline fall history, climate region, and urban-rural residence., Methods: The Women's Health Initiative recruited a national sample of postmenopausal women (50-79 years) across 40 U.S. clinical centers and conducted yearly assessments from 1993 to 2005 (n = 161,808). Women reporting a history of hip fracture or walking limitations were excluded, yielding a final sample of 157,583 participants. Falling was reported annually. NSES (income/wealth, education, occupation), walkability (population density, diversity of land cover, nearby high-traffic roadways), and green space (exposure to vegetation) were calculated annually and categorized into tertiles (low, intermediate, high). Generalized estimating equations assessed longitudinal relationships., Results: NSES was associated with falling before adjustment (high vs. low, odds ratio, 1.01; 95% confidence interval, 1.00-1.01). Walkability was significantly associated with falls after adjustment (high vs. low, odds ratio, 0.99; 95% confidence interval, 0.98-0.99). Green space was not associated with falling before or after adjustment. Study arm, race and ethnicity, household income, age, low physical functioning, fall history, and climate region modified the relationship between NSES and falling. Race and ethnicity, age, fall history, and climate region modified relationships between walkability and green space and falling., Conclusions: Our results did not show strong associations of NSES, walkability, or green space with falling. Future research should incorporate granular environmental measures that may directly relate to physical activity and outdoor engagement., (Copyright © 2023 Jacobs Institute of Women's Health, George Washington University. Published by Elsevier Inc. All rights reserved.)

Objectives: Preliminary studies play a key role in developing large-scale interventions but may be held to higher or lower scientific standards during the peer review process because of their preliminary study status., Study Design and Setting: Abstracts from 5 published obesity prevention preliminary studies were systematically modified to generate 16 variations of each abstract. Variations differed by 4 factors: sample size (n = 20 vs. n = 150), statistical significance (P < 0.05 vs. P > 0.05), study design (single group vs. randomized 2 groups), and preliminary study status (presence/absence of pilot language). Using an online survey, behavioral scientists were provided with a randomly selected variation of each of the 5 abstracts and blinded to the existence of other variations. Respondents rated each abstract on aspects of study quality., Results: Behavioral scientists (n = 271, 79.7% female, median age 34 years) completed 1,355 abstract ratings. Preliminary study status was not associated with perceived study quality. Statistically significant effects were rated as more scientifically significant, rigorous, innovative, clearly written, warranted further testing, and had more meaningful results. Randomized designs were rated as more rigorous, innovative, and meaningful., Conclusion: Findings suggest reviewers place a greater value on statistically significant findings and randomized control design and may overlook other important study characteristics., Competing Interests: Declaration of Competing Interest The authors have no competing interests or conflicts of interest to declare., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Study Objectives: Poor sleep and autonomic dysregulation can both disrupt metabolic processes. This study examined the individual and combined effects of poor sleep and reduced heart rate variability (HRV) on metabolic syndrome among 966 participants in the Midlife in the United States II (MIDUS II) study., Methods: Self-reported sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI). HRV was acquired from 11-minute resting heart rate recordings. Spearman correlations, general linear regression, and logistic regression models were used to examine the study hypotheses., Results: Poor sleep quality was associated with metabolic syndrome when global PSQI scores were evaluated as a continuous (odds ratio [OR]: 1.07, 95% confidence interval [CI]: 1.03 to 1.11) or categorical measure (cutoff > 5, OR: 1.58, 95% CI: 1.19 to 2.10), after adjustment for confounding. There also was an association between reduced HRV and metabolic syndrome (ln [HF-HRV] OR: 0.89, 95% CI: 0.80 to 0.99; ln [LF-HRV] OR: 0.82, 95% CI: 0.72 to 0.92; ln [SDRR] OR: 0.59, 95% CI: 0.43 to 0.79; ln [RMSSD] OR: 0.75, 95% CI: 0.60 to 0.94). When the combined effects of poor sleep and low HRV were examined, the association with metabolic syndrome was further strengthened relative to those with normal sleep and HRV., Conclusions: To the best of the author's knowledge, this is the first study to suggest a combined effect of poor sleep and low HRV on the odds of metabolic syndrome., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Purpose: Attention-deficit/hyperactivity disorder (ADHD) is a common childhood disorder often characterized by long-term impairments in family, academic, and social settings. Measuring the prevalence of ADHD is important as treatment options increase around the U.S. Prevalence data helps inform decisions by care providers, policymakers, and public health officials about allocating resources for ADHD. In addition, measuring geographic variation in prevalence estimates can facilitate hypothesis generation for future analytic work. Most U.S. studies of ADHD prevalence among children focus on national or demographic group rates., Methods: Using a small area estimation approach and data from the 2016 to 2018 National Survey of Children's Health, we estimated childhood ADHD prevalence estimates at the census regional division, state, and county levels. The sample included approximately 70,000 children aged 5-17 years., Results: The national ADHD rate was estimated to be 12.9% (95% Confidence Interval: 11.5%, 14.4%). Counties in the West South Central, East South Central, New England, and South Atlantic divisions had higher estimated rates of childhood ADHD (55.1%, 53.6%, 49.3%, and 46.2% of the counties had rates of 16% or greater, respectively) compared to counties in the Mountain, Mid Atlantic, West North Central, Pacific, and East North Central divisions (2.1%, 4%, 5.8%, 6.9%, and 11.7% of the counties had rates of 16% or greater, respectively)., Conclusions: These local-level rates are useful for decision-makers to target programs and direct sufficient ADHD resources based on communities' needs., (Copyright © 2023 Elsevier Inc. All rights reserved.)

(1) Background: Sleep, a physiological necessity, has strong inflammatory underpinnings. Diet is a strong moderator of systemic inflammation. This study explored the associations between the Dietary Inflammatory Index (DII®) and sleep duration, timing, and quality from the Energy Balance Study (EBS). (2) Methods: The EBS (n = 427) prospectively explored energy intake, expenditure, and body composition. Sleep was measured using BodyMedia’s SenseWear® armband. DII scores were calculated from three unannounced dietary recalls (baseline, 1-, 2-, and 3-years). The DII was analyzed continuously and categorically (very anti-, moderately anti-, neutral, and pro-inflammatory). Linear mixed-effects models estimated the DII score impact on sleep parameters. (3) Results: Compared with the very anti-inflammatory category, the pro-inflammatory category was more likely to be female (58% vs. 39%, p = 0.02) and African American (27% vs. 3%, p < 0.01). For every one-unit increase in the change in DII score (i.e., diets became more pro-inflammatory), wake-after-sleep-onset (WASO) increased (βChange = 1.00, p = 0.01), sleep efficiency decreased (βChange = −0.16, p < 0.05), and bedtime (βChange = 1.86, p = 0.04) and waketime became later (βChange = 1.90, p < 0.05). Associations between bedtime and the DII were stronger among African Americans (βChange = 6.05, p < 0.01) than European Americans (βChange = 0.52, p = 0.64). (4) Conclusions: Future studies should address worsening sleep quality from inflammatory diets, leading to negative health outcomes, and explore potential demographic differences.

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) to purchase. In this work, we develop a Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered (SIHVR) model to predict the burden of COVID-19 at the healthcare system level. The Bayesian SIHVR model provides daily estimates of the number of new COVID-19 patients admitted to inpatient care, the total number of non-ventilated COVID-19 inpatients, and the total number of ventilated COVID-19 patients at the healthcare system level. The model also incorporates county-level data on the number of reported COVID-19 cases, and county-level social distancing metrics, making it locally customizable. The uncertainty in model predictions is quantified with 95% credible intervals. The Bayesian SIHVR model is validated with an extensive simulation study, and then applied to data from two regional healthcare systems in South Carolina. This model can be adapted for other healthcare systems to estimate local resource needs., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Self et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Study Objectives: Sleep disturbances, which can worsen during pregnancy, have been linked to inflammatory processes. This study tested the hypothesis that more pro-inflammatory diets during pregnancy are associated with a decrease in sleep quality and shorter sleep duration., Methods: The Health in Pregnancy and Postpartum study promoted a healthy lifestyle in pregnant women with pre-pregnancy overweight or obesity (n = 207). Data from <16 weeks and 32 weeks gestation were used. Sleep was measured using BodyMedia's SenseWear® armband. Diet was assessed using two 24-hr dietary recalls. Energy-density Dietary Inflammatory Index (E-DIITM) scores were calculated from micro and macronutrients. Linear mixed-effects models estimated the impact of the E-DII score on sleep parameters., Results: Women with more pro-inflammatory diets, compared to those with more anti-inflammatory diets, were more likely to be nulliparous (51% vs. 25%, p = 0.03), frequent consumers of fast food (29% vs. 10% consuming on 4-6 days during the previous week, p = 0.01), ever-smokers (21% vs. 6%, p = 0.02), and younger (mean age 29.2 vs. 31.3 years, p = 0.02). For every one-unit increase (i.e., more pro-inflammatory) in the E-DII score, sleep latency increased by 0.69 min (p < 0.01). Among European Americans only, every one-unit higher E-DII was associated with a 2.92-min longer wake-after-sleep-onset (p = 0.02)., Conclusion: An E-DII score that is 5 points lower (i.e., more anti-inflammatory) would equate to about 105 min of additional sleep per week among European American women. Anti-inflammatory diets may help to counteract detriments in sleep during pregnancy, especially among European American women. Additional work is needed among African American women., Clinical Trials Identifier: Name: Promoting Health in Pregnancy and Postpartum (HIPP); URL: https://clinicaltrials.gov/ct2/show/NCT02260518; Registration Identifier: NCT02260518., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Whole-exome sequencing (WES) enables the detection of copy number variants (CNVs) with high resolution in protein-coding regions. However, variants in the intergenic or intragenic regions are excluded from studies. Fortunately, many of these samples have been previously sequenced by other genotyping platforms which are sparse but cover a wide range of genomic regions, such as SNP array. Moreover, conventional single sample-based methods suffer from a high false discovery rate due to prominent data noise. Therefore, methods for integrating multiple genotyping platforms and multiple samples are highly demanded for improved copy number variant detection. We developed BMI-CNV, a Bayesian Multisample and Integrative CNV (BMI-CNV) profiling method with data sequenced by both whole-exome sequencing and microarray. For the multisample integration, we identify the shared copy number variants regions across samples using a Bayesian probit stick-breaking process model coupled with a Gaussian Mixture model estimation. With extensive simulations, BMI-copy number variant outperformed existing methods with improved accuracy. In the matched data from the 1000 Genomes Project and HapMap project data, BMI-CNV also accurately detected common variants and significantly enlarged the detection spectrum of whole-exome sequencing. Further application to the data from The Research of International Cancer of Lung consortium (TRICL) identified lung cancer risk variant candidates in 17q11.2, 1p36.12, 8q23.1, and 5q22.2 regions., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Prolonged periods of social isolation are known to have significant negative health consequences and reduce quality of life, an effect that is particularly pronounced in older populations. Despite the known deleterious effects of social isolation, a key component of the response to the COVID-19 pandemic has been the issuance of stay at home and/or shelter in place orders. Relatively little is known about the potential effects these periods of social isolation could have on older adults, and less still is known about potential risk factors or protective factors that modulate these effects. Here, we describe results from a longitudinal study in which we measured quality of life both prior to and immediately following a one-month period of social isolation associated with the issuance and revocation of a shelter in place order (April 6, 2020 through May 4, 2020) in the state of South Carolina. Healthy adult participants (N = 62) between the ages of 60 and 80 who had already completed quality of life questionnaires prior to isolation again completed the questionnaires following a one-month order to shelter in place. Quality of life significantly decreased during the social isolation period, with older participants showing the greatest declines. Participants with higher levels of physical activity and better physical/mental health going into the isolation period tended to show greater decreases in quality of life over time. These results highlight the negative consequences of even short bouts of social isolation for the elderly and suggest that reductions in social contact related to COVID-19 may have significant effects on mental health and emotional well-being, at least among older individuals., Competing Interests: The authors have declared that no competing interests exist.

Background: To describe objectively measured physical activity (PA) in infants, and to identify demographic, behavioral, and environmental factors associated with infants' PA. Methods: Participants were 6-7-month-old infants and their mothers ( N  = 143 dyads) from two Southeastern US counties. Infant measures included PA assessed by accelerometers at ankle and waist sites, motor developmental status ( i.e. , stationary and locomotion), and anthropometric characteristics ( i.e. , height and weight). Mothers provided information on home environment, child care settings, and family demographic factors. PA levels were compared across demographic subgroups. Correlation coefficients described associations between PA and continuous variables, including motor developmental status and anthropometric characteristics. Multiple linear regression analyses examined factors found to be independently associated with PA. Results: Infants' PA counts were greater at the ankle (77,700 counts/hr) vs. the waist site (32,500 counts/hr). In univariate analyses, a diverse set of environmental, behavioral, and infant-level demographic factors were found to be significantly associated with PA at the ankle site. Multivariate analyses indicated that more advanced motor development status ( B  = 666.3 ± 329.8, p  < 0.05), attendance at home child care settings ( B  = -13,724.4 ± 5083.9, p  < 0.05), greater exposure to tummy time ( B  = 213.5 ± 79.9, p  < 0.05), and white racial/ethnic composition ( B  = -19,953.4 ± 5888.5, p  < 0.01) were independently, associated with infants' PA. Conclusions: In 6-7-month-old infants, objectively measured PA was found to be associated with motor developmental status and physical and social environmental factors, including both demographic moderators and factors that are influenced by parents and caregivers. Longitudinal studies are needed to determine if these relationships persist or change as infants develop.

Background: The Global Burden of Disease (GBD) Study provides estimates of death and disability from eighty-seven risk factors, including some micronutrient deficiencies., Objectives: To review methodological changes that led to large differences in the disease burden estimates for vitamin A and Zn deficiencies between the GBD 2017 and 2019 Studies., Methods: GBD publications were reviewed; additional information was provided by GBD researchers., Results: Vitamin A deficiency prevalence is based on plasma retinol concentration, whereas the estimate for Zn deficiency prevalence uses dietary adequacy as a proxy. The estimated global prevalence of vitamin A deficiency for children aged 1-4 years in the year 2017 decreased from 0·20 (95 % CI 0·17, 0·24) in GBD 2017 to 0·16 (95 % CI 0·15, 0·19) in GBD 2019, while the global prevalence of Zn deficiency did not change between the two studies (0·09 (95 % CI 0·04, 0·17) and 0·09 (95 % CI 0·03, 0·18)). New to 2019 was that meta-analyses were performed using Meta Regression - Bayesian, Regularized, Trimmed, a method developed for GBD. Due to this and multiple other methodological changes, the estimated number of deaths due to vitamin A deficiency dropped from 233 000 (179 000-294 000) to 24 000 (3000-50 000) from GBD 2017 to 2019, and for Zn deficiency from 29 000 (1000-77 000) to 2800 (700-6500), respectively., Conclusion: The changes in the estimated disease burdens due to vitamin A and Zn deficiencies in the GBD reports from 2017 to 2019 are due primarily to changes in the analytical methods employed, so may not represent true changes in disease burden. Additional effort is needed to validate these results.

Police officers experience exposures associated with increased inflammation, such as the stress associated with shiftwork and poor-quality diet, both of which have been shown to affect sleep duration and quality. This study examined the longitudinal and cross-sectional effects of the Energy-density Dietary Inflammatory Index (E-DII™) on objectively and subjectively measured sleep among police officers. Data were derived from the Buffalo Cardio-Metabolic Occupational Police Stress Cohort (n = 464 at baseline), with longitudinal data collected from 2004 to 2019. A food frequency questionnaire obtained estimated dietary intake from which E-DII scores were calculated. Dependent variables were objectively (Micro Motion Logger Sleep Watch™) and subjectively (Pittsburgh Sleep Quality Index) measured sleep quality and quantity. The analyses included a series of linear mixed-effects models used to examine cross-sectional and longitudinal associations between the E-DII and sleep quantity and quality. Cross-sectionally, more pro-inflammatory diets were associated with higher wake-after-sleep-onset but improved subjective sleep quality. In models accounting for both longitudinal and cross-sectional effects, for every 1-unit increase in the E-DII scores over time (representing a pro-inflammatory change), wake-after-sleep-onset increased by nearly 1.4 min (p = 0.07). This result was driven by officers who primarily worked day shifts (β = 3.33, p = 0.01). Conversely, for every 1-unit increase in E-DII score, the Pittsburgh Sleep Quality Index global score improved. More pro-inflammatory diets were associated with increased wake-after-sleep-onset, an objective measure of sleep quality. Intervention studies to reduce dietary inflammatory potential may provide greater magnitude of effect for changes in sleep quality., (© 2021 European Sleep Research Society.)

Background: Monitoring countries' progress toward the achievement of their nutrition targets is an important task, but data sparsity makes monitoring trends challenging. Childhood stunting and overweight data in the European region over the last 30 y have had low coverage and frequency, with most data only covering a portion of the complete age interval of 0-59 mo., Objectives: We implemented a statistical method to extract useful information on child malnutrition trends from sparse longitudinal data for these indicators., Methods: Heteroscedastic penalized longitudinal mixed models were used to accommodate data sparsity and predict region-wide, country-level trends over time. We leveraged prevalence estimates stratified by sex and partial age intervals (i.e., intervals that do not cover the complete 0-59 mo), which expanded the available data (for stunting: from 84 sources and 428 prevalence estimates to 99 sources and 1786 estimates), improving the robustness of our analysis., Results: Results indicated a generally decreasing trend in stunting and a stable, slightly diminishing rate for overweight, with large differences in trends between low- and middle-income countries compared with high-income countries. No differences were found between age groups and between sexes. Cross-validation results indicated that both stunting and overweight models were robust in estimating the indicators for our data (root mean squared error: 0.061 and 0.056; median absolute deviation: 0.045 and 0.042; for stunting and overweight, respectively)., Conclusions: These statistical methods can provide useful and robust information on child malnutrition trends over time, even when data are sparse., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.)