Comparison of the characteristics of the population eligible for lung cancer screening under 2013 and population newly eligible under 2021 US Preventive Services Task Force recommendations.

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.

Geographic Disparities in Availability of General and Specialized Pediatricians in the US and Prevalence of Childhood Neurodevelopmental Disorders.

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).

Clustering Patterns of 24-Hour Physical Activity in Children 6-36 Months Old.

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.

Functional Multivariable Logistic Regression With an Application to HIV Viral Suppression Prediction.

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.

Estimating Childhood Stunting and Overweight Trends in the European Region from Sparse Longitudinal Data.

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.

Longitudinal and cross-sectional associations between the dietary inflammatory index and objectively and subjectively measured sleep among police officers.

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 (ß = 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.

Estimates of Childhood Overweight and Obesity at the Region, State, and County Levels: A Multilevel Small-Area Estimation Approach.

Local-level childhood overweight and obesity data are often used to implement and evaluate community programs, as well as allocate resources to combat overweight and obesity. The most current substate estimates of US childhood obesity use data collected in 2007. Using a spatial multilevel model and the 2016 National Survey of Children's Health, we estimated childhood overweight and obesity prevalence rates at the Census regional division, state, and county levels using small-area estimation with poststratification. A sample of 24,162 children aged 10-17 years was used to estimate a national overweight and obesity rate of 30.7% (95% confidence interval: 27.0%, 34.9%). There was substantial county-to-county variability (range, 7.0% to 80.9%), with 31 out of 3,143 counties having an overweight and obesity rate significantly different from the national rate. Estimates from counties located in the Pacific region had higher uncertainty than other regions, driven by a higher proportion of underrepresented sociodemographic groups. Child-level overweight and obesity was related to race/ethnicity, sex, parental highest education (P < 0.01 for all), county-level walkability (P = 0.03), and urban/rural designation (P = 0.02). Overweight and obesity remains a vital issue for US youth, with substantial area-level variability. The additional uncertainty for underrepresented groups shows surveys need to better target diverse samples.

Trends in time-to-pregnancy in the USA: 2002 to 2017.

STUDY QUESTION: Has there been there a temporal change in time-to-pregnancy (TTP) in the USA. SUMMARY ANSWER: Overall, TTP was stable over time, but a longer TTP for women over 30 and parous women was identified. WHAT IS KNOWN ALREADY: Fertility rates in the USA have declined over the past several years. Although these trends have been attributed to changing reproductive intentions, it is unclear whether declining fecundity (the biologic ability to reproduce measured by TTP in the current report) may also play a role. Indeed, trends based on declining sperm quality and higher utilisation of infertility treatment suggest fecundity may be falling. STUDY DESIGN, SIZE, DURATION: This cross-sectional survey data from the National Survey of Family Growth was administered from 2002 to 2017. The surveys are based on nationally representative samples of reproductive-aged women in the USA. Interviews were conducted in person or through computer-assisted self-administration of sensitive questions. PARTICIPANTS/MATERIALS, SETTING, METHODS: The study included women who self-reported time spent trying to become pregnant allowing utilisation of the current duration approach to estimate the total duration of pregnancy attempt (i.e. TTP). In all, 1202 participants were analysed over each study period. To estimate a TTP distribution overall and by parity, we used a piecewise constant proportional hazards model that accounts for digit preference. Accelerated-failure-time regression models, which were weighted to account for the sampling design, were used to estimate time ratios (TRs). Models were adjusted for age, BMI, race, education, relationship status, parity, pelvic inflammatory disease treatment and any reproductive problems. MAIN RESULTS AND THE ROLE OF CHANCE: Of the participants analysed, the average age was 31.8 and BMI was 28.6, which was similar across the survey periods. Relationship status was the only demographic characteristic that changed over time. All other variables remained constant across the study periods. Overall, TRs comparing TTP between 2002 and 2017 increased slightly (TR: 1.02, 95% CI: 0.99, 1.04). When stratified by parity, parous women had a longer TTP over the later years of the study (TR: 1.04, 95% CI: 1.01, 1.06). TTP remained constant for nulliparous women. Similarly, TTP also increased over time for women over age thirty (TR: 1.02, 1.00, 1.05) but not for women under age thirty. LIMITATIONS, REASONS FOR CAUTION: Small changes in data collection over time may have impacted the findings. We accounted for this in sensitivity analyses using imputed data. Overall, TRs were slightly attenuated using the imputed data, but represented similar patterns to the original data. Results for parous women and women over 30 remained consistent in the sensitivity analyses. WIDER IMPLICATIONS OF THE FINDINGS: Consistent with reports of falling fertility rates and sperm counts, this study suggests parous and older couples in the USA may be taking longer to become pregnant. Although trends were suggestive of a small overall increase in TTP, particularly for parous women and women over age thirty, additional data are needed to attempt to understand these trends given the societal, economic and public health implications related to fecundity. STUDY FUNDING/COMPETING INTEREST(S): Funding was provided by National Institutes of Health grant R03HD097287 to A.C.M. There are no competing interests. TRIAL REGISTRATION NUMBER: N/A.

Incongruency of youth food and physical activity environments in the United States: Variations by region, rurality, and income.

Local environments are increasingly the focus of health behavior research and practice to reduce gaps between fruit/vegetable intake, physical activity (PA), and related guidelines. This study examined the congruency between youth food and PA environments and differences by region, rurality, and income across the United States. Food and PA environment data were obtained for all U.S. counties (N = 3142) using publicly available, secondary sources. Relationships between the food and PA environment tertiles was represented using five categories: 1) congruent-low (county falls in both the low food and PA tertiles), 2) congruent-high (county falls in both the high food and PA tertiles), 3) incongruent-food high/PA low (county falls in high food and low PA tertiles), 4) incongruent-food low/PA high (county falls in low food and high PA tertiles), and 5) intermediate food or PA (county falls in the intermediate tertile for food and/or PA). Results showed disparities in food and PA environment congruency according to region, rurality, and income (p < .0001 for each). Nearly 25% of counties had incongruent food and PA environments, with food high/PA low counties mostly in rural and low-income areas, and food low/PA high counties mostly in metropolitan and high-income areas. Approximately 8.7% of counties were considered congruent-high and were mostly located in the Northeast, metropolitan, and high-income areas. Congruent-low counties made up 10.0% of counties and were mostly in the South, rural, and low-income areas. National and regional disparities in environmental obesity determinants were identified that can inform targeted public health interventions.

Gestational weight gain disparities in South Carolina: Temporal trends, 2004-2015.

BACKGROUND: Few studies have examined secular trends in gestational weight gain (GWG) and findings are inconsistent. Parallel to increasing trends in pre-pregnancy obesity, we hypothesised similar increasing GWG trends. OBJECTIVES: The study examined trends in GWG in South Carolina (SC), using methods to reduce bias. We also examined whether the 12-year trends in GWG varied according to race/ethnicity and pre-pregnancy weight. METHODS: Data came from SC birth certificates, 2004 to 2015. We calculated standardised GWG z-scores (GWGZ), using smoothed reference values to account for gestational age and pre-pregnancy body mass index. Quantile regression was used to examine trends in GWGZ, adjusting for pre-pregnancy weight status, race/ethnicity, parity, WIC participation, smoking during pregnancy, residence, age, and birth cohort. RESULTS: Among 615 093 women, the mean GWGZ was -0.4 (SD = 1.3), which increased from -0.4 in 2004-2005 to -0.2 in 2014-2015. GWGZ increased at the 5th, 10th, 25th, 50th, and 75th percentiles (ranging 0.04 to 0.73 units), with differential trends observed in sub-groups by pre-pregnancy weight and racial/ethnic group. Notably, non-Hispanic White women showed larger increasing trends (0.89 units) compared to non-Hispanic Black (0.55 units) and Hispanic (0.76 units) women in the 5th percentile. Decreasing trends were seen overall for the 90th (-0.02) and 95th percentile (-0.06 units) but positive trends were not seen among women experiencing obese class 1 (no change in 90th and 95th), and 2 (0.01 units in 90th, -0.02 units in 95th). CONCLUSIONS: This study shows increasing GWGZ trends from the 5th to the 75th percentiles and decreasing trends in 90th and 95th percentiles in SC for the last decade. Racial/ethnic and pre-pregnancy weight disparities did not improve over the study period. Future research is needed to confirm these findings in other states and to develop strategies to narrow racial and pre-pregnancy weight disparities at the highest and lowest percentiles.

Basis for changes in the disease burden estimates related to vitamin A and zinc deficiencies in the 2017 and 2019 Global Burden of Disease Studies.

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.

Spatial clustering patterns and regional variations for food and physical activity environments across the United States.

This study examined spatial patterns of obesogenic environments for US counties. We mapped the geographic dispersion of food and physical activity (PA) environments, assessed spatial clustering, and identified food and PA environment differences across U.S. regions and rurality categories. Substantial low food score clusters were located in the South and high score clusters in the Midwest and West. Low PA score clusters were located in the South and high score clusters in the Northeast and Midwest (p < .0001). For region, the South had significantly lower food and PA environment scores. For rurality, rural counties had significantly higher food environment scores and metropolitan counties had significantly higher PA environment scores (p < .0001). This study highlights geographic clustering and disparities in food and PA access nationwide. State and region-wide environmental inequalities may be targeted using structural interventions and policy initiatives to improve food and PA access.

Development of a national childhood obesogenic environment index in the United States: differences by region and rurality.

BACKGROUND: Diverse environmental factors are associated with physical activity (PA) and healthy eating (HE) among youth. However, no study has created a comprehensive obesogenic environment index for children that can be applied at a large geographic scale. The purpose of this study was to describe the development of a childhood obesogenic environment index (COEI) at the county level across the United States. METHODS: A comprehensive search of review articles (n = 20) and input from experts (n = 12) were used to identify community-level variables associated with youth PA, HE, or overweight/obesity for potential inclusion in the index. Based on strength of associations in the literature, expert ratings, expertise of team members, and data source availability, 10 key variables were identified - six related to HE (# per 1000 residents for grocery/superstores, farmers markets, fast food restaurants, full-service restaurants, and convenience stores; as well as percentage of births at baby (breastfeeding)-friendly facilities) and four related to PA (percentage of population living close to exercise opportunities, percentage of population < 1 mile from a school, a composite walkability index, and number of violent crimes per 1000 residents). Data for each variable for all counties in the U.S. (n = 3142) were collected from publicly available sources. For each variable, all counties were ranked and assigned percentiles ranging from 0 to 100. Positive environmental variables (e.g., grocery stores, exercise opportunities) were reverse scored such that higher values for all variables indicated a more obesogenic environment. Finally, for each county, a total obesogenic environment index score was generated by calculating the average percentile for all 10 variables. RESULTS: The average COEI percentile ranged from 24.5-81.0 (M = 50.02,s.d. = 9.01) across US counties and was depicted spatially on a choropleth map. Obesogenic counties were more prevalent (F = 130.43,p < .0001) in the South region of the U.S. (M = 53.0,s.d. = 8.3) compared to the Northeast (M = 43.2,s.d. = 6.9), Midwest (M = 48.1,s.d. = 8.5), and West (M = 48.4,s.d. = 9.8). When examined by rurality, there were also significant differences (F = 175.86,p < .0001) between metropolitan (M = 46.5,s.d. = 8.4), micropolitan (M = 50.3,s.d. = 8.1), and rural counties (M = 52.9,s.d. = 8.8) across the U.S. CONCLUSION: The COEI can be applied to benchmark obesogenic environments and identify geographic disparities and intervention targets. Future research can examine associations with obesity and other health outcomes.

Linking Activity, Nutrition, and Child Health (LAUNCH): protocol for a longitudinal cohort study of children as they develop from infancy to preschool age.

BACKGROUND: Physical activity is known to provide important health benefits in children ages 3 years and above, but little is known about the effects of physical activity on health in very young children under age 3. LAUNCH (Linking Activity, Nutrition, and Child Health) is a study designed to expand the body of knowledge on development of physical activity behavior and associations between physical activity and other health characteristics as children transition from infancy to preschool age. METHODS: Physical activity and sedentary behavior will be measured objectively in young children over a period of 30 months. Each child will complete a measurement protocol at 6, 12, 18, 24, 30 and 36 months of age. The following factors will be measured at each time point: physical activity, sedentary behavior, anthropometric characteristics, and motor developmental status. Objectively-measured sleep behavior will be included as an optional component of the protocol. Parents will provide information on demographic factors, parenting behaviors, home and childcare characteristics, and the child's dietary and sleep behaviors. DISCUSSION: LAUNCH will employ a longitudinal study design and objective measures of physical activity, sedentary behavior and sleep in examining developmental trends for those characteristics in children between the ages of 6 and 36 months. Associations among physical activity, sedentary behavior, sleep, and weight status will be examined. Findings will inform public health guidance and intervention strategies for very young children.

Multiple processes independently predict motor learning.

BACKGROUND: Our ability to acquire, refine and adapt skilled limb movements is a hallmark of human motor learning that allows us to successfully perform many daily activities. The capacity to acquire, refine and adapt other features of motor performance, such as visual search, eye-hand coordination and visuomotor decisions, may also contribute to motor learning. However, the extent to which refinements of multiple behavioral features and their underlying neural processes independently contribute to motor learning remains unknown. In the current study, we used an ethological approach to test the hypothesis that practice-related refinements of multiple behavioral features would be independently predictive of motor learning. METHODS: Eighteen healthy, young adults used an upper-limb robot with eye-tracking to practice six trials of a continuous, visuomotor task once a week for six consecutive weeks. Participants used virtual paddles to hit away 200 "Targets" and avoid hitting 100 "Distractors" that continuously moved towards them from the back of the workspace. Motor learning was inferred from trial-by-trial acquisition and week-by-week retention of improvements on two measures of task performance related to motor execution and motor inhibition. Adaptations involving underlying neural processes were inferred from trial-by-trial acquisition and week-by-week retention of refinements on measures of skilled limb movement, visual search, eye-hand coordination and visuomotor decisions. We tested our hypothesis by quantifying the extent to which refinements on measures of multiple behavioral features (predictors) were independently predictive of improvements on our two measures of task performance (outcomes) after removing all shared variance between predictors. RESULTS: We found that refinements on measures of skilled limb movement, visual search and eye-hand coordination were independently predictive of improvements on our measure of task performance related to motor execution. In contrast, only refinements of eye-hand coordination were independently predictive of improvements on our measure of task performance related to motor inhibition. CONCLUSION: Our results provide indirect evidence that refinements involving multiple, neural processes may independently contribute to motor learning, and distinct neural processes may underlie improvements in task performance related to motor execution and motor inhibition. This also suggests that refinements involving multiple, neural processes may contribute to motor recovery after stroke, and rehabilitation interventions should be designed to produce refinements of all behavioral features that may contribute to motor recovery.

Symptom Management Among Cancer Survivors: Randomized Pilot Intervention Trial of Heart Rate Variability Biofeedback.

Chronic cancer-related symptoms (stress, fatigue, pain, depression, insomnia) may be linked with sympathetic nervous system over-activation and autonomic imbalance. Decreased heart rate variability (HRV) is an indicator of autonomic dysregulation that is commonly observed among cancer survivors. HRV biofeedback (HRVB) training induces HRV coherence, which maximizes HRV and facilitates autonomic and cardiorespiratory homeostasis. This randomized, wait-list-controlled, pilot intervention trial tested the hypothesis that HRVB can improve HRV coherence and alleviate cancer-related symptoms. The intervention group (n = 17) received 4-6 weekly HRVB training sessions until participants demonstrated skill acquisition. Controls (n = 17) received usual care. Outcomes assessed at baseline and follow-up included 15-min HRV recordings (HRV Coherence Ratio), and symptoms of: stress, distress, post-traumatic stress disorder (PTSD), pain, depression, fatigue, and sleep disturbance. Linear mixed models for repeated measures were used to assess Group-by-Time interactions, pre- versus post-treatment differences in mean symptom scores, and group differences at follow-up. Mean HRV Coherence Ratios (± standard error) improved in the HRVB group at follow-up (baseline: 0.37 ± 0.05, post-intervention: 0.84 ± 0.18, p = 0.01), indicating intervention validity. Statistically significant Group-by-Time interactions indicated treatment-related improvements in HRV Coherence Ratios (p = 0.03, Pre-vs. post-treatment effect size [Cohen's d]: 0.98), sleep symptoms (p = 0.001, d = 1.19), and sleep-related daytime impairment (p = 0.005, d = 0.86). Relative to controls, the intervention group experienced trends toward improvements in stress, distress, fatigue, PTSD, and depression, although no other statistically significant Group-by-Time interactions were observed. This pilot intervention found that HRVB training reduced symptoms of sleep disturbance among cancer survivors. Larger-scale interventions are warranted to further evaluate the role of HRVB for managing symptoms in this population. Registration: NCT03692624 www.clinicaltrials.gov.

Wheeze and Food Allergies in Children Born via Cesarean Delivery: The Upstate KIDS Study.

We examined whether cesarean delivery (CD) increased the risk of wheeze or food allergy in early childhood compared with vaginal delivery and whether these associations were mediated by breastfeeding. The study population was the Upstate KIDS cohort (2008-2010) of mothers and infants from the State of New York (excluding New York City). Infant's wheeze was reported by questionnaire every 4-6 months until 3 years of age, as were food allergies beginning at 8 months. Modified Poisson regression was used to compare risks of the outcomes according to mode of delivery (MOD). Potential confounders were identified a priori using directed acyclic graphs. Emergency CD (n = 1,356) was associated with elevated risk of wheeze, adjusting for pregnancy complications, maternal atopy, gestational age, birth weight, and smoking during pregnancy (risk ratio = 2.47, 95% confidence interval: 1.31, 4.66), and an increased risk of food allergy, adjusting for maternal atopy, prepregnancy body mass index, smoking during pregnancy, and parity (risk ratio = 3.02, 95% confidence interval: 1.26, 7.25). Neither outcome was significantly associated with planned CD (n = 1,565 infants). Breastfeeding mediated the association between MOD and wheeze but not food allergy. Other factors not associated with early-life microbial transfer, but relating to the development of the outcomes, might contribute to the association between MOD and wheeze/food allergy.

A varying-coefficient generalized odds rate model with time-varying exposure: An application to fitness and cardiovascular disease mortality.

Varying-coefficient models have become a common tool to determine whether and how the association between an exposure and an outcome changes over a continuous measure. These models are complicated when the exposure itself is time-varying and subjected to measurement error. For example, it is well known that longitudinal physical fitness has an impact on cardiovascular disease (CVD) mortality. It is not known, however, how the effect of longitudinal physical fitness on CVD mortality varies with age. In this paper, we propose a varying-coefficient generalized odds rate model that allows flexible estimation of age-modified effects of longitudinal physical fitness on CVD mortality. In our model, the longitudinal physical fitness is measured with error and modeled using a mixed-effects model, and its associated age-varying coefficient function is represented by cubic B-splines. An expectation-maximization algorithm is developed to estimate the parameters in the joint models of longitudinal physical fitness and CVD mortality. A modified pseudoadaptive Gaussian-Hermite quadrature method is adopted to compute the integrals with respect to random effects involved in the E-step. The performance of the proposed method is evaluated through extensive simulation studies and is further illustrated with an application to cohort data from the Aerobic Center Longitudinal Study.

Prediction intervals for penalized longitudinal models with multisource summary measures: An application to childhood malnutrition.

In many global health analyses, it is of interest to examine countries' progress using indicators of socio-economic conditions based on national surveys from varying sources. This results in longitudinal data where heteroscedastic summary measures, rather than individual level data, are available. Administration of national surveys can be sporadic, resulting in sparse data measurements for some countries. Furthermore, the trend of the indicators over time is usually nonlinear and varies by country. It is of interest to track the current level of indicators to determine if countries are meeting certain thresholds, such as those indicated in the United Nations Sustainable Development Goals. In addition, estimation of confidence and prediction intervals are vital to determine true changes in prevalence and where data is low in quantity and/or quality. In this article, we use heteroscedastic penalized longitudinal models with survey summary data to estimate yearly prevalence of malnutrition quantities. We develop and compare methods to estimate confidence and prediction intervals using asymptotic and parametric bootstrap techniques. The intervals can incorporate data from multiple sources or other general data-smoothing steps. The methods are applied to African countries in the UNICEF-WHO-The World Bank joint child malnutrition data set. The properties of the intervals are demonstrated through simulation studies and cross-validation of real data.

Personal network characteristics and body mass index: the role of education among Black Americans.

BACKGROUND: Personal (i.e. egocentric) network characteristics are associated with health outcomes, including overweight and obesity. Previous research suggests educational attainment may interact with network characteristics to buffer these relationships. Limited research has examined the personal network characteristics of Black Americans, who have increased risk of overweight and obesity. The purpose of the current study was to examine associations between network characteristics and body mass index (BMI), and whether educational attainment modified these associations among Black Americans. METHODS: In 2014, using respondent-driven sampling, we recruited 430 adult residents of eight low-income neighborhoods in Greenville, SC. Self-administered questionnaires assessed structural and compositional characteristics (i.e. size, density) of respondents' personal networks, socio-demographic characteristics, and health-related behaviors and conditions. Multilevel regression models with robust sandwich estimation accounted for clustering within respondent chains. RESULTS: Among Black adults overall, network density-the number of connections among network members-was positively associated with BMI. Higher education moderated this relationship; among Black adults with a college degree, higher network density was inversely associated with BMI. CONCLUSIONS: Our data suggest low educational attainment may reflect more homogenous and less resourceful networks. Multiple pathways are discussed for how education interacts with network density on BMI among Black Americans.