A Hypothesis Test for Detecting Spatial Patterns in Categorical Areal Data

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.

Identifying multilevel predictors of behavioral outcomes like park use: A comparison of conditional and marginal modeling approaches

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.

Sleep disorders and cancer incidence: examining duration and severity of diagnosis among veterans

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.

Are the Risk of Generalizability Biases Generalizable? A Meta-Epidemiological Study

Background Preliminary studies (e.g., pilot/feasibility studies) can result in misleading evidence that an intervention is ready to be evaluated in a large-scale trial when it is not. Risk of Generalizability Biases (RGBs, a set of external validity biases) represent study features that influence estimates of effectiveness, often inflating estimates in preliminary studies which are not replicated in larger-scale trials. While RGBs have been empirically established in interventions targeting obesity, the extent to which RGBs generalize to other health areas is unknown. Understanding the relevance of RGBs across health behavior intervention research can inform organized efforts to reduce their prevalence. Purpose The purpose of our study was to examine whether RGBs generalize outside of obesity-related interventions. Methods A systematic review identified health behavior interventions across four behaviors unrelated to obesity that follow a similar intervention development framework of preliminary studies informing larger-scale trials (i.e., tobacco use disorder, alcohol use disorder, interpersonal violence, and behaviors related to increased sexually transmitted infections). To be included, published interventions had to be tested in a preliminary study followed by testing in a larger trial (the two studies thus comprising a study pair). We extracted health-related outcomes and coded the presence/absence of RGBs. We used meta-regression models to estimate the impact of RGBs on the change in standardized mean difference (ΔSMD) between the preliminary study and larger trial. Results We identified sixty-nine study pairs, of which forty-seven were eligible for inclusion in the analysis (k = 156 effects), with RGBs identified for each behavior. For pairs where the RGB was present in the preliminary study but removed in the larger trial the treatment effect decreased by an average of ΔSMD=-0.38 (range - 0.69 to -0.21). This provides evidence of larger drop in effectiveness for studies containing RGBs relative to study pairs with no RGBs present (treatment effect decreased by an average of ΔSMD =-0.24, range - 0.19 to -0.27). Conclusion RGBs may be associated with higher effect estimates across diverse areas of health intervention research. These findings suggest commonalities shared across health behavior intervention fields may facilitate introduction of RGBs within preliminary studies, rather than RGBs being isolated to a single health behavior field.

Trends in maternal opioid use: Statewide differences by sociodemographic characteristics in Florida from 2000 to 2019

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.

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.

Longitudinal associations between sleep and weight status in infants and toddlers

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.

Factors Associated with Children's Physical Activity During Youth Soccer Practices

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.

Neighborhood Socioeconomic Status, Green Space, and Walkability and Risk for Falls Among Postmenopausal Women: The Women's Health Initiative

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.

Scientists' perception of pilot study quality was influenced by statistical significance and study design

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.

The role of sleep and heart rate variability in metabolic syndrome: evidence from the Midlife in the United States study

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.

County-Level Prevalence Estimates of Autism Spectrum Disorder in Children in the United States

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.

County-level prevalence estimates of ADHD in children in the United States

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.

Associations between the Dietary Inflammatory Index and Sleep Metrics in the Energy Balance Study (EBS)

(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.

A Bayesian susceptible-infectious-hospitalized-ventilated-recovered model to predict demand for COVID-19 inpatient care in a large healthcare system

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.

Dietary Inflammatory Index and sleep quality and duration among pregnant women with overweight or obesity

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.

Effects of social isolation on quality of life in elderly adults

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.

Behavioral, Environmental, and Demographic Factors Associated with Objectively Measured Physical Activity in Infants

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.

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 (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.

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.

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.

Challenges for Estimating the Global Prevalence of Micronutrient Deficiencies and Related Disease Burden: A Case Study of the Global Burden of Disease Study

Information on the prevalence of micronutrient deficiencies is needed to determine related disease burden; underpin evidence-based advocacy; and design, deliver, and monitor safe, effective interventions. Assessing the global prevalence of deficiency requires a valid micronutrient status biomarker with an appropriate cutoff to define deficiency and relevant data from representative surveys across multiple locations and years. The Global Burden of Disease Study includes prevalence estimates for iodine, iron, zinc, and vitamin A deficiencies, for which recommended biomarkers and appropriate deficiency cutoffs exist. Because representative survey data are lacking, only retinol concentration is used to model vitamin A deficiency, and proxy indicators are used for the other micronutrients (goiter for iodine, hemoglobin for iron, and dietary food adequacy for zinc). Because of data limitations, complex statistical modeling is required to produce current estimates, relying on assumptions and proxies that likely understate the extent of micronutrient deficiencies and the consequent global health burden.

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.

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.

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.

Shift Work Adaptation Among Police Officers: The BCOPS Study

Few studies have examined shiftwork adaptation among police officers or potential differences in disease biomarkers among adapted and maladapted shiftworkers. This study characterized shiftwork adaptation among 430 police officers from the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study. Police officers working fixed night shifts with symptoms characteristic of adaptation and maladaptation were identified using latent class analysis (n = 242). Two approaches were applied, one with police-specific symptoms and another using more general symptoms as shiftwork adaptation indicators. Biomarkers of inflammation, heart rate variability, and cardiometabolic risk were then compared between shiftwork adaptation groups, and with officers working day shifts, after adjusting for confounding. When analyses included police-specific symptoms, maladapted shiftworkers (n = 73) had more self-reported stress, sleep disturbances, fatigue, and less social support than adapted shiftworkers (n = 169). Using more general symptoms, maladapted officers (n = 56) reported more stress and depression, and less social support than adapted officers (n = 186). In police-specific models, adjusted (least-squares) means (± standard error) of circulating interleukin-6 (IL-6) concentrations in maladapted officers (0.8 ± 0.1 ln[pg/ml]) were modestly elevated relative to adapted shiftworkers (0.7 ± 0.1 ln[pg/ml], p = .09) and relative to permanent day workers (0.5 ± 0.1 ln[pg/ml], p ≤ 0.01), and leptin levels in maladapted officers (9.6 ± 0.1 ln[pg/ml]) exceeded those in the adapted (9.4 ± 0.1 ln[pg/ml], p ≤ 0.01) and day shift groups (9.4 ± 0.1 ln[pg/ml], p = .03). In the general model, adjusted mean tumor necrosis factor-alpha (TNF-α) concentrations among maladapted officers (5.6 ± 0.23 pg/ml) exceeded the adapted (4.8 ± 0.2 pg/ml, p ≤ 0.01) and day workers (5.0 ± 0.2 pg/ml, p = .04), and insulin among maladapted officers was higher (2.4 ± 0.1 ln[uu/ml]) than the adapted group (1.8 ± 0.1 ln[uu/ml], p = .03). No differences were observed for the other biomarkers. The results suggest that maladaptation among police officers working fixed night shifts may lead to increases in leptin, insulin, IL-6, and TNF-α; however, the cross-sectional design and possible residual confounding preclude interpretation of cause and effect. Prospective studies are planned to further characterize the relationship between shiftwork maladaptation and biomarkers of chronic disease risk in this police officer cohort.

Social inequalities in accelerated aging among southern U.S. women: an analysis of the biosocial and behavioral pathways linking social determinants to telomere length

Few studies have examined the biosocial pathways linking socioeconomic status (SES) to accelerated aging in a population-based sample of southern US women. Even fewer have examined the importance of chronic compared to perceived stress in linking SES to women's salivary telomere length (STL). Using data from a probability-based sample of 156 US women and structural equation modeling, we examined three pathways - chronic stress exposure, stress appraisal, and coping behavior - linking SES to STL. SES was positively associated with STL (β_TE = 0.16, p < .05). Everyday discrimination was negatively associated with STL (β_DE = -0.21, p < .05), but perceived stress was positively associated with STL (β_DE = 0.20, p < .05). Current smoking decreased STL (β_DE = -0.19, p < .01). Perceived stress acted to suppress the negative relationship of chronic stress exposure on STL. Given the dearth of STL studies that include measures of both perceived and chronic stress, our study supports the importance of disentangling stress measures and a biosocial approach to the study of accelerated aging.

Association of Patient Experience With Guideline-Concordant Colon Cancer Treatment in the Elderly

PURPOSE

The association between patient-reported experience of care and care quality is not well described. The purpose of this study was to assess the relationship between the patient-reported experience and receipt of guideline-concordant colon cancer (CC) treatment.

METHODS

Medicare beneficiaries with resected stage I-III CC (2003-2013) were identified in the linked SEER Consumer Assessment of Healthcare Providers and Systems data set. Patient-reported scores were compared by receipt of guideline concordant care (GCC) (resection of ≥ 12 lymph nodes [stage I-III] and adjuvant chemotherapy [stage III]). Linear mixed-effects regression was performed to compare adjusted mean patient experience scores by GCC.

RESULTS

Of the 1,010 identified patients, 58.4% of stage I (n = 192/329) and 73.4% of stage II (n = 298/406) patients underwent resection of ≥ 12 LN. Among stage III patients, 76.0% (n = 209/275) underwent resection of ≥ 12 lymph node and 52.4% (n = 144/275) received adjuvant chemotherapy. By multivariable analysis, patient-reported scores of healthcare quality, physicians, physician communication, getting needed care, and getting care quickly were similar among patients who received GCC compared with those who did not. However, mean scores of overall healthcare quality (91.3 v 82.4, P = .0004) and getting needed care (92.8 v 86.8, P = .047) were higher among stage III patients who received GCC compared with those who did not.

CONCLUSION

Patient-reported scores of healthcare quality and ability to get needed care are associated with GCC among elderly patients with stage III CC. Further investigation is needed to determine whether patient-reported experience correlates with other clinical measures of quality of CC care.

Semiparametric regression of the illness-death model with interval censored disease incidence time: An application to the ACLS data

To investigate the effect of fitness on cardiovascular disease and all-cause mortality using the Aerobics Center Longitudinal Study, we develop a semiparametric illness-death model account for intermittent observations of the cardiovascular disease incidence time and the right censored data of all-cause mortality. The main challenge in estimation is to handle the intermittent observations (interval censoring) of cardiovascular disease incidence time and we develop a semiparametric estimation method based on the expectation-maximization algorithm for a Markov illness-death regression model. The variance of the parameters is estimated using profile likelihood methods. The proposed method is evaluated using extensive simulation studies and illustrated with an application to the Aerobics Center Longitudinal Study data.

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.

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.

Small area estimation of county-level U.S. HIV-prevalent cases

PURPOSE

Recent trends of HIV in the United States have indicated that the epidemic is no longer an urban issue; however, HIV data in rural settings are incomplete. Our objective was to estimate HIV prevalence in U.S. counties using small area estimation techniques (SAE) to better assess the burden of HIV nationally.

METHODS

We performed SAE modeling to predict the reported number of HIV cases across the continental United States, including unreported counties using source data from the CDC National HIV Surveillance System. Our model borrowed strength from auxiliary HIV risk-indicator data, including geospatial information. Cross-validation was conducted to identify and assess the precision of the estimates.

RESULTS

Our findings showed that most of the 677 unreported counties had low HIV prevalence levels (quintiles 1-2). Estimates in the South had high levels of HIV (quintile 4-5). Cross-validation techniques indicated good precision of the estimates, as 42% of the residuals were within ±10 HIV cases.

CONCLUSIONS

HIV was highest along the coastlines and in the U.S. South. Cross-validation techniques provided sufficient support of our model. Our study provides a more complete picture of the burden of HIV across the United States and identifies communities in need of future targeted interventions.

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.

Comparison of Methods Used to Estimate the Global Burden of Disease Related to Undernutrition and Suboptimal Breastfeeding

The Global Burden of Disease study (GBD) is an ambitious effort to estimate the disease burden attributable to various risk factors. The results from the GBD are used around the world to monitor the UN established Sustainable Development Goals, set health policies and research strategies, among others. The GBD along with other studies, such as those from the Maternal Child Epidemiology Estimation Group and the Lancet Breastfeeding Series Group, produce estimates of the nutrition-related global burden of disease that exhibit considerable differences. These differences are difficult to reconcile due to the estimation methods, which in recent years have substantially increased in complexity. In this paper, we give a detailed review of the methods used by GBD and other entities to estimate the global burden of disease that is attributable to undernutrition and suboptimal breastfeeding. Further, we compare the methods to determine causes for differences in estimates. We find that the main determinant of differences in estimates is what causes of death are linked to each risk factor. Methods used to estimate nutrition-related disease burden need to be more clearly documented to foster discussion and collaboration on the important assumptions required to produce estimates.

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.

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.

Fecundity and Infertility Among Women with Disabilities in the United States

Background: Knowledge of fecundity and infertility in women with a disability (WWD) is limited. This study aims to compare the fecundity and infertility experiences of women with a self-identified disability, in domains of sensory (hearing and vision loss), cognitive (difficulty concentrating, remembering, and making decisions), and physical (difficulty walking or climbing stairs) disabilities, with those without a self-identified disability. Materials and Methods: Cross-sectional survey data from the National Survey of Family Growth (NSFG), 2011-2015, were analyzed. A final analytic sample of 383 women from the NSFG, aged 18-44 years, was included to study the fecundity rates of WWD and women without a disability, using the current duration approach. Results: Fecundity hazard ratios (FHRs) and the proportion of women experiencing infertility after 12 months of actively attempting pregnancy were reported for the comparison group and by each disability type. Women with a self-identified cognitive disability experienced significant decreases in fecundity (FHR = 0.56; 95% confidence interval [CI]: 0.30-0.88) when adjusting for age, education level, parity, living in a metropolitan area, and infertility services. Furthermore, the estimated proportion of infertile women without a disability was 0.38 (95% CI: 0.23-0.62) versus 0.51 (95% CI: 0.34-0.72) for women with a self-identified cognitive disability. Conclusions: Women with a self-identified cognitive disability experienced significant decreases in fecundity.

An Estrogen-Related Dietary Pattern and Postmenopausal Breast Cancer Risk in a Cohort of Women with a Family History of Breast Cancer

Background: The results of previous studies on diet and postmenopausal breast cancer risk have been inconclusive, but there is some evidence that dietary patterns developed to correlate with estrogen levels are associated with breast cancer. We aimed to examine the association of a previously developed estrogen-related dietary pattern (ERDP) with postmenopausal breast cancer in the Sister Study.Methods: The ERDP was calculated from food frequency questionnaire responses among Sister Study participants without a personal history of cancer and who contributed postmenopausal person-time at risk. Cox proportional hazards models were used to estimate HRs and 95% confidence intervals for the association between the ERDP and postmenopausal breast cancer.Results: With more than 261,959 person-years of follow-up and 1,968 incident cases, the ERDP was not associated with total, invasive, estrogen receptor (ER)-positive or ER-negative subtypes of breast cancer. Results were robust to various sensitivity analyses.Conclusions: The results do not support previous studies observing a positive association between a proestrogenic dietary pattern and postmenopausal breast cancer risk. Null results may be partially explained by high levels of other breast cancer risk factors within the study population, such as a family history of breast cancer.Impact: An estrogen-related dietary pattern may not be a strong predictor of breast cancer risk in all populations. Future studies of diet and breast cancer should evaluate the potential for effect modification by family history and consider differences in dietary assessment tools when comparing results across study populations. Cancer Epidemiol Biomarkers Prev; 27(10); 1223-6. ©2018 AACR.

Light-Intensity Physical Activity and Cardiometabolic Risk Among Older Adults With Multiple Chronic Conditions

PURPOSE

To assess the relationship between light-intensity physical activity (LIPA) and cardiometabolic risk factors among middle-aged and older adults with multiple chronic conditions.

DESIGN

Cross-sectional design utilizing data from the Health and Retirement Study (2010, 2012).

SETTING

Laboratory- and survey-based testing of a nationally representative sample of community-dwelling middle aged and older adults.

PARTICIPANTS

Adults aged 50 years and older (N = 14 996).

MEASURES

Weighted metabolic equivalent of tasks was calculated using self-reported frequency of light, moderate, and vigorous physical activity. Cardiometabolic risk factors (systolic and diastolic blood pressure, glycosylated hemoglobin [HbA_1c], high-density lipoprotein cholesterol [HDL-C], total cholesterol, and non-HDL-C) were objectively measured. A multiple chronic condition index was based on 8 self-reported chronic conditions.

ANALYSIS

Weighted multivariate linear regression models.

RESULTS

Light-intensity physical activity was independently associated with favorable HDL-C (β = 1.25; 95% confidence interval [CI]: 0.46-2.05) and total cholesterol (β = 2.72; 95% CI: 0.53-4.90) after adjusting for relevant confounders. The HDL-C health benefit was apparent when stratified by number of chronic conditions, for individuals with 2 to 3 conditions (β = 1.73; 95% CI: 0.58-2.89). No significant associations were observed between LIPA and blood pressure, HbA_1c, or non-HDL-C.

CONCLUSIONS

Engaging in LIPA may be an important health promotion activity to manage HDL-C and total cholesterol. Additional longitudinal research is needed to determine the causal association between LIPA and cardiometabolic risk which can potentially inform physical activity guidelines targeting older adults with multiple chronic conditions.

Concentrations of immune marker in newborn dried blood spots and early childhood development: Results from the Upstate KIDS Study

BACKGROUND

Evidence shows cytokine dysregulation in children with developmental disabilities. The association between immune activity during the perinatal period and child development is less clear.

METHODS

We examined the relationship between newborn concentrations of immune markers and child development. Within Upstate KIDS, a population-based birth cohort (2008-2010, upstate New York), we assayed immune markers, which are postulated to have neuro-modulatory effects, in newborn dried blood spots (NDBS, n = 3038). Mothers completed the Ages & Stages Questionnaire© (ASQ) for their children repeatedly through age 36 months. At 30 and 36 months, mothers also reported whether their children received any developmental services. We used generalised linear mixed models adjusted for maternal and child characteristics to test associations.

RESULTS

Sixteen immune markers were associated with failing ASQ in unadjusted models. After full adjustment (for gestational age, mode of delivery, parity, pregnancy smoking, etc.), we observed that higher levels of 4 markers, including platelet-derived growth factor-AA (PDGF-AA, OR 0.77, 95% CI 0.67, 0.89), plasminogen activator inhibitor-1 (OR 0.80, 95% CI 0.68, 0.94), stromal cell derived factor-1 (OR 0.85, 95% CI 0.73, 0.98), and macrophage inflammatory protein-1beta (OR 0.87, 95% CI 0.77, 0.98) were associated with lower odds of ASQ failure. The associations did not exist if correction for multiple comparisons was performed, except for PDGF-AA. Analyses with developmental service use revealed similar null findings.

CONCLUSIONS

Immune marker concentrations in NDBS may not be associated with developmental delay in the general population. Newborn concentrations of growth factor PDGF-AA may be protective of developmental delay in childhood.

An estrogen-related lifestyle score is associated with risk of postmenopausal breast cancer in the PLCO cohort

PURPOSE

Healthy or unhealthy lifestyle behaviors are often adopted together. We aimed to investigate the combined effect of estrogen-related lifestyle factors on postmenopausal breast cancer risk.

METHODS

Data from 27,153 women enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial were used. We created an estrogen-related lifestyle score (ERLS) by incorporating a previously developed measure of estrogenic diet, alcohol intake, body mass index (BMI), and physical activity. The scores ranged from 0 to 6 with alcohol and BMI accounting for higher weights than the other factors. To evaluate the preventive possibilities of a low estrogen-related lifestyle and to be consistent with other published lifestyle scores, higher scores were set to correspond with potentially lower estrogenic lifestyle. The association between the ERLS and incident breast cancer was examined using Cox proportional hazards models.

RESULTS

Participants with an ERLS of 4 or ≥ 5 had a 23% (HR 0.77; 95% CI 0.67-0.89) and 34% (HR 0.66; 95% CI 0.56-0.78) lower risk of breast cancer, respectively, compared to those with an ERLS ≤ 2 after multivariable adjustment. Estimates were similar when restricting to invasive cases or estrogen receptor-positive subtypes. No single lifestyle component appeared to drive the association.

CONCLUSIONS

Our findings suggest that the combined effect of a lifestyle characterized by a low estrogenic diet, low alcohol consumption, low body weight, and high levels of physical activity are associated with a reduction in postmenopausal breast cancer risk, possibly through an influence on estrogen metabolism.

A dietary pattern based on estrogen metabolism is associated with breast cancer risk in a prospective cohort of postmenopausal women

Increased exposure to estrogen is a risk factor for postmenopausal breast cancer, and dietary factors can influence estrogen metabolism. However, studies of diet and breast cancer have been inconclusive. We developed a dietary pattern associated with levels of unconjugated estradiol and the ratio of 2- and 16-hydroxylated estrogen metabolites in a subsample of Prostate, Lung, Colorectal and Ovarian Screening Trial (PLCO) participants (n = 653) using reduced rank regression, and examined its association with postmenopausal breast cancer prospectively in the larger PLCO cohort (n = 27,488). The estrogen-related dietary pattern (ERDP) was comprised of foods with positively-weighted intakes (non-whole/refined grains, tomatoes, cruciferous vegetables, cheese, fish/shellfish high in ω-3 fatty acids, franks/luncheon meats) and negatively-weighted intakes (nuts/seeds, other vegetables, fish/shellfish low in ω-3 fatty acids, yogurt, coffee). A 1-unit increase in the ERDP score was associated with an increase in total (HR: 1.09, 95% CI: 1.01-1.18), invasive (HR: 1.13; 95% CI: 1.04-1.24) and estrogen receptor (ER)-positive (HR: 1.13, 95% CI: 1.02-1.24) breast cancer risk after adjustment for confounders. Associations were observed for the fourth quartile of ERDP compared with the first quartile for overall breast cancer (HR: 1.14; 95% CI: 0.98-1.32), invasive cases (HR: 1.20, 95% CI: 1.02-1.42) and ER-positive cases (HR: 1.19; 95% CI: 0.99-1.41). The increased risk associated with increasing ERDP score was more apparent in strata of some effect modifiers (postmenopausal hormone therapy non-users and non-obese participants) where the relative estrogen exposure due to that factor was lowest, although the p values for interaction were not statistically significant. Results suggest a dietary pattern based on estrogen metabolism is positively associated with postmenopausal breast cancer risk, possibly through an estrogenic influence.