Participant attrition from statewide, population-based Survey of the Health of Wisconsin into the longitudinal SHOW COVID-19 cohort.

PURPOSE: Longitudinal studies are essential for examining how social and institutional determinants of health, historical and contemporary, affect disparities in COVID-19 related outcomes. The unequal impacts of COVID-19 likely exacerbated selected attrition in longitudinal research. This study examines attrition and survey mode effects in the SHOW COVID-19 study which recruited from a statewide, representative cohort. MATERIALS & METHODS: Participants were recruited from the Survey of the Health of Wisconsin (SHOW) cohort. Online surveys, or phone interviews, were administered at three timepoints during 2020-2021. The surveys captured social, behavioral, and structural determinants of health and the lived experience. Univariate and multivariate logistic regression was used to examine predictors of participation and survey mode effects. RESULTS: A total of 2304 adults completed at least one COVID-19 online survey. Participants were more educated, older, and more likely to be female, married, non-Hispanic, and White compared to non-participants. Phone participants were older, less educated, and more likely be non-White, food insecure, and have co-morbidities compared to online participants. Mode effects were seen with reporting COVID-19 beliefs, loneliness, and anxiety. CONCLUSION: The SHOW COVID-19 cohort offers unique longitudinal data but suffered from selected attrition. Phone interview is an important mode for retention and representation.

Objectively measured daytime sleepiness predicts weight change among adults: Findings from the Wisconsin Sleep Cohort Study.

OBJECTIVE: Body mass index (BMI) trajectories are associated with night-time sleep, but it is not clear how they relate to daytime sleepiness in population data. This study aimed to examine longitudinal associations between levels and changes in daytime sleepiness and BMI trajectories among men and women. METHODS: We estimated growth curve models among 827 participants in the Wisconsin Sleep Cohort Study (mean [sd] age = 55.2 [8.0] years at baseline). The outcome variable was BMI (kg/m2) and the key predictor was daytime sleepiness measured by Multiple Sleep Latency Test (MSLT) scores. Covariates included demographics, health behaviors, retirement status, stimulant use, and depressive symptoms. In sensitivity analyses, we evaluated the potential effects of cardiovascular disease, shift work status, and sleep apnea on the robustness of sleepiness and BMI associations. RESULTS: At the between-person level, men who were sleepier had higher BMI levels. At the within-person level, age moderated the positive association between sleepiness and BMI among women. Specifically, young women who became sleepier over time gained more BMI than older women with comparable increases in sleepiness. Furthermore, while BMI tended to increase with age among women, BMI trajectories were steeper among sleepy women than among well-rested women, who experienced less increase in BMI over time. CONCLUSION: The study suggested that levels and changes in daytime sleepiness as objectively measured by MSLT scores are associated with body mass among adults.

Prevalence and Course of Idiopathic Hypersomnia in the Wisconsin Sleep Cohort Study.

BACKGROUND AND OBJECTIVES: Idiopathic hypersomnia (IH) is a CNS disorder of hypersomnolence of unknown etiology. Due to the requirement for objective sleep testing to diagnose the disorder, there are currently no population-based estimates of the prevalence of IH nor data regarding the longitudinal course of IH in naturalistic settings. METHODS: Subjective and objective data from the Wisconsin Sleep Cohort study were used to identify cases with probable IH from participants with polysomnography and multiple sleep latency test data. Demographic, polysomnographic, and symptom-level data were compared between those with and without IH. Longitudinal trajectories of daytime sleepiness among those with IH were assessed to evaluate symptom persistence or remission over time. RESULTS: From 792 cohort study participants with available polysomnography and multiple sleep latency test data, 12 cases with probable IH were identified resulting in an estimated prevalence of IH of 1.5% (95% CI 0.7-2.5, p < 0.0001). Consistent with inclusion/exclusion criteria, cases with IH had more severe sleepiness and sleep propensity, despite similar or longer sleep times. Longitudinal data (spanning 12.1 ± 4.3 years) demonstrated a chronic course of sleepiness for most of the cases with IH, though pathologic somnolence remitted in roughly 40% of cases. DISCUSSION: These results demonstrate IH is more common in the working population than generally assumed with a prevalence on par with other common neurologic and psychiatric conditions. Further efforts to identify and diagnose those impaired by unexplained daytime somnolence may help clarify the causes of IH and the mechanisms underlying symptomatic remission.

Associations of gut microbiome richness and diversity with objective and subjective sleep measures in a population sample.

STUDY OBJECTIVES: Alterations in gut microbiota composition have been associated with several conditions, and there is emerging evidence that sleep quantity and quality are associated with the composition of the gut microbiome. Therefore, this study aimed to assess the associations between several measures of sleep and the gut microbiome in a large, population-based sample. METHODS: Data were collected from participants in the Survey of the Health of Wisconsin from 2016 to 2017 (N = 720). Alpha diversity was estimated using Chao1 richness, Shannon's diversity, and Inverse Simpson's diversity. Beta diversity was estimated using Bray-Curtis dissimilarity. Models for each of the alpha-diversity outcomes were calculated using linear mixed effects models. Permutational multivariate analysis of variance tests were performed to test whether gut microbiome composition differed by sleep measures. Negative binomial models were used to assess whether sleep measures were associated with individual taxa relative abundance. RESULTS: Participants were a mean (SD) age of 55 (16) years and 58% were female. The sample was 83% non-Hispanic white, 10.6% non-Hispanic black, and 3.5% Hispanic. Greater actigraphy-measured night-to-night sleep duration variability, wake-after-sleep onset, lower sleep efficiency, and worse self-reported sleep quality were associated with lower microbiome richness and diversity. Sleep variables were associated with beta-diversity, including actigraphy-measured night-to-night sleep duration variability, sleep latency and efficiency, and self-reported sleep quality, sleep apnea, and napping. Relative abundance of several taxa was associated with night-to-night sleep duration variability, average sleep latency and sleep efficiency, and sleep quality. CONCLUSIONS: This study suggests that sleep may be associated with the composition of the gut microbiome. These results contribute to the body of evidence that modifiable health habits can influence the human gut microbiome.

Cardiorespiratory Fitness Attenuates the Deleterious Effects of Sleep Apnea on Cerebral Structure and Perfusion in the Wisconsin Sleep Cohort Study.

BACKGROUND: Emerging evidence suggests that age-related changes in cerebral health may be sensitive to vascular risk modifiers, such as physical activity and sleep. OBJECTIVE: We examine whether cardiorespiratory fitness modifies the association of obstructive sleep apnea (OSA) severity with MRI-assessed measures of cerebral structure and perfusion. METHODS: Using data from a cross-sectional sample of participants (n = 129, 51% female, age range 49.6-85.3 years) in the Wisconsin Sleep Cohort study, we estimated linear models of MRI-assessed total and regional gray matter (GM) and white matter (WM) volumes, WM hyperintensity (WMH:ICV ratio), total lesion volume, and arterial spin labeling (ASL) cerebral blood flow (CBF), using an estimated measure of cardiorespiratory fitness (CRF) and OSA severity as predictors. Participants' sleep was assessed using overnight in-laboratory polysomnography, and OSA severity was measured using the apnea-hypopnea index (AHI), or the mean number of recorded apnea and hypopnea events per hour of sleep. The mean±SD time difference between PSG data collection and MRI data collection was 1.7±1.5 years (range: [0, 4.9 years]). RESULTS: OSA severity was associated with reduced total GM volume (ß=-0.064; SE = 0.023; p = 0.007), greater total WM lesion volume (interaction p = 0.023), and greater WMHs (interaction p = 0.017) in less-fit subjects. Perfusion models revealed significant differences in the association of AHI and regional CBF between fitness groups (interaction ps < 0.05). CONCLUSION: This work provides new evidence for the protective role of cardiorespiratory fitness against the deleterious effects of OSA on brain aging in late-middle age to older adults.

Sense of community and mental health: a cross-sectional analysis from a household survey in Wisconsin.

BACKGROUND: In the USA, one in five adults live with a mental illness, and researchers have estimated that nearly half of the population will have a mental illness over the course of their lifetime. Research has shown significant associations between social relationships and mental health outcomes at the individual and population levels. This study aims to examine whether sense of community, a type of social capital, is associated with mental health. METHODS: In a cross-sectional analysis, multiple logistic regression models were used to examine whether sense of community was associated with symptoms of depression, anxiety and stress reported over the last week. The analysis used data from the Survey of the Health of Wisconsin collected between 2014 and 2016. A total of 1647 observations are included in the analyses. RESULTS: Compared with those who report a positive sense of community, those with a negative sense of community had a significantly higher odds of reporting depression, anxiety and stress symptoms. Socioeconomic status is negatively associated with depression and anxiety, but not with stress. Women were more likely to experience moderate, severe, or extremely severe anxiety and stress, compared with men. CONCLUSION: This study extends current understanding of health benefits of social capital and found that individuals' sense of community is associated with reduced symptoms of depression, anxiety and stress. Further research examining mechanisms to support improved sense of community and other types of social capital could benefit health equity research.

The effect of low-abundance OTU filtering methods on the reliability and variability of microbial composition assessed by 16S rRNA amplicon sequencing.

PCR amplicon sequencing may lead to detection of spurious operational taxonomic units (OTUs), inflating estimates of gut microbial diversity. There is no consensus in the analytical approach as to what filtering methods should be applied to remove low-abundance OTUs; moreover, few studies have investigated the reliability of OTU detection within replicates. Here, we investigated the reliability of OTU detection (% agreement in detecting OTU in triplicates) and accuracy of their quantification (assessed by coefficient of variation (CV)) in human stool specimens. Stool samples were collected from 12 participants 22-55 years old. We applied several methods for filtering low-abundance OTUs and determined their impact on alpha-diversity and beta-diversity metrics. The reliability of OTU detection without any filtering was only 44.1% (SE=0.9) but increased after filtering low-abundance OTUs. After filtering OTUs with <0.1% abundance in the dataset, the reliability increased to 87.7% (SE=0.6) but at the expense of removing 6.97% reads from the dataset. When filtering was based on individual sample, the reliability increased to 73.1% after filtering OTUs with <10 copies while removing only 1.12% of reads. High abundance OTUs (>10 copies in sample) had lower CV, indicating better accuracy of quantification than low-abundance OTUs. Excluding very low-abundance OTUs had a significant impact on alpha-diversity metrics sensitive to the presence of rare species (observed OTUs, Chao1) but had little impact on relative abundance of major phyla and families and alpha-diversity metrics accounting for both richness and evenness (Shannon, Inverse Simpson). To increase the reliability of microbial composition, we advise removing OTUs with <10 copies in individual samples, particularly in studies where only one subsample per specimen is available for analysis.

Psychological distress and well-being among sensory impaired individuals during COVID-19 lockdown measures.

PURPOSE: Hearing and vision impairment are prevalent chronic conditions associated with poorer mental health. Limitations of in-person contacts during COVID-19-related lockdown measures may affect those with sensory impairments more severely exacerbating mental health problems. We aimed to determine whether hearing and/or visual impairment were associated with more psychological distress during a time of lockdown measures in Spring/Summer 2020 in Wisconsin. METHODS: We included 1341(64% women, aged 20-92 years) Survey of the Health of Wisconsin COVID-19 survey participants (May 2020-July,2020). We assessed self-reported current mental health and well-being and vision and hearing impairment. Logistic regression models with sensory impairments as determinants and mental health outcomes were adjusted for age, gender, race, education, heart disease, hypertension, hyperlipidemia, and diabetes. RESULTS: Vision impairment was associated with increased odds of generalized anxiety disorder (odds ratio = 2.10; 95% confidence interval = 1.32-3.29) and depressive symptoms (2.57;1.58-4.11), greater likelihood to report loneliness (1.65;1.00-2.64) and hopelessness (1.45;1.01-2.08). Hearing impaired individuals reported more loneliness (1.80;1.05-2.98) and hopelessness (1.42;0.99-2.03). Exploratory analyses revealed that sensory impaired individuals less often chose walking as a coping strategy during the pandemic. CONCLUSIONS: Individuals with sensory impairment may represent a particularly vulnerable population during the COVID-19 pandemic. Future research should determine underlying reasons and interventions to mitigate this populations' disadvantages.

The genetic etiology of periodic limb movement in sleep.

STUDY OBJECTIVES: Periodic limb movement in sleep is a common sleep phenotype characterized by repetitive leg movements that occur during or before sleep. We conducted a genome-wide association study (GWAS) of periodic limb movements in sleep (PLMS) using a joint analysis (i.e., discovery, replication, and joint meta-analysis) of four cohorts (MrOS, the Wisconsin Sleep Cohort Study, HypnoLaus, and MESA), comprised of 6843 total subjects. METHODS: The MrOS study and Wisconsin Sleep Cohort Study (N = 1745 cases) were used for discovery. Replication in the HypnoLaus and MESA cohorts (1002 cases) preceded joint meta-analysis. We also performed LD score regression, estimated heritability, and computed genetic correlations between potentially associated traits such as restless leg syndrome (RLS) and insomnia. The causality and direction of the relationships between PLMS and RLS was evaluated using Mendelian randomization. RESULTS: We found 2 independent loci were significantly associated with PLMS: rs113851554 (p = 3.51 × 10-12, ß = 0.486), an SNP located in a putative regulatory element of intron eight of MEIS1 (2p14); and rs9369062 (p = 3.06 × 10-22, ß = 0.2093), a SNP located in the intron region of BTBD9 (6p12); both of which were also lead signals in RLS GWAS. PLMS is genetically correlated with insomnia, risk of stroke, and RLS, but not with iron deficiency. Pleiotropy adjusted Mendelian randomization analysis identified a causal effect of RLS on PLMS. CONCLUSIONS: Because PLMS is more common than RLS, PLMS may have multiple causes and additional studies are needed to further validate these findings.

Metabolic health disparities driven by financial stress: Behavioural adaptation or modification?

Financial stress has been linked to an increased risk of metabolic syndrome, yet, it remains unclear whether suboptimal sleep duration and physical inactivity are the adaptive responses to financial stress or effect modifiers in the association between financial stress and metabolic syndrome. Hence, this study aims to examine whether physical activity and sleep duration mediate or moderate the bivariate association between financial stress and metabolic syndrome. A prospective secondary analysis was conducted using data from the Wisconsin Sleep Cohort Study (N = 445, mean [SD] age = 64 [7] years). Baseline moderation effect was examined using subgroup analysis with model constraints; prospective mediation model was examined using bias-corrected bootstrap confidence intervals. Results indicate that participants with higher financial stress were less likely to meet physical activity and sleep recommendations. Baseline moderation analysis indicates that meeting current recommendations of sleep duration and physical activity attenuated the association between financial stress and metabolic syndrome. In the prospective mediation analysis, weekly physical activity levels partially mediated the relationship between financial stress and metabolic syndrome, but sleep duration did not mediate this relationship. In conclusion, the joint effect of optimal sleep duration and physical activity disassociates financial stress from the risk of metabolic syndrome. Future interventions addressing metabolic risk might achieve better outcomes if clinicians and researchers factor in the behavioral adaptation of physical inactivity in financially stressed adults (Clinical Trial Registration: NCT00005557).

Association between stressful life events and non-optimal lipid levels among women with hyperlipidaemia.

AIMS: Psychological stress has been linked to lipid dysregulation with noticeable gender differences, but it remains unclear whether women are more susceptible to non-optimal lipid levels than men, when experiencing stressful life events. This study aims to examine the association between stressful life events and non-optimal lipid levels among persons with hyperlipidaemia and whether the association differs between men and women. METHODS AND RESULTS: A nested case-control study was performed using data from the Wisconsin Sleep Cohort (WSC) Study from 2011 to 2015, including 224 participants with hyperlipidaemia and without a history of myocardial infarction or heart failure. Among them, 63 participants with non-optimal LDL cholesterol or triglyceride levels were identified as cases, and 161 participants with optimal LDL cholesterol and triglyceride levels were identified as controls. Cases and controls were traced back to their self-reported life events collected through the Retirement and Sleep Trajectories study during 2010-11. The association between stressful life events and non-optimal lipid levels was examined using multivariable logistic regression; confounding effects were addressed using propensity score weighting and Mahalanobis distance matching; gender differences were examined using subgroup analysis. Results showed that a higher number of stressful life events during 2010-11 was associated with greater odds of non-optimal lipid levels during 2011-15 (odds ratio = 1.45, P = 0.03) among women with hyperlipidaemia, whereas the association was not significant among men with hyperlipidaemia (P = 0.910). CONCLUSION: Future studies are needed to examine the underlying mechanisms that explain gender differences in the association between stressful life events and non-optimal lipid levels. REGISTRATION: ClinicalTrials.gov NCT00005557.

Assessing the relationship between physical activity and the gut microbiome in a large, population-based sample of Wisconsin adults.

The gut microbiome is an important factor in human health and disease. While preliminary studies have found some evidence that physical activity is associated with gut microbiome richness, diversity, and composition, this relationship is not fully understood and has not been previously characterized in a large, population-based cohort. In this study, we estimated the association between several measures of physical activity and the gut microbiota in a cohort of 720 Wisconsin residents. Our sample had a mean age of 55 years (range: 18, 94), was 42% male, and 83% of participants self-identified as White. Gut microbial composition was assessed using gene sequencing of the V3-V4 region of 16S rRNA extracted from stool. We found that an increase of one standard deviation in weekly minutes spent in active transportation was associated with an increase in alpha diversity, particularly in Chao1's richness (7.57, 95% CI: 2.55, 12.59) and Shannon's diversity (0.04, 95% CI: 0.0008, 0.09). We identified interactions in the association between Inverse Simpson's diversity and physical activity, wherein active transportation for individuals living in a rural environment was associated with additional increases in diversity (4.69, 95% CI: 1.64, 7.73). We also conducted several permutational ANOVAs (PERMANOVA) and negative binomial regression analyses to estimate the relationship between physical activity and microbiome composition. We found that being physically active and increased physical activity time were associated with increased abundance of bacteria in the family Erysipelotrichaceae. Active transportation was associated with increased abundance of bacteria in the genus Phascolarctobacterium, and decreased abundance of Clostridium. Minutes in active transportation was associated with a decreased abundance of the family Clostridiaceae.

Individual Nutrition Is Associated with Altered Gut Microbiome Composition for Adults with Food Insecurity.

Diet is widely recognized as a key contributor to human gut microbiome composition and function. However, overall nutrition can be difficult to compare across a population with varying diets. Moreover, the role of food security in the relationship with overall nutrition and the gut microbiome is unclear. This study aims to investigate the association between personalized nutrition scores, variation in the adult gut microbiome, and modification by food insecurity. The data originate from the Survey of the Health of Wisconsin and the Wisconsin Microbiome Study. Individual nutrition scores were assessed using My Nutrition Index (MNI), calculated using data from food frequency questionnaires, and additional health history and demographic surveys. Food security and covariate data were measured through self-reported questionnaires. The gut microbiome was assessed using 16S amplicon sequencing of DNA extracted from stool samples. Associations, adjusted for confounding and interaction by food security, were estimated using Weighted Quantile Sum (WQS) regression models with Random Subset and Repeated Holdout extensions (WQSRSRH), with bacterial taxa used as components in the weighted index. Of 643 participants, the average MNI was 66.5 (SD = 31.9), and 22.8% of participants were food insecure. Increased MNI was significantly associated with altered gut microbial composition (ß = 2.56, 95% CI = 0.52−4.61), with Ruminococcus, Oscillospira, and Blautia among the most heavily weighted of the 21 genera associated with the MNI score. In the stratified interaction WQSRSRH models, the bacterial taxa most heavily weighted in the association with MNI differed by food security, but the level of association between MNI and the gut microbiome was not significantly different. More bacterial genera are important in the association with higher nutrition scores for people with food insecurity versus food security, including Streptococcus, Parabacteroides Faecalibacterium, and Desulfovibrio. Individual nutrition scores are associated with differences in adult gut microbiome composition. The bacterial taxa most associated with nutrition vary by level of food security. While further investigation is needed, results showed a higher nutrition score was associated with a wider range of bacterial taxa for food insecure vs. secure, suggesting nutritional quality in food insecure individuals is important in maintaining health and reducing disparities.

Age estimation from sleep studies using deep learning predicts life expectancy.

Sleep disturbances increase with age and are predictors of mortality. Here, we present deep neural networks that estimate age and mortality risk through polysomnograms (PSGs). Aging was modeled using 2500 PSGs and tested in 10,699 PSGs from men and women in seven different cohorts aged between 20 and 90. Ages were estimated with a mean absolute error of 5.8 ± 1.6 years, while basic sleep scoring measures had an error of 14.9 ± 6.29 years. After controlling for demographics, sleep, and health covariates, each 10-year increment in age estimate error (AEE) was associated with increased all-cause mortality rate of 29% (95% confidence interval: 20-39%). An increase from -10 to +10 years in AEE translates to an estimated decreased life expectancy of 8.7 years (95% confidence interval: 6.1-11.4 years). Greater AEE was mostly reflected in increased sleep fragmentation, suggesting this is an important biomarker of future health independent of sleep apnea.

The Survey of the Health of Wisconsin (SHOW) Program: An Infrastructure for Advancing Population Health.

Introduction: The Survey of the Health of Wisconsin (SHOW) was established in 2008 by the University of Wisconsin (UW) School of Medicine and Public Health (SMPH) with the goals of (1) providing a timely and accurate picture of the health of the state residents; and (2) serving as an agile resource infrastructure for ancillary studies. Today, the SHOW program continues to serve as a unique and vital population health research infrastructure for advancing public health. Methods: SHOW currently includes 5,846 adult and 980 minor participants recruited between 2008 and 2019 in four primary waves. WAVE I (2008-2013) includes annual statewide representative samples of 3,380 adults ages 21 to 74 years. WAVE II (2014-2016) is a triannual statewide sample of 1,957 adults (age ≥18 years) and 645 children (age 0-17). WAVE III (2017) consists of follow-up of 725 adults from the WAVE I and baseline surveys of 222 children in selected households. WAVEs II and III include stool samples collected as part of an ancillary study in a subset of 784 individuals. WAVE IV consists of 517 adults and 113 children recruited from traditionally under-represented populations in biomedical research including African Americans and Hispanics in Milwaukee, Wisconsin. Findings to Date: The SHOW resource provides unique spatially granular and timely data to examine the intersectionality of multiple social determinants and population health. SHOW includes a large biorepository and extensive health data collected in a geographically diverse urban and rural population. Over 60 studies have been published covering a broad range of topics including, urban and rural disparities in cardio-metabolic disease and cancer, objective physical activity, sleep, green-space and mental health, transcriptomics, the gut microbiome, antibiotic resistance, air pollution, concentrated animal feeding operations and heavy metal exposures. Discussion: The SHOW cohort and resource is available for continued follow-up and ancillary studies including longitudinal public health monitoring, translational biomedical research, environmental health, aging, microbiome and COVID-19 research.

Genetic risk for subjective reports of insomnia associates only weakly with polygraphic measures of insomnia in 2,770 adults.

STUDY OBJECTIVES: Subjective insomnia complaints and objective sleep changes are mostly studied outside of clinical trial studies. In this study, we tested whether 240 genetic variants associated with subjectively reported insomnia were also associated with objective insomnia parameters extracted from polysomnographic recordings in three studies. METHODS: The study sample (total n = 2,770) was composed of the Wisconsin Sleep Cohort (n = 1,091) and the Osteoporotic Fractures in Men (n = 1,026) study, two population-based studies, and the Stanford Sleep Cohort, a sleep center patient-based sample (n = 653). Seven objective polysomnographic features related to insomnia defined outcome variables, with each variant allele serving as predictor. Meta-regression was performed, accounting for common confounders as well as variance differences between studies. Additionally, a normalized genetic risk score was generated for each subject to serve as a predictor variable in separate linear mixed models assessing objective insomnia features. RESULTS: After correction for multiple testing, single-nucleotide polymorphisms associated with subjective insomnia were not significantly associated with 6 of 7 objective sleep measures. Only periodic limb movement index was significantly associated with rs113851554 (MEIS1), as found in previous studies. The normalized genetic risk score was only weakly associated with arousal index and duration of wake after sleep onset. CONCLUSIONS: Our findings suggest that subjective insomnia does not have a strong genetic signature mapping onto objective (polysomnographic) sleep variables. CITATION: Foldager J, Peppard PE, Hagen EW, et al. Genetic risk for subjective reports of insomnia associates only weakly with polygraphic measures of insomnia in 2,770 adults. J Clin Sleep Med. 2022;18(1):21-29.

Urinary lead level and colonization by antibiotic resistant bacteria: Evidence from a population-based study.

BACKGROUND: Infection by antibiotic resistant bacteria (ARB) is a global health crisis and asymptomatic colonization increases risk of infection. Nonhuman studies have linked heavy metal exposure to the selection of ARB; however, few epidemiologic studies have examined this relationship. This study analyzes the association between urinary lead level and colonization by ARB in a nonclinical human population. METHODS: Data came from the Survey of the Health of Wisconsin 2016-2017, and its ancillary Wisconsin Microbiome Study. Urinary lead levels, adjusted for creatinine, were used to assess exposure. ARB included methicillin resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), fluoroquinolone resistant Gram-negative bacilli (RGNB), and Clostridium difficile (C. diff), from skin, nose, and mouth swabs, and saliva and stool samples. Logistic regression, adjusted for covariates, was used to evaluate associations between Pb and ARB. Secondary analysis investigated Pb resistance from ARB isolates. RESULTS: Among 695 participants, 239 (34%) tested positive for ARB. Geometric mean urinary Pb (unadjusted) was 0.286 µg/L (95% confidence intervals [CI] = 0.263, 0.312) for ARB negative participants and 0.323 µg/L (95% CI = 0.287, 0.363) for ARB positive participants. Models adjusted for demographics, diet, and antibiotic use showed elevated odds of positive colonization for those in the 95th percentile (vs. below) of Pb exposure (odds ratio [OR] = 2.05, 95% CI = 0.95, 4.44), and associations were highest in urban residents (OR = 2.85, 95% CI = 1.07, 7.59). RGNB isolates were most resistant to Pb. DISCUSSION: These novel results suggest that Pb exposure is associated with increased colonization by ARB, and that RGNB are particularly resistant to Pb.

Assessing the impact of storage time on the stability of stool microbiota richness, diversity, and composition.

BACKGROUND: New technologies like next-generation sequencing have led to a proliferation of studies investigating the role of the gut microbiome in human health, particularly population-based studies that rely upon participant self-collection of samples. However, the impact of methodological differences in sample shipping, storage, and processing are not well-characterized for these types of studies, especially when transit times may exceed 24 h. The aim of this study was to experimentally assess microbiota stability in stool samples stored at 4 °C for durations of 6, 24, 48, 72, and 96 h with no additives to better understand effects of variable shipping times in population-based studies. These data were compared to a baseline sample that was immediately stored at - 80 °C after stool production. RESULTS: Compared to the baseline sample, we found that the alpha-diversity metrics Shannon's and Inverse Simpson's had excellent intra-class correlations (ICC) for all storage durations. Chao1 richness had good to excellent ICC. We found that the relative abundances of bacteria in the phyla Verrucomicrobia, Actinobacteria, and Proteobacteria had excellent ICC with baseline for all storage durations, while Firmicutes and Bacteroidetes ranged from moderate to good. We interpreted the ICCs as follows: poor: ICC < 0.50, moderate: 0.50 < ICC < 0.75, good: 0.75 < ICC < 0.90, and excellent: ICC > 0.90. Using the Bray-Curtis dissimilarity index, we found that the greatest change in community composition occurred between 0 and 24 h of storage, while community composition remained relatively stable for subsequent storage durations. Samples showed strong clustering by individual, indicating that inter-individual variability was greater than the variability associated with storage time. CONCLUSIONS: The results of this analysis suggest that several measures of alpha diversity, relative abundance, and overall community composition are robust to storage at 4 °C for up to 96 h. We found that the overall community richness was influenced by storage duration in addition to the relative abundances of sequences within the Firmicutes and Bacteroidetes phyla. Finally, we demonstrate that inter-individual variability in microbiota composition was greater than the variability due to changing storage durations.

Associations of school night sleep duration and circadian preference with middle school-aged student attendance, tardiness, and suspension.

OBJECTIVES: Research has associated both school night sleep duration (SNSD) and circadian preference (CP) with middle school-aged students' attendance and tardiness, but the interaction between these characteristics remains unexplored within this context, along with the impact of SNSD and CP on school suspension likelihood. Thus, this study investigated associations between SNSD, CP, and their interaction with middle school-aged student attendance, tardiness, and suspension, while accounting for sociodemographic characteristics. PARTICIPANTS: About 4175 students from 12 middle schools in the Madison, Wisconsin, Metropolitan School District. METHODS: Students completed a computer-based, sleep-related survey during class. Students reporting SNSD between 4 and 12 hours were included in the final analytical sample (N = 3860; mean age ± standard deviation = 12.0 ± 0.86 years; range = 10-16 years). CP was characterized using the single-item self-morningness/eveningness question. Linear mixed-effects regression estimated associations of SNSD and CP with tardiness and attendance. Logistic mixed-effects regression assessed associations with school suspension. Fully adjusted multilevel models included sociodemographic covariates, nesting students within schools. RESULTS: About 3860 student responses comprised the final sample, which had a SNSD of 8.15 ± 1.37 hours and general eveningness preference. Short-and-long SNSD associated with lower attendance and increased out-of-school suspension. Greater eveningness preference was negatively associated with attendance and tardiness. No SNSD and CP interactions emerged. Associations between sociodemographic characteristics and attendance, tardiness, and suspension were observed. CONCLUSIONS: Results support need for efforts to improve middle school-aged student sleep health and account for eveningness preference. Research clarifying the interactive influence of sleep, circadian, and sociodemographic characteristics on attendance and achievement is warranted.

Habitual sleep, sleep duration differential, and weight change among adults: Findings from the Wisconsin Sleep Cohort Study.

OBJECTIVES: Assess longitudinal associations between diary-measured sleep duration and clinically assessed body mass index (BMI). DESIGN: Multilevel growth curve analyses examined how within-person changes and between-person differences in habitual sleep duration were associated with BMI trajectories. SETTING: Sleep diaries across 2-6 consecutive weekday and weekend nights at each data collection point, repeatedly collected at approximate 4-year intervals, for an average of 9.2 (standard deviation [SD] = 3.6) years between 1989 and 2011. PARTICIPANTS: About 784 participants (47% women) enrolled in the Wisconsin Sleep Cohort Study (mean [SD] age = 51.1 [8.0] years at baseline). MEASUREMENTS: The outcome variable was BMI (kg/m2). Key predictors were habitual sleep duration (defined as average weekday nighttime sleep duration) and sleep duration differential (defined as the difference between average weekday and average weekend nighttime sleep duration) at each data collection wave. RESULTS: Men with shorter habitual sleep duration on weekdays had higher BMI than men with longer habitual sleep duration on weekdays (ß = -0.90 kg/m2/hour, se = 0.34, p = .008). Participants with larger differentials between weekday and weekend sleep duration experienced more rapid BMI gain over time for both men (ß = 0.033 kg/m2/year per hour differential, se = 0.017, p = .044) and women (ß = 0.057 kg/m2/year per hour differential, se = 0.027, p = .036). CONCLUSION: This study suggests that habitual short sleep is associated with higher BMI levels in men and that a larger weekday-weekend sleep differential is associated with increasing BMI trajectories among both men and women in mid-to-late life.