This study explored the divergence in population-level estimates of insufficient sleep (<6 h) by examining the explanatory role of race/ethnicity and contrasting values derived from logistic and Poisson regression modeling techniques. We utilized National Health and Nutrition Examination Survey data to test our hypotheses among 20-85 year-old non-Hispanic Black and non-Hispanic White adults. We estimated the odds ratios using the transformed logistic regression and Poisson regression with robust variance relative risk and 95% confidence intervals (CI) of insufficient sleep. Comparing non-Hispanic White (10176) with non-Hispanic Black (4888) adults (mean age: 50.61 ± 18.03 years, female: 50.8%), we observed that the proportion of insufficient sleepers among non-Hispanic Blacks (19.2-26.1%) was higher than among non-Hispanic Whites (8.9-13.7%) across all age groupings. The converted estimated relative risk ranged from 2.12 (95% CI: 1.59, 2.84) to 2.59 (95% CI: 1.92, 3.50), while the estimated relative risks derived directly from Poisson regression analysis ranged from 1.84 (95% CI: 1.49, 2.26) to 2.12 (95% CI: 1.64, 2.73). All analyses indicated a higher risk of insufficient sleep among non-Hispanic Blacks. However, the estimates derived from logistic regression modeling were considerably higher, suggesting the direct estimates of relative risk ascertained from Poisson regression modeling may be a preferred method for estimating population-level risk of insufficient sleep.

Epidemiologic studies use various biosample collection methods to study associations between human oral microbiota and health outcomes. However, the agreement between the different methods is unclear. We compared a commercially available OMNIgene ORAL kit to three alternative collection methods: Saccomanno's fixative, Scope mouthwash, and nonethanol mouthwash. Oral samples were collected from 40 individuals over 4 visits. Two samples were collected from each subject per visit: one with OMNIgene and one with an alternative method. DNA was extracted using the DSP DNA Virus Pathogen kit, and the V4 region of the 16S rRNA gene was PCR amplified and sequenced using MiSeq. Oral collection methods were compared based on alpha and beta diversity metrics and phylum- and genus-level relative abundances. All alpha diversity metrics were significantly lower for Saccomanno's fixative than for OMNIgene (P < 0.001), whereas the two mouthwashes were more similar to OMNIgene. Principal-coordinate analysis (PCoA) using the Bray-Curtis and weighted UniFrac beta diversity matrices showed large differences in the microbial compositions of samples collected with Saccomanno's compared to those with OMNIgene and the mouthwashes. Clustering by collection method was not observed in unweighted UniFrac PCoA plots, suggesting differences in relative abundances but not specific taxa detected by the collection methods. Relative abundances of most taxa were significantly different between OMNIgene and the other methods at each taxonomic level, with Saccomanno's showing the least agreement with OMNIgene. There were clear differences in oral microbial communities between the four oral collection methods, particularly for Saccomanno's fixative.IMPORTANCE We compared four different oral collection methods for studying the human oral microbiome: an OMNIgene ORAL kit, Scope mouthwash, nonethanol mouthwash, and Saccomanno's fixative. Our study shows that the type of the collection method can have a large impact on the results of an oral microbiome analysis. We recommend that one consistent oral collection method should be used for all oral microbiome comparisons. While Scope and nonethanol mouthwashes are less expensive and provide results similar to those with OMNIgene, Saccomanno's fixative may be unfavorable due to the microbial differences detected in this study. Our results will help guide the design of future oral microbiome studies.

Diarrhea is a leading cause of illness and death among children aged <5 years in developing countries. This paper describes the clinical and epidemiological methods used to conduct the Global Enteric Multicenter Study (GEMS), a 3-year, prospective, age-stratified, case/control study to estimate the population-based burden, microbiologic etiology, and adverse clinical consequences of acute moderate-to-severe diarrhea (MSD) among a censused population of children aged 0-59 months seeking care at health centers in sub-Saharan Africa and South Asia.

A new lower-cost rapid-throughput human papillomavirus (HPV) test (careHPV, Qiagen, Gaithersburg, USA) has been shown to have high sensitivity for the detection of high grade cervical intraepithelial neoplasia.

In 2016, Venezuela faced a large diphtheria outbreak that extended until 2019. Nasopharyngeal or oropharyngeal samples were prospectively collected from 51 suspected cases and retrospective data from 348 clinical records was retrieved from 14 hospitals between November 2017 and November 2018. Confirmed pathogenic Corynebactrium isolates were biotyped. Multilocus Sequence Typing (MLST) was performed followed by next-generation-based core genome-MLST and minimum spanning trees were generated. Subjects between 10 and 19 years of age were mostly affected (n = 95; 27.3%). Case fatality rates (CFR) were higher in males (19.4%), as compared to females (15.8%). The highest CFR (31.1%) was observed among those under 5, followed by the 40 to 49 age-group (25.0%). Nine samples corresponded to C. diphtheriae and 1 to C. ulcerans. Two Sequencing Types (ST), ST174 and ST697 (the latter not previously described) were identified among the eight C. diphtheriae isolates from Carabobo state. Cg-MLST revealed only one cluster also from Carabobo. The Whole Genome Sequencing analysis revealed that the outbreak seemed to be caused by different strains with C. diphtheriae and C. ulcerans coexisting. The reemergence and length of this outbreak suggest vaccination coverage problems and an inadequate control strategy.

Ensuring privacy of research subjects when epidemiologic data are shared with outside collaborators involves masking (modifying) the data, but overmasking can compromise utility (analysis potential). Methods of statistical disclosure control for protecting privacy may be impractical for individual researchers involved in small-scale collaborations.

Peak exposures are of concern because they can potentially overwhelm normal defense mechanisms and induce adverse health effects. Metrics of peak exposure have been used in epidemiologic and exposure studies, but consensus is lacking on its definition. The relevant characteristics of peak exposure are dependent upon exposure patterns, biokinetics of exposure, and disease mechanisms. The objective of this review was to summarize the use of peak metrics in epidemiologic and exposure studies. A comprehensive search of Medline, Embase, Web of Science, and NIOSHTIC-2 databases was conducted using keywords related to peak exposures. The retrieved references were reviewed and selected for indexing if they included a peak metric and met additional criteria. Information on health outcomes and peak exposure metrics was extracted from each reference. A total of 1,215 epidemiologic or exposure references were identified, of which 182 were indexed and summarized. For the 72 epidemiologic studies, the health outcomes most frequently evaluated were: chronic respiratory effects, cancer and acute respiratory symptoms. Exposures were frequently assessed using task-based and full-shift time-integrated methods, qualitative methods, and real-time instruments. Peak exposure summary metrics included the presence or absence of a peak event, highest exposure intensity and frequency greater than a target. Peak metrics in the 110 exposure studies most frequently included highest exposure intensity, average short-duration intensity, and graphical presentation of the real-time data (plots). This review provides a framework for considering biologically relevant peak exposure metrics for epidemiologic and exposure studies to help inform risk assessment and exposure mitigation.

The objectives of the study was to determine the types, challenges and implications of surveillance methods for controlling Covid-19 pandemic. An integrative article review was done. The source of data were documents from WHO, Euro-surveillance, CDC, Saudi CDC, MOH, and journals from PubMed, Medline, etc. The inclusion searching criteria were surveillance, Covid-19, types, benefits and challenges, during the period 2005-2020. Published studies, reviews and guidelines that determined these criteria were collected. Data extraction and analysis were completed for all included articles. A critical appraisal was done based on the University of Michigan Practice Guideline's levels of evidence. The final sample for the integrative review comprised 30 studies. Results revealed that types of Covid-9 surveillance includes routine surveillance (comprehensive, case-based, and aggregated weakly methods), active, wildlife, syndromic, sentinel and sentinel-syndromic methods. Laboratory and hospital-based surveillance are another important types. Help-lines, surveys, participatory electronic, digital and event-based surveillance are relatively new cost-effective methods. Many surveillance indicators can be calculated. Timely and accurate of surveillance data is an essential element for effective Covid-19 interventions. Regarding challenges, the quality of surveillance in developing countries is constrained by resources and training. The main limitations of surveillance are under-ascertainment/under-reporting, lack of timeliness and completeness of surveillance data. In conclusion, surveillance is a cornerstones for controlling Covid-19 pandemic. Enhancing Covid-19 surveillance is vital for rapid cases detection, containing spread & ending pandemic.

Environmental epidemiology, when focused on the life course of exposure to a specific pollutant, requires historical exposure estimates that are difficult to obtain for the full time period due to gaps in the historical record, especially in earlier years. We show that these gaps can be filled by applying multiple imputation methods to a formal risk equation that incorporates lifetime exposure. We also address challenges that arise, including choice of imputation method, potential bias in regression coefficients, and uncertainty in age-at-exposure sensitivities.

Although researchers have described numerous risk factors for salmonellosis and for infection with specific common serotypes, the drivers of Salmonella serotype diversity among human populations remain poorly understood. In this retrospective observational study, we partition records of serotyped non-typhoidal Salmonella isolates from human clinical specimens reported to CDC national surveillance by demographic, geographic and seasonal characteristics and adapt sample-based rarefaction methods from the field of community ecology to study how Salmonella serotype diversity varied within and among these populations in the USA during 1996-2016. We observed substantially higher serotype richness in children <2 years old than in older children and adults and steadily increasing richness with age among older adults. Whereas seasonal and regional variation in serotype diversity was highest among infants and young children, variation by specimen source was highest in adults. Our findings suggest that the risk for infection from uncommon serotypes is associated with host and environmental factors, particularly among infants, young children and older adults. These populations may have a higher proportion of illness acquired through environmental transmission pathways than published source attribution models estimate.

Common methods for confounder identification such as directed acyclic graphs (DAGs), hypothesis testing, or a 10 % change-in-estimate (CIE) criterion for estimated associations may not be applicable due to (a) insufficient knowledge to draw a DAG and (b) when adjustment for a true confounder produces less than 10 % change in observed estimate (e.g. in presence of measurement error).

Epidemiologic collections have been a major resource for genotype-phenotype studies of complex disease given their large sample size, racial/ethnic diversity, and breadth and depth of phenotypes, traits, and exposures. A major disadvantage of these collections is they often survey households and communities without collecting extensive pedigree data. Failure to account for substantial relatedness can lead to inflated estimates and spurious associations. To examine the extent of cryptic relatedness in an epidemiologic collection, we as the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study accessed the National Health and Nutrition Examination Surveys (NHANES) linked to DNA samples ("Genetic NHANES") from NHANES III and NHANES 1999-2002. NHANES are population-based cross-sectional surveys conducted by the National Center for Health Statistics at the Centers for Disease Control and Prevention. Genome-wide genetic data is not yet available in NHANES, and current data use agreements prohibit the generation of GWAS-level data in NHANES samples due issues in maintaining confidentiality among other ethical concerns. To date, only hundreds of single nucleotide polymorphisms (SNPs) genotyped in a variety of candidate genes are available for analysis in NHANES. We performed identity-by-descent (IBD) estimates in three self-identified subpopulations of Genetic NHANES (non-Hispanic white, non- Hispanic black, and Mexican American) using PLINK software to identify potential familial relationships from presumed unrelated subjects. We then compared the PLINKidentified relationships to those identified by an alternative method implemented in Kinship-based INference for Genome-wide association studies (KING). Overall, both methods identified familial relationships in NHANES III and NHANES 1999-2002 for all three subpopulations, but little concordance was observed between the two methods due in major part to the limited SNP data available in Genetic NHANES. Despite the lack of genome-wide data, our results suggest the presence of cryptic relatedness in this epidemiologic collection and highlight the limitations of restricted datasets such as NHANES in the context of modern day genetic epidemiology studies.

We review approaches for characterizing "peak" exposures in epidemiologic studies and methods for incorporating peak exposure metrics in dose-response assessments that contribute to risk assessment. The focus was on potential etiologic relations between environmental chemical exposures and cancer risks. We searched the epidemiologic literature on environmental chemicals classified as carcinogens in which cancer risks were described in relation to "peak" exposures. These articles were evaluated to identify some of the challenges associated with defining and describing cancer risks in relation to peak exposures. We found that definitions of peak exposure varied considerably across studies. Of nine chemical agents included in our review of peak exposure, six had epidemiologic data used by the U.S. Environmental Protection Agency (US EPA) in dose-response assessments to derive inhalation unit risk values. These were benzene, formaldehyde, styrene, trichloroethylene, acrylonitrile, and ethylene oxide. All derived unit risks relied on cumulative exposure for dose-response estimation and none, to our knowledge, considered peak exposure metrics. This is not surprising, given the historical linear no-threshold default model (generally based on cumulative exposure) used in regulatory risk assessments. With newly proposed US EPA rule language, fuller consideration of alternative exposure and dose-response metrics will be supported. "Peak" exposure has not been consistently defined and rarely has been evaluated in epidemiologic studies of cancer risks. We recommend developing uniform definitions of "peak" exposure to facilitate fuller evaluation of dose response for environmental chemicals and cancer risks, especially where mechanistic understanding indicates that the dose response is unlikely linear and that short-term high-intensity exposures increase risk.

BACKGROUND: Chronic fatigue syndrome (CFS) has no diagnostic clinical signs or diagnostic laboratory abnormalities and it is unclear if it represents a single illness. The CFS research case definition recommends stratifying subjects by co-morbid conditions, fatigue level and duration, or functional impairment. But to date, this analysis approach has not yielded any further insight into CFS pathogenesis. This study used the integration of peripheral blood gene expression results with epidemiologic and clinical data to determine whether CFS is a single or heterogeneous illness. RESULTS: CFS subjects were grouped by several clinical and epidemiological variables thought to be important in defining the illness. Statistical tests and cluster analysis were used to distinguish CFS subjects and identify differentially expressed genes. These genes were identified only when CFS subjects were grouped according to illness onset and the majority of genes were involved in pathways of purine and pyrimidine metabolism, glycolysis, oxidative phosphorylation, and glucose metabolism. CONCLUSION: These results provide a physiologic basis that suggests CFS is a heterogeneous illness. The differentially expressed genes imply fundamental metabolic perturbations that will be further investigated and illustrates the power of microarray technology for furthering our understanding CFS.

New Delhi metallo-β-lactamase (NDM) represents an emergent mechanism of carbapenem resistance associated with high mortality and limited antimicrobial treatment options. Because the blaNDM resistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods like speciation, antimicrobial resistance testing, and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks.

Background: Androgenetic alopecia (AGA) and alopecia areata (AA) are the most common types of non-cicatricial alopecia. Both diseases have limited effective therapeutic options and affect patient quality of life. Pharmacogenetic tests can help predict the most appropriate treatment option by evaluating the single nucleotide polymorphisms (SNPs) corresponding to genes related to alopecia. The objective of the study was to evaluate and compare selected SNPs and genes in AA and AGA patients from Romania and Brazil. Materials and Methods: We performed a retrospective study regarding the associations between AA and AGA and 45 tag SNPs of 15 genes in 287 Romanian and 882 Brazilian patients. The DNA samples were collected from oral mucosa using a swab. The SNPs were determined by the qPCR technique. Each genetic test displays the subject's genotype of the selected gene and the prediction of a successful treatment (e.g., genotype AA of the GR-alpha gene is related to a predisposition to normal sensibility to topical glucocorticoid, and, therefore, glucocorticoids should be effective). Results: The GR-alpha, GPR44-2, SULT1A1, and CRABP2 genes were statistically significantly different in Brazil compared to Romania. The SULT1A1 activity that predicts the response to minoxidil treatment showed in our analysis that minoxidil is recommended in half of the cases of AGA and AA. Patients with AGA and a high expression of SRD5A1 or PTGFR-2 may benefit from Dutasteride or Latanoprost treatment, respectively. Most of the studied genes showed no differences between the two populations. Conclusions: The DNA analysis of the patients with alopecia may contribute to a successful treatment.

Background Intensive systolic blood pressure treatment (<120 mm Hg) in SPRINT (Systolic Blood Pressure Intervention Trial) improved survival compared with standard treatment (<140 mm Hg) over a median follow-up of 3.3 years. We projected life expectancy after observed follow-up in SPRINT using SPRINT-eligible participants in the NHLBI-PCS (National Heart, Lung, and Blood Institute Pooled Cohorts Study). Methods and Results We used propensity scores to weight SPRINT-eligible NHLBI-PCS participants to resemble SPRINT participants. In SPRINT participants, we estimated in-trial survival (<4 years) using a time-based flexible parametric survival model. In SPRINT-eligible NHLBI-PCS participants, we estimated posttrial survival (≥4 years) using an age-based flexible parametric survival model and applied the formula to SPRINT participants to predict posttrial survival. We projected overall life expectancy for each SPRINT participant and compared it to parametric regression (eg, Gompertz) projections based on SPRINT data alone. We included 8584 SPRINT and 10 593 SPRINT-eligible NHLBI-PCS participants. After propensity weighting, mean (SD) age was 67.9 (9.4) and 68.2 (8.8) years, and 35.5% and 37.6% were women in SPRINT and NHLBI-PCS, respectively. Using the NHLBI-PCS-based method, projected mean life expectancy from randomization was 21.0 (7.4) years with intensive and 19.1 (7.2) years with standard treatment. Using the Gompertz regression, life expectancy was 11.2 (2.3) years with intensive and 10.5 (2.2) years with standard treatment. Conclusions Combining SPRINT and NHLBI-PCS observed data likely offers a more realistic estimate of life expectancy than parametrically extrapolating SPRINT data alone. These results offer insight into the potential long-term effectiveness of intensive SBP goals.

Few multicenter pediatric studies have comprehensively described the epidemiologic characteristics of cisplatin-associated acute kidney injury using standardized definitions.

Current evidence supports the notion that environmental exposures are associated with DNA-methylation and expression changes that can impact human health. Our objective was to conduct a systematic review of epidemiologic studies evaluating the association between environmental chemicals with DNA methylation levels in adults. After excluding arsenic, recently evaluated in a systematic review, we identified a total of 17 articles (6 on cadmium, 4 on lead, 2 on mercury, 1 on nickel, 1 on antimony, 1 on tungsten, 5 on persistent organic pollutants and perfluorinated compounds, 1 on bisphenol A, and 3 on polycyclic aromatic hydrocarbons). The selected articles reported quantitative methods to determine DNA methylation including immunocolorimetric assays for total content of genomic DNA methylation, and microarray technologies, methylation-specific quantitative PCR, Luminometric Methylation Assay (LUMA), and bisulfite pyrosequencing for DNA methylation content of genomic sites such as gene promoters, LINE-1, Alu elements, and others. Considering consistency, temporality, strength, dose-response relationship, and biological plausibility, we concluded that the current evidence is not sufficient to provide inference because differences across studies and limited samples sizes make it difficult to compare across studies and to evaluate sources of heterogeneity. Important questions for future research include the need for larger and longitudinal studies, the validation of findings, and the systematic evaluation of the dose-response relationships. Future studies should also consider the evaluation of epigenetic marks recently in the research spotlight such as DNA hydroxymethylation and the role of underlying genetic variants.

Background: Primary immunodeficiencies (PIDs) are rare genetic disorders leading to immunologic abnormalities that can affect different organs and systems. We determined the epidemiology, clinical, and geospatial characteristics of PID disorders among patients diagnosed over a 5 year period in a reference hospital covering a mesoregion in São Paulo, Brazil. Methods: A retrospective analysis of 39 patients with recognizable PIDs according to the criteria of the European Society of Primary Immunodeficiencies were enrolled. Thirty-four patients came from outpatient immunodeficiency clinics and five patients from active search. Demographic, clinical, and immunologic data were collected, and maps were constructed using a geographic information system. Results: The ratio of females to males was 1.4:1, and 48.7% of patients were younger than 17 years of age. The mean age at the onset of symptoms in children was 2.0 years [standard error of the mean (SEM), 1.7 years] and the diagnosis lag was 5.1 years (SEM, 3.1 years); the mean age at diagnosis in adults was 16.3 years (SEM, 11.8 years) and the lag was 10.8 years (SEM, 10.9 years). Antibody deficiency and common variable immunodeficiencies were the most common categories and phenotypes, respectively. The need for intravenous antibiotics and respiratory tract infections were the most prevalent warning signs, with an overall mortality rate of 15.3%. Autoimmune diseases were diagnosed in 56.4% and visceral leishmaniasis in 5.1% of patients. In the active search, 29 patients were investigated and 17.2% were diagnosed; early diagnosis, the involvement of multidisciplinary professionals, and dissemination of knowledge achieved milestone benefits. The distribution of PID networks in Brazil shows great asymmetry between regions and at a regional level; it was shown that the patients lived mainly in Presidente Prudente municipality. Conclusions: The implementation of an immunodeficiency outpatient clinic in a referral hospital covering a mesoregion with a large population has led to the generation of policies and practices to improve the diagnosis, quality of life, and care of patients with PIDs and their families. Furthermore, the search for hospitalized patients with warning signs for PIDs showed great benefits. Inequality in the distribution of PID network centers in Brazil was demonstrated.