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bioRxiv2017

Bioimpedance and new onset heart failure: A longitudinal study of ~500,000 individuals from the general population

ImportanceHeart failure constitutes a high burden on patients and society, but although lifetime risk is high, it is difficult to predict without costly or invasive testing. Knowledge about novel risk factors could enable early diagnosis and possibly preemptive treatment.\n\nObjectiveTo establish new risk factors for heart failure.\n\nDesignWe applied supervised machine learning in UK Biobank in an agnostic search of risk factors for heart failure. Novel predictors were then subjected to several in-depth analyses, including multivariable Cox models of incident heart failure, and assessment of discrimination and calibration.\n\nSettingPopulation-based cohort study.\n\nParticipants500,451 individuals who volunteered to participate in the UK Biobank cohort study, excluding those with prevalent heart failure.\n\nExposure3646 variables reflecting different aspects of lifestyle, health and disease-related factors.\n\nMain OutcomeIncident heart failure hospitalization.\n\nResultsMachine learning confirmed many known and putative risk factors for heart failure, and identified several novel candidates. Mean reticulocyte volume appeared as one novel factor, and leg bioimpedance another; the latter appearing as the most important new factor. Leg bioimpedance was significantly lower in those who developed heart failure (p=1.1x10-72) during up to 9.8-year follow-up. When adjusting for known heart failure risk factors, leg bioimpedance was inversely related to heart failure (hazard ratio [95%CI], 0.60 [0.48-0.73]) and 0.75 [0.59-0.94], in age- and sex-adjusted and fully adjusted models, respectively, comparing the upper vs. lower quartile). A model including leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good predictive capacity of future heart failure hospitalization (C-index=0.82) and good calibration.\n\nConclusions and RelevanceLeg bioimpedance is inversely associated with heart failure incidence in the general population. A simple model of exclusively non-invasive measures, combining leg bioimpedance with history of myocardial infarction, age, and sex provides accurate predictive capacity.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhich are the most important risk factors for incident heart failure?\n\nFindingsIn this population-based cohort study of ~500,000 individuals, machine learning identified well-established risk factors, but also several novel factors. Among the most important were leg bioimpedance and mean reticulocyte volume. There was a strong inverse relationship between leg bioimpedance and incident heart failure, also in adjusted analyses. A model entailing leg bioimpedance, age, sex, and self-reported history of myocardial infarction showed good predictive capacity of heart failure hospitalization and good calibration.\n\nMeaningLeg bioimpedance appears to be an important new factor associated with incident heart failure.

epidemiology↗

bioRxiv2017

Investigating causality in associations between education and smoking: A two-sample Mendelian randomization study

BackgroundLower educational attainment is associated with increased rates of smoking, but ascertaining causality is challenging. We used two-sample Mendelian randomization (MR) analyses of summary statistics to examine whether educational attainment is causally related to smoking.\n\nMethods and FindingsWe used summary statistics from genome-wide association studies of educational attainment and a range of smoking phenotypes (smoking initiation, cigarettes per day, cotinine levels and smoking cessation). Various complementary MR techniques (inverse-variance weighted regression, MR Egger, weighted-median regression) were used to test the robustness of our results. We found broadly consistent evidence across these techniques that higher educational attainment leads to reduced likelihood of smoking initiation, reduced heaviness of smoking among smokers (as measured via self-report and cotinine levels), and greater likelihood of smoking cessation among smokers.\n\nConclusionsOur findings indicate a causal association between low educational attainment and increased risk of smoking, and may explain the observational associations between educational attainment and adverse health outcomes such as risk of coronary heart disease.

epidemiology↗

bioRxiv2017

Effect modification of FADS2 polymorphisms on the association between breastfeeding and intelligence: results from a collaborative meta-analysis

BackgroundAccumulating evidence suggests that breastfeeding benefits the childrens intelligence. Long-chain polyunsaturated fatty acids (LC-PUFAs) present in breast milk may explain part of this association. Under a nutritional adequacy hypothesis, an interaction between breastfeeding and genetic variants associated with endogenous LC-PUFAs synthesis might be expected. However, the literature on this topic is controversial.\n\nMethods and FindingsWe investigated this GenexEnvironment interaction in a de novo meta-analysis involving >12,000 individuals in the primary analysis, and >45,000 individuals in a secondary analysis using relaxed inclusion criteria. Our primary analysis used ever breastfeeding, FADS2 polymorphisms rs174575 and rs1535 coded assuming a recessive effect of the G allele, and intelligence quotient (IQ) in Z scores. Using random effects meta-analysis, ever breastfeeding was associated with 0.17 (95% CI: 0.03; 0.32) higher Z scores in IQ, or about 2.1 points. There was no strong evidence of interaction, with pooled covariate-adjusted interaction coefficients (i.e., difference between genetic groups of the difference in IQZ scores comparing ever with never breastfed individuals) of 0.12 (95% CI: -0.19; 0.43) and 0.06 (95% CI: -0.16; 0.27) for the rs174575 and rs1535 variants, respectively. Secondary analyses corroborated these results. In studies with >5.85 and <5.85 months of breastfeeding duration, pooled estimates for the rs174575 variant were 0.50 (95% CI: -0.06; 1.06) and 0.14 (95% CI: -0.10; 0.38), respectively, and 0.27 (95% CI: -0.28; 0.82) and -0.01 (95% CI: -0.19; 0.16) for the rs1535 variant. However, between-group comparisons were underpowered.\n\nConclusionsOur findings do not support an interaction between ever breastfeeding and FADS2 polymorphisms. However, our subgroup analysis raises the possibility that breastfeeding supplies LC-PUFAs requirements for cognitive development (if such threshold exists) if it lasts for some (currently unknown) time. Future studies in large individual-level datasets would allow properly powered subgroup analyses and would improve our understanding on the role of breastfeeding duration in the breastfeedingxFADS2 interaction.

epidemiology↗

bioRxiv2017

Relative quantification of Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia and Aggregatibacter actinomycetemcomitans high-risk bacterial species in Romanian patients evaluated for periodontal disease

Three bacterial species pertaining to the red complex (Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia) and Aggregatibacter actinomycetemcomitans were investigated in relation to the incidence and severity of periodontal disease. A total of 259 patients were included in this study, 179 being diagnosed with periodontal disease. The gingival crevicular fluid samples were obtained from periodontal pockets and the presence and levels of target bacteria were assessed following DNA extraction and real-time quantitative PCR. Our results account for significant positive associations between the number of bacterial species from the red complex coexisting within a patient and several clinical signs (gingival bleeding, inflammation and bone deterioration). A similar positive association was found between bacterial load of the red complex species and the clinical Case Type diagnostic of the periodontal disease, as well as the probing depth with the most evident results for T. denticola. In conclusion, our study, a first for the Romanian population, confirms previous results found elsewhere and finds a possible regional pathogenic specificity for T. denticola as a major factor for periodontitis severity.

epidemiology↗

bioRxiv2017

Dose-dependent effects of inhaled corticosteroids on bone mineral density in postmenopausal women with asthma or COPD: A registry-based cohort study

BackgroundThe effect of long-term inhaled corticosteroid (ICS) therapy on the bone health of older adults remains unclear due to its possible impact on bone mineral density (BMD).\n\nObjectiveTo evaluate, cross-sectionally and longitudinally, the impact of ICS use on BMD in postmenopausal women with asthma or chronic obstructive pulmonary disease (COPD).\n\nMethodsWe used a population-based bone densitometry registry linked with administrative health data of the province of Manitoba, Canada (1999-2013), to identify women with diagnosed asthma or COPD. ICS use was defined as cumulative dispensed days prior to baseline BMD (cross-sectional analysis), and medication possession ratio (MPR) between two BMD measurements (longitudinal analysis). Results were adjusted for multiple covariates including the underlying respiratory diagnosis and its severity.\n\nResultsIn the cross sectional analysis, compared with non-users, women with the highest tertile of prior ICS exposure had lower baseline BMD at the femoral neck (-0.09 standard deviations [SD] below a healthy young adult, 95% CI: -0.16, -0.02) and total hip (-0.14 SD, 95% CI: -0.22, -0.05), but not at the lumbar spine. Longitudinally, the highest tertile of ICS exposure was associated with a slight decline in total hip BMD relative to non-users (-0.02 SD/year, 95% CI: -0.04, -0.01), with no significant effect at the femoral neck and lumbar spine. Middle and lower tertiles of ICS use had no significant effects.\n\nConclusionHigh exposure to ICS was associated with a small adverse effect on baseline hip BMD and total hip BMD loss in post-menopausal women with asthma or COPD.

epidemiology↗

bioRxiv2017

Characterising undiagnosed chronic obstructive pulmonary disease: a systematic review and meta-analysis

BackgroundA significant proportion of patients with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Characterising these patients can increase our understanding of the hidden burden of COPD and the effectiveness of case detection interventions.\n\nMethodsWe conducted a systematic review and meta-analysis to compare patient and disease risk factors between patients with undiagnosed persistent airflow limitation and those with diagnosed COPD. We searched MEDLINE and EMBASE for observational studies of adult patients meeting accepted spirometric definitions of COPD. We extracted and pooled summary data on the proportion or mean of each risk factor among diagnosed and undiagnosed patients (unadjusted analysis), and coefficients for the adjusted association between risk factors and diagnosis status (adjusted analysis). This protocol is registered with PROSPERO (CRD42017058235).\n\nFindings2,083 records were identified through database searching and 16 articles were used in the meta-analyses. Diagnosed patients were less likely to have mild (v. moderate to very severe) COPD (odds ratio [OR] 0{middle dot}30, 95% CI 0{middle dot}24-0{middle dot}37, 6 studies) in unadjusted analysis. This association remained significant but its strength was attenuated in the adjusted analysis (OR 0{middle dot}72, 95% CI 0{middle dot}58-0{middle dot}89, 2 studies). Diagnosed patients were more likely to report respiratory symptoms such as wheezing (OR 3{middle dot}51, 95% CI 2{middle dot}19-5{middle dot}63, 3 studies) and phlegm (OR 2{middle dot}16, 95% CI 1{middle dot}38-3{middle dot}38, 3 studies), had more severe dyspnoea (modified Medical Research Council scale mean difference 0{middle dot}52, 95% CI 0{middle dot}40-0{middle dot}64, 3 studies) and slightly greater smoking history than undiagnosed patients. Patient age, sex, current smoking status, and the presence of coughing were not associated with a previous diagnosis.\n\nInterpretationPatients with undiagnosed persistent airflow limitation had less severe airflow obstruction and fewer respiratory symptoms than diagnosed patients. This indicates that there is lower disease burden among undiagnosed patients compared to those with diagnosed COPD, which may significantly delay the diagnosis of COPD.\n\nFundingCanadian Institutes of Health Research.\n\nDeclaration of interestsWe declare no competing interests.\n\nAuthor ContributionsMS, SB, and KJ formulated the study idea and designed the study. KJ and SG performed all data analyses and MS, SB and DS contributed to interpretation of findings. KJ wrote the first draft of the manuscript. All authors critically commented on the manuscript and approved the final version. MS is the guarantor of the manuscript.

epidemiology↗

bioRxiv2017

A novel data-driven model for real-time influenza forecasting

We provide data-driven machine learning methods that are capable of making real-time influenza forecasts that integrate the impacts of climatic factors and geographical proximity to achieve better forecasting performance. The key contributions of our approach are both applying deep learning methods and incorporation of environmental and spatio-temporal factors to improve the performance of the influenza forecasting models. We evaluate the method on Influenza Like Illness (ILI) counts and climatic data, both publicly available data sets. Our proposed method outperforms existing known influenza forecasting methods in terms of their Mean Absolute Percentage Error and Root Mean Square Error. The key advantages of the proposed data-driven methods are as following: (1) The deep-learning model was able to effectively capture the temporal dynamics of flu spread in different geographical regions, (2) The extensions to the deep-learning model capture the influence of external variables that include the geographical proximity and climatic variables such as humidity, temperature, precipitation and sun exposure in future stages, (3) The model consistently performs well for both the city scale and the regional scale on the Google Flu Trends (GFT) and Center for Disease Control (CDC) flu counts. The results offer a promising direction in terms of both data-driven forecasting methods and capturing the influence of spatio-temporal and environmental factors for influenza forecasting methods.

epidemiology↗

bioRxiv2017

Review of UNAIDS national estimates of men who have sex with men, gay dating application users, and HIV 90-90-90 data

BackgroundAchieving the 90-90-90 is essential to keep people alive and to end AIDS. Men who have sex with men (MSM) often have the least access to HIV services.\n\nPurposeEstimates for key populations are often unavailable, dated or have very wide confidence intervals and more accurate estimates are required.\n\nMethodsWe compared registered users from a major gay dating application (2016) from 29 countries with the latest available (2013-2016) UNAIDS estimates by country. We searched the Internet, PubMed, national surveillance reports, UNAIDS country reports, Presidents Emergency Plan for AIDS Relief (PEPFAR) 2016 and 2017 operational plans, and conference abstracts for the latest nationally representative continua for MSM.\n\nResultsOf comparison countries, only 18 countries had UNAIDS or other MSM population estimates in the public domain. UNAIDS estimates were larger than the gay dating application users in 9 countries, perhaps reflecting incomplete market penetration for the application. The gay dating application users in 9 countries were above the UNAIDS estimates; 8 were over 30% higher and three more than double the reported estimate. Seven partial or complete nationally representative care continua for MSM were published between 2010 and 2016. Among estimated MSM living with HIV, viral suppression varied between 42% (United States) to 99% (Denmark). The quality of the continua methods varied (quality data not shown).\n\nConclusion\"What is not monitored is not done\" and social media has significant promise to improve estimates to ensure that MSM and other vulnerable people living with HIV and their communities are not left behind on the way to ending AIDS.

epidemiology↗

bioRxiv2017

Clustering of adult-onset diabetes into novel subgroups guides therapy and improves prediction of outcome

BackgroundDiabetes is presently classified into two main forms, type 1 (T1D) and type 2 diabetes (T2D), but especially T2D is highly heterogeneous. A refined classification could provide a powerful tool individualize treatment regimes and identify individuals with increased risk of complications already at diagnosis.\n\nMethodsWe applied data-driven cluster analysis (k-means and hierarchical clustering) in newly diagnosed diabetic patients (N=8,980) from the Swedish ANDIS (All New Diabetics in Scania) cohort, using five variables (GAD-antibodies, BMI, HbA1c, HOMA2-B and HOMA2-IR), and related to prospective data on development of complications and prescription of medication from patient records. Replication was performed in three independent cohorts: the Scania Diabetes Registry (SDR, N=1466), ANDIU (All New Diabetics in Uppsala, N=844) and DIREVA (Diabetes Registry Vaasa, N=3485). Cox regression and logistic regression was used to compare time to medication, time to reaching the treatment goal and risk of diabetic complications and genetic associations.\n\nFindingsWe identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease, but had been prescribed similar diabetes treatment compared to the less susceptible individuals in clusters 4 and 5. The insulin deficient cluster 2 had the highest risk of retinopathy. In support of the clustering, genetic associations to the clusters differed from those seen in traditional T2D.\n\nInterpretationWe could stratify patients into five subgroups predicting disease progression and development of diabetic complications more precisely than the current classification. This new substratificationn may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.\n\nFundingThe funders of the study had no role in study design, data collection, analysis, interpretation or writing of the report.\n\nResearch in contextEvidence before this study\n\nThe current diabetes classification into T1D and T2D relies primarily on presence (T1D) or absence (T2D) of autoantibodies against pancreatic islet beta cell autoantigens and age at diagnosis (earlier for T1D). With this approach 75-85% of patients are classified as T2D. A third subgroup, Latent Autoimmune Diabetes in Adults (LADA,<10%), is defined by presence of autoantibodies against glutamate decarboxylase (GADA) with onset in adult age. In addition, several rare monogenic forms of diabetes have been described, including Maturity Onset Diabetes of the Young (MODY) and neonatal diabetes. This information is provided by national guidelines (ADA,WHO, IDF, Diabetes UK etc) but has not been much updated during the past 20 years and very few attempts have been made to explore heterogeneity of T2D. A topological analysis of potential T2D subgroups using electronic health records was published in 2015 but this information has not been implemented in the clinic.\n\nAdded value of this study\n\nHere we applied a data-driven cluster analysis of 5 simple variables measured at diagnosis in 4 independent cohorts of newly-diagnosed diabetic patients (N=14755) and identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease.\n\nImplications of the available evidence\n\nThis new sub-stratification may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes

epidemiology↗

bioRxiv2017

Evaluation of Metrics for Benchmarking Antimicrobial Use in the United Kingdom Dairy Industry

The issue of antimicrobial resistance is of global concern across human and animal health. In 2016 the UK government committed to new targets for reducing antimicrobial use (AMU) in livestock. However, though a number of metrics for quantifying AMU are defined in the literature, all give slightly different interpretations.\n\nThis paper reviews a selection of metrics for AMU in the dairy industry: total mg, total mg/kg, daily dose and daily course metrics. Although the focus is on their application to the dairy industry, the metrics and issues discussed are relevant across livestock sectors.\n\nIn order to be used widely, a metric should be understandable and relevant to the veterinarians and farmers who are prescribing and using antimicrobials. This means that clear methods, assumptions (and possible biases), standardised values and exceptions should be published for all metrics. Particularly relevant are assumptions around the number and weight of cattle at risk of treatment and definitions of dose rates and course lengths; incorrect assumptions can mean metrics over- or under-represent AMU.\n\nThe authors recommend that the UK dairy industry work towards UK-specific metrics using UK-specific medicine dose and course regimens as well as cattle weights in order to monitor trends nationally.

epidemiology↗

bioRxiv2017

Two diseases, same person: moving towards a combined HIV and TB continuum of care

SettingThe Human Immunodeficiency Virus (HIV) and Mycobacterium tuberculosis syndemic remains a global public health threat. Separate HIV and TB global targets have been set, however, success will depend on achieving combined disease control objectives and care continua.\n\nObjectiveReview available policy, budgets and data to re-conceptualize TB and HIV disease control objectives by combining HIV and TB care continua.\n\nMethodsFor 22 WHO TB and TB/HIV priority countries, we used 2014 and 2015 data from the HIV90-90-90watch website, UNAIDS Aidsinfo, and WHO 2016 Global TB Report. Global resources available in TB and HIV/TB activities for 2003-2017 was collected from publically available sources.\n\nResultsIn 22 high burden countries people living with HIV (PLHIV) on ART ranged from 9-70%; viral suppression was 38-63%. TB treatment success ranged from 34-94% with 13 (43% HIV/TB burden) countries above 80% TB treatment success. From 2003-2017, global international and domestic resources for HIV-associated TB and TB averaged $2.6 billion per year; the total for 2003-2017 was 39 billion dollars.\n\nConclusionReviewing combined HIV and TB targets demonstrate disease control progress and challenges. Using an integrated HIV and TB continuum supports HIV and TB disease control efforts focused on improving both individual and public health.\n\nFundingNone

epidemiology↗

bioRxiv2017

Ceasing the use of the highest priority critically important antimicrobials does not adversely affect production, health or welfare parameters in dairy cows

Due to scientific, public and political concern regarding antimicrobial resistance (AMR), several EU countries have already taken steps to reduce antimicrobial (AM) usage in production animal medicine, particularly that of the highest priority critically important AMs (HP-CIAs). While veterinarians are aware of issues surrounding AMR, barriers to change such as concerns of reduced animal health, welfare or production may inhibit AM prescribing changes.\n\nFarmers from seven dairy farms in South West England engaged in changing AM use through an active process of education and herd health planning meetings. Prescribing data was collected from veterinary sales records; production and health data were accessed via milk recording and farm-recorded data.\n\nThis study demonstrates that cattle health and welfare - as measured by production parameters, fertility, udder health, mobility data and culling rates - can be maintained and even improved alongside a complete cessation in the use of HP-CIAs as well as an overall reduction of AM use on dairy farms.\n\nThis study also identified a need to consider different metrics when analysing AM use data, including dose-based metrics as well as those of total quantities to allow better representation of the direction and magnitude of changes in AM use.

epidemiology↗

bioRxiv2017

Preliminary results of models to predict areas in the Americas with increased likelihood of Zika virus transmission in 2017.

Numerous Zika virus vaccines are being developed. However, identifying sites to evaluate the efficacy of a Zika virus vaccine is challenging due to the general decrease in Zika virus activity. We compare results from three different modeling approaches to estimate areas that may have increased relative risk of Zika virus transmission during 2017. The analysis focused on eight priority countries (i.e., Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama, and Peru). The models projected low incidence rates during 2017 for all locations in the priority countries but identified several subnational areas that may have increased relative risk of Zika virus transmission in 2017. Given the projected low incidence of disease, the total number of participants, number of study sites, or duration of study follow-up may need to be increased to meet the efficacy study endpoints.

epidemiology↗

bioRxiv2017

Food environments and obesity: cannot see the fat for the restaurants?

We recently showed that across the mainland USA there is no association between the density of fast food and full service restaurants and the prevalence of obesity. In a recent editorial it was suggested there are 4 problems with our analysis. The suggested problems were the area of analysis may not reflect adequately the exposure to different outlets, using the absolute numbers of restaurants rather than their ratio, using a global model which assumes the same relationship across all sites and finally the potential for residual confounding. In this short note we address all four of these issues and provide some new analysis of the impact of the ratio of restaurant types on obesity prevalence showing there is only a very weak association (r2 = 0.006). We conclude that none of the supposed weaknesses in our original analysis are valid.

epidemiology↗

bioRxiv2017

The Microbiomes of Pancreatic Tissue in Pancreatic Cancer and Non-Cancer Subjects

ObjectiveTo determine whether bacteria are present in the pancreas of pancreatic cancer and non-cancer subjects and examine whether bacterial profiles vary by site and disease phenotype.\n\nDesign77 patients requiring surgery for pancreatic diseases, or diseases of the foregut, at the Rhode Island Hospital (RIH) were recruited into this study between 2014 and 2016. In addition, 36 whole pancreas were obtained from the National Disease Research Interchange (NDRI) from subjects who were of similar age as the RIH patients and had not died of cancer. The primary exposure of interest was the measurement of the relative abundance of bacterial taxa in all tissue specimens using 16S rRNA gene sequencing.\n\nResultsNumber of bacterial reads per sample varied substantially across sample type and patients, but all demonstrated the presence of diverse gastrointestinal bacteria, including bacterial taxa typically identified in the oral cavity. Bacterial profiles were noted to be more similar within individuals across sites in the pancreas, than between individuals by site, suggesting that the pancreas as a whole has its own microbiome. Comparing the mean relative abundance of bacterial taxa in pancreatic cancer patients to those without cancer revealed differences in bacterial taxa previously linked to periodontal disease, including Porphyromonas.\n\nConclusionsBacterial taxa known to inhabit the oral cavity, as well as the intestine, were identified in pancreatic tissue of cancer and non-cancer subjects. Whether any of these bacteria play a causal role in pancreatic carcinogenesis, or are simply opportunistic in nature, needs to be further examined.

epidemiology↗

bioRxiv2017

fingertipsR: an R package for accessing population health information in England

Fingertips is a major public repository of population and public health indicators for England, built and maintained by Public Health England (PHE). The indicators are arranged in thematic or topical profiles covering a wide range of health issues including:\n\nO_LIbroad Health Profiles\nC_LIO_LIspecific topics such as liver disease and end of life\nC_LIO_LIrisk factors including alcohol, smoking, physical activity\nC_LIO_LIpopulation healthcare health services data for general practices, cancer, mental health\nC_LIO_LIhealth protection data on general health protection, TB, antimicrobial resistance\nC_LIO_LIlifecourse profiles for younger and older people\nC_LIO_LImortality and morbidity.\nC_LI\n\nFingertips makes data available for more than 1,500 indicators spread across more than 70 profiles. The data can be accessed from https://fingertips.phe.org.uk where the data are visualised in variety of ways including heatmaps, choropleth maps, line charts for trends, \"spine\" charts (graphs which compare multiple indicators for a single geographic area), scatter plots and so on. Data can be obtained as downloads or figures which can be exported or cut and paste into reports and slides.\n\nA recent addition to the Fingertips platform was an Automated Programming Interface (API) to enable developers to re-use the data. To facilitate access to Fingertips data we have designed an R package - fingertipsR - enabling rapid and easy access to the data by analysts and data scientists. The package is available from the Comprehensive R Archive Network (CRAN).\n\nThis paper describes the fingertipsR package which provides tools accessing a wide range of public health data for England from the Fingertips website using its API.

epidemiology↗

bioRxiv2017

Sociodemographic patterning in the oral microbiome of a diverse sample of New Yorkers

11.1 PurposeVariations in the oral microbiome are potentially implicated in social inequalities in oral disease, cancers, and metabolic disease. We describe sociodemographic variation of oral microbiomes in a diverse sample.\n\n1.2 MethodsWe performed 16S rRNA sequencing on mouthwash specimens in a subsample (n=282) of the 2013-14 population-based New York City Health and Nutrition Examination Study (NYC-HANES). We examined differential abundance of 216 operational taxonomic units (OTUs), and alpha and beta diversity by age, sex, income, education, nativity, and race/ethnicity. For comparison, we also examined differential abundance by diet, smoking status, and oral health behaviors.\n\n1.3 Results69 OTUs were differentially abundant by any sociodemographic variable (false discovery rate < 0.01), including 27 by race/ethnicity, 21 by family income, 19 by education, three by sex. We also found 49 differentially abundant by smoking status, 23 by diet, 12 by oral health behaviors. Genera differing for multiple sociodemographic characteristics included Lactobacillus, Prevotella, Porphyromonas, Fusobacterium.\n\n1.4 ConclusionsWe identified oral microbiome variation consistent with health inequalities, with more taxa differing by race/ethnicity than diet, and more by SES variables than oral health behaviors. Investigation is warranted into possible mediating effects of the oral microbiome in social disparities in oral, metabolic and cancers.\n\nHighlightsO_LIMost microbiome studies to date have had minimal sociodemographic variability, limiting what is known about associations of social factors and the microbiome.\nC_LIO_LIWe examined the oral microbiome in a population-based sample of New Yorkers with wide sociodemographic variation.\nC_LIO_LINumerous taxa were differentially abundant by race/ethnicity, income, education, marital status, and nativity.\nC_LIO_LIFrequently differentially abundant taxa include Porphyromonas, Fusobacterium, Streptococcus, and Prevotella, which are associated with oral and systemic disease.\nC_LIO_LIMediation of health disparities by microbial factors may represent an important intervention site to reduce health disparities, and should be explored in prospective studies.\nC_LI

epidemiology↗

bioRxiv2017

Association of a biomarker-based frailty index with telomere length in older US adults: Findings from NHANES 1999-2002

ObjectivesTo study the link between frailty and cellular senescence, we examine the association of leukocyte telomere length (LTL) with a recently introduced measure of subclinical frailty that is based entirely on laboratory test biomarkers (FI-LAB).\n\nMethodsThis study was conducted on a random sample of 1890 Americans aged 60+. Multiple Linear Regression was used to examine the relationship between FI-LAB and LTL.\n\nResultsA statistically significant association was found between FI-LAB and LTL after adjusting for multiple covariates, indicating that higher FI-LAB scores are associated with shorter telomeres.\n\nDiscussionOur study results establish a link between subclinical frailty (FI-LAB) and cellular aging, which may help elucidate the pathophysiological mechanisms giving rise to frailty.

epidemiology↗