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bioRxiv2018

Access to and use of preventive intermittent treatment for Malaria during pregnancy: a qualitative study in Chokwe district, Southern Mozambique

BackgroundMalaria remains a significant health problem in Mozambique, particularly to pregnant women and children less than five years old. Intermittent preventive treatment is recommended for malaria prevention in pregnancy (IPTp). Despite the widespread use and cost-effectiveness of this intervention, the coverage remains low. In this study, we aimed to explore the factors limiting the access and use of IPTp-SP in Chokwe district.\n\nMethods and findingsWe used qualitative research methods through semi-structured interviews to collect data from 46 pregnant women and four health care staff from Chokwe, a rural area of southern Mozambique. Data were transcribed, manually coded and analysed using content and thematic method. Participants were not aware of pregnancy-related risks of malaria infection or the benefit of malaria prevention in pregnancy. Late and infrequently antenatal care (ANC) attendance, concerns about the long waiting time at ANC consultations,plus reluctance to disclose the pregnancy early, emerged as driving factors for inadequate IPTp delivery.\n\nConclusionsPregnant women experience substantial barriers to receive adequate IPTp-SP dosing for malaria prevention. Poor awareness, non-compliance with ANC attendance and poor attitude of health care staff were main barriers to IPTp-SP delivery. There is a need to strengthen actions that improve awareness about malaria and prevention among pregnant women, as well as quality services across the ANC services in order to increase IPTp-SP uptake.

epidemiology↗

bioRxiv2018

A natural history model for planning prostate cancer testing: calibration and validation using Swedish registry data

Recent prostate cancer screening trials have given conflicting results and it is unclear how to reduce prostate cancer mortality while minimising overdiagnosis and overtreatment. Prostate cancer testing is a partially observable process, and planning for testing requires either extrapolation from randomised controlled trials or, more flexibly, modelling of the cancer natural history.\n\nAn existing US prostate cancer natural history model (Gulati et al, Biostatistics 2010;11:707-719) did not model for differences in survival between Gleason 6 and 7 cancers and predicted too few Gleason 7 cancers for contemporary Sweden. We re-implemented and re-calibrated the US model to Sweden. We extended the model to more finely describe the disease states, their time to biopsy-detectable cancer and prostate cancer survival. We first calibrated the model to the incidence rate ratio observed in the European Randomised Study of Screening for Prostate Cancer (ERSPC) together with age-specific cancer staging observed in the Stockholm PSA (prostate-specific antigen) and Biopsy Register; we then calibrated age-specific survival by disease states under contemporary testing and treatment using the Swedish National Prostate Cancer Register.\n\nAfter calibration, we were able to closely match observed prostate cancer incidence trends in Sweden. Assuming that patients detected at an earlier stage by screening receive a commensurate survival improvement, we find that the calibrated model replicates the observed mortality reduction in a simulation of ERSPC.\n\nUsing the resulting model, we predicted incidence and mortality following the introduction of regular testing. Compared with a model of the current testing pattern, organised 8 yearly testing for men aged 55-69 years was predicted to reduce prostate cancer incidence by 0.11% with no increase in the mortality rate. The model is open source and suitable for planning for effective prostate cancer screening into the future.\n\nAuthor summaryA naive perspective is that cancer screening is simple: people are screened, some cancers are detected early, and cancer mortality rates decline. However, the mathematics for screening becomes difficult quickly, it is hard to infer causation from observational data, and even large randomised screening studies provide limited evidence. Simulations are therefore important for planning cancer screening.\n\nWe found an older US prostate cancer natural history model to be poorly suited for contemporary Sweden. We therefore re-implemented and re-calibrated the US model using data from Swedish registries.\n\nOur revised model, the Stockholm \"Prostata\" model, provides predictions similar to those observed in the detailed Swedish registers on prostate cancer incidence and mortality. By modelling the mechanisms of the screening effect, we can predict the benefits and harms under a range of screening interventions.

epidemiology↗

bioRxiv2018

Targeting hotspots to reduce transmission of malaria in Senegal: modeling of the effects of human mobility

BackgroundIn central Senegal malaria incidences have declined in recent years in response to scaling-up of control measures, but now remains stable, making elimination improbable. Additional control measures are needed to reduce transmission.\n\nMethodsBy using a meta-population mathematical model, we evaluated chemotherapy interventions targeting stable malaria hotspots, using a differential equation framework and incorporating human mobility, and fitted to weekly malaria incidences from 45 villages, over 5 years. Three simulated approaches for selecting intervention targets were compared: a) villages with at least one malaria case during the low transmission season of the previous year; b) villages ranked highest in terms of incidence during the high transmission season of the previous year; c) villages ranked based on the degree of connectivity with adjacent populations.\n\nResultsOur mathematical modeling, taking into account human mobility, showed that the intervention strategies targeting hotspots should be effective in reducing malaria incidence in both treated and untreated areas.\n\nConclusionsMathematical simulations showed that targeted interventions allow increasing malaria elimination potential.

epidemiology↗

bioRxiv2018

Population based hospitalization burden of laboratory-confirmed hand, foot and mouth disease caused by multiple enterovirus serotypes in southern China

BackgroundHand, foot and mouth disease (HFMD) is spread widely across Asia, and the hospitalization burden is as yet not well understood. Here, we estimated serotype-specific and age-specific hospitalization rates of HFMD in Southern China.\n\nMethodsWe enrolled pediatric patients admitted to 3/3 county-level hospitals and 3/23 township level hospitals in Anhua county, Hunan (CN) with HFMD, and collected samples to identify enterovirus serotypes by RT-PCRs between October 2013 and September 2016. The information of other eligible but un-enrolled patients were retrospectively collected from the same six hospitals. Monthly number of hospitalizations for all causes was collected from each of 23 township level hospitals to extrapolate hospitalizations associated with HFMD among these.\n\nResultsDuring the three years, an estimated 3,236 pediatric patients were hospitalized with lab-confirmed HFMD, and among these only one patient was severe. The mean hospitalization rates were 660 (95% CI: 638-684) per 100,000 person-years for lab-confirmed HFMD, with higher rates among CV-A16 and CV-A6 associated HFMD (213 vs 209 per 100,000 person-years), and lower among EV-A71, CV-A10 and other enteroviruses associated HFMD (134, 39 and 66 per 100,000 person-years, p<0.001). Children aged 12-23 months had the highest hospitalization rates (3,594/100,000 person-years), followed by those aged 24-35 months (1,828/100,000 person-years) and 6-11 months (1,572/100,000 person-years). Compared with other serotypes, CV-A6-associated hospitalizations were evident at younger ages.\n\nConclusionsOur study indicates a substantial hospitalization burden associated with non-severe HFMD in a rural county in southern China. Future mitigation policies should take into account the disease burden identified, and optimize interventions for HFMD.

epidemiology↗

bioRxiv2018

Levels of prescribing for four major antibiotic classes and rates of septicemia hospitalization in different US states

BackgroundRates of sepsis/septicemia hospitalization in the US have risen significantly during recent years, and antibiotic resistance and use may contribute to those rates through various mechanisms.\n\nMethodsWe used multivariable linear regression to relate state-specific rates of outpatient prescribing overall for fluoroquinolones, penicillins, macrolides, and cephalosporins between 2011-2012 to state-specific rates of hospitalization with septicemia (ICD-9 codes 038.xx present anywhere on discharge diagnosis) in each of the following age groups of adults: (18-49y, 50-64y, 65-74y, 75-84y, 85+y) reported to the Healthcare Cost and Utilization Project (HCUP) between 2011-2012, adjusting for additional covariates, and random effects associated with the ten US Health and Human Services (HHS) regions.\n\nResultsRates of penicillin prescribing were positively associated with septicemia hospitalization rates in the analyses for persons aged 50-64y, 65-74y, and 74-84y. Percent African Americans in a given age group was positively associated with septicemia hospitalization rates in the analyses for persons aged 75-84y and over 85y. Average minimal daily temperature was positively associated with septicemia hospitalization rates in the analyses for persons aged 18-49y, 50-64y, 75-84y and over 85y.\n\nConclusionsOur results suggest positive associations between the rates of prescribing for penicillins and the rates of sepsis hospitalization in US adults aged 50-84y. Further studies are needed to understand the potential effect of antibiotic replacement in the treatment of various syndromes, such as replacement of fluoroquinolones by other antibiotics, possibly penicillins following the recent US FDA guidelines on restriction of fluoroquinolone use, on the rates of sepsis hospitalization.

epidemiology↗

bioRxiv2018

Antimicrobial resistance prevalence and rates of hospitalization with septicemia in the diagnosis in adults in different US states

ObjectivesRates of hospitalization with sepsis/septicemia and associated mortality in the US have risen significantly during the last two decades. Antibiotic resistance may contribute to the rates of sepsis-related outcomes through lack of clearance of bacterial infections following antibiotic treatment during different stages of infection. However, there is limited information about the relation between prevalence of resistance to various antibiotics in different bacteria and rates of sepsis-related outcomes. MethodsFor different age groups of adults (18-49y,50-64y,65-74y,75-84y,85+y) and combinations of antibiotics/bacteria, we evaluated associations between state-specific prevalence (percentage) of resistant samples for a given combination of antibiotics/bacteria among catheter-associated urinary tract infections in the CDC Antibiotic Resistance Patient Safety Atlas data between 2011-2014 and rates of hospitalization with septicemia (ICD-9 codes 038.xx present on the discharge diagnosis) reported to the Healthcare Cost and Utilization Project (HCUP), as well as rates of mortality with sepsis (ICD-10 codes A40-41.xx present on death certificate). ResultsAmong the different combinations of antibiotics/bacteria, prevalence of resistance to fluoroquinolones in E. coli had the strongest association with septicemia hospitalization rates for individuals aged over 50y, and with sepsis mortality rates for individuals aged 18-84y. A number of positive correlations between prevalence of resistance for different combinations of antibiotics/bacteria and septicemia hospitalization/sepsis mortality rates in adults were also found. ConclusionsOur findings, as well as our related work on the relation between antibiotic use and sepsis rates support the association between resistance to/use of certain antibiotics and rates of sepsis-related outcomes, suggesting the potential utility of antibiotic replacement.

epidemiology↗

bioRxiv2018

Inpatient mobility to predict hospital-onset Clostridium difficile: a network approach

With hospital-onset Clostridium difficile Infection (CDI) still a common occurrence in the U.S., this paper examines the relationship between unit-wide CDI susceptibility and inpatient mobility and creates a predictive measure of CDI called \"Contagion Centrality\". A mobility network was constructed using two years of patient electronic health record (EHR) data within a 739-bed hospital (Jan. 2013 - Dec. 2014; n=72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility. Closeness centrality was a statistically significant measure associated with unit susceptibility (p-value < 0.05), highlighting the importance of incoming patient mobility in CDI prevention at the unit-level. Contagion Centrality (CC) was calculated using incoming inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. This measure is statistically significant (p-value <0.05) with our outcome of hospital-onset CDI cases, and captures the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create an easily interpretable and informative clinical tool showing this relationship and risk of hospital-onset CDI in real-time. Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak, and thus provide clinicians and infection prevention staff with advanced warning and specific location data to concentrate prevention efforts.

epidemiology↗

bioRxiv2018

Geographic shifts in Aedes aegypti habitat suitability in Ecuador using larval surveillance data and ecological niche modeling: implications of climate change for public health vector control

Arboviral disease transmission by Aedes mosquitoes poses a major challenge to public health systems in Ecuador, where constraints on health services and resource allocation call for spatially informed management decisions. Employing a unique dataset of larval occurrence records provided by the Ecuadorian Ministry of Health, we used ecological niche models (ENMs) to estimate the current geographic distribution of Aedes aegypti in Ecuador, using mosquito presence as a proxy for risk of disease transmission. ENMs built with the Genetic Algorithm for Rule-Set Production (GARP) algorithm and a suite of environmental variables were assessed for agreement and accuracy. The top model of larval mosquito presence was projected to the year 2050 under various combinations of greenhouse gas emissions scenarios and models of climate change. Under current climatic conditions, larval mosquitoes were not predicted in areas of high elevation in Ecuador, such as the Andes mountain range, as well as the eastern portion of the Amazon basin. However, all models projected to scenarios of future climate change demonstrated potential shifts in mosquito distribution, wherein range contractions were seen throughout most of eastern Ecuador, and areas of transitional elevation became suitable for mosquito presence. Encroachment of Ae. aegypti into mountainous terrain was estimated to affect up to 4,215 km2 under the most extreme scenario of climate change, an area which would put over 12,000 people currently living in transitional areas at risk. This distributional shift into communities at higher elevations indicates an area of concern for public health agencies, as targeted interventions may be needed to protect vulnerable populations with limited prior exposure to mosquito-borne diseases. Ultimately, the results of this study serve as a tool for informing public health policy and mosquito abatement strategies in Ecuador.\n\nAuthor summaryThe yellow fever mosquito (Aedes aegypti) is a medically important vector of arboviral diseases in Ecuador, such as dengue fever and chikungunya. Managing Ae. aegypti is a challenge to public health agencies in Latin America, where the use of limited resources must be planned in an efficient, targeted manner. The spatial distribution of Ae. aegypti can be used as a proxy for risk of disease exposure, guiding policy formation and decision-making. We used ecological niche models in this study to predict the range of Ae. aegypti in Ecuador, based on agency larval mosquito surveillance records and layers of environmental predictors (e.g. climate, altitude, and human population). The best models of current range were then projected to the year 2050 under a variety of greenhouse gas emissions scenarios and models of climate change. All modeled future scenarios predicted shifts in the range of Ae. aegypti, allowing us to assess human populations that may be at risk of becoming exposed to Aedes vectored diseases. As climate changes, we predict that communities living in areas of transitional elevation along the Andes mountain range are vulnerable to the expansion of Aedes aegypti.

epidemiology↗

bioRxiv2018

The effect of liver enzymes on adiposity: a Mendelian randomization study

Poorer liver function is positively associated with diabetes in Mendelian randomization (MR) studies. Observationally, adiposity is associated with poorer liver function. To clarify the etiology, we assessed the association of liver function with adiposity observationally and using two sample MR for validation.\n\nIn the \"Children of 1997\" birth cohort, we used multivariable linear regression to assess the associations of ALT and alkaline phosphatase (ALP) (IU/L) at [~]17.5 years with body mass index (BMI) (kg/m2). Using MR, genetic variants predicting ALT, ALP and gamma glutamyltransferase (GGT) (100% change in concentration), were applied to genome-wide association studies of BMI, waist circumference (WC) and waist-hip ratio (WHR) (standard deviations) to obtain unconfounded inverse-variance weighting estimates.\n\nObservationally, ALT was positively associated with BMI (0.10, 95% confidence interval (CI) 0.09 to 0.11). ALP was inversely associated with BMI (-0.018, 95% CI -0.024 to -0.012). Using MR, ALT was inversely associated with BMI (-0.14, 95% CI -0.20 to -0.07), but not WC or WHR. ALP and GGT were unrelated to adiposity.\n\nPoorer liver function might not cause adiposity; instead higher ALT might reduce BMI. Whether ALT contributes to diabetes by reducing muscle mass, given the no association of ALT with WC or WHR, requires investigation.\n\nAbbreviations

epidemiology↗

bioRxiv2018

Peripartum cardiomyopathy and hypertensive disorders of pregnancy and cardiovascular events among 1.6 million California pregnancies

BackgroundCardiovascular complications during and soon after pregnancy present an opportunity to assess risk for subsequent cardiovascular disease. We sought to determine whether peripartum cardiomyopathy and hypertensive disorder of pregnancy subtypes predict future myocardial infarction, heart failure, or stroke independent of one another and independent of other risks like gestational diabetes, preterm birth, and intrauterine growth restriction.\n\nMethods and ResultsThe California Healthcare Cost and Utilization Project database was used to identify all hospitalized pregnancies from 2005-2009, with follow-up through 2011, for a retrospective cohort study. Pregnancies, exposures, covariates and outcomes were defined by ICD-9 codes. Among 1.6 million pregnancies (mean age 28y; median follow-up time to event 2.7y), 558 cases of peripartum cardiomyopathy, 123,603 cases of hypertensive disorders of pregnancy, 107,636 cases of gestational diabetes, 116,768 preterm births, and 23,504 cases of intrauterine growth restriction were observed. Using multivariable Cox proportional hazards models, peripartum cardiomyopathy was independently associated with a 13.0-fold increase in myocardial infarction [95%CI, 4.1-40.9], a 39.2-fold increase in heart failure [95%CI, 30.0-51.9], and a 7.7-fold increase in stroke [95%CI, 2.4-24.0]. Hypertensive disorders of pregnancy were associated with a 1.4 [95%CI, 1.0-2.0] to 7.6 [95%CI, 5.4-10.7] fold higher risk of myocardial infarction, heart failure, and stroke. Gestational diabetes, preterm birth, and intrauterine growth restriction had more modest associations with CVD.\n\nConclusionsThese findings support close monitoring of women with cardiovascular pregnancy complications for prevention of early subsequent cardiovascular events and further study of mechanisms underlying their development.

epidemiology↗

bioRxiv2018

Association between long-term air pollution exposure and DNA methylation: the REGICOR study.

BackgroundLimited evidence suggests that epigenetic mechanisms may partially mediate the adverse effects of air pollution on health. Our aims were to identify new genomic loci showing differential DNA methylation associated with long-term exposure to air pollution and to replicate loci previously identified in other studies.\n\nMethodsA two-stage epigenome-wide association study was designed: 630 individuals from the REGICOR study were included in the discovery and 454 participants of the EPIC-Italy study in the validation stage. DNA methylation was assessed using the Infinium HumanMethylation450 BeadChip. NOX, NO2, PM10, PM2.5, PMcoarse, traffic intensity and traffic load exposure were measured according to the ESCAPE protocol. A systematic review was undertaken to identify those cytosine-phosphate-guanine (CpGs) associated with air pollution in previous studies and we screened for them in the discovery study.\n\nResultsIn the discovery stage of the epigenome-wide association study, 81 unique CpGs were associated with air pollution (p-value <10-5) but none of them were validated in the replication sample. Furthemore, we identified 12 CpGs in the systematic review showing differential methylation with a p-value fulfilling the Bonferroni criteria and 1642 CpGs fulfilling the false discovery rate criteria, all of which were related to PM2.5 or NO2. None of them was replicated in the discovery study, in which the top hits were located in an intergenic region on chromosome 1 (cg10893043, p-value=6.79{middle dot}10-5) and in the PXK and ARSA genes (cg16560256, p-value=2.23{middle dot}10-04; cg11953250, p-value=3.64{middle dot}10-04).\n\nConclusionsNeither new genomic loci associated with long-term air pollution were identified, nor previously identified loci were replicated. Continued efforts to test this potential association are warranted.

epidemiology↗

bioRxiv2018

Spatial distribution of mammography adherence in a Swiss urban population and its association with socioeconomic status

PurposeLocal physical and social environment has a defining influence on individual behaviour and health-related outcomes. However, it remains undetermined if its impact is independent of individual socioeconomic status. In this study, we evaluated the spatial distribution of mammography adherence in the state of Geneva (Switzerland) using individual-level data and assessed its independence from socioeconomic status (SES).\n\nMethodsGeo-referenced individual-level data from the population-based cross-sectional Bus Sante study (n = 5,002) were used to calculate local indicators of spatial association (LISA) and investigate the spatial dependence of mammography adherence. Spatial clusters are reported without adjustment; adjusted for neighbourhood income and individual educational attainment; and demographic factors (age and Swiss nationality). The association between adjusted clusters and the proximity to the nearest screening centre was also evaluated.\n\nResultsMammography adherence was not randomly distributed throughout Geneva with clusters geographically coinciding with known SES distributions. After adjustment for SES indicators, clusters were reduced to 56.2% of their original size (n = 1,033). Adjustment for age and nationality further reduced the number of individuals exhibiting spatially dependent behaviour (36.5% of the initial size). The identified SES-independent hot spots and cold-spots of mammography adherence were not explained by proximity to the nearest screening centre.\n\nConclusionsSES and demographic factors play an important role in shaping the spatial distribution of mammography adherence. However, the spatial clusters persisted after confounder adjustment indicating that additional neighbourhood-level determinants could influence mammography adherence and be the object of targeted public health interventions.

epidemiology↗

bioRxiv2018

Increased frequency of travel may act to decrease the chance of a global pandemic

The high frequency of modern travel has led to concerns about a devastating pandemic since a lethal pathogen strain could spread worldwide quickly. Many historical pandemics have arisen following pathogen evolution to a more virulent form. However, some pathogen strains invoke immune responses that provide partial cross-immunity against infection with related strains. Here, we consider a mathematical model of successive outbreaks of two strains - a low virulence strain outbreak followed by a high virulence strain outbreak. Under these circumstances, we investigate the impacts of varying travel rates and cross-immunity on the probability that a major epidemic of the high virulence strain occurs, and the size of that outbreak. Frequent travel between subpopulations can lead to widespread immunity to the high virulence strain, driven by exposure to the low virulence strain. As a result, major epidemics of the high virulence strain are less likely, and can potentially be smaller, with more connected subpopulations. Cross-immunity may be a factor contributing to the absence of a global pandemic as severe as the 1918 influenza pandemic in the century since.

epidemiology↗

bioRxiv2018

On the role of different age groups during pertussis epidemics in California, 2010 and 2014

BackgroundThere is limited information on the roles of different age groups in propagating pertussis outbreaks, and the temporal changes in those roles since the introduction of acellular pertussis vaccines.\n\nMethodsThe relative roles of different age groups in propagating the 2010 and the 2014 pertussis epidemics in California were evaluated using the RR statistic that measures the change in the groups proportion among all detected cases before-vs.-after the epidemic peak.\n\nResultsFor the 2010-11 epidemic, evidence for a predominant transmission age group was weak, with the largest RR estimates being 1.26(95%CI (1.08,1.46)) (aged 11-13y); 1.19(1.01,1.4) (aged 9-10y); 1.17(0.86,1.59) (aged 14-15y); 1.12(0.86,1.46) (aged 16-19y); and 1.1(0.89,1.36) (aged 7-8y). The 2014 epidemic showed a strong signal of the role of older adolescents, with the highest RR estimate being in those aged 14-15y (RR=1.83(1.61,2.07)), followed by adolescents aged 16-19y (RR=1.41(1.24,1.61)) and 11-13y (RR=1.26(1.12,1.41)), with lower RR estimates in other age groups.\n\nConclusionsAs the time following introduction of acellular pertussis vaccines in California progressed, older adolescents played an increasing role in transmission during the major pertussis outbreaks. Booster pertussis vaccination for older adolescents with vaccines effective against pertussis transmission should be considered with the aim of mitigating future pertussis epidemics in the community.

epidemiology↗

bioRxiv2018

Association of age and colostrum discarding with breastfeeding in Ethiopia: systematic review and meta-analyses

IntroductionEven though optimal breastfeeding is important, significantly low percentage of mothers initiate breastfeeding timely and maintain exclusive breastfeeding for 6 months. The aim of this meta-analyses and systematic review was to investigate whether maternal/caregivers age, infant age (0-6 months) and discarding colostrum affects timely initiation of breastfeeding (TIBF) and exclusive breastfeeding (EBF) in Ethiopia.\n\nMethodsA systematic search of PubMed, SCOPUS, EMBASE, CINHAL, Web of Science and WHO Global Health Library electronic databases was done for all English published articles from 2000 to January 2018, supplemented by manual search of identified articles and grey literatures bibliographies. Two reviewers independently screened, extracted and graded the quality studies using Newcastle-Ottawa Scale (NOS). Heterogeneity was assessed using the I2 and Cochran Chi-square statistics. A weighted inverse variance random-effects model meta-analysis was done.\n\nResultA total of 37 articles (i.e., 14 studies on TIBF and 23 on EBF) were included. TIBF was associated with colostrum discarding (Odds ratio (OR) = 0.38, 95% CI = 0.21-0.68) but not with maternal/caregivers age (OR = 0.98, 95% CI = 0.83-1.15). In addition, colostrum discarding (OR = 0.56, 95% CI = 0.37-0.84) and infant age (OR = 1.86, 95% CI = 1.45-2.39) were significantly associated with EBF but not maternal/caregivers age (OR = 1.07, 95% CI = 0.81-1.40).\n\nConclusionThis meta-analyses indicated absence of association between maternal/caregivers age and breastfeeding practice. Colostrum discarding was associated with both EBF and TIBE. This evidence could be helpful to counsel all reproductive age mothers and who discard colostrum.

epidemiology↗

bioRxiv2018

Age Distribution, Trends, and Forecasts of Under-5 Mortality in Sub-Saharan Africa

BackgroundDespite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In Sub-Saharan Africa, the Millennium Development Goals targets for child mortality were met only by a few countries, and recently new targets were set in goals for Sustainable Development that include the eradication of preventable deaths by reducing neonatal and under-5 mortality rates to at least as low 12 and 25 per 1000 live births by 2030, respectively. As the reduction of preventable deaths has a direct impact on their age distribution, the foci of this study are assessing age patterns, trends over time, and forecasts of mortality rates in Sub-Saharan Africa.\n\nMethods and findingsData came from 104 nationally-representative Demographic and Health Surveys with full birth histories from 31 Sub-Saharan African countries from 1990 to 2016 (a total of 448 country-years of data). We assessed the distribution of age at death through the following demographic model. First, we used a direct method for the estimation of death rates with full-birth histories from survey data to construct age profiles of under-5 mortality on a monthly basis. Second, a two-dimensional P-spline approach was used to smooth out raw estimates of death rates by age and time. Third, a variant of the Lee-Carter model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency group for Child Mortality Estimation to adjust, validate and minimize the risk of bias in survival, truncation, and recall in mortality estimation.\n\nOur study has three salient findings. First, we observe a monotonous decline of death rates at every age in most countries, but with notable differences in the age-patterns over time. Second, our projections of continued decline of child mortality differ from existing estimates from the United Nations Inter-agency group for Child Mortality Estimation in 5 countries for both neonatal and under-5 mortality. Finally, we predict that only 5 countries (Guinea, Liberia, Rwanda, Tanzania, and Uganda) are on track to achieve the sustainable development goal targets on child mortality by 2030. Poor data quality issues that include bias in the report of births and deaths, or age heaping, remain a limitation of this study.\n\nConclusionsThis study is the first to combine full birth history data and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in Sub-Saharan Africa. We demonstrate that countries with a rapid pace of mortality reduction across ages would be more likely to achieve the sustainable development goal targets of child mortality reduction. Our mortality model predicts that if neonatal and under-5 deaths decline at the rates observed during the last 25 years, only 5 countries would reach those targets by 2030, 15 would achieve them between 2030 and 2050, and 11 afterwards.

epidemiology↗

bioRxiv2018

Body mass index trajectories preceding first report of poor self-rated health: a longitudinal case-control analysis of the English Longitudinal Study of Ageing

BackgroundStudies have consistently found that obesity is associated with poor self-rated health, but how body mass index (BMI) developed in the lead up to poor self-rated health is unknown.\n\nMethodsWe nested a longitudinal case-control study in the English Longitudinal Study of Ageing (1998-2015) to investigate BMI trajectories in the years preceding a first self-report of poor health. Participants rated their health at each data collection; every other collection included a BMI assessment by a nurse. Case status was defined as a first report of poor health during follow-up. Three age- and sex-matched controls were identified per case using density sampling. BMI trajectories were fitted to time backwards prior to first report of poor health using mixed-effects models. Age and sex were potential modifiers. We conducted subgroup analyses of those not reporting certain chronic diseases or smoking.\n\nResultsWe identified 732 cases and 2195 controls. Age, but not sex, modified the association between BMI and self-rated health. Participants reporting poor health at age 60 had a 1.5 kg/m2 (95%CI: 0.8 to 2.1) higher BMI at the time of reporting than controls, and their BMI had previously increased sharply. After age 75, cases no longer had higher BMI than controls, and their BMI had decreased sharply prior to reporting poor health. Age was also an effect modifier among those without diabetes, however BMI trajectories were more similar among the middle-aged.\n\nConclusionDevelopment of BMI was associated with poor self-rated health; however, the nature of the association depended markedly on age.\n\nO_TEXTBOXWhat is already known on this subjectO_LIStudies based on a single body mass index measurement have consistently found that being underweight or obese was associated with poor self-rated health.\nC_LIO_LIHow body mass index developed in the lead up to poor self-rated health was unknown.\nC_LI\n\nC_TEXTBOX\n\nO_TEXTBOXWhat this study addsO_LIIn the present study, body mass index trajectories leading up to poor self-rated health were strongly dependent on age at first report of poor health. Middle-aged participants with poor self-rated health had higher body mass index than controls; both groups had increasing body mass index over time.\nC_LIO_LIIn contrast, a report of poor health at age 75 or later was preceded by a decrease in body mass index; controls were 10 years older than cases before they started to lose body mass index.\nC_LIO_LIOur results suggest that future prospective studies and clinical decision making should take into account the age-dependent association between development of body mass index preceding poor self-rated health.\nC_LI\n\nC_TEXTBOX

epidemiology↗

bioRxiv2018

What is the impact of gender of new-born, antenatal care and postnatal care on breastfeeding practices in Ethiopia? A systematic review and meta-analysis

ObjectiveThe aim of this systematic review and meta-analysis was to investigate the association of gender of new-born, antenatal care (ANC) and postnatal care (PNC) with timely initiation of breastfeeding (TIBF) and exclusive breastfeeding (EBF) practice in Ethiopia.\n\nDesignSystematic review and meta-analysis\n\nMethodsPubMed, EMBASE, CINAHL, WHO Global Health Library, Web of Science and SCOPUS databases systematically searched and complemented by manual searches to retrieve all available literature. Newcastle-Ottawa Scale (NOS) was used for quality assessment of included studies. Eggers regression test at p-value threshold [≤] 0.01 was used to examine publication bias. Cochrans Q X2 test, {tau}2, and I2 statistics were used to test heterogeneity, estimate amount of total/residual heterogeneity and measure variability attributed to heterogeneity respectively. A meta-analysis using a weighted inverse variance random-effects model was performed. The trend of evidence over time was evaluated by performing a cumulative meta-analysis. Furthermore, mixed-effects meta-regression analysis was done to identify possible sources of heterogeneity.\n\nResultsOf 523 articles retrieved, 17 studies (N = 26,146 mothers) on TIBF and 27 studies (N = 17,819 mothers) on EBF were included in the final analysis. ANC (OR = 2.24, 95% CI 1.65 -3.04, p <0.001, I2 = 90.9%), PNC (OR = 1.86, 95% CI 1.41 - 2.47, p <0.001, I2 = 63.4%) and gender of new-born (OR = 1.31, 95% CI 1.01 - 1.68, p = 0.04, I2 = 81.7%) significantly associated with EBF. In addition, ANC (OR = 1.70, 95% CI 1.10 - 2.65, p = 0.02, I2 = 93.1%) was significantly associated with TIBF but not gender of new-born (OR = 1.02, 95% CI 0.86 -1.21, p = 0.82, I2 = 66.2%).\n\nConclusionsIn line with our hypothesis, gender of new-born, ANC and PNC significantly associated with EBF. Likewise, ANC significantly associated with TIBF. Optimal care during pregnancy and after birth is important to ensure adequate breastfeeding. This meta-analysis study provided evidence on breastfeeding practices and its associated factors in Ethiopian context, which can be useful for cross-country and cross-cultural comparison and for breastfeeding improvement initiative in Ethiopia.\n\nProtocol registration and publicationCRD42017056768 and 10.1136/BMJOPEN-2017-017437\n\nStrengths and limitations of this studyO_LIThis systematic review and meta-analysis was conducted based on the registered and published protocol.\nC_LIO_LISince it is the first study in Ethiopia, the information could be helpful for future researchers, public health practitioners, and healthcare policymakers.\nC_LIO_LIAlmost all included studies were observational which may hinder causality inference.\nC_LIO_LIPerhaps the results may not be nationally representative given that studies from some regions are lacking.\nC_LIO_LIBased on the conventional methods of the heterogeneity test, a few analyses suffer from high between-study variation.\nC_LI

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