Bayesian Hierarchical Regression Model Research Articles

Assessing the effect of socioeconomic factors on prevalence of dyslipidemia among iranian adult population; district level analysis from 2016 STEPS national study using small area estimation.

Atherosclerotic Cardiovascular Disease (CVD) is the leading cause of death globally and dyslipidemia plays a critical role in the development of this condition. This study aimed to analyze the potential impact of socioeconomic factors on the prevalence of dyslipidemia at district level in Iran. Understanding these factors is important for development of future risk factor control programs. We used the nationwide Iran STEPwise approach to risk factor Surveillance (STEPS) 2016 survey as a representative dataset on the Non-Communicable Diseases (NCDs) risk factors in Iran. To obtain a district level dyslipidemia estimates, we utilized the small area estimation method with a Bayesian spatial hierarchical multilevel regression and multilevel mixed models. The principal component analysis was applied to derive household wealth index. For evaluation of education, successful years of schooling was calculated at district level. Urbanization ratio was defined as the proportion of residents in the urban area to the urban and rural areas for each district. The highest difference was found for hypercholesterolemia coverage with 9.11 times difference among the lowest and highest prevalence across the country's district for males. Men with lower income, lower urbanization, and lower education levels had lower values of high-density lipoprotein (HDL) cholesterol, and higher level of hypercholesterolemia, and hypertriglyceridemia (P-value < 0.001). Triglyceride levels were directly correlated with all analyzed socioeconomic factors in both females and males (P-value < 0.001). We demonstrated that there is an inverse relationship between socioeconomic levels and dyslipidemia indices as populations with higher socioeconomic levelsconsistently had higher mean dyslipidemia levels. Our findings provide an excellent fundamental framework for healthcare administrators and policymakers to set goals and pursue effective preventive strategies. The online version contains supplementary material available at 10.1007/s40200-022-01027-x.

Hierarchical Bayesian Gaussian process regression model for loss reserving using combinations of squared exponential kernels

This paper extends the work of Lally and Hartman (2018) on the Gaussian Process (GP) regression with input warping to model claims development and to estimate loss reserves. In an attempt to provide more structure to the loss reserving GP model in improving predictive accuracy and reducing predictive uncertainties, the effects of applying combinations of additive and multiplicative squared exponential kernels into the GP model are being studied. There are evidences of improvements in the estimates of loss reserves when any form of additive kernel is applied in the GP model compared to the multiplicative squared exponential kernel that was proposed in the earlier work.

Equity in antenatal care visits among adolescent mothers: An analysis of 54 country levels trend and projection of coverage from 2000 to 2030.

BackgroundEnsuring utilization of antenatal care (ANC) services by adolescent mothers (ages 10-19) is an enormous challenge in low-and middle-income countries (LMICs). This study provides the first comprehensive analysis of ANC visits among adolescent and adult mothers.MethodsUsing all available Demographic and Health Survey and Multiple Indicator Cluster Surveys between 2000 and 2019 in 54 LMICs, we estimated proportion of ANC visits among women. Bayesian hierarchical regression models were used to estimate trend, projection, and determinants of single and four ANC visits (ANC1 and ANC4) independently. Equity analysis were performed to assess the magnitude of wealth-based and urban-rural inequalities in access to ANC visits.ResultsCompared to women aged 36-49 years, coverage of ANC1 and ANC4 are expected to increase significantly for adolescent mothers and women aged 20-35 years. This increase was observed at the national level, as well as both urban and rural areas in most countries between 2000 and 2030. By 2030, the coverage of ANC1 is predicted to reach 80% or more in all countries except Angola, Central African Republic and Togo, whereas only 16 countries are predicted to reach 80% or more for ANC4. According to wealth quintile, the lowest inequalities with highest coverage of 80% or more ANC4 will be observed in Armenia, Cambodia, Dominican Republic, Ghana, Maldives, Indonesia, and Sao Tome and Principe in 2030. Determinant analysis found increased odds of receiving ANC visits during pregnancy for adolescent mothers with higher educational levels, frequency of listening/watching mass media, and various household socio-economic status factors.ConclusionsThis study calls for advanced, innovative and cost-effective approaches to increase ANC coverage among adolescent mothers, particularly in rural areas and/or in low socioeconomic groups.

Extrinsic and intrinsic factors affecting the activity budget of alpine marmots (Marmota marmota)

Extrinsic and intrinsic factors may influence the activity budget of wild animals, resulting in a variation in the time spent in different activities among populations or individuals of the same species. In this study, we examined how extrinsic and intrinsic factors affect the behaviour of the alpine marmot (Marmota marmota), a hibernating social rodent inhabiting high-elevation prairies in the European Alps. We collected behavioural observations during scan sampling sessions on marked individuals at two study sites with different environmental characteristics. We used Bayesian hierarchical multinomial regression models to analyse the influence of both intrinsic (sex and age-dominance status) and extrinsic (environmental and climatic variables) factors on the above-ground activity budget. Marmots spent most of their time above ground foraging, and were more likely to forage when it was cloudy. Extrinsic factors such as the site, period of the season (June, July–August, and August–September), and time of the day were all related to the probability of engaging in vigilance behaviour, which reaches its peak in early morning and late afternoon and during July, the second period included in the study. Social behaviours, such as affiliative and agonistic behaviours, were associated mostly with sex and age-dominance status, and yearlings were the more affiliative individuals compared to other status. Overall, our results suggest that in alpine marmots, intrinsic factors mostly regulate agonistic and affiliative behaviours, while extrinsic factors, with the unexpected exception of temperature, affect the probabilities of engaging in all types of behavioural categories.

Trends in gross body coordination and cardiorespiratory fitness-a hierarchical Bayesian Analysis of 35000 2nd Graders.

A negative decline of motor competence in children has been observed over the last decades. Though most studies derive their inferences from only two distant points in time and thus neglect to investigate the variability of the temporal trends. Between the year 2000 and 2011, 35018second graders performed the Körperkoordinationstest für Kinder (KTK), consisting of four items (WB, HH, JS, and MS) and a six minute run test (6MRT). A hierarchical Bayesian regression model with varying intercepts and temporal trends was fitted to the data. Age, sex, and BMI categories were included as input variables. The outcome variables were z-standardized to the initial cohort. In all four KTK items, we observed a yearly decline of -0.020 (95% UI -0.038 to -0.001) for WB, -0.054 (95% UI -0.071, -0.037) for HH, -0.028 (95% UI -0.045 to -0.012) for JS and -0.088 (95% UI -0.108 to -0.067) for MS. For the 6MRT, no trend was identified. Overweight and obese children showed a disadvantage in all tests scores. Negative time interactions were observed for overweight and obese children in HH and JS. A substantial between-city variation for all temporal trends was observed. The predictive validation for all models but MS was successful. A general negative decline was confirmed for coordinative abilities but not in cardiorespiratory fitness. For all outcome variables, a substantial between-city variation was observed, highlighting the importance of environmental factors in motor development. Overweight and obese children demonstrated an urgent need for action.

Unprecedented High Northern Australian Streamflow Linked to an Intensification of the Indo‐Australian Monsoon

AbstractStreamflow in Australia’s northern rivers has been steadily increasing since the 1970s, most likely due to increased intensity in the Indo‐Australian monsoon. However, because of limited data availability, it is hard to assess this recent trend and therefore contextualize potential future climatic changes. In this study, we used a network of 63 precipitation‐sensitive tree‐ring chronologies from the Indo‐Australian and Asian monsoon regions to reconstruct streamflow in the Daly catchment in the Northern Territory of Australia from 1413 to 2005 CE. We used a novel wavelet‐based method to transform the variance structure of the tree‐ring chronologies to better match the hydroclimate prior to reconstruction with a hierarchical Bayesian regression model. Our streamflow reconstruction accounts for 72%–78% of the variance in the instrumental period and closely matches both historical flood events and independent proxy records, increasing confidence in its validity. We find that while streamflow has been increasing since the 1800s, the most recent 40‐year period is unprecedented in the last ∼600 years. Comparison to an independent coral‐based streamflow record shows regional coherency in this trend. Extreme high flows were found to be linked to La Niña events, but we found no significant relationship between streamflow and El Niño events, or streamflow and other regional climatic drivers. More work is therefore needed to understand the drivers of the recent streamflow increase, but, regardless of the cause, water managers should be aware of the paleoclimatic context before making decisions on water allocations.

P49 Determinants of trends in reported antibiotic use for sick children from LMICs (2005–17): analysis of 132 national surveys from 73 countries

ObjectivesTo analyse trends in reported antibiotic use for children aged <5 years with fever, diarrhoea or cough with fast or difficult breathing (outcome) from low- and middle-income countries (LMICs) during 2005–17, disaggregated by the following user characteristics: rural/urban residence, maternal education, household wealth and healthcare source visited.MethodsBased on 132 Demographic and Health Surveys and Multiple Indicator Cluster Surveys from 73 LMICs, the outcome, disaggregated by user characteristics for all country-years was estimated using a hierarchical Bayesian linear regression model.ResultsAcross LMICs during 2005–17, the greatest relative increases in the outcome occurred in rural areas, poorest quintiles and least educated populations, particularly in low-income countries and South-East Asia. In low-income countries, rural areas had a 72% relative increase from 17.8% [uncertainty interval (UI): 5.2%–44.9%] in 2005 to 30.6% (11.7%–62.1%) in 2017, compared with a 29% relative increase in urban areas from 27.1% (8.7%–58.2%) in 2005 to 34.9% (13.3%–67.3%) in 2017. Despite these increases, the outcome was consistently highest in urban areas, wealthiest quintiles, and populations with the highest maternal education.ConclusionsThese estimates suggest that the increasing reported antibiotic use for sick children aged <5 years in LMICs during 2005–17 was driven by gains among groups often underserved by formal health services.

Trend and projection of skilled birth attendants and institutional delivery coverage for adolescents in 54 low- and middle-income countries, 2000\u20132030

BackgroundLimitations to accessing delivery care services increase the risks of adverse outcomes during pregnancy and delivery for all pregnant women, particularly among adolescents in LMICs. In order to inform adolescent-specific delivery care initiatives and coverage, we conducted a comprehensive analysis of trends, projections and inequalities in coverage of delivery care services among adolescents at national, urban-rural and socio-economic levels in LMICs.MethodsUsing 224 nationally representative cross-sectional survey data between 2000 and 2019, we estimated the coverage of institutional delivery (INSD) and skilled birth attendants (SBA). Bayesian hierarchical regression models were used to estimate trends, projections and determinants of INSD and SBA.ResultsCoverage of delivery care services among adolescents increased substantially at the national level, as well as in both urban and rural areas in most countries between 2000 and 2018. Of the 54 LMICs, 24 countries reached 80% coverage of both INSD and SBA in 2018, and predictions for 40 countries are set to exceed 80% by 2030. The trends in coverage of INSD and SBA of adult mothers mostly align with those for adolescent mothers. Our findings show that urban-rural and wealth-based inequalities to delivery care remain persistent by 2030. In 2018, urban settings across 54 countries had higher rates of coverage exceeding 80% compared to rural for both INSD (45 urban, 16 rural) and SBA (50 urban, 19 rural). Several factors such as household head age ≥ 46 years, household head being female, access to mass media, lower parity, higher education, higher ANC visits and higher socio-economic status could increase the coverage of INSD and SBA among adolescents and adult women.ConclusionsMore than three-quarters of the LMICs are predicted to achieve 80% coverage of INSD and SBA among adolescent mothers in 2030, although with sustained inequalities.

Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering

Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal—a region of exceptionally low malaria transmission (entomological inoculation rate less than 1). Genetic identity (identity by state, IBS) was established using a 24-single nucleotide polymorphism molecular barcode, identity by descent was calculated from whole genome sequence data, and a hierarchical Bayesian regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts.

Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study.

Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM2.5). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM2.5 exposure models. The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM2.5 kitchen concentrations (n=2,365) and male and/or female PM2.5 exposure monitoring (n=910) in a subset of households in Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania and Zimbabwe. PURE-AIR measurements were combined with survey data on cooking environment characteristics in hierarchical Bayesian log-linear regression models. Model performance was evaluated using leave-one-out cross validation. Predictive models were applied to survey data from the larger PURE cohort (22,480 households; 33,554 individuals) to quantitatively estimate PM2.5 exposures. The final models explained half (R2=54%) of the variation in kitchen PM2.5 measurements (root mean square error (RMSE) (log scale):2.22) and personal measurements (R2=48%; RMSE (log scale):2.08). Primary cooking fuel type, heating fuel type, country and season were highly predictive of PM2.5 kitchen concentrations. Average national PM2.5 kitchen concentrations varied nearly 3-fold among households primarily cooking with gas (20μg/m3 (Chile); 55μg/m3 (China)) and 12-fold among households primarily cooking with wood (36μg/m3 (Chile)); 427μg/m3 (Pakistan)). Average PM2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile). Using survey data to estimate PM2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction.

Current Inequities in Smoking Prevalence on District Level in Iran: A Systematic Analysis on the STEPS Survey.

Background: The prevalence of tobacco smoking and its burden on societies is not homogenous at the national and district levels. This nationwide study aimed to investigate current inequalities in the prevalence of smoking at the district level and the association of smoking behaviors with gender, wealth, education, and urbanization in Iran. Study design: A cross-sectional study. Methods: This study was conducted by analyzing the data of the STEPS survey 2016 with 30541 participants. The small-area estimation method using the Bayesian spatial hierarchical multilevel regression model was employed to generate district-level prevalence of all types of smoking by gender. The inequalities between the groups by wealth, education, and urbanization were investigated via concentration index. Results: The prevalence rates of current daily cigarette smoking were found to be at the range of 4.6-40.9 and 0-4.5 among men and women, respectively. Current daily cigarette smoking was higher in men than in women: 19.0 (95% CI: 9.5-28.7) vs 0.7 (95% CI: 0-6.9). Women with lower wealth, education, or urbanization were more likely to smoke tobacco or be exposed to secondhand smoking. On the other hand, men with higher wealth or education indices were more likely to smoke tobacco. Men with lower wealth, education, or urbanization were more likely to be exposed to secondhand smoking. Conclusion: The smoking behavior varied significantly at the district level in Iran. Gender, wealth, education, and urbanization were determinants of smoking prevalence.

Predicting thermal satisfaction as a function of indoor CO[formula omitted] levels: Bayesian modelling of new field data

In the pursuit of mitigating the performance gap between model-predicted thermal comfort and measurements of perceived thermal comfort, recent studies have investigated the multi-domain nature of thermal comfort and IEQ. This paper presents an update to a recent work that applied Bayesian logistic regression to examine possible independent correlations between perceived thermal comfort of building occupants and metrics of indoor environmental quality (IEQ) such as CO2 concentrations. The prior work made use of the COPE dataset, a 20-year-old field database of objective and subjective IEQ measurements collected from approximately 800 occupants of open-plan offices in large Canadian and US cities. This study updates that work with a new IEQ field study of 141 workstations carried out at the University of British Columbia across 2019 and 2020. In addition, a new, hierarchical (multi-level) Bayesian logistic regression model is formulated and applied. The new results not only increase the credibility of observing measurements of CO2 concentrations to improve predictions of thermal satisfaction in the original COPE dataset, but that the credibility of this evidence is strengthened on the addition of the new data. At indoor temperatures of 23.5 °C, the probability of an occupant feeling thermally satisfied at measured CO2 levels of 550 ppm was 0.62 [0.54 - 0.69, 95% CrI]. This decreased to 0.28 [0.17-0.42, 95% CrI] at 750 ppm.This study does not suggest these observations are generalizable outside the COPE and UBC datasets, nor does it suggest that CO2 must be affecting occupants physiologically or psychologically to cause these observations. However, it is suggested that CO2 levels may remain overlooked as a contextual, or latent variable for the real-time prediction of perceived thermal comfort in buildings. For instance, prior research has observed a relationship between indoor CO2 levels and perceived air quality as well as a relationship between multiple perceptual factors of IEQ, such as air quality and thermal comfort. If the findings of this paper continue to be found in future studies, measurements of CO2 concentrations may be used to improve the accuracy of thermal comfort prediction models. The core recommendation for future work is therefore to expand measurements in future thermal comfort field studies to include, at least, measurements of indoor CO2 levels. A greater dataset is needed to determine whether the findings of this study are possibly universally applicable, and/or whether knowledge of indoor CO2 concentrations may improve personalized models of thermal comfort that are building- and context-specific.

Hospital and Operator Variation in Cardiac Rehabilitation Referral and Participation After Percutaneous Coronary Intervention: Insights From Blue Cross Blue Shield of Michigan Cardiovascular Consortium.

Despite its established benefit and strong endorsement in international guidelines, cardiac rehabilitation (CR) use remains low. Identifying determinants of CR referral and use may help develop targeted policies and quality improvement efforts. We evaluated the variation in CR referral and use across percutaneous coronary intervention (PCI) hospitals and operators. We performed a retrospective observational cohort study of all patients who underwent PCI at 48 nonfederal Michigan hospitals between January 1, 2012 and March 31, 2018 and who had their PCI clinical registry record linked to administrative claims data. The primary outcomes included in-hospital CR referral and CR participation, defined as at least one outpatient CR visit within 90 days of discharge. Bayesian hierarchical regression models were fit to evaluate the association between PCI hospital and operator with CR referral and use after adjusting for patient characteristics. Among 54 217 patients who underwent PCI, 76.3% received an in-hospital referral for CR, and 27.1% attended CR within 90 days after discharge. There was significant hospital and operator level variation in in-hospital CR referral with median odds ratios of 3.88 (95% credible interval [CI], 3.06-5.42) and 1.64 (95% CI, 1.55-1.75), respectively, and in CR participation with median odds ratios of 1.83 (95% CI, 1.63-2.15) and 1.40 (95% CI, 1.35-1.47), respectively. In-hospital CR referral was significantly associated with an increased likelihood of CR participation (adjusted odds ratio, 1.75 [95% CI, 1.52-2.01]), and this association varied by treating PCI hospital (odds ratio range, 0.92-3.75) and operator (odds ratio range, 1.26-2.82). In-hospital CR referral and 90-day CR use after PCI varied significantly by hospital and operator. The association of in-hospital CR referral with downstream CR use also varied across hospitals and less so across operators suggesting that specific hospitals and operators may more effectively translate CR referrals into downstream use. Understanding the factors that explain this variation will be critical to developing strategies to improve CR participation overall.

Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City

BackgroundThere is growing evidence that exposure to green space can impact mental health, but these effects may be context dependent. We hypothesized that associations between residential green space and mental health can be modified by social vulnerability. MethodWe conducted an ecological cross-sectional analysis to evaluate the effects of green space exposure on mental disorder related emergency room (ER) visits in New York City at the level of census tract. To objectively represent green space exposure at the neighborhood scale, we calculated three green space exposure metrics, namely proximity to the nearest park, percentage of green space, and visibility of greenness. Using Bayesian hierarchical spatial Poisson regression models, we evaluated neighborhood social vulnerability as a potential modifier of greenness-mental disorder associations, while accounting for the spatially correlated structures. ResultsWe found significant associations between green space exposure (involving both proximity and visibility) and total ER visits for mental disorders in neighborhoods with high social vulnerability, but no significant associations in neighborhoods with low social vulnerability. We also identified specific neighborhoods with particularly high ER utilization for mental disorders. ConclusionsOur findings suggest that exposure to green space is associated with ER visits for mental disorders, but that neighborhood social vulnerability can modify this association. Future research is needed to confirm our finding with longitudinal designs at the level of individuals.

Bayesian Variable Selection For Semiparametric Logistic Regression

Lasso variable selection is an attractive approach to improve the prediction accuracy. Bayesian lasso approach is suggested to estimate and select the important variables for single index logistic regression model. Laplace distribution is set as prior to the coefficients vector and prior to the unknown link function (Gaussian process). A hierarchical Bayesian lasso semiparametric logistic regression model is constructed and MCMC algorithm is adopted for posterior inference. To evaluate the performance of the proposed method BSLLR is through comparing it to three existing methods BLR, BPR and BBQR. Simulation examples and numerical data are to be considered. The results indicate that the proposed method get the smallest bias, SD, MSE and MAE in simulation and real data. The proposed method BSLLR performs better than other methods.

A Bayesian meta-analysis of infants' ability to perceive audio-visual congruence for speech.

This paper quantifies the extent to which infants can perceive audio-visual congruence for speech information and assesses whether this ability changes with native language exposure over time. A hierarchical Bayesian robust regression model of 92separate effect sizes extracted from 24studies indicates a moderate effect size in a positive direction (0.35, CI [0.21: 0.50]). This result suggests that infants possess a robust ability to detect audio-visual congruence for speech. Moderator analyses, moreover, suggest that infants' audio-visual matching ability for speech emerges at an early point in the process of language acquisition and remains stable for both native and non-native speech throughout early development. A sensitivity analysis of the meta-analytic data, however, indicates that a moderate publication bias for significant results could shift the lower credible interval to include null effects. Based on these findings, we outline recommendations for new lines of enquiry and suggest ways to improve the replicability of results in future investigations.

Using a coupled-oscillator model of speech rhythm to estimate rhythmic variability in two Brazilian Portuguese varieties (CE and SP)

This paper presents preliminary results of a semi-automatic methodology to extract three parameters of a dynamic model of speech rhythm. The model attempts to analyze the production of rhythm as a system of coupled oscillators which represent syllabicity and phrase stress as levels of temporal organization. The estimated parameters are the syllabic oscillator entrainment rate (alpha), the syllabic oscillator decay rate (beta), and the coupling strength between the oscillators (w0). The methodology involves finding the &lt;alpha, beta, w0&gt; combination that minimizes the distance between natural duration contours and simulated contours generated using several combinations of the parameters. The distance between natural and model-generated contours was measured in two ways by comparing: (1) plain or overt syllable to syllable duration and (2) relative change along both contours.We applied this methodology to read speech produced by five speakers of the state of Ceará (CE) and eight speakers of the state of São Paulo (SP). Mean w0 and alpha values are compatible with the view that Brazilian Portuguese is a mixed-rhythm language. Results from two bayesian hierarchical regression models do not suggest a difference between SP and CE speakers, but indicate a difference between the two methods, with the relative change method generating lower alpha values and higher w0 values, and the reverse for the plain duration method.

1007Vitamin B6 intake, its active form pyridoxal 5’-phosphate, and markers of B6 activity and catabolism

Abstract Background Several biological pathways implicated in cancer risk rely on vitamin B6, which can be measured in its active form pyridoxal 5’-phosphate (PLP). Functional markers of B6 enzymatic activity have been proposed, including the homocysteine:cysteine ratio (Hcy:Cys, a marker of transsulfuration), 3-hydroxykynurenine ratio (HKr, a marker of tryptophan catabolism), and the 4-pyridoxic acid ratio (PAr, a marker of B6 catabolism). We investigated the extent to which these markers are associated with B6 intake. Methods Data from 4,750 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study were included. We estimated the expected percentage change in each of the markers (PLP, Hcy:Cys, HKr, and PAr) for a doubling in B6 intake using log-linear Bayesian hierarchical regression models with log-transformed intake and biomarker data. Results The percent change (posterior mean [95% Credible Interval (CrI)]) for a doubling of B6 intake was 61.0 [51.2, 71.8] for PLP, -12.7 [-15.2, -9.9] for Hcy:Cys, -12.9 [-15.7, -9.9] for HKr, and 1.3 [-3.5, 6.2] for PAr. Conclusions B6 intake is most strongly associated with PLP, but is also associated with functional markers of transsulfuration and tryptophan catabolism, in the direction of increased activity in these pathways. There is no evidence of a linear association between vitamin B6 intake and catabolism. Key messages Our results show differing sensitivity of PLP, markers of tryptophan catabolism and transsulfuration, and vitamin B6 catabolism to B6 intake.

Equity and determinants in universal health coverage indicators in Iraq, 2000\u20132030: a national and subnational study

BackgroundEquity is one of three dimensions of universal health coverage (UHC). However, Iraq has had capital-focused health services and successive conflicts and political turmoil have hampered health services around the country. Iraq has embarked on a new reconstruction process since 2018 and it could be time to aim for equitable healthcare access to realise UHC. We aimed to examine inequality and determinants associated with Iraq’s progress towards UHC targets.MethodsWe assessed the progress toward UHC in the context of equity using six nationally representative population-based household surveys in Iraq in 2000–2018. We included 14 health service indicators and two financial risk protection indicators in our UHC progress assessment. Bayesian hierarchical regression model was used to estimate the trend, projection, and determinant analyses. Slope and relative index of inequality were used to assess wealth-based inequality.ResultsIn the national-level health service indicators, inequality indices decreased substantially from 2000 to 2030. However, the wide inequalities are projected to remain in DTP3, measles, full immunisations, and antenatal care in 2030. The pro-rich inequality gap in catastrophic health expenditure increased significantly in all governorates except Sulaimaniya from 2007 to 2012. The higher increases in pro-rich inequality were found in Missan, Karbala, Erbil, and Diala. Mothers’ higher education and more antenatal care visits were possible factors for increased coverage of health service indicators. The higher number of children and elderly population in the households were potential risk factors for an increased risk of catastrophic and impoverishing health payment in Iraq.ConclusionsTo reduce inequality in Iraq, urgent health-system reform is needed, with consideration for vulnerable households having female-heads, less educated mothers, and more children and/or elderly people. Considering varying inequity between and within governorates in Iraq, reconstruction of primary healthcare across the country and cross-sectoral targeted interventions for women should be prioritised.

Global, regional, and national estimates and trends in stillbirths from 2000 to 2019: a systematic assessment

SummaryBackgroundStillbirths are a major public health issue and a sensitive marker of the quality of care around pregnancy and birth. The UN Global Strategy for Women's, Children's and Adolescents’ Health (2016–30) and the Every Newborn Action Plan (led by UNICEF and WHO) call for an end to preventable stillbirths. A first step to prevent stillbirths is obtaining standardised measurement of stillbirth rates across countries. We estimated stillbirth rates and their trends for 195 countries from 2000 to 2019 and assessed progress over time.MethodsFor a systematic assessment, we created a dataset of 2833 country-year datapoints from 171 countries relevant to stillbirth rates, including data from registration and health information systems, household-based surveys, and population-based studies. After data quality assessment and exclusions, we used 1531 datapoints to estimate country-specific stillbirth rates for 195 countries from 2000 to 2019 using a Bayesian hierarchical temporal sparse regression model, according to a definition of stillbirth of at least 28 weeks’ gestational age. Our model combined covariates with a temporal smoothing process such that estimates were informed by data for country-periods with high quality data, while being based on covariates for country-periods with little or no data on stillbirth rates. Bias and additional uncertainty associated with observations based on alternative stillbirth definitions and source types, and observations that were subject to non-sampling errors, were included in the model. We compared the estimated stillbirth rates and trends to previously reported mortality estimates in children younger than 5 years.FindingsGlobally in 2019, an estimated 2·0 million babies (90% uncertainty interval [UI] 1·9–2·2) were stillborn at 28 weeks or more of gestation, with a global stillbirth rate of 13·9 stillbirths (90% UI 13·5–15·4) per 1000 total births. Stillbirth rates in 2019 varied widely across regions, from 22·8 stillbirths (19·8–27·7) per 1000 total births in west and central Africa to 2·9 (2·7–3·0) in western Europe. After west and central Africa, eastern and southern Africa and south Asia had the second and third highest stillbirth rates in 2019. The global annual rate of reduction in stillbirth rate was estimated at 2·3% (90% UI 1·7–2·7) from 2000 to 2019, which was lower than the 2·9% (2·5–3·2) annual rate of reduction in neonatal mortality rate (for neonates aged <28 days) and the 4·3% (3·8–4·7) annual rate of reduction in mortality rate among children aged 1–59 months during the same period. Based on the lower bound of the 90% UIs, 114 countries had an estimated decrease in stillbirth rate since 2000, with four countries having a decrease of at least 50·0%, 28 having a decrease of 25·0–49·9%, 50 having a decrease of 10·0–24·9%, and 32 having a decrease of less than 10·0%. For the remaining 81 countries, we found no decrease in stillbirth rate since 2000. Of these countries, 34 were in sub-Saharan Africa, 16 were in east Asia and the Pacific, and 15 were in Latin America and the Caribbean.InterpretationProgress in reducing the rate of stillbirths has been slow compared with decreases in the mortality rate of children younger than 5 years. Accelerated improvements are most needed in the regions and countries with high stillbirth rates, particularly in sub-Saharan Africa. Future prevention of stillbirths needs increased efforts to raise public awareness, improve data collection, assess progress, and understand public health priorities locally, all of which require investment.FundingBill & Melinda Gates Foundation and the UK Foreign, Commonwealth and Development Office.