Ecologic versus individual-level sources of bias in ecologic estimates of contextual health effects

TAS2R38 haplotypes, COVID-19 infection, and symptomatology: a cross-sectional analysis of data from the Canadian Longitudinal Study on Aging

The TAS2R38 gene is well known for its function in bitter taste sensitivity, but evidence also suggests a role in innate immunity. TAS2R38 may be relevant in coronavirus disease 2019 (COVID-19), but research findings are inconsistent. The objective of this study was to explore whether common TAS2R38 haplotypes are associated with COVID-19 infection and symptomatology in the Canadian Longitudinal Study on Aging (CLSA). Data from the CLSA COVID-19 Questionnaire and Seroprevalence sub-studies were utilized with CLSA genetic data for common TAS2R38 haplotypes related to bitter taste sensitivity. Haplotypes were categorized into three diplotype groups: [P]AV homozygotes, [P]AV/[A]VI heterozygotes, and [A]VI homozygotes. No significant differences were observed between diplotypes and COVID-19 infection frequency. Among self-reported COVID-19 cases (n = 76), and in uncorrected exploratory analyses, heterozygotes were less likely to report experiencing sinus pain compared to [P]AV homozygotes. Among seroprevalence-confirmed cases (n = 177), [A]VI homozygotes were less likely to report experiencing a sore/scratchy throat compared to [P]AV homozygotes. However, both observations were non-significant upon correction for multiple testing. In this study, TAS2R38 haplotypes were not significantly associated with COVID-19 infection or symptomatology. Nevertheless, in light of some exploratory patterns and conflicting evidence, additional research is warranted to evaluate links between TAS2R38 and innate immunity.

Potential Effects of Long-Term Exposure to Air Pollution on Dementia: A Longitudinal Analysis in American Indians Aged 55 Years and Older

(1) Background: American Indians are disproportionately affected by air pollution, an important risk factor for dementia. However, few studies have investigated the effects of air pollution on the risk of dementia among American Indians. (2) Methods: This retrospective cohort study included a total of 26,871 American Indians who were 55+ years old in 2007, with an average follow-up of 3.67 years. County-level average air pollution data were downloaded from land-use regression models. All-cause dementia was identified using ICD-9 diagnostic codes from the Indian Health Service's (IHS) National Data Warehouse and related administrative databases. Cox models were employed to examine the association of air pollution with dementia incidence, adjusting for co-exposures and potential confounders. (3) Results: The average PM2.5 levels in the IHS counties were lower than those in all US counties, while the mean O3 levels in the IHS counties were higher than the US counties. Multivariable Cox regressions revealed a positive association between dementia and county-level O3 with a hazard ratio of 1.24 (95% CI: 1.02-1.50) per 1 ppb standardized O3. PM2.5 and NO2 were not associated with dementia risk after adjusting for all covariates. (4) Conclusions: O3 is associated with a higher risk of dementia among American Indians.

Ecological Study on Global Health Effects due to Source-Specific Ambient Fine Particulate Matter Exposure

Ambient air pollution of fine particulate matter with diameters less than 2.5 μm (PM2.5) is associated with millions of premature deaths per year, recognized as a leading global health concern. The dose-response relation between ambient PM2.5 exposure and mortality risk is the most fundamental information for assessments of the health effects of PM2.5. The existing dose-response relations were generally developed based on the assumption of equal contribution to toxicity from various sources. However, the sources of PM2.5 may significantly influence health effects. In this study, we conducted an ecological study to investigate the global long-term correlation between source-specific PM2.5 exposure and cause-specific mortality risk (SPECM) based on the regional aggregate data of the publically available official health databases from 528 regions worldwide with a total registered population of 3.2 billion. The results provided preliminary epidemiological evidence for differing chronic health effects across various sources. The relative mortality risks of lung cancer and circulatory diseases were closely correlated with the primary emissions from industrial and residential combustion sources. Chronic lower respiratory diseases were mostly associated with the mass concentration of particulate matter.

The role of firearm and alcohol availability in firearm suicide: A population-based weighted case-control study

Firearm availability has been linked to firearm self-harm, but the joint relationship with alcohol availability, while supported by theory, has not been examined. This study sought to quantify the separate and joint relations of community firearm and alcohol availability with individual-level risk of (fatal and nonfatal) firearm self-harm. We conducted a case-control study of California residents, 2005-2015, using statewide mortality, hospital, firearm transfer, and alcohol license data. We estimated monthly marginal risk differences per 100,000 in the overall population and in white men aged 50+ under various hypothetical changes to firearm and alcohol availability and assessed additive interactions using case-control-weighted g-computation. In the overall population, non-pawn shop firearm dealer density was associated with firearm self-harm (RD: 0.02, 95% CI: 0.003, 0.04) but pawn shop firearm dealer and alcohol outlet densities were not. Secondary analyses revealed a relationship between firearm sales density and firearm self-harm (RD: 0.07, 95% CI: 0.04, 0.10). There were no additive interactions between measures of firearm and alcohol availability. Among older white men, generally the same exposures were related to self-harm as in the overall population, but point estimates were substantially larger. Findings suggest community-level approaches to reducing firearm sales may help mitigate suicide risk.

Small-Area Geographic and Socioeconomic Inequalities in Colorectal Cancer in Cyprus

Colorectal cancer (CRC) is one of the leading causes of death and morbidity worldwide. To date, the relationship between regional deprivation and CRC incidence or mortality has not been studied in the population of Cyprus. The objective of this study was to analyse the geographical variation of CRC incidence and mortality and its possible association with socioeconomic inequalities in Cyprus for the time period of 2000-2015. This is a small-area ecological study in Cyprus, with census tracts as units of spatial analysis. The incidence date, sex, age, postcode, primary site, death date in case of death, or last contact date of all alive CRC cases from 2000-2015 were obtained from the Cyprus Ministry of Health's Health Monitoring Unit. Indirect standardisation was used to calculate the sex and age Standardise Incidence Ratios (SIRs) and Standardised Mortality Ratios (SMRs) of CRC while the smoothed values of SIRs, SMRs, and Mortality to Incidence ratio (M/I ratio) were estimated using the univariate Bayesian Poisson log-linear spatial model. To evaluate the association of CRC incidence and mortality rate with socioeconomic deprivation, we included the national socioeconomic deprivation index as a covariate variable entering in the model either as a continuous variable or as a categorical variable representing quartiles of areas with increasing levels of socioeconomic deprivation. The results showed that there are geographical areas having 15% higher SIR and SMR, with most of those areas located on the east coast of the island. We found higher M/I ratio values in the rural, remote, and less dense areas of the island, while lower rates were observed in the metropolitan areas. We also discovered an inverted U-shape pattern in CRC incidence and mortality with higher rates in the areas classified in the second quartile (Q2-areas) of the socioeconomic deprivation index and lower rates in rural, remote, and less dense areas (Q4-areas). These findings provide useful information at local and national levels and inform decisions about resource allocation to geographically targeted prevention and control plans to increase CRC screening and management.

The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis

BACKGROUND

Racial inequities in maternal mortality in the U.S. continue to be stark.

METHODS

The 2015-2018, 4-year total population, county-level, pregnancy-related mortality ratio (PRM; deaths per 100,000 live births; National Center for Health Statistics (NCHS), restricted use mortality file) was linked with the Public Health Exposome (PHE). Using data reduction techniques, 1591 variables were extracted from over 62,000 variables for use in this analysis, providing information on the relationships between PRM and the social, health and health care, natural, and built environments. Graph theoretical algorithms and Bayesian analysis were applied to PHE/PRM linked data to identify latent networks.

RESULTS

PHE variables most strongly correlated with total population PRM were years of potential life lost and overall life expectancy. Population-level indicators of PRM were overall poverty, smoking, lack of exercise, heat, and lack of adequate access to food.

CONCLUSIONS

In this high-dimensional analysis, overall life expectancy, poverty indicators, and health behaviors were found to be the strongest predictors of pregnancy-related mortality. This provides strong evidence that maternal death is part of a broader constellation of both similar and unique health behaviors, social determinants and environmental exposures as other causes of death.

Association between indoor residual spraying and pregnancy outcomes: a quasi-experimental study from Uganda

BACKGROUND

Malaria is a risk factor for adverse pregnancy outcomes. Indoor residual spraying with insecticide (IRS) reduces malaria infections, yet the effects of IRS on pregnancy outcomes are not well established. We evaluated the impact of a large-scale IRS campaign on pregnancy outcomes in Eastern Uganda.

METHODS

Birth records (n = 59 992) were obtained from routine surveillance data at 25 health facilities from five districts that were part of the IRS campaign and six neighbouring control districts ∼27 months before and ∼24 months after the start of the campaign (January 2013-May 2017). Campaign effects on low birthweight (LBW) and stillbirth incidence were estimated using the matrix completion method (MC-NNM), a machine-learning approach to estimating potential outcomes, and compared with the difference-in-differences (DiD) estimator. Subgroup analyses were conducted by HIV and gravidity.

RESULTS

MC-NNM estimates indicated that the campaign was associated with a 33% reduction in LBW incidence: incidence rate ratio (IRR) = 0.67 [95% confidence interval (CI): 0.49-0.93)]. DiD estimates were similar to MC-NNM [IRR = 0.69 (0.47-1.01)], despite a parallel trends violation during the pre-IRS period. The campaign was not associated with substantial reductions in stillbirth incidence [IRRMC-NNM = 0.94 (0.50-1.77)]. HIV status modified the effects of the IRS campaign on LBW [βIRSxHIV = 0.42 (0.05-0.78)], whereby HIV-negative women appeared to benefit from the campaign [IRR = 0.70 (0.61-0.81)], but not HIV-positive women [IRR = 1.12 (0.59-2.12)].

CONCLUSIONS

Our results support the effectiveness of the campaign in Eastern Uganda based on its benefit to LBW prevention, though HIV-positive women may require additional interventions. The IRS campaign was not associated with a substantively lower stillbirth incidence, warranting further research.

The effect of livestock density on Trypanosoma brucei gambiense and T. b. rhodesiense: A causal inference-based approach

Domestic and wild animals are important reservoirs of the rhodesiense form of human African trypanosomiasis (rHAT), however quantification of this effect offers utility for deploying non-medical control activities, and anticipating their success when wildlife are excluded. Further, the uncertain role of animal reservoirs—particularly pigs—threatens elimination of transmission (EOT) targets set for the gambiense form (gHAT). Using a new time series of high-resolution cattle and pig density maps, HAT surveillance data collated by the WHO Atlas of HAT, and methods drawn from causal inference and spatial epidemiology, we conducted a retrospective ecological cohort study in Uganda, Malawi, Democratic Republic of the Congo (DRC) and South Sudan to estimate the effect of cattle and pig density on HAT risk.

For rHAT, we found a positive effect for cattle (RR 1.61, 95% CI 0.90, 2.99) and pigs (RR 2.07, 95% CI 1.15, 2.75) in Uganda, and a negative effect for cattle (RR 0.88, 95% CI 0.71, 1.10) and pigs (RR 0.42, 95% CI 0.23, 0.67) in Malawi. For gHAT we found a negative effect for cattle in Uganda (RR 0.88, 95% CI 0.50, 1.77) and South Sudan (RR 0.63, 95% CI 0.54, 0.77) but a positive effect in DRC (1.17, 95% CI 1.04, 1.32). For pigs, we found a positive gHAT effect in both Uganda (RR 2.02, 95% CI 0.87, 3.94) and DRC (RR 1.23, 95% CI 1.10, 1.37), and a negative association in South Sudan (RR 0.66, 95% CI 0.50, 0.98). These effects did not reach significance for the cattle-rHAT effect in Uganda or Malawi, or the cattle-gHAT and pig-gHAT effects in Uganda.

While ecological bias may drive the findings in South Sudan, estimated E-values and simulation studies suggest unmeasured confounding and underreporting are unlikely to explain our findings in Malawi, Uganda, and DRC. Our results suggest cattle and pigs may be important reservoirs of rHAT in Uganda but not Malawi, and that pigs—and possibly cattle—may be gHAT reservoirs.

Institutional Racism and Health: a Framework for Conceptualization, Measurement, and Analysis

Despite growing interest in the health-related consequences of racially discriminatory institutional policies and practices, public health scholars have yet to reach a consensus on how to measure and analyze exposure to institutional racism. The purpose of this paper is to provide an overview of the conceptualization, measurement, and analysis of institutional racism in the context of quantitative research on minority health and health disparities in the United States. We begin by providing definitions of key concepts (e.g., racialization, racism, racial inequity) and describing linkages between these ideas. Next, we discuss the hypothesized mechanisms that link exposure to institutional racism with health. We then provide a framework to advance empirical research on institutional racism and health, informed by a literature review that summarizes measures and analytic approaches used in previous studies. The framework addresses six considerations: (1) policy identification, (2) population of interest, (3) exposure measurement, (4) outcome measurement, (5) study design, and (6) analytic approach. Research utilizing the proposed framework will help inform structural interventions to promote minority health and reduce racial and ethnic health disparities.

Ice cleat distribution programmes and ice cleat use among older adults: repeated cross-sectional evidence from 63 municipal interventions in Sweden

INTRODUCTION

Ice cleats may help prevent ice-related falls in places with icy roads, but there is limited evidence about the association between ice cleat distribution and ice cleat use. Our study examined the association between Swedish municipal distribution programmes and ice cleat use among older adults (65+ years).

METHODS

We combined data on municipal ice cleat distribution programmes (n=63) with repeated cross-sectional self-reports of ice cleat use in Sweden from 2007, 2010, 2014 and 2018. Respondents (n=63 234) were classified as exposed if they lived in a municipality with a programme, belonged to an eligible age group and responded after distribution (n=2507). Dose-response was assessed using distributed ice cleat pairs per capita (mean: 0.38). Linear probability models were used to estimate probability differences in ice cleat use between exposed and unexposed respondents, adjusting for age, sex, country of birth, education, survey wave and municipality. Ineligible age groups living in programme municipalities, who should be unaffected by ice cleat distribution, were used for bias assessment.

RESULTS

Exposure to ice cleat distribution programmes was associated with 7.5 percentage points (95% CI 4.2 to 10.9) higher self-reported ice cleat use after confounding adjustment. The association was larger in municipalities that distributed one pair of ice cleats per capita (17.3 percentage points (95% CI 11.2 to 23.4)). No association was found among the ineligible age groups (-2.3 (95% CI -5.5 to 1.0)).

CONCLUSION

Distributing ice cleats to older adults may help increase their use of ice cleats in settings with icy road conditions.

Application of Place-Based Methods to Lung Transplant Medicine

Lung transplantation is an increasingly common lifesaving therapy for patients with fatal lung diseases, but this intervention has a critical limitation as median survival after LT is merely 5.5 years. Despite the profound impact of place-based factors on lung health, this has not been rigorously investigated in LT recipients—a vulnerable population due to the lifelong need for daily life-sustaining immunosuppression medications. There have also been longstanding methodological gaps in transplant medicine where both time and place have not been measured; gaps which could be filled by the geospatial sciences. As part of an exploratory analysis, we studied recipients transplanted at our center over a two-year period. The main outcome was at least one episode of rejection within the first year after transplant. We found recipients averaged 1.7 unique residential addresses, a modest relocation rate. Lung rejection was associated with census tracts of predominantly underrepresented minorities or where English was not the primary language as measured by the social vulnerability index. Census tracts likely play an important role in measuring and addressing geographic disparities in transplantation. In a future paradigm, patient spatial data could become an integrated part of real time clinical care to aid in personalized risk stratification and personalized delivery of healthcare.

Spatial-temporal generalized additive model for modeling COVID-19 mortality risk in Toronto, Canada

This article presents a spatial-temporal generalized additive model for modeling geo-referenced COVID-19 mortality data in Toronto, Canada. A range of factors and spatial-temporal terms are incorporated into the model. The non-linear and interactive effects of the neighborhood-level factors, i.e., population density and average of income, are modeled as a two-dimensional spline smoother. The change of spatial pattern over time is modeled as a three-dimensional tensor product smoother. By fitting this model, the space-time effect can uncover the underlying spatial-temporal pattern that is not explained by the covariates. The performance of the modeling method based on the individual data is also compared to the modeling methods based on the aggregated data in terms of in-sample and out-of-sample predictive checking. The results suggest that the individual-level based analysis provided a better overall model fit and higher predictive accuracy for detecting epidemic peaks in this application as compared to the analysis based on the aggregated data.

Association of neighborhood greenness with severity of hand, foot, and mouth disease

Background

Hand, foot, and mouth disease (HFMD) is an epidemic infectious disease in China. Relationship of neighborhood greenness with human health has been widely studied, yet its association with severe HFMD has not yet been established.

Methods

Individual HFMD cases that occurred in Guangdong province in 2010 were recruited and were categorised into mild and severe cases. Residential greenness was assessed using global land cover data. We used a case-control design (i.e., severe versus mild cases) with logistic regression models to assess the association between neighborhood greenness and HFMD severity. Effect modification was also examined.

Results

A total of 131,606 cases were included, of whom 130,840 were mild cases and 766 were severe cases. In an unadjusted model, HFMD severity increased with higher proportion of neighborhood greenness (odds ratio, OR = 1.029, 95%CI: 1.009–1.050). The greenness-HFMD severity association remained (OR = 1.031, 95%CI: 1.006–1.057) after adjusting for population density, demographic variables and climate variables. Both population density (Z = 4.148, P < 0.001) and relative humidity (Z = -4.297, P < 0.001) modified the association between neighborhood greenness and HFMD severity. In the stratified analyses, a protective effect (OR = 0.769, 95%CI: 0.687–0.860) of greenness on HFMD severity were found in the subgroup of population density being lower than and equal to 5 ln(no.)/km². While in both the subgroups of population density being higher than 5, the greenness had hazard effects (subgroup of > 5 & ≤7: OR = 1.071, 95%CI: 1.024–1.120; subgroup of > 7: OR = 1.065, 95%CI: 1.034–1.097) on HFMD severity. As to relative humidity, statistically significant association between greenness and HFMD severity was only observed in the subgroup of being lower than and equal to 76% (OR = 1.059, 95%CI: 1.023–1.096).

Conclusions

Our study found that HFMD severity is associated with the neighborhood greenness in Guangdong, China. This study provides evidence on developing a prevention strategy of discouraging the high-risk groups from going to the crowded green spaces during the epidemic period.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12444-7.

The impact of changing cigarette smoking habits and smoke-free legislation on orofacial cleft incidence in the United Kingdom: Evidence from two time-series studies

BACKGROUND

Both active and passive cigarette smoking have previously been associated with orofacial cleft aetiology. We aimed to analyse the impact of declining active smoking prevalence and the implementation of smoke-free legislation on the incidence of children born with a cleft lip and/or palate within the United Kingdom.

METHODS AND FINDINGS

We conducted regression analysis using national administrative data in the United Kingdom between 2000-2018. The main outcome measure was orofacial cleft incidence, reported annually for England, Wales and Northern Ireland and separately for Scotland. First, we conducted an ecological study with longitudinal time-series analysis using smoking prevalence data for females over 16 years of age. Second, we used a natural experiment design with interrupted time-series analysis to assess the impact of smoke-free legislation. Over the study period, the annual incidence of orofacial cleft per 10,000 live births ranged from 14.2-16.2 in England, Wales and Northern Ireland and 13.4-18.8 in Scotland. The proportion of active smokers amongst females in the United Kingdom declined by 37% during the study period. Adjusted regression analysis did not show a correlation between the proportion of active smokers and orofacial cleft incidence in either dataset, although we were unable to exclude a modest effect of the magnitude seen in individual-level observational studies. The data in England, Wales and Northern Ireland suggested an 8% reduction in orofacial cleft incidence (RR 0.92, 95%CI 0.85 to 0.99; P = 0.024) following the implementation of smoke-free legislation. In Scotland, there was weak evidence for an increase in orofacial cleft incidence following smoke-free legislation (RR 1.16, 95%CI 0.94 to 1.44; P = 0.173).

CONCLUSIONS

These two ecological studies offer a novel insight into the influence of smoking in orofacial cleft aetiology, adding to the evidence base from individual-level studies. Our results suggest that smoke-free legislation may have reduced orofacial cleft incidence in England, Wales and Northern Ireland.

Mask use in community settings in the context of COVID-19: A systematic review of ecological data

BACKGROUND

The wearing of medical and non-medical masks by the general public in community settings is one intervention that is important for the reduction of SARS-CoV-2 transmission, and has been the subject of considerable research, policy, advocacy and debate. Several observational studies have used ecological (population-level) data to assess the effect of masks on transmission, hospitalization, and mortality at the region or community level.

METHODS

We undertook this systematic review to summarize the study designs, outcomes, and key quality indicators of using ecological data to evaluate the association between mask wearing and COVID-19 outcomes. We searched the World Health Organization (WHO) COVID-19 global literature database up to 5 March 2021 for studies reporting the impact of mask use in community settings on outcomes related to SARS-CoV-2 transmission using ecological data.

FINDINGS

Twenty one articles were identified that analysed ecological data to assess the protective effect of policies mandating community mask wearing. All studies reported SARS-CoV-2 benefits in terms of reductions in either the incidence, hospitalization, or mortality, or a combination of these outcomes. Few studies assessed compliance to mask wearing policies or controlled for the possible influence of other preventive measures such as hand hygiene and physical distancing, and information about compliance to these policies was lacking.

INTERPRETATION

Ecological studies have been cited as evidence to advocate for the adoption of universal masking policies. The studies summarized by this review suggest that community mask policies may reduce the population-level burden of SARS-CoV-2. Methodological limitations, in particular controlling for the actual practice of mask wearing and other preventive policies make it difficult to determine causality. There are several important limitations to consider for improving the validity of ecological data.

Using Multilevel Regression and Poststratification to Estimate Physical Activity Levels from Health Surveys

BACKGROUND

Large-scale health surveys often consider sociodemographic characteristics and several health indicators influencing physical activity that often vary across subpopulations. Data in a survey for some small subpopulations are often not representative of the larger population.

OBJECTIVE

We developed a multilevel regression and poststratification (MRP) model to estimate leisure-time physical activity across Brazilian state capitals and evaluated whether the MRP outperforms single-level regression estimates based on the Brazilian cross-sectional national survey VIGITEL (2018).

METHODS

We used various approaches to compare the MRP and single-level model (complete-pooling) estimates, including cross-validation with various subsample proportions tested.

RESULTS

MRP consistently had predictions closer to the estimation target than single-level regression estimations. The mean absolute errors were smaller for the MRP estimates than single-level regression estimates with smaller sample sizes. MRP presented substantially smaller uncertainty estimates compared to single-level regression estimates. Overall, the MRP was superior to single-level regression estimates, particularly with smaller sample sizes, yielding smaller errors and more accurate estimates.

CONCLUSION

The MRP is a promising strategy to predict subpopulations' physical activity indicators from large surveys. The observations present in this study highlight the need for further research, which could, potentially, incorporate more information in the models to better interpret interactions and types of activities across target populations.

Health care system efficiency and life expectancy: A 140-country study

Despite the evidence of links between health expenditure and health care efficiency, it is still unclear why countries with similar levels of health expenditures experience different outputs in terms of life expectancy at birth. Health care system efficiency might shed some light on the question. Using output-oriented data envelopment analysis, we compared the health systems of 140 countries in terms of attained life expectancy. Efficiency is determined by the distance from the closest country on the best practice frontier, which identifies the highest attainable life expectancy observed for any given level of health care spending. By using national data form the Human Development Data, we built the efficiency frontier and computed the potential life expectancy increase for each country. The potential improvement was, on average, 5.47 years [95%CI: 4.71-6.27 years]. The least efficient countries (10th percentile of the efficiency score) could improve by 11.78 years, while the most efficient countries (90th percentile of the efficiency score) could only improve by 0.83 years. We then analyzed, with regression analysis stratified by average education level, and by the role of health-related variables in differentiating efficient and inefficient countries from each other. The results suggest that, among countries with lower levels of education, decreasing unemployment and income inequality increases average life expectancy, without increasing health expenditure levels.

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data

Electronic health record (EHR)-derived real-world data (RWD) can be sourced to create external comparator cohorts to oncology clinical trials. This exploratory study assessed whether EHR-derived patient cohorts could emulate select clinical trial control arms across multiple tumor types. The impact of analytic decisions on emulation results was also evaluated. By digitizing Kaplan-Meier curves, we reconstructed published control arm results from 15 trials that supported drug approvals from January 1, 2016, to April 30, 2018. RWD cohorts were constructed using a nationwide EHR-derived de-identified database by aligning eligibility criteria and weighting to trial baseline characteristics. Trial data and RWD cohorts were compared using Kaplan-Meier and Cox proportional hazards regression models for progression-free survival (PFS) and overall survival (OS; individual cohorts) and multitumor random effects models of hazard ratios (HRs) for median endpoint correlations (across cohorts). Post hoc, the impact of specific analytic decisions on endpoints was assessed using a case study. Comparing trial data and weighted RWD cohorts, PFS results were more similar (HR range = 0.63-1.18, pooled HR = 0.84, correlation of median = 0.91) compared to OS (HR range = 0.36-1.09, pooled HR = 0.76, correlation of median = 0.85). OS HRs were more variable and trended toward worse for RWD cohorts. The post hoc case study had OS HR ranging from 0.67 (95% confidence interval (CI): 0.56-0.79) to 0.92 (95% CI: 0.78-1.09) depending on specific analytic decisions. EHR-derived RWD can emulate oncology clinical trial control arm results, although with variability. Visibility into clinical trial cohort characteristics may shape and refine analytic approaches.

Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods

Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary.

Invasive disease caused by Group B Streptococcus (GBS) in young infants continues to be a major public health problem in both developed and developing countries. However, data on the incidence of this infection during the first week of life are only available for a small number of countries, which has complicated the quantification of the burden of this disease globally. In this paper, we develop a Bayesian framework to estimate the incidence of invasive GBS infection that combines data from multiple types of epidemiological studies, with adjustment for relevant factors such as diagnostic methods used in the studies. We present estimates from a series of models, and our results highlight the potential weaknesses of different types of studies and the importance to consider the entire evidence when estimating global burden of invasive neonatal infections. We believe this model is a step toward better quantification of the number of cases in different regions.

Converging or diverging trajectories of mortality under one year of age in the Baltic States: a comparison with the European Union

BACKGROUND

Information about trends in perinatal and child health inequalities is scarce, especially in the Eastern Europe. We analyzed how mortality under 1 year of age has been changing in the Baltic States and the European Union (EU) over 25 years, and what associations occurred between changes in macroeconomic factors and mortality.

METHODS

Data on fetal, neonatal, infant mortality, and macroeconomic factors were extracted from WHO database. Joinpoint regression analysis was performed to analyze time trajectories of mortality over 1990-2014. We also investigated how the changes in health expenditures and Gross Domestic Product (GDP) contributed to the changes in mortality.

RESULTS

The reduction of fetal, neonatal and infant mortality in the Baltic countries led to convergence with the EU. In Estonia this process was the fastest, and then the rates tended to diverge. The strongest effect in reduction of neonatal mortality was related to the annual increase in health expenditure and GDP which had occurred in the same year, and a decrease in fetal mortality associated with an increase in health expenditure and GDP in the 4th and 5th year, respectively, following the initial change.

CONCLUSIONS

These findings outlined convergences and divergences in mortality under 1 year of age in the Baltic States compared with the patterns of the EU. Our data highlighted a need to define health policy directions aimed at the implementation of effective intervention modalities addressing reduction of risks in prenatal and early life.

Is Cannabis being used as a substitute for non-medical opioids by adults with problem substance use in the United States? A within-person analysis

BACKGROUND AND AIMS

Ecological studies have suggested that Cannabis legalization might have led to a decrease in opioid overdose deaths. Such studies do not provide information about whether individuals are substituting Cannabis for opioids at different points in time. The current study assessed the magnitude of the daily association between Cannabis and opioid use in individual adults with and without pain who use non-medical opioids.

DESIGN

Prospective cohort study.

SETTING

The greater New York area and a suburban inpatient addiction program.

PARTICIPANTS

Adults with problem substance use who use non-medical opioids, recruited from May 2016-June 2019. The analytical sample included 13 271 days of observation among 211 participants (64% male, 41% white, 78% unmarried, 80% unemployed, mean age 43 years).

MEASUREMENTS

Participants completed interviewer- and self-administered computerized surveys, and then responded to an interactive voice response (IVR) system daily for the following 90 days. The main exposures, Cannabis use and pain, were defined as responding affirmatively to the IVR question: 'Did you use Cannabis yesterday?' and endorsing moderate or severe pain at baseline, respectively. The main outcome, non-medical or illicit opioid use during 90-day follow-up, was defined as responding affirmatively to IVR question: 'Did you use heroin yesterday?' or 'Did you use prescription opioids more than prescribed or without a prescription yesterday?'.

FINDINGS

The mean IVR completion rate was 70%. The unadjusted odds ratio (aOR) indicating same-day use of Cannabis and opioids was 2.00 [95% confidence interval (CI) = 1.54-2.59]. Controlling for demographic characteristics, recruitment method, opioid types at baseline and pain, the aOR was 1.86 (95% CI = 1.44-2.41). A test of interaction between pain and Cannabis use to determine if the association of Cannabis with opioid use differed between people with moderate-to-severe pain and less-than-moderate pain was inconclusive.

CONCLUSIONS

Among US adults with problem substance use who use non-medical opioids, the odds of opioid use appear to be approximately doubled on days when Cannabis is used. This relationship does not appear to differ between people with moderate or more severe pain versus less than moderate pain, suggesting that Cannabis is not being used as a substitute for illegal opioids.

Data quality assessment and subsampling strategies to correct distributional bias in prevalence studies

Background

Healthcare-associated infections (HAIs) represent a major Public Health issue. Hospital-based prevalence studies are a common tool of HAI surveillance, but data quality problems and non-representativeness can undermine their reliability.

Methods

This study proposes three algorithms that, given a convenience sample and variables relevant for the outcome of the study, select a subsample with specific distributional characteristics, boosting either representativeness (Probability and Distance procedures) or risk factors’ balance (Uniformity procedure). A “Quality Score” (QS) was also developed to grade sampled units according to data completeness and reliability.

The methodologies were evaluated through bootstrapping on a convenience sample of 135 hospitals collected during the 2016 Italian Point Prevalence Survey (PPS) on HAIs.

Results

The QS highlighted wide variations in data quality among hospitals (median QS 52.9 points, range 7.98–628, lower meaning better quality), with most problems ascribable to ward and hospital-related data reporting. Both Distance and Probability procedures produced subsamples with lower distributional bias (Log-likelihood score increased from 7.3 to 29 points). The Uniformity procedure increased the homogeneity of the sample characteristics (e.g., − 58.4% in geographical variability).

The procedures selected hospitals with higher data quality, especially the Probability procedure (lower QS in 100% of bootstrap simulations). The Distance procedure produced lower HAI prevalence estimates (6.98% compared to 7.44% in the convenience sample), more in line with the European median.

Conclusions

The QS and the subsampling procedures proposed in this study could represent effective tools to improve the quality of prevalence studies, decreasing the biases that can arise due to non-probabilistic sample collection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01277-y.

Be careful with ecological associations

Ecological studies are observational studies commonly used in public health research. The main characteristic of this study design is that the statistical analysis is based on pooled (i.e., aggregated) rather than on individual data. Thus, patient-level information such as age, gender, income and disease condition are not considered as individual characteristics but as mean values or frequencies, calculated at country or community level. Ecological studies can be used to compare the aggregated prevalence and incidence data of a given condition across different geographical areas, to assess time-related trends of the frequency of a pre-defined disease/condition, to identify factors explaining changes in health indicators over time in specific populations, to discriminate genetic from environmental causes of geographical variation in disease, or to investigate the relationship between a population-level exposure and a specific disease or condition. The major pitfall in ecological studies is the ecological fallacy, a bias which occurs when conclusions about individuals are erroneously deduced from results about the group to which those individuals belong. In this paper, by using a series of examples, we provide a general explanation of the ecological studies and provide some useful elements to recognize or suspect ecological fallacy in this type of studies.

GlaucoMap - Distribution of Glaucoma Surgical Procedures in the United States

PURPOSE

To understand the distribution of trabeculectomies, glaucoma drainage implants (GDI) and micro-invasive glaucoma surgeries (MIGS) performed in the United States through geospatial mapping.

METHODS

We performed an observational cohort study to evaluate glaucoma surgeries in patients age ≥65. The most recently released data from Centers for Medicare Part B Carrier Summary Files were queried to determine the number of glaucoma surgeries performed per state during the year of 2017. We created choropleth maps, titled "GlaucoMap", to characterize the rates of various surgeries performed across the United States, defined as the number of procedures performed per 10,000 individuals. A chi-squared analysis was further used to evaluate differences in surgical preferences across geographic region. Standardized residuals (SR) were calculated to determine regional influences on surgical distribution.

RESULTS

There were 174,788 glaucoma surgeries performed: 22,862 trabeculectomies (13.1%), 19,991 GDI (11.4%) and 131,935 (75.5%) MIGS. The Northeast had the highest trabeculectomy rate, GDI was highest in the Southeast and MIGS were highest in the Southwest. There was a statistically significant difference in proportional use of conventional surgeries versus MIGS across various regions in the United States (p < 0.0001). Given the high trabeculectomy and GDI rates and relatively low MIGS adoption in the Southeast, we observed a +7.03 SR for conventional surgeries and -4.01 SR for MIGS. The Southwest and Western states had the highest MIGS rate and contributed +3.29 and +3.24 SR toward disproportional MIGS preference, respectively. The preference for conventional surgeries in the Northeast (SR = +2.93) and MIGS in the Midwest (SR = +0.99) also contribute to the overall differences in glaucoma surgeries across the United States.

CONCLUSION

GlaucoMap is useful for visualizing the distribution of glaucoma surgeries in the United States. The heterogeneity in surgical preferences points to regional differences in glaucoma management.

How does deprivation influence secondary care costs after hip fracture?

We studied the association between deprivation and healthcare costs after hip fracture. Hospital costs in the year following hip fracture were £1120 higher for those living in more deprived areas. Most of this difference was explained by pre-existing health inequalities which should be targeted to reduce this disparity.

INTRODUCTION

To quantify differences in hospital costs following hip fracture between those living in higher and lower deprivation areas of England, we investigate pre- and post-fracture variables that explain the association.

METHODS

We used English Hospital Episodes Statistics linked to the National Hip Fracture Database (April 2011-March 2015) and national mortality data to identify patients admitted with hip fracture aged 60+ years. Hospital care was costed using 2017/2018 national reference costs, by index of multiple deprivation quintile. Three generalised linear model regressions estimated associations between deprivation and costs and the pre- and post-fracture variables that mediate this relationship.

RESULTS

Patients from the most deprived areas had higher hospital costs in the year post-fracture (£1,120; 95% CI £993 to £1,247) than those from the least deprived areas. If all patients could have incurred similar costs to those in the least deprived quintile, this would equate to an annual reduction in expenditure of £28.8 million. Pre-fracture characteristics, particularly comorbidities and anaesthetic risk grade, accounted for approximately 50% of the association between deprivation and costs. No evidence was found that post-fracture variables, such as transfer to a residential or nursing home, contributed to the association between deprivation and costs.

CONCLUSIONS

Socioeconomic inequalities are associated with substantial costs for the NHS after hip fracture. We did not identify post-fracture targets for intervention to reduce the impact of inequalities on post-fracture costs. The case for interventions to reduce comorbid conditions, improve health-related behaviours and prevent falls in deprived areas is clear but challenging to implement.

U.S. Adults With Pain, a Group Increasingly Vulnerable to Nonmedical Cannabis Use and Cannabis Use Disorder: 2001-2002 and 2012-2013

OBJECTIVE

Given changes in U.S. marijuana laws, attitudes, and use patterns, individuals with pain may be an emerging group at risk for nonmedical cannabis use and cannabis use disorder. The authors examined differences in the prevalence of nonmedical cannabis use and cannabis use disorder among U.S. adults with and without pain, as well as whether these differences widened over time.

METHODS

Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, 2001-2002; N=43,093) and NESARC-III (2012-2013; N=36,309) were analyzed using logistic regression. Risk differences of past-year nonmedical cannabis use, frequent (at least three times a week) nonmedical use, and DSM-IV cannabis use disorder were estimated for groups with and without moderate to severe pain, and these risk differences were tested for change over time.

RESULTS

Any nonmedical cannabis use was more prevalent in respondents with than without pain (2001-2002: 5.15% compared with 3.74%; 2012-2013: 12.42% compared with 9.02%), a risk difference significantly greater in the 2012-2013 data than in the 2001-2002 data. The prevalence of frequent nonmedical cannabis use did not differ by pain status in the 2001-2002 survey, but was significantly more prevalent in those with than without pain in the 2012-2013 survey (5.03% compared with 3.45%). Cannabis use disorder was more prevalent in respondents with than without pain (2001-2002: 1.77% compared with 1.35%; 2012-2013: 4.18% compared with 2.74%), a significantly greater risk difference in the data from 2012-2013 than from 2001-2002.

CONCLUSIONS

The results suggest that adults with pain are a group increasingly vulnerable to adverse cannabis use outcomes, warranting clinical and public health attention to this risk. Psychiatrists and other health care providers treating patients with pain should monitor such patients for signs and symptoms of cannabis use disorder.

A flexible hierarchical framework for improving inference in area-referenced environmental health studies

Study designs where data have been aggregated by geographical areas are popular in environmental epidemiology. These studies are commonly based on administrative databases and, providing a complete spatial coverage, are particularly appealing to make inference on the entire population. However, the resulting estimates are often biased and difficult to interpret due to unmeasured confounders, which typically are not available from routinely collected data. We propose a framework to improve inference drawn from such studies exploiting information derived from individual-level survey data. The latter are summarized in an area-level scalar score by mimicking at ecological level the well-known propensity score methodology. The literature on propensity score for confounding adjustment is mainly based on individual-level studies and assumes a binary exposure variable. Here, we generalize its use to cope with area-referenced studies characterized by a continuous exposure. Our approach is based upon Bayesian hierarchical structures specified into a two-stage design: (i) geolocated individual-level data from survey samples are up-scaled at ecological level, then the latter are used to estimate a generalized ecological propensity score (EPS) in the in-sample areas; (ii) the generalized EPS is imputed in the out-of-sample areas under different assumptions about the missingness mechanisms, then it is included into the ecological regression, linking the exposure of interest to the health outcome. This delivers area-level risk estimates, which allow a fuller adjustment for confounding than traditional areal studies. The methodology is illustrated by using simulations and a case study investigating the risk of lung cancer mortality associated with nitrogen dioxide in England (UK).

Association of endemic goitre and exceptional longevity in Sardinia: evidence from an ecological study

This study aims to test the hypothesis that a high prevalence of endemic goitre, considered as a proxy measure for subclinically reduced thyroid function in the population, is geographically associated with exceptional longevity. Using historical data available for 377 Sardinian municipalities in the first half of the twentieth century, we performed an ecological study to investigate the geographic distribution of goitre and its spatial association with demographic indicators of population longevity. This analysis was conducted by using both conventional ordinary least square and geographically weighted regression models to take into account spatial autocorrelation and included other longevity-associated factors previously identified in Sardinia. The spatial analysis revealed that the goitre rate (p < 0.0001), the proportion of inhabitants involved in pastoralism (p = 0.016), the terrain inclination (p = 0.008), and the distance from the workplace as a proxy for physical activity (p = 0.023) were consistently associated with population longevity at an aggregated level in the 377 municipalities. Within the limits of an ecological study design, our findings support the existence of a significant association between high goitre prevalence and increased probability to survive into old age. The present study confirms previous results and is consistent with animal studies and epidemiological surveys in other long-lived areas known as Blue Zones. Potential mechanisms underlying this association need to be further investigated.

Alcohol Outlet Density and Area-Level Heavy Drinking Are Independent Risk Factors for Higher Alcohol-Related Complaints

Alcohol outlet density has well-documented associations with social and health indicators such as crime and injury. However, significantly less is known about the relationships among alcohol-related complaints. Bayesian hierarchical Poisson regression with spatial autocorrelation was used to model the association between on- and off-premises alcohol outlet density and area-level prevalence of current drinkers and heavy drinking, and graffiti density-an indicator of physical disorder-in association with calls from civilians reporting illegal use, alcohol sales, and other alcohol-related activities (hereafter alcohol-related complaints). Complaints were separated into two groups based on whether they occurred at (a) clubs/bars/restaurants or (b) elsewhere. Alcohol-related complaints and graffiti were collected from NYC Open Data. Alcohol density data are from ESRI Business Analyst and information on the prevalence of drinking from the New York City Community Health Survey. The unit of analysis consisted of ZIP codes in New York City (n = 167), and the design was a cross-sectional analysis of aggregated data between 2009 and 2015. In multivariable models, a one-unit increase in off-premises alcohol outlet density was associated with a 47% higher risk of alcohol-related complaints at clubs, bars, and restaurants [rate ratio (RR = 1.46, 95% CI = 1.21, 1.77)]. Area-level prevalence of heavy drinking was associated with a 59% higher risk of alcohol-related complaints at the club, bars, and restaurants (RR = 1.59, 95% CI = 1.34, 1.86) and a 40% higher risk of complaints elsewhere (RR = 1.40, 95% CI = 1.20, 1.63). In New York City, area-level heavy drinking prevalence is a strong independent mechanism that links alcohol outlet density to alcohol-related complaints. Area-level heavy drinking should be investigated as a predictor of other public health problems such as drug overdose mortality.

Road Traffic Noise Exposure and Birth Outcomes: An Updated Systematic Review and Meta-Analysis

Unlike the other WHO evidence reviews, the systematic review on birth outcomes could not provide a quantitative estimate of the effect of environmental noise. With that in mind, we aimed to update it with additional studies published through to 12 May, 2019 to allow for a formal meta-analysis of the association of residential road traffic noise with birth weight, low birth weight (LBW), small for gestational age (SGA), and preterm birth (PTB). The quality effects and random effects estimators were used for meta-analysis and the robustness of findings was tested in several sensitivity analyses. Nine studies were included in the qualitative synthesis, from which we extracted seven estimates for birth weight (n = 718,136 births) and LBW (n = 620,221), and five for SGA (n = 547,256) and PTB (n = 74,609). We found -8.26 g (95% CI: -20.61 g, 4.10 g) (I2 = 87%) lower birth weight associated with a 10 dB(A) increase in day-evening-night noise level (Lden), and this effect became significant in sensitivity analyses. No evidence of significant effects was found for LBW (OR = 1.06; 95% CI: 0.91, 1.23) (I2 = 49%), SGA (OR = 1.02; 95% CI: 0.86, 1.21) (I2 = 90%), or PTB (OR = 1.00; 95% CI: 0.79, 1.27) (I2 = 69%). The quality of evidence for continuous birth weight was graded as "moderate", while for the other outcomes it was deemed "very low". Finally, we discuss limitations of the risk of bias assessment criteria employed by Nieuwenhuijsen et al.

Small-area socioeconomic deprivation indices in Cyprus: development and association with premature mortality

Background

Area-level measures of socioeconomic deprivation are important for understanding and describing health inequalities. The aim of this study was the development and validation of a small-area index of socioeconomic deprivation for Cypriot communities and the investigation of its association with the spatial distribution of all-cause premature adult mortality.

Methods

Six area-level socioeconomic indicators were used from the 2011 national population census (low educational attainment, unemployment, not owner occupied household, single-person household, divorced or widowed and single-parent households). After normalization and standardization of the geographically smoothed indicators, Principal Component Analysis (PCA) was used to construct indicator weights. The association between deprivation indices and the spatial distribution of all-cause premature adult mortality was estimated in Poisson log-linear spatial models.

Results

PCA resulted in two principal components explaining the 65.7% of the total variance. The first principal component included four indicators (low educational attainment, single-person households, divorced or widowed and single-parent households, the latter however with a negative loading) and it thought more likely to capture rural-related aspects of deprivation. The second principal component included the other two indicators (unemployment and not owner occupied households) and it is more likely to capture urban-related aspects of material deprivation. Restricting the analysis in the metropolitan areas of the island resulted in a different set of indicators for the urban-specific deprivation index. All developed indices were linearly associated with all-cause premature adult mortality. The all-cause premature adult mortality increased by 17% per 1 standard deviation (SD) increase in rural-related socioeconomic deprivation (95% CrI: 8–27%) and 8% per 1 SD increase in urban-related aspects of material deprivation (95% CrI: 3–15%) in the nationwide analysis and 9% per 1 SD increase in urban-specific socioeconomic deprivation (95% CrI: 4–15%) across metropolitan areas.

Conclusions

The results of this study demonstrate that a set of small-area indices of socioeconomic deprivation across Cypriot communities have good construct and predictive validity. However, the study indicates that different aspects of socioeconomic deprivation may be important in rural and urban areas in Cyprus. The developed socioeconomic deprivation indices could offer a valid new tool for Cypriot public health research and policy in terms of identifying areas in greatest need, guiding resource allocation and developing area-targeted public health programmes and policies.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6973-0) contains supplementary material, which is available to authorized users.

Incorporating geography into a new generalized theoretical and statistical framework addressing the modifiable areal unit problem

Background

All analyses of spatially aggregated data are vulnerable to the modifiable areal unit problem (MAUP), which describes the sensitivity of analytical results to the arbitrary choice of spatial aggregation unit at which data are measured. The MAUP is a serious problem endemic to analyses of spatially aggregated data in all scientific disciplines. However, the impact of the MAUP is rarely considered, perhaps partly because it is still widely considered to be unsolvable.

Results

It was originally understood that a solution to the MAUP should constitute a comprehensive statistical framework describing the regularities in estimates of association observed at different combinations of spatial scale and zonation. Additionally, it has been debated how such a solution should incorporate the geographical characteristics of areal units (e.g. shape, size, and configuration), and in particular whether this can be achieved in a purely mathematical framework (i.e. independent of areal units). We argue that the consideration of areal units must form part of a solution to the MAUP, since the MAUP only manifests in their presence. Thus, we present a theoretical and statistical framework that incorporates the characteristics of areal units by combining estimates obtained from different scales and zonations. We show that associations estimated at scales larger than a minimal geographical unit of analysis are systematically biased from a true minimal-level effect, with different zonations generating uniquely biased estimates. Therefore, it is fundamentally erroneous to infer conclusions based on data that are spatially aggregated beyond the minimal level. Instead, researchers should measure and display information, estimate effects, and infer conclusions at the smallest possible meaningful geographical scale. The framework we develop facilitates this.

Conclusions

The proposed framework represents a new minimum standard in the estimation of associations using spatially aggregated data, and a reference point against which previous findings and misconceptions related to the MAUP can be understood.

Electronic supplementary material

The online version of this article (10.1186/s12942-019-0170-3) contains supplementary material, which is available to authorized users.

Spatial identification of environmental health hazards potentially associated with adverse birth outcomes

Reduced birth weight (RBW) and reduced head circumference (RHC) are adverse birth outcomes (ABOs), often linked to environmental exposures. However, spatial identification of specific health hazards, associated with these ABOs, is not always straightforward due to presence of multiple health hazards and sources of air pollution in urban areas. In this study, we test a novel empirical approach to the spatial identification of environmental health hazards potentially associated with the observed RHC and RBW patterns. The proposed approach is implemented as a systematic search, according to which alternative candidate locations are ranked based on the strength of association with the observed birth outcome patterns. For empirical validation, we apply this approach to the Haifa Bay Area (HBA) in Israel, which is characterized by multiple health hazards and numerous sources of air pollution. We identified a spot in the local industrial zone as the main risk source associated with the observed RHC and RBW patterns. Multivariate regressions, controlling for personal, neighborhood, and geographic factors, revealed that the relative risks of RHC and RBW tend to decline, other things being equal, as a function of distance from the identified industrial spot. We recommend the proposed identification approach as a preliminary risk assessment tool for environmental health studies, in which detailed information on specific sources of air pollution and air pollution dispersion patterns is unavailable due to limited reporting or insufficient monitoring.

Estimation of the Ecological Fallacy in the Geographical Analysis of the Association of Socio-Economic Deprivation and Cancer Incidence

Ecological deprivation indices at the level of spatial units are often used to measure and monitor inequalities in health despite the possibility of ecological fallacy. For the purpose of this study, the European Deprivation Index (EDI) was used, which is based on Townsend theorization of relative deprivation. The Slovenian version of EDI (SI-EDI) at the aggregated level (SI-EDI-A) was calculated to the level of the national assembly polling stations. The SI-EDI was also calculated at the individual level (SI-EDI-I) by the method that represents a methodological innovation. The degree of ecological fallacy was estimated with the Receiver Operating Characteristics (ROC) curves. By calculating the area under the ROC curve, the ecological fallacy was evaluated numerically. Agreement between measuring deprivation with SI-EDI-A and SI-EDI-I was analysed by graphical methods and formal testing. The association of the socio-economic status and the cancer risk was analysed in all first cancer cases diagnosed in Slovenia at age 16 and older in the period 2011⁻2013. Analysis was done for each level separately, for SI-EDI-I and for SI-EDI-A. The Poisson regression model was implemented in both settings but adapted specifically for aggregated and individual data. The study clearly shows that ecological fallacy is unavoidable. However, although the association of cancer incidence and socio-economic deprivation at individual and aggregated levels was not the same for all cancer sites, the results were very similar for the majority of investigated cancer sites and especially for cancers associated with unhealthy lifestyles. The results confirm the assumptions from authors' previous research that using the level of the national assembly polling stations would be the acceptable way to aggregate data when explaining inequalities in health in Slovenia in ecological studies.

Using a Clustering Approach to Investigate Socio-Environmental Inequality in Preterm Birth-A Study Conducted at Fine Spatial Scale in Paris (France)

Background & Objectives: Today, to support public policies aiming to tackle environmental and health inequality, identification and monitoring of the spatial pattern of adverse birth outcomes are crucial. Spatial identification of the more vulnerable population to air pollution may orient health interventions. In this context, the objective of this study is to investigate the geographical distribution of the risk of preterm birth (PTB, gestational age ≤36 weeks) at the census block level in in city of Paris, France. We also aimed to assess the implication of neighborhood characteristics including air pollution and socio-economic deprivation. Material & Methods: Newborn health data are available from the first birth certificate registered by the Maternal and Child Care department of Paris. All PTB from January 2008 to December 2011 were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level and annual average ambient concentrations of NO₂. A spatial clustering approach was used to investigate the spatial distribution of PTB. Results: Our results highlight that PTB is non-randomly spatially distributed, with a cluster of high risk in the northeastern area of Paris (RR = 1.15; p = 0.06). After adjustment for socio-economic deprivation and NO₂ concentrations, this cluster becomes not statistically significant or shifts suggesting that these characteristics explain the spatial distribution of PTB; further, their combination shows an interaction in comparison with SES or NO₂ levels alone. Conclusions: Our results may inform the decision makers about the areas where public health efforts should be strengthened to tackle the risk of PTB and to choose the most appropriate and specific community-oriented health interventions.

Epidemiology of Pediatric Critical Care Transport in Northern Alberta and the Western Arctic

OBJECTIVE

Specialized pediatric critical care transport teams are essential to pediatric retrieval systems. This study aims to describe the contemporary transports performed by a Canadian pediatric critical care transport team and to compare the treatment and outcomes of children referred from high-level care (hospitals offering pediatric services where an adult ICU exists) and nonhigh-level care (all other hospitals) hospitals.

DESIGN

A descriptive cohort study.

SETTING

The Stollery Children's Hospital in Edmonton, Alberta, Western Canada.

PATIENTS

Children younger than 17 years old transported by the transport team from referral hospitals within the Stollery Children's Hospital catchment area to Stollery Children's Hospital between 1998 and 2015.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Characteristics of transports, patient demographics presenting vital signs, and outcomes were described overall and compared by transport-related time and referral hospital types (high-level care and nonhigh-level care). In total, 3,352 transports met the inclusion criteria; 1,049 were retrieved from eight high-level care hospitals and 2,303 from 53 nonhigh-level care hospitals; the median one-way transport distance was 383 kilometers, and 70% of the transports were air transports. The annual number of transports has increased during the study period. The PICU admission rate was between 40% and 55%. Transports from high-level care hospitals had significantly higher odds of being admitted to the PICU (odds ratio, 1.96; 95% CI, 1.31-2.93). The odds of intubation at the referral hospital were higher in the high-level care group, but the odds of intubation upon PICU admission was similar between the two groups. Mortality during or after transport was not significantly different between high-level care and nonhigh-level care hospitals.

CONCLUSIONS

The current transport system has multiple priorities with regard to efficiency and quality. The medical services at referral hospitals may affect the likelihood of PICU admission and subsequent PICU length of stay; however, no negative impact was observed in other outcomes including mortality.

Early neonatal mortality in twin pregnancy: Findings from 60 low- and middle-income countries

Background

Around the world, the incidence of multiple pregnancies reaches its peak in the Central African countries and often represents an increased risk of death for women and children because of higher rates of obstetrical complications and poor management skills in those countries. We sought to assess the association between twins and early neonatal mortality compared with singleton pregnancies. We also assessed the role of skilled birth attendant and mode of delivery on early neonatal mortality in twin pregnancies.

Methods

We conducted a secondary analysis of individual level data from 60 nationally-representative Demographic and Health Surveys including 521 867 singleton and 14 312 twin births. We investigated the occurrence of deaths within the first week of life in twins compared to singletons and the effect of place and attendance at birth; also, the role of caesarean sections against vaginal births was examined, globally and after countries stratification per caesarean sections rates. A multi-level logistic regression was used accounting for homogeneity within country, and homogeneity within twin pairs.

Results

Early neonatal mortality among twins was significantly higher when compared to singleton neonates (adjusted odds ratio (aOR) 7.6; 95% confidence interval (CI) = 7.0-8.3) in these 60 countries. Early neonatal mortality was also higher among twins than singletons when adjusting for birth weight in a subgroup analysis of those countries with data on birth weight (n = 20; less than 20% of missing values) (aOR = 2.8; 95% CI = 2.2-3.5). For countries with high rates (>15%) of caesarean sections (CS), twins delivered vaginally in health facility had a statistically significant (aOR = 4.8; 95% CI = 2.4-9.4) increased risk of early neonatal mortality compared to twins delivered through caesarean sections. Home twin births without SBA was associated with increased mortality compared with delivering at home with SBA (aOR = 1.3; 95% CI = 1.0-1.8) and with vaginal birth in health facility (aOR = 1.7; 95% CI = 1.4-2.0).

Conclusions

Institutional deliveries and increased access of caesarian sections may be considered for twin pregnancies in low- and middle- income countries to decrease early adverse neonatal outcomes.

Low-level arsenic exposure from drinking water is associated with prostate cancer in Iowa

Inorganic arsenic is a toxic naturally occurring element in soil and water in many regions of the US including the Midwest. Prostate cancer is the second most common type of cancer in men in Iowa, surpassed only by non-melanotic skin cancer. Epidemiology studies have evaluated arsenic exposure from drinking water and prostate cancer, but most have focused on high-level exposures outside the US. As drinking water from groundwater sources is a major source of arsenic exposure, we conducted an ecologic study to evaluate prostate cancer and arsenic in drinking water from public water sources and private wells in Iowa, where exposure levels are low, but duration of exposure can be long. Arsenic data from public water systems were obtained from the Iowa Safe Drinking Water Information System for the years 1994-2003 and for private wells from two Iowa Well Water Studies, the Iowa Community Private Well Study (ICPWS, 2002-2003) and Iowa Statewide Rural Well Water Survey Phase 2 (SWIRL2, 2006-2008) that provided data for 87 Iowa counties. Prostate cancer incidence data from 2009 to 2013 for Iowa were obtained from Surveillance, Epidemiology and End Results' SEER*Stat software. County averages of water arsenic levels varied from 1.08 to 18.6 ppb, with three counties above the current 10 ppb limit. Based on the tertiles of arsenic levels, counties were divided into three groups: low (1.08-2.06 ppb), medium (2.07-2.98 ppb), and high (2.99-18.6 ppb). Spatial Poisson regression modeling was conducted to estimate the risk ratios (RR) of prostate cancer by tertiles of arsenic level at a county level, adjusted for demographic and risk factors. The RR of prostate cancer were 1.23 (95% CI, 1.16-1.30) and 1.28 (95% CI, 1.21-1.35) in the medium and high groups, respectively, compared to the low group after adjusting for risk factors. The RR increased to 1.36 (95% CI, 1.28-1.45) in the high group when analyses were restricted to aggressive prostate cancers (Gleason score ≥ 7). This study shows a significant dose-dependent association between low-level arsenic exposure and prostate cancer, and if this result is replicated in future individual-level studies, may suggest that 10 ppb is not protective for human health.

Is atmospheric pollution exposure during pregnancy associated with individual and contextual characteristics? A nationwide study in France

Background

Exposure to atmospheric pollutants is a danger for the health of pregnant mother and children. Our objective was to identify individual (socioeconomic and behavioural) and contextual factors associated with atmospheric pollution pregnancy exposure at the nationwide level.

Method

Among 14 921 women from the French nationwide ELFE (French Longitudinal Study of Children) mother-child cohort recruited in 2011, outdoor exposure levels of PM2.5, PM10 (particulate matter <2.5 µm and <10 µm in diameter) and NO2 (nitrogen dioxide) were estimated at the pregnancy home address from a dispersion model with 1 km resolution. We used classification and regression trees (CART) and linear regression to characterise the association of atmospheric pollutants with individual (maternal age, body mass index, parity, education level, relationship status, smoking status) and contextual (European Deprivation Index, urbanisation level) factors.

Results

Patterns of associations were globally similar across pollutants. For the CART approach, the highest tertile of exposure included mainly women not in a relationship living in urban and socially deprived areas, with lower education level. Linear regression models identified different determinants of atmospheric pollutants exposure according to the residential urbanisation level. In urban areas, atmospheric pollutants exposure increased with social deprivation, while in rural areas a U-shaped relationship was observed.

Conclusion

We highlighted social inequalities in atmospheric pollutants exposure according to contextual characteristics such as urbanisation level and social deprivation and also according to individual characteristics such as education, being in a relationship and smoking status. In French urban areas, pregnant women from the most deprived neighbourhoods were those most exposed to health-threatening atmospheric pollutants.

Does the extension of primary care practice opening hours reduce the use of emergency services?

Overcrowding in emergency departments generates potential inefficiencies. Using regional administrative data, we investigate the impact that an increase in the accessibility of primary care has on emergency visits in Italy. We consider two measures of avoidable emergency visits recorded at list level for each General Practitioner. We test whether extending practices' opening hours to up to 12 hours/day reduces the inappropriate utilization of emergency services. Since subscribing to the extension program is voluntary, we account for the potential endogeneity of participation in a count model for emergency admissions in two ways: first, we use a two-stage residual inclusion approach. Then we exploit panel methods on data covering a three-year period, thus accounting directly for individual heterogeneity. Our results show that increasing primary care accessibility acts as a restraint on the inappropriate use of emergency departments. The estimated effect is in the range of a 10-15% reduction in inappropriate admissions.

Fruit and Vegetable, Fat, and Sugar-Sweetened Beverage Intake Among Low-Income Mothers Living in Neighborhoods With Supplemental Nutrition Assistance Program-Education

OBJECTIVE

To examine among low-income mothers the consumption of fruits and vegetables (FV), high-fat foods, and sugar-sweetened beverages (SSBs) and overall diet quality in relation to levels of reach of Supplemental Nutrition Assistance Program-Education (SNAP-Ed) interventions across 2,907 California census tracts.

DESIGN

Cross-sectional telephone survey conducted from April through October, 2014 using the Automated Self-administered 24-Hour Recall dietary assessment.

PARTICIPANTS

Mothers or primary caregivers (n = 6,355) from randomly selected SNAP households. The sample was 42.6% Latina, 25.5% white, and 17.6% African American. The response rate was 60.5%.

MAIN OUTCOME MEASURES

Cups of FV; calories from high-fat foods; and cups of SSBs, overall and from items purchased from fast-food restaurants. Overall diet quality was assessed by the Healthy Eating Index-2010.

ANALYSIS

Linear regression controlling for race/ethnicity and education, with significance at P ≤ .05.

RESULTS

Mothers from high SNAP-Ed reach census tracts ate more cups of FV, consumed fewer calories from high-fat foods, and drank fewer cups of SSBs. Healthy Eating Index-2010 scores did not vary by levels of SNAP-Ed reach.

CONCLUSIONS AND IMPLICATIONS

Supplemental Nutrition Assistance Program-Education interventions are related to increased intake of FV and decreased consumption of high-fat foods and SSBs, but not overall diet quality. Future studies should include assessment of physical activity to investigate caloric balance in association with levels of SNAP-Ed interventions.

Spatial Proximity to Incidents of Community Violence Is Associated with Fewer Suicides in Urban California

Suicide is a leading cause of premature mortality. Aspects of the social environment such as incidents of violence in the community may induce psychological distress and affect suicidality, but these determinants are not well understood. We conducted an ecological study using California vital statistics records, geocoded to address of the decedent, to examine whether proximity to homicide was associated with the occurrence of suicide in urban census tracts. For each urban tract (N = 7194) and each month in 2012, we assessed homicides in the tract or within buffer zones around the tract with a 1-month lag. We estimated two risk difference parameters that capture how suicide risk is related to differences in homicide exposure. Proximity to homicides was negatively associated with suicide occurrence after controlling for demographic factors, seasonality, and other confounders. Estimates suggest that the absence of homicides would be associated with a 4.2 % higher number of tract-months with one or more suicides (95 % confidence interval 2.2-6.0). This relationship was stronger in tracts that were wealthier, older, and less civically engaged. Results were robust to a wide variety of sensitivity tests. Contrary to expectations, we identified a consistent negative association of proximity to homicide with suicide occurrence. It may be that a homicide deters or distracts from suicidality or that aggression or hopelessness may be expressed as inward or outward directed violence in different settings. Further investigation is needed to identify the drivers of this association.

A geostatistical investigation of agricultural and infrastructural risk factors associated with primary verotoxigenic E. coli (VTEC) infection in the Republic of Ireland, 2008-2013

Ireland reports the highest incidence of verotoxigenic Escherichia coli (VTEC) infection in Europe. This study investigated potential risk factors for confirmed sporadic and outbreak primary VTEC infections during 2008-2013. Overall, 989 VTEC infections including 521 serogroup O157 and 233 serogroup O26 were geo-referenced to 931 of 18 488 census enumeration areas. The geographical distribution of human population, livestock, unregulated groundwater sources, domestic wastewater treatment systems (DWWTS) and a deprivation index were examined relative to notification of VTEC events in 524 of 6242 rural areas. Multivariate modelling identified three spatially derived variables associated with VTEC notification: private well usage [odds ratio (OR) 6·896, P < 0·001], cattle density (OR 1·002, P < 0·001) and DWWTS density (OR 0·978, P = 0·002). Private well usage (OR 18·727, P < 0·001) and cattle density (OR 1·001, P = 0·007) were both associated with VTEC O157 infection, while DWWTS density (OR 0·987, P = 0·028) was significant within the VTEC O26 model. Findings indicate that VTEC infection in the Republic of Ireland is particularly associated with rural areas, which are associated with a ubiquity of pathogen sources (cattle) and pathways (unregulated groundwater supplies).

Ageing, Chronic Disease and Injury: A Study in Western Victoria (Australia)

Background: An increasing burden of chronic disease and associated health service delivery is expected due to the ageing Australian population. Injuries also affect health and wellbeing and have a long-term impact on health service utilisation. There is a lack of comprehensive data on disease and injury in rural and regional areas of Australia. The aim of the Ageing, Chronic Disease and Injury study is to compile data from various sources to better describe the patterns of chronic disease and injury across western Victoria.

Design: Ecological study.

Methods: Information on demographics, socioeconomic indicators and lifestyle factors are obtained from health surveys and government departments. Data concerning chronic diseases and injuries will be sourced from various registers, health and emergency services, local community health centres and administrative databases and compiled to generate profiles for the study region and for sub-populations within the region.

Expected impact for public health: This information is vital to establish current and projected population needs to inform policy and improve targeted health services delivery, care transition needs and infrastructure development. This study provides a model that can be replicated in other geographical settings.

The epidemiologic principles underlying traffic safety study designs

This article describes the epidemiological principles underlying four observational study designs commonly used to assess traffic safety: the case-control, case-crossover, culpability and quasi-induced exposure designs. We focus in particular on the specific challenges for preventing bias using each design. Whereas recruiting controls representative of the source population poses a special challenge in case-control traffic safety studies, case-crossover designs are prone to recall bias, and culpability and quasi-induced exposure studies can be undermined by difficulties assigning crash responsibility. Using causal diagrams and worked examples, we provide a simple way to teach traffic safety designs to epidemiologists and to encourage proper application of epidemiological principles among researchers designing traffic safety studies.

Use of geographic indicators of healthcare, environment and socioeconomic factors to characterize environmental health disparities

BACKGROUND

An environmental health inequality is a major public health concern in Europe. However just few studies take into account a large set of characteristics to analyze this problematic. The aim of this study was to identify and describe how socioeconomic, health accessibility and exposure factors accumulate and interact in small areas in a French urban context, to assess environmental health inequalities related to infant and neonatal mortality.

METHODS

Environmental indicators on deprivation index, proximity to high-traffic roads, green space, and healthcare accessibility were created using the Geographical Information System. Cases were collected from death certificates in the city hall of each municipality in the Nice metropolitan area. Using the parental addresses, cases were geocoded to their census block of residence. A classification using a Multiple Component Analysis following by a Hierarchical Clustering allow us to characterize the census blocks in terms of level of socioeconomic, environmental and accessibility to healthcare, which are very diverse definition by nature. Relation between infant and neonatal mortality rate and the three environmental patterns which categorize the census blocks after the classification was performed using a standard Poisson regression model for count data after checking the assumption of dispersion.

RESULTS

Based on geographic indicators, three environmental patterns were identified. We found environmental inequalities and social health inequalities in Nice metropolitan area. Moreover these inequalities are counterbalance by the close proximity of deprived census blocks to healthcare facilities related to mother and newborn. So therefore we demonstrate no environmental health inequalities related to infant and neonatal mortality.

CONCLUSION

Examination of patterns of social, environmental and in relation with healthcare access is useful to identify census blocks with needs and their effects on health. Similar analyzes could be implemented and considered in other cities or related to other birth outcomes.

Estimating the Impact of Health-related Behaviors on Geographic Variation in Cardiovascular Mortality: A New Approach Based on the Synthesis of Ecological and Individual-level Data

BACKGROUND

Incidence of and mortality from cardiovascular disease (CVD) exhibit a strong geographical pattern, with inhabitants of more affluent neighborhoods showing a substantially lower risk of CVD mortality than inhabitants of deprived neighborhoods. Thus far, there is insufficient evidence as to what extent these differences can be attributed to differences in health-related behaviors.

METHODS

Using a Hierarchical Related Regression approach, we combined individual and aggregate (ecological) data to investigate the extent to which small-area variation in CVD mortality in Dutch neighborhoods can be explained by several behavioral risk factors (i.e., smoking, drinking, overweight, and physical inactivity). The proposed approach combines the benefits of both an ecological analysis (in terms of data availability and statistical power) and an individual-level analysis (in terms of identification of the parameters and interpretation of the results).

RESULTS

After correcting for differences in age and sex, accounting for differences in the behavioral risk factors reduces income-related inequalities in CVD mortality by approximately 30%.

CONCLUSIONS

Direct targeting of the excess prevalence of unhealthy behaviors in deprived neighborhoods is identified as a relevant strategy to reduce inequalities in CVD mortality. Our results also show that the proposed Hierarchical Related Regression approach provides a powerful method for the investigation of small-area variation in health outcomes.