The ecology of birth defects: socio-economic and environmental determinants of gastroschisis in North Carolina

Gastroschisis is a serious birth defect that has increased in prevalence in North Carolina over the past decade. The causes of the defect, and the reasons for this increase, are largely unknown. This study uses the disease ecology framework and spatial methodologies - spatial statistics, Geographic Information Systems, and hydrological modeling - to explore the geographic distribution of gastroschisis in North Carolina and suggest possible socioeconomic and environmental factors that may contribute to the disease. Specific questions addressed in this study include: 1) Do significant geographic clusters of gastroschisis exist in North Carolina? 2) Do clusters suggest the presence of point-source environmental pollutants? 3) What area-level socioeconomic characteristics are related to gastroschisis outcomes? 4) What can this tell us about possible causes of the disease? Using data from a population-based birth defects registry, this study uses Kulldorff's spatial scan statistic to identify the location and extent of clusters of gastroschisis births in North Carolina between 1999 and 2004. Spatial clusters are controlled for four major risk factors (maternal age, race, prior births and Medicaid status) to ensure that the clusters are not an artifact of the population composition of the State. The relationship between neighborhood socioeconomic characteristics (e.g., race, poverty, education and unemployment) and gastroschisis outcomes are examined using logistic regression models, which combine individual-level and neighborhood-level variables. Finally, simple hydrological models are used to determine if exposure to upstream textile mill effluent increases the risk for a gastroschisis affected pregnancy. Results indicate the presence of a localized cluster of gastroschisis in the rural southern Piedmont of North Carolina. In addition, both individual-level (Medicaid status) and neighborhood-level (poverty and unemployment) socioeconomic factors appear to contribute to the risk of a gastroschisis affected pregnancy, suggesting that neighborhood-level socioeconomic factors exert an independent causal effect on gastroschisis. Despite the localized nature of the cluster, which often suggests the presence of an environmental contaminant, there is no evidence to support this hypothesis. These results may help understanding the myriad social, economic and environmental factors that combine and interact to influence gastroschisis outcomes

Effects of health intervention programs and arsenic exposure on child mortality from acute lower respiratory infections in rural Bangladesh

BackgroundRespiratory infections continue to be a public health threat, particularly to young children in developing countries. Understanding the geographic patterns of diseases and the role of potential risk factors can help improve future mitigation efforts. Toward this goal, this paper applies a spatial scan statistic combined with a zero-inflated negative-binomial regression to re-examine the impacts of a community-based treatment program on the geographic patterns of acute lower respiratory infection (ALRI) mortality in an area of rural Bangladesh. Exposure to arsenic-contaminated drinking water is also a serious threat to the health of children in this area, and the variation in exposure to arsenic must be considered when evaluating the health interventions.MethodsALRI mortality data were obtained for children under 2 years old from 1989 to 1996 in the Matlab Health and Demographic Surveillance System. This study period covers the years immediately following the implementation of an ALRI control program. A zero-inflated negative binomial (ZINB) regression model was first used to simultaneously estimate mortality rates and the likelihood of no deaths in groups of related households while controlling for socioeconomic status, potential arsenic exposure, and access to care. Next a spatial scan statistic was used to assess the location and magnitude of clusters of ALRI mortality. The ZINB model was used to adjust the scan statistic for multiple social and environmental risk factors.ResultsThe results of the ZINB models and spatial scan statistic suggest that the ALRI control program was successful in reducing child mortality in the study area. Exposure to arsenic-contaminated drinking water was not associated with increased mortality. Higher socioeconomic status also significantly reduced mortality rates, even among households who were in the treatment program area.ConclusionCommunity-based ALRI interventions can be effective at reducing child mortality, though socioeconomic factors may continue to influence mortality patterns. The combination of spatial and non-spatial methods used in this paper has not been applied previously in the literature, and this study demonstrates the importance of such approaches for evaluating and improving public health intervention program

Evidence for localised HIV related micro-epidemics associated with the decentralised provision of antiretroviral treatment in rural South Africa: a spatio-temporal analysis of changing mortality patterns (2007-2010).

BACKGROUND: In this study we analysed the spatial and temporal changes in patterns of mortality over a period when antiretroviral therapy (ART) was rolled out in a rural region of north-eastern South Africa. Previous studies have identified localised concentrated HIV related sub-epidemics and recommended that micro-level analyses be carried out in order to direct focused interventions. METHODS: Data from an ongoing health and socio-demographic surveillance study was used in the analysis. The follow-up was divided into two periods, 2007-2008 and 2009-2010, representing the times immediately before and after the effects on mortality of the decentralised ART provision from a newly established local health centre would be expected to be evident. The study population at the start of the analysis was approximately 73 000 individuals. Data were aggregated by village and also using a 2 × 2 km grid. We identified villages, grid squares and regions in the site where mortality rates within each time period or rate ratios between the periods differed significantly from the overall trends. We used clustering techniques to identify cause-specific mortality hotspots. FINDINGS: Comparing the two periods, there was a 30% decrease in age and gender standardised adult HIV-related and TB (HIV/TB) mortality with no change in mortality due to other causes. There was considerable spatial heterogeneity in the mortality patterns. Areas separated by 2 to 4 km with very different epidemic trajectories were identified. There was evidence that the impact of ART in reducing HIV/TB mortality was greatest in communities with higher mortality rates in the earlier period. CONCLUSIONS: This study shows the value of conducting high resolution spatial analyses in order to understand how local micro-epidemics contribute to changes seen over a wider area. Such analyses can support targeted interventions

Quantifying the Population-level Effect of the COVID-19 Mass Vaccination Campaign in Israel: a Modeling Study

BackgroundEstimating real-world vaccine effectiveness is challenging since a variety of population factors can impact vaccine effectiveness.We aimed to assess the population-level reduction in cumulative SARS-CoV-2 cases, hospitalizations and mortality due to the BNT162b2 mRNA COVID-19 vaccination campaign in Israel during January-February, 2021.MethodsAn SIR model and a Dynamic Survival Analysis (DSA) statistical approach was used. Daily counts of tested positive and of vaccine doses administered obtained from the Israeli Ministry of Health, were used to calibrate the model. The model was parameterized using values derived from a previous phase of the pandemic during which similar lockdown and other preventive measures were implemented in order to take into account the effect of these preventing measures on COVID-19 spread.ResultsOur model predicts for the total population a reduction of 648,585 SARS-CoV-2 cases (75% confidence interval [CI]: 25,877–1,396,963) during the first 2 months of the vaccination campaign. The number of averted hospitalizations for moderate – severe conditions were 16,101 (75 % CI: 2,010–33,035) and reduction of death was estimated as 5,123 (CI: 388–10,815) fatalities.Among children aged 0-19 years, we estimated a reduction of 163,436 (CI: 0–433,233) SARS-CoV-2 cases which we consider as an indirect effect of the vaccine.ConclusionsOur results suggest that the rapid vaccination campaign prevented hundreds of thousands of new cases as well as thousands of hospitalizations and fatalities and has probably averted a major health care crisis

Residential Mobility Across Early Childhood and Children’s Kindergarten Readiness

Understanding residential mobility in early childhood is important for contextualizing family, school, and neighborhood influences on child well-being. We examined the consequences of residential mobility for socioemotional and cognitive kindergarten readiness using the Early Childhood Longitudinal Study-Birth Cohort, a nationally representative longitudinal survey that followed U.S. children born in 2001 from infancy to kindergarten. We described individual, household, and neighborhood characteristics associated with residential mobility for children aged 0–5. Our residential mobility indicators examined frequency of moves, nonlinearities in move frequency, quality of moves, comparisons between moving houses and moving neighborhoods, and heterogeneity in the consequences of residential mobility. Nearly three-quarters of children moved by kindergarten start. Mobility did not predict cognitive scores. More moves, particularly at relatively high frequencies, predicted lower kindergarten behavior scores. Moves from socioeconomically advantaged to disadvantaged neighborhoods were especially problematic, whereas moves within a ZIP code were not. The implications of moves were similar across socioeconomic status. The behavior findings largely support an instability perspective that highlights potential disruptions from frequent or problematic moves. Our study contributes to literature emphasizing the importance of contextualizing residential mobility. The high prevalence and distinct implications of early childhood moves support the need for further research

Evidence of localized clustering of gastroschisis births in North Carolina, 1999-2004

Examining the geographic distribution of birth defects can be useful in exploratory etiologic research. Identification of clusters of certain defects may uncover possible environmental or socio-economic risk factors and assist with the generation of hypotheses about underlying causes of these conditions. In North Carolina, the prevalence of gastroschisis, a serious abdominal wall defect, has increased over the past decade and anecdotal evidence from clinicians suggests the possibility of clustering of this condition. This study uses a spatial scan statistic to identify the location and extent of clusters of gastroschisis births in North Carolina between 1999 and 2004. Data on cases of gastroschisis were obtained from the North Carolina Birth Defect Monitoring Program (NCBDMP) and control births were chosen from all resident live births without birth defects contained in the North Carolina composite linked birth files. The clusters were controlled for five major risk factors (maternal age, race, parity, Medicaid status, maternal smoking) to ensure that the clusters were not artifacts of unequal population distribution. Results indicate a localized cluster of gastroschisis in the rural southern Piedmont of North Carolina which persists even after controlling for all major risk factors. Adjusting for these risk factors shifted the location of the cluster substantially, demonstrating the importance of adjusting for underlying population distribution. Since clusters persisted after adjusting for individual-level risk factors, environmental contaminants may explain the excess of gastroschisis cases. This study is among the first to assess spatial clustering of gastroschisis using GIS methods. This study also demonstrates the importance of controlling for covariates in spatial analysis and illustrates the usefulness of the spatial scan statistic in exploratory etiologic research.Birth defects Gastroschisis Spatial scan statistic Spatial cluster Covariates USA SaTScan

Adjusting for geographic variation in observational comparative effectiveness studies: a case study of antipsychotics using state Medicaid data.

BACKGROUND: Area-level variation in treatment and outcomes may be a potential source of confounding bias in observational comparative effectiveness studies. This paper demonstrates how to use exploratory spatial data analysis (ESDA) and spatial statistical methods to investigate and control for these potential biases. The case presented compares the effectiveness of two antipsychotic treatment strategies: oral second-generation antipsychotics (SGAs) vs. long-acting paliperiodone palmitate (PP). METHODS: A new-start cohort study was conducted analyzing patient-level administrative claims data (8/1/2008-4/30/2011) from Missouri Medicaid. ESDA techniques were used to examine spatial patterns of antipsychotic prescriptions and outcomes (hospitalization and emergency department (ED) visits). Likelihood of mental health-related outcomes were compared between patients starting PP (N = 295) and oral SGAs (N = 8,626) using multilevel logistic regression models adjusting for patient composition (demographic and clinical factors) and geographic region. RESULTS: ESDA indicated significant spatial variation in antipsychotic prescription patterns and moderate variation in hospitalization and ED visits thereby indicating possible confounding by geography. In the multilevel models for this antipsychotic case example, patient composition represented a stronger source of confounding than geographic context. CONCLUSION: Because geographic variation in health care delivery is ubiquitous, it could be a comparative effectiveness research (CER) best practice to test for possible geographic confounding in observational data. Though the magnitude of the area-level geography effects were small in this case, they were still statistically significant and should therefore be examined as part of this observational CER study. More research is needed to better estimate the range of confounding due to geography across different types of observational comparative effectiveness studies and healthcare utilization outcomes