City-Specific Spatiotemporal Infant and Neonatal Mortality Clusters: Links with Socioeconomic and Air Pollution Spatial Patterns in France

A spatial indicator of environmental and climatic vulnerability in Rome

BACKGROUND

Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies.

METHODS

From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km² in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM_2.5, PM₁₀, NO₂, C₆H₆, SO₂), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described.

RESULTS

The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO₂ in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index.

CONCLUSIONS

A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.

Neighborhood inequalities and the decline of infant mortality in São Paulo

This paper documents changes in infant mortality (IM) rates in São Paulo, Brazil, between 2003 and 2013 and examines the association among neighborhood characteristics and IM. We investigate the extent to which increased use of health care services and improvements in economic and social conditions are associated with reductions in IM. Using data from the Brazilian Census and the São Paulo Secretaria Municipal da Saúde/SMS, we conducted a longitudinal analysis of panel data in all 96 districts of São Paulo for every year between 2003 and 2013. Our regression model includes district level measures that reflect economic, health care and social determinants of IM. We find that investments in health care have contributed to lower IM rates in the city, but the direct effect of increased spending is most evident for people living in São Paulo's middle- and high-income neighborhoods. Improvements in social conditions were more strongly associated with IM declines than increases in the use of health care among São Paulo's low-income neighborhoods. To reduce health inequalities, policies should target benefits to lower-income neighborhoods. Subsequent research should document the consequences of recent changes in Brazil's economic capacity and commitment to public health spending for population health.

Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling

Background

Neonatal mortality rate (NMR), infant mortality rate (IMR), and child mortality rate (CMR) show a huge difference across countries, which has been posing challenges for public health policies and medical resource allocation.

Methods

Bayesian spatiotemporal model is applied to assess the detailed spatiotemporal evolution of NMR, IMR, and CMR from a global perspective. Panel data from 185 countries from 1990 to 2019 are collected.

Results

The continuously decreasing trend of NMR, IMR, and CMR indicated a great improvement in neonatal, infant, and child mortality worldwide. Further, huge differences in the NMR, IMR, and CMR still exist across countries. In addition, the gap of NMR, IMR, and CMR across the countries presented a widening trend from the perspective of dispersion degree and kernel densities. The spatiotemporal heterogeneities demonstrated that the decline degree among these three indicators could be observed as CMR > IMR > NMR. Countries such as Brazil, Sweden, Libya, Myanmar, Thailand, Uzbekistan, Greece, and Zimbabwe showed the highest values of b_1i , indicating a weaker downward trend compared to the overall downward trend in the world.

Conclusions

This study revealed the spatiotemporal patterns and trends in the levels and improvement of NMR, IMR, and CMR across countries. Further, NMR, IMR, and CMR show a continuously decreasing trend, but the differences in improvement degree present a widening trend across countries. This study provides further implications for policy in newborns, infants, and children's health to reduce health inequality worldwide.

Russian subject-level index of multidimensional deprivation and its association with all-cause and infant mortality

Background

Social and environmental inequalities in public health are recognized as global problems of our time. From the point of view of the theory of deprivation, social and environmental determinants identified as deprivation indicators, which help to detect health inequality. Indices are one of the most practical and powerful tools for measuring the level of deprivation.

Objectives

The aims of our study are (1) to develop a Russian derivation index to measure the levels of deprivation and (2) to analyze its associations with total and infant mortality.

Material and methods

Deprivation indicators were obtained from the Federal State Statistics Service of Russia. All mortality data were taken from the official website of the Federal Research Institute for Health Organization and Informatics of Ministry of Health of the Russian Federation from 2009 to 2012. Principal components analysis with varimax rotation was used to (1) select suitable deprivation indicators and (2) create the index. A Spearman's correlation was run to determine the relationship of deprivation with all-cause and infant mortality. Ordinary least squares (OLS) regression was used to assess the relationship between deprivation and infant mortality. Development of the index and statistical analysis were carried out using R and SPSS software.

Results

There is not a statistically significant correlation between deprivation and all-cause mortality. OLS regression showed a significant relationship between deprivation and infant mortality (p = 0.02). For every one-unit increase in the index score, infant mortality rate increases by about 20%.

The evolution of infant mortality and neighbourhood inequalities in four world cities: 1988-2016

OBJECTIVES

To determine the level of neighbourhood inequalities in infant mortality (IM) rates in the urban core of four world cities and to examine the association between neighbourhood-level income and IM. We compare our findings with those published in 2004 to better understand how these city health systems have evolved.

METHODS

We compare IM rates among and within the four cities using data from four periods: 1988-1992; 1993-1997; 2003-2008 and 2012-2016. Using a maximum-likelihood negative binomial regression model that controls for births, we predict the relationship between neighbourhood-level income and IM.

RESULTS

IM rates have declined in all four cities. Neighbourhood-level income is statistically significant for New York and, for the two most recent periods, in Paris. In contrast, there is no significant relationship between neighbourhood income and IM in London or Tokyo.

CONCLUSIONS

Despite programmes to reduce IM inequalities at national and local levels, these persist in New York. Until the early part of this century, none of the other cities experienced a relationship between neighbourhood income and IM, but growing income inequalities within Paris have changed this situation and it now has geographic inequalities that are comparable to Manhattan.

POLICY IMPLICATIONS

Policy-makers in these cities should focus on better understanding the social and economic factors associated with neighbourhood inequalities in IM.

Clusters of cause specific neonatal mortality and its association with per capita gross domestic product: A structured spatial analytical approach

Background

Infant mortality rate is a measure of population health and neonatal mortality account for great proportion of these deaths. Underdevelopment might be associated to higher neonatal mortality risk due to assistant related factors. Spatial and temporal distribution of mortality help identifying and developing strategies for interventions.

Objective

To investigate the cluster areas of asphyxia-associated neonatal mortality and to explore its association with per capita gross domestic product (GDP) in São Paulo State (SP), Brazil.

Methods

Ecological study including live births residents in SP from 2004–2013. Neonatal deaths (0–27 days) with perinatal asphyxia were defined as intrauterine hypoxia, birth asphyxia or meconium aspiration syndrome written in any line of the Death Certificate. Geoprocessing analytical approach included detection of first order effects through quintiles and spatial moving average maps, followed by second order effects by global and local spatial autocorrelation (Moran and LISA, respectively) before and after smoothing with local Bayesian estimates. Finally, Spearman correlation was applied between asphyxia-associated neonatal mortality and mean per capita GDP rates for the municipalities with significant LISA.

Results

There were 6,713 asphyxia-associated neonatal deaths among 5,949,267 live births (rate: 1.13/1000) in SP. Spatial moving average maps showed a non-random distribution among municipalities, with presence of clusters (I = 0.048; p = 0.023). LISA map identified clusters of asphyxia-associated neonatal mortality in the south, southeast and northwest. After applying local Bayes estimates, clusters were more pronounced (I = 0.589; p = 0.001). There was a partial overlap of the areas of higher asphyxia-associated neonatal mortality and lower mean per capita GDP.

Conclusions

Spatial analysis identified cluster areas of high asphyxia-associated neonatal mortality and low per capita GDP rates, with a significant negative correlation. This optimized, structured, and hierarchical approach to identify high-risk areas of cause-specific neonatal mortality may be helpful for guiding public health efforts to decrease neonatal mortality.

Combined Impacts of Prenatal Environmental Exposures and Psychosocial Stress on Offspring Health: Air Pollution and Metals

PURPOSE OF REVIEW

Pregnant women and their offspring are vulnerable to the adverse effects of environmental and psychosocial stressors, individually and in combination. Here, we review the literature on how air pollution and metal exposures may interact with structural and individual-level stressors (including poverty and stressful life events) to impact perinatal and child outcomes.

RECENT FINDINGS

The adverse associations between air pollution and metal exposures and adverse infant and child health outcomes are often exacerbated by co-exposure to psychosocial stressors. Although studies vary by geography, study population, pollutants, stressors, and outcomes considered, the effects of environmental exposures and psychosocial stressors on early health outcomes are sometimes stronger when considered in combination than individually. Environmental and psychosocial stressors are often examined separately, even though their co-occurrence is widespread. The evidence that combined associations are often stronger raises critical issues around environmental justice and protection of vulnerable populations.

Infant Mortality Related to NO2 and PM Exposure: Systematic Review and Meta-Analysis

Background: We conducted this systematic review and meta-analysis to address the crucial public health issue of the suspected association between air pollution exposure during pregnancy and the risk of infant mortality. Methods: We searched on MEDLINE ^® databases among articles published until February, 2019 for case-control, cohort, and ecological studies assessing the association between maternal exposure to Nitrogen Dioxide (NO₂) or Particular matter (PM) and the risk of infant mortality including infant, neonatal, and post-neonatal mortality for all-and specific-causes as well. Study-specific risk estimates were pooled according to random-effect and fixed-effect models. Results: Twenty-four articles were included in the systematic review and 14 of the studies were taken into account in the meta-analysis. We conducted the meta-analysis for six combinations of air pollutants and infant death when at least four studies were available for the same combination. Our systematic review has revealed that the majority of studies concluded that death risk increased with increased exposure to air pollution including PM₁₀, PM_2.5, and NO₂. Our meta-analysis confirms that the risk of post-neonatal mortality all-causes for short-term exposure to PM₁₀ increased significantly (pooled-OR = 1.013, 95% CI (1.002, 1.025). When focusing on respiratory-causes, the risk of post-neonatal death related to long-term exposure to PM₁₀ reached a pooled-OR = 1.134, 95% CI (1.011, 1.271). Regarding Sudden Infant Death Syndrome (SIDS), the risk also increased significantly: pooled-OR = 1.045, 95% CI (1.01, 1.08) per 10 µg/m³), but no specific gestational windows of exposure were identified. Conclusion: In spite of a few number of epidemiological studies selected in the present literature review, our finding is in favor of a significant increase of infant death with the increase of air pollution exposure during either the pregnancy period or the first year of a newborn’s life. Our findings have to be interpreted with caution due to weaknesses that could affect the strength of the associations and then the formulation of accurate conclusions. Future studies are called to overcome these limitations; in particular, (i) the definition of infant adverse outcome, (ii) exposure assessment, and (iii) critical windows of exposure, which could affect the strength of association.

Infant Mortality in Moscow: the Perils of Progress in Russia's World City

This paper examines changes in infant mortality (IM) in Moscow, Russia's largest and most affluent city. Along with some remarkable improvements in Moscow's health system over the period between 2000 and 2014, the overall IM rate for Moscow's residents decreased substantially between 2000 and 2014. There remains, however, substantial intra-city variation across Moscow's 125 neighborhoods. Our regression models suggest that in higher-income neighborhoods measured by percent of population with rental income as a primary source, the IM rate is significantly lower than in lower-income neighborhoods measured by percent of population with transfer income as primary source (housing and utility subsidies and payments to working and low-income mothers, single mothers and foster parents). We also find that the density of physicians in a neighborhood is negatively correlated with the IM rate, but the effect is small. The density of nurses and hospital beds has no effect. We conclude that overall progress on health outcomes and measures of access does not, in itself, solve the challenge of intra-urban inequalities.

Joint Impact of Synthetic Chemical and Non-chemical Stressors on Children's Health

PURPOSE OF REVIEW

Pregnant women are exposed to numerous synthetic chemicals (e.g., pesticides, phthalates, polychlorinated biphenyls) in their daily lives as well as a range of non-chemical stressors, including poverty, depression, discrimination, and stressful life events. Although many studies have examined individual exposures to chemical and non-chemical stressors in relation to child health outcomes, very few studies have considered these exposures together. Here, we review the recent epidemiologic literature on the joint impact of chemical and non-chemical stressors on child outcomes.

RECENT FINDINGS

Considerable co-exposure to chemical and non-chemical stressors occurs in vulnerable populations. Non-chemical stressors may modify the impact of chemical exposures on children's health, typically exacerbating their negative impact, but associations differ considerably by the chemicals and populations of interest. Additional research is urgently needed to better understand the cumulative risks of multiple stressors on children's health and the underlying physiological mechanisms.

Mapping Variation in Breast Cancer Screening: Where to Intervene?

Small geographic areas with lower mammography screening participation rates may reflect gaps in screening efforts. Our objective was to use spatial analyses to understand disparities in mammography screening use and to identify factors to increase its uptake in areas that need it in Lyon metropolitan area, France. Data for screened women between the ages of 50 and 74 were analyzed. Census blocks of screened and non screened women were extracted from the mammography screening programme 2015-2016 dataset. We used spatial regression models, within a generalized additive framework to determine clusters of census blocks with significantly higher prevalence of non-participation of mammography screening. Smoothed risk maps were crude and adjusted on the following covariates: deprivation index and opportunistic screening. Among 178,002 women aged 50 to 74, 49.9% received mammography screening. As hypothesized, women living in highly deprived census blocks had lower participation rates compared to less deprived blocks, 45.2% vs. 51.4% p < 0.001. Spatial analyses identified four clusters, one located in an urban area and three in suburban areas. Moreover, depending on the location of the cluster, the influence came from different variables. Knowing the impact of site-specific risk factors seems to be important for implementing an appropriate prevention intervention.

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.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also developed a framework to map geriatric depression risk across a city, which can be used for identifying neighborhoods with higher risk for public health surveillance and sustainable urban planning.