A Comprehensive Review on Social Inequalities and Pregnancy Outcome-Identification of Relevant Pathways and Mechanisms

Scientific literature tends to support the idea that the pregnancy and health status of fetuses and newborns can be affected by maternal, parental, and contextual characteristics. In addition, a growing body of evidence reports that social determinants, measured at individual and/or aggregated level(s), play a crucial role in fetal and newborn health. Numerous studies have found social factors (including maternal age and education, marital status, pregnancy intention, and socioeconomic status) to be linked to poor birth outcomes. Several have also suggested that beyond individual and contextual social characteristics, living environment and conditions (or "neighborhood") emerge as important determinants in health inequalities, particularly for pregnant women. Using a comprehensive review, we present a conceptual framework based on the work of both the Commission on Social Determinants of Health and the World Health Organization (WHO), aimed at describing the various pathways through which social characteristics can affect both pregnancy and fetal health, with a focus on the structural social determinants (such as socioeconomic and political context) that influence social position, as well as on intermediary determinants. We also suggest that social position may influence more specific intermediary health determinants; individuals may, on the basis of their social position, experience differences in environmental exposure and vulnerability to health-compromising living conditions. Our model highlights the fact that adverse birth outcomes, which inevitably lead to health inequity, may, in turn, affect the individual social position. In order to address both the inequalities that begin in utero and the disparities observed at birth, it is important for interventions to target various unhealthy behaviors and psychosocial conditions in early pregnancy. Health policy must, then, support: (i) midwifery availability and accessibility and (ii) enhanced multidisciplinary support for deprived pregnant women.

Health Equity Impact Assessment Related to Air Pollution Reduction

Despite considerable improvements in terms of prevention, management, and regulation, air pollution remains a leading environmental health issue worldwide [...].

Physical activity and gestational weight gain: a systematic review of observational studies

BACKGROUND

Now that excessive weight gain during pregnancy is recognized as leading to complications during pregnancy that affect foetal growth, limiting weight gain during pregnancy has become a public health concern. Our aim was to perform a systematic review to assess whether observational studies reported associations between Physical Activity (PA) and Gestational Weight Gain (GWG). We were particularly interested in whether insufficient PA might be associated with high GWG.

METHODS

Using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we searched the MEDLINE ® databases for articles published up to February 2020 concerning case-control, cohort, and ecological studies assessing the association between PA during pregnancy and the risk of excessive and/or inadequate GWG.

RESULTS

21 observational studies on the PA of pregnant women were screened. 11 of these focused on excessive GWG, and of these a majority tend to show a significant association between various aspects of PA and excessive GWG. However, the results were more mitigated when it came to rate of GWG: three studies found that neither meeting PA recommendations nor high levels of total PA nor time spent in moderate vigorous physical activity (MVPA) or engaged in sedentary behaviour were associated with weekly GWG, while two others suggested that pregnant women not meeting PA guidelines in late pregnancy did have a higher rate of GWG. Of the seven studies investigating total GWG, only one found no association with PA. All studies suggested an inverse association between PA and total GWG - yet not all studies are statistically significant.

CONCLUSION

Despite the small number of observational studies selected for our research, our findings support the main international findings, suggesting that active pregnant women gained less weight than inactive women; a lack of PA may therefore contribute to excessive GWG. The limitations of this body of evidence impede the formulation of firm conclusions. Further studies focusing clearly on the general PA assessment classification scheme are called for, to address limitations capable of affecting the strength of association.

Symptoms of anxiety and depression during the COVID-19 pandemic in six European countries and Australia - Differences by prior mental disorders and migration status

BACKGROUND

Little is known about changes of mental health during the COVID-19 pandemic in potentially disadvantaged groups. We investigated changes in anxiety and depression symptoms during the first year of the pandemic in six European countries and Australia by prior mental disorders and migration status.

METHODS

Overall, 4674 adults answered a web-based survey in May-June 2020 and were followed by three repeated surveys up to February 2021. Information on psychosocial, financial and demographic, living conditions, prior mental disorders, depression and anxiety symptoms during the pandemic and migration status was collected. Weighted general estimation equations modelling was used to investigate the association between prior mental disorders, migration status, and symptoms over time.

RESULTS

Most participants were <40 years old (48%), women (78%) and highly educated (62%). The baseline prevalence of depressive and anxiety symptoms ranged between 19%-45% and 13%-35%, respectively. In most countries, prevalence rates remained unchanged throughout the pandemic and were higher among people with prior mental disorders than without even after adjustment for several factors. We observed interactions between previous mental disorders and symptoms of anxiety or depression over time in two countries. No difference by migration status was noted.

LIMITATIONS

Convenience sampling limits generalizability. Self-assessed symptoms of depression and anxiety might involve some misclassification.

CONCLUSIONS

Depression and anxiety symptoms were worse among individuals with prior mental disorders than without, but there was no clear trend of worsening mental health in the observed groups during the observed period.

[Societal inequalities and the urban exposome: Social origins for different exposures]

Today, many epidemiological studies have proved the adverse health consequences of environmental exposure. For instance, air pollution exposure is recognized to be related with respiratory and cardiovascular diseases as well as adverse pregnancy outcomes. Noise nuisances are also known to increase cardiovascular diseases and to disturb the sleeping quality. Inversely, the access and availability of various resources, as parks, green spaces, and playgrounds positively affect health, psychological and physical well-being, and favorable health behaviors. In this present literature review, we will focus on the urban dimension of exposome, defined by Robinson et al. as the accumulation of all urban settings favorable or unfavorable to health, from the time of life in utero [1].

Impact of Longitudinal Social Support and Loneliness Trajectories on Mental Health during the COVID-19 Pandemic in France

(1) Background: Little is known about how the COVID-19 pandemic has impacted social support and loneliness over time and how this may predict subsequent mental health problems. This study aims to determine longitudinal trajectories of social support and loneliness in the French general population during the first year of the COVID-19 pandemic and study whether variations in these trajectories are associated with symptoms of depression and anxiety; (2) Methods: Analyses were based on data from 681 French participants in the international COVID-19 Mental Health Study (COMET) study, collected at four periods of time between May 2020 and April 2021. Group-based trajectory modelling (GBTM) was used to determine social support and loneliness trajectories. Associations between the identified trajectories and symptoms of depression and anxiety, measured with the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder scale (GAD-7), were tested through multivariate linear regression models; (3) Results: Social support trajectories revealed four stable groups: 'poor' (17.0%), 'moderate' (42.4%), 'strong' (35.4%) and 'very strong' (5.1%). Loneliness trajectories also identified four groups: 'low stable' (17.8%), 'low rising' (40.2%), 'moderate stable' (37.6%) and 'high rising' (5.0%). Elevated symptoms of depression were associated with poor social support as well as all identified loneliness trajectories, while high levels of anxiety were associated with moderate stable and high rising loneliness trajectories; (4) Conclusions: High and increasing levels of loneliness are associated with increased symptoms of depression and anxiety during the pandemic. Interventions to address loneliness are essential to prevent common mental health problems during the pandemic and afterwards.

Measuring hospital spatial accessibility using the enhanced two-step floating catchment area method to assess the impact of spatial accessibility to hospital and non-hospital care on the length of hospital stay

Background

Optimal healthcare access improves the health status and decreases health inequalities. Many studies demonstrated the importance of spatial access to healthcare facilities in health outcomes, particularly using the enhanced two-step floating catchment area (E2SFCA) method. The study objectives were to build a hospital facility access indicator at a fine geographic scale, and then to assess the impact of spatial accessibility to inpatient hospital and non-hospital care services on the length of hospital stay (LOS).

Methods

Data concerning older adults (≥75 years) living in the Nord administrative region of France were used. Hospital spatial accessibility was computed with the E2SFCA method, and the LOS score was calculated from the French national hospital activity and patient discharge database. The relationship between LOS and spatial accessibility to inpatient hospital care and to three non-hospital care types (general practitioners, physiotherapists, and home-visiting nurses) was analyzed with linear regression models.

Results

The mean number (standard deviation) of beds per 10,000 inhabitants was 19.0 (10.69) in Medical, Surgical and Obstetrics (MCO) facilities and 5.58 (2.19) in Postoperative and Rehabilitation Care (SSR) facilities, highlighting important variations within the region. Accessibility to hospital services was higher in large urban areas, despite the dense population and higher demand. In 2014, the mean LOS scores were 0.26 for MCO and 0.85 for SSR, but their geographical repartition was non-homogeneous. The linear regression analysis revealed a strong negative and significant association between LOS and non-hospital care accessibility.

Conclusions

This is the first study to measure spatial accessibility to inpatient hospital care in France using the E2SFCA method, and to investigate the relationship between healthcare utilization (LOS score) and spatial accessibility to inpatient hospital care facilities and three types of non-hospital care services. Our findings might help to make decisions about deploying additional beds and to identify the best locations for non-hospital care services. They might also contribute to improve access, and to ensure the best coordination and sustainability of inpatient and outpatient services, in order to better cover the population’s healthcare needs. International studies using multiple consensual indicators of healthcare outcomes and accessibility and sophisticated modeling methods are needed.

Efficiency of fine scale and spatial regression in modelling associations between healthcare service spatial accessibility and their utilization

BACKGROUND

Healthcare accessibility, a key public health issue, includes potential (spatial accessibility) and realized access (healthcare utilization) dimensions. Moreover, the assessment of healthcare service potential access and utilization should take into account the care provided by primary and secondary services. Previous studies on the relationship between healthcare spatial accessibility and utilization often used conventional statistical methods without addressing the scale effect and spatial processes. This study investigated the impact of spatial accessibility to primary and secondary healthcare services on length of hospital stay (LOS), and the efficiency of using a geospatial approach to model this relationship.

METHODS

This study focused on the ≥ 75-year-old population of the Nord administrative region of France. Inpatient hospital spatial accessibility was computed with the E2SFCA method, and then the LOS was calculated from the French national hospital activity and patient discharge database. Ordinary least squares (OLS), spatial autoregressive (SAR), and geographically weighted regression (GWR) were used to analyse the relationship between LOS and spatial accessibility to inpatient hospital care and to three primary care service types (general practitioners, physiotherapists, and home-visiting nurses). Each model performance was assessed with measures of goodness of fit. Spatial statistical methods to reduce or eliminate spatial autocorrelation in the residuals were also explored.

RESULTS

GWR performed best (highest R2 and lowest Akaike information criterion). Depending on global model (OLS and SAR), LOS was negatively associated with spatial accessibility to general practitioners and physiotherapists. GWR highlighted local patterns of spatial variation in LOS estimates. The distribution of areas in which LOS was positively or negatively associated with spatial accessibility varied when considering accessibility to general practitioners and physiotherapists.

CONCLUSIONS

Our findings suggest that spatial regressions could be useful for analysing the relationship between healthcare spatial accessibility and utilization. In our case study, hospitalization of elderly people was shorter in areas with better accessibility to general practitioners and physiotherapists. This may be related to the presence of effective community healthcare services. GWR performed better than LOS and SAR. The identification by GWR of how these relationships vary spatially could bring important information for public healthcare policies, hospital decision-making, and healthcare resource allocation.

Are the effects of air pollution on birth weight modified by infant sex and neighborhood socioeconomic deprivation? A multilevel analysis in Paris (France)

Adverse birth outcomes related to air pollution are well documented; however, few studies have accounted for infant sex. There is also scientific evidence that the neighborhood socioeconomic profile may modify this association even after adjusting for individual socioeconomic characteristics. The objective is to analyze the association between air pollution and birth weight by infant sex and neighborhood socioeconomic index. All birth weights (2008-2011) were geocoded at census block level. Each census block was assigned a socioeconomic deprivation level, as well as daily NO2 and PM10 concentrations. We performed a multilevel model with a multiple statistical test and sensible analysis using the spline function. Our findings suggest the existence of a differential association between air pollution and BW according to both neighborhood socioeconomic level and infant sex. However, due to multiple statistical tests and controlling the false discovery rate (FDR), all significant associations became either not statistically significant or borderline. Our findings reinforce the need for additional studies to investigate the role of the neighborhood socioeconomic which could differentially modify the air pollution effect.

Geographical Pattern of COVID-19-Related Outcomes over the Pandemic Period in France: A Nationwide Socio-Environmental Study

BACKGROUND

Several studies have investigated the implication of air pollution and some social determinants on COVID-19-related outcomes, but none of them assessed the implication of spatial repartition of the socio-environmental determinants on geographic variations of COVID-19 related outcomes. Understanding spatial heterogeneity in relation to the socio-environmental determinant and COVID-19-related outcomes is central to target interventions toward a vulnerable population.

OBJECTIVES

To determine the spatial variability of COVID-19 related outcomes among the elderly in France at the department level. We also aimed to assess whether a geographic pattern of Covid-19 may be partially explained by spatial distribution of both long-term exposure to air pollution and deprived living conditions.

METHODS

This study considered four health events related to COVID-19 infection over the period of 18 March and 02 December 2020: (i) hospitalization, (ii) cases in intensive health care in the hospital, (iii) death in the hospital, and (iv) hospitalized patients recovered and returned back home. We used the percentage of household living in an overcrowding housing to characterize the living conditions and long-term exposure to NO2 to analyse the implication of air pollution. Using a spatial scan statistic approach, a Poisson cluster analysis method based on a likelihood ratio test and Monte Carlo replications was applied to identify high-risk clusters of a COVID-19-related outcome.

RESULT

our results revealed that all the outcomes related to COVID-19 infection investigated were not randomly distributed in France with a statistically significant cluster of high risk located in Eastern France of the hospitalization, cases in the intensive health care at the hospital, death in the hospital, and recovered and returned back home compared to the rest of France (relative risk, RR = 1.28, p-value = 0.001, RR = 3.05, p = 0.001, RR = 2.94, p = 0.001, RR = 2.51, p = 0.001, respectively). After adjustments for socio-environmental determinants, the crude cluster shifts according to different scenarios suggested that both the overcrowding housing level and long-term exposure to largely NO2 explain the spatial distribution of COVID-19-related outcomes.

CONCLUSIONS

Our findings suggest that the geographic pattern of COVID-19-related outcomes is largely explained by socio-spatial distribution of long-term exposure to NO2. However, to better understand spatial variations of COVID-19-related outcomes, it would be necessary to investigate and adjust it for other determinants. Thus, the current sanitary crisis reminds us of how unequal we all are in facing this disease.

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.

Influence of Individual and Contextual Perceptions and of Multiple Neighborhoods on Depression

The risk of depression is related to multiple various determinants. The consideration of multiple neighborhoods daily frequented by individuals has led to increased interest in analyzing socio-territorial inequalities in health. In this context, the main objective of this study was (i) to describe and analyze the spatial distribution of depression and (ii) to investigate the role of the perception of the different frequented spaces in the risk of depression in the overall population and in the population stratified by gender. Data were extracted from the 2010 SIRS (a French acronym for "health, inequalities and social ruptures") cohort survey. In addition to the classic individual characteristics, the participants reported their residential neighborhoods, their workplace neighborhoods and a third one: a daily frequented neighborhood. A new approach was developed to simultaneously consider the three reported neighborhoods to better quantify the level of neighborhood socioeconomic deprivation. Multiple simple and cross-classified multilevel logistic regression models were used to analyze the data. Depression was reported more frequently in low-income (OR = 1.89; CI = [1.07-3.35]) or middle-income (OR = 1.91; CI = [1.09-3.36]) neighborhoods and those with cumulative poverty (OR = 1.64; CI = [1.10-2.45]). In conclusion, a cumulative exposure score, such as the one presented here, may be an appropriate innovative approach to analyzing their effects in the investigation of socio-territorial inequalities in health.

Asthma and Indoor Environment: Usefulness of a Global Allergen Avoidance Method on Asthma Control and Exposure to Molds

The usefulness and feasibility of a global allergens avoidance method with counselors visiting patients' home for allergens measures and adapted advices were prospectively evaluated through asthma control and environment evaluation. Twenty seven patients were prospectively included and compared to a cohort of 30 control patients. The level of control of asthma at inclusion and after 1 year was evaluated by the clinical signs, the evolution of the FEV1, and the healthcare use. Environmental measurements included the fungal load of 5 surfaces of the dwellings and the evaluation of moisture. A significant clinical improvement in the population that benefited from the home counselors visit was observed compared to the baseline (p < 0.0001), as well as a decreased number of hospitalizations for asthma and of the consumption of anti-asthma drugs (p < 0.01). Dampness markers slightly improved with an improvement of the fungal loads in two-third of the dwellings.

Assessment of the spatial accessibility to health professionals at French census block level

Background

The evaluation of geographical healthcare accessibility in residential areas provides crucial information to public policy. This work developed an improved indicator: the Index of Spatial Accessibility (ISA) to measure geographical healthcare accessibility at the smallest available infra-urban level, that is, the Îlot Regroupé pour des Indicateurs Statistiques.

Methods

This study was carried out in the department of Nord, France. Healthcare professionals are geolocalized using postal addresses available on the French state health insurance website. ISA is derived from Enhanced Two-Step Floating Catchment Area (E2FCA) algorithm. We have constructed a catchment for each healthcare provider, by taking into account residential building centroids, car travel time as calculated by Google Maps and the edge effect. Principal Component Analyses (PCA) were used to build a composite ISA to describe the global accessibility of different kinds of health professionals.

Results

We applied our method to studying geographical healthcare accessibility for pregnant women, by selecting three types of healthcare provider: general practitioners, gynecologists and midwives. A total of 3587 healthcare providers are potentially able to provide care for inhabitants of the department of Nord. On average there are 92 general practitioners, 22 midwives and 21 gynecologists per 100,000 residents. The composite ISA for the three types of healthcare provider is 39 per 100,000 residents.

Conclusions

ISA is a multidimensional and improved measure, which combines the volume of services relative to population size with the proximity of services relative to the population’s location, available at the smallest feasible geographical scale. It could guide policy makers towards highlighting critical areas in need of more healthcare providers, and these areas should be earmarked for further knowledge-based policy making.

Key messages

Indicator of healthcare access at fine spatial scale allows us to identify precisely critical areas where healthcare professionals need to be allocated. ISA is a multidimensional measure, which combines the volume of services relative to population size with the proximity of services relative to the population’s location.

Education and hypertension in the CONSTANCES cohort: which factors mediate this association?

Background

Individual socioeconomic characteristics and in particular education have been shown to be strongly associated with hypertension (HTN). Few studies have examined the mechanisms involved in such associations and understanding them would help to reduce the burden of social inequalities. We aimed to investigate whether specific risk factors of HTN intervene as mediators in the association between individual education and HTN in a large sample of French adults.

Methods

In this cross-sectional analysis, participants are adults aged between 18 and 69 years old recruited to the CONSTANCES cohort over the period 2012-2015. We included behavioral (poor diet, physical inactivity, alcohol consumption), anthropometric (body mass index) and socioeconomic risk factors (income and longest occupation) as potential mediators. Analyses were stratified by sex. Natural direct and indirect effects of education on HTN were estimated using weighted Poisson regression models with inverse odds weighting.

Results

A total of 62,247 individuals (53% women, mean age 48±13 years) were included. Prevalence of HTN was 37.3% [95%-Confidence Interval (95%-CI) =36.6-38.0] in men and 23.2% [95%-CI=22.7-23.8] in women. We found a steep educational gradient of HTN in both sexes, larger among young adults in relative terms. Low education was strongly associated with HTN: RRTotal Effect=1.16 [95%-CI=1.12-1.21] in men and 1.26 [95%-CI=1.21-1.32] in women. Behavioral, anthropometric and socioeconomic risk factors accounted for 49% and 32% of the total effect in men and women respectively.

Conclusions

This study underlines the importance of education in inequalities in HTN and suggests that behavioral, anthropometric and socioeconomic risk factors substantially mediate the association between education and HTN. Future research using longitudinal data should be done to help understand the causal pathway linking education and HTN.

Key messages

A strong gradient of decreased prevalence of hypertension with higher individual education is observed in both sexes and in early adulthood, suggesting that prevention should start early. Behavioral, anthropometric and socioeconomic characteristics at adulthood substantially mediate the association between education and hypertension.

Adverse Birth Outcomes as Indicators of Poor Fetal Growth Conditions in a French Newborn Population-A Stratified Analysis by Neighborhood Deprivation Level

Background: Adverse birth outcomes are related to unfavorable fetal growth conditions. A latent variable, named Favorable Fetal Growth Condition (FFGC), has been defined by Bollen et al., in 2013; he showed that this FFGC latent variable mediates the effects of maternal characteristics on several birth outcomes. Objectives: The objectives of the present study were to replicate Bollen’s approach in a population of newborns in Paris and to investigate the potential differential effect of the FFGC latent variable according to the neighborhood socioeconomic level. Methods: Newborn health data were available from the first birth certificate registered by the Maternal and Child Care department of the City of Paris. All newborns (2008–2011) were geocoded at the mother residential census block. Each census block was assigned a socioeconomic deprivation level. Several mothers’ characteristics were collected from the birth certificates: age, parity, education and occupational status and the occupational status of the father. Three birth outcomes were considered: birth weight (BW), birth length (BL) and gestational age (GA). Results: Using a series of structural equation models, we confirm that the undirected model (that includes the FFGC latent variable) provided a better fit for the data compared with the model where parental characteristics directly affected BW, BL, and/or GA. However, the strength, the direction and statistical significance of the associations between the exogenous variables and the FFGC were different according to the neighborhood deprivation level. Conclusion: Future research should be designed to assess the how robust the FFGC latent variable is across populations and should take into account neighborhood characteristics to identify the most vulnerable group and create better design prevention policies.

Geographical variations in the prevalence of hypertension in France: Cross-sectional analysis of the CONSTANCES cohort

AIMS

While international variations in the prevalence of hypertension are well described, less is known about intra-national disparities and their determinants. We wanted to describe the variations in hypertension prevalence within France and to determine how much lifestyle and socioeconomic factors contributed to explain these regional variations.

METHODS

Participants (62,247 French adults aged 18 to 69 years) were recruited in the 16 centres of the CONSTANCES study between 2012 and 2015. Hypertension was defined as blood pressure higher than 140/90 mmHg and/or taking antihypertensive medications. The contribution of lifestyle and socioeconomic factors to hypertension prevalence variations among centres was examined using sequential hierarchical logistic models.

RESULTS

Hypertension prevalence was 37.3% (95% confidence interval (CI) = 36.6-38.0) in men and 23.2% (95% CI = 22.7-23.8) in women. Hypertension prevalence rates varied by almost two-fold among centres (1.9 in men, 1.6 in women) with the highest prevalence in the north and the east of France. Body mass index was strongly associated with hypertension in women (odds ratio (OR)_{1-unit increase} = 1.11 (95% CI = 1.11-1.12)) and was the highest contributor to between-centre variations (27% in women), followed by socioeconomic characteristics (e.g. OR_{high versus low education} = 0.85 (95% CI = 0.83-0.87), contributing to 14% of variations in women). Together, family history of hypertension, body mass index, education, occupation and residential area socioeconomic level explained about 30% and 40% of between-centre variations in men and women, respectively.

CONCLUSION

Hypertension prevalence greatly varies among French regions and this is partly explained by known lifestyle and socioeconomic factors. Nevertheless, these variations and all the hypertension determinants have not been fully deciphered yet.

Does residential mobility during pregnancy induce exposure misclassification for air pollution?

BACKGROUND

Prenatal exposure to outdoor air pollution has been shown to have health effects in many studies; low birth weight, preterm delivery, small for gestational age, and stillbirth are the most often cited. However, exposure of pregnant women is difficult to quantify, especially with regard to their mobility, which is rarely taken into account in epidemiological studies. This study aimed to assess the impact of mobility of pregnant women living in Paris, France, on their exposure estimates to nitrogen dioxide (NO₂).

METHODS

A total of 486 pregnant women were recruited in 5 maternity hospitals in Paris between January and April 2016. A questionnaire was used to collect mothers' characteristics (demography, education, etc.) and to assess their daily mobility during pregnancy (time spent at work, commuting time and mode used to move from residential to occupational places). Daily NO₂ concentrations were estimated based on the combination of annual average concentrations modeled at the census block scale and daily concentrations measured from fixed monitoring stations. Different models were used to compare the exposure of pregnant women in residential and occupational places, also taking into account travel time and travel mode. The socioeconomic profile of the census blocks was characterized using a multi-component index.

RESULTS

During the first trimester of pregnancy, women living in the least deprived census blocks were exposed to higher concentrations of NO₂ than those living in the most deprived ones. Occupational mobility had a small impact on exposure levels (average increase after taking account of mobility: + 0.52 μg/m³) which was not related to the socioeconomic profile of the women. The commuting mode made a greater difference (+ 1.46 μg/m³ on average), in particular among women living in the most deprived census blocks.

CONCLUSIONS

Our study illustrates that air pollution exposure can be underestimated when ignoring occupational mobility and commuting mode of pregnant women. This effect might be differential according to the neighborhood deprivation profile.

Does the edge effect impact on the measure of spatial accessibility to healthcare providers?

BACKGROUND

Spatial accessibility indices are increasingly applied when investigating inequalities in health. Although most studies are making mentions of potential errors caused by the edge effect, many acknowledge having neglected to consider this concern by establishing spatial analyses within a finite region, settling for hypothesizing that accessibility to facilities will be under-reported. Our study seeks to assess the effect of edge on the accuracy of defining healthcare provider access by comparing healthcare provider accessibility accounting or not for the edge effect, in a real-world application.

METHODS

This study was carried out in the department of Nord, France. The statistical unit we use is the French census block known as 'IRIS' (Ilot Regroupé pour l'Information Statistique), defined by the National Institute of Statistics and Economic Studies. The geographical accessibility indicator used is the "Index of Spatial Accessibility" (ISA), based on the E2SFCA algorithm. We calculated ISA for the pregnant women population by selecting three types of healthcare providers: general practitioners, gynecologists and midwives. We compared ISA variation when accounting or not edge effect in urban and rural zones. The GIS method was then employed to determine global and local autocorrelation. Lastly, we compared the relationship between socioeconomic distress index and ISA, when accounting or not for the edge effect, to fully evaluate its impact.

RESULTS

The results revealed that on average ISA when offer and demand beyond the boundary were included is slightly below ISA when not accounting for the edge effect, and we found that the IRIS value was more likely to deteriorate than improve. Moreover, edge effect impact can vary widely by health provider type. There is greater variability within the rural IRIS group than within the urban IRIS group. We found a positive correlation between socioeconomic distress variables and composite ISA. Spatial analysis results (such as Moran's spatial autocorrelation index and local indicators of spatial autocorrelation) are not really impacted.

CONCLUSION

Our research has revealed minor accessibility variation when edge effect has been considered in a French context. No general statement can be set up because intensity of impact varies according to healthcare provider type, territorial organization and methodology used to measure the accessibility to healthcare. Additional researches are required in order to distinguish what findings are specific to a territory and others common to different countries. It constitute a promising direction to determine more precisely healthcare shortage areas and then to fight against social health inequalities.

Small-area spatiotemporal analysis of heatwave impacts on elderly mortality in Paris: A cluster analysis approach

BACKGROUND

Heat-waves have a substantial public health burden. Understanding spatial heterogeneity at a fine spatial scale in relation to heat and related mortality is central to target interventions towards vulnerable communities.

OBJECTIVES

To determine the spatial variability of heat-wave-related mortality risk among elderly in Paris, France at the census block level. We also aimed to assess area-level social and environmental determinants of high mortality risk within Paris.

METHODS

We used daily mortality data from 2004 to 2009 among people aged >65 at the French census block level within Paris. We used two heat wave days' definitions that were compared to non-heat wave days. A Bernoulli cluster analysis method was applied to identify high risk clusters of mortality during heat waves. We performed random effects meta-regression analyses to investigate factors associated with the magnitude of the mortality risk.

RESULTS

The spatial approach revealed a spatial aggregation of death cases during heat wave days. We found that small scale chronic PM₁₀ exposure was associated with a 0.02 (95% CI: 0.001; 0.045) increase of the risk of dying during a heat wave episode. We also found a positive association with the percentage of foreigners and the percentage of labor force, while the proportion of elderly people living in the neighborhood was negatively associated. We also found that green space density had a protective effect and inversely that the density of constructed feature increased the risk of dying during a heat wave episode.

CONCLUSION

We showed that a spatial variation in terms of heat-related vulnerability exists within Paris and that it can be explained by some contextual factors. This study can be useful for designing interventions targeting more vulnerable areas and reduce the burden of heat waves.

Developing a data-driven spatial approach to assessment of neighbourhood influences on the spatial distribution of myocardial infarction

BACKGROUND

There is a growing understanding of the role played by 'neighbourhood' in influencing health status. Various neighbourhood characteristics-such as socioeconomic environment, availability of amenities, and social cohesion, may be combined-and this could contribute to rising health inequalities. This study aims to combine a data-driven approach with clustering analysis techniques, to investigate neighbourhood characteristics that may explain the geographical distribution of the onset of myocardial infarction (MI) risk.

METHODS

All MI events in patients aged 35-74 years occurring in the Strasbourg metropolitan area (SMA), from January 1, 2000 to December 31, 2007 were obtained from the Bas-Rhin coronary heart disease register. All cases were geocoded to the census block for the residential address. Each areal unit, characterized by contextual neighbourhood profile, included socioeconomic environment, availability of amenities (including leisure centres, libraries and parks, and transport) and psychosocial environment as well as specific annual rates standardized (per 100,000 inhabitants). A spatial scan statistic implemented in SaTScan was then used to identify statistically significant spatial clusters of high and low risk of MI.

RESULT

MI incidence was non-randomly spatially distributed, with a cluster of high risk of MI in the northern part of the SMA [relative risk (RR) = 1.70, p = 0.001] and a cluster of low risk of MI located in the first and second periphery of SMA (RR 0.04, p value  =  0.001). Our findings suggest that the location of low MI risk is characterized by a high socioeconomic level and a low level of access to various amenities; conversely, the location of high MI risk is characterized by a high level of socioeconomic deprivation-despite the fact that inhabitants have good access to the local recreational and leisure infrastructure.

CONCLUSION

Our data-driven approach highlights how the different contextual dimensions were inter-combined in the SMA. Our spatial approach allowed us to identify the neighbourhood characteristics of inhabitants living within a cluster of high versus low MI risk. Therefore, spatial data-driven analyses of routinely-collected data georeferenced by various sources may serve to guide policymakers in defining and promoting targeted actions at fine spatial level.

Systematic literature review of reproductive outcome associated with residential proximity to polluted sites

This study aims to assess the evidence on adverse pregnancy outcome associated with living close to polluted industrial sites, and identify the strengths and weaknesses of published epidemiological studies. A systematic literature search has been performed on all epidemiological studies published in developed countries since 1990, on the association between residential proximity to industrial sites (hazardous waste sites, industrial facilities and landfill sites) and adverse pregnancy outcome (low birth weight, preterm birth, small for gestational age, intrauterine growth retardation, infant mortality, congenital malformation). Based on 41 papers, our review reveals an excess risk of reproductive morbidity. However, no studies show significant excess risk of mortality including fetal death, neonatal or infant mortality and stillbirth. All published studies tend to show an increased risk of congenital abnormalities, yet not all are statistically significant. All but two of these studies revealed an excess risk of low birth weight. Results for preterm birth, small for gestational age and intrauterine growth retardation show the same pattern. There is suggestive evidence from the post-1990 literature that residential proximity to polluted sites (including landfills, hazardous waste sites and industrial facilities) might contribute to adverse reproductive outcomes, especially congenital malformations and low birth weight—though not mortality. This body of evidence has limitations that impede the formulation of firm conclusions, and new, well-focused studies are called for. The review findings suggest that continued strengthening of rules governing industrial emissions as well as industrial waste management and improved land use planning are needed.

Neighborhood Deprivation and Risk of Congenital Heart Defects, Neural Tube Defects and Orofacial Clefts: A Systematic Review and Meta-Analysis

Background

We conducted this systematic review and meta-analysis to address the open question of a possible association between the socioeconomic level of the neighborhoods in which pregnant women live and the risk of Congenital Heart Defects (CHDs), Neural Tube Defects (NTDs) and OroFacial Clefts (OFCs).

Methods

We searched MEDLINE from its inception to December 20^th, 2015 for case-control, cohort and ecological studies assessing the association between neighborhood socioeconomic level and the risk of CHDs, NTDs and the specific phenotypes Cleft Lip with or without Cleft Palate (CLP) and Cleft Palate (CP). Study-specific risk estimates were pooled according to random-effect and fixed-effect models.

Results

Out of 245 references, a total of seven case-control studies, two cohort studies and two ecological studies were assessed in the systematic review; all studies were enrolled in the meta-analysis with the exception of the two cohort studies. No significant association has been revealed between CHDs or NTDs and neighborhood deprivation index. For CLP phenotype subgroups, we found a significantly higher rate in deprived neighborhoods (Odds Ratios (OR) = 1.22, 95% CI: 1.10, 1.36) whereas this was not significant for CP phenotype subgroups (OR = 1.20, 95%CI: 0.89, 1.61).

Conclusion

In spite of the small number of epidemiological studies included in the present literature review, our findings suggest that neighborhood socioeconomic level where mothers live is associated only with an increased risk of CLP phenotype subgroups. This finding has methodological limitations that impede the formulation of firm conclusions, and further investigations should confirm this association.

Assessment of the spatial accessibility to health professionals at French census block level

BACKGROUND

The evaluation of geographical healthcare accessibility in residential areas provides crucial information to public policy. Traditional methods - such as Physician Population Ratios (PPR) or shortest travel time - offer only a one-dimensional view of accessibility. This paper developed an improved indicator: the Index of Spatial Accessibility (ISA) to measure geographical healthcare accessibility at the smallest available infra-urban level, that is, the Îlot Regroupé pour des Indicateurs Statistiques.

METHODS

This study was carried out in the department of Nord, France. Healthcare professionals are geolocalized using postal addresses available on the French state health insurance website. ISA is derived from an Enhanced Two-Step Floating Catchment Area (E2FCA). We have constructed a catchment for each healthcare provider, by taking into account residential building centroids, car travel time as calculated by Google Maps and the edge effect. Principal Component Analyses (PCA) were used to build a composite ISA to describe the global accessibility of different kinds of health professionals.

RESULTS

We applied our method to studying geographical healthcare accessibility for pregnant women, by selecting three types of healthcare provider: general practitioners, gynecologists and midwives. A total of 3587 healthcare providers are potentially able to provide care for inhabitants of the department of Nord. On average there are 92 general practitioners, 22 midwives and 21 gynecologists per 100,000 residents. The composite ISA for the three types of healthcare provider is 39 per 100,000 residents. A comparative analysis between ISA and physician-population ratios indicates that ISA represents a more even distribution whereas the physician-population ratios show an 'all-or-nothing' approach.

CONCLUSION

ISA is a multidimensional and improved measure, which combines the volume of services relative to population size with the proximity of services relative to the population's location, available at the smallest feasible geographical scale. It could guide policy makers towards highlighting critical areas in need of more healthcare providers, and these areas should be earmarked for further knowledge-based policy making.

The need for, and value of, a spatial scan statistical tool for tackling social health inequalities

Today, one important challenge in developed countries is health inequalities. Research conducted in public health policy issues supply little evidence for effective interventions aiming to improve population health and to reduce health inequalities. There is a need for a powerful tool to support priority setting and guide policy makers in their choice of health interventions, and that maximizes social welfare. This paper proposes to divert a spatial tool based on Kulldorff's scan method to investigate social inequalities in health. This commentary argues that this spatial approach can be a useful tool to tackle social inequalities in health by guiding policy makers at three levels: (i) supporting priority setting and planning a targeted intervention; (ii) choosing actions or interventions which will be performed for the whole population, but with a scale and intensity proportionate to need; and (iii) assessing health equity of public interventions.

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

Infant and neonatal mortality indicators are known to vary geographically, possibly as a result of socioeconomic and environmental inequalities. To better understand how these factors contribute to spatial and temporal patterns, we conducted a French ecological study comparing two time periods between 2002 and 2009 for three (purposefully distinct) Metropolitan Areas (MAs) and the city of Paris, using the French census block of parental residence as the geographic unit of analysis. We identified areas of excess risk and assessed the role of neighborhood deprivation and average nitrogen dioxide concentrations using generalized additive models to generate maps smoothed on longitude and latitude. Comparison of the two time periods indicated that statistically significant areas of elevated infant and neonatal mortality shifted northwards for the city of Paris, are present only in the earlier time period for Lille MA, only in the later time period for Lyon MA, and decrease over time for Marseille MA. These city-specific geographic patterns in neonatal and infant mortality are largely explained by socioeconomic and environmental inequalities. Spatial analysis can be a useful tool for understanding how risk factors contribute to disparities in health outcomes ranging from infant mortality to infectious disease-a leading cause of infant mortality.

Volatile and semi-volatile organic compounds of respiratory health relevance in French dwellings

Over the last decades, the prevalence of childhood respiratory conditions has dramatically increased worldwide. Considering the time spent in enclosed spaces, indoor air pollutants are of major interest to explain part of this increase. This study aimed to measure the concentrations of pollutants known or suspected to affect respiratory health that are present in dwellings in order to assess children's exposure. Measurements were taken in 150 homes with at least one child, in Brittany (western France), to assess the concentrations of 18 volatile organic compounds (among which four aldehydes and four trihalomethanes) and nine semi-volatile organic compounds (seven phthalates and two synthetic musks). In addition to descriptive statistics, a principal component analysis (PCA) was used to investigate grouping of contaminants. Formaldehyde was highly present and above 30 μg/m(3) in 40% of the homes. Diethyl phthalate, diisobutyl phthalate, and dimethylphthalate were quantified in all dwellings, as well as Galaxolide and Tonalide. For each chemical family, the groups appearing in the PCA could be interpreted in term of sources. The high prevalence and the levels of these compounds, with known or suspected respiratory toxicity, should question regulatory agencies to trigger prevention and mitigation actions.

Influence of Socio-Economic Inequalities on Access to Renal Transplantation and Survival of Patients with End-Stage Renal Disease

Background

Public and scientific concerns about the social gradient of end-stage renal disease and access to renal replacement therapies are increasing. This study investigated the influence of social inequalities on the (i) access to renal transplant waiting list, (ii) access to renal transplantation and (iii) patients’ survival.

Methods

All incident adult patients with end-stage renal disease who lived in Bretagne, a French region, and started dialysis during the 2004–2009 period were geocoded in census-blocks. To each census-block was assigned a level of neighborhood deprivation and a degree of urbanization. Cox proportional hazards models were used to identify factors associated with each study outcome.

Results

Patients living in neighborhoods with low level of deprivation had more chance to be placed on the waiting list and less risk of death (HR = 1.40 95%CI: [1.1–1.7]; HR = 0.82 95%CI: [0.7–0.98]), but this association did not remain after adjustment for the patients’ clinical features. The likelihood of receiving renal transplantation after being waitlisted was not associated with neighborhood deprivation in univariate and multivariate analyses.

Conclusions

In a mixed rural and urban French region, patients living in deprived or advantaged neighborhoods had the same chance to be placed on the waiting list and to undergo renal transplantation. They also showed the same mortality risk, when their clinical features were taken into account.

Data analysis techniques: a tool for cumulative exposure assessment

Everyone is subject to environmental exposures from various sources, with negative health impacts (air, water and soil contamination, noise, etc.or with positive effects (e.g. green space). Studies considering such complex environmental settings in a global manner are rare. We propose to use statistical factor and cluster analyses to create a composite exposure index with a data-driven approach, in view to assess the environmental burden experienced by populations. We illustrate this approach in a large French metropolitan area. The study was carried out in the Great Lyon area (France, 1.2 M inhabitants) at the census Block Group (BG) scale. We used as environmental indicators ambient air NO2 annual concentrations, noise levels and proximity to green spaces, to industrial plants, to polluted sites and to road traffic. They were synthesized using Multiple Factor Analysis (MFA), a data-driven technique without a priori modeling, followed by a Hierarchical Clustering to create BG classes. The first components of the MFA explained, respectively, 30, 14, 11 and 9% of the total variance. Clustering in five classes group: (1) a particular type of large BGs without population; (2) BGs of green residential areas, with less negative exposures than average; (3) BGs of residential areas near midtown; (4) BGs close to industries; and (5) midtown urban BGs, with higher negative exposures than average and less green spaces. Other numbers of classes were tested in order to assess a variety of clustering. We present an approach using statistical factor and cluster analyses techniques, which seem overlooked to assess cumulative exposure in complex environmental settings. Although it cannot be applied directly for risk or health effect assessment, the resulting index can help to identify hot spots of cumulative exposure, to prioritize urban policies or to compare the environmental burden across study areas in an epidemiological framework.

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France

Background

Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France.

Methods

All adult patients living in Bretagne and beginning renal replacement therapy during the 2004–09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence.

Results

The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted.

Conclusions

Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Effects of air pollution on the risk of congenital anomalies: a systematic review and meta-analysis

Congenital anomalies are the main causes of preterm and neonatal mortality and morbidity. We investigated the association between congenital anomalies and mothers' exposure to air pollution during pregnancy by combining risk estimates for a variety of air pollutants (SO2, NO2, PM10, PM2.5, CO and O3) and anomaly defect outcomes. Seventeen articles were included in the systematic review and thirteen studies were taken into account in the meta-analysis. Combined estimated were calculated separately according to whether the exposure metric was continuous or categorical. Only one significant combination was; NO2 concentrations were significantly associated with coarctation of the aorta (OR = 1.20 per 10 ppb, 95% CI, (1.02, 1.41)). This finding could stem from strong heterogeneity in study designs. Improved exposure assessment methods, in particular more accurate spatial measurements or modeling, standardized definition of cases and of better control of confounders are highly recommended for future congenital anomalies research in this area.

Chronic air pollution and social deprivation as modifiers of the association between high temperature and daily mortality

BACKGROUND

Heat and air pollution are both associated with increases in mortality. However, the interactive effect of temperature and air pollution on mortality remains unsettled. Similarly, the relationship between air pollution, air temperature, and social deprivation has never been explored.

METHODS

We used daily mortality data from 2004 to 2009, daily mean temperature variables and relative humidity, for Paris, France. Estimates of chronic exposure to air pollution and social deprivation at a small spatial scale were calculated and split into three strata. We developed a stratified Poisson regression models to assess daily temperature and mortality associations, and tested the heterogeneity of the regression coefficients of the different strata. Deaths due to ambient temperature were calculated from attributable fractions and mortality rates were estimated.

RESULTS

We found that chronic air pollution exposure and social deprivation are effect modifiers of the association between daily temperature and mortality. We found a potential interactive effect between social deprivation and chronic exposure with regards to air pollution in the mortality-temperature relationship.

CONCLUSION

Our results may have implications in considering chronically polluted areas as vulnerable in heat action plans and in the long-term measures to reduce the burden of heat stress especially in the context of climate change.

An exploratory spatial analysis to assess the relationship between deprivation, noise and infant mortality: an ecological study

BACKGROUND

Few studies have explored how noise might contribute to social health inequalities, and even fewer have considered infant mortality or its risk factors as the health event of interest.In this paper, we investigate the impact of neighbourhood characteristics - both socio-economic status and ambient noise levels - on the spatial distribution of infant mortality in the Lyon metropolitan area, in France.

METHODS

All infant deaths (n = 715) occurring between 2000 and 2009 were geocoded at census block level. Each census block was assigned multi-component socio-economic characteristics and Lden levels, which measure exposure to noise. Using a spatial-scan statistic, we examined whether there were significant clusters of high risk of infant mortality according to neighbourhood characteristics.

RESULTS

Our results highlight the fact that infant mortality is non-randomly distributed spatially, with clusters of high risk in the south-east of the Lyon metropolitan area (RR = 1.44; p = 0.09). After adjustments for socio-economic characteristics and noise levels, this cluster disappears or shifts according to in line with different scenarios, suggesting that noise and socio-economic characteristics can partially explain the spatial distribution of infant mortality.

CONCLUSION

Our findings show that noise does have an impact on the spatial distribution of mortality after adjustments for socio-economic characteristics. A link between noise and infant mortality seems plausible in view of the three hypothetical, non-exclusive, pathways we propose in our conceptual framework: (i) a psychological pathway, (ii) a physiological disruption process and (iii) an unhealthy behaviours pathway. The lack of studies makes it is difficult to compare our findings with others. They require further research for confirmation and interpretation.

A statistical procedure to create a neighborhood socioeconomic index for health inequalities analysis

Introduction

In order to study social health inequalities, contextual (or ecologic) data may constitute an appropriate alternative to individual socioeconomic characteristics. Indices can be used to summarize the multiple dimensions of the neighborhood socioeconomic status. This work proposes a statistical procedure to create a neighborhood socioeconomic index.

Methods

The study setting is composed of three French urban areas. Socioeconomic data at the census block scale come from the 1999 census. Successive principal components analyses are used to select variables and create the index. Both metropolitan area-specific and global indices are tested and compared. Socioeconomic categories are drawn with hierarchical clustering as a reference to determine “optimal” thresholds able to create categories along a one-dimensional index.

Results

Among the twenty variables finally selected in the index, 15 are common to the three metropolitan areas. The index explains at least 57% of the variance of these variables in each metropolitan area, with a contribution of more than 80% of the 15 common variables.

Conclusions

The proposed procedure is statistically justified and robust. It can be applied to multiple geographical areas or socioeconomic variables and provides meaningful information to public health bodies. We highlight the importance of the classification method. We propose an R package in order to use this procedure.

A new air quality perception scale for global assessment of air pollution health effects

Despite improvements in air quality in developed countries, air pollution remains a major public health issue. To fully assess the health impact, we must consider that air pollution exposure has both physical and psychological effects; this latter dimension, less documented, is more difficult to measure and subjective indicators constitute an appropriate alternative. In this context, this work presents the methodological development of a new scale to measure the perception of air quality, useful as an exposure or risk appraisal metric in public health contexts. On the basis of the responses from 2,522 subjects in eight French cities, psychometric methods are used to construct the scale from 22 items that assess risk perception (anxiety about health and quality of life) and the extent to which air pollution is a nuisance (sensorial perception and symptoms). The scale is robust, reproducible, and discriminates between subpopulations more susceptible to poor air pollution perception. The individual risk factors of poor air pollution perception are coherent with those findings in the risk perception literature. Perception of air pollution by the general public is a key issue in the development of comprehensive risk assessment studies as well as in air pollution risk management and policy. This study offers a useful new tool to measure such efforts and to help set priorities for air quality improvements in combination with air quality measurements.

Social inequalities resulting from health risks related to ambient air quality--A European review

BACKGROUND

Environmental nuisances, including ambient air pollution, are thought to contribute to social inequalities in health. There are two major mechanisms, which may act independently or synergistically, through which air pollution may play this role. Disadvantaged groups are recognized as being more often exposed to air pollution (differential exposure) and may also be more susceptible to the resultant health effects (differential susceptibility).

METHOD

European research articles were obtained through a literature search in the Medline database using keywords 'Socioeconomic Factors, Air Pollution, Health' and synonymous expressions.

RESULTS

Some studies found that poorer people were more exposed to air pollution whereas the reverse was observed in other papers. A general pattern, however, is that, irrespective of exposure, subjects of low socio-economic status experience greater health effects of air pollution. So far as we are aware, no European study has explored this relationship among children.

CONCLUSION

The housing market biases land use decisions and may explain why some subgroups suffer from both a low socio-economic status and high exposure to air pollution. Some data may be based on inaccurate exposure assessment. Cumulative exposures should be taken into account to explore health problems more accurately. The issue of exposure and health inequalities in relation to ambient air quality is complex and calls for global appraisal. There is no single pattern. Policies aimed at reducing the root causes of these inequalities could be based on urban multipolarity and diversity, two attributes that require long-term urban planning.

Asthma attacks and deprivation: gradients in use of mobile emergency medical services

BACKGROUND

To test whether rates of emergency telephone calls for asthma attacks are associated with contextual socioeconomic deprivation in the Strasbourg metropolitan area (France).

METHODS

Two mobile emergency medical service networks provided all data for 2000-2005 about emergency calls for asthma attacks, georeferenced by census block. Contextual deprivation was measured for each census block by a composite index, constructed by principal component analysis. Emergency call rates were calculated for each census block and for different age groups. Empirical Bayesian smoothing was used to reduce the instability of outlying rates.

RESULTS

Positive spatial autocorrelation was detected in both the health and the socioeconomic datasets. In all age groups, rates of calls for asthma attacks increased linearly with deprivation. Correlation coefficients between these two factors varied according to age group: 0.53 for the group aged 0-9 years, 0.46 for 10-19 years, 0.65 for 20-39 years, 0.70 for 40-64 years, 0.68 for 65 and older, and 0.77 for the age-standardised incidence ratio. These correlation coefficients were highly significant (p<0.01), even after spatial autocorrelation was taken into account.

CONCLUSION

The socioeconomic gradients observed are consistent with those observed for severe forms of asthma and asthma hospitalisations in Western countries.

Air pollution, asthma attacks, and socioeconomic deprivation: a small-area case-crossover study

With few exceptions, studies of short-term health effects of air pollution use pollutant concentrations that are averaged citywide as exposure indicators. They are thus prone to exposure misclassification and consequently to bias. Measurement of the relations between air pollution and health, generally and in specific populations, could be improved by employing more geographically precise exposure estimates. The authors investigated short-term relations between ambient air pollution estimated in small geographic areas (French census blocks) and asthma attacks in Strasbourg, France, in 2000-2005--in the general population and in populations with contrasting levels of socioeconomic deprivation. Emergency health-care networks provided data on 4,683 telephone calls made for asthma attacks. Deprivation was estimated using a block-level index constructed from census data. Hourly concentrations of particulate matter less than 10 microm in aerodynamic diameter (PM(10)), sulfur dioxide, nitrogen dioxide, and ozone were modeled by block with ADMS-Urban software. Adjusted case-crossover analyses showed that asthma calls were positively but not significantly associated with PM(10) (for a 10-microg x m(-3) increase, odds ratio (OR) = 1.035, 95% confidence interval (CI): 0.997, 1.075), sulfur dioxide (OR = 1.056, 95% CI: 0.979, 1.139), and nitrogen dioxide (OR = 1.025, 95% CI: 0.990, 1.062). No association was observed for ozone (OR = 0.998, 95% CI: 0.965, 1.032). Socioeconomic deprivation had no significant influence on these relations.