Creation and testing of the Domiscore-a tool to characterize the impact of housing on health and well-being.

BACKGROUND: Despite evidence of the major impact housing carries on health, many individuals still live in unhealthy dwellings. In France, the Domiscore has been proposed as a tool to assess the quality of dwellings with regard to their health impact, to allow for a better detection of unsafe housing and to improve dwellings. The aim of this paper is to present the method used to construct the Domiscore and test its relevance and usability. METHODS: The Domiscore grid, inspired by the Nutriscore, consists of 46 variables-such as air quality, light or outdoor view. Each variable is scored on a four-point scale using in situ observation, mandatory diagnostics and open access data. The sum of each variable's score results in an overall risk score for the dwelling. The Domiscore was tested in two phases. During the first testing phase, 11 real estate professionals, health professionals and social workers used the Domiscore for on-site visits in different geographic areas of France. They then participated in a semi-structured qualitative interview. The second phase consisted in a public consultation with diverse stakeholders such as public authorities, housing activists and social workers, using an online survey to collect their opinions on the Domiscore's relevance, understandability and usability. RESULTS: The Domiscore was tested on 28 homes. Variables completion rates were high irrespective of tester profile for all home visits (91%, SD = 4.7%). The mean time needed to fill in the grid was 1.5 h. The public consultation returned 151 responses. The Domiscore was deemed easy to understand, relevant, and rather easy to fill out. Most participants found the Domiscore useful for information gathering, awareness raising, detecting at-risk situations and agreed that it could contribute to enhance housing conditions. Its length was noted, although the inclusion of additional variables was also suggested. CONCLUSIONS: The results of this study suggest that the Domiscore is accessible to housing specialists and other professionals for the evaluation of a dwelling's health impacts and the standardized detection of dangerous situations. The testing process allowed for improvements in the grid and training materials for future users.

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.

Development of Serious Games (Equit'Game) to Address Health and Environmental Inequalities: Protocol for an App-Delivered Program to Perform a Territorial Diagnosis.

BACKGROUND: Territorial diagnosis is a prerequisite for local actions concerning public health and for the reduction of social, environmental, and health-related inequalities. To orient local programs or initiatives targeting health inequalities, policymakers need a simulation of territorial diagnosis tools. Yet, very few platforms have been developed for the purpose of guiding public authorities as they seek to reduce these social inequalities. OBJECTIVE: This study aimed to describe the design and methods of the development process of a territorial diagnosis tool based on a serious game named Equit'Game that puts learners at the heart of the territorial diagnosis process, asking them to review the current state of health, environmental state, and socioeconomic state of their territory. METHODS: The realistic situations employed in our serious game should encourage players, in a fun and playful manner, to (1) appropriate the data of their own territory, (2) apply their methodological knowledge in a practical way, (3) reflect on the most pertinent statistical or spatial tools for their situation, and (4) ultimately, to acquire new knowledge and skills in the use of territorial diagnosis tools with a spatial dynamic. Equit'Game was deployed over the course of a week's training and structured into 4 levels: level 1, Dataminer (identifying relevant information to respond to the question); level 2, Analyst (selecting the appropriate method of analysis); level 3, Atlas (mapping the data); and level 4, Cluster (extraction of statistical and spatial information). Equit'Game has also been designed as a sort of virtual campus, creating a fun learning environment in which each door represents a level. Users can access Equit'Game via a platform compatible with tablets, PCs, and mobile phones. RESULTS: In the first step, we tested our application interface designed especially for adults among a panel of local health professionals. The following are some of the most relevant points: font size and colors used, voice accompaniment in texts and messages guiding the user, clear and easy interfaces, and the change between successive game levels. In the second step, we used our application, Equit'Game, with postgraduate students from the School of Public Health (École des hautes études en santé publique). At the end of the game session, we conducted a satisfaction survey, including several items covering both the application interface and the execution of the game. CONCLUSIONS: Equit'Game was developed to help learners with the techniques of territorial diagnosis, with the aim of creating an innovative tool for public health capable of conveying educational messages and providing a structure for training. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/11786.

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.

Early Life Exposures to Perfluoroalkyl Substances in Relation to Adipokine Hormone Levels at Birth and During Childhood.

BACKGROUND: Birth cohort studies have linked exposure to perfluoroalkyl substances (PFASs) with child anthropometry. Metabolic hormone dysregulation needs to be considered as a potential adverse outcome pathway. We examined the associations between PFAS exposures and concentrations of adipokine hormones from birth to adolescence. METHODS: We studied 80 mother-child pairs from a Faroese cohort born in 1997 to 2000. Five PFASs were measured in maternal pregnancy serum and in child serum at ages 5, 7, and 13 years. Leptin, adiponectin, and resistin were analyzed in cord serum and child serum at the same ages. We fitted multivariable-adjusted generalized estimating equations to assess the associations of PFASs at each age with repeated adipokine concentrations at concurrent and subsequent ages. RESULTS: We observed tendencies of inverse associations between PFASs and adipokine hormones specific to particular ages and sex. Significant associations with all adipokines were observed for maternal and child 5-year serum PFAS concentrations, whereas associations for PFASs measured at ages 7 to 13 years were mostly null. The inverse associations with leptin and adiponectin were seen mainly in females, whereas the inverse PFAS associations with resistin levels were seen mainly in males. Estimates for significant associations (P value <0.05) suggested mean decreases in hormone levels (range) by 38% to 89% for leptin, 16% to 70% for adiponectin, and 33% to 62% for resistin for each twofold increase in serum PFAS concentration. CONCLUSIONS: These findings suggest adipokine hormone dysregulation in early life as a potential pathway underlying PFAS-related health outcomes and underscore the need to further account for susceptibility windows and sex-dimorphic effects in future investigations.

Physico-chemical properties and gestational diabetes predict transplacental transfer and partitioning of perfluoroalkyl substances.

BACKGROUND: Per- and polyfluoroalkyl substances (PFASs) are a growing public health concern. Some longer chain PFASs bioaccumulate and many compounds persist in the environment for long time periods. Recent studies have established their ability to pass through placenta, yet data on the transplacental transfer efficiency and partitioning of short and long chain PFASs in blood matrices are limited. OBJECTIVES: To assess predictors of the partitioning of 17 PFAS compounds detected in the maternal serum, umbilical cord serum and whole cord blood samples from matched mother-newborn pairs from two Faroe Islands cohorts. METHODS: We examined 151 mother-newborn pairs from two successive Faroese birth cohorts. Cord:maternal serum (transplacental transfer) and serum:whole cord blood (blood partitioning) ratios were estimated for 17 PFAS compounds. We also examined the relationships of these ratios with maternal, newborns', and physico-chemical properties using multivariable regression analyses. RESULTS: Moderate to high correlations were observed between maternal and cord serum PFAS concentrations (ρ: 0.41 to 0.95), indicating significant transfer of these compounds from the mother to the fetus. Median transplacental transfer ratios were generally below 1, except for perfluorooctane sulfonamide (FOSA), and ranged between 0.36 for perfluorodecanoate (PFDA) and perfluoroundecanoate (PFUnDA) and 1.21 for FOSA. Most PFASs exhibited a preference to the serum component of the blood, except FOSA and perfluoroheptanoate (PFHpA), with blood partitioning ratios ranging from 0.36 for FOSA to 2.75 for PFUnDA. Both the functional groups and carbon chain length of different PFASs were important predictors of transplacental transfer and blood partitioning. We observed a U-shaped relationship between transplacental transfer ratios and carbon chain length for perfluorocarboxylates and perfluorosulfonates. Importantly, gestational diabetes was also a strong predictor of transplacental transfer ratios, with significantly higher transfer in mothers with gestational diabetes. CONCLUSIONS: Our findings provide a better understanding of the transplacental transfer and blood partitioning of a large number of PFAS compounds. Results elucidate the importance of chemical structure for future risk assessments and choice of appropriate blood matrices for measurement of PFAS compounds.

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.

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.

Do airway inflammation and airway responsiveness markers at the start of apprenticeship predict their evolution during initial training? A longitudinal study among apprentice bakers, pastry makers and hairdressers.

BACKGROUND: The natural history of airway inflammation and symptoms in occupations at risk of asthma is still not fully understood. We aimed to study the evolution during apprenticeship of inflammation markers, bronchial hyperresponsiveness (BHR) and symptoms in at-risk subgroups as defined from measurements of markers made shortly after the start of training. METHODS: Respiratory symptoms, FEV1 and airway resistance post-bronchial challenge (MBC) test results, fractional exhaled nitric oxide (FeNO) measurements, and eosinophils in nasal lavage fluid were investigated in apprentice bakers, pastry-makers and hairdressers. Four visits were conducted: at the start of the training and every six months thereafter. Four baseline risk groups were defined, based on, (i) a high level of FeNO (NO), (ii) eosinophils > 1% (Eosino), (iii) a ≥ 15% decrease in FEV1 during the MBC test (HR), and (iv) a ≥ 50% increase in the resistance (Resist). The statistical analysis relied on mixed models. RESULTS: At baseline, the inflammation markers were related to the MBC markers. There was no evidence to suggest that the baseline risk groups predict a differential evolution of the airway inflammation and bronchial responsiveness markers, or the asthma-like symptoms considered. The baseline risk groups defined from MBC test predicted the levels of MBC markers. Similarly, the baseline risk groups based on eosinophilic inflammation predicted the levels of markers for eosinophilia. These results were similar in the three training tracks, with the exception of the FeNO levels which were not different according to the Eosino risk group. Twelve possible new asthma cases were identified, only the HR risk group predicted their occurrence. CONCLUSIONS: Among this young population, at-risk groups based on initial high levels of inflammation markers did not experience any worsening during the follow-up. However, initial BHR predicted consistently high levels of all markers considered and occurrence of possible asthma.

Risk assessment of occupational exposure to heavy metal mixtures: a study protocol.

BACKGROUND: Sfax is a very industrialized city located in the southern region of Tunisia where heavy metals (HMs) pollution is now an established matter of fact. The health of its residents mainly those engaged in industrial metals-based activities is under threat. Indeed, such workers are being exposed to a variety of HMs mixtures, and this exposure has cumulative properties. Whereas current HMs exposure assessment is mainly carried out using direct air monitoring approaches, the present study aims to assess health risks associated with chronic occupational exposure to HMs in industry, using a modeling approach that will be validated later on. METHODS: To this end, two questionnaires were used. The first was an identification/descriptive questionnaire aimed at identifying, for each company: the specific activities, materials used, manufactured products and number of employees exposed. The second related to the job-task of the exposed persons, workplace characteristics (dimensions, ventilation, etc.), type of metals and emission configuration in space and time. Indoor air HMs concentrations were predicted, based on the mathematical models generally used to estimate occupational exposure to volatile substances (such as solvents). Later on, and in order to validate the adopted model, air monitoring will be carried out, as well as some biological monitoring aimed at assessing HMs excretion in the urine of workers volunteering to participate. Lastly, an interaction-based hazard index HIint and a decision support tool will be used to predict the cumulative risk assessment for HMs mixtures. DISCUSSION: One hundred sixty-one persons working in the 5 participating companies have been identified. Of these, 110 are directly engaged with HMs in the course of the manufacturing process. This model-based prediction of occupational exposure represents an alternative tool that is both time-saving and cost-effective in comparison with direct air monitoring approaches. Following validation of the different models according to job processes, via comparison with direct measurements and exploration of correlations with biological monitoring, these estimates will allow a cumulative risk characterization.

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.

Contribution of job-exposure matrices for exposure assessment in occupational safety and health monitoring systems: application from the French national occupational disease surveillance and prevention network.

OBJECTIVES: To detect new hazards ("signals"), occupational health monitoring systems mostly rest on the description of exposures in the jobs held and on reports by medical doctors; these are subject to declarative bias. Our study aims to assess whether job-exposure matrices (JEMs) could be useful tools for signal detection by improving exposure reporting. METHODS: Using the French national occupational disease surveillance and prevention network (RNV3P) data from 2001 to 2011, we explored the associations between disease and exposure prevalence for 3 well-known pathology/exposure couples and for one debatable couple. We compared the associations measured when using physicians' reports or applying the JEMs, respectively, for these selected diseases and across non-selected RNV3P population or for cases with musculoskeletal disorders, used as two reference groups; the ratio of exposure prevalences according to the two sources of information were computed for each disease category. RESULTS: Our population contained 58,188 subjects referred with pathologies related to work. Mean age at diagnosis was 45.8 years (95% CI 45.7; 45.9), and 57.2% were men. For experts, exposure ratios increase with knowledge on exposure causality. As expected, JEMs retrieved more exposed cases than experts (exposure ratios between 12 and 194), except for the couple silica/silicosis, but not for the MSD control group (ratio between 0.2 and 0.8). CONCLUSIONS: JEMs enhanced the number of exposures possibly linked with some conditions, compared to experts' assessment, relative to the whole database or to a reference group; they are less likely to suffer from declarative bias than reports by occupational health professionals.

Estimating indoor galaxolide concentrations using predictive models based on objective assessments and data about dwelling characteristics.

BACKGROUND: Galaxolide (HHCB) is used for fragrance in many consumer products. The aim of the current study was to use objective assessments of HHCB to build a predictive model in order to estimate indoor-measured HHCB concentrations from questionnaire-based data on dwelling characteristics and occupants' habits and activities. METHODS: Environmental assessments of indoor HHCB, dwelling characteristics were carried out in 150 dwellings in Brittany (France). Among the various models that were tested, the best predictive model for the reduced set of characteristics was identified on the basis of the coefficient of determination (R2) criterion. RESULTS: Linear regression model showed among the best performances (R2 = 0.48), together with some more complex models. According to the estimated results, the main variables that significantly increased HHCB concentrations were: living in rural area, drying clothes inside dwellings, painted walls, chipboard furniture, double glazing, damaged floors and duration of bathroom door being kept open. Laminated floors and presence of indoor plants were found to significantly decrease HHCB concentrations. DISCUSSION: The linear model based on objective assessments and questionnaire-derived data about dwelling characteristics and occupants' activities constituted an easy method for predicting indoor air HHCB concentrations. For studies including a large number of dwellings, modeling of HHCB concentrations is cheaper than measuring it in every location. Our methodological procedure can be applied to other indoor air pollutants.

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 20th, 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.

Neighbourhood Characteristics and Long-Term Air Pollution Levels Modify the Association between the Short-Term Nitrogen Dioxide Concentrations and All-Cause Mortality in Paris.

BACKGROUND: While a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France). METHODS: A time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866). RESULTS: The mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], p<0.001). Among these deprived census blocks, excess risk was even higher where long-term average NO2 concentrations were above 55.8 µg/m3 (the top tercile of distribution): ER=4.84% (95%CI=[1.56;8.24], p for interaction=0.02). CONCLUSION: Our results show that people living in census blocks characterized by low socioeconomic status are more vulnerable to air pollution episodes. There is also an indication that people living in these disadvantaged census blocks might experience even higher risk following short-term air pollution episodes, when they are also chronically exposed to higher NO2 levels.

Concentration and determinants of molds and allergens in indoor air and house dust of French dwellings.

Molds and allergens are common indoor biocontaminants. The aims of this study were to assess the concentrations of common molds in indoor air and floor dust and the concentrations of house dust mite, cat and dog allergens in mattress dust in French dwellings, and to assess predictors of these concentrations. A sample of 150 houses in Brittany (western France) was investigated. Airborne Cladosporium and Penicillium were detected in more than 90% of the dwellings, Aspergillus in 46% and Alternaria in only 6% of the housings. Regarding floor dust samples, Cladosporium and Penicillium were detected in 92 and 80% of the housings respectively, Aspergillus in 49% and Alternaria in 14%. House dust mite allergens Der p1 and Der f1 were detected in 90% and 77% of the mattress dust samples respectively and Can f1 and Fel d1 in 37% and 89% of the homes. Airborne and dustborne mold concentrations, although not statistically correlated (except for Aspergillus) shared most of their predictors. Multivariate linear models for mold levels, explaining up to 62% of the variability, showed an influence of the season, of the age of the dwelling, of aeration habits, presence of pets, smoking, signals of dampness, temperature and relative humidity. Allergens in the dust of the mattress were strongly related to the presence of pets and cleaning practices of bedsheets, these factors accounting for 60% of the variability. This study highlights ubiquitous contamination by molds and underlines complex interaction between outdoor and indoor sources and factors.

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.