*Strengths and Limitations*

One strength of this work is the use of small area-level analyses allowing a correct understanding of the geographic patterns of PTB. Moreover, this type of analysis is crucial for revealing local-level health inequalities that are often masked when analysis is produced at large spatial scales.

Unlike geographical information system approach used to map and to visualize the spatial trends of PTB risk, in our study, we use a spatial clustering approach allowing us to identify areas of significantly elevated risk of PTB and to investigate spatial implications of adjustment for neighborhood characteristics. Another strength of our study is the databases used in our analysis to investigate PTB in France:


However, the interpretation of our findings must also consider some weaknesses. Our approach, which uses ecological data, has several limitations. One is the absence of individual data such as maternal age, marital status and number of previous births. In addition, race/ethnic differences were not recorded in the first birth certificate because the French legislation prohibits the collection of any data based on race and ethnicity. Therefore, all statistical unit are considered equal. Data about the race/ethnicity were not available and were thus not included in our analysis. However, our study rests on a fine geographical resolution scale—census block—which has been designed by the Census bureau to be as homogeneous as possible in terms of population size and socio-economic and demographic characteristics. The level of homogeneity of the census blocks ensures the minimization of ecological bias, and the findings from this spatial analysis tend to be close to what could be observed at individual level [109,110]. Nonetheless, some degree of misclassification inevitably exists in individual characteristics and environmental exposures, and these could results in associations being biased towards the null. Another limitation is the absence of certain parental characteristics like lifestyle behaviors [92,95,111] including maternal nutritional deficits or status toxicants such as nicotine, cocaine or alcohol and access to healthcare [91,93–97,112]. Also, while socio-economic characteristics do not change rapidly over time, exposure to air pollution is highly variable and the present study considerer average NO2 concentrations over several years, the same value being assigned to all births that occurred in the same census block, irrespective of seasonality. From our data, the crude estimate of the PTB rate by season in Paris over the study period increase during the winter (rate of preterm equal 5.12%) while in summer the rate is 4.36%. A recent meta-analysis study [113] revealed that the pooled relative risks of preterm births increase during the winter months (maximum observed in January) and the beginning of summer (maximum observed in June). The air pollution concentrations follow similar temporal trend with the highest and lowest level in winter and in summer respectively. Indeed, the main emission sources of nitrogen oxides are road traffic (56%) and residential sector (18%) [114]. During summer, NO2 concentrations are lower, due to the slowdown of activities in the city and in particular the decrease of road traffic associated with the holiday period, and also in link with the chemistry of ozone formation. Due to the lack of data (we have not the daily concentrations of NO2 per census block), it was not possible to explore the air pollution PTB effect by season. This limitation is a common feature of ecological studies as the one we conducted. Epidemiological approaches that allow estimation of personal exposure information provide a complementary viewpoint, with their own limitations.

Finally others characteristic such as green space could be associated with pregnancy outcome. In previous work we describe conceptual framework with 3 hypothetical pathways by which green spaces may have a beneficial effect on adverse pregnancy outcomes [55]. In addition, in recent study conducted in the same study area—city of Paris, we assessed the spatial variability of heat-wave-related mortality risk among elderly at the census block level and the most likely cluster for increased mortality risk is located in the same zone of cluster of high risk of PTB, in the East of Paris. In this study, we found that green space density had a protective effect [115]. In the future, It would be therefore interesting to collect all environmental exposures data from various sources, with negative health impacts (air, water and soil contamination, noise, etc.) or with positive effects (e.g., green space) and assess the effect of cumulative exposure on PTB risk using composite exposure index which performed in French [116].
