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.

Background: Social and physical characteristics of the daily visited neighborhoods have gained an extensive interest in analyzing socio-territorial inequalities in health and healthcare. The objective of the present paper is to estimate and discuss the role of individual and contextual factors on participation in preventive health-care activities (smear screening) in the Greater Paris area focusing on the characteristics of daily visited neighborhoods in terms of medical densities and social deprivation. Methods: The study included 1817 women involved in the SIRS survey carried out in 2010. Participants could report three neighborhoods they regularly visit (residence, work/study, and the next most regularly visited). Two "cumulative exposure scores" have been computed from household income and medical densities (general practitioners and gynecologists) in these neighborhoods. Multilevel logistic regression models were used to measure association between late cervical screening (> 3 years) and characteristics of daily visited neighborhoods (residential, work or study, visit). Results: One-quarter of the women reported that they had not had a smear test in the previous 3 years. Late smear test was found to be more frequent among younger and older women, among women being single, foreigners and among women having a low-level of education and a limited activity space. After adjustment on individual characteristics, a significant association between the cumulative exposure scores and the risk of a delayed smear test was found: women who were exposed to low social deprivation and to low medical densities in the neighborhoods they daily visit had a significantly higher risk of late cervical cancer screening than their counterparts. Conclusions: For a better understanding of social and territorial inequalities in healthcare, there is a need for considering multiple daily visited neighborhoods. Cumulative exposure scores may be an innovative approach for analyzing contextual effects of daily visited neighborhoods rather than focusing on the sole residential neighborhood.

Background: The consideration of multiple spaces frequented daily by individuals is attracting interest for the analysis of socioterritorial health and healthcare inequalities in light of the high daily mobility in urban settings and the increasing availability of mobility data. Our objective was to estimate the associations between attributes of daily frequented neighborhoods and delayed cervical smear tests in the Greater Paris area. Methods: Data were extracted from the 2010 SIRS cohort survey. Participants could report three neighborhoods (residence, work, and the next most regularly frequented). All multivariate analyses were conducted: simple multilevel logistic regression models, cross-classified multilevel logistic regression models were used to simultaneously consider the three types of neighborhoods studied (residential, work or study, visit) with active and mobile women. Finally, associations with socioeconomic and medical diversity scores (adjusted for the five individual characteristics) were estimated by logistic regression models that took sampling design into consideration. Results: One-quarter of the women reported that they had not had a smear test in the previous three years. After adjusting for individual characteristics, there was a significant association between the socioeconomic and medical diversity scores for the multiple neighborhoods frequented and the risk of a delayed smear test. Women who reside and work in poor neighborhoods and whose next most regularly frequented neighborhood was also poor had a significantly higher risk of late cervical cancer screening. Conclusions: In the characterization of social and territorial inequalities in healthcare, social epidemiology and health geography show a growing interest in considering multiple spaces frequented daily by individuals. A cumulative exposure score, such as the one presented here, may be a relevant approach for analyzing their effects. Keywords: Multilevel analysis, neighborhood, daily mobility, cancer prevention, cervical cancer, social inequalities, Paris area