Application of the urban exposome framework using drinking water and quality of life indicators: a proof-of-concept study in Limassol, Cyprus

Abstract

Background: Cities face rapid changes leading to increasing inequalities and emerging public health issues that require cost-effective interventions. The urban exposome concept refers to the continuous monitoring of urban environmental and health indicators using the city and smaller intra-city areas as measurement units in an interdisciplinary approach that combines qualitative and quantitative methods from social sciences, to epidemiology and exposure assessment.

Methods: In this proof of concept study, drinking water and quality of life indicators were described as part of the development of the urban exposome of Limassol (Cyprus) and were combined with agnostic environment-wide association analysis. This study was conducted as a two-part project with a qualitative part assessing the perceptions of city stakeholders, and quantitative part using a cross-sectional study design (an urban population study). We mapped the water quality parameters and participants' opinions on city life (i.e., neighborhood life, health care, and green space access) using quarters (small administrative areas) as the reference unit of the city. In an exploratory, agnostic, environment-wide association study analysis, we used all variables (questionnaire responses and water quality metrics) to describe correlations between them.

Results: Overall, urban drinking-water quality using conventional indicators of chemical (disinfection byproducts-trihalomethanes (THM)) and microbial (coliforms, E. coli, and Enterococci) quality did not raise particular concerns. The general health and chronic health status of the urban participants were significantly (false discovery rate corrected p-value < 0.1) associated with different health conditions such as hypertension and asthma, as well as having financial issues in access to dental care. Additionally, correlations between THM exposures and participant behavioral characteristics (e.g., household cleaning, drinking water habits) were documented.

Conclusion: This proof-of-concept study showed the potential of using integrative approaches to develop urban exposomic profiles and identifying within-city differences in environmental and health indicators. The characterization of the urban exposome of Limassol will be expanded via the inclusion of biomonitoring tools and untargeted metabolomics.

Keywords: Epidemiology; Exposome; Small area; Urban health.

Figure 1. Urban exposome—human exposome continuum, and the practical application of the urban exposome framework in the urban setting of Limassol city.

The parts of the urban exposome specifically discussed in the current analysis include a perceptions study and an urban population study, which includes parameters measured in drinking-water to assess the water quality coupled with questionnaire responses about individual lifestyle, behavioral, and personal health indicators.

Figure 2. Maps of the median water total THM (A), BrTHM (B), and free chlorine (C) levels by quarter within the municipality of Limassol, Cyprus (2017).

Figure 3. Maps of the percentage of samples with detectable counts of the monitored microbial parameters, i.e. Coliforms (A), and total viable counts at 22 (B) and 37C (C), by quarter within the municipality of Limassol, Cyprus (2017).

Figure 4. Percentage of study participants reporting constraints in access to health care, i.e. financial issue in access to dental care (A) and delays due to long waiting lists (B), by quarter of the Limassol municipality, Cyprus (2017).

Figure 5. Percentage of study participants agreeing with different statements about life in the neighborhood, i.e. on sharing the same values with the neighbors (A), and whether there is someone to help in the neighborhood (B), by quarter of the Limassol municipality, Cyprus (2017).

Figure 6. Maps by quarter of the percentage of study participants within the quarters of Limassol municipality, Cyprus (2017) agreeing that they live in close proximity to green space (A) and they do activities in the green space nearby (B).

Figure 7. Correlation plot (Spearman correlation coefficient) for all the variables used in the environment-wide association exploratory analysis.

Figure 8. Circular plots of the correlations between the variables used in the environmental-wide analysis by block/group of variables accounting for general health (A) and any disease the past year (B).