Autore: Orazio Valerio Giannico, Unit of Statistics and Epidemiology, Local Health Authority of Taranto (ASL Taranto)
valeriogiannico.igiene@gmail.com
Anna Maria Nannavecchia, Strategic Regional Agency for Health and Social Care of Apulia (ARESS Puglia) Rodolfo Sardone, Unit of Statistics and Epidemiology, Local Health Authority of Taranto (ASL Taranto) Antonio Chieti, Strategic Regional Agency for Health and Social Care of Apulia (ARESS Puglia) Ida Galise, Regional Agency for Environmental Prevention and Protection of Apulia (ARPA Puglia) Vincenzo Campanaro, Regional Agency for Environmental Prevention and Protection of Apulia (ARPA Puglia) Vito Bruno, Regional Agency for Environmental Prevention and Protection of Apulia (ARPA Puglia) Maria Tutino, Regional Agency for Environmental Prevention and Protection of Apulia (ARPA Puglia) Sante Minerba, Unit of Statistics and Epidemiology, Local Health Authority of Taranto (ASL Taranto) Antonia Mincuzzi, Unit of Statistics and Epidemiology, Local Health Authority of Taranto (ASL Taranto) Lucia Bisceglia, Strategic Regional Agency for Health and Social Care of Apulia (ARESS Puglia)
Categoria Primaria: Ambiente e salute
Categoria Secondaria: One health/Epidemiologia veterinaria
Introduction. In urban environments, the symbiotic relationship between green spaces, air quality, and human health plays a pivotal role in shaping the well-being of communities.
Objectives. In this Health Impact Assessment (HIA) study, we aimed to quantify the all-cause mortality burden that could have been avoided in 2013-15 in population aged ≥20 years if different counterfactual exposures had been achieved in Bari.
Methods. Population weighted exposures (PWE) were calculated using the 2015 Global Human Settlement Layer Population (100 meters). Exposure to green spaces was estimated using the greenest season (April-June) normalized difference vegetation index (NDVI) from Landsat 8 (30m). To reflect the WHO 2016 recommendations, the exposure was estimated within a 300m radius buffer. Counterfactual exposure was set rounding the country-specific 75th population-weighted percentile of the exposure. We used the exposure response function (ERF) from Rojas-Rueda 2019. Exposures to air pollution (annual PM10, PM2.5, NO2, peak season O3, ug/m3) were estimated through a Random Forest Machine Learning Approach (200m). Counterfactual exposures were set according to the WHO 2021 Guidelines. We used the ERFs from Chen 2021 and Huangfu 2020. For each exposure, age-specific preventable or attributable deaths (AD/PD) were calculated by multiplying the baseline deaths (all cause daily mortality from ISTAT) for the preventable or attributable fractions (AR/PF). Years of life lost (YLLs) were calculated by multiplying the PD/AD for the age-class and year specific life expectancy (Bari Province mortality tables from ISTAT).
Results. In 2015, the PWEs to NDVI, PM10, PM2.5, NO2 and O3 were 0.22, 26.84, 17.63, 33.89 and 72.56, respectively. PF/AFs (%) were 3.2 (2.4;4.8), 4.5 (3.4;6.7), 9.3 (7.1;10.3), 4.6 (2.3;8.9) and 1.2 (0;2.5). A total of 108 (81;161), 151 (115;223), 309 (237;345), 155 (79;299) and 42 (0;82) PD/ADs were estimated, respectively (impacts not intended to be summed-up). A total of 1147 (859;1723), 1618 (1227;2377), 3303 (2530;3677), 1647 (837;3189) and 443 (0;876) YLLs were estimated. The higher mortality burden was observed in the 80+ age class: 67, 94, 192, 96 and 26 PD/ADs. Similar findings emerged for 2013 and 2014.
Conclusions. This study, utilizing satellite-derived and modeled high-resolution exposure data, stands as a pioneering effort in Southern Italy. Enhancing access to green spaces and meeting the WHO guidelines could prevent a substantial number of premature deaths, potentially up to 9% of all deaths when PM2.5 exposure is considered.