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<p>Air pollution is a known risk factor for adverse birth outcomes, including Small for Gestational Age (SGA) births. This study examines the association between fine particulate matter (<i>PM</i><sub>2<i>.</i>5</sub>) exposure and SGA births in Milan, Italy, considering spatial dependencies and socioeconomic factors. We applied a Bayesian hierarchical spatial model with a binomial regression framework to birth data aggregated at a 500&#xa0;m × 500&#xa0;m grid level. A Conditional Autoregressive (CAR) prior captured spatial correlations. Covariates included maternal age, Deprivation Index, Normalized Difference Vegetation Index (NDVI), surface temperature, and Road Coverage. Parameter estimation was performed using Markov Chain Monte Carlo (MCMC) methods. Among 7635 eligible births in 2016, 8.5% were SGA. A 10<i>&#xa0;µg/m</i><sup>3</sup> increase in <i>PM</i><sub>2<i>.</i>5</sub> was associated with a 15% increase in SGA odds (OR: 1.153, IQR: 0.853–1.556). The D eprivation Index also showed a strong positive association (OR: 1.075, IQR: 1.028–1.125). NDVI exhibited a weak positive association, potentially reflecting socioeconomic disparities. Maternal age, temperature, and Road Coverage were not significantly associated with SGA. <i>PM</i><sub>2<i>.</i>5</sub> exposure and socioeconomic deprivation are linked to higher SGA risk in Milan. The spatial correlation highlights localized risk factors. Targeted policies to reduce air pollution and address social inequalities are needed to improve perinatal outcomes.</p>

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Prenatal exposure to fine particulate matter PM2.5 and small for gestational age: a Bayesian model for area-based data in Milan

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月29日

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  • Simone Colombara,
  • Rossella Murtas,
  • Sara Tunesi,
  • Alessandra Guglielmi,
  • Antonio Giampiero Russo,
  • Paola Angelini,
  • Serena Broccoli,
  • Marco Monti,
  • Nicola Caranci,
  • Katia Raffaelli,
  • Daniela Fortuna,
  • Paolo Giorgi Rossi,
  • Marta Ottone,
  • Laura Bonvicini,
  • Luisa Frova,
  • Stefano Marchetti,
  • Lidia Gargiuolo,
  • Andrea Ranzi,
  • Simone Giannini,
  • Stefano Marchesi,
  • Annamaria Colacci,
  • Francesca Russo,
  • Vanessa Groppi,
  • Luisa Memo,
  • Sofia Memoli,
  • Gisella Pitter,
  • Elena Narne,
  • Giulia Capodaglio,
  • Manuel Zorzi,
  • Nicola Gennaro,
  • Laura Cestari,
  • Rodolfo Bassan,
  • Massimo Bressan,
  • Luca Zagolin,
  • Nicoletta Cornaggia,
  • Veronica Todeschini,
  • Matteo Lazzarini,
  • Michele Carugno,
  • Elisa Borroni,
  • Morena Stroscia,
  • Raffaella Pastore,
  • Silvia Ripetta,
  • Nicolas Zengarini,
  • Carlo Mamo,
  • Fulvio Ricceri,
  • Chiara De Girolamo,
  • Giuseppe Costa,
  • Massimo Stafoggia,
  • Carla Ancona,
  • Federica Nobile,
  • Paola Michelozzi,
  • Maria Antonietta Reatini,
  • Giorgio Cattani,
  • Lucia Bisceglia,
  • Rossella Bruni,
  • Anna Maria Nannavecchia,
  • Antonio Chieti,
  • Davide Parisi,
  • Valerio Giannico,
  • Alessandra Nocioni,
  • Vincenzo Campanaro,
  • Maria Tutino,
  • Leo Germinario,
  • Angela Morabito,
  • Maria Serinelli,
  • Sebastiano Pollina Addario,
  • Margherita Ferrante,
  • Giovanna Fantaci,
  • Gea Oliveri Conti,
  • Antonello Marras,
  • Stefania La Grutta,
  • Mirella Profita,
  • Velia Malizia,
  • Ilaria Stanisci,
  • Pietro Alfano,
  • Filippo Sapienza,
  • Sara Maio,
  • Sandra Baldacci,
  • Giuseppe Sarno,
  • Francesca Costabile,
  • Paolo Chiodini,
  • Simona Signoriello,
  • Vittorio Simeon,
  • Annafrancesca Smimmo,
  • Paola Schiattarella,
  • Teresa Speranza,
  • Luigi Pierno,
  • Marco Baldini,
  • Silvia Bartolacci,
  • Miriam Sileno,
  • Walter Ricciardi,
  • Leonardo Villani,
  • Angelo Del Favero,
  • Giovanna Failla

摘要

Air pollution is a known risk factor for adverse birth outcomes, including Small for Gestational Age (SGA) births. This study examines the association between fine particulate matter (PM2.5) exposure and SGA births in Milan, Italy, considering spatial dependencies and socioeconomic factors. We applied a Bayesian hierarchical spatial model with a binomial regression framework to birth data aggregated at a 500 m × 500 m grid level. A Conditional Autoregressive (CAR) prior captured spatial correlations. Covariates included maternal age, Deprivation Index, Normalized Difference Vegetation Index (NDVI), surface temperature, and Road Coverage. Parameter estimation was performed using Markov Chain Monte Carlo (MCMC) methods. Among 7635 eligible births in 2016, 8.5% were SGA. A 10 µg/m3 increase in PM2.5 was associated with a 15% increase in SGA odds (OR: 1.153, IQR: 0.853–1.556). The D eprivation Index also showed a strong positive association (OR: 1.075, IQR: 1.028–1.125). NDVI exhibited a weak positive association, potentially reflecting socioeconomic disparities. Maternal age, temperature, and Road Coverage were not significantly associated with SGA. PM2.5 exposure and socioeconomic deprivation are linked to higher SGA risk in Milan. The spatial correlation highlights localized risk factors. Targeted policies to reduce air pollution and address social inequalities are needed to improve perinatal outcomes.