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A Multi-Pollutant and Meteorological Analysis of Cardiorespiratory Mortality among the Elderly in São Paulo, Brazil—An Artificial Neural Networks Approach

Author

Listed:
  • Luciana Leirião

    (Institute of Environmental, Chemical and Pharmaceutical Sciences, Federal University of Sao Paulo (UNIFESP), Diadema 09913030, Brazil)

  • Michelle de Oliveira

    (Institute of Environmental, Chemical and Pharmaceutical Sciences, Federal University of Sao Paulo (UNIFESP), Diadema 09913030, Brazil)

  • Tiago Martins

    (Institute of Environmental, Chemical and Pharmaceutical Sciences, Federal University of Sao Paulo (UNIFESP), Diadema 09913030, Brazil)

  • Simone Miraglia

    (Institute of Environmental, Chemical and Pharmaceutical Sciences, Federal University of Sao Paulo (UNIFESP), Diadema 09913030, Brazil)

Abstract

Traditionally, studies that associate air pollution with health effects relate individual pollutants to outcomes such as mortality or hospital admissions. However, models capable of analyzing the effects resulting from the atmosphere mixture are demanded. In this study, multilayer perceptron neural networks were evaluated to associate PM 10 , NO 2 , and SO 2 concentrations, temperature, wind speed, and relative air humidity with cardiorespiratory mortality among the elderly in São Paulo, Brazil. Daily data from 2007 to 2019 were considered and different numbers of neurons on the hidden layer, algorithms, and a combination of activation functions were tested. The best-fitted artificial neural network (ANN) resulted in a MAPE equal to 13.46%. When individual season data were analyzed, the MAPE decreased to 11%. The most influential variables in cardiorespiratory mortality among the elderly were PM 10 and NO 2 concentrations. The relative humidity variable is more important during the dry season, and temperature is more important during the rainy season. The models were not subjected to the multicollinearity issue as with classical regression models. The use of ANNs to relate air quality to health outcomes is still very incipient, and this work highlights that it is a powerful tool that should be further explored.

Suggested Citation

  • Luciana Leirião & Michelle de Oliveira & Tiago Martins & Simone Miraglia, 2023. "A Multi-Pollutant and Meteorological Analysis of Cardiorespiratory Mortality among the Elderly in São Paulo, Brazil—An Artificial Neural Networks Approach," IJERPH, MDPI, vol. 20(8), pages 1-23, April.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:8:p:5458-:d:1120483
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    References listed on IDEAS

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    1. Laura Andrea Rodríguez-Villamizar & Néstor Yezid Rojas-Roa & Luis Camilo Blanco-Becerra & Víctor Mauricio Herrera-Galindo & Julián Alfredo Fernández-Niño, 2018. "Short-Term Effects of Air Pollution on Respiratory and Circulatory Morbidity in Colombia 2011–2014: A Multi-City, Time-Series Analysis," IJERPH, MDPI, vol. 15(8), pages 1-12, July.
    2. José Carlos Curvelo Santana & Amanda Carvalho Miranda & Charles Lincoln Kenji Yamamura & Silvério Catureba da Silva Filho & Elias Basile Tambourgi & Linda Lee Ho & Fernando Tobal Berssaneti, 2020. "Effects of Air Pollution on Human Health and Costs: Current Situation in São Paulo, Brazil," Sustainability, MDPI, vol. 12(12), pages 1-20, June.
    3. Karina Camasmie Abe & Simone Georges El Khouri Miraglia, 2016. "Health Impact Assessment of Air Pollution in São Paulo, Brazil," IJERPH, MDPI, vol. 13(7), pages 1-10, July.
    4. Tatiane Morais Ferreira & Maria Cristina Forti & Clarice Umbelino De Freitas & Felipe Parra Nascimento & Washington Leite Junger & Nelson Gouveia, 2016. "Effects of Particulate Matter and Its Chemical Constituents on Elderly Hospital Admissions Due to Circulatory and Respiratory Diseases," IJERPH, MDPI, vol. 13(10), pages 1-11, September.
    5. SungChul Seo & Choongki Min & Madeline Preston & Sanghoon Han & Sung-Hyuk Choi & So Young Kang & Dohyeong Kim, 2022. "Ambient PM Concentrations as a Precursor of Emergency Visits for Respiratory Complaints: Roles of Deep Learning and Multi-Point Real-Time Monitoring," Sustainability, MDPI, vol. 14(5), pages 1-8, February.
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