International Journal of Biometeorology

, Volume 63, Issue 11, pp 1517–1524 | Cite as

Excess of children’s outpatient consultations due to asthma and bronchitis and the association between meteorological variables in Canoas City, Southern Brazil

  • Igor Rojahn da SilvaEmail author
  • Anderson Spohr Nedel
  • Júlio Renato Quevedo Marques
  • Luciano Ritter Nolasco Júnior
Special Issue: Brazilian Congress - Jaboticabal 2017


The southern Brazilian city of Canoas, situated in the metropolitan region of Porto Alegre, is subject to several annual meteorological phenomena, such as cold fronts and squall lines. Here, we assess the relationship between meteorological conditions and outpatient consultations for asthma or bronchitis in children from Canoas City. Data from outpatient consultations of children (below 9 years), between January/2005 and September/2008, were combined with daily meteorological data from 12UTC (morning) and 18UTC (afternoon). We identified 42 days with an excess of outpatient consultations (peaks). Consultations were negatively correlated with temperature and human thermal comfort index (HTCI) from the 3 previous days based on consultation data at 12 and 18UTC, and positively correlated with atmospheric pressure. A positive correlation with relative humidity was significant only at 12UTC. The highest correlations occurred on the day of consultation (12UTC) with temperature, relative humidity, and atmospheric pressure, as well as 2 days previous to the HTCI. The sensation of cold was associated with about 55% of the days of the period at 12UTC: considering only the peaks of consultations, this association exceeds 90% of days. The highest frequencies of respiratory complications (June, July, and August) were associated with negative temperature anomalies, wind speed and direction, and positive anomalies in relative humidity and atmospheric pressure. Nearly half (45%) of the air masses associated with respiratory complications arrived at Canoas from a SW direction, 19% from the south and 14% from the west. In summary, observed increases in respiratory complications were mainly associated with the presence of cold and humid air (and/or falling temperature with increasing humidity) in the morning.


Air mass Cold High pressure system Respiratory diseases 



The authors would like to thank the Instituto Nacional de Meteorologia (INMET) for transferring the meteorological data, the Centro Estadual de Vigilância em Saúde, belonging with the Secretaria da Saúde do Rio Grande do Sul (CEVS/SES/RS) for providing the health data and the Air Resources Laboratory/National Center for Environment Prediction (ARL/NOAA) for making available the HYSPLIT model.


  1. Azevedo JMF (2010) A influência das variáveis ambientais (meteorológicas e de qualidade do ar) na morbidade respiratória e cardiovascular na Área Metropolitana do Porto. Thesis, University of São PauloGoogle Scholar
  2. Bucher K, Haase C (1993) Meteorotropy and medical-meteorological forecasts. Rev Experientia 49:759–768CrossRefGoogle Scholar
  3. Coelho MS (2007) Uma análise estatística com vistas a previsibilidade de internações por doenças respiratórias em função de condições meteorotrópicas na cidade de São Paulo. Thesis, University of São PauloGoogle Scholar
  4. DATASUS (2016). Accessed 29 december 2016
  5. Draxler RR, Hess GD (1998) An overview of the HYSPLIT_4 modeling system of trajectories, dispersion, and deposition. Aust Meteorol Mag 47:295–308Google Scholar
  6. Fanger PO (1970) Thermal comfort. Analysis and applications in environmental engineering. McGraw-Hill, New YorkGoogle Scholar
  7. Givoni B (1976) Man, climate and architecture. Van Nostrand Reinhold Company, LondonGoogle Scholar
  8. Gobo JPA, Galvani E (2012) Aplicação do Índice de temperatura efetiva com vento (TEV) nos estudos de conforto térmico para o estado do Rio Grande do Sul. Revista Geonorte 1(5):403–413Google Scholar
  9. Gonçalves FLT, Carvalho LMV, Conde FC, Latorre MRDO, Saldiva PHN, Braga ALF (2005) The effects of air pollution and meteorological parameters on respiratory morbidity during the summer in Sao Paulo city. Environ Int 31:343–349CrossRefGoogle Scholar
  10. Hondula DM, Davis RE, Knight DB, Sitka LJ, Enfield K, Gawtry SB, Stenger PJ, Deaton ML, Normile CP, Lee TR (2012) A respiratory alert model for the Shenandoah Valley, Virginia, USA. Int J Biometeorol 57:91–105CrossRefGoogle Scholar
  11. Jamason PF, Kalkstein LS, Gergen PJ (1997) A synoptic evaluation of asthma hospital admissions in new York City. Am J Respir Crit Care Med 156:1781–1788CrossRefGoogle Scholar
  12. Lecha LB (1998) Biometeorological classification of daily weather types for the humid tropics. Int J Biometeorol 42:77–83CrossRefGoogle Scholar
  13. Lopes FN (2015) Associação entre condições meteorológicas de inverno e doenças respiratórias em crianças na cidade de Pelotas-RS. Dissertation, Federal University of PelotasGoogle Scholar
  14. Maia JA (2002) Uma análise do conforto térmico e suas relações meteorotrópicas na cidade de São Paulo. Dissertation, University of São PauloGoogle Scholar
  15. Martins MCH (2003) Avaliação de interação entre poluição atmosférica e variáveis socioeconômicas como agravantes das condições de saúde no município de São Paulo: um estudo de ecologia humana. Thesis, University of São PauloGoogle Scholar
  16. McGregor GR, Walters S, Wordley J (1999) Daily hospital respiratory admissions and winter air mass types, Birmingham, UK. Int J Biometeorol 43:21–30CrossRefGoogle Scholar
  17. Monteiro LM (2008) Modelos Preditivos de Conforto Térmico: quantificação de relações entre variáveis microclimáticas e de sensação térmica para avaliação e projeto de espaços abertos. Thesis, University of São PauloGoogle Scholar
  18. Nedel AS (2008) Condições meteorológicas favoráveis à ocorrência de doenças respiratórias em crianças da cidade de São Paulo. Thesis, University of São PauloGoogle Scholar
  19. Petrou I, Dimitriou K, Kassomenos P (2015) Distinct atmospheric patterns and associations with acute heat-induced mortality in five regions of England. Int J Biometeorol 59:1413–1424CrossRefGoogle Scholar
  20. Prietsch SOM, Fischer GB, Cesar JA, Fabris AR, Mehanna H, Ferreira THP, Scheifer LA (2002) Doença aguda das vias aéreas inferiores em menores de cinco anos: influência do ambiente doméstico e do tabagismo materno. J Pediatr 78(5):415–422Google Scholar
  21. Rothfusz LP (1990) The heat index equation (or, more than you ever wanted to know about heat index). National Oceanic and Atmospheric Administration. Accessed 03 July 2016
  22. Rusticucci M, Bettolli ML, Harris de Los Angeles M (2002) Association between weather conditions and the number of patients at the emergency room in an Argentine hospital. Int J Biometeorol 46:42–51CrossRefGoogle Scholar
  23. Steadman RG (1979) The assessment of sultriness. Part I: a temperature-humidity index based on human physiology and clothing science. J Appl Meteorol 18:861–873CrossRefGoogle Scholar
  24. Suping Z, Guanglin M, Yanwen W, Ji L (1992) Study of the relationships between weather conditions and the marathon race, and of meteorotropic effects on distance runners. Int J Biometeorol 36:63–68CrossRefGoogle Scholar
  25. VIGIAR (2015). Manual de Instruções. Accessed 12 december 2016

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© ISB 2018

Authors and Affiliations

  1. 1.Postgraduate Program of Meteorology, College of MeteorologyFederal University of PelotasPelotasBrazil

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