A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand

Eleven years of hospital admissions data for Auckland, New Zealand for respiratory conditions are analyzed using a Poisson regression modelling approach, incorporating a spline function to represent time, based on a detailed record of haze events and surface air pollution levels over an eleven-year...

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Main Authors: Kim Natasha Dirks, James Scarfe, Nicholas Philip Talbot, Roger Marshall, Jennifer Anne Salmond
Format: Article
Language:English
Published: MDPI AG 2017-11-01
Series:Climate
Subjects:
Online Access:https://www.mdpi.com/2225-1154/5/4/86
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spelling doaj-632206dce1054dd49639c3d30d49a0482020-11-25T00:21:26ZengMDPI AGClimate2225-11542017-11-01548610.3390/cli5040086cli5040086A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New ZealandKim Natasha Dirks0James Scarfe1Nicholas Philip Talbot2Roger Marshall3Jennifer Anne Salmond4School of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New ZealandBay of Plenty District Health Board, Tauranga Hospital, 829 Cameron Road, Private Bag 12024, Tauranga 3134, New ZealandAuckland Council, Private Bag 92300, Auckland 1010, New ZealandSchool of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New ZealandSchool of Environment, Faculty of Science, University of Auckland, Private Bag 92019, Auckland 1142, New ZealandEleven years of hospital admissions data for Auckland, New Zealand for respiratory conditions are analyzed using a Poisson regression modelling approach, incorporating a spline function to represent time, based on a detailed record of haze events and surface air pollution levels over an eleven-year period, taking into account the daily average temperature and humidity, the day of the week, holidays and trends over time. NO2 was the only pollutant to show a statistically significant increase (p = 0.009) on the day of the haze event for the general population. Ambient concentrations of CO, NO and NO2 were significantly associated with admissions with an 11-day lag period for the 0–14 year age group and a 5–7 day lag period for the 65+ year age group. A 3-day lag period was found for the 15–64 year age group for CO, NO and PM10. Finally, the incidence of brown haze was linked to significant increases in hospital admissions. A lag period of 5 days was recorded between haze and subsequent increases in admissions for the 0–14 year age group and the 65+ group and an 11-day lag for the 15–64 year age group. The results provide the first statistical link between Auckland brown haze events, surface air pollution and respiratory health. Medical institutions and practitioners could benefit from improved capacity to predict Auckland’s brown haze events in order prepare for the likely increases in respiratory admissions over the days ahead.https://www.mdpi.com/2225-1154/5/4/86brown hazeair pollutantsrespiratory health
collection DOAJ
language English
format Article
sources DOAJ
author Kim Natasha Dirks
James Scarfe
Nicholas Philip Talbot
Roger Marshall
Jennifer Anne Salmond
spellingShingle Kim Natasha Dirks
James Scarfe
Nicholas Philip Talbot
Roger Marshall
Jennifer Anne Salmond
A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand
Climate
brown haze
air pollutants
respiratory health
author_facet Kim Natasha Dirks
James Scarfe
Nicholas Philip Talbot
Roger Marshall
Jennifer Anne Salmond
author_sort Kim Natasha Dirks
title A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand
title_short A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand
title_full A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand
title_fullStr A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand
title_full_unstemmed A Statistical Analysis of the Relationship between Brown Haze and Surface Air Pollution Levels on Respiratory Hospital Admissions in Auckland, New Zealand
title_sort statistical analysis of the relationship between brown haze and surface air pollution levels on respiratory hospital admissions in auckland, new zealand
publisher MDPI AG
series Climate
issn 2225-1154
publishDate 2017-11-01
description Eleven years of hospital admissions data for Auckland, New Zealand for respiratory conditions are analyzed using a Poisson regression modelling approach, incorporating a spline function to represent time, based on a detailed record of haze events and surface air pollution levels over an eleven-year period, taking into account the daily average temperature and humidity, the day of the week, holidays and trends over time. NO2 was the only pollutant to show a statistically significant increase (p = 0.009) on the day of the haze event for the general population. Ambient concentrations of CO, NO and NO2 were significantly associated with admissions with an 11-day lag period for the 0–14 year age group and a 5–7 day lag period for the 65+ year age group. A 3-day lag period was found for the 15–64 year age group for CO, NO and PM10. Finally, the incidence of brown haze was linked to significant increases in hospital admissions. A lag period of 5 days was recorded between haze and subsequent increases in admissions for the 0–14 year age group and the 65+ group and an 11-day lag for the 15–64 year age group. The results provide the first statistical link between Auckland brown haze events, surface air pollution and respiratory health. Medical institutions and practitioners could benefit from improved capacity to predict Auckland’s brown haze events in order prepare for the likely increases in respiratory admissions over the days ahead.
topic brown haze
air pollutants
respiratory health
url https://www.mdpi.com/2225-1154/5/4/86
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