Analysing spatially referenced public health data: a comparison of three methodological approaches

Dunn, Christine E.; Kingham, Simon; Rowlingson, Barry; Bhopal, Raj; Cockings, Samantha; Foy, Chris; Acquilla, S.; Halpin, Jane; Diggle, Peter J.; Walker, David

doi:10.1016/s1353-8292(00)00033-2

Cited by 29 publications

(11 citation statements)

References 14 publications

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“…In light of this the contextual role of unseasonably high air temperatures is therefore worthy of further investigation. Further work is warranted to explore spatial dispersal mechanisms through techniques such as air quality dispersion modelling, the results of which can be interfaced to Geographical Information Systems (GIS) software [10,30,31]. Using mean monthly temperatures for states in the Mid-Atlantic region of the USA, Hicks et al [22] found statistically significant correlations between monthly case counts of legionellosis and temperature in the preceding month.…”

Section: Discussionmentioning

confidence: 99%

Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling

et al. 2012

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This study investigated the relationships between Legionnaires' disease (LD) incidence and weather in Glasgow, UK, by using advanced statistical methods. Using daily meteorological data and 78 LD cases with known exact date of onset, we fitted a series of Poisson log-linear regression models with explanatory variables for air temperature, relative humidity, wind speed and year, and sine-cosine terms for within-year seasonal variation. Our initial model showed an association between LD incidence and 2-day lagged humidity (positive, P = 0·0236) and wind speed (negative, P = 0·033). However, after adjusting for year-by-year and seasonal variation in cases there were no significant associations with weather. We also used normal linear models to assess the importance of short-term, unseasonable weather values. The most significant association was between LD incidence and air temperature residual lagged by 1 day prior to onset (P = 0·0014). The contextual role of unseasonably high air temperatures is worthy of further investigation. Our methods and results have further advanced understanding of the role which weather plays in risk of LD infection.

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Section: Discussionmentioning

confidence: 99%

Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling

et al. 2012

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“…The findings show consistent results; the cluster identified by spatial analyses remained significant when traditional epidemiologic methods were used, and it was not explained by potential confounders. A recent study comparing 'traditional' epidemiological methods, GIS, and point pattern analysis for use in the spatially referenced public health data concluded that results complement, rather than contradict or duplicate each other [29].…”

Section: Discussionmentioning

confidence: 99%

Geographic clustering of residence in early life and subsequent risk of breast cancer (United States)

Han

Rogerson

Nie

et al. 2004

Cancer Causes Control

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“…Areas differ in exposure to factors including noise and air pollution. When analysing these physical influences units at a level higher than socially homogeneous units or administrative units are relevant (25).…”

Section: What Is a Level And Which Levels Are Relevant?mentioning

confidence: 99%

Multilevel modelling and public health policy

Leyland

Groenewegen

2003

Scand J Public Health

163

100

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This paper therefore lays out the a basic description of multilevel modelling, discusses the problems of alternative approaches, and details the relevance for public health policy before describing which levels are relevant and illustrating the different kinds of hypotheses that can be tested using multilevel modelling. A series of examples is used throughout the paper. These relate to regional variations in the incidence of heart disease, the allocation of health resources, the relationship between neighbourhood disorder and mental health, the demand-control model in occupational health, and a school intervention to prevent cardiovascular disease.

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Analysing spatially referenced public health data: a comparison of three methodological approaches

Cited by 29 publications

References 14 publications

Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling

Meteorological conditions and incidence of Legionnaires' disease in Glasgow, Scotland: application of statistical modelling

Geographic clustering of residence in early life and subsequent risk of breast cancer (United States)

Multilevel modelling and public health policy

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