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The impact of nonlinear exposure risk relationships on seasonal time series data: modelling danish neonatal birth anthropometric data

McGrath, John , Barnett, Adrian, Eyles, Darryl , Burne, Thomas , Pedersen, Carsten , & Mortensen, Preben (2007) The impact of nonlinear exposure risk relationships on seasonal time series data: modelling danish neonatal birth anthropometric data. BMC Medical Research Methodology, 7(45), pp. 1-10.

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Abstract

Background

Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods

Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results

The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion

In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

Impact and interest:

8 citations in Scopus
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6 citations in Web of Science®

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ID Code: 45058
Item Type: Journal Article
DOI: 10.1186/1471-2288-7-45
ISSN: 1471-2288
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000)
Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > PUBLIC HEALTH AND HEALTH SERVICES (111700)
Deposited On: 25 Aug 2011 08:16
Last Modified: 01 Mar 2012 00:02

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