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 B. and Mortensen, Preben Bo (2007) The impact of nonlinear exposure-risk relationships on seasonal time-series data: modelling Danish neonatal birth anthropometric data. BMC Medical Research Methodology, 7 Article Number: 45. doi:10.1186/1471-2288-7-45


Author McGrath, John
Barnett, Adrian
Eyles, Darryl
Burne, Thomas
Pedersen, Carsten B.
Mortensen, Preben Bo
Title The impact of nonlinear exposure-risk relationships on seasonal time-series data: modelling Danish neonatal birth anthropometric data
Journal name BMC Medical Research Methodology   Check publisher's open access policy
ISSN 1471-2288
Publication date 2007-10-15
Year available 2007
Sub-type Article (original research)
DOI 10.1186/1471-2288-7-45
Open Access Status DOI
Volume 7
Start page Article Number: 45
Total pages 10
Editor M. Norton
Place of publication London, England
Publisher BioMed Central Ltd
Collection year 2008
Language eng
Subject 321204 Mental Health
C1
730211 Mental health
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.
Keyword Coronary-heart-disease
Vitamin-d Deficiency
London-Based Cohort
Body-mass Index
BMI
Outdoor Temperature
weight
Pregnancy
Pregnancy
growth
mortality
Determinants
Q-Index Code C1
Q-Index Status Confirmed Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2008 Higher Education Research Data Collection
School of Medicine Publications
 
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Created: Fri, 28 Mar 2008, 01:01:27 EST by Carmel Meir on behalf of School of Medicine