Distributed lag non‐linear models
Open accessAbstract
Environmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure–response relationship. Here we develop the family of distributed lag non‐linear models (DLNM), a modelling framework that can simultaneously represent non‐linear exposure–response dependencies and delayed effects. This methodology is based on the definition of a ‘cross‐basis’, a bi‐dimensional space of functions that describes simultaneously the shape of the relationship along both the space of the predictor and the lag dimension of its occurrence. In this way the approach provides a unified framework for a range of models that have previously been used in this setting, and new more flexible variants. This family of models is implemented in the package dlnm within the statistical environment R. To illustrate the methodology we use examples of DLNMs to represent the relationship between temperature and mortality, using data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) for New York during the period 1987–2000. Copyright © 2010 John Wiley & Sons, Ltd.
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Using DLMs allowed estimation of differences in metal uptake between ASD cases and control twin pairs at discrete developmental stages while accounting for exposures at other time points.
“Using DLMs, we were able to estimate the differences in metal uptake between ASD cases and control twin pairs at discrete developmental stages, while accounting for exposures at other time points.”
From Fetal and postnatal metal dysregulation in autism (2017) · cites this paper as [25]
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- Authors
- Gasparrini, A., Armstrong, B., & Kenward, M. G.
- Affiliations
- London School of Hygiene & Tropical Medicine (GB)
- Corresponding author
- Gasparrini, A.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2010-08-26
- Volume
- 29
- Issue
- 21
- Pages
- 2224-2234
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- PMC
- PMC2998707
- OpenAlex
- W2006203329
- Cited by
- 2,481
- References
- 39
- Citations by year
- 2026: 319 · 2025: 301 · 2024: 338 · 2023: 244 · 2022: 267 · 2021: 207 · 2020: 173 · 2019: 142 · 2018: 110 · 2017: 90 · 2016: 76 · 2015: 53 · 2014: 55 · 2013: 52 · 2012: 31
- FWCI
- 25.65
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Statistics in Medicine (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Funders
- Re-use of this article is permitted in accordance with the Terms and Conditions set out at [http://wileyonlinelibrary.com/author resources/onlineopen.html]
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
- Keywords
- distributed lag non-linear model, lagged effects, temperature-mortality relationship, air pollution
- MeSH terms
- Algorithms, Environmental Exposure, Humans, Mortality, New York City, Risk, Software, Temperature, Time Factors, Models, Statistical, Databases, Factual, Nonlinear Dynamics, Internet
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