Extreme temperature exposure and urolithiasis: A time series analysis in Ganzhou, China

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. Show more

Nephrolithiasis is a highly prevalent disease worldwide with rates ranging from 7 to 13% in North America, 5-9% in Europe, and 1-5% in Asia. Due to high rates of new and recurrent stones, management of stones is expensive and the disease has a high level of acute and chronic morbidity. The goal of this study is to review the epidemiology of stone disease in order to improve patient care. A review of the literature was conducted through a search on Pubmed®, Medline®, and Google Scholar®. This review was presented and peer-reviewed at the 3rd International Consultation on Stone Disease during the 2014 Société Internationale d'Urologie Congress in Glasgow. It represents an update of the 2008 consensus document based on expert opinion of the most relevant studies. There has been a rising incidence in stone disease throughout the world with a narrowing of the gender gap. Increased stone prevalence has been attributed to population growth and increases in obesity and diabetes. General dietary recommendations of increased fluid, decreased salt, and moderate intake of protein have not changed. However, specific recommended values have either changed or are more frequently reported. Geography and environment influenced the likelihood of stone disease and more information is needed regarding stone disease in a large portion of the world including Asia and Africa. Randomized controlled studies are lacking but are necessary to improve recommendations regarding diet and fluid intake. Understanding the impact of associated conditions that are rapidly increasing will improve the prevention of stone disease. Show more

Ambient temperature is an important determinant of daily mortality that is of interest both in its own right and as a confounder of other determinants investigated using time-series regressions, in particular, air pollution. The temperature-mortality relationship is often found to be substantially nonlinear and to persist (but change shape) with increasing lag. We review and extend models for such nonlinear multilag forms. Popular models for mortality by temperature at given lag include polynomial and natural cubic spline curves, and the simple but more easily interpreted linear thresholds model, comprising linear relationships for temperatures below and above thresholds and a flat middle section. Most published analyses that have allowed the relationship to persist over multiple lags have done so by assuming that spline or threshold models apply to mean temperature in several lag strata (e.g., lags 0-1, 2-6, and 7-13). However, more flexible models are possible, and a modeling framework using products of basis functions ("cross-basis" functions) suggests a wide range, some used previously and some new. These allow for stepped or smooth changes in the model coefficients as lags increase. Applying a range of models to data from London suggest evidence for relationships up to at least 2 weeks' lag, with smooth models fitting best but lag-stratified threshold models allowing the most direct interpretation. A wide range of multilag nonlinear temperature-mortality relationships can be modeled. More awareness of options should improve investigation of these relationships and help control for confounding by them. Show more