Publications by authors named "Richard Summerhayes"
Background: There is evidence, although inconsistent, that long term exposure to disinfection by products (DBPs) increases the risk of bowel cancer. No study has been conducted in Australia to examine this association and due to difference in the methods of disinfection the risk can vary across geographical regions and. This study was conducted to analyse the association of trihalomethanes (THMs) in water with colon and rectal cancer in NSW Australia.
View Article and Find Full Text PDFBackground: Trihalomethanes in drinking water have been associated with higher occurrence of small-for-gestational-age (SGA) births, although results have been inconsistent.
Method: We geocoded residential address for mother of live, singleton, term births to 33 water distribution systems in a large metropolitan area of New South Wales, Australia (314,982 births between 1998 and 2004) and classified births into <10th percentile and ≥ 10 percentile of weight for gestational age. Mean trihalomethane exposure was estimated by trimester and for the entire pregnancy based on monthly sampling in each of the 33 water distribution systems.
Aim: This paper describes the spatio-temporal variation of trihalomethanes in drinking water in New South Wales, Australia from 1997 to 2007
Method: We obtained data on trihalomethanes (THMs) from two metropolitan and 13 rural water utilities and conducted a descriptive analysis of the spatial and temporal trends in THMs and the influence of season and drought.
Results: Concetrations of monthly THMs in the two metropolitan water utilities of Sydney/Illawarra (mean 66.8 μg/L) and Hunter (mean 62.
In the field of disease mapping, little has been done to address the issue of analysing sparse health datasets. We hypothesised that by modelling two outcomes simultaneously, one would be able to better estimate the outcome with a sparse count. We tested this hypothesis utilising Bayesian models, studying both birth defects and caesarean sections using data from two large, linked birth registries in New South Wales from 1990 to 2004.
View Article and Find Full Text PDFObjective: To better characterize the relation between socioeconomic disadvantage and small-for-gestational age births (SGA).
Design: Analysis of data from a mandatory population-based surveillance system.
Setting: Public or private hospitals and at home.
Article Synopsis
- The paper outlines a framework to explore how socioeconomic and cultural factors affect health in rural areas, focusing on both individual and community-level influences.
- It highlights that socioeconomic disadvantage and indigenous status are major contributors to health disparities in rural communities, along with challenges in accessing healthcare services.
- The findings emphasize that factors like local social dynamics, individual attitudes, and environmental issues are critical in understanding the health of residents in rural Australia.
Article Synopsis
- The study investigates how socioeconomic factors relate to acute coronary events and mortality in New South Wales, Australia, from 1996 to 2002, using advanced statistical models to analyze data.
- Findings reveal that higher socioeconomic disadvantage correlates with an increased risk of mortality from ischemic heart disease and lower rates of critical medical procedures like angiography.
- Additionally, areas with a higher indigenous population experience higher admission and mortality rates, and living in the state capital correlates with increased access to necessary interventions.
Article Synopsis
- The Conditional Autoregressive (CAR) model is commonly used in small-area ecological studies but lacks extensive evaluation on how different neighbourhood weight matrices affect its smoothing performance.
- In a study of birth records and defects in New South Wales from 1995-2003, various adjacency-based and distance-based neighbourhood weight matrices were tested to see which provided better predictions.
- The results indicated that distance-based matrices outperformed adjacency-based ones, with specific models demonstrating varying levels of accuracy in identifying high-risk areas, highlighting the importance of selecting the appropriate neighbourhood weight matrix for ecological modeling.