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Individual Event Modeling
Published in Andrew B. Lawson, Using R for Bayesian Spatial and Spatio-Temporal Health Modeling, 2021
By specific it is meant that a locational geocode is the focus of the individual health outcome analysis. In this sense this is a directly spatial analysis (rather than a spatial contextual analysis). For example, in environmental epidemiology it is a common theme that proximity to potential insults (e.g., sources of pollution) should be a primary concern in the assessment of disease risk. This can take two forms. First location of an individual (such as residence) is related to the ‘local’ environment at or near that location. In this case measures of potential insults could be evaluated at or near the location. These could be interpolated to the location (of residence). A classic example would be particulate matter in the air (PM2.5 or 10) could be thought to relate to asthma incidence. If residential location of asthma sufferers is available then PM2.5 or PM10 measured at monitor sites in the vicinity of the residences could be interpolated to location of residence (Kibria et al., 2002, Chang, 2016). In this case, the disease outcome is yi at the i th location (coordinates: ). Assume that we have a set of n measurement sites for an environmental insult A model is required for the interpolation to the m individual locations. Ultimately a joint model for the disease outcome and interpolation must be assumed.
Our strained relations with environmental agents
Published in Richard Lawson, Jonathon Porritt, Bills of Health, 2018
Richard Lawson, Jonathon Porritt
Investigations into the effects of environmental agents concentrate on definite events that can be measured without dispute, such as death or cancer. More subtle conditions such as tiredness, apparent depression or general increase in low-grade illness are not picked up by these methods. Viewed in this light, environmental epidemiology is still in its infancy. A prodigious amount of work is necessary to decide each point of scientific debate, and it is entirely possible that we are missing a large amount of environmentally induced illness through not rightly knowing what to look for. The effects of tobacco would not have been recognized without the presence of a comparative group of non-smokers - yet where is the comparable population that is not affected to some degree by environmental pollution?
General Survey of Geomedicine
Published in Jul Låg, Geomedicine, 2017
The word epidemiology in human and veterinary medicine was originally used in connection with infectious diseases. Illnesses with physiological background were included later. In environmental epidemiology many geomedical problems are discussed.22
The methodological rigour of systematic reviews in environmental health
Published in Critical Reviews in Toxicology, 2022
J. M. L. Menon, F. Struijs, P. Whaley
We employed a purposive SR sampling strategy aimed at covering a range of environmental health topics in a narrow, recent time window. We defined environmental health as “the investigation of associations between exposures to exogenous environmental challenges and health outcomes,” including toxicology and environmental epidemiology, as per our protocol (Menon et al. 2020). To be eligible for inclusion in the SR sample, documents had to fulfil the following criteria:identify explicitly as a “systematic review” in their title;assess the effect of a non-acute, non-communicable, environmental exposure on a health outcome;include studies in people or mammalian models;be available in HTML format;be published between 1 January 2019 and 30 June 2020.
Using the Matrix to bridge the epidemiology/risk assessment gap: a case study of 2,4-D
Published in Critical Reviews in Toxicology, 2021
Carol J. Burns, Judy S. LaKind
The fields of environmental epidemiology and exposure science have provided consequential data for use in meta-analyses, systematic reviews, and ultimately, public health decision-making. Yet while activities such as the development of reference doses have been based on data from epidemiology studies, it is often the case that these data are secondary to toxicological data or are judged to be insufficient to examine exposure-outcome associations (Nachman et al. 2011; EFSA Panel on Plant Protection Products et al. 2017; Deener et al. 2018). While calls have been made for improving the utility of epidemiology for risk assessment, hurdles remain (Burns et al. 2014; Christensen et al. 2015; Birnbaum et al. 2016). In an effort to move the needle on this issue, an international, multi-sector group with expertise in risk assessment, toxicology, epidemiology, and exposure science developed the Matrix (Table 1), a structured approach to bridging the risk assessment-epidemiology gap (Burns et al. 2019).
Pyrethroid epidemiology: a quality-based review
Published in Critical Reviews in Toxicology, 2018
Carol J. Burns, Timothy P. Pastoor
The many instruments that provide guidance in reporting and interpretation of epidemiology data demonstrate the need for quality epidemiology research. As the reliance upon animal toxicology data declines, the importance of valid and reliable epidemiology data increases. To be used for human health risk assessment, proposals for future environmental epidemiology studies should improve the status quo for evaluation of exposure to pyrethroids (and other pesticides) and confirming health effects. The barriers to study quality entail a balance of cost, time and burdens to the study subject (s). A broader conversation is needed to recognize the different purposes of human data, e.g. clinical, research and regulation (risk assessment). A case in point is collecting two semen samples in clinical settings to establish a diagnostic category, but one sample may be sufficient to develop research hypotheses (Chiu et al. 2017). To test hypotheses, particularly for human health risk assessment, minimizing the risk of bias is more important than statistical precision. Epidemiologists and those who rely on human data must begin to agree on best practices.