David Kriebel

Bio: David Kriebel is an academic researcher from University of Massachusetts Lowell. The author has contributed to research in topics: Population & Poison control. The author has an hindex of 46, co-authored 186 publications receiving 7803 citations. Previous affiliations of David Kriebel include University of Massachusetts Amherst & College of Health Sciences, Bahrain.

Research Methods in Occupational Epidemiology

Abstract: 1. Introduction 2. Characterizing the workplace environment 3. Overview of study designs 4. Precision and validity in study design 5. Cohort studies 6. Case-control studies 7. Cross-sectional and repeated measure studies 8. Occupational health surveillance 9. Advanced statistical analysis 10. Exposure and dose modelling 11. Special applications of occupational epidemiology

The precautionary principle in environmental science.

Abstract: Environmental scientists play a key role in society's responses to environmental problems, and many of the studies they perform are intended ultimately to affect policy. The precautionary principle, proposed as a new guideline in environmental decision making, has four central components: taking preventive action in the face of uncertainty; shifting the burden of proof to the proponents of an activity; exploring a wide range of alternatives to possibly harmful actions; and increasing public participation in decision making. In this paper we examine the implications of the precautionary principle for environmental scientists, whose work often involves studying highly complex, poorly understood systems, while at the same time facing conflicting pressures from those who seek to balance economic growth and environmental protection. In this complicated and contested terrain, it is useful to examine the methodologies of science and to consider ways that, without compromising integrity and objectivity, research can be more or less helpful to those who would act with precaution. We argue that a shift to more precautionary policies creates opportunities and challenges for scientists to think differently about the ways they conduct studies and communicate results. There is a complicated feedback relation between the discoveries of science and the setting of policy. While maintaining their objectivity and focus on understanding the world, environmental scientists should be aware of the policy uses of their work and of their social responsibility to do science that protects human health and the environment. The precautionary principle highlights this tight, challenging linkage between science and policy.

Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done?

Abstract: OBJECTIVES: To review the appropriateness of the prevalence odds ratio (POR) and the prevalence ratio (PR) as effect measures in the analysis of cross sectional data and to evaluate different models for the multivariate estimation of the PR. METHODS: A system of linear differential equations corresponding to a dynamic model of a cohort with a chronic disease was developed. At any point in time, a cross sectional analysis of the people then in the cohort provided a prevalence based measure of the effect of exposure on disease. This formed the basis for exploring the relations between the POR, the PR, and the incidence rate ratio (IRR). Examples illustrate relations for various IRRs, prevalences, and differential exodus rates. Multivariate point and interval estimation of the PR by logistic regression is illustrated and compared with the results from proportional hazards regression (PH) and generalised linear modelling (GLM). RESULTS: The POR is difficult to interpret without making restrictive assumptions and the POR and PR may lead to different conclusions with regard to confounding and effect modification. The PR is always conservative relative to the IRR and, if PR > 1, the POR is always > PR. In a fixed cohort and with an adverse exposure, the POR is always > or = IRR, but in a dynamic cohort with sufficient underlying follow up the POR may overestimate or underestimate the IRR, depending on the duration of follow up. Logistic regression models provide point and interval estimates of the PR (and POR) but may be intractable in the presence of many covariates. Proportional hazards and generalised linear models provide statistical methods directed specifically at the PR, but the interval estimation in the case of PH is conservative and the GLM procedure may require constrained estimation. CONCLUSIONS: The PR is conservative, consistent, and interpretable relative to the IRR and should be used in preference to the POR. Multivariate estimation of the PR should be executed by means of generalised linear models or, conservatively, by proportional hazards regression.

The future of sustainability science: a solutions-oriented research agenda

Abstract: Over the last decade, sustainability science has been at the leading edge of widespread efforts from the social and natural sciences to produce use-inspired research. Yet, how knowledge generated by sustainability science and allied fields will contribute to transitions toward sustainability remains a critical theoretical and empirical question for basic and applied research. This article explores the limitations of sustainability science research to move the field beyond the analysis of problems in coupled systems to interrogate the social, political and technological dimensions of linking knowledge and action. Over the next decade, sustainability science can strengthen its empirical, theoretical and practical contributions by developing along four research pathways focused on the role of values in science and decision-making for sustainability: how communities at various scales envision and pursue sustainable futures; how socio-technical change can be fostered at multiple scales; the promotion of social and institutional learning for sustainable development.

Bias in occupational epidemiology studies

Abstract: The design of occupational epidemiology studies should be based on the need to minimise random and systematic error. The latter is the focus of this paper, and includes selection bias, information bias and confounding. Selection bias can be minimised by obtaining a high response rate (and by appropriate selection of the control group in a case-control study). In general, it is important to ensure that information bias is minimised and is also non-differential (for example, that the misclassification of exposure is not related to disease status) by collecting data in a standardised manner. A major concern in occupational epidemiology studies usually relates to confounding, because exposure has not been randomly allocated, and the groups under study may therefore have different baseline disease risks. For each of these types of bias, the goal should be to avoid the bias by appropriate study design and/or appropriate control in the analysis. However, it is also important to attempt to assess the likely direction and strength of biases that cannot be avoided or controlled.

IARC Monographs on the Evaluation of Carcinogenic Risks to Humans

Abstract: Viral hepatitis in all its forms is a major public health problem throughout the world, affecting several hundreds of millions of people. Viral hepatitis is a cause of considerable morbidity and mortality both from acute infection and chronic sequelae which include, in the case of hepatitis B, C and D, chronic active hepatitis and cirrhosis. Hepatocellular carcinoma, which is one of the 10 commonest cancers worldwide, is closely associated with hepatitis B and, at least in some regions of the world, with hepatitis C virus. This timely monograph is a distillation of knowledge of hepatitis B, C and D, based on a review of 1000 studies by a small group of scientists. (It is interesting to note in passing that some 5000 papers on viral hepatitis are published annually in the world literature.) The epidemiological, clinical and experimental data on the association between infection with hepatitis B virus and primary liver cancer in humans are reviewed in a readable and succinct format. The available information on hepatitis C and progression to chronic infection is also evaluated and it is concluded (perhaps a little prematurely) that hepatitis C virus is carcinogenic. However, it is concluded that hepatitis D virus, an unusual virus with a number of similarities to certain plant viral satellites and viroids, cannot be classified as a human carcinogen. There are some minor criticisms: there are few illustrations and some complex tabulations (for example, Table 6) and no subject index. A cumulative cross index to IARC Monographs is of little value and occupies nearly 30 pages. This small volume is a useful addition to the overwhelming literature on viral hepatitis, and the presentation is similar to the excellent World Health Organisation Technical Reports series on the subject published in the past. It is strongly recommended as a readable up-to-date summary of a complex subject; and at a cost of 65 Sw.fr (approximately £34) is excellent value. A J ZUCKERMAN

A Modified Poisson Regression Approach to Prospective Studies with Binary Data

Abstract: Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson regression with a robust error variance) to estimate this effect measure directly. A simple 2-by-2 table is used to justify the validity of this approach. Results from a limited simulation study indicate that this approach is very reliable even with total sample sizes as small as 100. The method is illustrated with two data sets.

Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio

Abstract: Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies with techniques that directly estimate the prevalence ratio. We compared Cox regression with constant time at risk, Poisson regression and log-binomial regression against the standard Mantel-Haenszel estimators. Models with robust variance estimators in Cox and Poisson regressions and variance corrected by the scale parameter in Poisson regression were also evaluated. Three outcomes, from a cross-sectional study carried out in Pelotas, Brazil, with different levels of prevalence were explored: weight-for-age deficit (4%), asthma (31%) and mother in a paid job (52%). Unadjusted Cox/Poisson regression and Poisson regression with scale parameter adjusted by deviance performed worst in terms of interval estimates. Poisson regression with scale parameter adjusted by χ2 showed variable performance depending on the outcome prevalence. Cox/Poisson regression with robust variance, and log-binomial regression performed equally well when the model was correctly specified. Cox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to non-specialists than the odds ratio. However, precautions are needed to avoid estimation problems in specific situations.

The Environmental Protection Agency

Abstract: The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

Targeting hypoxia in cancer therapy

Abstract: Hypoxia is a feature of most tumours, albeit with variable incidence and severity within a given patient population. It is a negative prognostic and predictive factor owing to its multiple contributions to chemoresistance, radioresistance, angiogenesis, vasculogenesis, invasiveness, metastasis, resistance to cell death, altered metabolism and genomic instability. Given its central role in tumour progression and resistance to therapy, tumour hypoxia might well be considered the best validated target that has yet to be exploited in oncology. However, despite an explosion of information on hypoxia, there are still major questions to be addressed if the long-standing goal of exploiting tumour hypoxia is to be realized. Here, we review the two main approaches, namely bioreductive prodrugs and inhibitors of molecular targets upon which hypoxic cell survival depends. We address the particular challenges and opportunities these overlapping strategies present, and discuss the central importance of emerging diagnostic tools for patient stratification in targeting hypoxia.