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Measures of Association and Public Health Impact
Published in Frank R. Spellman, Fundamentals of Wastewater-Based Epidemiology, 2021
Another measure of association is an odds ratio; it quantifies the relationship between an exposure with two categories and health outcome. Moreover, the odds ratio is the measure of choice in a case-control study. A case-control study is based on enrolling a group of persons with disease (“case-patients”) and a comparable group without disease (“controls”). The number of persons in the control group is usually decided by the investigation. Often, the size of the population from which the case-patients came is not known. As a result, risks, rates, risk ratios, or rater ratios can’t be calculated from the typical case-control study. However, you can calculate an odds ratio and interpret it as an approximation of the risk ratio, particularly when the disease is uncommon in the population.
Environmental Epidemiology
Published in Lorris G. Cockerham, Barbara S. Shane, Basic Environmental Toxicology, 2019
The odds ratio (OR) is an estimate of relative risk derived from case-control studies, described in more detail earlier in Section E. This measure of risk is the ratio of odds or proportions, that is, the proportion of a group experiencing an exposure to the proportion not experiencing the same exposure. For example, Alavanja et al. (1989) conducted a case-control study of non-Hodgkin’s lymphoma deaths and matched control deaths, all of which were identified through a file of U.S. Department of Agriculture employees dying between 1970 and 1979. They reported an odds ratio of 2.6 (p < 0.05) for soil conservationists after 1960, indicating that this group of USDA workers were disproportionately represented among the cases compared to controls. It is hypothesized that the positive results seen for non-Hodgkin’s lymphoma and certain other cancers in workers employed in agriculture-related occupations may be related to herbicide or insecticide exposure.
Sensitivity Analysis
Published in Charles Yoe, Principles of Risk Analysis, 2019
The odds ratio or odds of an event is simply P(A)1−P(A) or, in words, it is the ratio of the probability that the event occurs to the probability that the event does not occur (Gordis 1996). The log of the odds ratio or logit simply takes the log of the odds ratio, i.e., logit = log P(A)1−P(A).
Effects of exposure to moisture on biodeterioration of facade finishes in the hot-humid tropical environment of Enugu metropolis, Nigeria
Published in Architectural Science Review, 2022
Lawrence A. Isiofia, Francis O. Uzuegbuman, Eziyi O. Ibem
The data were analysed using descriptive and logistic regression analyses. The former involved the calculation of frequency and percentage distributions of the buildings according to their types/uses, exposed or not exposed façade, colonized and non-colonized façade and extent of microbial colonization. The logistic regression analysis was used to investigate the relationship between exposure to moisture and colonization of façade finishes and surfaces of the buildings sampled. This analysis helped in predicting the likelihood of biodeterioration of façade finishes occurring when external envelope of buildings in Enugu metropolis are exposed to moisture. The Odds ratios were estimated based on 95% confidence interval with P-value < 0.05 taken as the significance level. Results of the analyses are presented in tables and charts.
Basketball performance is affected by the schedule congestion: NBA back-to-backs under the microscope
Published in European Journal of Sport Science, 2021
Pedro T. Esteves, Kazimierz Mikolajec, Xavier Schelling, Jaime Sampaio
Stage 4: Predicting the probability to win a match in view of congestion cycles. A binary logistic regression was used to investigate the effects of fixture congestion cycles with 4 levels (back-to-back games, 1 day rest; 2 days rest; 3 or more days rest), game location (2 levels: home and away) and quality of the opponent (3 levels: top, middle and bottom teams) on the likelihood to win a match (2 levels: game won or lost). Odds ratios (OR) and the respective 95% confidence intervals were computed and considered statistically significant if the upper and lower boundaries of the 95% confidence intervals excluded 1.00. Statistical analyses were performed using IBM Corp. Released 2015. IBM SPSS Statistics for Mac, Version 23.0. Armonk, NY: IBM Corp.
The Network of Household Barriers to Achieving SDG 1, 2 and 3 in Maputo, Mozambique
Published in Journal of Hunger & Environmental Nutrition, 2021
Cameron McCordic, Bruce Frayne
This investigation relies on descriptive statistics to identify the kinds of challenges faced by households with chronically ill members. In the course of this investigation, two kinds of analyses are used: odds ratios and web graphs. Odds ratios provide a means of assessing the change in odds of one event occurring given the occurrence of another event [among two dichotomous or binary variables). For example, the change in the odds of household food insecurity given the existence of household members with chronic illness. These calculations are paired with Pearson’s Chi-Square tests in order to provide a p-value for the observed odds ratio in these calculations.