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Extra virgin olive oil (EVOO) has healthy benefits for noncommunicable diseases (NCDs). However, limited evidence is available about the effects of liver disease and non-alcoholic fatty liver disease (NAFLD). We evaluate whether dose-increased consumption of EVOO is associated with a lower prevalence of NAFLD and if these effects vary based on body weight. The study included 2436 subjects with a 33% NAFLD prevalence. Daily EVOO was categorized into tertiles: low (0–24 g/day), moderate (25–37 g/day), and high consumption (>37 g/day). Subjects were also classified by body mass index (BMI) as normo-weight (18.5–24.9), overweight (25–29.9), and obese (≥30). Logistic regression analysis was applied to calculate odds ratios (ORs) for NAFLD, considering a 20-gram increment in EVOO intake and accounting for EVOO categories combined with BMI classes. The ORs were 0.83 (0.74;0.93) C.I. p = 0.0018 for continuous EVOO, 0.89 (0.69;1.15) C.I. p = 0.37, and 0.73 (0.55;0.97) C.I. p = 0.03 for moderate and high consumption, respectively, when compared to low consumption. Overall, the percent relative risk reductions (RRR) for NAFLD from low to high EVOO consumption were 18% (16.4%;19.2%) C.I. and 26% (25%;27.4%) C.I. in overweight and obese subjects. High EVOO consumption is associated with a reduced risk of NAFLD. This effect is amplified in overweight subjects and even more in obese subjects.

Risk management is a significant part of federal wildland fire management in the USA because policy encourages the use of fire to maintain and restore ecosystems while protecting life and property. In this study, patterns of wildfire risk were explored from operational relative risk assessments (RRA) completed by land managers on 5087 wildfires from 2010 to 2017 in every geographic area of the USA. The RRA is the formal risk assessment used by land managers to develop strategies on emerging wildfires when concerns and issues related to wildfire management are in real-time. Only 38% of these wildfires were rated as high risk and 28% had high ratings for values at risk. Large regional variations were evident, with the West Coast regions selecting high risk and the South-west and Eastern regions selecting low risk. There were finer-scale influences on perceived risk when summarised on a jurisdictional level. Finally, risk summarised by USA agencies showed that the National Park Service and USDA Forest Service selected high risk less frequently compared with other agencies. By illuminating patterns of risk, this research intends to stimulate examination of the social, cultural, and physiographic factors influencing conceptions of risk.

Logistic regression models are frequently used in cohort studies to determine the association between treatment and dichotomous outcomes in the presence of confounding variables. In a logistic regression model, the association between exposure and outcome is measured using the odds ratio (OR). The OR can be difficult to interpret and only approximates the relative risk (RR) in certain restrictive settings. Several authors have suggested that for dichotomous outcomes, RRs, RR reductions, absolute risk reductions, and the number needed to treat (NNT) are more clinically meaningful measures of treatment effect. We describe a method for deriving clinically meaningful measures of treatment effect from a logistic regression model. This method involves determining the probability of the outcome if each subject in the cohort was treated and if each subject was untreated. These probabilities are then averaged across the study cohort to determine the average probability of the outcome in the population if all subjects were treated and if they were untreated. Risk differences, RRs, and NNTs were derived using a logistic regression model. Clinically meaningful measures of effect can be derived from a logistic regression model in a cohort study. These methods can also be used in randomized controlled trials when logistic regression is used to adjust for possible imbalance in prognostically important baseline covariates.

Preimplantation genetic testing for polygenic disease risk (PGT-P) represents a new tool to aid in embryo selection. Previous studies demonstrated the ability to obtain necessary genotypes in the embryo with accuracy equivalent to in adults. When applied to select adult siblings with known type I diabetes status, a reduction in disease incidence of 45–72% compared to random selection was achieved. This study extends analysis to 11,883 sibling pairs to evaluate clinical utility of embryo selection with PGT-P. Results demonstrate simultaneous relative risk reduction of all diseases tested in parallel, which included diabetes, cancer, and heart disease, and indicate applicability beyond patients with a known family history of disease.

The aim of the present study was to assess the risk of primary central nervous system (CNS) tumour incidence in a cohort of 22,377 Mayak Production Association workers chronically exposed to ionising radiation. There were 96 primary CNS tumours, including 42 cases of glioma and 44 cases of meningioma, registered during the whole follow-up period (1948–2018). The study demonstrated that the risk of primary CNS tumour incidence was associated with sex, attained age, calendar period, tall body height, age at the beginning of exposure, and facility type. There was no association found between risk of CNS tumour incidence and body mass index, smoking (males) and alcohol consumption status. The study did not find an effect of the total external gamma radiation dose absorbed in the brain on risk of CNS tumour incidence irrespective of whether an adjustment for the total external neutron dose absorbed in the brain was included or not. Excess relative risk per 1 Gy of external gamma brain dose was 0.05 (95% confidence interval (CI) −0.30; 0.70) for all CNS tumours, −0.18 (95% CI –; 0.44) for gliomas, and 0.38 (95% CI −0.32; 2.08) for meningiomas without adjustment for total neutron brain dose. There was no effect modification by sex, attained age, age at hire or facility.

Doc number: 14 Abstract Background: Relative risk is a summary metric that is commonly used in epidemiological investigations. Increasingly, epidemiologists are using log-binomial models to study the impact of a set of predictor variables on a single binary outcome, as they naturally offer relative risks. However, standard statistical software may report failed convergence when attempting to fit log-binomial models in certain settings. The methods that have been proposed in the literature for dealing with failed convergence use approximate solutions to avoid the issue. This research looks directly at the log-likelihood function for the simplest log-binomial model where failed convergence has been observed, a model with a single linear predictor with three levels. The possible causes of failed convergence are explored and potential solutions are presented for some cases. Results: Among the principal causes is a failure of the fitting algorithm to converge despite the log-likelihood function having a single finite maximum. Despite these limitations, log-binomial models are a viable option for epidemiologists wishing to describe the relationship between a set of predictors and a binary outcome where relative risk is the desired summary measure. Conclusions: Epidemiologists are encouraged to continue to use log-binomial models and advocate for improvements to the fitting algorithms to promote the widespread use of log-binomial models.

Background and aims: Elicitation of an innate immune response to bacterial products is mediated through pattern recognition receptors (PRRs) such as the toll-like receptors (TLRs) and the NODs. The recently characterised Asp299Gly polymorphism in the lipopolysaccharide (LPS) receptor TLR4 is associated with impaired LPS signalling and increased susceptibility to Gram negative infections. We sought to determine whether this polymorphism was associated with Crohn’s disease (CD) and/or ulcerative colitis (UC). Methods: Allele frequencies of the TLR4 Asp299Gly polymorphism and the three NOD2/CARD15 polymorphisms (Arg702Trp, Gly908Arg, and Leu1007fsinsC) were assessed in two independent cohorts of CD patients (cohort 1, n = 334; cohort 2, n = 114), in 163 UC patients, and in 140 controls. A transmission disequilibrium test (TDT) was then performed on 318 inflammatory bowel disease (IBD) trios. Results: The allele frequency of the TLR4 Asp299Gly polymorphism was significantly higher in CD (cohort 1: 11% v 5%, odds ratio (OR) 2.31 (95% confidence interval (CI) 1.28–4.17), p = 0.004; and cohort 2: 12% v 5%, OR 2.45 (95% CI 1.24–4.81), p = 0.007) and UC patients (10% v 5%, OR 2.05 (95% CI 1.07–3.93), p = 0.027) compared with the control population. A TDT on 318 IBD trios demonstrated preferential transmission of the TLR4 Asp299Gly polymorphism from heterozygous parents to affected children (T/U: 68/34, p = 0.01). Carrying polymorphisms in both TLR4 and NOD2 was associated with a genotype relative risk (RR) of 4.7 compared with a RR of 2.6 and 2.5 for TLR4 and NOD2 variants separately. Conclusion: We have reported on a novel association of the TLR4 Asp299Gly polymorphism with both CD and UC. This finding further supports the genetic influence of PRRs in triggering IBD.

Background and ObjectivesPatients undergoing breast cancer surgery frequently experience chronic postoperative pain. The primary objective of this randomized study was to determine if thoracic paravertebral block (TPVB) reduced the incidence of chronic pain after a modified radical mastectomy (MRM) when compared with general anesthesia (GA).MethodsOne hundred eighty women undergoing MRM were randomized to 1 of 3 study groups: group 1: standardized GA, group 2: GA with a single-injection TPVB and placebo paravertebral infusion, and group 3: GA with a continuous TPVB. Outcomes assessed postoperatively included acute postoperative pain and analgesic consumption and, at 3 and 6 months, the incidence and severity of chronic pain and physical and mental health-related quality of life (HRQOL).ResultsThere was no significant difference in the incidence of chronic pain at 3 months (P = 0.13) and 6 months (P = 0.79) after the MRM between the study groups. The relative risk of developing chronic pain (P = 0.25) was also similar between the groups. There was no difference in acute pain (P = 0.22) or postoperative analgesic consumption (P = 0.67) between the groups. Nevertheless, differences were observed in chronic pain–related secondary outcome variables. The TPVB groups reported lower chronic pain scores (P < 0.05), exhibited fewer symptoms and signs of chronic pain (P ⩽ 0.01), and also experienced better physical and mental HRQOL than did the GA group. Chronic pain scores also decreased with time in all study groups (P < 0.05).ConclusionsThere is no significant difference in the incidence or relative risk of chronic pain at 3 and 6 months after an MRM when TPVB is used in conjunction with GA. Nevertheless, patients who receive a TPVB report less severe chronic pain, exhibit fewer symptoms and signs of chronic pain, and also experience better physical and mental HRQOL.

According to the World Health Organization (WHO), in 2016, 91% of the global population was living in places where guidelines on air quality were not met, which results in an estimated figure of seven million deaths annually. The new Brazilian air quality standards, CONAMA 491/2018, was the first revision in over two decades and has as final target the WHO guidelines for air quality, although no deadline has been established for implementation. The goal of this work was to quantify public health gains of this new policy based on hospitalizations due to respiratory diseases, the most studied outcome in Brazilian time series studies, in four Brazilian Southeast capitals: São Paulo (SP), Rio de Janeiro (RJ), Belo Horizonte (MG), and Vitória (ES) for PM 10 , PM 2,5 , SO 2 , CO, and O 3 . Population and hospitalizations data for all respiratory diseases for people under 5 years old, over 64 years old, most vulnerable populations, and all ages were analyzed. The air quality monitoring data was analyzed in two different periods: 2016 to 2018 for São Paulo and Vitória; and between 2015 and 2017 for Belo Horizonte and Rio de Janeiro, according to available monitoring data. A literature review was carried out to determine the appropriate relative risk to be used in the estimations, and the public health gains were calculated based on the selected relative risks for each city. The highest estimate was for São Paulo, with 3454 avoidable respiratory hospital admissions (all ages). In total, the four cities accounted for 4148 avoidable hospitalizations, which was associated to $1.1 million public health gains. Results considering the day of exposure (lag 0) were superior to those with the 5-day moving average (lag 5). The results highlighted the importance of adopting more restrictive standards and called for public policies, the necessity of expanding the air quality monitoring network, mapping emission sources, and improve the knowledge about the interaction between air pollution and health outcomes beyond respiratory disease for the region.

Given the limitations of current approaches for disease relative risk mapping, it is necessary to develop a comprehensive mapping method not only to simultaneously downscale various epidemiologic indicators, but also to be suitable for different disease outcomes. We proposed a three-step progressive statistical method, named disease relative risk downscaling (DRRD) model, to localize different spatial epidemiologic relative risk indicators for disease mapping, and applied it to the real world hand, foot, and mouth disease (HFMD) occurrence data over Mainland China. First, to generate a spatially complete crude risk map for disease binary variable, we employed ordinary and spatial logistic regression models under Bayesian hierarchical modeling framework to estimate county-level HFMD occurrence probabilities. Cross-validation showed that spatial logistic regression (average prediction accuracy: 80.68%) outperformed ordinary logistic regression (69.75%), indicating the effectiveness of incorporating spatial autocorrelation effect in modeling. Second, for the sake of designing a suitable spatial case–control study, we took spatial stratified heterogeneity impact expressed as Chinese seven geographical divisions into consideration. Third, for generating different types of disease relative risk maps, we proposed local-scale formulas for calculating three spatial epidemiologic indicators, i.e., spatial odds ratio, spatial risk ratio, and spatial attributable risk. The immediate achievement of this study is constructing a series of national disease relative risk maps for China’s county-level HFMD interventions. The new DRRD model provides a more convenient and easily extended way for assessing local-scale relative risks in spatial and environmental epidemiology, as well as broader risk assessment sciences.