Machinery Risk Assessment for Risk Reduction

New avenues are reviewed and discussed for preventing industrial machine-related injury by means of realistic risk evaluation and reduction processes at the design and application stages of machinery development and use. U.S. guidelines and European standards on machinery risk assessment procedures are described. Applications of risk assessment for machine-related injury risk management and teaching machine-risk control are discussed.     

Risk Assessment and Risk Management: An Essential Integration

The integration of Risk Assessment and Risk Management is a necessary step in environmental regulation. The compromises involved in the Risk Management process can not be allowed to violate the scientific integrity of the Risk Assessment. The inclusion of a cost/benefit analysis necessitates the valuation of ecological processes. These values are based on the costs of replacement in volume, in kind, and in place. The Risk Management is then presented as a Rolling Stewardship where Risk Management is balanced with Cash Management.     

Absolute Risk and Loss-of-Lifetime Estimates for Quantitative Risk Assessment

Quantitative risk assessments in public health settings intend to describe the hazard of a specific exposure in a given population on the basis of epidemiological and/or experimental results. Two different risk quantities, the absolute lifetime excess risk and the loss-of-lifetime, which differ in their definition of hazard, are discussed and compared. For both measures estimation procedures are derived and the relationship between the various estimates which are currently in use are investigated. It is shown that the two most common estimators can be written as special cases of a more general concept. This leads to conclusions about the assumptions on which different estimation procedures are implicitly based. For all discussed estimators variance estimates are derived. The analytical results for both risk parameters will be elucidated by an example on lung cancer risk due to residential radon in Germany.     

Korean Risk Assessment Model for Breast Cancer Risk Prediction

Purpose

We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk.

Methods

Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail''s equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort.

Results

The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (p<0.001 and <0.001, respectively). The observed incidence of breast cancer in the two cohorts was similar to the expected incidence from the KoBCRAT (KMCC, p = 0.880; NCC, p = 0.878). The AUC using the KoBCRAT was 0.61 for the KMCC and 0.89 for the NCC cohort.

Conclusions

Our findings suggest that the KoBCRAT is a better tool for predicting the risk of breast cancer in Korean women, especially urban women.     

Body Mass Index Genetic Risk Score and Endometrial Cancer Risk

Genome-wide association studies (GWAS) have identified common variants that predispose individuals to a higher body mass index (BMI), an independent risk factor for endometrial cancer. Composite genotype risk scores (GRS) based on the joint effect of published BMI risk loci were used to explore whether endometrial cancer shares a genetic background with obesity. Genotype and risk factor data were available on 3,376 endometrial cancer case and 3,867 control participants of European ancestry from the Epidemiology of Endometrial Cancer Consortium GWAS. A BMI GRS was calculated by summing the number of BMI risk alleles at 97 independent loci. For exploratory analyses, additional GRSs were based on subsets of risk loci within putative etiologic BMI pathways. The BMI GRS was statistically significantly associated with endometrial cancer risk (P = 0.002). For every 10 BMI risk alleles a woman had a 13% increased endometrial cancer risk (95% CI: 4%, 22%). However, after adjusting for BMI, the BMI GRS was no longer associated with risk (per 10 BMI risk alleles OR = 0.99, 95% CI: 0.91, 1.07; P = 0.78). Heterogeneity by BMI did not reach statistical significance (P = 0.06), and no effect modification was noted by age, GWAS Stage, study design or between studies (P≥0.58). In exploratory analyses, the GRS defined by variants at loci containing monogenic obesity syndrome genes was associated with reduced endometrial cancer risk independent of BMI (per BMI risk allele OR = 0.92, 95% CI: 0.88, 0.96; P = 2.1 x 10⁻⁵). Possessing a large number of BMI risk alleles does not increase endometrial cancer risk above that conferred by excess body weight among women of European descent. Thus, the GRS based on all current established BMI loci does not provide added value independent of BMI. Future studies are required to validate the unexpected observed relation between monogenic obesity syndrome genetic variants and endometrial cancer risk.     

Risk and disease

The way that diseases such as high blood pressure (hypertension), high cholesterol, and diabetes are defined is closely tied to ideas about modifiable risk. In particular, the threshold for diagnosing each of these conditions is set at the level where future risk of disease can be reduced by lowering the relevant parameter (of blood pressure, low-density lipoprotein, or blood glucose, respectively). In this article, I make the case that these criteria, and those for diagnosing and treating other "risk-based diseases," reflect an unfortunate trend towards reclassifying risk as disease. I closely examine stage 1 hypertension and high cholesterol and argue that many patients diagnosed with these "diseases" do not actually have a pathological condition. In addition, though, I argue that the fact that they are risk factors, rather than diseases, does not diminish the importance of treating them, since there is good evidence that such treatment can reduce morbidity and mortality. For both philosophical and ethical reasons, however, the conditions should not be labeled as pathological. The tendency to reclassify risk factors as diseases is an important trend to examine and critique.