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Purpose: It has been argued that rare diseases should be recognized as a public health priority. However, there is a shortage of epidemiological data describing the true burden of rare diseases. This study investigated hospital service use to provide a better understanding of the collective health and economic impacts of rare diseases. Methods: Novel methodology was developed using a carefully constructed set of diagnostic codes, a selection of rare disease cohorts from hospital administrative data, and advanced data--linkage technologies. Outcomes included health-service use and hospital admission costs. Results: In 2010, cohort members who were alive represented approximately 2.0% of the Western Australian population. The cohort accounted for 4.6% of people discharged from hospital and 9.9% of hospital discharges, and it had a greater average length of stay than the general population. The total cost of hospital discharges for the cohort represented 10.5% of 2010 state inpatient hospital costs. Conclusions: This population-based cohort study provides strong new evidence of a marked disparity between the proportion of the population with rare diseases and their combined health-system costs. The methodology will inform future rare-disease studies, and the evidence will guide government strategies for managing the service needs of people living with rare diseases.

Cancer will continue to be a leading cause of ill health and death unless we can capitalize on the potential for 30-40% of these cancers to be prevented. In this light, cancer prevention represents an enormous opportunity for public health, potentially saving much of the pain, anguish, and cost associated with treating cancer. However, there is a challenge for governments, and the wider community, in prioritizing cancer prevention activities, especially given increasing financial constraints. This paper describes a method for identifying cancer prevention priorities. This method synthesizes detailed cancer statistics, expert opinion, and the published literature for the priority setting process. The process contains four steps: assessing the impact of cancer types; identifying cancers with the greatest impact; considering opportunities for prevention; and combining information on impact and preventability. The strength of our approach is that it is straightforward, transparent and reproducible for other settings. Applying this method in Western Australia produced a priority list of seven adult cancers which were identified as having not only the biggest impact on the community but also the best opportunities for prevention. Work conducted in an additional project phase went on to present data on these priority cancers to a public consultation and develop an agenda for action in cancer prevention.

PURPOSE: It has been argued that rare diseases should be recognized as a public health priority. However, there is a shortage of epidemiological data describing the true burden of rare diseases. This study investigated hospital service use to provide a better understanding of the collective health and economic impacts of rare diseases. METHODS: Novel methodology was developed using a carefully constructed set of diagnostic codes, a selection of rare disease cohorts from hospital administrative data, and advanced data-linkage technologies. Outcomes included health-service use and hospital admission costs. RESULTS: In 2010, cohort members who were alive represented approximately 2.0% of the Western Australian population. The cohort accounted for 4.6% of people discharged from hospital and 9.9% of hospital discharges, and it had a greater average length of stay than the general population. The total cost of hospital discharges for the cohort represented 10.5% of 2010 state inpatient hospital costs. CONCLUSIONS: This population-based cohort study provides strong new evidence of a marked disparity between the proportion of the population with rare diseases and their combined health-system costs. The methodology will inform future rare-disease studies, and the evidence will guide government strategies for managing the service needs of people living with rare diseases.Genet Med advance online publication 22 September 2016Genetics in Medicine (2016); doi:10.1038/gim.2016.143.

BACKGROUND: Attributions of causality are common for many diseases, including breast cancer. The risk of developing breast cancer can be reduced by modifications to lifestyle and behaviours to minimise exposure to specific risk factors, such as obesity. However, these modifications will only occur if women believe that certain behaviours/lifestyle factors have an impact on the development of breast cancer. METHOD: The Breast Cancer, Environment and Employment Study is a case-control study of breast cancer conducted in Western Australia between 2009 and 2011. As part of the study 1109 women with breast cancer and 1633 women without the disease completed a Risk Perception Questionnaire in which they were asked in an open-ended question for specific cause/s to the development of breast cancer in themselves or in others. The study identified specific causal beliefs, and assessed differences in the beliefs between women with and without breast cancer. RESULTS: The most common attributions in women without breast cancer were to familial or inherited factors (77.6%), followed by lifestyle factors, such as poor diet and smoking (47.1%), and environmental factors, such as food additives (45.4%). The most common attributions in women with breast cancer were to mental or emotional factors (46.3%), especially stress, followed by lifestyle factors (38.6%) and physiological factors (37.5%), particularly relating to hormonal history. CONCLUSIONS: While the majority of participants in this study provided one or more causal attributions for breast cancer, many of the reported risk factors do not correspond to those generally accepted by the scientific community. These misperceptions could be having a significant impact on the success of prevention and early detection programs that seek to minimise the pain and suffering caused by this disease. In particular, women who have no family history of the disease may not work to minimise their exposure to the modifiable risk factors.

Background: Attributions of causality are common for many diseases, including breast cancer. The risk of developing breast cancer can be reduced by modifications to lifestyle and behaviours to minimise exposure to specific risk factors, such as obesity. However, these modifications will only occur if women believe that certain behaviours/lifestyle factors have an impact on the development of breast cancer. Method: The Breast Cancer, Environment and Employment Study is a case-control study of breast cancer conducted in Western Australia between 2009 and 2011. As part of the study 1109 women with breast cancer and 1633 women without the disease completed a Risk Perception questionnaire in which they were asked in an open-ended question for specific cause/s to the development of breast cancer in themselves or in others. The study identified specific causal beliefs, and assessed differences in the beliefs between women with and without breast cancer. Results: The most common attributions in women without breast cancer were to familial or inherited factors (77.6%), followed by lifestyle factors, such as poor diet and smoking (47.1%), and environmental factors, such as food additives (45.4%). The most common attributions in women with breast cancer were to mental or emotional factors (46.3%), especially stress, followed by lifestyle factors (38.6%) and physiological factors (37.5%), particularly relating to hormonal history.Conclusions: While the majority of participants in this study provided one or more causal attributions for breast cancer, many of the reported risk factors do not correspond to those generally accepted by the scientific community. These misperceptions could be having a significant impact on the success of prevention and early detection programs that seek to minimise the pain and suffering caused by this disease. In particular, women who have no family history of the disease may not work to minimise their exposure to the modifiable risk factors.

Background: Research on the possible association between shiftwork and breast cancer is complicated because there are many different shiftwork factors, which might be involved including: light at night, phase shift, sleep disruption and changes in lifestyle factors while on shiftwork (diet, physical activity, alcohol intake and low sun exposure). Methods: We conducted a population-based case-control study in Western Australia from 2009 to 2011 with 1205 incident breast cancer cases and 1789 frequency age-matched controls. A self-administered questionnaire was used to collect demographic, reproductive, and lifestyle factors and lifetime occupational history and a telephone interview was used to obtain further details about the shiftwork factors listed above. Results: A small increase in risk was suggested for those ever doing the graveyard shift (work between midnight and 0500 hours) and breast cancer (odds ratio (OR) 1.16, 95% confidence interval (CI) = 0.97-1.39). For phase shift, we found a 22% increase in breast cancer risk (OR 1.22, 95% CI = 1.01-1.47) with a statistically significant dose-response relationship (P = 0.04). For the other shiftwork factors, risks were marginally elevated and not statistically significant. Conclusion: We found some evidence that some of the factors involved in shiftwork may be associated with breast cancer but the ORs were low and there were inconsistencies in duration and dose-response relationships.

BACKGROUND: Research on the possible association between shiftwork and breast cancer is complicated because there are many different shiftwork factors, which might be involved including: light at night, phase shift, sleep disruption and changes in lifestyle factors while on shiftwork (diet, physical activity, alcohol intake and low sun exposure). METHODS: We conducted a population-based case-control study in Western Australia from 2009 to 2011 with 1205 incident breast cancer cases and 1789 frequency age-matched controls. A self-administered questionnaire was used to collect demographic, reproductive, and lifestyle factors and lifetime occupational history and a telephone interview was used to obtain further details about the shiftwork factors listed above. RESULTS: A small increase in risk was suggested for those ever doing the graveyard shift (work between midnight and 0500 hours) and breast cancer (odds ratio (OR)=1.16, 95% confidence interval (CI)=0.97-1.39). For phase shift, we found a 22% increase in breast cancer risk (OR=1.22, 95% CI=1.01-1.47) with a statistically significant dose-response relationship (P=0.04). For the other shiftwork factors, risks were marginally elevated and not statistically significant. CONCLUSION: We found some evidence that some of the factors involved in shiftwork may be associated with breast cancer but the ORs were low and there were inconsistencies in duration and dose-response relationships.

Breast cancer is one of the most commonly diagnosed invasive cancers. Established risk factors account for only a small proportion of cases. Previous studies have found reductions in sleep duration and quality in the general population over time. There is evidence to suggest a link between poor sleep and an increased risk of breast cancer. In this study, we investigated the relationship between breast cancer and sleep duration and quality in Western Australian women. Data were obtained from a population-based case-control study conducted from 2009 to 2011. Participants completed a self-administered questionnaire that included questions on sleep. Odds ratios and 95% confidence intervals were calculated using unconditional logistic regression. Sensitivity analysis for potential selection and misclassification bias was also conducted. We found no association between self-reported sleep duration on workdays and risk of breast cancer (for <6 hours, odds ratio (OR) = 1.05 (95% CI: 0.82, 1.33); for 6–7 hours, OR = 0.96 (95% CI: 0.80, 1.16); and for >8 hours, OR = 1.10 (95% CI: 0.87, 1.39),compared with the reference category of 7–8 hours’ sleep). In addition, we found no association between sleep duration on nonworkdays, subjective sleep quality, or combined duration and quality and risk of breast cancer. This study does not provide evidence to support an association between self-reported sleep duration or quality and the risk of breast cancer.

Purpose It has been acknowledged by those in the field of sleep epidemiology that the current measures of sleep used in many epidemiological studies do not adequately capture the complexity and variability of sleep. A number of ways to improve the measurement of sleep have been proposed. This study aimed to assess the relationship between novel ‘sleep disturbance’ metrics, as expanded measures of sleep, and breast cancer risk.Methods Data for this study were derived from a population-based case–control study conducted in Western Australia between 2009 and 2011. Participants completed a self-administered questionnaire that included questions about demographic, reproductive, and lifestyle factors in addition to questions on sleep. Four metrics of exposure to sleep disturbance (cumulative, average, duration, and peak)were developed. Unconditional logistic regression was used to examine the association between metrics of sleep disturbance and breast cancer risk.Results There was no evidence to support an association between any of the sleep disturbance metrics and breast cancer risk. Compared with the reference group of unexposed women, the fully adjusted ORs for cumulative sleep disturbance (harm) metric were as follows: 1st tertile 0.90 (95 % CI: 0.72–1.13); OR for the 2nd tertile 1.04 (95 % CI: 0.84–1.29); and OR for the 3rd tertile 1.02 (95 % CI:0.82–1.27).Conclusions This study found no association between several metrics of sleep disturbance and risk of breast cancer. Our experience with developing metrics of sleep disturbance may be of use to others in sleep epidemiology wishing to expand their scope of sleep measurement.

Background: Research on the possible association between shiftwork and breast cancer is complicated because there are many different shiftwork factors, which might be involved including: light at night, phase shift, sleep disruption and changes in lifestyle factors while on shiftwork (diet, physical activity, alcohol intake and low sun exposure).Methods: We conducted a population-based case–control study in Western Australia from 2009 to 2011 with 1205 incident breast cancer cases and 1789 frequency age-matched controls. A self-administered questionnaire was used to collect demographic, reproductive, and lifestyle factors and lifetime occupational history and a telephone interview was used to obtain further details about the shiftwork factors listed above.Results: A small increase in risk was suggested for those ever doing the graveyard shift (work between midnight and 0500 hours) and breast cancer (odds ratio (OR)¼1.16, 95% confidence interval (CI)¼0.97–1.39). For phase shift, we found a 22% increase in breast cancer risk (OR¼1.22, 95% CI¼1.01–1.47) with a statistically significant dose–response relationship (P¼0.04). For the other shiftwork factors, risks were marginally elevated and not statistically significant. Conclusion: We found some evidence that some of the factors involved in shiftwork may be associated with breast cancer but the ORs were low and there were inconsistencies in duration and dose–response relationships.

Background: Self-report remains the most practical and cost-effective method for epidemiologic sleep studies involving large population-based samples. Several validated questionnaires have been developed to assess sleep, but these tools are lengthy to administer and may be impractical for epidemiologic studies. We examined whether a 3-item sleep questionnaire, similar to those typically used in epidemiologic studies, closely corresponded with objective measures of sleep as assessed using actigraphy monitoring. Methods: Eligible participants were Western Australian women aged 18 to 80 years. Participants completed a sleep questionnaire, wore a wrist actigraph for 7 nights, and completed a brief daily sleep log. Objective actigraphy measurements for 56 participants were summarized by mean and mode and compared with the subjective reports, using weighted kappa and delta. Results: Data collected from the questionnaire showed poor agreement with objectively measured sleep, with kappas ranging from −0.19 to 0.14. Conclusions: Our results indicate that sleep questions typically used in epidemiologic studies do not closely correspond with objective measures of sleep as assessed using actigraphy. The findings have implications for studies that have used such sleep questions. A means of appropriately measuring sleep as a risk factor in epidemiologic studies remains to be determined.

Background: The longer-term health impacts of poor sleep quality are of increasing interest, as evidence suggests that there are rising levels of sleep disturbance in the community. Studies have reported links between sleep quality and increased morbidity and mortality. However, the results of these studies are constrained by limitations in the measurement of sleep quality in epidemiologic studies. The Breast Cancer Environment and Employment Study (BCEES) has developed a sleep questionnaire that attempts to address some of the limitations of previous sleep questionnaires. The present study assessed the test-retest reliability of the sleep questionnaire used in the Breast Cancer Environment and Employment Study (BCEES). Methods: Subjects for this reliability study were women who were participating as controls in the BCEES study. Test-retest reliability was evaluated for individual items, using weighted kappa for categorical variables and intraclass correlation coefficients (ICC) and limits of agreement for continuous variables. Results: Most sleep questions showed good agreement, ranging from 0.78 to 0.45. The ICC was 0.45 (95% CI 0.32–0.59) for lifetime sleep loss per year and 0.60 (95% CI 0.49–0.71) for symptom severity. Conclusions: The test-retest reliability of the general sleep questions was good, and future epidemiologic studies of sleep could reliably expand the number of assessed domains of sleep quality. However, reliability decreased as increasing detail was required from participants about specific periods of sleep disturbance, and changes to the questionnaire are warranted.

Objective: Prostate canceris one of the most commonly diagnosed cancers in Western men and one in three Australian men develops the cancer before the age of 75. Currently, only increasing age, race and family history have been well established as risk factors. A growing number of studies have investigated occupation in relation to prostate cancer but, like other risk factors, no associations have been confirmed. Mining employs a significant proportion of the work force in Western Australia. The aims of this study were to describe the characteristics of miners in the Western Australian Prostate Health Study, investigate mining as a risk factor for prostate cancer, conduct a systematic search of the literature for studies that have investigated mining as an occupational risk factor for prostate cancer and compare and contrast their methodologies and results. Methods: Data were obtained from a population-based case control study conducted from 1 January 2001 to 20 August 2002 at The University of Western Australia. Results: After controlling for age, family history and military service in Vietnam, miners had a statistically significantly reduced risk of prostate cancer (adjusted OR 0.35, 95% CI 0.16 to 0.75). The systematic literature search of studies examining mining and prostate cancer found a reasonably consistent trend of a decreased risk of prostate cancer among miners. None of the published articles discussed their results regarding mining and prostate cancer in detail, and a biological mechanism to support these results has not previously been suggested. Conclusion The relationship between mining and prostate cancer deserves further investigation.

Assessing occupational exposure in retrospective community-based case-control studies is difficult as measured exposure data are very seldom available. The expert assessment method is considered the most accurate way to attribute exposure but it is a time consuming and expensive process and may be seen as subjective, nonreproducible, and nontransparent. In this paper, we describe these problems and outline our solutions as operationalized in a web-based software application (OccIDEAS). The novel aspects of OccIDEAS are combining all steps in the assessment into one software package; enmeshing the process of assessment into the development of questionnaires; selecting the exposure(s) of interest; specifying rules for exposure assignment; allowing manual or automatic assessments; ensuring that circumstances in which exposure is possible for an individual are highlighted for review; providing reports to ensure consistency of assessment. Development of this application has the potential to make high-quality occupational assessment more efficient and accessible for epidemiological studies.