Impacts of major health conditions affecting the Australian sheepmeat value chain: a review.

Major health conditions in sheep contribute to substantial economic losses throughout the sheepmeat supply chain in Australia. A systematic review was undertaken to explore the measurable impact of six conditions: arthritis, sheep measles, pleurisy, pneumonia, grass seeds and rib fractures, on the production of lamb and mutton across the meat value chain. Peer-reviewed scientific literature from three databases and non-peer-reviewed articles and reports from Australian government and non-government websites were searched between 11 and 17 November 2019. Original articles, including studies conducted in Australia and New Zealand, that had measurable impacts on conditions of interest were included. The search yielded 16 articles and reports and were classified as producer impact and/or processor impact studies. Mortalities were quantified for pneumonia and arthritis, with pneumonia having the highest impact for producers. Grass seed infestation resulted in the highest impact on carcase and liveweight losses compared to arthritis and pneumonia. Arthritis had the highest trim weight losses for both lamb and mutton and the highest rate of carcase condemnation. Grass seed was the only condition where other impacts on the processor (chain speed and staff relocation to the boning room) were quantified. Although quantifiable production and processing losses were available for some conditions, this review has highlighted that limited quantifiable data based on scientifically sound research were not available for other conditions. The evidence for some conditions found in this review can be used to target future research activities and to further assist producers in making informed management decisions on prevention and control.

Population levels of wellbeing and the association with social capital.

BACKGROUND: This research investigates wellbeing at the population level across demographic, social and health indicators and assesses the association between wellbeing and social capital. METHOD: Data from a South Australian monthly chronic disease/risk factor surveillance system of randomly selected adults (mean age 48.7 years; range 16-99) from 2014/5 (n = 5551) were used. Univariable analyses compared wellbeing/social capital indicators, socio-demographic, risk factors and chronic conditions. Multi-nominal logistic regression modelling, adjusting for multiple covariates was used to simultaneously estimate odds ratios for good wellbeing (reference category) versus neither good nor poor, and good wellbeing versus poor wellbeing. RESULTS: 48.6% were male, mean age 48.7 (sd 18.3), 54.3% scored well on all four of the wellbeing indicators, and positive social capital indicators ranged from 93.1% for safety to 50.8% for control over decisions. The higher level of social capital corresponded with the good wellbeing category. Modeling showed higher odds ratios for all social capital variables for the lowest level of wellbeing. These higher odds ratios remained after adjusting for confounders. CONCLUSIONS: The relationship between wellbeing, resilience and social capital highlights areas for increased policy focus.

Chronic breathlessness associated with poorer physical and mental health-related quality of life (SF-12) across all adult age groups.

Little is known about the impact of chronic breathlessness (modified Medical Research Council (mMRC) score ≥2 for most days, at least three of the last six months) on health-related quality of life (Short Form-12 (SF-12)). 3005 adults from randomly selected households were interviewed face-to-face in South Australia. mMRC ≥2 community prevalence was 2.9%. Adjusted analyses showed clinically meaningful and statistically significant decrements of physical and mental components of SF-12 (mean SF-12 summary scores in physical (-13.0 (-16.0 to -10.2)) and mental (-10.7 (-13.7 to -7.8)) components compared with people with mMRC=0) as chronic breathlessness severity increased, across five age groupings.

Feeling angry about current health status: using a population survey to determine the association with demographic, health and social factors.

BACKGROUND: Feeling angry about their health status may influence disease progression in individuals, creating a greater burden on the health care system. Identifying associations between different variables and feeling angry about health status may assist health professionals to improve health outcomes. This study used path analysis to explore findings from a population-based survey, informed by qualitative descriptions obtained from focus groups, to determine the prevalence of health-related anger within the community and variables associated with reporting health-related anger. METHODS: A population-based Computer Assisted Telephone Interview (CATI) survey of 3003 randomly selected adults Australia-wide was conducted to examine the prevalence of health-related anger. A wide range of other covariates were included in the survey. Multivariable logistic regression and path analysis were undertaken to identify the relationships between different variables associated with feeling angry about the health status of people, to explore the direction of these associations and as a consequence of the results, consider implications for health service use and delivery. RESULTS: Overall, 18.5 % of the population reported feeling angry about their health "some of the time", "most of the time" or "all of the time". People who felt angry about their health were more likely to have a severe health condition, at least one chronic condition, high psychological distress, fair to poor health status, and needed to adjust their daily lives because of a health condition. Having a tertiary level education was protective. Receiving some form of social support, usually from a support group, and not always doing as advised by a doctor, were also associated with a higher likelihood of being angry about their health. CONCLUSIONS: People living with significant health problems are more likely to feel angry about their health. The path between illness and anger is, however, complex. Further research is needed to understand the extent that feeling angry influences the progression of health problems and, if necessary, how to minimise this progression. What also needs examining is whether identifying people who feel angry in the general population could be a predictor of persons most likely to develop significant health problems.

Psychological factors and asthma quality of life: a population based study.

BACKGROUND: Reports of psychological conditions in asthmatic subjects have been limited to certain population groups or convenience samples. A study was undertaken of the prevalence of psychological distress in asthma in the general population and its associations with quality of life. METHODS: The WANTS Health and Well-being Survey is a population household interview survey of adults (age > or =18) in Western Australia, the Northern Territory, and South Australia. Data obtained were weighted to the closest census data to provide population representative estimates. Positive answers to two questions: "Have you ever been told by a doctor that you have asthma?" and "Do you still have asthma?" determined current doctor-diagnosed asthma. Other items included the SF-12, the Kessler-10 index of psychological distress, questions on feelings of lack of control in different areas of life, and on mental health conditions. RESULTS: From the available sample of 10 080, 7619 interviews were completed (participation rate 74.8%), with 834 people reporting current doctor-diagnosed asthma (11.2%). Psychological distress was more frequent in those with asthma (17.9% v 12.2%, p<0.01) and a higher proportion with asthma were at higher risk for anxiety or depression (40.5% v 31.2%, p<0.01). Mental health conditions were also more common (16.2% v 10.8%, p<0.01), as was the frequency of those who sometimes or always felt a lack of control over their health (33.5% v 24.3%, p<0.01). People with both asthma and psychological distress had significantly lower scores on the SF-12 physical component summary (PCS) than those with either asthma or distress alone. Among those with psychological distress, mental component summary (MCS) scores did not differ between asthmatic and non-asthmatic respondents. In a multiple regression model the frequency of a feeling of lack of control over health-together with age, family's financial situation, education level, and number of days partially unable to work or perform usual duties-was significantly associated with scores on the PCS (r = 0.73, adjusted r2 = 0.54). CONCLUSION: These results, from a representative population sample, show that psychological distress and decreased feelings of control are common in asthma and are significantly associated with physical health status.

Underdiagnosed asthma in South Australia.

BACKGROUND: The prevalence of undiagnosed asthma in the general population and the clinical and demographic characteristics of these patients compared with those with diagnosed asthma are unclear. METHODS: The North West Adelaide Health Survey (NWAHS) is a population household interview survey of adults (age>18 years) in the north western suburbs of Adelaide, South Australia (regional population 0.6 million). Data obtained were weighted to the closest census data to provide population representative estimates. Positive answers to: "Have you ever had asthma?"; "Has it been confirmed by a doctor?"; "Do you still have asthma?" determined current physician diagnosed asthma. A positive bronchodilator response on spirometric testing according to ATS criteria without a physician's diagnosis determined undiagnosed asthma. Other measures included the SF-12 health survey questionnaire, the Selim index of severity of chronic lung disease, skin allergy tests, and demographic data. RESULTS: Of the 3422 individuals interviewed, 2523 (74%) agreed to participate in the clinical assessment. Of these, 292 (11.6%) had asthma, 236 (9.3%) with a doctor's diagnosis of asthma and 56 (2.3%) with undiagnosed asthma defined on spirometric criteria; thus, 19.2% of the total asthma group were undiagnosed. Those undiagnosed were more likely (p<0.05) to be >40 years old, on government benefits, with an income 65 years. Health service use over the previous year was similar for both asthma groups. CONCLUSION: Undiagnosed asthma is common among the Australian population, with a similar clinical spectrum to those with diagnosed asthma.

Mental health status of the South Australian population.

OBJECTIVE: To determine, by the use of a telephone survey, the mental health status of SA adults (18+ years) using the GHQ-28, SF-12 and self-report as indicators of mental health, and to examine risk factors for mental health morbidity. SAMPLE: A random representative sample of South Australian adults selected from the Electronic White Pages. Overall, 2,501 interviews were conducted (74.0% response rate). RESULTS: Overall, 19.5% of respondents had a mental health problem as determined by the GHQ-28, 11.8% as determined by the mental health component summary score of the SF-12 and 11.9% self-reported a mental health condition. The percentage of people with a mental health problem who had used a psychologist or a psychiatrist in the previous 12 months was 9.6% for people diagnosed by the GHQ-28, 16.2% by SF-12 and 23.7% for self-report. The logistic regression analyses undertaken to describe people with a mental health problem as determined by the GHQ-28 and to describe people who visited a psychologist or psychiatrist produced different age categories, demographic and co-morbidity indicators. Variables found in both analyses included living in the metropolitan area, being economically inactive and being a high user of health services. CONCLUSIONS: One in five South Australian adults has a mental problem. Although the prevalence is higher for younger age groups, older adults are more likely to visit a psychologist or a psychiatrist. IMPLICATIONS: Telephone interviewing produces robust indicators of the prevalence of mental health problems and is a cost-effective way of identifying prevalence estimates or tracking changes over time.

Suicidal ideation in a random community sample: attributable risk due to depression and psychosocial and traumatic events.

OBJECTIVE: To determine the attributable risk for suicidal ideation of depression and psychosocial and traumatic events in a random and representative population. METHOD: Data were gathered from a random and representative sample of 2501 South Australians. Suicidal ideation and clinical depression were determined by the general health questionnaire (GHQ-28) and the short-form health survey (SF-12) respectively, and information regarding psychosocial stressors and traumatic events was collated. These data were subjected to univariate and multivariate analyses to determine the population-attributable risks for suicidal ideation. RESULTS: Overall, 5.6% of men and 5.3% of women had suicidal ideation. Univariate analyses demonstrated a significant attributable risk for suicidal ideation for depression and the majority of the psychosocial and traumatic events. Multivariate analysis demonstrated that clinical depression remained significantly associated with suicidal ideation, with a population-attributable risk of 46.9%. Because of the small number of people in the population who experience both suicidal ideation and specific events, multivariate analysis could not be applied to individual events. However, even when the psychosocial events were summed, they no longer remained significantly associated with suicidal ideation, whereas the summation of traumatic events remained significant, with a population-attributable risk of 38.0%. CONCLUSIONS: These results confirm the importance of traumatic events as significant factors in contributing to suicidal ideation. However, of even greater importance is that they indicate, unequivocally, the magnitude of the contribution of clinical depression to suicidal ideation, with the population-attributable risk of depression indicating that elimination of mood disorders would reduce suicidal ideation by up to 46.9%.

Reliability of self-reported behavioural health risk factors in a South Australian telephone survey.

OBJECTIVE: To test the reliability of telephone health survey questions. METHOD: A telephone survey on mental health of South Australians in 1997 was re-administered to a random sub-sample of 102 respondents between 32 and 79 days after the original survey. RESULTS: Demographic questions (age, gender, number of adults and children in the household) showed the highest reproducibility and were almost perfect. Questions regarding health risk factors, such as smoking and drinking behaviour, showed substantial to almost perfect agreement. Co-morbidity variables were substantially reproducible where prevalence estimates were not close to zero. CONCLUSIONS: The results were comparable to findings from similar studies associated with the Behavioral Risk Factor Surveillance System (BRFSS) in the United States. The study suggests that the telephone health survey instrument used in South Australia is reliable for estimating health conditions and behaviours in the population.

Random digit dialling and Electronic White Pages samples compared: demographic profiles and health estimates.

OBJECTIVE: To compare the methodologies of and health estimates derived from two telephone household survey methods. In particular, to establish if White Pages telephone listings provide a relatively unbiased sampling frame for population health surveys. METHOD: In South Australia in 1998, a health survey questionnaire was administered by telephone to two randomly selected population samples. The first method used EWP (Electronic White Pages, n = 6,012), which contains all listed residential telephone numbers as the sampling frame. The results were compared to a RDD (random digit dialling, n = 3,080) sample where all listed and unlisted telephone numbers were included in the sampling frame. Demographic variables and health estimates were compared between the surveys, and then compared to a 'gold standard' door-to-door household survey conducted concurrently. RESULTS: The response rate for EWP (83.8%) exceeded that of RDD (65.4%). More than four times as many calls were required per completed interview in RDD. Demographic profiles and health estimates were substantially similar. CONCLUSIONS: EWP requires fewer telephone calls and enables approach letters establishing the bona fides of the survey to be sent to each selected address before calling, increasing the response rate. RDD is a more inclusive sampling frame but also includes non-connected and business numbers, and offers no significant advantages in providing health estimates. IMPLICATIONS: There are substantial methodological and cost advantages in using EWP over RDD as the sampling, frame for population health surveys, without introducing significant bias into health estimates.