Suchergebnisse

Purpose: To present the prevalence of 3 broad categories of mental disorder (anxiety-related, affective and other disorders) by socioeconomic status and examine the associated socioeconomic risk factors of mental disorders in Australia. Design: A population-based, cross-sectional national health survey on mental health and its risk factors across Australia. Setting: National Health Survey (NHS), 2017-2018 conducted by the Australian Bureau of Statistics (ABS) Participants: Under aged: 4,945 persons, Adult: 16,370 persons and total: 21,315 persons Measures: Patient-reported mental disorder outcomes Analysis: Weighted prevalence rates by socioeconomic status (equivalised household income, education qualifications, Socio-Economic Index for Areas (SEIFA) scores, labor force status and industry sector where the adult respondent had their main job) were estimated using cross-tabulation. Logistic regression utilizing subsamples of underage and adult age groups were analyzed to test the association between socioeconomic status and mental disorders. Results: Anxiety-related disorders were the most common type of disorders with a weighted prevalence rate of 20.04% (95% CI: 18.49-21.69) for the poorest, 13.85% (95% CI: 12.48-15.35) for the richest and 16.34% (95% CI: 15.7-17) overall. The weighted prevalence rate for mood/affective disorders were 20.19% (95% CI: 18.63-21.84) for the poorest, 9.96% (95% CI: 8.79-11.27) for the richest, and 13.57% (95% CI: 12.99-14.17) overall. Other mental disorders prevalence were for the poorest: 9.07% (95% CI: 7.91-10.39), the richest: 3.83% (95% CI: 3.14-4.66), and overall: 5.93% (95% CI: 5.53-6.36). These patterns are also reflected if all mental disorders were aggregated with the poorest: 30.97% (95% CI: 29.15-32.86), the richest: 19.59% (95% CI: 18.02-21.26), and overall: 23.93% (95% CI: 23.19-24.69). The underage logistic regression model showed significant lower odds for the middle (AOR: 0.75, 95% CI: 0.53 -1.04, p < 0.1), rich (AOR: 0.71, 95% CI: 0.5-0.99, p < 0.05) and richest (AOR: 0.6, 95% CI: 0.41-0.89, p < 0.01) income groups. Similarly, in the adult logistic model, there were significant lower odds for middle (AOR: 0.84, 95% CI: 0.72-0.98, p < 0.05), rich (AOR: 0.73, 95% CI: 0.62-0.86, p < 0.01) and richest (AOR: 0.76, 95% CI: 0.63-0.91, p < 0.01) income groups. Conclusion: The prevalence of mental disorders in Australia varied significantly across socioeconomic groups. Knowledge of different mental health needs in different socioeconomic groups can assist in framing evidence-based health promotion and improve the targeting of health resource allocation strategies.

AbstractThe aim of this study was to understand the 'farming life' factors that affect the mental health help‐seeking of farmers. Semi‐structured interviews were completed with 10 farmers, 10 farmers' partners, and eight General Practitioners (GPs), covering mental health help‐seeking. Interview data were then analysed using thematic analysis resulting in three themes: Lifestyle and culture, farming priorities, and the challenges of farming. The findings showed that the lifestyle and culture of farming values traits such as stoicism and self‐reliance, which is ingrained in farmers' identities and appears antithetical to mental health help‐seeking. The farming priorities theme highlighted that farmers are time‐poor and believe mental health help‐seeking to be time‐consuming and an interference to their work, which is their primary priority. Lastly, this research revealed that farming challenges, such as financial volatility, increase the need for help, but can also reduce the ability to seek help. Implications of the findings highlight a need to carefully engage with farming cultures more broadly when seeking to support the mental health of the farming community.

Objective: To examine if geographic variations in the participation rates in the National Bowel Cancer Screening Program (NBCSP) are related to population-level socio-demographic characteristics. Methods: Data reflecting participation in the NBCSP for 504 Local Government Areas (LGAs) between July 2011 and June 2013 were extracted from the Social Health Atlas of Australia. Logistic regression models were used to examine independent associations (odds ratios [ORs]) between participation, Remoteness Area (RA) and selected socio-demographic variables. Results: Compared to the participation rate for major cities (33.4%), participation was significantly higher in inner regional areas (36.5%, OR=1.15), but was much lower in remote (27.9%, OR=0.77) or very remote areas (25.0%, OR=0.65). When controlling for study period, gender, proportion of persons aged 65 years and older, Indigenous status, cultural background and socioeconomic status, significantly higher rates were observed in all non-metropolitan areas than in major cities. Indigenous status was strongly related to the poorer participation in remote areas. Conclusions: Socio-demographic characteristics, particularly Indigenous status, cultural background and population ageing, seem to be more important drivers of regional disparities in NBCSP participation than geographic remoteness. Implications for public health: This study provides important evidence to understand the regional disparities in participating in the national screening program.

Objective: To examine if geographic variations in the participation rates in the National Bowel Cancer Screening Program (NBCSP) are related to population-level socio-demographic characteristics. Methods: Data reflecting participation in the NBCSP for 504 Local Government Areas (LGAs) between July 2011 and June 2013 were extracted from the Social Health Atlas of Australia. Logistic regression models were used to examine independent associations (odds ratios [ORs]) between participation, Remoteness Area (RA) and selected socio-demographic variables. Results: Compared to the participation rate for major cities (33.4%), participation was significantly higher in inner regional areas (36.5%, OR=1.15), but was much lower in remote (27.9%, OR=0.77) or very remote areas (25.0%, OR=0.65). When controlling for study period, gender, proportion of persons aged 65 years and older, Indigenous status, cultural background and socioeconomic status, significantly higher rates were observed in all non-metropolitan areas than in major cities. Indigenous status was strongly related to the poorer participation in remote areas. Conclusions: Socio-demographic characteristics, particularly Indigenous status, cultural background and population ageing, seem to be more important drivers of regional disparities in NBCSP participation than geographic remoteness. Implications for public health: This study provides important evidence to understand the regional disparities in participating in the national screening program.