The Australian journal of rural health · 2026
Mapping the Aggregated Behavioural Risk Factors for Colorectal Cancer by Small Areas Across Australia.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Goodwin Belinda C, Myers Larry S, Perry Nicole, Cameron Jessica K, Baade Peter, Browne Matthew, Murawski Beatrice, Collins Louisa G
Аннотация
OBJECTIVE: Disparities in colorectal cancer exist for incidence and survival in disadvantaged and rural areas. This study created a composite indicator of multiple modifiable risk factors for colorectal cancer to visualise relative prevalence across Australia at the small-area level and by socio-economic status.
DESIGN: Cross-sectional ecological analysis.
SETTING: The Australian 2020-2021 National Health Survey.
PARTICIPANTS: 9796 participants sampled from the Australian adult population (18 years +), living in 2350 small areas.
METHODS: Data on the prevalence of smoking, alcohol consumption, body mass index, and physical activity were used to generate colorectal cancer risk index scores. Index scores were calculated for each person, and mean scores were created for each small area using Bayesian spatial modelling. Index scores were compared across area-level socio-economic quintiles and geographical remoteness subgroups.
RESULTS: Although limited data was available in remote areas, observed patterns indicated that locations outside of major cities tended to have moderate-to-high index scores (mean 0.44, SD 0.25), while major cities showed higher proportions of areas with lower but more variable scores overall (mean 0.34 SD 0.21). Risk scores were higher in disadvantaged areas (0.39, SD 0.21) than advantaged areas (0.33. SD 0.21). This trend was consistent across education, occupation, and economic resources indices.
CONCLUSION: People living further away from major cities and in socioeconomically disadvantaged areas may be more likely to have multiple modifiable health behaviours for colorectal cancer. When applied to a geographically representative dataset, the Index may be used to inform targeted health promotion interventions and localised community-based actions to reduce colorectal cancer risk and close the socio-economic and geographical gaps in incidence and mortality.
DESIGN: Cross-sectional ecological analysis.
SETTING: The Australian 2020-2021 National Health Survey.
PARTICIPANTS: 9796 participants sampled from the Australian adult population (18 years +), living in 2350 small areas.
METHODS: Data on the prevalence of smoking, alcohol consumption, body mass index, and physical activity were used to generate colorectal cancer risk index scores. Index scores were calculated for each person, and mean scores were created for each small area using Bayesian spatial modelling. Index scores were compared across area-level socio-economic quintiles and geographical remoteness subgroups.
RESULTS: Although limited data was available in remote areas, observed patterns indicated that locations outside of major cities tended to have moderate-to-high index scores (mean 0.44, SD 0.25), while major cities showed higher proportions of areas with lower but more variable scores overall (mean 0.34 SD 0.21). Risk scores were higher in disadvantaged areas (0.39, SD 0.21) than advantaged areas (0.33. SD 0.21). This trend was consistent across education, occupation, and economic resources indices.
CONCLUSION: People living further away from major cities and in socioeconomically disadvantaged areas may be more likely to have multiple modifiable health behaviours for colorectal cancer. When applied to a geographically representative dataset, the Index may be used to inform targeted health promotion interventions and localised community-based actions to reduce colorectal cancer risk and close the socio-economic and geographical gaps in incidence and mortality.