{"title":"A summary of the 2023 Society of Obstetric Medicine of Australia and New Zealand (SOMANZ) hypertension in pregnancy guideline.","authors":"Renuka Shanmugalingam, Angela Makris","doi":"10.5694/mja2.52576","DOIUrl":"https://doi.org/10.5694/mja2.52576","url":null,"abstract":"","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":" ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142895865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A summary of the 2023 Society of Obstetric Medicine of Australia and New Zealand (SOMANZ) hypertension in pregnancy guidelines.","authors":"Cathy Latino, Oyekoya T Ayonrinde","doi":"10.5694/mja2.52575","DOIUrl":"https://doi.org/10.5694/mja2.52575","url":null,"abstract":"","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":" ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142895871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Craig Williams, Christie Byrne, Shannon Evenden, Veronica Soebarto, Stefan Caddy-Retalic, Carmel Williams, Yonatal Tefera, Xiaoqi Feng, Andrew Lowe
{"title":"Urban green space provision: the case for policy-based solutions to support human health.","authors":"Craig Williams, Christie Byrne, Shannon Evenden, Veronica Soebarto, Stefan Caddy-Retalic, Carmel Williams, Yonatal Tefera, Xiaoqi Feng, Andrew Lowe","doi":"10.5694/mja2.52569","DOIUrl":"https://doi.org/10.5694/mja2.52569","url":null,"abstract":"","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":" ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142895889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Genetic counsellors: facilitating the integration of genomics into health care.","authors":"Tatiane Yanes, Eliza Courtney, Mary-Anne Young, Amy Pearn, Aideen McInerney-Leo, Jodie Ingles","doi":"10.5694/mja2.52568","DOIUrl":"https://doi.org/10.5694/mja2.52568","url":null,"abstract":"","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":" ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142864656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Each serum creatinine pathology test result in Australia is routinely returned with a report on the estimated glomerular filtration rate (eGFR). The equation for calculating the eGFR has been updated, and Australian practitioners may be curious to know why this might concern them.</p><p>The eGFR equations were derived from multiple studies that used direct measurements of kidney function with accurate but intensive methods that are generally reserved for research, such as the clearance of the exogenous filtration markers inulin, iothalamate, or iohexol.<span><sup>1</sup></span> The Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)<sub>2009</sub> equations included serum creatinine concentration, age, sex, and race (Black or non-Black) as variables.<span><sup>1</sup></span> A new, race-free equation was developed after concerns in the United States regarding the validity, accuracy, and implications of including a binary or non-binary race component.<span><sup>2</sup></span> In 2021 the CKD-EPI published a newly derived and validated race-free equation (CKD-EPI<sub>2021</sub>), and reported that the new equations produced estimates of measured kidney function that were within the accepted 30% margin of error.<span><sup>3</sup></span> The CKD-EPI confirmed that equations based on creatinine and cystatin concentrations consistently produce more accurate estimates than equations based on creatinine alone. It also reconfirmed the clinical relevance of eGFR, reporting a strong inverse linear association with the risk of kidney failure, adverse cardiovascular events, and death. The association of lower eGFR with adverse event risk is the underlying rationale for risk-based categories in the widely used KDIGO classification of chronic kidney disease.<span><sup>4</sup></span> Using the new equation without a race coefficient is now the recommended standard.<span><sup>5</sup></span></p><p>Practitioners may wonder about the implications of the change for Australia. At the individual level, the difference is mostly a minor, one-off change in eGFR that might only be apparent in people who are being frequently monitored at the time of the equation change. At the population level, even small changes in the calculated eGFR could affect how health systems anticipate and plan for chronic kidney disease (CKD)-associated health care.</p><p>CKD has a large impact on community health and on health budgets. It affects an estimated one in ten Australian adults, and one in five Aboriginal and Torres Strait Islander adults.<span><sup>6</sup></span> The association of CKD with adverse outcomes<span><sup>4</sup></span> is reflected by the prediction that CKD-associated death will be the fifth leading cause of years of lost life globally by 2040.<span><sup>7</sup></span> Even now, it has been estimated that CKD costs the Australian economy $9.9 billion each year.<span><sup>8</sup></span></p><p>How the CKD-EPI<s
{"title":"Re-thinking kidney function: a new approach to kidney function estimation and the identification of chronic kidney disease","authors":"Jessica Dawson, Meg Jardine","doi":"10.5694/mja2.52560","DOIUrl":"10.5694/mja2.52560","url":null,"abstract":"<p>Each serum creatinine pathology test result in Australia is routinely returned with a report on the estimated glomerular filtration rate (eGFR). The equation for calculating the eGFR has been updated, and Australian practitioners may be curious to know why this might concern them.</p><p>The eGFR equations were derived from multiple studies that used direct measurements of kidney function with accurate but intensive methods that are generally reserved for research, such as the clearance of the exogenous filtration markers inulin, iothalamate, or iohexol.<span><sup>1</sup></span> The Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)<sub>2009</sub> equations included serum creatinine concentration, age, sex, and race (Black or non-Black) as variables.<span><sup>1</sup></span> A new, race-free equation was developed after concerns in the United States regarding the validity, accuracy, and implications of including a binary or non-binary race component.<span><sup>2</sup></span> In 2021 the CKD-EPI published a newly derived and validated race-free equation (CKD-EPI<sub>2021</sub>), and reported that the new equations produced estimates of measured kidney function that were within the accepted 30% margin of error.<span><sup>3</sup></span> The CKD-EPI confirmed that equations based on creatinine and cystatin concentrations consistently produce more accurate estimates than equations based on creatinine alone. It also reconfirmed the clinical relevance of eGFR, reporting a strong inverse linear association with the risk of kidney failure, adverse cardiovascular events, and death. The association of lower eGFR with adverse event risk is the underlying rationale for risk-based categories in the widely used KDIGO classification of chronic kidney disease.<span><sup>4</sup></span> Using the new equation without a race coefficient is now the recommended standard.<span><sup>5</sup></span></p><p>Practitioners may wonder about the implications of the change for Australia. At the individual level, the difference is mostly a minor, one-off change in eGFR that might only be apparent in people who are being frequently monitored at the time of the equation change. At the population level, even small changes in the calculated eGFR could affect how health systems anticipate and plan for chronic kidney disease (CKD)-associated health care.</p><p>CKD has a large impact on community health and on health budgets. It affects an estimated one in ten Australian adults, and one in five Aboriginal and Torres Strait Islander adults.<span><sup>6</sup></span> The association of CKD with adverse outcomes<span><sup>4</sup></span> is reflected by the prediction that CKD-associated death will be the fifth leading cause of years of lost life globally by 2040.<span><sup>7</sup></span> Even now, it has been estimated that CKD costs the Australian economy $9.9 billion each year.<span><sup>8</sup></span></p><p>How the CKD-EPI<s","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"222 2","pages":"72-73"},"PeriodicalIF":6.7,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52560","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142854474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objectives: To examine bulk-billing rates and out-of-pocket costs for non-bulk-billed general practitioner services in Australia at the Statistical Area 3 (SA3) level; to assess differences by area-level socio-economic disadvantage and remoteness.
Study design: Retrospective analysis of administrative data (Medicare claims data).
Setting, participants: All Medicare claims for non-referred general practitioner services in Australia during the 2022 calendar year, as recorded in the Person Level Integrated Data Asset (PLIDA).
Main outcome measures: Mean proportions of general practitioner services that were bulk-billed and mean patient out-of-pocket costs for non-bulk-billed general practitioner visits by SA3 region, adjusted for area-level age and sex, both overall and by area-level socio-economic disadvantage (Index of Relative Socioeconomic Disadvantage quintile) and remoteness (simplified Modified Monash Model category).
Results: During 2022, 82% (95% confidence interval [CI], 80-83%) of general practitioner services in Australia were bulk-billed; the mean out-of-pocket cost for non-bulk-billed visits was $43 (95% CI, $42-44). By SA3, mean bulk-billing rates ranged between 46% and 99%, mean out-of-pocket costs for non-bulk-billed general practitioner visit between $16 and $99. Bulk-billing rates were higher in regions in the most socio-economically disadvantaged quintile (86%; 95% CI, 84-88%) than those in the least disadvantaged quintile (73%; 95% CI, 70-76%); the mean rate was not significantly different for remote (86%; 95% CI, 79-92%) and metropolitan areas (81%; 95% CI, 79-83%). Out-of-pocket costs for non-bulk-billed general practitioner services were higher in remote ($56; 95% CI, $46-66) than in metropolitan areas ($43; 95% CI, $42-44), and lower in areas in the most socio-economically disadvantaged quintile ($42; 95% CI, $40-45) than in those in the least disadvantaged quintile ($47; 95% CI, $45-49).
Conclusion: Although most general practitioner services are bulk-billed, out-of-pocket costs for non-bulk-billed services are relatively high, particularly for people in remote and socio-economically disadvantaged areas of Australia.
{"title":"Bulk-billing rates and out-of-pocket costs for general practitioner services in Australia, 2022, by SA3 region: analysis of Medicare claims data.","authors":"Karinna Saxby, Yuting Zhang","doi":"10.5694/mja2.52562","DOIUrl":"https://doi.org/10.5694/mja2.52562","url":null,"abstract":"<p><strong>Objectives: </strong>To examine bulk-billing rates and out-of-pocket costs for non-bulk-billed general practitioner services in Australia at the Statistical Area 3 (SA3) level; to assess differences by area-level socio-economic disadvantage and remoteness.</p><p><strong>Study design: </strong>Retrospective analysis of administrative data (Medicare claims data).</p><p><strong>Setting, participants: </strong>All Medicare claims for non-referred general practitioner services in Australia during the 2022 calendar year, as recorded in the Person Level Integrated Data Asset (PLIDA).</p><p><strong>Main outcome measures: </strong>Mean proportions of general practitioner services that were bulk-billed and mean patient out-of-pocket costs for non-bulk-billed general practitioner visits by SA3 region, adjusted for area-level age and sex, both overall and by area-level socio-economic disadvantage (Index of Relative Socioeconomic Disadvantage quintile) and remoteness (simplified Modified Monash Model category).</p><p><strong>Results: </strong>During 2022, 82% (95% confidence interval [CI], 80-83%) of general practitioner services in Australia were bulk-billed; the mean out-of-pocket cost for non-bulk-billed visits was $43 (95% CI, $42-44). By SA3, mean bulk-billing rates ranged between 46% and 99%, mean out-of-pocket costs for non-bulk-billed general practitioner visit between $16 and $99. Bulk-billing rates were higher in regions in the most socio-economically disadvantaged quintile (86%; 95% CI, 84-88%) than those in the least disadvantaged quintile (73%; 95% CI, 70-76%); the mean rate was not significantly different for remote (86%; 95% CI, 79-92%) and metropolitan areas (81%; 95% CI, 79-83%). Out-of-pocket costs for non-bulk-billed general practitioner services were higher in remote ($56; 95% CI, $46-66) than in metropolitan areas ($43; 95% CI, $42-44), and lower in areas in the most socio-economically disadvantaged quintile ($42; 95% CI, $40-45) than in those in the least disadvantaged quintile ($47; 95% CI, $45-49).</p><p><strong>Conclusion: </strong>Although most general practitioner services are bulk-billed, out-of-pocket costs for non-bulk-billed services are relatively high, particularly for people in remote and socio-economically disadvantaged areas of Australia.</p>","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":" ","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142837190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elisa K Bongetti, Rory Wolfe, James B Wetmore, Anne M Murray, Robyn L Woods, Michelle A Fravel, Mark R Nelson, Nigel P Stocks, Suzanne G Orchard, Kevan R Polkinghorne
<div> <section> <h3> Objectives</h3> <p>To assess the clinical impact on generally healthy older Australians of changing from the 2009 CKD-EPI (CKD-EPI<sub>2009</sub>) to the 2021 CKD-EPI (CKD-EPI<sub>2021</sub>) equation for calculating the estimated glomerular filtration rate (eGFR).</p> </section> <section> <h3> Study design</h3> <p>Secondary analysis of data from the prospective ASPirin in Reducing events in the Elderly (ASPREE) cohort study.</p> </section> <section> <h3> Setting, participants</h3> <p>Australians aged 70 years or older living in the community and without life-limiting medical conditions, recruited 1 March 2010 – 31 December 2014 for the ASPREE trial.</p> </section> <section> <h3> Main outcome measures</h3> <p>Baseline characteristics and long term health outcomes for participants classified to different chronic kidney disease (CKD) stages by CKD-EPI<sub>2021</sub> and CKD-EPI<sub>2009</sub>, and for those classified to the same CKD stage by both equations.</p> </section> <section> <h3> Results</h3> <p>Complete data were available for 16 244 Australian ASPREE trial participants. At baseline, their mean age was 75.3 years (standard deviation, 4.4 years), and 8938 were women (55%); the median eGFR (CKD-EPI<sub>2009</sub>) was 74 mL/min/1.73 m<sup>2</sup> (interquartile range [IQR], 64–85 mL/min/1.73 m<sup>2</sup>), the median urine albumin-to-creatinine ratio 0.8 mg/mmol (IQR, 0.5–1.4 mg/mmol). eGFR values were higher for most participants with CKD-EPI<sub>2021</sub> than with CKD-EPI<sub>2009</sub> (median difference, 3.8 mL/min/1.73 m<sup>2</sup>; IQR, 3.3–4.4 mL/min/1.73 m<sup>2</sup>), and 3274 participants (20%) were classified to less advanced CKD stages by CKD-EPI<sub>2021</sub>. The proportion of participants with eGFR values below 60 mL/min/1.73 m<sup>2</sup> (clinical CKD) was 17% (2770 participants) with CKD-EPI<sub>2009</sub> and 12% (1994 participants) with CKD-EPI<sub>2021</sub>. Participants were followed up at a median of 6.5 years (IQR, 5.4–7.9 years); the risks of reaching the disability-free survival composite endpoint (adjusted hazard ratio [aHR], 0.94; 95% confidence interval [CI], 0.84–1.05), all-cause mortality (aHR, 0.90; 95% CI, 0.78–1.03), major cardiac events (aHR, 0.94; 95% CI, 0.79–1.13), and hospitalisations with heart failure (aHR, 1.00; 95% CI, 0.67–1.49) were each similar for participants reclassified or not reclassified by CKD-EPI<sub>2021</sub>.</p> </section>
{"title":"Classification of chronic kidney disease in older Australian adults by the CKD-EPI 2009 and 2021 equations: secondary analysis of ASPREE study data","authors":"Elisa K Bongetti, Rory Wolfe, James B Wetmore, Anne M Murray, Robyn L Woods, Michelle A Fravel, Mark R Nelson, Nigel P Stocks, Suzanne G Orchard, Kevan R Polkinghorne","doi":"10.5694/mja2.52559","DOIUrl":"10.5694/mja2.52559","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To assess the clinical impact on generally healthy older Australians of changing from the 2009 CKD-EPI (CKD-EPI<sub>2009</sub>) to the 2021 CKD-EPI (CKD-EPI<sub>2021</sub>) equation for calculating the estimated glomerular filtration rate (eGFR).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study design</h3>\u0000 \u0000 <p>Secondary analysis of data from the prospective ASPirin in Reducing events in the Elderly (ASPREE) cohort study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting, participants</h3>\u0000 \u0000 <p>Australians aged 70 years or older living in the community and without life-limiting medical conditions, recruited 1 March 2010 – 31 December 2014 for the ASPREE trial.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main outcome measures</h3>\u0000 \u0000 <p>Baseline characteristics and long term health outcomes for participants classified to different chronic kidney disease (CKD) stages by CKD-EPI<sub>2021</sub> and CKD-EPI<sub>2009</sub>, and for those classified to the same CKD stage by both equations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Complete data were available for 16 244 Australian ASPREE trial participants. At baseline, their mean age was 75.3 years (standard deviation, 4.4 years), and 8938 were women (55%); the median eGFR (CKD-EPI<sub>2009</sub>) was 74 mL/min/1.73 m<sup>2</sup> (interquartile range [IQR], 64–85 mL/min/1.73 m<sup>2</sup>), the median urine albumin-to-creatinine ratio 0.8 mg/mmol (IQR, 0.5–1.4 mg/mmol). eGFR values were higher for most participants with CKD-EPI<sub>2021</sub> than with CKD-EPI<sub>2009</sub> (median difference, 3.8 mL/min/1.73 m<sup>2</sup>; IQR, 3.3–4.4 mL/min/1.73 m<sup>2</sup>), and 3274 participants (20%) were classified to less advanced CKD stages by CKD-EPI<sub>2021</sub>. The proportion of participants with eGFR values below 60 mL/min/1.73 m<sup>2</sup> (clinical CKD) was 17% (2770 participants) with CKD-EPI<sub>2009</sub> and 12% (1994 participants) with CKD-EPI<sub>2021</sub>. Participants were followed up at a median of 6.5 years (IQR, 5.4–7.9 years); the risks of reaching the disability-free survival composite endpoint (adjusted hazard ratio [aHR], 0.94; 95% confidence interval [CI], 0.84–1.05), all-cause mortality (aHR, 0.90; 95% CI, 0.78–1.03), major cardiac events (aHR, 0.94; 95% CI, 0.79–1.13), and hospitalisations with heart failure (aHR, 1.00; 95% CI, 0.67–1.49) were each similar for participants reclassified or not reclassified by CKD-EPI<sub>2021</sub>.</p>\u0000 </section>\u0000 \u0000 ","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"222 2","pages":"74-81"},"PeriodicalIF":6.7,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52559","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142837224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Georgia Behrens, Madeleine Skellern, Alice McGushin, Paul Kelly, The Hon Ged Kearney
<p>Climate change poses profound and urgent challenges to the health and wellbeing of people in Australia. With an average of 1.51°C of warming since records began,<span><sup>1</sup></span> the health impacts of climate change are already being felt across Australia.<span><sup>2</sup></span> Meanwhile, the health system itself is responsible, either directly or indirectly, for around 5.3% of Australia's greenhouse gas emissions.<span><sup>3</sup></span> There is a clear need for Australia to achieve “healthy, climate-resilient communities, and a sustainable, resilient, high-quality, net zero health system.”<span><sup>3</sup></span> This vision is outlined in Australia's first National Health and Climate Strategy (hereafter, the Strategy), proudly launched in December 2023 by the Honourable Ged Kearney MP, Assistant Minister for Health and Aged Care. In this perspective article, we review the Strategy's origins, development, and key features; discuss the challenges that must be tackled in the coming years; and highlight the leadership role that health professionals can play in the response to climate change.</p><p>The National Health and Climate Strategy is built on decades of outstanding Australian work on climate change and human health. Australians have been at the forefront of climate and health research for more than thirty years, and have been pioneers in drawing the global health community's collective attention to the impacts of climate change on human health and wellbeing. We acknowledge the many individuals and organisations who have persistently advocated for human and planetary health for over a decade, and welcome their ongoing contributions and leadership in this space.<span><sup>4, 5</sup></span></p><p>Consultation also highlighted the need to enable and embrace leadership on climate and health policy by First Nations people. Stakeholders spoke of the opportunities inherent in holistic partnerships with First Nations communities to improve health, reduce emissions and foster climate resilience. They also highlighted that First Nations peoples’ deep and nuanced knowledge — developed over tens of thousands of years of close observation and sustained custodianship of Country — is not only crucial in addressing the impacts of climate change on First Nations peoples’ health, but also can improve health and build climate resilience for all people in Australia.</p><p>At the heart of the Strategy is an ambitious agenda to transform Australia's health system into one that is sustainable and climate resilient while improving care quality and health outcomes. The Australian Government recognises that insights and leadership from health professionals will be crucial to achieving this agenda.</p><p>On health system decarbonisation, at the time of writing the Australian Government was working to publish baseline emissions estimates for the Australian health system, and to develop a net zero implementation guide for the Australian health system in
{"title":"Making climate change a national health priority: Australia's first National Health and Climate Strategy","authors":"Georgia Behrens, Madeleine Skellern, Alice McGushin, Paul Kelly, The Hon Ged Kearney","doi":"10.5694/mja2.52552","DOIUrl":"10.5694/mja2.52552","url":null,"abstract":"<p>Climate change poses profound and urgent challenges to the health and wellbeing of people in Australia. With an average of 1.51°C of warming since records began,<span><sup>1</sup></span> the health impacts of climate change are already being felt across Australia.<span><sup>2</sup></span> Meanwhile, the health system itself is responsible, either directly or indirectly, for around 5.3% of Australia's greenhouse gas emissions.<span><sup>3</sup></span> There is a clear need for Australia to achieve “healthy, climate-resilient communities, and a sustainable, resilient, high-quality, net zero health system.”<span><sup>3</sup></span> This vision is outlined in Australia's first National Health and Climate Strategy (hereafter, the Strategy), proudly launched in December 2023 by the Honourable Ged Kearney MP, Assistant Minister for Health and Aged Care. In this perspective article, we review the Strategy's origins, development, and key features; discuss the challenges that must be tackled in the coming years; and highlight the leadership role that health professionals can play in the response to climate change.</p><p>The National Health and Climate Strategy is built on decades of outstanding Australian work on climate change and human health. Australians have been at the forefront of climate and health research for more than thirty years, and have been pioneers in drawing the global health community's collective attention to the impacts of climate change on human health and wellbeing. We acknowledge the many individuals and organisations who have persistently advocated for human and planetary health for over a decade, and welcome their ongoing contributions and leadership in this space.<span><sup>4, 5</sup></span></p><p>Consultation also highlighted the need to enable and embrace leadership on climate and health policy by First Nations people. Stakeholders spoke of the opportunities inherent in holistic partnerships with First Nations communities to improve health, reduce emissions and foster climate resilience. They also highlighted that First Nations peoples’ deep and nuanced knowledge — developed over tens of thousands of years of close observation and sustained custodianship of Country — is not only crucial in addressing the impacts of climate change on First Nations peoples’ health, but also can improve health and build climate resilience for all people in Australia.</p><p>At the heart of the Strategy is an ambitious agenda to transform Australia's health system into one that is sustainable and climate resilient while improving care quality and health outcomes. The Australian Government recognises that insights and leadership from health professionals will be crucial to achieving this agenda.</p><p>On health system decarbonisation, at the time of writing the Australian Government was working to publish baseline emissions estimates for the Australian health system, and to develop a net zero implementation guide for the Australian health system in","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"222 2","pages":"63-65"},"PeriodicalIF":6.7,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52552","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142829210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Berhe W Sahle, Emily Banks, Robyn Williams, Grace Joshy, Garry Jennings, Jonathan C Craig, Nicholas G Larkins, Francine Eades, Rebecca Q Ivers, Sandra Eades
<div> <section> <h3> Objective</h3> <p>To assess the distribution of blood pressure levels and the prevalence of hypertension and pre-hypertension in young Indigenous people (10–24 years of age).</p> </section> <section> <h3> Study design</h3> <p>Prospective cohort survey study (Next Generation: Youth Wellbeing Study); baseline data analysis.</p> </section> <section> <h3> Setting, participants</h3> <p>Aboriginal and Torres Strait Islander people aged 10–24 years living in regional, remote, and urban communities in Central Australia, Western Australia, and New South Wales; recruitment: March 2018 – March 2020.</p> </section> <section> <h3> Main outcome measures</h3> <p>Blood pressure categorised as normal, pre-hypertension, or hypertension using the 2017 American Academy of Pediatrics guidelines (10–17 years) or 2017 American College of Cardiology/American Heart Association guidelines (18–24 years); associations of demographic characteristics and health behaviours with hypertension and pre-hypertension, reported as relative risk ratios (RRRs) with 95% confidence intervals (CIs).</p> </section> <section> <h3> Results</h3> <p>Complete data were available for 771 of 1244 study participants (62%); their mean age was 15.4 years (standard deviation [SD], 3.9 years), 438 were girls or young women (56.8%). Mean systolic blood pressure was 111.2 mmHg (SD, 13.7 mmHg), mean diastolic blood pressure 66.3 mmHg (SD, 11.0 mmHg). Mean systolic blood pressure was higher for male than female participants (mean difference, 6.38 mmHg; 95% CI, 4.60–8.16 mmHg), and it increased by 1.06 mmHg (95% CI, 0.76–1.36 mmHg) per year of age. Mean systolic blood pressure increased by 0.42 mmHg (95% CI, 0.28–0.54 mmHg) and diastolic blood pressure by 0.46 mmHg (95% CI, 0.35–0.57 mmHg) per 1.0 kg/m<sup>2</sup> increase in body mass index. Ninety-one participants (11.8%) had blood pressure readings indicating pre-hypertension, and 148 (19.2%) had hypertension. The risks of pre-hypertension (RRR, 4.22; 95% CI, 2.52–7.09) and hypertension (RRR, 1.93; 95% CI, 1.27–2.91) were higher for male than female participants; they were greater for people with obesity than for those with BMI values in the normal range (pre-hypertension: RRR, 2.39 [95% CI, 1.26–4.55]; hypertension: RRR, 3.20 [95% CI, 1.91–5.35]) and for participants aged 16–19 years (pre-hypertension: 3.44 [95% CI, 1.88–6.32]; hypertension: RRR, 2.15 [95% CI, 1.29–3.59]) or 20–24 years (pre-hypertension: 4.12 [95% CI, 1.92–8.85]; hy
{"title":"Blood pressure in young Aboriginal and Torres Strait Islander people: analysis of baseline data from a prospective cohort study","authors":"Berhe W Sahle, Emily Banks, Robyn Williams, Grace Joshy, Garry Jennings, Jonathan C Craig, Nicholas G Larkins, Francine Eades, Rebecca Q Ivers, Sandra Eades","doi":"10.5694/mja2.52558","DOIUrl":"10.5694/mja2.52558","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To assess the distribution of blood pressure levels and the prevalence of hypertension and pre-hypertension in young Indigenous people (10–24 years of age).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Study design</h3>\u0000 \u0000 <p>Prospective cohort survey study (Next Generation: Youth Wellbeing Study); baseline data analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Setting, participants</h3>\u0000 \u0000 <p>Aboriginal and Torres Strait Islander people aged 10–24 years living in regional, remote, and urban communities in Central Australia, Western Australia, and New South Wales; recruitment: March 2018 – March 2020.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main outcome measures</h3>\u0000 \u0000 <p>Blood pressure categorised as normal, pre-hypertension, or hypertension using the 2017 American Academy of Pediatrics guidelines (10–17 years) or 2017 American College of Cardiology/American Heart Association guidelines (18–24 years); associations of demographic characteristics and health behaviours with hypertension and pre-hypertension, reported as relative risk ratios (RRRs) with 95% confidence intervals (CIs).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Complete data were available for 771 of 1244 study participants (62%); their mean age was 15.4 years (standard deviation [SD], 3.9 years), 438 were girls or young women (56.8%). Mean systolic blood pressure was 111.2 mmHg (SD, 13.7 mmHg), mean diastolic blood pressure 66.3 mmHg (SD, 11.0 mmHg). Mean systolic blood pressure was higher for male than female participants (mean difference, 6.38 mmHg; 95% CI, 4.60–8.16 mmHg), and it increased by 1.06 mmHg (95% CI, 0.76–1.36 mmHg) per year of age. Mean systolic blood pressure increased by 0.42 mmHg (95% CI, 0.28–0.54 mmHg) and diastolic blood pressure by 0.46 mmHg (95% CI, 0.35–0.57 mmHg) per 1.0 kg/m<sup>2</sup> increase in body mass index. Ninety-one participants (11.8%) had blood pressure readings indicating pre-hypertension, and 148 (19.2%) had hypertension. The risks of pre-hypertension (RRR, 4.22; 95% CI, 2.52–7.09) and hypertension (RRR, 1.93; 95% CI, 1.27–2.91) were higher for male than female participants; they were greater for people with obesity than for those with BMI values in the normal range (pre-hypertension: RRR, 2.39 [95% CI, 1.26–4.55]; hypertension: RRR, 3.20 [95% CI, 1.91–5.35]) and for participants aged 16–19 years (pre-hypertension: 3.44 [95% CI, 1.88–6.32]; hypertension: RRR, 2.15 [95% CI, 1.29–3.59]) or 20–24 years (pre-hypertension: 4.12 [95% CI, 1.92–8.85]; hy","PeriodicalId":18214,"journal":{"name":"Medical Journal of Australia","volume":"222 2","pages":"91-101"},"PeriodicalIF":6.7,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.5694/mja2.52558","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142812955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：