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Liu J, Varghese BM, Hansen A, Dear K, Morgan G, Driscoll T, Zhang Y, Gourley M, Capon A, Bi P. Projection of high temperature-related burden of kidney disease in Australia under different climate change, population and adaptation scenarios: population-based study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 41:100916. [PMID: 37867620 PMCID: PMC10587708 DOI: 10.1016/j.lanwpc.2023.100916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/21/2023] [Accepted: 09/11/2023] [Indexed: 10/24/2023]
Abstract
Background The dual impacts of a warming climate and population ageing lead to an increasing kidney disease prevalence, highlighting the importance of quantifying the burden of kidney disease (BoKD) attributable to high temperature, yet studies on this subject are limited. The study aims to quantify the BoKD attributable to high temperatures in Australia across all states and territories, and project future BoKD under climatic, population and adaptation scenarios. Methods Data on disability-adjusted-life-years (DALYs) due to kidney disease, including years of life lost (YLL), and years lived with disability (YLD), were collected during 2003-2018 (baseline) across all states and territories in Australia. The temperature-response association was estimated using a meta-regression model. Future temperature projections were calculated using eight downscaled climate models to estimate changes in attributable BoKD centred around 2030s and 2050s, under two greenhouse gas emissions scenarios (RCP4.5 and RCP8.5), while considering changes in population size and age structure, and human adaptation to climate change. Findings Over the baseline (2003-2018), high-temperature contributed to 2.7% (Standard Deviation: 0.4%) of the observed BoKD in Australia. The future population attributable fraction and the attributable BoKD, projected using RCP4.5 and RCP8.5, showed a gradually increasing trend when assuming no human adaptation. Future projections were most strongly influenced by the population change, with the high temperature-related BoKD increasing by 18.4-67.4% compared to the baseline under constant population and by 100.2-291.2% when accounting for changes in population size and age structure. However, when human adaptation was adopted (from no to partial to full), the high temperature-related BoKD became smaller. Interpretation It is expected that increasing high temperature exposure will substantially contribute to higher BoKD across Australia, underscoring the urgent need for public health interventions to mitigate the negative health impacts of a warming climate on BoKD. Funding Australian Research Council Discovery Program.
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Affiliation(s)
- Jingwen Liu
- School of Public Health, The University of Adelaide, Australia
| | | | - Alana Hansen
- School of Public Health, The University of Adelaide, Australia
| | - Keith Dear
- School of Public Health, The University of Adelaide, Australia
| | - Geoffrey Morgan
- Sydney School of Public Health, The University of Sydney, Australia
| | - Timothy Driscoll
- Sydney School of Public Health, The University of Sydney, Australia
| | - Ying Zhang
- Sydney School of Public Health, The University of Sydney, Australia
| | - Michelle Gourley
- Burden of Disease and Mortality Unit, Australian Institute of Health and Welfare, Australia
| | - Anthony Capon
- Monash Sustainable Development Institute, Monash University, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Australia
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Liu J, Hansen A, Varghese BM, Dear K, Tong M, Prescott V, Dolar V, Gourley M, Driscoll T, Zhang Y, Morgan G, Capon A, Bi P. Estimating the burden of disease attributable to high ambient temperature across climate zones: methodological framework with a case study. Int J Epidemiol 2023; 52:783-795. [PMID: 36511334 PMCID: PMC10244055 DOI: 10.1093/ije/dyac229] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 11/30/2022] [Indexed: 10/24/2023] Open
Abstract
BACKGROUND With high temperature becoming an increasing health risk due to a changing climate, it is important to quantify the scale of the problem. However, estimating the burden of disease (BoD) attributable to high temperature can be challenging due to differences in risk patterns across geographical regions and data accessibility issues. METHODS We present a methodological framework that uses Köppen-Geiger climate zones to refine exposure levels and quantifies the difference between the burden observed due to high temperatures and what would have been observed if the population had been exposed to the theoretical minimum risk exposure distribution (TMRED). Our proposed method aligned with the Australian Burden of Disease Study and included two parts: (i) estimation of the population attributable fractions (PAF); and then (ii) estimation of the BoD attributable to high temperature. We use suicide and self-inflicted injuries in Australia as an example, with most frequent temperatures (MFTs) as the minimum risk exposure threshold (TMRED). RESULTS Our proposed framework to estimate the attributable BoD accounts for the importance of geographical variations of risk estimates between climate zones, and can be modified and adapted to other diseases and contexts that may be affected by high temperatures. CONCLUSIONS As the heat-related BoD may continue to increase in the future, this method is useful in estimating burdens across climate zones. This work may have important implications for preventive health measures, by enhancing the reproducibility and transparency of BoD research.
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Affiliation(s)
- Jingwen Liu
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
| | - Alana Hansen
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
| | - Blesson M Varghese
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
| | - Keith Dear
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
| | - Michael Tong
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
| | - Vanessa Prescott
- Burden of Disease and Mortality Unit, Australian Institute of Health and Welfare, Canberra, ACT, Australia
| | - Vergil Dolar
- Burden of Disease and Mortality Unit, Australian Institute of Health and Welfare, Canberra, ACT, Australia
| | - Michelle Gourley
- Burden of Disease and Mortality Unit, Australian Institute of Health and Welfare, Canberra, ACT, Australia
| | - Timothy Driscoll
- Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia
| | - Ying Zhang
- Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia
| | - Geoffrey Morgan
- Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia
| | - Anthony Capon
- Monash Sustainable Development Institute, Monash University, Melbourne, VIC, Australia
| | - Peng Bi
- School of Public Health, University of Adelaide, Adelaide, SA, Australia
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Weber C, Hobday M, Sun W, Kirkland L, Nedkoff L, Katzenellenbogen JM. Evolution of non-fatal burden estimates for cardiovascular disease in Australia: a comparison of national and state-wide methodology of burden of disease. AUST HEALTH REV 2022; 46:756-764. [PMID: 36395787 DOI: 10.1071/ah22149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/23/2022] [Indexed: 11/19/2022]
Abstract
Objective Burden of disease studies measure the impact of disease at the population level;however, methods and data sources for estimates of prevalence vary. Using a selection of cardiovascular diseases, we aimed to describe the implications of using different disease models and linked administrative data on prevalence estimation within three Australian burden of disease studies. Methods Three different methods (A = 2011 Australian Burden of Disease Study; B = 2015 Australian Burden of Disease Study; C = 2015 Western Australian Burden of Disease Study), which used linked data, were used to compare prevalence estimates of stroke, aortic aneurysm, rheumatic valvular heart disease (VHD) and non-rheumatic VHD. We applied these methods to 2015 Western Australian data, and calculated crude overall and age-specific prevalence for each condition. Results Overall, Method C produced estimates of cardiovascular prevalence that were lower than the other methods, excluding non-rheumatic VHD. Prevalence of acute and chronic stroke was up to one-third higher in Method A and B compared to Method C. Aortic aneurysms had the largest change in prevalence, with Method A producing an eight-fold higher estimate compared to Method C, but Method B was 10-20% lower. Estimates of VHD varied dramatically, with an up to six-fold change in prevalence in Method C due to substantial changes to disease models and the use of linked data. Conclusions Prevalence estimates require the best available data sources, updated disease models and constant review to inform government policy and health reform. Availability of nation-wide linked data will markedly improve future burden estimates.
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Affiliation(s)
- Courtney Weber
- School of Population and Global Health, The University of Western Australia, WA, Australia; and Centre for Clinical Research in Emergency Medicine, Harry Perkins Institute of Medical Research, Perth, WA, Australia; and Western Australian Department of Health, East Perth, WA, Australia
| | - Michelle Hobday
- Western Australian Department of Health, East Perth, WA, Australia
| | - Wendy Sun
- Western Australian Department of Health, East Perth, WA, Australia
| | - Laura Kirkland
- Western Australian Department of Health, East Perth, WA, Australia
| | - Lee Nedkoff
- School of Population and Global Health, The University of Western Australia, WA, Australia; and Cardiology Population Health Laboratory, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
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de Luca K, Briggs AM, French SD, Ferreira ML, Cross M, Blyth F, March L. Disability burden due to musculoskeletal conditions and low back pain in Australia: findings from GBD 2019. Chiropr Man Therap 2022; 30:22. [PMID: 35505334 PMCID: PMC9063272 DOI: 10.1186/s12998-022-00434-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 04/19/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To report the national prevalence, years lived with disability (YLDs) and attributable risk factors for all musculoskeletal conditions and separately for low back pain (LBP), as well as compare the disability burden related to musculoskeletal with other health conditions in Australia in 2019. METHODS Global Burden of Disease (GBD) 2019 study meta-data on all musculoskeletal conditions and LBP specifically were accessed and aggregated. Counts and age-standardised rates, for both sexes and across all ages, for prevalence, YLDs and attributable risk factors are reported. RESULTS In 2019, musculoskeletal conditions were estimated to be the leading cause of YLDs in Australia (20.1%). There were 7,219,894.5 (95% UI: 6,847,113-7,616,567) prevalent cases of musculoskeletal conditions and 685,363 (95% UI: 487,722-921,471) YLDs due to musculoskeletal conditions. There were 2,676,192 (95% UI: 2,339,327-3,061,066) prevalent cases of LBP and 298,624 (95% UI: 209,364-402,395) YLDs due to LBP. LBP was attributed to 44% of YLDs due to musculoskeletal conditions. In 2019, 22.3% and 39.8% of YLDs due to musculoskeletal conditions and LBP, respectively, were attributed to modifiable GBD risk factors. CONCLUSIONS The ongoing high burden due to musculoskeletal conditions impacts Australians across the life course, and in particular females and older Australians. Strategies for integrative and organisational interventions in the Australian healthcare system should support high-value care and address key modifiable risk factors for disability such as smoking, occupational ergonomic factors and obesity.
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Affiliation(s)
- Katie de Luca
- Discipline of Chiropractic, School of Health, Medical and Applied Sciences, CQUniversity, Brisbane, Australia.
| | - Andrew M Briggs
- Curtin School of Allied Health and Curtin enAble Institute, Faculty of Health Sciences, Curtin University, Perth, Australia.,Global Alliance for Musculoskeletal Health, Sydney, Australia
| | - Simon D French
- Department of Chiropractic, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Manuela L Ferreira
- Institute of Bone and Joint Research, Kolling Institute, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Marita Cross
- Global Alliance for Musculoskeletal Health, Sydney, Australia.,Institute of Bone and Joint Research, Kolling Institute, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Fiona Blyth
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Lyn March
- Institute of Bone and Joint Research, Kolling Institute, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.,Florance and Cope Professorial Department of Rheumatology, Royal North Shore Hospital, Sydney, Australia
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