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Global Burden of Disease Study 2019 (GBD 2019) Data Input Sources Tool

The Global Burden of Disease Study 2019 (GBD 2019) synthesizes a large number of input sources to estimate mortality, causes of death and illness, and risk factors.

The Data Input Sources Tool lets you explore GBD 2019 input sources and retrieve relevant metadata.

Use the selection boxes below to see these input sources by GBD component, geography, and cause. After you have made your selection, you can view and access GHDx catalog records for input sources used by GBD.

Download these input sources as a CSV file to see more information about how they were used in the analysis for the Global Burden of Disease. This CSV file contains relevant metadata about the input sources as suggested in the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER), a statement that promotes best practices in reporting health estimates.

For detailed information on the tool and the contents of the CSV files, refer to the following documents:

Results

Results for component: Nonfatal Health Outcomes, cause: Musculoskeletal disorders, location: Australia.

Total Citations: 14

Total Source Metadata Rows: 345

Citations

Australian Bureau of Statistics. Australia Disability, Ageing, and Carers Survey 2003.

Australian Bureau of Statistics. Australia Disability, Ageing, and Carers Survey 2009.

Australian Bureau of Statistics. Australia National Health Survey 1995. Canberra, Australia: Australian Bureau of Statistics.

Australian Bureau of Statistics. Australia National Health Survey 2001. Canberra, Australia: Australian Bureau of Statistics.

Australian Bureau of Statistics. Australia National Health Survey 2004-2005.

Australian Bureau of Statistics. Australia National Health Survey 2007-2008. Canberra, Australia: Australian Bureau of Statistics.

Department of Health and Ageing (Australia), World Health Organization (WHO). Australia World Health Survey 2003. Geneva, Switzerland: World Health Organization (WHO), 2005.

World Health Organization Regional Office for Europe (EURO-WHO). Health Behaviour in School-aged Children: WHO Collaborative Cross-National survey/study (HBSC) 2010.

Broom AF, Kirby ER, Sibbritt DW, Adams J, Refshauge KM. Back pain amongst mid-age Australian women: A longitudinal analysis of provider use and self-prescribed treatments. Complement Ther Med. 2012; 20(5): 275-82.

Szoeke CEI, Cicuttini FM, Guthrie JR, Clark MS, Dennerstein L. Factors affecting the prevalence of osteoarthritis in healthy middle-aged women: data from the longitudinal Melbourne Women's Midlife Health Project. Bone. 2006; 39(5): 1149-1155.

Grimmer K, Nyland L, Milanese S. Longitudinal investigation of low back pain in Australian adolescents: a five-year study. Physiother Res Int. 2006; 11(3): 161-72.

O'Sullivan PB, Beales DJ, Smith AJ, Straker LM. Low back pain in 17 year olds has substantial impact and represents an important public health disorder: a cross-sectional study. BMC Public Health. 2012; 12(1): 100.

Walker BF, Muller R, Grant WD. Low back pain in Australian adults: prevalence and associated disability. J Manipulative Physiol Ther. 2004; 27(4): 238-44.

Kodama R, Muraki S, Oka H, Iidaka T, Teraguchi M, Kagotani R, Asai Y, Yoshida M, Morizaki Y, Tanaka S, Kawaguchi H, Nakamura K, Akune T, Yoshimura N. Prevalence of hand osteoarthritis and its relationship to hand pain and grip strength in Japan: The third survey of the ROAD study. Mod Rheumatol. 2016; 26(5): 767-73.