Cargando…
Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates
OBJECTIVE: To examine if the rankings of state HIV age-standardised death rates (SDRs) would be different if different standard populations (SPs) were used when age-specific death rates (ASDRs) in states being compared do not have a consistent relationship. DESIGN: A cross-sectional population-based...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016403/ https://www.ncbi.nlm.nih.gov/pubmed/35437248 http://dx.doi.org/10.1136/bmjopen-2021-056441 |
_version_ | 1784688522545856512 |
---|---|
author | Tai, Shu-Yu Liang, Fu-Wen Hng, Yen-Yee Lo, Yi-Hsuan Lu, Tsung-Hsueh |
author_facet | Tai, Shu-Yu Liang, Fu-Wen Hng, Yen-Yee Lo, Yi-Hsuan Lu, Tsung-Hsueh |
author_sort | Tai, Shu-Yu |
collection | PubMed |
description | OBJECTIVE: To examine if the rankings of state HIV age-standardised death rates (SDRs) would be different if different standard populations (SPs) were used when age-specific death rates (ASDRs) in states being compared do not have a consistent relationship. DESIGN: A cross-sectional population-based observational study. SETTING: 36 states in the USA. PARTICIPANTS: Residents living in the 36 states. MAIN OUTCOME MEASURES: HIV SDR by state using two SPs, namely US2000 and US2020. RESULTS: US HIV ASDR by state did not have consistent relationships. Of 36 states analysed, the HIV death rates of people aged 55–64 years were higher than people aged 45–54 years in 20 states; on the contrary, the HIV death rates of people aged 55–64 years were lower than people aged 45–54 years in 16 states. No change in ranking in 19 states and change in ranking in 17 states. Of the 17 states whose rankings changed, the rankings of 9 states calculated using US2000 were higher (lower SDR) than those calculated using US2020; in 8 states, the rankings were lower (higher SDR). The states with the greatest changes in rankings between US2000 and US2020 were Kentucky (12th and 9th, respectively) and Massachusetts (8th and 11th, respectively). CONCLUSIONS: Calculating SDR using elder SP (US2020) would disproportionately increase the SDR in states with peak HIV death rate in older adults than those used younger SP (US2000). |
format | Online Article Text |
id | pubmed-9016403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-90164032022-05-04 Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates Tai, Shu-Yu Liang, Fu-Wen Hng, Yen-Yee Lo, Yi-Hsuan Lu, Tsung-Hsueh BMJ Open Epidemiology OBJECTIVE: To examine if the rankings of state HIV age-standardised death rates (SDRs) would be different if different standard populations (SPs) were used when age-specific death rates (ASDRs) in states being compared do not have a consistent relationship. DESIGN: A cross-sectional population-based observational study. SETTING: 36 states in the USA. PARTICIPANTS: Residents living in the 36 states. MAIN OUTCOME MEASURES: HIV SDR by state using two SPs, namely US2000 and US2020. RESULTS: US HIV ASDR by state did not have consistent relationships. Of 36 states analysed, the HIV death rates of people aged 55–64 years were higher than people aged 45–54 years in 20 states; on the contrary, the HIV death rates of people aged 55–64 years were lower than people aged 45–54 years in 16 states. No change in ranking in 19 states and change in ranking in 17 states. Of the 17 states whose rankings changed, the rankings of 9 states calculated using US2000 were higher (lower SDR) than those calculated using US2020; in 8 states, the rankings were lower (higher SDR). The states with the greatest changes in rankings between US2000 and US2020 were Kentucky (12th and 9th, respectively) and Massachusetts (8th and 11th, respectively). CONCLUSIONS: Calculating SDR using elder SP (US2020) would disproportionately increase the SDR in states with peak HIV death rate in older adults than those used younger SP (US2000). BMJ Publishing Group 2022-04-18 /pmc/articles/PMC9016403/ /pubmed/35437248 http://dx.doi.org/10.1136/bmjopen-2021-056441 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Epidemiology Tai, Shu-Yu Liang, Fu-Wen Hng, Yen-Yee Lo, Yi-Hsuan Lu, Tsung-Hsueh Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates |
title | Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates |
title_full | Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates |
title_fullStr | Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates |
title_full_unstemmed | Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates |
title_short | Impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on US state HIV death rates |
title_sort | impacts of using different standard populations in calculating age-standardised death rates when age-specific death rates in the populations being compared do not have a consistent relationship: a cross-sectional population-based observational study on us state hiv death rates |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016403/ https://www.ncbi.nlm.nih.gov/pubmed/35437248 http://dx.doi.org/10.1136/bmjopen-2021-056441 |
work_keys_str_mv | AT taishuyu impactsofusingdifferentstandardpopulationsincalculatingagestandardiseddeathrateswhenagespecificdeathratesinthepopulationsbeingcompareddonothaveaconsistentrelationshipacrosssectionalpopulationbasedobservationalstudyonusstatehivdeathrates AT liangfuwen impactsofusingdifferentstandardpopulationsincalculatingagestandardiseddeathrateswhenagespecificdeathratesinthepopulationsbeingcompareddonothaveaconsistentrelationshipacrosssectionalpopulationbasedobservationalstudyonusstatehivdeathrates AT hngyenyee impactsofusingdifferentstandardpopulationsincalculatingagestandardiseddeathrateswhenagespecificdeathratesinthepopulationsbeingcompareddonothaveaconsistentrelationshipacrosssectionalpopulationbasedobservationalstudyonusstatehivdeathrates AT loyihsuan impactsofusingdifferentstandardpopulationsincalculatingagestandardiseddeathrateswhenagespecificdeathratesinthepopulationsbeingcompareddonothaveaconsistentrelationshipacrosssectionalpopulationbasedobservationalstudyonusstatehivdeathrates AT lutsunghsueh impactsofusingdifferentstandardpopulationsincalculatingagestandardiseddeathrateswhenagespecificdeathratesinthepopulationsbeingcompareddonothaveaconsistentrelationshipacrosssectionalpopulationbasedobservationalstudyonusstatehivdeathrates |