Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status?
Attrition is a potential source of bias in cohort studies. Although attrition may be inevitable in cohort studies of older people, there is little empirical evidence as to whether bias due to such attrition is also inevitable. Anonymised primary care data, routinely collected in clinical practice an...
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Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0083948&type=printable |
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| author | Rosie J Lacey Kelvin P Jordan Peter R Croft |
| author_facet | Rosie J Lacey Kelvin P Jordan Peter R Croft |
| author_sort | Rosie J Lacey |
| collection | DOAJ |
| description | Attrition is a potential source of bias in cohort studies. Although attrition may be inevitable in cohort studies of older people, there is little empirical evidence as to whether bias due to such attrition is also inevitable. Anonymised primary care data, routinely collected in clinical practice and independent of any cohort research study, represents an ideal unselected comparison dataset with which to compare primary care data from consenting responders to a cohort study. Our objective was to use this method as a novel means to assess if (i) responders at follow-up stages in a cohort study remain representative of responders at baseline and (ii) attrition biases estimates of longitudinal associations. We compared primary care consultation morbidities and prescription prevalences among circa 32,000 patients aged 50+ who contribute to an anonymised general practice database (Consultations in Primary Care Archive (CiPCA)) with those from patients aged 50+ in the North Staffordshire Osteoarthritis Project (NorStOP) cohort, United Kingdom (2002-2008; n=16,159). 8,197 (51%) persons responded to the NorStOP baseline survey and consented to medical record review. 5,121 and 3,311 responded at 3- and 6-year follow-ups. Differences in consulting prevalence of non-musculoskeletal morbidities between NorStOP responders and CiPCA comparison population did not increase over the two follow-up points except for ischaemic heart disease. Differences observed at baseline for osteoarthritis-related consultations were generally unchanged at the two follow-ups (standardised prevalence ratios for osteoarthritis (1.09-1.13) and joint pain (1.12-1.23)). Age and gender adjusted associations between baseline consultation for chronic morbidity and future new osteoarthritis and related consultations were similar in CiPCA (adjusted Hazard Ratio: 1.40; 95% Confidence Interval: 1.34,1.47) and NorStOP 6-year responders (1.32; 1.15,1.51). There was little evidence that responders at follow-ups represented any further selection bias to that present at baseline. Attrition in cohort studies of older people does not inevitably indicate bias. |
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| language | English |
| publishDate | 2013-01-01 |
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| spelling | doaj-art-9f5299f7a60d442a82d24ccf59d71d052025-08-20T02:34:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-01812e8394810.1371/journal.pone.0083948Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status?Rosie J LaceyKelvin P JordanPeter R CroftAttrition is a potential source of bias in cohort studies. Although attrition may be inevitable in cohort studies of older people, there is little empirical evidence as to whether bias due to such attrition is also inevitable. Anonymised primary care data, routinely collected in clinical practice and independent of any cohort research study, represents an ideal unselected comparison dataset with which to compare primary care data from consenting responders to a cohort study. Our objective was to use this method as a novel means to assess if (i) responders at follow-up stages in a cohort study remain representative of responders at baseline and (ii) attrition biases estimates of longitudinal associations. We compared primary care consultation morbidities and prescription prevalences among circa 32,000 patients aged 50+ who contribute to an anonymised general practice database (Consultations in Primary Care Archive (CiPCA)) with those from patients aged 50+ in the North Staffordshire Osteoarthritis Project (NorStOP) cohort, United Kingdom (2002-2008; n=16,159). 8,197 (51%) persons responded to the NorStOP baseline survey and consented to medical record review. 5,121 and 3,311 responded at 3- and 6-year follow-ups. Differences in consulting prevalence of non-musculoskeletal morbidities between NorStOP responders and CiPCA comparison population did not increase over the two follow-up points except for ischaemic heart disease. Differences observed at baseline for osteoarthritis-related consultations were generally unchanged at the two follow-ups (standardised prevalence ratios for osteoarthritis (1.09-1.13) and joint pain (1.12-1.23)). Age and gender adjusted associations between baseline consultation for chronic morbidity and future new osteoarthritis and related consultations were similar in CiPCA (adjusted Hazard Ratio: 1.40; 95% Confidence Interval: 1.34,1.47) and NorStOP 6-year responders (1.32; 1.15,1.51). There was little evidence that responders at follow-ups represented any further selection bias to that present at baseline. Attrition in cohort studies of older people does not inevitably indicate bias.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0083948&type=printable |
| spellingShingle | Rosie J Lacey Kelvin P Jordan Peter R Croft Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? PLoS ONE |
| title | Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? |
| title_full | Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? |
| title_fullStr | Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? |
| title_full_unstemmed | Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? |
| title_short | Does attrition during follow-up of a population cohort study inevitably lead to biased estimates of health status? |
| title_sort | does attrition during follow up of a population cohort study inevitably lead to biased estimates of health status |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0083948&type=printable |
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