Evidence map›Paper›PMID 32586986›Full record

ArticleJournal of epidemiology and community health2020

Association of attrition with mortality: findings from 11 waves over three decades of the Whitehall II study.

Mifuyu Akasaki, Mika Kivimäki, Andrew Steptoe, Owen Nicholas, Martin J Shipley

Abstract read
In one paragraph

Article in Journal of epidemiology and community health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Association of cerebral small vessel disease burden with brain structure and cognitive and vascular risk trajectories in mid-to-late life.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mifuyu AkasakiDepartment of Behavioural Science and Health, University College London, London, UK mifuyu.akasaki.15@ucl.ac.uk.ORCID 0000-0003-3588-9084
Mika KivimäkiDepartment of Epidemiology and Public Health, University College London, London, UK.
Andrew SteptoeDepartment of Behavioural Science and Health, University College London, London, UK.
Owen Nicholas *Department of Statistical Science, University College London, London, UK.
Martin J Shipley *Department of Epidemiology and Public Health, University College London, London, UK.

Funding

Education, socioeconomic status and Aging: transitions from multimorbidity to functional limitations and mortalityR01AG056477 · NIA · UNIVERSITY COLLEGE LONDON · PI KIVIMAKI, MIKA J, SINGH-MANOUX, ARCHANA · 2018 to 2022
$2.8M
Role of mid- and late-life risk factors in social inequalities in Alzheimer's Disease and Related DementiasRF1AG062553 · NIA · INSERM PARIS 5 · PI KIVIMAKI, MIKA J, SINGH-MANOUX, ARCHANA · 2019 to 2019
$1.5M
Education and Aging: transitions from multi-morbidity to functional limitationsR56AG056477 · NIA · UNIVERSITY COLLEGE LONDON · PI KIVIMAKI, MIKA J, SINGH-MANOUX, ARCHANA · 2017 to 2017
$365k
British Heart Foundation 32334Medical Research Council K013351Medical Research Council MR/R024227/1Medical Research Council MR/S011676/1Medical Research Council R024227Medical Research Council S011676NIA NIH HHS R01 AG056477NIA NIH HHS R56 AG056477NIA NIH HHS RF1 AG062553
6 · The paper itself

Abstract

backgroundAttrition, the loss of participants as a study progresses, is a considerable challenge in longitudinal studies. This study examined whether two forms of attrition, 'withdrawal' (formal discontinued participation) and 'non-response' (non-response among participants continuing in the study), have different associations with mortality and whether these associations differed across time in a multi-wave longitudinal study.

methodsParticipants were 10 012 civil servants who participated at the baseline of the Whitehall II cohort study with 11 data waves over an average follow-up of 28 years. We performed competing-risks analyses to estimate sub-distribution HRs and 95% CIs, and likelihood ratio tests to examine whether hazards differed between the two forms of attrition. We then applied linear regression to examine any trend of hazards against time.

resultsAttrition rate at data collections ranged between 13% and 34%. There were 495 deaths recorded from cardiovascular disease and 1367 deaths from other causes. Study participants lost due to attrition had 1.55 (95% CI 1.26 to 1.89) and 1.56 (1.39 to 1.76) times higher hazard of cardiovascular and non-cardiovascular mortality than responders, respectively. Hazards for withdrawal and non-response did not differ for either cardiovascular (p value =0.28) or non-cardiovascular mortality (p value =0.38). There was no linear trend in hazards over the 11 waves (cardiovascular mortality p value =0.11, non-cardiovascular mortality p value =0.61).

conclusionAttrition can be a problem in longitudinal studies resulting in selection bias. Researchers should examine the possibility of selection bias and consider applying statistical approaches that minimise this bias.

Indexed as

Cardiovascular DiseasesMortalityAdultBiasFemaleHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsUnited KingdomBIOSTATISTICSEpidemiological methodsEPIDEMIOLOGYMEDICAL STATISTICSSocial and life-course epidemiologySOCIAL EPIDEMIOLOGYSTATISTICSStochastic PorcessTIME-SERIES

Identifiers

PMID32586986
PMCPMC8071845

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.