Evidence map›Paper›PMID 37821822›Full record

ArticleBMC medical research methodology2023

Can non-participants in a follow-up be used to draw conclusions about incidences and prevalences in the full population invited at baseline? An investigation based on the Swedish MDC cohort.

Anton Nilsson, Jonas Björk, Ulf Strömberg, Carl Bonander

Abstract read
In one paragraph

Article in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Anton NilssonEpidemiology, Population Studies and Infrastructures (EPI@LUND), Tornblad Institute, Lund University, Biskopsgatan 9, Hämtställe 21, 22362, Lund, Sweden. anton.nilsson@med.lu.se.
Jonas BjörkEpidemiology, Population Studies and Infrastructures (EPI@LUND), Tornblad Institute, Lund University, Biskopsgatan 9, Hämtställe 21, 22362, Lund, Sweden.
Ulf StrömbergHealth Economics and Policy, School of Public Health & Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
Carl BonanderHealth Economics and Policy, School of Public Health & Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundParticipants in epidemiological cohorts may not be representative of the full invited population, limiting the generalizability of prevalence and incidence estimates. We propose that this problem can be remedied by exploiting data on baseline participants who refused to participate in a re-examination, as such participants may be more similar to baseline non-participants than what baseline participants who agree to participate in the re-examination are.

methodsWe compared background characteristics, mortality, and disease incidences across the full population invited to the Malmö Diet and Cancer (MDC) study, the baseline participants, the baseline non-participants, the baseline participants who participated in a re-examination, and the baseline participants who did not participate in the re-examination. We then considered two models for estimating characteristics and outcomes in the full population: one ("the substitution model") assuming that the baseline non-participants were similar to the baseline participants who refused to participate in the re-examination, and one ("the extrapolation model") assuming that differences between the full group of baseline participants and the baseline participants who participated in the re-examination could be extended to infer results in the full population. Finally, we compared prevalences of baseline risk factors including smoking, risky drinking, overweight, and obesity across baseline participants, baseline participants who participated in the re-examination, and baseline participants who did not participate in the re-examination, and used the above models to estimate the prevalences of these factors in the full invited population.

resultsCompared to baseline non-participants, baseline participants were less likely to be immigrants, had higher socioeconomic status, and lower mortality and disease incidences. Baseline participants not participating in the re-examination generally resembled the full population. The extrapolation model often generated characteristics and incidences even more similar to the full population. The prevalences of risk factors, particularly smoking, were estimated to be substantially higher in the full population than among the baseline participants.

conclusionsParticipants in epidemiological cohorts such as the MDC study are unlikely to be representative of the full invited population. Exploiting data on baseline participants who did not participate in a re-examination can be a simple and useful way to improve the generalizability of prevalence and incidence estimates.

Indexed as

ObesityFollow-Up StudiesHumansIncidencePrevalenceSwedenContinuum of resistanceGeneralizabilityMortalityRepresentativityRisk factorsSelf-selection

Identifiers

PMID37821822
PMCPMC10568880

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.