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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

BACKGROUND: Participants 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...

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Autores principales: Nilsson, Anton, Björk, Jonas, Strömberg, Ulf, Bonander, Carl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568880/
https://www.ncbi.nlm.nih.gov/pubmed/37821822
http://dx.doi.org/10.1186/s12874-023-02053-w
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author Nilsson, Anton
Björk, Jonas
Strömberg, Ulf
Bonander, Carl
author_facet Nilsson, Anton
Björk, Jonas
Strömberg, Ulf
Bonander, Carl
author_sort Nilsson, Anton
collection PubMed
description BACKGROUND: Participants 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. METHODS: We 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. RESULTS: Compared 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. CONCLUSIONS: Participants 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-02053-w.
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spelling pubmed-105688802023-10-13 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 Nilsson, Anton Björk, Jonas Strömberg, Ulf Bonander, Carl BMC Med Res Methodol Research BACKGROUND: Participants 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. METHODS: We 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. RESULTS: Compared 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. CONCLUSIONS: Participants 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-02053-w. BioMed Central 2023-10-11 /pmc/articles/PMC10568880/ /pubmed/37821822 http://dx.doi.org/10.1186/s12874-023-02053-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Nilsson, Anton
Björk, Jonas
Strömberg, Ulf
Bonander, Carl
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568880/
https://www.ncbi.nlm.nih.gov/pubmed/37821822
http://dx.doi.org/10.1186/s12874-023-02053-w
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