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.

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Nilsson, AntonLund University,Lunds universitet,EPI@LUND,Forskargrupper vid Lunds universitet,Lund University Research Groups (author)

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.

Article/chapterEnglish2023

Publisher, publication year, extent ...

BioMed Central (BMC),2023

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LIBRIS-ID:oai:gup.ub.gu.se/331016
https://gup.ub.gu.se/publication/331016URI
https://doi.org/10.1186/s12874-023-02053-wDOI
https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-97450URI
https://lup.lub.lu.se/record/cbb1d09c-d180-4f3e-b3fd-de16a61a18e7URI

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Language:English

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Subject category:ref swepub-contenttype
Subject category:art swepub-publicationtype

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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.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.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.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.

Subject headings and genre

NATURVETENSKAP Matematik Sannolikhetsteori och statistik hsv//swe
NATURAL SCIENCES Mathematics Probability Theory and Statistics hsv//eng
MEDICIN OCH HÄLSOVETENSKAP Hälsovetenskap Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi hsv//swe
MEDICAL AND HEALTH SCIENCES Health Sciences Public Health, Global Health, Social Medicine and Epidemiology hsv//eng
Humans
Incidence
Prevalence
Follow-Up Studies
Sweden
epidemiology
Obesity
Generalizability
Risk and Environmental Studies
Continuum of resistance
Generalizability
Mortality
Representativity
Risk factors
Self-selection

Added entries (persons, corporate bodies, meetings, titles ...)

Björk, JonasLund University,Lunds universitet,EPI@LUND,Forskargrupper vid Lunds universitet,Lund University Research Groups,Skåne University Hospital(Swepub:lu)ymed-jbj (author)
Strömberg, Ulf,1964Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för samhällsmedicin och folkhälsa,Institute of Medicine, School of Public Health and Community Medicine,University of Gothenburg, Sweden(Swepub:gu)xstrou (author)
Bonander, CarlKarlstad University,Karlstads universitet,Gothenburg University,Göteborgs universitet,Institutionen för medicin, avdelningen för samhällsmedicin och folkhälsa,Institute of Medicine, School of Public Health and Community Medicine,Centrum för forskning om samhällsrisker, CSR (från 2020),University of Gothenburg, Sweden(Swepub:kau)carlbona (author)
EPI@LUNDForskargrupper vid Lunds universitet (creator_code:org_t)

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In:BMC Medical Research Methodology: BioMed Central (BMC)23:11471-2288

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By the author/editor: Nilsson, Anton; Björk, Jonas; Strömberg, Ulf, ...; Bonander, Carl

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NATURAL SCIENCES: NATURAL SCIENCES; and Mathematics; and Probability Theo ...

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Health Sciences; and Public Health Gl ...

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By the university: University of Gothenburg; Karlstad University; Lund University

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