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Mapping domains of early-life determinants of future multimorbidity across three UK longitudinal cohort studies.

Mapping domains of early-life determinants of future multimorbidity across three UK longitudinal cohort studies.
Mapping domains of early-life determinants of future multimorbidity across three UK longitudinal cohort studies.
Objectives: many studies use a reductionist approach to isolate the influence of one factor in childhood on multimorbidity rather than consider the combined effect of wider determinants. We aimed to explore how potential multiple early-life determinants of multimorbidity can be audited and characterised across three UK cohort studies.


Approach: we used the 1958 National Child Development Study (NCDS), the 1970 British Cohort Study (BCS70), and the Aberdeen Children of the 1950s Study (ACONF) to identify and categorise early-life variables that fit into 12 previously conceptualised domains of early-life determinants of multimorbidity. A data audit manually assigned variables into the domain they best represented. Principal component analysis (PCA) reduced the dimensionality of the data and structured variables into subgroups. Important PCA components defined as the component that contributed the greatest proportion of the overall variance were identified.


Results: seven domains were characterised by 74 va
Stannard, Sebastian
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Berrington, Ann
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Fraser, Simon
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Paranjothy, Shantini
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Hoyle, Rebecca
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Owen, Rhiannon
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Akbari, Ashley
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Shiranirad, Mozhdeh
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Chiovoloni, Roberta
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Alwan, Nisreen
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Stannard, Sebastian
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Berrington, Ann
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Fraser, Simon
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Paranjothy, Shantini
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Hoyle, Rebecca
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Owen, Rhiannon
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Akbari, Ashley
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Shiranirad, Mozhdeh
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Chiovoloni, Roberta
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Alwan, Nisreen
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Stannard, Sebastian, Berrington, Ann, Fraser, Simon, Paranjothy, Shantini, Hoyle, Rebecca, Owen, Rhiannon, Akbari, Ashley, Shiranirad, Mozhdeh, Chiovoloni, Roberta and Alwan, Nisreen (2024) Mapping domains of early-life determinants of future multimorbidity across three UK longitudinal cohort studies. International Journal of Population Data Science, 9 (5). (doi:10.23889/ijpds.v9i5.2559).

Record type: Meeting abstract

Abstract

Objectives: many studies use a reductionist approach to isolate the influence of one factor in childhood on multimorbidity rather than consider the combined effect of wider determinants. We aimed to explore how potential multiple early-life determinants of multimorbidity can be audited and characterised across three UK cohort studies.


Approach: we used the 1958 National Child Development Study (NCDS), the 1970 British Cohort Study (BCS70), and the Aberdeen Children of the 1950s Study (ACONF) to identify and categorise early-life variables that fit into 12 previously conceptualised domains of early-life determinants of multimorbidity. A data audit manually assigned variables into the domain they best represented. Principal component analysis (PCA) reduced the dimensionality of the data and structured variables into subgroups. Important PCA components defined as the component that contributed the greatest proportion of the overall variance were identified.


Results: seven domains were characterised by 74 va

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Published date: 10 September 2024

Identifiers

Local EPrints ID: 495430
URI: http://eprints.soton.ac.uk/id/eprint/495430
PURE UUID: c5ce1812-b1b7-4a2b-a547-76953c2b55cb
ORCID for Sebastian Stannard: ORCID iD orcid.org/0000-0002-6139-1020
ORCID for Ann Berrington: ORCID iD orcid.org/0000-0002-1683-6668
ORCID for Simon Fraser: ORCID iD orcid.org/0000-0002-4172-4406
ORCID for Rebecca Hoyle: ORCID iD orcid.org/0000-0002-1645-1071
ORCID for Mozhdeh Shiranirad: ORCID iD orcid.org/0000-0003-4346-3059
ORCID for Nisreen Alwan: ORCID iD orcid.org/0000-0002-4134-8463

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Date deposited: 13 Nov 2024 17:42
Last modified: 15 Nov 2024 03:07

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Contributors

Author: Sebastian Stannard ORCID iD
Author: Ann Berrington ORCID iD
Author: Simon Fraser ORCID iD
Author: Shantini Paranjothy
Author: Rebecca Hoyle ORCID iD
Author: Rhiannon Owen
Author: Ashley Akbari
Author: Mozhdeh Shiranirad ORCID iD
Author: Roberta Chiovoloni
Author: Nisreen Alwan ORCID iD

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