Multimorbidity and the household context: measurement and associations with health and social care use
dc.contributor.advisor
Guthrie, Bruce
dc.contributor.advisor
Dibben, Chris
dc.contributor.advisor
Lone, Nazir
dc.contributor.advisor
Mercer, Stewart
dc.contributor.author
MacRae, Clare
dc.contributor.sponsor
Medical Research Council (MRC)
en
dc.date.accessioned
2025-08-01T12:31:11Z
dc.date.available
2025-08-01T12:31:11Z
dc.date.issued
2025-08-01
dc.description.abstract
BACKGROUND:
Multimorbidity (multiple long-term conditions) presents significant challenges to
health and social care systems worldwide, especially as populations age and more
older adults live alone. The impact of multimorbidity in households on unplanned
hospitalisation and transitioning to live in a care home is an under-explored area of
study that might present opportunities for developing interventions.
METHODS:
First, I explored the implications of making different methodological choices when
measuring multimorbidity to ensure consistency in my studies. I did this by
comparing the estimated prevalence of multimorbidity when varying the number and
selection of long-term conditions considered in the count. Then, I examined the
impact of the choice of data source (namely primary care, hospital inpatient, and
primary care linked to hospital inpatient data) on multimorbidity prevalence
ascertainment and the likelihood of mortality. The results of these studies informed
my selection of long-term conditions and choice of data sources in the following two
studies.
Second, I examined the associations between multimorbidity in households and
unplanned hospitalisation and transitioning to live in a care home. To do this, I
explored how the association between an individual’s multimorbidity status
(categorised as 0-1, 2-3, and ≥4 long-term conditions) and the hazard of these two
outcomes varied by household size (categorised as 1, 2, and ≥3 residents) in a
population of adults aged ≥65. I then examined the impact of household size and the
multimorbidity status of household co-residents on unplanned hospitalisations and
transitioning to live in a care home in a study of adults aged ≥18. I used multistate
models that incorporated household random effects and accounted for the
competing risk of death, examining the outcomes of unplanned hospitalisation and
transitioning to live in a care home in separate models.
I conducted all studies using large population-based datasets, including linked
primary care and hospital inpatient records, from England using the Clinical
Population Research Datalink and Wales using the SAIL Databank.
RESULTS:
In a cross-sectional analysis of 1,168,620 individuals of all ages living in England,
multimorbidity prevalence estimates varied widely depending on the number and
selection of long-term conditions considered in counts. When only the two most
common long-term conditions were considered, multimorbidity prevalence was 4.6%
(95% CI 4.6-4.6) but was substantially higher (40.5%, 95% CI 40.4-40.6) when all
the long-term conditions in the study (80) were included in the count. A ceiling where
the prevalence reached over 99% of that reached when all 80 long-term conditions
were included occurred when considering the 52 most prevalent long-term
conditions. Using a list of long-term conditions recommended in a recent Delphi
study resulted in multimorbidity prevalence estimates close to this threshold.
Using primary care linked to hospital inpatient data, compared to hospital inpatient
data, multimorbidity was substantially more prevalent (32.2% versus 16.5%) in a
second cross-sectional analysis, including 2,340,027 individuals of all ages living in
Wales. Additionally, for the same comparison, those with multimorbidity were
younger (mean age 62.5 versus 66.8), a higher proportion of women (54.2% versus
52.6%), and had a higher likelihood of 1-year mortality (in people with ≥4 versus 0-1
long-term conditions the adjusted odds ratio was 8.34 [95% CI 8.02-8.68] using
linked, but 6.95 (95%CI 6.79-7.12] when the same comparison was made using
hospital inpatient data).
In my cohort study of 391,686 adults living in Wales and aged ≥65, 36.8% lived
alone, 54.0% lived in two-person, and 9.2% lived in three-or-more-person
households. The number of long-term conditions was strongly associated with
hospitalisation and care home transition (e.g., in two-person households, ≥4 long-
term conditions versus 0-1 long-term conditions, adjusted hazard ratio [aHR] 2.46
[95%CI 2.42-2.50] for hospitalisation and 3.00 [95%CI 2.90-3.10] for care home).
The association between the number of long-term conditions and unplanned
hospitalisation and care home transition varied by household size, with the
association being less pronounced in those living alone. Household size was
modestly associated with unplanned hospitalisation but more strongly associated
with care home transition (e.g., in people with 0-1 long-term conditions, living alone
versus in a two-person household, aHR 1.20 [95%CI 1.17-1.22] for hospitalisation
and 1.45 [95%CI 1.39-1.51] for care home transition). The risk of care home
transition was similar for people with 0-1 long-term conditions who lived alone and
those who had 2-3 long-term conditions who lived in a two-person household.
The highest unplanned hospitalisation and care home transition rates were in those
living alone (92.0 and 5.9 events/1000 person-years, respectively) in my final study,
including 1,472,185 individuals aged ≥18 years and living in Wales. Event rates for
both outcomes were lower in all shared households and lowest when co-residents
did not have multimorbidity. In three-or-more-person households, compared to living
alone, the aHR for unplanned hospitalisation was lowest when co-residents did not
have multimorbidity (0.87, 95%CI 0.86-0.88) and intermediate when at least one co-
resident did have multimorbidity (0.92, 95%CI 0.91-0.93). Differences were more
substantial for care home transition, for example, living with co-residents without
multimorbidity aHR 0.57, 95% CI 0.55-0.59, or with at least one co-resident with
multimorbidity aHR 0.78, 95% CI 0.75-0.80).
CONCLUSIONS:
The prevalence of multimorbidity varied substantially depending on the number of
long-term conditions considered in the count and the data source used. Therefore,
consistency of measurement is needed to achieve consistent results across studies.
Household size, an individual’s multimorbidity status, and their co-resident’s
multimorbidity status modestly increased the risk of unplanned hospitalisation and
more substantially increased the risk of transitioning to live in a care home. However,
living alone was associated with the greatest hazard in all models.
Understanding
the mechanisms of the associations between household composition and co-resident
health status with these outcomes is important to develop targeted strategies that
support healthy and independent living.
en
dc.identifier.uri
https://hdl.handle.net/1842/43757
dc.identifier.uri
http://dx.doi.org/10.7488/era/6290
dc.language.iso
en
en
dc.publisher
The University of Edinburgh
en
dc.relation.hasversion
MacRae C, Mercer SW, Henderson D, et al. Age, sex, and socioeconomic differences in multimorbidity measured in four ways: UK primary care cross-sectional analysis. Br J Gen Pract 2023:BJGP.2022.0405. doi: 10.3399/BJGP.2022.0405
en
dc.relation.hasversion
MacRae C, McMinn M, Mercer SW, et al. The impact of varying the number and selection of conditions on estimated multimorbidity prevalence: A cross-sectional study using a large, primary care population dataset. PLoS Med 2023;20(4):e1004208-e08. doi: 10.1371/journal.pmed.1004208
en
dc.relation.hasversion
MacRae C, Morales D, Mercer SW, et al. Impact of data source choice on multimorbidity measurement: a comparison study of 2.3 million individuals in the Welsh National Health Service. BMC Med 2023;21(1):1-309. doi: 10.1186/s12916-023-02970-z
en
dc.relation.hasversion
C, Whittaker H, Mukherjee M, et al. Deriving a Standardised Recommended Respiratory Disease Codelist Repository for Future Research. Pragmatic and observational research 2022;13:1. doi: 10.2U7/POR.S353400
en
dc.relation.hasversion
MacRae C, McMinn M, Mercer S, et al. The impact of varying the number and selection of conditions on estimated multimorbidity prevalence: a cross-sectional study using a large, primary care population dataset. PLOS Medicine April 2023 https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004208
en
dc.relation.hasversion
MacRae C, Fisken HW, Lawrence E, et al. Household and area determinants of emergency department attendance and hospitalisation in people with multimorbidity: a systematic review. BMJ open 2022;12(10):e063441-e41. doi: 10.1136/bmjopen-2022-063441
en
dc.relation.hasversion
MacRae C, Morales D, Mercer SM. Impact of data source choice on multimorbidity measurement: a comparison study of 2.3 million individuals in the Welsh National Health Service. BMC Medicine 2023 https://doi.org/10.1186/s12916-023-02970-z
en
dc.relation.hasversion
MacRae C, McMinn M, Mercer SW, et al. The impact of varying the number and selection of conditions on estimated multimorbidity prevalence::a cross-sectional study using a large, primary care population dataset. 2023
en
dc.rights.embargodate
2026-08-01
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dc.subject
Multimorbidity
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dc.subject
Household context
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dc.subject
Unplanned hospitalisation
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dc.subject
Care home transition
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dc.subject
Data sources
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dc.title
Multimorbidity and the household context: measurement and associations with health and social care use
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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dcterms.accessRights
RESTRICTED ACCESS
en
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