Evidence map›Paper›PMID 36429428›Full record

ArticleInternational journal of environmental research and public health2022

Cumulative Health Drivers of Overnight Hospitalization for Australian Working-Age Adults Living Alone: The Early Warning Potential of Functionality.

John Rodwell

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 76% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

John RodwellDepartment of Management & Marketing, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0003-1682-0719
Swinburne University of Technology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a need to better understand the drivers of hospital utilization for the large and growing number of adults living alone. The cumulative effect of health drivers can be assessed by initially considering clinically advised information, then considering issues that a general practitioner or the person themselves may know. Logistic regression analyses were conducted on longitudinal data from the Household, Income, and Labor Dynamics in Australia (HILDA) survey with three time points over four years (n = 1019). The significant predictors of overnight hospitalization were the presence of a long-term health condition (Time 1), hospitalization severity and comorbidity (Time 1), work ability (Time 2), physical functioning (Time 2), being separated/divorced and having one or more health care cards. Health issues were predictive up to four years before the hospitalization window. That baseline risk of hospitalization was modified as symptoms and relatively salient changes in functionality accumulated. Specific sub-groups of hospital users had access due to insurance or special coverage. The impact of living alone on hospitalization may be able to be partly addressed through interventions such as improving access to primary care and using early warning triggers such as decreasing functionality to seek primary care before seeking hospitalization.

Indexed as

Home EnvironmentHospitalizationAdultAustraliaHumansIncomeSurveys and Questionnairesaccumulationhealth insurancehealth trajectoryhospitalizationliving alonephysical functioningwork ability

Identifiers

PMID36429428
PMCPMC9689992
OpenAlexW4308869578

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.