Evidence map›Paper›PMID 35733122›Full record

ArticleBMC geriatrics2022

Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis.

Tina Sadarangani, Carla Perissinotto, Jonelle Boafo, Jie Zhong, Gary Yu

Abstract read
In one paragraph

Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Article
  2. A National Survey of Day Care Centers Hosting People With Dementia in Italy.International journal of geriatric psychiatry · 2025
    Article
  3. Article
  4. Review
  5. Article
  6. Article
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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

5 authors.

Tina SadaranganiNew York University Rory Meyers College of Nursing, 433 First Avenue, New York, NY, 10010, USA. trs233@nyu.edu.
Carla PerissinottoUniversity of California San Francisco School of Medicine, Division of Geriatrics, 490 Illinois Street, San Francisco, CA, 94158, USA.
Jonelle BoafoNew York University Rory Meyers College of Nursing, 433 First Avenue, New York, NY, 10010, USA.
Jie ZhongNew York University Rory Meyers College of Nursing, 433 First Avenue, New York, NY, 10010, USA.
Gary YuNew York University Rory Meyers College of Nursing, 433 First Avenue, New York, NY, 10010, USA.

Funding

Training Core (I)U54AG063546 · NIA · BROWN UNIVERSITY · PI Heather Gwynn Allore · 2019 to 2026
$125.9M
Leveraging mobile health technology to reduce avoidable healthcare utilization in persons with Alzheimer's Disease and Related Dementias in adult day centersK23AG071948 · NIA · NEW YORK UNIVERSITY · PI SADARANGANI, TINA · 2021 to 2025
$1.1M
Bridging Communication Gaps between Primary Care Providers and Adult Day Service Centers to Reduce Emergency Department Use and Hospitalizations among Persons with DementiaR21AG069801 · NIA · NEW YORK UNIVERSITY · PI SADARANGANI, TINA · 2020 to 2021
$793k
NIA NIH HHS K23 AG071948NIA NIH HHS R21 AG069801
6 · The paper itself

Abstract

backgroundPersons living with dementia (PLWD) in adult day centers (ADCs) represent a complex and vulnerable population whose well-being is at risk based on numerous factors. Greater knowledge of the interaction between dementia, chronic conditions, and social determinants of health would enable ADCs to identify and target the use of their resources to better support clients in need of in-depth intervention. The purpose of this paper is to (a) classify PLWD in ADCs according to their level of medical complexity and (b) identify the demographic, functional, and clinical characteristics of those with the highest degree of medical complexity.

methodsThis was a secondary data analysis of 3052 clients with a dementia diagnosis from 53 ADCs across the state of California between 2012 and 2019. The most common diagnosis codes were organized into 28 disease categories to enable a latent class analysis (LCA). Chi-square test, analysis of variance (ANOVA), and Kruskal-Wallis tests were conducted to examine differences among latent classes with respect to clinical and functional characteristics.

resultsAn optimal 4-class solution was chosen to reflect chronic conditions among PLWD: high medical complexity, moderate medical complexity, low medical complexity, and no medical complexity. Those in the high medical complexity were taking an average of 12.72 (+/- 6.52) medications and attending the ADC an average of 3.98 days (+/- 1.31) per week-values that exceeded any other class. They also experienced hospitalizations more than any other group (19.0%) and met requirements for the nursing facility level of care (77.4%). In addition, the group experienced the greatest frequency of bladder (57.5%) and bowel (15.7%) incontinence.

conclusionsOur results illustrate a high degree of medical complexity among PLWD in ADCs. A majority of PLWD not only have multimorbidity but are socially disadvantaged. Our results demonstrate that a comprehensive multidisciplinary approach that involves community partners such as ADCs is critically needed that addresses functional decline, loneliness, social isolation, and multimorbidity which can negatively impact PLWD.

Indexed as

DementiaMultimorbidityChronic DiseaseHumansLatent Class AnalysisPalliative CareAdult Day CareAlzheimer's DiseaseLatent Class AnalysisMultiple Chronic Conditions

Identifiers

PMID35733122
PMCPMC9216285

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LicenceCC BY
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Registered trials

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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.