Evidence map›Paper›PMID 38455912›Full record

ArticleFrontiers in epidemiology2023

Projected incidence trends of need for long-term care in German men and women from 2011 to 2021.

Sabrina Voß, Stephanie Knippschild, Luisa Haß, Thaddäus Tönnies, Ralph Brinks

Abstract read
In one paragraph

Article in Frontiers in epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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.

Sabrina VoßFaculty of Health, School of Medicine, Chair for Medical Biometry and Epidemiology, Witten/Herdecke University, Witten, Germany.
Stephanie KnippschildFaculty of Health, School of Medicine, Chair for Medical Biometry and Epidemiology, Witten/Herdecke University, Witten, Germany.
Luisa HaßFaculty of Health, School of Medicine, Chair for Medical Biometry and Epidemiology, Witten/Herdecke University, Witten, Germany.
Thaddäus TönniesFaculty of Health, School of Medicine, Chair for Medical Biometry and Epidemiology, Witten/Herdecke University, Witten, Germany.
Ralph BrinksFaculty of Health, School of Medicine, Chair for Medical Biometry and Epidemiology, Witten/Herdecke University, Witten, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The German Federal Statistical Office routinely collects and reports aggregated numbers of people in need of long-term care (NLTC) stratified by age and sex. Age- and sex-specific prevalence of NLTC from 2011 to 2021 is reported as well. One estimation of the incidence rate of NLTC based on the age- and sex-specific prevalence exists that did not explore possible trends in incidence [based on MRR (mortality rate ratio)], which is important for an adequate projection of the future number of people with NLTC. Objective: We aim to explore possible trends in age-specific incidence of NLTC in German men and women from 2011 to 2021 based on different scenarios about excess mortality (in terms of MRR). Methods: The incidence of NLTC was calculated based on an illness-death model and a related partial differential equation based on data from the Federal Statistical Office. Estimation of annual percent change (APC) of the incidence rate was conducted in eight scenarios. Results: There are consistent indications for trends in incidence for men and women aged 50-79 years with APC in incidence rate of more than +9% per year (up to nearly 19%). For ages 80+ the APC is between +0.4% and +12.5%. In all scenarios, women had higher age-specific APCs than men. Conclusion: We performed the first analysis of APC in the age- and sex-specific incidence rate of NLTC in Germany and revealed an increasing trend in the incidences. With these findings, a future prevalence of NLTC can be estimated which may exceed current prognoses.

Indexed as

aggregated datachronic conditionsepidemiologyfrailtyillness-death modellong-term carepartial differential equation

Identifiers

PMID38455912
PMCPMC10910887

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