Evidence map›Paper›PMID 36311812›Full record

ArticleStatistical methods & applications2022

When does morbidity start? An analysis of changes in morbidity between 2013 and 2019 in Italy.

Andrea Pastore, Stefano F Tonellato, Emanuele Aliverti, Stefano Campostrini

Abstract read
In one paragraph

Article in Statistical methods & applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

4 authors.

Andrea PastoreDepartment of Economics, Ca' Foscari University, Venice, Italy.ORCID 0000-0001-6165-2932
Stefano F TonellatoDepartment of Economics, Ca' Foscari University, Venice, Italy.
Emanuele AlivertiDepartment of Economics, Ca' Foscari University, Venice, Italy.
Stefano CampostriniDepartment of Economics, Ca' Foscari University, Venice, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Morbidity is one of the key aspects for assessing populations' well-being. In particular, chronic diseases negatively affect the quality of life in the old age and the risk that more years added to lives are years of disability and illness. Novel analysis, interventions and policies are required to understand and potentially mitigate this issue. In this article, we focus on investigating whether in Italy the compression of morbidity is in act in the recent years, parallely to an increase of life expectancy. Our analysis rely on large repeated cross-sectional data from the national surveillance system passi, providing deep insights on the evolution of morbidity together with other socio-demographical variables. In addition, we investigate differences in morbidity across subgroups, focusing on disparities by gender, level of education and economic difficulties, and assessing the evolution of these differences across the period 2013-2019.

Indexed as

Health-statisticsLongevityMorbidity compressionSurveillance system

Identifiers

PMID36311812
PMCPMC9589774

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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.