Evidence map›Paper›PMID 41514439›Full record

ArticlePopulation health metrics2026

The decline of 'Deaths of Despair' in Italy: unveiling this phenomenon in a new context.

Giacomo Lanfiuti Baldi, Andrea Nigri, Sergi Trias-Llimós, Elisabetta Barbi

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Article in Population health metrics, 2026. 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

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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

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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

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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.

Giacomo Lanfiuti BaldiDepartment of Statistics, Sapienza University of Rome, Rome, Italy. giacomo.lanfiutibaldi@uniroma1.it.ORCID 0009-0006-5476-0031
Andrea NigriDepartment of Social Sciences, University of Foggia, Foggia, Italy.ORCID 0000-0002-2707-3678
Sergi Trias-LlimósDepartment of Political and Social Sciences, Pompeu Fabra University, Barcelona, Spain.ORCID 0000-0002-8052-6736
Elisabetta BarbiDepartment of Statistics, Sapienza University of Rome, Rome, Italy.ORCID 0000-0003-2765-8825

Funding

Ministero dell'Università e della Ricerca PRIN 2022 The pre-Covid-19 stall in life expectancy in Italy: looking for explanations
6 · The paper itself

Abstract

backgroundThe term "Deaths of Despair" (DoD) refers to mortality due to alcohol consumption, drug use, and suicides. While extensively studied in the United States, where these deaths have markedly increased, less is known about their patterns in other contexts. This study explores the relevance of this concept to Italy, a country with comparatively lower rates, to determine whether these causes of death exhibit common trends and can be meaningfully grouped under a single category.

methodsWe use cause-specific mortality data from the Italian National Institute of Statistics covering the period 1983 to 2018. Data are aggregated by gender and five-year age groups at the NUTS1 regional level. The Potential Gain in Life Expectancy is used to assess the impact of each cause on overall mortality. To explore potential long-term relationships between the causes and across regions, we apply Cointegration Analysis to the time series.

resultsThe analysis shows a general decline in mortality from causes typically associated with despair in Italy, mainly driven by a reduction in alcohol-related deaths. Drug-related mortality and suicide show more heterogeneous trends across regions and over time. Cointegration Analysis reveals no evidence of long-term dependency among these causes or across regions, with only a few exceptions. This indicates that the observed causes do not share a common underlying temporal structure.

conclusionsFindings suggest that in the Italian context, deaths from alcohol, drugs, and suicide do not follow a unified pattern and should not be treated as a single category. Rather, they represent distinct public health issues with different regional trajectories and determinants. As such, they require targeted and differentiated policy responses rather than a unified approach.

Indexed as

Alcohol DrinkingMortalitySubstance-Related DisordersSuicideCause of DeathFemaleHumansItalyLife ExpectancyMaleAlcoholCauses-of-DeathsDeaths-of-DespairDrugsItalyMortalitySuicide

Identifiers

PMID41514439
PMCPMC12801950

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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.