Evidence map›Paper›PMID 41665810›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2026

The Impact of Neighbours and Neighbourhoods on Major Depressive Disorders in Adults.

Anna Tort-Carrera, J Paul Elhorst, Govert E Bijwaard

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2026. 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
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.

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

3 authors.

Anna Tort-CarreraNetherlands Interdisciplinary Demographic Institute (NIDI)-Royal Netherlands Academy of Sciences (KNAW), The Hague, The Netherlands. a.tort.carrera@rug.nl.ORCID http://orcid.org/0000-0001-8142-5972
J Paul ElhorstFaculty of Economics and Business, University of Groningen (RUG), Groningen, The Netherlands.
Govert E BijwaardNetherlands Interdisciplinary Demographic Institute (NIDI)-Royal Netherlands Academy of Sciences (KNAW), The Hague, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major Depressive Disorder (MDD) is a significant global health concern, yet the influence of social interactions among individual neighbours, in addition to neighbourhood characteristics, remains underexplored. This study applies linear-in-means models and spatial econometric techniques to examine whether and which social interactions influence MDD among adults. The data used relate to two repeated cross-sections of 19,700 individuals aged 23 to 65 years collected via the MINI neuropsychiatric interview in two waves of the Lifelines Cohort Study in Northern Netherlands, supplemented with neighbourhood-level information from Statistics Netherlands. Three types of social interactions - peer, contextual, and correlated - are assessed, with Bayesian comparison tests identifying contextual and correlated effects as the most influential. Subsequently, a two-step regression model is employed to address the high prevalence of zero outcomes. The results highlight the influence of contextual and correlated effects among individual neighbours, in addition to individual and neighbourhood characteristics. These findings emphasise the need for further research into social interactions on MDD and support for public health interventions that take them into account.

Indexed as

Major Depressive DisorderNeighborhood CharacteristicsResidence CharacteristicsSocial InteractionAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedNetherlandsYoung AdultLifelinesLinear-in-means modelMDDSocial interaction effects

Identifiers

PMID41665810
PMCPMC13235667

What OpenQuestion holds

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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.