Evidence map›Paper›PMID 23460045›Full record

ArticleSocial psychiatry and psychiatric epidemiology2013

Associations between community characteristics and psychiatric admissions in an urban area.

Cramer Simone, Losert Carolin, Schmauß Max, Kilian Reinhold

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Article in Social psychiatry and psychiatric epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. The Impacts of Housing Characteristics and Built-Environment Features on Mental Health.International journal of environmental research and public health · 2022
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Cramer SimoneDepartment of Psychiatry and Psychotherapy II, University of Ulm at Bezirkskrankenhaus Günzburg, Günzburg, Germany, simone.cramer@gmail.com.
Losert Carolin
Schmauß Max
Kilian Reinhold

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeNeighbourhood characteristics are known to be associated with higher rates of hospital admission for psychiatric disorders.

methodsAn ecological study with aggregated data was carried out. All cases for schizophrenia and depression in the 42 city districts of Augsburg were identified over a 4-year-period (2006-2009) and neighbourhood variables were obtained. Negative binomial regression adjusted the effects for year of admission and accommodation in inpatient centres.

resultsThere was significant association of high unemployment rate, low proportion of working population and high population density with higher rates of admission for schizophrenia. An increase of 1 % in unemployment rate [incidence rate ration (IRR) 1.0451, 95 % CI 1.0175-1.0734] was associated with 5 % raise of admission rates for schizophrenia and an increase of 1 % in working population (IRR 0.9793, 95 % CI 0.9605-0.9985) with a decrease of admission rates by 2 %. High proportion of single households and high percentage of persons eligible for social security increased admission rate for depression. Thus 1 % increase in the proportion of single households (IRR 1.0095, 95 % CI 1.0030-1.0162) and of the proportion of persons eligible for social security (IRR 1.0148, 95 % CI 1.0002-1.0297) both independently were associated with an increased rate of admission for depression of 1 %.

conclusionOur analysis demonstrated that measures of social isolation in neighbourhoods and social contacts at work influenced admission for schizophrenia and depression: in neighbourhoods with less social contacts and with a higher proportion of persons not working the admission rates increased. The problem of confounding in ecological studies need to be considered.

Indexed as

Residence CharacteristicsSocial EnvironmentCatchment Area, HealthDepressionFactor Analysis, StatisticalFemaleGermanyHealth SurveysHospitalizationHospitals, PsychiatricHousingHumansMaleMiddle AgedRegression AnalysisRisk Factors

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