Evidence map›Paper›PMID 35586179›Full record

ArticleJournal of health monitoring2018

Socioeconomic status and subjective social status measurement in KiGGS Wave 2.

Thomas Lampert, Jens Hoebel, Benjamin Kuntz, Stephan Müters, Lars Eric Kroll

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In one paragraph

Article in Journal of health monitoring, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 1 pooled it
–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

87 citing papers in PubMed, 1 synthesis or guideline pooled it.

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27 more citing papers are in PubMed but not listed here.

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.

Thomas LampertRobert Koch Institute, Berlin, Department of Epidemiology and Health Monitoring.
Jens HoebelRobert Koch Institute, Berlin, Department of Epidemiology and Health Monitoring.
Benjamin KuntzRobert Koch Institute, Berlin, Department of Epidemiology and Health Monitoring.
Stephan MütersRobert Koch Institute, Berlin, Department of Epidemiology and Health Monitoring.
Lars Eric KrollRobert Koch Institute, Berlin, Department of Epidemiology and Health Monitoring.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article describes the method applied to measure socioeconomic status (SES) and subjective social status (SSS) in the current wave of the German Health Interview and Examination Survey for Children and Adolescents (KiGGS Wave 2), which was conducted over three years between 2014 and 2017. The composite multidimensional SES index was calculated as a sum of point scores for the parents' education level, occupational status and equivalised disposable income. SSS was assessed in the 11 to 17 year age group using a German version of the MacArthur Scale for children and adolescents. To demonstrate the use of both instruments, we present examples that highlight the association between SES and SSS with the general health of children and adolescents in the 3 to 17 and/or 11 to 17 age groups. Over 95% of parents rated the general health of their children as 'very good' or 'good'. However, the analyses clearly reveal that children and adolescents from families with low SES and SSS have poorer general health than their better-off peers. Even when mutually adjusted, both low SES and SSS are independently associated with poorer general health. In addition to the SES index, studies on the health of children and adolescents should therefore also consider SSS. In this way, additional aspects of the socioeconomic conditions of families can be taken into account.

Indexed as

HEALTH MONITORINGKIGGSMETHODSSOCIOECONOMIC STATUSSUBJECTIVE SOCIAL STATUS

Identifiers

PMID35586179
PMCPMC8848848

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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.