Evidence map›Paper›PMID 23906947›Full record

ArticleBMJ open2013

Mortality risks in relation to occupational category and position among the Japanese working population: the Jichi Medical School (JMS) cohort study.

Kumi Hirokawa, Akizumi Tsutsumi, Kazunori Kayaba, Jichi Medical Cohort study group

Abstract read
In one paragraph

Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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.

Kumi HirokawaDepartment of Nursing, Baika Women's University, Ibaraki, Osaka, Japan.
Akizumi Tsutsumi
Kazunori Kayaba
Jichi Medical Cohort study group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesA well-known demographic finding in modern society is the inverse association between socioeconomic status and mortality. The purpose of the study was to examine socioeconomic indicators, such as occupational category (white-collar vs blue -collar) and occupational position (managerial vs non-managerial) as determinants of all -cause, cardiovascular disease (CVD) and cancer mortality in a Japanese working population.

designThis is a prospective study.

participantsData of a baseline survey were collected between 1992 and 1995, and ultimately 6929 Japanese workers aged 65 years and younger (3333 men and 3596 women) from 12 rural communities across Japan were followed until the end of 2005.

main outcome measuresThe HRs of death and 95% CIs from all causes were calculated using the Cox proportional hazard model.

resultsMen in blue-collar jobs showed an increased all-cause mortality risk compared with those in white-collar jobs (HR 1.64, 95% CI 1.10 to 2.45). Stratified by occupational category, non-managerial women in blue-collar jobs showed a decreased CVD mortality risk compared with managerial women (HR 0.15, 95% CI 0.03 to 0.81), after adjusting for confounding factors. However, non-managerial women in white-collar jobs showed an increased mortality risk compared with managerial women, although this was not significant (HR 2.34, 95% CI 0.25 to 21.87).

conclusionsSocioeconomic disparity according to occupational category was related to the risk of all-cause mortality among Japanese men. There is a potential interaction of occupational category and position in CVD mortality among Japanese women.

Indexed as

OCCUPATIONAL & INDUSTRIAL MEDICINEPUBLIC HEALTH

Identifiers

PMID23906947
PMCPMC3733305

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.