Evidence map›Paper›PMID 31365105›Full record

ArticleJAMA network open2019

Assessment of Relative Utility of Underlying vs Contributory Causes of Death.

G David Batty, Catharine R Gale, Mika Kivimäki, Steven Bell

Abstract read
In one paragraph

Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  10. Risk factors for lung cancer in never-smokers: Multi-cohort study.medRxiv : the preprint server for health sciences · 2025
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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.

G David BattySchool of Biological and Population Health Sciences, Oregon State University, Corvallis.
Catharine R GaleMedical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom.
Mika KivimäkiDepartment of Epidemiology and Public Health, University College London, London, United Kingdom.
Steven BellCardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Funding

British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946Medical Research Council G0700704Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MR/S011676/1
6 · The paper itself

Abstract

Importance: In etiological research, investigators using death certificate data have traditionally extracted underlying cause of mortality alone. With multimorbidity being increasingly common, more than one condition is often compatible with the manner of death. Using contributory cause plus underlying cause would also have some analytical advantages, but their combined utility is largely untested. Objective: To compare the relative utility of cause of death data extracted from the underlying cause field vs any location on the death certificate (underlying and contributing combined). Design, Setting, and Participants: This study compares the association of 3 known risk factors (cigarette smoking, low educational attainment, and hypertension) with health outcomes based on where cause of death data appears on the death certificate in 2 prospective cohort study collaborations (UK Biobank [N = 502 655] and the Health Survey for England [15 studies] and the Scottish Health Surveys [3 studies] [HSE-SHS; N = 193 873]). Data were collected in UK Biobank from March 2006 to October 2010 and in HSE-SHS from January 1994 to December 2008. Data analysis began in June 2018 and concluded in June 2019. Main Outcomes and Measures: Death from cardiovascular disease, cancer, dementia, and injury. For each risk factor-mortality end point combination, a ratio of hazard ratios (RHR) was computed by dividing the effect estimate for the underlying cause by the effect estimate for any mention. Results: In UK Biobank, there were 14 421 deaths (2.9%) during a mean (SD) of 6.99 (1.03) years of follow up; in HSE-SHS, there were 21 314 deaths (11.0%) during a mean (SD) of 9.61 (4.44) years of mortality surveillance. Established associations of risk factors with death outcomes were essentially the same irrespective of placement of cause on the death certificate. Results from each study were mutually supportive. For having ever smoked cigarettes (vs never having smoked) in the UK Biobank, the RHR for cardiovascular disease was 0.98 (95% CI, 0.87-1.10; P value for difference = .69); for cancer, the RHR was 0.99 (95% CI, 0.93-1.05; P value for difference = .69). In the HSE-SHS, the RHR for cardiovascular disease was 0.94 (95% CI, 0.87-1.01; P value for difference = .09); for cancer, it was 1.01 (95% CI, 0.94-1.10; P value for difference = .75). Conclusions and Relevance: Risk factor-end point associations were not sensitive to the placement of data on the death certificate. This has implications for the examination of the association of risk factors with causes of death where there may be too few events to compute reliable effect estimates based on the underlying field alone.

Indexed as

Cause of DeathDeath CertificatesAdultAgedCardiovascular DiseasesCigarette SmokingEducational StatusFemaleHealth SurveysHumansHypertensionMaleMiddle AgedNeoplasmsPopulation SurveillanceProportional Hazards Models

Identifiers

PMID31365105
PMCPMC6669894

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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.