Evidence map›Paper›PMID 24586936›Full record

ArticlePloS one2014

Adverse lifestyle leads to an annual excess of 2 million deaths in China.

G Neil Thomas, Man Ping Wang, Sai Yin Ho, Kwok Hang Mak, Kar Keung Cheng, Tai Hing Lam

Registry-linked trialAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04025151 (Nurse-led Alcohol Brief Intervention Plus Mobile Personalized Chat-based Support on Reducing Alcohol Use in University Students), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT04025151 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Nurse-led Alcohol Brief Intervention Plus Mobile Personalized Chat-based Support on Reducing Alcohol Use in University Students: a Pragmatic Randomized Controlled Trial

TypeinterventionalSponsorThe University of Hong KongRan2020 to 2022Enrolled770ConditionsAlcohol MisuseArmsAlcohol brief intervention, 12-page health warning leaflet, Regular messages through Instant Messaging (IM), Real-time chat-based support through IM Apps, General health through SMS
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Trial
  2. Review
  3. 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

6 authors.

G Neil ThomasPublic Health, Epidemiology, and Biostatistics, University of Birmingham, Birmingham, United Kingdom ; Institute of Public Health, Social and Preventive Medicine, Mannheim Medical Faculty, University of Heidelberg, Mannheim, Germany.
Man Ping WangSchool of Nursing, University of Hong Kong, Hong Kong SAR, China.
Sai Yin HoSchool of Public Health, University of Hong Kong, Hong Kong SAR, China.
Kwok Hang MakDepartment of Health, Hong Kong SAR Government, Hong Kong SAR, China.
Kar Keung ChengPublic Health, Epidemiology, and Biostatistics, University of Birmingham, Birmingham, United Kingdom.
Tai Hing LamSchool of Public Health, University of Hong Kong, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdverse lifestyle factors have been associated with increased mortality, but data are lacking on their combined effect in developing populations, which we address in the present study.

methodsIn a death registry-based, case-control study among Hong Kong Chinese aged 30+y, proxy-reported lifestyle factors 10 y ago were collected for 21,363 cases (81% of all deaths) and 12,048 living controls. Risks associated with poor diet, inactivity, heavy alcohol intake, and smoking for all-cause and cause-specific mortality, adjusting for potential confounders, were determined, and excess deaths for the Chinese population were calculated.

resultsAdjusted odds ratios for all-cause mortality were 1.15 (95% CI 1.09, 1.23), 1.34 (1.27, 1.43), 1.36 (1.21, 1.52), and 1.58 (1.46, 1.70) for poor diet, inactivity, heavy alcohol intake and smoking, respectively. Increasing numbers of adverse lifestyle factors were associated with a dose-dependent increase in adjusted odds ratios of 1.30 (1.20, 1.40), 1.67 (1.54, 1.81), 2.32 (2.08, 2.60), and 3.85 (3.12, 4.75) for 1, 2, 3, and 4 risk factors relative to those with none. The population attributable fraction for all-cause, all-CVD and all-cancer mortality were 26.6%, 15.0%, and 32.1%, resulting in an excess of 2,017,541; 489,884; and 607,517 deaths annually, respectively. Although smoking was associated with the greatest excess loss of life (867,530), heavy drinking (680,466), and physical inactivity (678,317) were similarly important.

conclusionAdverse lifestyle factors contribute to one quarter of all deaths in China. Improving lifestyle practices, particularly focussing on moderating alcohol intake and increasing activity, and smoking cessation are critical to reducing the lifestyle-associated health burden.

Indexed as

Cause of DeathLife StyleAdultAgedAlcohol DrinkingAsian PeopleCase-Control StudiesDietFemaleHong KongHumansMaleMiddle AgedMotor ActivityNeoplasmsRegistries

Identifiers

PMID24586936
PMCPMC3935915

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Registered trials

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.