Evidence map›Paper›PMID 39379988›Full record

ArticleBMC medicine2024

Association of weight change with all-cause and cause-specific mortality: an age-stratified analysis.

Qing-Mei Huang, Dong Shen, Jian Gao, Huan Chen, Jia-Hao Xie, Hao-Yu Yan, Bin Wu, Zhi-Hao Li, Gang Liu, Chen Mao

Abstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

10 authors.

Qing-Mei HuangDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Dong ShenDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Jian GaoDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Huan ChenDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Jia-Hao XieDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Hao-Yu YanDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Bin WuDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Zhi-Hao LiDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Gang LiuShenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China.
Chen MaoDepartment of Epidemiology, School of Public Health, Southern Medical University, No. 1023-1063, Satai South Road, Baiyun District, Guangzhou, Guangdong, 510515, China. maochen9@smu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe associations of weight change with all-cause and cause-specific mortality stratified by age remains unclear. We evaluated the age-stratified (< 65 vs ≥ 65 years) associations of weight change with all-cause and cause-specific mortality in a large sample of Chinese adults.

methodsOur cohort study included 746,991 adults aged at least 45 years from the Shenzhen Healthcare Big Data Cohort in China. BMI change were categorized as change within 5% (stable), decrease by 5% to 10%, decrease by > 10%, increase by 5% to 10%, and increase by > 10%. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause, non-communicable disease, cardiovascular disease (CVD), and cancer mortality according to BMI change, with adjustment for potential confounders.

resultsDuring a median follow-up of 2.2 years (2,330,180 person-years), there were 10,197 deaths. A notable interaction emerged between weight change and age. For participants ≥ 65 years, compared with stable BMI, more than a 10% decrease in BMI was associated with higher risk of all-cause mortality (HR: 1.69, 95% CI: 1.54-1.86), non-communicable disease mortality (HR: 1.67, 95% CI: 1.52-1.84), CVD mortality (HR: 1.55, 95% CI: 1.34-1.80), and cancer mortality (HR: 1.59, 95% CI: 1.33-1.92). Similar patterns of results for 5% to 10% decrease in BMI were observed. More than a 10% increase in BMI was associated with increased risk of all-cause mortality (HR: 1.13, 95% CI: 1.04-1.24), non-communicable disease mortality (HR: 1.14, 95% CI: 1.04-1.25), and CVD mortality (HR: 1.27, 95% CI: 1.12-1.44). For participants < 65 years, only more than a 10% decrease in BMI was associated with higher risk of all-cause mortality (HR: 1.41, 95% CI: 1.12-1.77), non-communicable disease mortality (HR: 1.43, 95% CI: 1.13-1.81), and cancer mortality (HR: 1.79, 95% CI: 1.29-2.47).

conclusionsWeight loss and excessive weight gain were associated with increased risks of mortality among older adults, while only excessive weight loss was associated with increased risks of mortality among middle-aged adults.

Indexed as

Body Mass IndexCardiovascular DiseasesAgedAge FactorsCause of DeathChinaCohort StudiesFemaleHumansMaleMiddle AgedNeoplasmsNoncommunicable DiseasesProportional Hazards ModelsRisk FactorsWeight GainAll-cause mortalityCancer mortalityCohort StudyCVD mortalityWeight change

Identifiers

PMID39379988
PMCPMC11462817

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.