Evidence map›Paper›PMID 36965505›Full record

ArticleJournal of the American Medical Directors Association2023

Development and Validation of a Lifespan Prediction Model in Chinese Adults Aged 65 Years or Older.

Jinhui Zhou, Chen Chen, Jun Wang, Sixin Liu, Xinwei Li, Yuan Wei, Lihong Ye, Jiaming Ye, Virginia Byers Kraus, Yuebin Lv and 1 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Directors Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Jinhui ZhouChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Chen ChenChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Jun WangChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Sixin LiuChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China.
Xinwei LiChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
Yuan WeiChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
Lihong YeChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jiaming YeChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.
Virginia Byers KrausDuke Molecular Physiology Institute and Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
Yuebin LvChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoming ShiChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. Electronic address: shixm@chinacdc.cn.

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI CATHLEEN S COLON-EMERIC, Susan Nicole Hastings · 2006 to 2026
$24.6M
NIA NIH HHS P30 AG028716
6 · The paper itself

Abstract

objectivesPrevious studies investigated factors associated with mortality. Nevertheless, evidence is limited regarding the determinants of lifespan. We aimed to develop and validate a lifespan prediction model based on the most important predictors.

designA prospective cohort study. SETTING AND

participantsA total of 23,892 community-living adults aged 65 years or older with confirmed death records between 1998 and 2018 from 23 provinces in China.

methodsInformation including demographic characteristics, lifestyle, functional health, and prevalence of diseases was collected. The risk prediction model was generated using multivariate linear regression, incorporating the most important predictors identified by the Lasso selection method. We used 1000 bootstrap resampling for the internal validation. The model performance was assessed by adjusted R

resultsTwenty-one predictors were included in the final lifespan prediction model. Older adults with longer lifespans were characterized by older age at baseline, female, minority race, living in rural areas, married, with healthier lifestyles and more leisure engagement, better functional status, and absence of diseases. The predicted lifespans were highly consistent with observed lifespans, with an adjusted R CONCLUSIONS AND IMPLICATIONS: The lifespan prediction model was validated with good performance, the web-based prediction tool can be easily applied in practical use as it relies on all easily accessible variables.

Indexed as

East Asian PeopleLongevityAgedFemaleHumansIndependent LivingLife StyleLinear ModelsMaleProspective Studiesage at deathfunctional performancelongevitypublic healthRisk factors

Identifiers

PMID36965505
PMCPMC10335838

What Socratic holds

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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 Socratic graph.