Evidence map›Paper›PMID 38333737›Full record

ArticleFrontiers in public health2024

The impact of modifiable health metrics on mortality for older adults with low cognitive function.

Wei Wang, Pengfei Sun, Tingting Lv, Min Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

4 authors.

Wei WangDepartment of Clinical Laboratory, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Pengfei SunDepartment of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Tingting LvLiver Center, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Min LiClinical Epidemiology and EBM Unit, Beijing Friendship Hospital, Beijing Clinical Research Institute, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Cognitive impairment has emerged as a major contributing factor to mortality for older adults. Identifying the strong modifiable health metrics against mortality is of high priority, especially in this high-risk population. Methods: This population-based study used data of US adults aged≥60 years old from the National Health and Nutrition Examination Survey 2011-2014 cycles. De-identified data for participants who completed cognitive function test were extracted. Mortality data was obtained by linking to the 2019 public-use linked mortality file. Results: Participants with low global cognition had higher risk of all-cause mortality (HR = 1.46; 95%CI, 1.04-2.05). The highest prevalence of ideal level of health metrics was observed for sleep duration (54.36% vs. 62.37%), and the lowest was noted for blood pressure (12.06% vs. 21.25%) for participants with low and average to high global cognition, respectively. Ideal status of physical activity and diet quality were significantly associated with all-cause mortality among participants with low global cognition (HR = 0.48, 95%CI: 0.28-0.82; HR = 0.63, 95%CI: 0.43-0.95). The corresponding population-attributable fractions were 26.58 and 15.90%, respectively. Conclusion: Low cognitive function was associated with increased risk of all-cause death for older adults. Attainment of healthy metrics, especially sufficient physical activity, consuming healthy diet and being never smoked, provided strong protection against death risk.

Indexed as

Cognitive DysfunctionQuality Indicators, Health CareAgedCognitionHumansMiddle AgedNutrition SurveysRisk Factorsagedcognitionexercisehealthy dietmortality

Identifiers

PMID38333737
PMCPMC10850326

What OpenQuestion holds

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LicenceCC BY
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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.