Evidence map›Paper›PMID 39754064›Full record

ArticleBMC public health2025

Associations of healthy lifestyle and family income to poverty ratio with all-cause mortality among people with prediabetes and diabetes: a prospective cohort study.

Zhu Li, Lin Zhou, Yongshi Wu, Tao Ding, Yuxin Gan, Xiang Fan

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

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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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

6 authors.

Zhu LiSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China.
Lin ZhouSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China.
Yongshi WuSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China.
Tao DingSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China.
Yuxin GanSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China.
Xiang FanSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, No. 548 Binwen Road, Binjiang District, Hangzhou, 310053, China. fanxiang_78@hotmail.com.

Funding

National Natural Science Foundation of China 82405046Talent Special Project of Zhejiang Chinese Medical University 2024ZR03
6 · The paper itself

Abstract

backgroundFamily income to poverty ratio (PIR) may have independent effects on diet and lifestyle factors and the development of prediabetes and diabetes, as well as on mortality. It is unclear how the protective effect of a healthy lifestyle against death differs between individuals with different glucose metabolic profiles and whether PIR mediates this effect. This study aimed to explore whether healthy lifestyle and family PIR reduced the risk of all-cause mortality in participants with different metabolic status and the mediating role of PIR. SUBJECTS AND

methodsIn total, 21,411 participants from the 2001-2018 National Health and Nutrition Examination Survey (NHANES) and follow-up until 2019 were included. The weighted healthy lifestyle score was constructed based on smoking, alcohol consumption, physical activity, diet (HEI-2015), and body mass index. Generalized linear regression models were used to analyze the association between healthy lifestyle, PIR, and all-cause mortality. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals, Kaplan-Meier survival curve was used to analyze the all-cause mortality associated with PIR and lifestyle. Furthermore, the mediation proportion of PIR in all-cause mortality attributed to healthy lifestyle was analyzed among participants with normal glucose regulation, prediabetes, or diabetes after multivariable adjustment.

resultsThere were significant differences in healthy lifestyle and PIR among people with normal glucose regulation, prediabetes and diabetes. During a mean follow-up of 92 months, participants with prediabetes or diabetes were also likely to have a higher mortality rate, respectively 583 (8.3%) and 263 (12.7%). More than 2 healthy lifestyles were associated with 42% (HR, 0.58; 95% CI, 0.35-0.95) to 76% (HR, 0.24; 95% CI, 0.12-0.44) reduced risk of all-cause mortality among participants with prediabetes, but among those with diabetes, who had ≥ 4 healthy lifestyles were associated with 72% reduced risk of all-cause mortality (HR, 0.28; 95% CI, 0.09-0.90). The middle and high PIR were associated with at least a 37% (HR, 0.63; 95% CI, 0.47-0.83) to 65% (HR, 0.35; 95% CI, 0.18-0.68) lower risk of all-cause mortality in participants with prediabetes and diabetes. Furthermore, PIR mediated 5.81-14.93% and 7.72-10.10% of the association between healthy lifestyle and all-cause mortality among normal glucose regulation and prediabetic participants, respectively. However, the mediating effect of PIR was not significant among diabetic participants.

conclusionsOur findings highlight the importance of promoting adherence to a healthy lifestyle and improving PIR in prediabetic patients to reduce the risk of all-cause mortality, and the protective effect is more significant with more healthy lifestyles and higher PIR. This study can help clinicians and health systems develop more targeted treatments for people with different metabolic levels.

Indexed as

Diabetes MellitusHealthy LifestylePovertyPrediabetic StateAdultAgedCause of DeathFemaleHumansIncomeMaleMiddle AgedMortalityNutrition SurveysProspective StudiesHealthy lifestyleMortalityNHANESPrediabetic

Identifiers

PMID39754064
PMCPMC11697864

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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.