Evidence map›Paper›PMID 36237838›Full record

ArticlePreventive medicine reports2022

Lifestyle patterns and incident type 2 diabetes in the Dutch lifelines cohort study.

Ming-Jie Duan, Louise H Dekker, Juan-Jesus Carrero, Gerjan Navis

Open access · goldAbstract read
In one paragraph

Article in Preventive medicine reports, 2022. 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
1.8field-weighted citation impact, top 15% of its field
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, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

4 authors at 3 institutions in 2 countries.

Ming-Jie DuanDepartment of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Louise H DekkerDepartment of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Juan-Jesus CarreroDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Gerjan NavisDepartment of Internal Medicine, University Medical Center Groningen, Groningen, The Netherlands.
University Medical Center Groningen · NLKarolinska Institutet · SENational Institute for Public Health and the Environment · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to identify the underlying subgroups of the population characterized by distinct lifestyle patterns, and to investigate the associations between lifestyle patterns and risk of incident type 2 diabetes. Using data from the Dutch Lifelines cohort study, latent class analysis was performed to derive lifestyle patterns on five lifestyle factors, i.e., smoking, diet quality, TV watching time, physical activity level, and risk drinking. Associations between lifestyle patterns and incident type 2 diabetes were estimated. Among 61,869 participants analyzed, we identified 900 cases of type 2 diabetes during follow-up (205,696 person-years; incidence rate 4.38 per 1000 person-years). Five lifestyle pattern groups were identified. Using the "healthy lifestyle group" as reference, the "unhealthy lifestyle group" had the highest risk for type 2 diabetes (HR 1.51 [95%CI 1.24, 1.85]), followed by the "poor diet and low physical activity group" (HR 1.26 [95%CI 1.03, 1.55]). The "risk drinker group" and the "couch potato group" (characterized by excessive TV watching) showed no significantly elevated risk. These models were adjusted for age, sex, total energy intake, education, BMI, family history of diabetes, and blood glucose level at baseline. Our study shows that lifestyle factors tended to cluster in unique behavioral patterns within the heterogeneous population. These lifestyle patterns were differentially associated with incident type 2 diabetes. Our findings support the relevance of considering lifestyle patterns in type 2 diabetes prevention. Tailored prevention strategies that target multiple lifestyle risk factors for different lifestyle pattern groups may optimize the effectiveness of diabetes prevention at the population level.

Indexed as

BIC-LL, Bayesian information criterion with log likelihood for the number of parameters adjustedEpidemiologyFFQ, Food frequency questionnaireLCA, Latent class analysisLifestyleLifestyle patternsLLDS, Lifeline diet scoreMVPA, Moderate-to-vigorous physical activityPAF, Population attributable fractionPublic healthSQUASH, Short QUestionnaire to ASsess Health-enhancing physical activityType 2 diabetes

Identifiers

PMID36237838
PMCPMC9551208
OpenAlexW4300861849

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.