Evidence map›Paper›PMID 39681898›Full record

ArticleBMC global and public health2024

Clustering of lifestyle risk factors in relation to suicidal thoughts and behaviors in young adolescents: a cross-national study of 45 low- and middle-income countries.

Yongle Zhan, Pei Wang, Yongan Zhan, Zhiming Lu, Yidan Guo, Noor Ani Ahmad, Andrew Owusu, Tepirou Chher, Johnson T Hinneh, Krishna Kumar Aryal and 6 more

Abstract read
In one paragraph

Article in BMC global and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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

16 authors.

Yongle ZhanDepartment of Surgery, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Pei WangDepartment of Statistics, Miami University, Oxford, OH, USA. wangp33@miamioh.edu.
Yongan ZhanSchool of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Zhiming LuInstitute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, China.
Yidan GuoSchool of Mathematical and Statistical Sciences, Clemson University, Clemson, SC, USA.
Noor Ani AhmadInstitute for Public Health, Ministry of Health, Putrajaya, Malaysia.
Andrew OwusuDepartment of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN, USA.
Tepirou ChherPreventive Medicine Department, Ministry of Health, Phnom Penh, Cambodia.
Johnson T HinnehMinistry of Education, Monrovia, Liberia.
Krishna Kumar AryalBergen Centre for Ethics and Priority Setting in Health, University of Bergen, Bergen, Norway.
Noorali DarwishMinistry of Public Health of Afghanistan, Kabul, Afghanistan.
Sameera J SenanayakeAustralian Centre for Health Services Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
Bushra Abdulrahman Ahmed MufadhalConsultant of Public Health, School Health & Nutrition, Sana'a, Yemen.
Alissar RadyWorld Health Organization Country Office, Beirut, Lebanon.
Marcia Bassier-PaltooHealth Programs and Delivery Division, Ontario Ministry of Health, Toronto, ON, Canada.
Suvd BatbaatarNational Center for Public Health, Ministry of Health, Ulaanbaatar, Mongolia.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundPrior research has reaffirmed lifestyle risk behaviors to cluster among adolescents. However, the lifestyle cluster effect on suicidal thoughts and behaviors (STBs) was unclear among adolescents in low- and middle-income countries (LMICs). No comparison of such associations was conducted across nations.

methodsData from 45 LMICs were obtained from the Global School-based Student Health Survey (GSHS) between 2009 and 2019. Lifestyle behavior factors were collected through a structured questionnaire. Suicidal ideation, plan, and attempt were ascertained by three single-item questions. Lifestyle risk scores were calculated via a sufficient dimension reduction technique, and lifestyle risk clusters were constructed using a latent class analysis. Generalized linear mixed models with odds ratio (OR) and 95% confidence interval (CI) were used to estimate the lifestyle-STB associations.

resultsA total of 229,041 adolescents were included in the final analysis. The weighted prevalence of suicidal ideation, plan, and attempt was 7.37%, 5.81%, and 4.59%, respectively. Compared with the favorable lifestyle group, the unfavorable group had 1.48-, 1.53-, and 3.11-fold greater odds of suicidal ideation (OR = 1.48, 95%CI: 1.30-1.69), plan (OR = 1.53, 95%CI 1.34-1.75), and attempt (OR = 3.11, 95%CI 2.64-3.65). Four clusters of lifestyle risk behaviors were identified, namely healthy lifestyles (H-L), insufficient intake of vegetables and fruit (V-F), frequent consumption of soft drinks and fast food (D-F), and tobacco smoking and alcohol drinking (S-A) clusters. Compared with H-L cluster, V-F cluster was associated with 43% and 42% higher odds of suicidal ideation and plan, followed by S-A cluster (26% for ideation and 20% for plan), but not significant in D-F cluster (P > 0.05). D-F cluster was associated with 2.85-fold increased odds of suicidal attempt, followed by V-F cluster (2.43-fold) and S-A cluster (1.18-fold).

conclusionsClustering of lifestyle risk behaviors is informative for risk stratification of STBs in resource-poor settings. Lifestyle-oriented suicide prevention efforts should be initiated among school-attending adolescents in LMICs.

Indexed as

AdolescentCross-nationalLatent class analysisLifestyle risk behaviorLMICRisk stratificationSufficient dimension reductionSuicidal attemptSuicidal ideationSuicidal plan

Identifiers

PMID39681898
PMCPMC11622970

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.