Pei Wang

Dr. Pei Wang


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 April 2024 in BMC Global and Public Health
Verified
Journal Article
Open access
PDF file
YZYongle Zhan
Yongle Zhan
PWPei Wang
Pei Wang
YZYongan Zhan
Yongan Zhan
ZLZhiming Lu
Zhiming Lu
YGYidan Guo
Yidan Guo
SBSuvd Batbaatar
Suvd Batbaatar
Background: Prior 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. Methods: Data 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. Results: A 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). Conclusions: Clustering 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.

SWShengwei Wang
Shengwei Wang
Songbo HuSongbo Hu
Songbo Hu
PWPei Wang
Pei Wang
WYWu Yuhang
Wu Yuhang
ZLZhitao Liu
Zhitao Liu
HZHuilie Zheng
Huilie Zheng
Objective: To estimate and compare age trends and the disability-free life expectancy (DFLE) of the population over 60 years old in 2018 in Jiangxi Province, China, by sex and urban–rural areas. Methods: The model life table was employed to estimate the age-specific mortality rate by sex and urban–rural areas, based on the Summary of Health Statistics of Jiangxi Province in 2018 and the Sixth National Health Service survey of Jiangxi Province. DFLE and its ratio to life expectancy (LE) were obtained by the Sullivan method. Results: In 2018, the DFLE among people over 60 is 17.157 years for men and is 19.055 years for women, accounting for 89.7% and 86.5% of their LE respectively. The DFLE/LE of men is higher than that of women at all ages. LE and DFLE are higher for the population in urban areas than in rural areas. For women, DFLE/LE is higher in urban areas than in rural areas (except at ages 75 and 80). Urban men have a higher DFLE/LE than rural men (except at age 85). The difference in DFLE between men and women over 60 years is 1.898 years, of which 2.260 years are attributable to the mortality rate, and 0.362 years are due to the disability-free prevalence. In addition, the difference in DFLE between urban–rural elderly over 60 years old is mostly attributed to the mortality rate by gender (male: 0.902/1.637; female: 0.893/1.454), but the impact of the disability-free rate cannot be ignored either (male: 0.735/1.637; female: 0.561/1.454). Conclusions: The increase in DFLE is accompanied by the increase in LE, but with increased age, DFLE/LE gradually decreases. With advancing age, the effect of disability on elderly people becomes more severe. The government administration must implement some preventive actions to improve health awareness and the life quality of the elderly. Rural elderly; rural women in particular, need to be paid more attention and acquire more health care.

29 April 2023 in Biology
Verified
Journal Article
Open access
PDF file
Yongle ZhanYongle Zhan
Yongle Zhan
XRXiaohao Ruan
Xiaohao Ruan
PWPei Wang
Pei Wang
DHDa Huang
Da Huang
JHJingyi Huang
Jingyi Huang
Rong NaRong Na
Rong Na
Objective: Early evidence is disputable for the effects of modifiable lifestyle behaviors on prostate cancer (PCa) risk. No research has yet appraised such causality in different ancestries using a Mendelian randomization (MR) approach. Methods: A two-sample univariable and multivariable MR analysis was performed. Genetic instruments associated with lifestyle behaviors were selected based on genome-wide association studies. Summary-level data for PCa were obtained from PRACTICAL and GAME-ON/ELLIPSE consortia for Europeans (79,148 PCa cases and 61,106 controls), and ChinaPCa consortium for East Asians (3343 cases and 3315 controls). Replication was performed using FinnGen (6311 cases and 88,902 controls) and BioBank Japan data (5408 cases and 103,939 controls). Results: Tobacco smoking was identified as increasing PCa risks in Europeans (odds ratio [OR]: 1.95, 95% confidence interval [CI]: 1.09–3.50, p = 0.027 per standard deviation increase in the lifetime smoking index). For East Asians, alcohol drinking (OR: 1.05, 95%CI: 1.01–1.09, p = 0.011) and delayed sexual initiation (OR: 1.04, 95%CI: 1.00–1.08, p = 0.029) were identified as risk factors, while cooked vegetable consumption (OR: 0.92, 95%CI: 0.88–0.96, p = 0.001) was a protective factor for PCa. Conclusions: Our findings broaden the evidence base for the spectrum of PCa risk factors in different ethnicities, and provide insights into behavioral interventions for prostate cancer.