Sihui Peng

Dr. Sihui Peng

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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8 May 2017 in International Journal of Health Geographics
Verified
Journal Article
Open access
PDF file
TYTingzhong Yang
Tingzhong Yang
LYLingwei Yu
Lingwei Yu
RBRoss Barnett
Ross Barnett
SJShuhan Jiang
Shuhan Jiang
SPSihui Peng
Sihui Peng
LLLu Li
Lu Li
Many studies have examined childhood and adolescent obesity, but few have examined young adults and the effect of their home and current living environments on prevalence rates. The present study explores contextual factors affecting overweight and obesity among university students in China and, in particular, focuses on how the SES–obesity relationship varies across different geographical contexts. Participants were 11,673 students, who were identified through a multistage survey sampling process conducted in 50 universities. Individual data was obtained through a self-administered questionnaire, and contextual variables were retrieved from a national database. Multilevel logistic regression models were used to examine urban and regional variations in overweight and obesity. Overall the prevalence of overweight and obesity in the study sample was 9.5% (95% CI 7.7, 11.3%). After controlling for individual factors, both attributes of the home location (regional GDP per capita and rurality) and the current university location (city population) were found to be important, thus suggesting that the different origins of students affect current levels of obesity. At the individual level, while students with more financial resources were more likely to be obese, the extent of this relationship was highly dependent upon area income and city size. The results of this study add important insights about the role of contextual factors affecting overweight and obesity among young adults and indicate a need to take into account both past as well as present environmental influences when considering the role of contextual factors in models of the nutrition transition.

29 December 2015 in International Journal of Health Geographics
Verified
Journal Article
Open access
PDF file
TYTingzhong Yang
Tingzhong Yang
SJShuhan Jiang
Shuhan Jiang
RBRoss Barnett
Ross Barnett
SPSihui Peng
Sihui Peng
LYLingwei Yu
Lingwei Yu
Second hand smoke (SHS) exposure is a severe public health problem, especially in low and middle countries, but no studies have examined both individual and city-level variables influencing exposure. A cross-sectional multistage sampling design was used to survey subjects from 21 cities in China. Using a standardized questionnaire individual level information was collected. City-level variables were retrieved from the National Bureau of Statistics database. Multilevel logistic regression analysis was used to assess SHS exposure variation at both the individual and city level. SHS exposure prevalence among non-smokers was 28.1 % (95 % CI 27.1–29.0). At the individual level lower educational attainment and income and higher exposure to tobacco advertising were associated with higher SHS exposure. On the other hand richer cities, and those with more anti-smoking media news coverage, had less SHS exposure. The presence of city smokefree regulations was unrelated to exposure. Given its human and economic costs, reducing SHS exposure should receive greater priority than it does in China. The results point to the need for the enactment of national smokefree laws in order to combat unacceptably high levels of SHS exposure.

18 February 2025 in BMC Public Health
Verified
Journal Article
Open access
PDF file
TYTingzhong Yang
Tingzhong Yang
SPSihui Peng
Sihui Peng
RCRandall R Cottrell
Randall R Cottrell
This study examines the longitudinal influence of quarantine and the COVID-19 surge after quarantine was released on behavioral and mental problems among the Chinese university students. A longitudinal observation design was utilized. There were 10 waves of surveys including the pre-quarantine period, the quarantine period, and the quarantine releasing period. The non-parametric linear mixed-effects model and generalized estimating equations were used to examine the association between the dependent and independent variables. Two-hundred and two (88.21%) participants completed 10 waves of the survey. The COVID-19 surge was positively associated with perceived severity for COVID-19 infection (β: 0.2162, p < 0.01), the quarantine period was negatively associated with perceived risk (β: -0.3632, p < 0.01). The quarantine was negatively associated with both behavior belief (β: -0.6164, p < 0.01) and outcome belief for lockdown (β: -0.0976, p < 0.01). The COVID-19 surge was only positively associated with behavior belief for the lockdown (β: 0.1073, p < 0.01). Both the COVID-19 surge and the quarantine periods were positively associated with mental disorders, and the standard β values were 0.2611 and 0.3846. The quarantine also had an influence on short sleep duration (β: 0.2681, p < 0.05). This study yielded new information about the influence of the COVID-19 surge, the quarantine period and the period after quarantine was released on the behavioral and mental problems among Chinese university students. Policy changes and health education are essential for minimizing the adverse health effects of these responses. This may have important implications for policies and disease prevention strategies targeted at controlling COVID-19.

26 June 2020 in medRxiv
Verified
Preprint
Open access
PDF file
XYXiaozhao Y Yang
Xiaozhao Y Yang
SPSihui Peng
Sihui Peng
TYTingzhong Yang
Tingzhong Yang
WZWeifang Zhang
Weifang Zhang
HWHui Hui Wang
Hui Hui Wang
RCRandall R Cottrell
Randall R Cottrell
Objective: To examine changing trends of uncertainty stress, and its impact on disease fear and prevention behaviors during the Chinese COVID-19 epidemic using a prospective observational study. Methods: The study employed a longitudinal design. Participants were recruited for an online panel survey from chat groups on social media platforms. There were 5 waves of interviews. Information on uncertainty stress and related variables were collected via the online survey. Descriptive statistics and the GIM program were used for data analysis. Results: Participants numbered 150 for the linkable baseline survey and 102 (68%) for the final survey. Uncertainty stress(β: -0.047, S.E: 0.118, p>0.05) did not show a statistically significant temporal change trend over the observation period. Disease fear manifested a statistically significant downwards trend (β: -0.342, S.E: 0.157, p<0.05), and prevention behaviors indicated an upwards trend (β: 0.048, S.E: 0.021, p<0.05) during the observation period. Uncertainty stress was positively associated with disease fear (β: 0.45046, S.E: 0.05964, p<0.0001), and negatively associated with self-efficacy (β: -0.6698, S.E: 0.01035, p<0.0001), and prevention behaviors (β:-0.02029, S.E: 0.00876, p: 0.0209). Conclusion: This study yielded new information about uncertainty stress among Chinese people during the COVID-19 epidemic. Policy changes and public education are essential for minimizing the negative effects of uncertainty stress in disease prevention.