中华疾病控制杂志

Epidemiological trends, influencing factors and response strategies for emerging infectious diseases

FANG Xinyu, FAN Yinguang, YANG Shigui, YE Dongqing

2025, 29(1): 1-7. doi: 10.16462/j.cnki.zhjbkz.2025.01.001

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Emerging infectious diseases have a significant burden on public health and socioeconomic systems. In the context of globalization, we are facing the severe challenge of emerging infectious diseases continuously appearing, which leads to bring the outbreaks and epidemics of these diseases back into focus the international community. Emerging infectious diseases are characterized by their suddenness and unpredictability. Their outbreaks and epidemics result from ongoing mutations of pathogens and are also related to ecological disruptions and changes in social and demographic factors. To explore the key factors of emerging infectious diseases in depth and to effectively respond to their outbreaks and epidemics, it is essential to advocate for the "One Health" concept, strengthen our capabilities and technologies for addressing emerging infectious diseases, and apply scientific and technological advancements rationally to ensure biosafety. This review aims to comprehensively examine the historical impacts of emerging infectious diseases, analyze their causes, and discuss effective response strategies and technologies, providing a reference for addressing potential future pandemics of emerging infectious diseases.

Trajectories of antenatal depression in pregnant women and their association with adverse birth outcomes: Tongji-Huaxi-Shuangliu birth cohort

LI Xianli, WANG Jingyi, XU Jiajing, YUAN Jiaying, LIU Gang, PAN An, PAN Xiongfei

2025, 29(1): 8-14. doi: 10.16462/j.cnki.zhjbkz.2025.01.002

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Objective To identify longitudinal trajectories of antenatal depression among pregnant women in southwest China and assess their associations with adverse birth outcomes. Methods From 2017 to 2020, 4 741 pairs of pregnant women and their offspring were included in the Tongji-Huaxi-Shuangliu Birth Cohort. All participants used the validated Chinese version of the Edinburgh Postnatal Depression Scale to assess depressive symptoms throughout early (≤15 weeks), middle (24-28 weeks), and late (>28 weeks) pregnancy stages. Fetal birth outcomes were obtained from electronic medical records at delivery. The latent class mixed model was used to identify the trajectories of antenatal depression. The associations between depression trajectories and adverse birth outcomes were examined using propensity score-based inverse probability of treatment weighting and logistic regression modeling. Results We identified four distinct trajectories, including the low-stable group (n=1 327, 27.99%), moderate-stable group (n=2 610, 55.05%), up-then-down group (n=407, 8.59%), and down-then-up group (n=397, 8.37%). Compared to the low-stable group, the down-then-up group showed higher risks of low birth weight (OR=2.29, 95% CI: 1.06-4.97) and preterm birth (OR=1.91, 95% CI: 1.09-3.33) (all P < 0.05), but the association was not significant for newborns of small for gestational age (OR=0.80, 95% CI: 0.45-1.39, P=0.424). Conclusions There existed dynamic change patterns in antennal depression during the whole pregnancy, which were differentially associated with adverse birth outcomes. Identifying the onset and development of antenatal depression can facilitate timely interventions in order to prevent adverse birth outcomes.

Association of maternal dietary habits in early pregnancy with congenital heart disease in offspring: a case-control study

CHEN Kebin, WANG Tingting, SUN Mengting, LUO Manjun, RUAN Xiaorui, QIN Jiabi

2025, 29(1): 15-21. doi: 10.16462/j.cnki.zhjbkz.2025.01.003

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Objective To explore the association of dietary habits of mothers in early pregnancy with the risk of congenital heart disease (CHD) in offspring. Methods A case-control study was conducted in Hunan Children′s Hospital from September 2017 to March 2020. A questionnaire was used to collect the corresponding data. The logistic regression analysis was used to analyze the association of maternal dietary habits in early pregnancy with risk of CHD and its specific phenotypes in offspring, as well as to conduct subgroup analysis for variables with statistically significant differences in the general data analysis to assess the stability of the correlation. Results The mothers who ate more pickled vegetables (OR=1.67, 95% CI: 1.36-2.02), stinky tofu (OR=1.68, 95% CI: 1.24-2.30), smoked food (OR=2.21, 95% CI: 1.78-2.74), barbecue food (OR=1.77, 95% CI: 1.37-2.29), fried food (OR=1.46, 95% CI: 1.19-1.79), preserved egg (OR=0.46, 95% CI: 0.32-0.66), salted egg (OR=0.24, 95% CI: 0.13-0.31), fresh meat (OR=0.60, 95% CI: 0.48-0.75), fresh fish and shrimp (OR=0.32, 95% CI: 0.26-0.39), fresh eggs (OR=0.53, 95% CI: 0.43-0.66), fresh fruits (OR=0.52, 95% CI: 0.41-0.66), beans (OR=0.69, 95% CI: 0.58-0.81), as well as milk and dairy products (OR=0.55, 95% CI: 0.48-0.64) were associated with a risk of CHD in offspring, and the difference were statistically significant (all P < 0.001). The subgroup analysis showed that these associations of maternal dietary habits with CHD were stable. Additionally, the similar results were also found for specific phenotypes of CHD. Conclusions The maternal dietary habits in early pregnancy are significantly associated with the risk of CHD and its specific phenotypes, with a stable association among different populations. The study can provide a scientific basis for the prevention of CHD from the perspective of dietary guidance during early pregnancy.

Independent and interaction effects of high-risk pregnancy and number of prenatal visits on low birth weight

BIAN Yanxia, WANG Li, LI Huangfu, YI Guobao

2025, 29(1): 22-26. doi: 10.16462/j.cnki.zhjbkz.2025.01.004

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Objective To explore the independent and interaction effects of high-risk pregnancy and number of prenatal visits on low birth weight (LBW). Methods Data pertaining to newborns who gave birth in Yangqu Country from January 2012 to December 2021 and their parents were collected through the Taiyuan Maternal and Child Health Comprehensive Management Platform. We used logistic regression model to analyze the independent and interaction effects. Results In this study, the detection rate of LBW was 2.58%. After controlling for confounding variables, logistic regression analysis implied that both high-risk pregnancy (OR=2.683, 95% CI: 1.791-4.019) and < 5 times of prenatal visits (OR=2.802, 95% CI: 2.113-3.717) were positively associated with LBW (all P < 0.05). The interaction between high-risk pregnancy and number of prenatal visits exhibited an additive effect on the likelihood of LBW (RERI=6.557, 95% CI: 1.007-12.107; API=0.652, 95% CI: 0.436-0.867; SI=3.616, 95% CI: 1.708-7.654). The risk of delivering an infant with LBW was 10.068 times greater when both high-risk pregnancy and < 5 prenatal visits were present, compared to when neither of these factors was present (OR=10.068, 95% CI: 5.679-17.850). Conclusions The combined interaction of high-risk pregnancies and infrequent prenatal visits heightens the risk of delivering infants with LBW. It is advised that special attention be given to the number of prenatal visits and that health education tailored to expectant mothers with high-risk pregnancies be provided to reduce the incidence of low birth weight infants.

A study on the quality of overall beverage intake and its associations with glucose metabolism in pregnant women

LAN Minyan, CHEN Yaqing, LIU Yu, HE Xuanqing, GU Xiaonan, HUANG Shuyue, LI Mengfan, CAI Li

2025, 29(1): 27-33. doi: 10.16462/j.cnki.zhjbkz.2025.01.005

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Objective To evaluate the overall quality of beverage intake among pregnant women using the healthy beverage index (HBI) and explore its association with glucose metabolism levels and gestational diabetes mellitus (GDM). Methods From 2017 to 2018 1 029 pregnant women at 20-28 weeks of gestation were enrolled. Beverage intake quantity and frequency were collected using the food frequency questionnaire through face-to-face interviews. Scores for the 10 subcategories and total score of HBI, with a maximum total score of 100, were calculated. Oral glucose tolerance tests and blood sample analyses were conducted to evaluate glucose metabolism levels and diagnose GDM. Multiple linear regression and logistic regression were conducted for association analysis. Results The average HBI score was (79.81±9.84), with 18.85% diagnosed with GDM. Among the subcategories, compared to pregnant women with higher sugar-sweetened beverage intake, those with lower sugar-sweetened beverage intake had lower fasting blood glucose (B=-0.39, 95% CI: -0.63-0.51, P=0.002). Compared to pregnant women with higher total beverage energy, those with lower total beverage energy had lower fasting blood glucose (B=-0.09, 95% CI: -0.17-0.01, P=0.020) and a reduced risk of GDM (OR=0.52, 95% CI: 0.29-0.90, P=0.024). No significant associations of HBI total score and scores of other HBI subcategories with glucose metabolism levels or GDM were found. Conclusions This is the first study utilizing HBI to evaluate the overall quality of beverage intake among pregnant women, and the results show that pregnant women scored relatively high. Sugar-sweetened beverages and total beverage energy in line with guidline recommendation were associated with lower fasting blood glucose and reduced GDM risk.

Epidemiological analysis of other infectious diarrhea diseases in China from 2010 to 2020

ZHAI Xueyan, GAO Hongzhu, MO Yingning

2025, 29(1): 34-41. doi: 10.16462/j.cnki.zhjbkz.2025.01.006

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Objective To analyze the spatial and temporal epidemiological characteristics of other infectious diarrheal diseases in China between 2010 and 2020, and to predict the number of incidence in January-December 2021, in order to provide a reference for the prevention of the diseases. Methods Descriptive epidemiology and spatial autocorrelation analysis were used to analyze the epidemiological characteristics, and the results were visualized by ArcGIS 10.8 software.A seasonal autoregressive integrated moving average (SARIMA) model was constructed to make short-term prediction. Results From 2010 to 2020, the number of cases of other infectious diarrheal diseases in China was 11 269 993 and the number of deaths was 214, with an average annual reported incidence rate of 19.45/100 000 per year. There are two peaks of incidence in summer and winter every year, with a clear trend of backward shift of the peak in winter. The majority of the incidence occur in children aged 0-< 5 years old. The disease is mainly distributed among scattered children, students and farmers. Spatial autocorrelation analysis showed that there were obvious localized clustering characteristics (P < 0.05), and the "high-high" clustering areas included Hebei, Shandong, Tianjin, and Guangdong. The SARIMA (1, 0, 0) (0, 1, 0)₁₂ prediction model showed that there will be a significant increase in the number of cases in the period of January to December 2021, and the bi-seasonal peak characteristics remained significant. Conclusions The incidence of other infectious diarrhea in the southeast coastal areas such as Zhejiang Province and Guangdong Province is relatively high, and the SARIMA (1, 0, 0) (0, 1, 0)₁₂ model has a good fitting effect. During other high incidence seasons of infectious diarrhea, it is necessary to combine the spatiotemporal epidemic characteristics of different regions and increase monitoring and prevention of high incidence population.

The trend and prediction of the number of reported cases of active pulmonary tuberculosis in Guiyang and its prediction

LIANG Zuhua, PAN Chunliu, WANG Junhua, HUANG Yan, BAI Lulu, CHENG Hong, WANG Lin, ZHANG Haoyan

2025, 29(1): 42-48. doi: 10.16462/j.cnki.zhjbkz.2025.01.007

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Objective To study the trend of reported cases of active pulmonary tuberculosis (PTB) in Guiyang from 2010 to 2022, and to select the best model to predict the number of active PTB cases in Guiyang. Methods The data of monthly reported cases of active PTB in Guiyang from January 2010 to December 2022 were collected, and the Mann-Kendall trend test was used to analyze the trend of its change. Additionally, the ARIMA seasonal model, SARIMAX model, Holt-Winters exponential smoothing model and Prophet model were established. The optimal model was selected according to the principle of minimization of the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). Results The number of reported cases of active PTB in Guiyang from 2010 to 2022 showed an overall decreasing trend (Z=-7.75, P < 0.01), and had a typical seasonal distribution, with the peak of incidence in March of each year and the trough in February of the following year. Meteorological factors such as average temperature and average air pressure were associated with the number of active PTB cases with a lag effect. Comparisons revealed that the SARIMAX(2, 1, 1)(0, 1, 1)₁₂ model, which integrates a 7-month lag in mean atmospheric pressure and a 3-month lag in mean air temperature, fitted (RMSE=33.713, MAPE=8.936%, MAE=25.552) and predicted (RMSE=22.910, MAPE= 7.353%, MAE=20.000) were better than other models. It prediction results showed that the number of reported PTB cases in Guiyang City in 2024 would be 2 638, with an average monthly incidence of 220 cases, which continued to show a decreasing trend. Conclusions The reported incidence of active active PTB in Guiyang showed a downward trend, and the inclusion of meteorological factors could improve the accuracy of the model. The SARIMAX(2, 1, 1)(0, 1, 1)12 model with the mean temperature and mean air pressure had the best prediction performance, which better captured the trend of active PTB cases in Guiyang, and was more suitable for short-term prediction of the number of PTB cases in Guiyang, which could help the local government to formulate effective interventions and prevention and control strategies.

Influencing factors for delay of pulmonary tuberculosis case finding in adolescents in Chongqing, 2016-2022

WANG Xiangliu, SHUI Yichao, LUO Wenjun, LUO Hui, KONG Deliang, ZHANG Ting, WU Chengguo, PU Chuan

2025, 29(1): 49-54. doi: 10.16462/j.cnki.zhjbkz.2025.01.008

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Objective To analyze the discovery delays and influencing factors of adolescent pulmonary tuberculosis in Chongqing Municipality from 2016 to 2022, and to provide scientific basis for reducing the discovery delays of tuberculosis. Methods The case data of adolescent pulmonary tuberculosis patients in Chongqing Municipality from 2016 to 2022 were collected through the China disease control and prevention information system, and the current status of adolescent pulmonary tuberculosis discovery delays and the factors affecting them were analyzed using descriptive analysis, univariate analysis, and multifactorial logistic regression. Results A total of 18 856 adolescents in Chongqing were included in the study, with males accounting for 61.16% and students accounting for 50.10%. The average time of delay in detection was 50.46 d, with a delay rate of 46.47%; the average time of delay in consultation was 43 d, with a delay rate of 54.41%; and the average time of delay in diagnosis was 7.46 d, with a delay rate of 13.61%. The multifactorial results showed that other occupations (OR=1.402, 95% CI: 1.315-1.494), mobile population (OR=1.109, 95% CI: 1.036-1.186), passive detection (OR=3.457, 95% CI: 3.059-3.908), and retreatment (OR=1.229, 95% CI: 1.026-1.472) were risk factors for delayed detection of adolescent pulmonary tuberculosis patients in Chongqing (all P < 0.05). Conclusions The level of delayed detection of adolescent patients in Chongqing was high, but the overall trend was decreasing. Health education on knowledge related to pulmonary tuberculosis among adolescents should be strengthened to improve pulmonary tuberculosis prevention and treatment.

Characteristics of the cyclical cycle and non-linear prediction of acquired immunodeficiency syndrome incidence and mortality in China

LIU Chao, BAI Shasha, HAN Min, DONG Mengqi, ZHANG Juanjuan

2025, 29(1): 55-60. doi: 10.16462/j.cnki.zhjbkz.2025.01.009

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Objective To analyze the fluctuation pattern of the incidence and mortality of acquired immunodeficiency syndrome (AIDS) in China, reveal its cyclical characteristics and predict short-term trends. Methods Based on Census X-13 seasonal adjustment method, we analyzed the seasonal characteristics of China′s AIDS incidence and mortality from January 2004 to February 2024. In addition, the cyclical characteristics of AIDS incidence and mortality were analyzed using the Hodrick-Prescott (HP) filter method after removing seasonal influences. Furthermore, the AIDS incidence and mortality from March to December 2024 were predicted using a nonlinear regression model. Results The number of AIDS cases and deaths in China has been continuously increasing. Annual data exhibited a significant seasonal and trend variations, with peak incidence occurring in September-October and peak mortality in July-August. From January 2004 to February 2024, AIDS cases and deaths have revealed four complete cycles, each averaging 60 months in length, with unstable amplitude. The relationship between cases and deaths over time have formed an inverted "U" shape. Conclusions The cyclic cycle AIDS incidence and mortality in China have become longer. Predictions indicate a future downward trend in both incidence and mortality, so we should pay close attention to the epidemic situation of AIDS, and actively take preventive and control measures.

Association study between mixed air pollutant exposure and progression of pulmonary nodules

XU Ruining, ZHANG Xinyue, CHEN Jie, SHI Yiqiu, LIU Kefu, WANG Lina

2025, 29(1): 61-66. doi: 10.16462/j.cnki.zhjbkz.2025.01.010

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Objective To explore the single and mixed exposure effects of air pollutants on the progression of pulmonary nodules. Methods Individuals identified with pulmonary nodules in the medical examination were included. The average daily exposure concentrations of air pollutants in the year before the physical examination were estimated using the data from environmental monitoring stations and the diameters of pulmonary nodules were followed up each year. Generalized estimating equation models, quantile g-computation models (QgC) and bayesian kernel machine regression models (BKMR) were used to estimate the effects of air pollutants exposure singly and mixed on the annual change in pulmonary nodule diameter. Results A total of 785 individuals with pulmonary nodules were finally included in the study. The results of the generalized estimating equation analysis showed that for per interquartile range (IQR) increment in exposure levels of NO₂, PM_2.5, and PM₁₀, the annual increases in nodule diameter were 0.30 mm, 0.51 mm, and 0.32 mm, respectively. The results of the QgC model showed that per IQR increment in exposure levels of the mixed pollutants, the annual increases in nodule diameter were 0.50 mm (95% CI: 0.09 mm-0.91 mm). The BKMR model suggested that PM_2.5 was an important factor influencing nodule progression and a dose-response relationship was observed between them. Conclusions Air pollutants are associated with increased changes in pulmonary nodule diameter, and PM_2.5 is the most important component of the mixed pollutants affecting nodule diameter.

Hourly-scale associations between temperature change and emergency department visits for schizophrenia in Hefei, Anhui Province, China

LIU Jintao, YAN Junwei, WU Keyu, FAN Yinguang, SU Hong, CHENG Jian

2025, 29(1): 67-73. doi: 10.16462/j.cnki.zhjbkz.2025.01.011

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Objective To investigate the hourly-scale association between ambient temperature changes and schizophrenia-related emergency department (ED) visits. Methods We conducted a retrospective analysis of ED visit records for schizophrenia at the Anhui Mental Health Centre from 1 March 2015 to 31 December 2019. Hour-by-hour temperature data at the city level of Hefei was extracted from the ERA5-Land dataset as an exposure. A time-stratified case-crossover design was used to explore the association between hourly-scale changes in temperature and schizophrenia emergencies, with subgroups analyzed by age and gender. Subgroup analyses were performed to explore potential effect modification by age and gender. Results A total of 12 423 ED events for schizophrenia were identified, averaging 0.31 events per hour. The exposure-response relationship curve revealed an increased risk of schizophrenia-related ED presentations with rising temperatures within a 23-hour exposure window. Peak effects were observed at the first and 15th hour post-exposure, with each 1 ℃ temperature increase associated with a 1.17% (95% CI: 0.42%-1.92%) and 1.26%(95% CI: 0.25%-2.29%) increase in ED visit risk, respectively. Further stratification by time of day revealed a significant association between a 1 ℃ temperature increase and a 5.61% (95% CI: 1.65%-9.74%) elevated risk of ED visits between 21:00 and 00:00. Notably, subgroup analyses found a stronger association between temperature increases and schizophrenia-related ED visits among women compared to men. Conclusions There is an hourly-scale association between temperature change and schizophrenia emergencies, with an elevated risk emerging within hours of a temperature increase. These results underscore the need for targeted interventions to mitigate the acute risks associated with heat exposure among individuals with schizophrenia, particularly during sensitive time windows and within vulnerable subpopulations.

Analysis and forecast of Parkinson′s disease burden in China from 1990 to 2021

ZHANG Wenbin, WANG Yongjie, LING Yao, ZHANG Zhiyi, WANG Shihong, KONG Danli, DING Yuanlin

2025, 29(1): 74-81. doi: 10.16462/j.cnki.zhjbkz.2025.01.012

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Objective The purpose of this study was to analyze the incidence, prevalence, burden, and mortality trends of Parkinson′s disease in China from 1990 to 2021, and to predict the trend of Parkinson′s disease in 2022-2042, so as to provide reference for formulating prevention and treatment strategies. Methods Data from the Global Burden of Disease (GBD) 2021 database were used to collect relevant indicators of Parkinson′s disease burden in China from 1990 to 2021, including incidence, prevalence, mortality, and disability-adjusted life years (DALYs). Trend changes were analyzed based on percentage change rates (%) and exponentially averaged percentage change(EAPC). Data processing and statistical analyses were conducted using Excel 2021 and SPSS 27.0, with trend predictions performed using the autoregressive integrated moving average (ARIMA) model. Results In 2021, the incidence, prevalence, mortality, and DALYs rates of Parkinson′s disease in China were 35.73/100 000, 356.85/100 000, 6.47/100 000, and 151.78/100 000, respectively—representing increases of 359.46%, 544.06%, 133.58%, and 160.68% compared to 1990. The incidence, prevalence, mortality, and DALYs rates of Parkinson′s disease in China from 1990 to 2021 all showed a significant upward trend (EAPC of 5.12%, 6.08%, 2.63%, and 3.05%, respectively, P<0.001). Among males, these rates (41.51/100 000, 401.93/100 000, 7.51/100 000, and 175.84/100 000) were 1.40, 1.30, 1.40, and 1.40 times higher than those of females (29.67/100 000, 309.6/100 000, 5.38/100 000, and 126.57/100 000), respectively. Analysis of different age groups indicated that the highest incidence rate of Parkinson′s disease occurred in the 85-<90 and 90-<95 age groups (329.20/100 000 and 329.25/100 000, respectively), while the population aged 95 and older had the highest prevalence rate (5 090.17/100 000). The mortality rate peaked at 210.72/100 000 among those aged 90-<95. ARIMA model projections indicated that the incidence, prevalence, mortality, and DALYs rates would continue to rise from 2022 to 2042, with the rates for the entire population expected to reach 81.97/100 000, 904.08/100 000, 12.80/100 000, and 369.42/100 000 by 2042, with significant gender disparities. Conclusions The prevalence and overall burden of Parkinson′s disease in China have progressively increased over time, particularly among the elderly population. Moving forward, there is a need for enhanced health education, disease screening, early diagnosis, and treatment, alongside improved psychological and social support for patients and their families, to mitigate the impact of the disease on individuals and society.

Risk factors for cardiometabolic multimorbidity based on LASSO regression and random forest algorithms

ZHANG Shuying, XU Shan, TAN Yanfang, LING Kexin, LI Yuan, LIU Xiangtong

2025, 29(1): 82-88. doi: 10.16462/j.cnki.zhjbkz.2025.01.013

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Objective This study aims to identify risk factors of cardiometabolic multimorbidity (CMM) based on LASSO regression and random forest algorithms, providing a scientific basis for clinical decisions. Methods Using data from 14 358 individuals over 45 during the 2011-2020 follow-up period in the China health and retirement longitudinal study (CHARLS), variables were selected using the feature importance assessment from LASSO regression and random forest. Study participants were randomly divided into a training set and a test set at a ratio of 8∶2. The synthetic minority over-sampling technique (SMOTE) was employed to adjust the training set to a balanced dataset, then a disease prediction model was built using the random forest algorithm. Finally, grid search and 5-fold cross-validation were used to optimize the prediction model. Sensitivity analysis was conducted to ensure the model′s robustness. Results The accuracy of the prediction model reached 99.46%, the recall rate was 69.03%, the F1 score was 0.82, and the average area under curve value was 0.93. The model demonstrated good robustness through sensitivity analysis. The following factors were identified as predictors for CMM: gender, age, waist circumference, occupation, education level, fasting blood glucose, unhealthy lifestyle behaviors, mobility, baseline self-reported diseases, wind force, and use of unclean energy sources. Conclusions This study successfully builds a prediction model for CMM, indicating the correlation of several risk factors with CMM, which provides a scientific basis for clinicians to undertake early intervention in CMM high-risk groups.

Association of sleep and dietary rhythm disorders on the development of depressive symptoms in secondary school students

SU Huaqian, WANG Kai, YONG Zhongtian, LI Han, HAN Jiangtao, LI Yingjun, WANG Li

2025, 29(1): 89-94. doi: 10.16462/j.cnki.zhjbkz.2025.01.014

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Objective Exploring the association of joint exposure to sleep rhythm disorders and eating rhythm disorders on the development of depressive symptoms in secondary school students and further exploring possible mechanisms. Methods Using stratified random cluster sampling, A total of 2 660 secondary school students were included in all grades of three junior high schools and two senior high schools in Taiyuan City in October-November 2021. The adolescent biorhythmic disorder evaluation questionnaire was used to assess sleep and eating rhythm disorders, and the patient health questionnaire-9 (PHQ-9)rating scale was used to assess depressive symptoms. The data were analysed using R 4.2.2 statistical software. Results The overall detection rate of depressive symptoms among the 2 660 students was 41.7 per cent, and 72.3 percent among secondary school students with both high sleep rhythm and high eating rhythm disorders. Both sleep rhythm disorders and eating rhythm disorders were positively associated with the occurrence of depressive symptoms in secondary school students (all P < 0.05). The joint exposure to sleep and eating disorders increased the risk of depressive symptoms among secondary school students, with the group with high sleep and high eating disorders having the highest risk of depressive symptoms, which was 13.682 times higher than the group with low sleep and low eating disorders(95% CI: 9.149-20.461, P < 0.001). No significant multiplicative or additive interactions between sleep and eating disorders on the development of depressive symptoms in secondary school students were found. Conclusions Both sleep rhythm disorders and eating rhythm disorders are risk factors for the development of depressive symptoms in secondary school students, and the risk of depressive symptoms is increased with joint exposure to both.

The association between traditional tibetan pastoral dietary patterns and obesity in Qinghai Province

WANG Haijing, WANG Yanxiang, XU Ruijie, SUN Xiaomin, ZHANG Tianxiao, GAZANG Zhuoma, WANG Youfa, PENG Wen

2025, 29(1): 95-101. doi: 10.16462/j.cnki.zhjbkz.2025.01.015

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Objective This study aimed to identify different dietary patterns among the Tibetan population and explore their relationship with the risk of obesity. Methods Based on the established open cohort of the plateau population, a cross-sectional analysis was conducted with 1 913 Tibetan adults who were recruited for the first time in 2018 and 2022. Questionnaire surveys and physical examination data were collected. The K-means clustering method was utilized to identify different dietary patterns. Modified Poisson regression as employed to analyze the relationship between dietary patterns and overweight, obesity, and overweight/obesity. Results The prevalence of overweight/obesity among the Tibetan population was 60.2%. Two dietary pattern groups were identified: the pastoral dietary group (n=1 221), characterized by consumption of tsampa and Tibetan cheese, and the modern dietary group (n=692), characterized by the consumption of vegetables and refined carbohydrates. Compared to the modern dietary group, the risk of being overweight and overweight/obesity in the pastoral dietary pattern population was reduced by 16.4% (RR=0.836, 95% CI: 0.715-0.978, P=0.025) and 10.6% (RR=0.894, 95% CI: 0.816-0.979, P=0.015) respectively, indicating a significant protective effect. Furthermore, an interaction effect was observed between dietary factors and altitude. The risk of overweight in the pastoral dietary group was 22.4% lower (RR=0.776, 95% CI: 0.649-0.928, P=0.005) than in the modern dietary group among the individuals living at high-altitude. Conclusions Two dietary patterns were identified among the Tibetans, and the pastoral dietary pattern was associated with a reduced risk of overweight/obesity, especially at high altitudes. This finding highlights the combined impact of traditional dietary patterns and environmental factors on health and provides scientific evidence for developing targeted health intervention strategies for high-altitude pastoral residents.

Application of mathematical models in the prevention and control of infectious diseases

ZHOU Wenyong, WEN Zexuan, WANG Weibing

2025, 29(1): 102-107. doi: 10.16462/j.cnki.zhjbkz.2025.01.016

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With the acceleration of globalization, the outbreak and prevalence of infectious diseases have once again become important challenges in the field of public health. Compared to the traditional research that focuses on infectious sources, transmission routes, and susceptible populations, mathematical models focus on the dynamic connections among the three and replicate transmission dynamics or predict epidemic development based on mathematical principles and transmission mechanisms of infectious diseases. Mathematical models are currently used to solve many practical problems in prevention and control of infectious disease, including but not limited to predicting the trend of infectious disease, estimating disease burden and medical resource demand, evaluating the effectiveness of intervention measures, assessing vaccine efficacy and optimizing distribution strategies, and exploring the epidemic mechanism of infectious diseases. This article briefly describes the application of mathematical models in prevention and control of infectious diseases through a review.

The impact of infection exposure among close contacts of tuberculosis cases in school on epidemic risk prediction

ZHANG Xiaolong, CUI Caiyan, FU Ying, WANG Feixian, LI Yun, JIANG Jun

2025, 29(1): 108-110. doi: 10.16462/j.cnki.zhjbkz.2025.01.017

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Objective To investigate the predictive efficacy of latent tuberculosis infection (LTBI) rate among close contacts in school pulmonary tuberculosis (PTB) epidemic, and analyze the relationship between exposure level and epidemic risk. Methods Based on 630 school PTB outbreaks, screening data were collected from 630 index cases and 37 522 close contacts. Unconditional logistic regression was used to analyze the association between LTBI rate and PTB outbreak clustering risk. Restricted cubic splines (RCS) were employed to explore their non-linear relationship, and receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of LTBI rate for outbreak clustering risk. Results RCS analysis revealed that the risk of a PTB outbreak increased as the LTBI rate rose when the LTBI rate among close contacts of bacteriologically negative patients exceeded 2.48% or among bacteriologically positive patients exceeded 6.92%. After multivariate adjustment, for every 1% increase in the LTBI rate, the odds ratio (OR) for the risk of outbreak clustering was 1.235 (95% CI: 1.175-1.297). Analyzed by LTBI rate tertiles, compared with LTBI rate of < 5%, the OR=3.906 (95% CI: 1.427-10.692) when LTBI rate was 5%- < 9% and the OR=19.195 (95% CI: 8.588-42.902) when LTBI rate was ≥10%. The ROC further revealed that an LTBI rate of 13.81% was the optimal threshold value for predicting the clustering risk of school PTB outbreaks, with ROC area under the curve (AUC) of 0.87 (95% CI: 0.81-0.93). Conclusions An elevated LTBI rate among close contacts is an important early warning indicator for the clustering risk of PTB outbreaks in schools.

The relationship between the expression of IL-2 and IL-10 in the peripheral blood of HBsAg carrier pregnant women and HBV intrauterine transmission

YAN Xiaoyue, MA Sihang, HOU Wenting, WEN Leji, ZHANG Lei

2025, 29(1): 111-116. doi: 10.16462/j.cnki.zhjbkz.2025.01.018

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Abstract:
Objective To investigate the expression changes, influencing factors and predictive value of hepatitis B surface antigen (HBsAg)-positive maternal peripheral blood interleukin (IL)-2 and IL-10 levels in hepatitis B virus (HBV) intrauterine transmission. Methods An epidemiologic survey was conducted on 327 HBsAg-positive mothers who delivered at Northwest Women′s and Children′s Hospital in Shaanxi Province in 2015-2017. The levels of cytokines interleukin-2 and interleukin-10 were detected by enzyme-linked immunosorbent assay for the five hepatitis B items in the peripheral blood of pregnant women and newborns. Real-time fluorescence quantitative PCR was used for the levels of HBV-DNA, and flow-liquid microarray for the levels of cytokines IL-2 and IL-10. Multifactorial analyses were performed using a binary logistic regression analysis model, and the value of IL-2 and IL-10 in predicting transmission outcomes was analyzed using the receiver operating characteristic curve. Results The rates of dominant HBV transmission (DBT), occult hepatitis B virus transmission (OBT) and intrauterine transmission were 10.40% (34/327), 15.29% (50/327) and 25.69% (84/327), respectively. There was a significant difference in IL-10 expression between NBIT group and OBT group (Z=-2.054, P=0.040). The level of IL-10 in hepatitis B e antigen positive pregnant women was significantly higher than that in HBeAg negative pregnant women (U=8 355.000, P=0.007). Besides, the expression level of IL-10 increases with the the increase of DNA load. HBeAg-positive pregnant women were at greater risk of DBT than OBT(P < 0.001). The results of the receiver operating characteristic curve showed that IL-2 had an area under curve of 0.676 for predicting intrauterine transmission of HBV at HBV-DNA levels of 10³-10⁶ IU/mL (95% CI: 0.534-0.819, P < 0.05) and IL-10 had an AUC of 0.626 for predicting intrauterine transmission of HBV at HBV-DNA levels < 10³ IU/mL (95% CI: 0.537-0.715, P < 0.05). Conclusions The expression of IL-2 and IL-10 are increased in HBsAg carrier pregnant women, especially the expression of IL-10 increased with maternal HBeAg positivity and HBV DNA load in the NBIT group. It can be considered as a predictor index for the early prediction of HBV intrauterine occult transmission, which can provide a parameter for the immunological detection of high risk infants with HBV infection.

Trend on mortalities among the urban labor force population in Chinese mainland from 2011 to 2020 and the correlation study of influencing factors

LI Bo, HAO Xiaohong, GUO Shuyun, DONG Ruxin, CHE Linxing, LEI Lijian

2025, 29(1): 117-121. doi: 10.16462/j.cnki.zhjbkz.2025.01.019

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Objective To analyze the mortality trend and influencing factors of urban labor force population in Chinese mainland from 2011 to 2020. Methods The Joinpoint regression model was used to analyze the trends of mortality rate in urban labor force population in mainland China. Grey correlation analysis was used to evaluate the correlation strength between the type of employment unit, labor force demographic structure (age, gender, education), working hours, tobacco and alcohol consumption, major air pollutants, traffic accident fatalities, and express delivery business volume and the trend of major causes of death. Results From 2011 to 2020, the standardized mortality rate of urban labor force population in China showed a downward trend. The standardized mortality rate of top five causes of death showed a downward trend. The mortality rate of heart disease in the 35-<40-year-old group is on the rise. The results of influencing factor analysis showed that long-term work was strongly associated with malignant tumors (r=0.923), heart disease (r=0.946), cerebrovascular disease (r=0.929), injury and poisoning (r=0.919) standardized mortality. The daily mean concentration of atmospheric carbon monoxide (CO) was strongly associated with standardized mortality from respiratory diseases (r=0.904). Conclusions From 2011 to 2020, the mortality rate of urban labor force population in Chinese mainland generally shows a downward trend, but the mortality rate of heart disease in the 35-<40 age group increases year by year. Long working hours has become the biggest hidden danger to the health of Chinese mainland′s urban labor force.

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2025 Vol. 29, No. 1

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Editor

Editor-in-Chief Ye Dongqing M.D.

Assistant editor Fan Yinguang M.D.

Assistant editor Pan Haifeng M.D.

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