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Administrative Authorities: National Health Commission of the People's Republic of China
Sponsor: National Health Commission of the People's Republic of China
Editing Publishing: Editorial Board of Chinese Journal of Disease Control & Prevention
Established in: March 1997
Editor in Chief: Ye Dongqing(Anhui)
CN 34-1304/R ISSN 1674-3679
Core Journal of China
China Boutique Scientific and Technological Periodical
Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
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2025, 29(7): 745-749.
doi: 10.16462/j.cnki.zhjbkz.2025.07.001
Abstract
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Abstract:
Objective To identify genetic variants that influence the levels of metabolites in colorectal cancer (CRC), providing a theoretical basis for the prevention and diagnosis of CRC. Methods A linear regression model was used to systematically identify genetic variants significantly associated with plasma metabolite levels in a large sample of European CRC patients, defining these variants as CRC plasma metabolism quantitative trait loci (metQTLs). Subsequently, enrichment analysis was used to assess the contribution of metQTLs to the genetic risk of CRC. Polygenic risk score (PRS) model was constructed to evaluate the application value of metQTLs in identifying high-risk populations for CRC. Finally, the association between metQTLs and CRC susceptibility was verified in an independent case-control study among Chinese individuals. Results A total of 1 687 metQTL associations were identified (all false discovery rate < 0.05) among 1 198 CRC patients, and CRC metQTLs were significantly enriched in CRC susceptibility regions identified by previous genome-wide association studies (OR=1.95, 95% CI: 1.25-3.06, P=0.002). In PRS model, the risk of CRC was 1.53 times higher in the high score group compared to the low score group (HR=1.53, 95% CI: 1.43-1.63, P < 0.001). Finally, validation in the Chinese population revealed that the rs174574 A>C increased the risk of CRC in both additive (OR=1.66, 95% CI: 1.47-1.90), dominant (OR=1.28, 95% CI: 1.17-1.41), and recessive models (OR=1.57, 95% CI: 1.38-1.77). Conclusions Genetic variants affecting metabolite levels are associated with CRC susceptibility, and may be applied to stratify CRC risk and to identify high-risk populations.
2025, 29(7): 750-757.
doi: 10.16462/j.cnki.zhjbkz.2025.07.002
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Objective This study aimed to investigate the impact of living arrangements on the risks of frailty among the oldest-old in China and whether this association vary by gender and residential location. Methods Data were obtained from the 2002-2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Based on questionnaire data, living arrangements were classified as living with families, living alone, or residing in an institutional care setting, including the duration of each arrangement and the composition of cohabiting family members. Frailty status was evaluated using a frailty index composed of 39 variables. The Cox proportional hazards regression model was used to assess the impact of living arrangements on the risks of frailty, with stratified analyses conducted by gender and residential location. Results In the analysis of frailty outcomes, 7 311 participants were included, with a cumulative follow-up of 32 628 person-years. There was a negative correlation between living alone and the risk of frailty (HR=0.82, 95% CI: 0.76-0.90, P < 0.001), while living in a nursing home had no significant impact on frailty risk (P=0.065). There was no significant association between the duration of living alone or in a nursing home and the risk of frailty. No significant impact of the composition of cohabiting family members on the risk of frailty was found. The stratified analysis of gender and residence found that living alone was negatively correlated with the risk of weakness in women (HR=0.79, 95% CI: 0.71-0.87, P < 0.001), and negatively correlated with the risk of weakness in urban residents (HR=0.81, 95% CI: 0.70-0.93) and rural residents (HR=0.82, 95% CI: 0.74-0.92) (all P>0.05). Living in pension institutions was only positively correlated with the risk of weakness in men (HR=1.76, 95% CI: 1.25-2.47, P < 0.001). There was no significant difference in the composition of different cohabiting family members and the risk of frailty (all P>0.05). Stratified analysis of gender and residence found that other family members in women were positively correlated with frailty risk (HR=1.37, 95% CI: 1.01-1.86, P=0.046); Other family members in urban residents were positively correlated with frailty risk (HR=1.33, 95% CI: 1.06-1.67, P=0.014). The stratified analysis of gender and residence found that living alone was negatively correlated with the risk of weakness in women (HR=0.79, 95% CI: 0.71-0.87, P < 0.001), and negatively correlated with the risk of weakness in urban residents (HR=0.81, 95% CI: 0.70-0.93) and rural residents (HR=0.82, 95% CI: 0.74-0.92) (all P>0.05). Living in pension institutions was only positively correlated with the risk of weakness in men (HR=1.76, 95% CI: 1.25-2.47, P < 0.001). There was no significant difference in the composition of different cohabiting family members and the risk of frailty (all P>0.05). Stratified analysis of gender and residence found that other family members in women were positively correlated with frailty risk (HR=1.37, 95% CI: 1.01-1.86, P=0.046); Other family members in urban residents were positively correlated with frailty risk (HR=1.33, 95% CI: 1.06-1.67, P=0.014). Conclusions Compared to those living with families members, living alone is negatively correlated with the risk of frailty, while residing in a nursing home is positively correlated with the risk of frailty, but there are gender and place of residence differences. For elderly people living in nursing homes, further assistance is needed to build and expand their social networks; For elderly people living alone, the government can further strengthen volunteer service capabilities, enhance their sense of community belonging and social support, and further promote the development of a healthy aging society in China.
2025, 29(7): 758-764.
doi: 10.16462/j.cnki.zhjbkz.2025.07.003
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Objective To investigate the association between biological age and the risk of cardiometabolic diseases among residents in South China, providing evidence for early risk prediction. Methods This study utilized baseline data (March 2018 to December 2020) from the South China Cohort. Biological age was computed using biomarkers, including alkaline phosphatase, total cholesterol, creatinine fasting glucose, systolic blood pressure, blood urea nitrogen, serum uric acid, lymphocyte percentage, mean corpuscular volume, and white blood cell count. Participants were classified into two groups: healthy aging (biological age < chronological age) and accelerated aging (biological age > chronological age). Logistic regression models were employed to evaluate the associations between biological age and the prevalence of cardiometabolic diseases. Odds ratios (ORs) with 95% CI were calculated to compare disease risks between the two groups, with age- and gender-stratified analyses conducted to address potential confounding. Results The study included 51 045 participants: 28 762 (56.3%) in the healthy aging group and 22 283 (43.7%) in the accelerated aging group. Logistic regression analysis using chronological age, gender, body mass index, education level, smoking and drinking as covariates showed that compared with the healthy aging group, the accelerated aging group had a significantly higher likelihood of cardiovascular disease (OR=2.38, 95% CI: 2.25-2.51), hypertension (OR=2.55, 95% CI: 2.41-2.70), stroke (OR=1.39, 95% CI: 1.14-1.71), coronary heart disease (OR=1.18, 95% CI: 1.06-1.32), and diabetes (OR=3.27, 95% CI: 3.01-3.55). Stratified analysis revealed consistently higher cardiometabolic disease risks in the accelerated aging group versus the healthy aging group across age and female. Conclusions Biological age effectively identifies individuals at high risk of accelerated aging and demonstrates strong associations with cardiometabolic diseases, offering a novel approach for early screening and intervention.
2025, 29(7): 765-774.
doi: 10.16462/j.cnki.zhjbkz.2025.07.004
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Objective This study aimed to develop a Bayesian network (BN)-based risk prediction model for gout flare in asymptomatic hyperuricemia (AHU) patients to provide scientific evidence for early risk stratification. Methods This study was based on the inflammatory and immune-mediated disease cohort, from which a specialized AHU cohort was established, including 3 343 participants. A LASSO-logistic regression was used to screen complex multidimensional clinical data, and the selected variables were then incorporated into the construction of the BN model. The Markov blanket was extracted to determine the minimal conditional dependency set, and conditional probabilities were calculated. The model was validated by evaluating accuracy, area under the curve, and log-loss. Results During the follow-up period, 478 participants developed gout, with a median follow-up time of 4.145 (4.074, 4.227) years. LASSO-logistic regression identified 15 key predictors, including serum uric acid (SUA) level, glomerular filtration rate (GFR), occupation, metabolic equivalent, age, secondhand smoke exposure, white meat intake frequency, smoking, glycosylated hemoglobin, education level, high-density lipoprotein cholesterol, breakfast skipping frequency, BMI, sedentary time, and sugary drink intake frequency. The results showed that SUA levels, GFR, and BMI directly influenced gout onset in patients with AHU. Additionally, patients with AHU who had a BMI < 25.0 kg/m2, SUA≥535 μmol/L and GFR≤90 mL/(min·1.73 m2) had the highest risk of gout onset (64.3%). The model achieved an accuracy of 86.4% and a log-loss of 0.374. Conclusions The BN model developed in this study provides a novel tool for risk stratification of gout flare in AHU patients, demonstrating significant potential for early screening and precision intervention. Further multicenter validation is necessary to enhance its clinical applicability.
2025, 29(7): 775-781.
doi: 10.16462/j.cnki.zhjbkz.2025.07.005
Abstract:
Objective To investigate the association between serum uric acid and non-alcoholic fatty liver disease in an elderly population. Methods A cross-sectional study was conducted among adults aged ≥65 years recruited from three community health centers in Wuhan, China, between December 2020 and August 2022. Participants completed questionnaires, underwent physical examinations and blood biochemical testing, and were assessed for nonalcoholic fatty liver disease via abdominal ultrasonography. Logistic regression quantified the association between serum uric acid levels and NAFLD risk, expressed as odds ratios (ORs) with 95% confidence intervals (CIs). Stratified analyses by gender were performed. Results The study included 1 353 elderly participants, with an overall NAFLD prevalence of 37.32%. Logistic regression revealed that compared to the lowest serum uric acid quartile (Q1: ≤257 μmol/L), the adjusted ORs (95% CIs) for NAFLD in the Q2 (> 258-310 μmol/L), Q3 (> 311- < 370 μmol/L), and Q4 (≥370 μmol/L) groups were 1.02 (0.70-1.51), 1.63 (1.11-2.39), and 2.29 (1.50-3.51), respectively. Each 60 μmol/L increment in serum uric acid was associated with a 29% increased risk of NAFLD (OR=1.29, 95% CI: 1.16-1.44). Gender-stratified analyses demonstrated a consistent dose-response relationship between elevated serum uric acid levels and NAFLD risk in both males and females. Gender stratification analysis showed a consistent dose-response relationship between elevated serum uric acid levels and NAFLD risk in men and women. Conclusions Serum uric acid levels exhibit a significant positive association with NAFLD prevalence in the elderly, suggesting that hyperuricemia may serve as an independent risk factor for NAFLD. Proactive management of serum UA levels in older adults could contribute to NAFLD prevention strategies.
2025, 29(7): 782-789.
doi: 10.16462/j.cnki.zhjbkz.2025.07.006
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Objective To analyze the trends in the disease burden of non-alcoholic fatty liver disease (NAFLD) and other chronic liver diseases-related cirrhosis in China and globally from 1990 to 2021, predicting future trajectories, and providing evidence for prevention strategies. Methods Data on incidence, mortality, and disability-adjusted life years of NAFLD and other chronic liver diseases-related cirrhosis were extracted from the Global Burden of Disease database. Joinpoint regression analysis was used to calculate annual percentage changes (APC) and average annual percentage changes (AAPC). A Bayesian age-period-cohort (BAPC) model was applied to project disease burden up to 2035. Results In 2021, China exhibited a higher age-standardized incidence rate of NAFLD and other chronic liver diseases-related cirrhosis (621.18 per 100 000) compared to the global average (592.78 per 100 000). From 1990 to 2021, China experienced declines in age-standardized DALY rate (AAPC=-1.99%) and mortality rate (AAPC=-1.72%), while the age-standardized incidence rate increased (AAPC=0.74%). Joinpoint analysis revealed: For standardized mortality rate, it phased declines during 1990-2015, with insignificant changes post-2015; For standardized incidence rate, it gradual rise from 1990-1999 (APC=0.19%-0.56%), followed by a transient decline (APC=-1.30%) in 2000-2004, and renewed increases post-2004 (APC=0.78%-2.21%); For DALY rate, the overall reduction during 1990-2015 (APC=-2.63%--1.54%), stabilizing after 2015. Globally, age-standardized DALY and mortality rates declined with fluctuations but at slower rates than in China. BAPC projections indicated that by 2035, incident cases in China will rise by 26.50%, while deaths will decrease by 38.43%. The age-standardized incidence growth rate in China (0.74%) will remain significantly lower than the global rate, and age-standardized mortality is projected to continue declining. Conclusions Despite reductions in age-standardized disease burden in China from 1990 to 2021, the growing number of incident cases of NAFLD and related cirrhosis highlights persistent challenges in controlling these conditions. Prioritizing early intervention for metabolic disorders and strengthening prevention systems for chronic liver diseases are critical to mitigating future risks.
2025, 29(7): 790-797.
doi: 10.16462/j.cnki.zhjbkz.2025.07.007
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Objective Based on machine learning algorithms, risk prediction models for non-/hypo- response to hepatitis B vaccine of infants born to HBsAg-positive mothers in Taiyuan city were constructed to provide a reference for early identification and prevention of such high-risk infants. Methods HBsAg-positive mothers and their infants born in the Department of Obstetrics and Gynecology of the Third People′s Hospital of Taiyuan City between November 2019 and October 2023 were selected as the study population. The data were collected through questionnaire surveys and medical record reviews. The multivariate logistic regression model was used to screen risk factors. The dataset was divided using five-fold cross-validation. After that, the synthetic minority over-sampling technique resampling technique was applied to the training set data. The logistic regression, extreme gradient boosting), decision tree and random forest prediction models were constructed. The area under the curve (AUC) was used to evaluate the prediction performance of the models. Results A total of 253 HBsAg-positive maternal and infant cases were collected, and the non-/hypo- response rate was 10.28% (26/253) among infants after hepatitis B vaccination. The logistic regression model showed that maternal hepatitis B virus DNA load, the percentage of neonatal myeloid differentiation factor 88 protein, the percentage of phosphorylation of nuclear factor kappa-B protein and the percentage of plasma cell were influencing factors for the non-/hypo-response to hepatitis B vaccine in infants. Considering the above factors, the AUC of each model was above 0.800 in the validation set. The XGBoost model had the highest predictive performance, and the AUC value was 0.919. Conclusions The risk prediction model for the non-/hypo- response to hepatitis B vaccine in infants of HBsAg-positive mothers in Taiyuan city based on machine learning algorithms, especially the XGBoost algorithm, has good efficacy, which helps predict the occurrence of the non-/hypo- response to hepatitis B vaccine in infants.
2025, 29(7): 798-803.
doi: 10.16462/j.cnki.zhjbkz.2025.07.008
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Objective Using the social ecological model, this study aims to systematically investigate multi-level determinants of adolescent smoking behavior in Fujian, China, encompassing individual, familial, peer, and school dimensions, and to establish an evidence base for multidimensional intervention strategies. Methods In 2021, a multi-stage stratified cluster sampling approach was employed to recruit 7 652 students from junior, general senior, and vocational high schools in Fujian Province, with a response rate of 94.4%. Weighted complex sampling and multivariate logistic regression analyses were conducted to examine associated risk factors. Results The weighted prevalence of smoking experimentation among adolescents was 15.24% (95% CI: 14.12-16.36), with 2.92% (95% CI: 2.45-3.40) classified as current smokers. Multivariate analysis identified significant risk factors across three domains: At the family level, parental smoking was associated with a 153% increased risk of current smoking (OR=2.53, 95% CI: 1.76-3.55, P < 0.001), while adolescents receiving ≥30 CNY weekly allowance showed a 260% elevated risk (OR=3.60, 95% CI: 2.08-6.23, P < 0.001). At the peer level, those who accepted offered cigarettes had 67.63 times higher current smoking risk than those who refused (OR=67.63, 95% CI: 29.57-154.68, P < 0.001). The high-frequency teacher smoking exposure group showed 8.52 times higher risk (OR=9.52, 95% CI: 4.39-20.65, P < 0.001), and the campus smoking phenomenon group demonstrated 3.00 times elevated risk (OR=4.00, 95% CI: 2.78-5.75, P < 0.001). Conclusions Adolescent smoking behavior demonstrates significant clustering among rural populations, males, and vocational high school students. To address this, we propose a multi-level intervention framework. At the individual level, allowance restrictions combined with cognitive behavioral interventions should be implemented; at the family level, parental smoking cessation contracts with monitoring mechanisms should be established; and at the school level, teacher smoking bans alongside mandatory tobacco control curricula should be enforced. Simultaneously, the construction of healthy school should be promoted.
2025, 29(7): 804-811.
doi: 10.16462/j.cnki.zhjbkz.2025.07.009
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Objective To explore the influence of indoor environmental exposure factors during the early childhood period on attention deficit hyperactivity disorder (ADHD) in children aged 3 to 12 years old, and to provide preventive suggestions for reducing the risk of children developing ADHD. Methods From August to November 2022, a questionnaire survey was conducted in 36 kindergartns and 22 primary schools in Xinzhan District of Hefei City, Anhui Province. The general demographic characteristics of the children and their parents, related factors of indoor environmental exposure, and ADHD-like behaviors of children were investigated. Multivariate logistic regression models was used to analyze the effects of children′s and parents′ general demographic characteristics and indoor environmental exposure in early childhood on the risk of ADHD-like behaviors in children aged 3-12 years. Results A total of 14 518 children who met the screening criteria were included in this study, and 330 children with ADHD-like behaviors were confirmed by the standardized assessment process, with an overall positive rate of 2.3%. Multivariate logistic regression model results showed that: The risk of ADHD-like behaviors in children aged 7-12 years was 1.81 times higher than that in children aged 3- < 7 years (OR=1.81, 95% CI: 1.36-2.42); The risk of ADHD in children with a history of passive smoking in early childhood increased by 0.76 times (OR=1.76, 95% CI: 1.36-2.42, 1.32-2.34); Average weekly cooking time > 70-280 min (OR=2.71, 95% CI: 1.23-5.95) >280-700 min (OR=5.02, 95% CI: 2.32-10.83) and >700 min (OR=4.90, 95% CI: 2.24-10.72) were the risk factors for ADHD-like behavior in children (all P < 0.05); The gender of children was female (OR=0.42, 95% CI: 0.33-0.54), the family had the habit of indoor dust removal (OR=0.78, 95% CI: 0.61-1.00), the habit of changing bedding (OR=0.59, 95% CI: 0.38-0.91) and turning on the range hood (OR=0.53, 95% CI: 0.30-0.95) were protective factors for ADHD-like behaviors in children (all P < 0.05). Conclusions Male children, children aged 7-12 years old and their parents with relatively low education level had a higher risk of ADHD-like behaviors. The history of passive smoking, cooking oil fue (average weekly cooking time, ways to reduce cooking oil fue) and mosquito coils exposure during early childhood would increase the risk of ADHD-like behaviors in children aged 3-12 years.
2025, 29(7): 812-818.
doi: 10.16462/j.cnki.zhjbkz.2025.07.010
Abstract:
Objective To assess the knowledge among parents of preschool children regarding attention deficit hyperactivity disorder (ADHD) and its potential influencing factors, providing evidence for the prevention and intervention of ADHD in children. Methods From October to December 2022, an online questionnaire survey was conducted among parents from eight kindergartens in Xuhui District, Shanghai, using stratified cluster sampling. Knowledge levels were equally divided into high, medium, and low tertiles. Chi-square tests were used to compare differences between groups, and logistic regression was applied to explore the factors influencing parents′ knowledge levels. Results The average correct rate regarding ADHD among parents was (70.69±8.73)%. Risk factors for low knowledge level included father (aOR=2.02, 95% CI: 1.60-2.56), undergraduate (aOR=2.06, 95% CI: 1.63-2.59) or high school or below (aOR=3.87, 95% CI: 2.54-5.88) educational level, medium (aOR=1.28, 95% CI: 1.00-1.62) or low (aOR=1.99, 95% CI: 1.30-3.04) average annual family income, and less than 16 h parental time per week (8-< 16 h: aOR=1.36, 95% CI: 1.00-1.84; < 8 h: aOR=2.23, 95% CI: 1.54-3.23). Conversely, parents with age at childbirth of 31-40 years (aOR=0.77, 95% CI: 0.63-0.94) or living in a household with both parents and grandparents (aOR=0.76, 95% CI: 0.62-0.93) was possible protective factors (all P < 0.05). More than 80% of parents held negative attitudes toward children with ADHD, while there was a higher proportion among those with high knowledge levels. Conclusions Parents of preschool children had relatively limited knowledge of ADHD in Xuhui District, Shanghai. Its influencing factors included parental roles, age at childbirth, education level, family structure, average annual family income, and parental time. Also, parental attitudes toward children with ADHD tended to be negative. Those findings highlighted the need for targeted health education interventions.
2025, 29(7): 819-826.
doi: 10.16462/j.cnki.zhjbkz.2025.07.011
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Objective To explore the household transmission characteristics of acute respiratory infection (ARI) in Shanghai from April 2023 to May 2024, so as to provide a basis for the targeted implementation of prevention and control measures. Methods A prospective follow-up study was conducted, including the natural population of the Shanghai community on a household basis. The ARI incidence was followed up, and household introduction rates and secondary attack rates were calculated. Risk factors were analyzed using a generalized estimation equation, and the pairwise transmission probability within households was estimated using a Markov chain household transmission model. Results Females (RR=1.23, 95% CI: 1.08-1.41), healthcare workers (RR=1.35, 95% CI: 1.01-1.81), and people with underlying diseases (RR=1.17, 95% CI: 1.14-1.35) were more likely to become household index cases (all P < 0.05). The family secondary attack rate of ARI in the general population was 11.4% (95% CI: 10.1%-12.6%), and the secondary attack risk was higher for healthcare workers (RR=2.91, 95% CI: 1.20-7.05), children (≥18 years old) of the index cases (RR=2.34, 95% CI: 1.11-4.92), and spouses (RR=2.55, 95% CI: 1.35-4.82) (all P < 0.05). Families with more than three people had a higher secondary attack rate(25.8%) compared to two-person and three-person househoulds(attack rate=17.2%, RR=1.62, 95% CI: 1.13-2.31). The model estimated the pairwise transmission probability within households to be 0.27, with a single infector causing an average of 0.40 household ARI infections. Conclusions ARI carries a transmission risk within households, particularly among healthcare workers, adult children and spouses of index cases. Households with more than three members have a higher secondary attack rate. Enhanced intra-household prevention measures are recommended, especially for high-risk groups.
2025, 29(7): 827-834.
doi: 10.16462/j.cnki.zhjbkz.2025.07.012
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Objective To comprehensively identify candidate diagnostic biomarkers for systemic lupus erythematosus (SLE) by integrating bioinformatics technology with multiple machine learning algorithms, followed by experimental validation using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Methods The GSE81622 dataset was retrieved from the Gene Expression Omnibus database for differential expression gene analysis. The SLE-related modules were determined and the protein-protein interaction network was constructed by using the weighted gene co-expression network analysis. The least absolute shrinkage and selection operator and random forest were adopted. Three machine learning algorithms, namely random forest (recursive feature elimination with support vector machine) and recursive feature elimination with support vector machine, were used to screen key genes. The key genes were verified by qRT-PCR experiment, and the receiver operating characteristic curve was constructed to evaluate their diagnostic effect. Results Differential expression analysis identified 84 differentially expressed genes. The analysis results of the weighted gene co-expression network showed that the red module had the strongest positive correlation with SLE, and the black module had the strongest negative correlation with SLE. The protein interaction network eliminated 7 genes that had no interaction and determined the top 30 genes based on their importance. Three machine learning algorithms ultimately identified three candidate diagnostic biomarkers for SLE: RNASE2, KLRB1 and KLRF1. The results of qRT-PCR showed that there were significant differences in the expression of the three candidate diagnostic biomarkers between SLE patients and the control group. RNASE2 showed an up-regulation trend, while KLRF1 and KLRB1 showed a down-regulation trend, which was consistent with the results of bioinformatics analysis. In both the training set and the validation set, the areas under the receiver operating characteristic curves of the three candidate diagnostic biomarkers were all greater than 0.85. Conclusions RNASE2, KLRB1 and KLRF1 can be used as candidate diagnostic biomarkers for SLE and have high diagnostic value, opening up new ideas for the early diagnosis of SLE patients.
2025, 29(7): 835-843.
doi: 10.16462/j.cnki.zhjbkz.2025.07.013
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Objective To evaluate the antihypertensive effects of glucagon-like peptide-1 receptor agonist (GLP-1 RA) on overweight or obese patients with diabetes through a Meta-analysis. Methods A systematic search was conducted in the PubMed, Embase, and Cochrane Central Register of Controlled Trials databases for randomized controlled trials published up to March 8, 2025. A random-effects model was used to pool the reductions in systolic blood pressure and diastolic blood pressure. Subgroup analysis and Meta-regression were performed to assess heterogeneity. Results A total of 18 randomized controlled trials involving 10 305 participants were included. The Meta-analysis demonstrated that GLP-1 RA resulted in a reduction of systolic blood pressure by 2.95 mmHg (95% CI: -3.91 mmHg--1.98 mmHg, P < 0.001) (I2=59.2%) and diastolic blood pressure by 0.68 mmHg (95% CI: -1.23 mmHg--0.14 mmHg, P=0.001) (I2=44.4%). The effect on systolic blood pressure was consistent across different types of GLP-1 RAs. Meta-regression analysis indicated that the antihypertensive effect of GLP-1 RA was not influenced by age, gender, baseline body mass index, or the magnitude of weight reduction. Conclusions The use of GLP-1 RA significantly reduces systolic blood pressure and diastolic blood pressure in overweight or obese patients with diabetes.
2025, 29(7): 844-849.
doi: 10.16462/j.cnki.zhjbkz.2025.07.014
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Mycoplasma pneumoniae (MP) infection is one of the predominant pathogens causing community-acquired pneumonia, which can lead to outbreaks in densely populated settings. Although MP outbreaks occur sporadically, there are currently no established guidelines, protocols, or standardized procedures for outbreak investigation and response. To address this gap, the Public Health Emergency Response Committee of the Anhui Preventive Medicine Association convened a panel of experts to develop a consensus document on the management of MP outbreaks. This consensus outlines criteria for defining outbreaks of MP, among other key aspects. It aims to provide a scientific reference to enhance MP outbreak response capabilities and to standardize on-site outbreak management practices in China.
Mycoplasma pneumoniae (MP) infection is one of the predominant pathogens causing community-acquired pneumonia, which can lead to outbreaks in densely populated settings. Although MP outbreaks occur sporadically, there are currently no established guidelines, protocols, or standardized procedures for outbreak investigation and response. To address this gap, the Public Health Emergency Response Committee of the Anhui Preventive Medicine Association convened a panel of experts to develop a consensus document on the management of MP outbreaks. This consensus outlines criteria for defining outbreaks of MP, among other key aspects. It aims to provide a scientific reference to enhance MP outbreak response capabilities and to standardize on-site outbreak management practices in China.
2025, 29(7): 850-853.
doi: 10.16462/j.cnki.zhjbkz.2025.07.015
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Objective To analyze the outcomes and cost-effectiveness of lung cancer screening in Ma′anshan City, Anhui Province, China, from 2020 to 2024, and to provide evidence for optimizing screening strategies and health policies. Methods Based on screening data, we evaluated the high-risk rate, compliance rate, and positive lesion detection rate among community residents aged 50-74 years. Cost-effectiveness ratio (CER), and early detection cost index (EDCI) were calculated. Results Among 13 542 participants, 4 547 individuals were identified as high-risk (high-risk rate: 33.58%). Of these, 2 903 (compliance rate: 63.84%) underwent low-dose computed tomography (LDCT). The total screening cost was CNY 1 168 001, with a cost per detected positive nodule of CNY 2 115.94 and per suspected lung cancer case of CNY 40 275.90. The CER was CNY 13 23.61, and the overall EDCI was 0.36. The 70-74 age group exhibited the lowest EDCI (0.19). Conclusions LDCT screening in high-risk populations demonstrates cost-utility value, particularly in the 70-74 age group. Future strategies should prioritize gender-and age-specific optimization to enhance screening efficiency.
2025, 29(7): 854-862.
doi: 10.16462/j.cnki.zhjbkz.2025.07.016
Abstract:
Objective To explore the effect of short-term to nitrogen dioxide (NO2) exposure on the number of confirmed tuberculosis (TB) cases in Gansu Province from 2016 to 2020, and to provide a scientific basis for the development of targeted air quality improvement and disease early warning measures in Gansu Province. Methods Confirmed cases of tuberculosis, air pollutants and meteorological data were collected from 2016 to 2020 in Gansu Province, and a generalized additive model combined with a distributional lag nonlinear model was used to analyse the relationship between NO2 exposure and confirmed diagnosis of tuberculosis, which was further stratified by gender, age and season. Results During the study period, the average number of confirmed TB cases per day was 13.00(5.00, 19.00), and the average concentration range of NO2 was 21.20(26.28, 18.18) μg/m3. Single-contamination model analysis showed that NO2 had a statistically significant effect on the number of confirmed TB cases from lag 1 to lag 7 and lag 07, effect value reached its maximum at lag 07, with a 12.2% increase in the relative risk of confirmed TB cases for every 10 μg/m3 increase in NO2 (RR=1.122, 95% CI: 1.059-1.189). Stratified analyses showed that the correlation was most significant at a cumulative lag of 7 days for both males and females, with each 10 μg/m3 increase in NO2 concentration increasing the relative risk of a confirmed TB diagnosis by 13.9% (RR=1.139, 95% CI: 1.063-1.220) and 9.8% (RR=1.098, 95% CI: 1.021-1.181), respectively; the relative risk of a confirmed TB diagnosis increased by 12.2% (RR=1.122, 95% CI: 1.059-1.189) for those aged < 65 years and ≥ 65 years. Both < 65 years old and ≥65 years old had the largest effect value at a cumulative lag of 7 days, and each 10 μg/m3 increase in NO2 concentration increased the relative risk of confirmed TB diagnosis by 7.3% (RR=1.073, 95% CI: 1.004-1.146) and 21.9% (RR=1.219, 95% CI: 1.128-1.317), respectively; after stratification by cold and warm seasons, the cold season was associated with a higher risk of confirmed TB diagnosis, and the cold season was associated with an increase in NO2 exposure. The correlation between NO2 exposure and the number of TB diagnoses was most significant at a cumulative lag of 5 days, with a 20.8% increase in the relative risk of TB diagnosis for every 10 μg/m3 increase in NO2 concentration (RR=1.208, 95% CI: 1.073-1.361). In contrast, only lag7 was not statistically significant during the warm season, and all the rest were statistically significant, and the correlation was negative. Conclusions Short-term exposure to NO2 in Gansu Province from 2016 to 2020 increases the risk of tuberculosis, and men and the elderly are the key populations, and the cold season is a risk factor for short-term exposure to NO2. Health protection for men and the elderly should be strengthened, especially during the cold season and high pollution periods.
2025, 29(7): 863-868.
doi: 10.16462/j.cnki.zhjbkz.2025.07.017
Abstract:
Objective To investigate the causal relationship between genetically predicted childhood obesity and non-alcoholic fatty liver disease (NAFLD), and to provide a genetic basis for early prevention and intervention strategies of NAFLD in childhood and adulthood. Methods We conducted a two-sample Mendelian randomization (MR) study, selecting single nucleotide polymorphisms (SNPs) associated with childhood obesity from large-scale genome-wide association analyses as instrumental variables (with no linkage disequilibrium), and used NAFLD as the outcome to assess the potential causal relationship between childhood obesity and NAFLD. Results Inverse variance weighted analysis demonstrated a positive causal relationship between childhood obesity and NAFLD (OR=1.526, 95% CI: 1.298-1.793, P < 0.001). The odds ratios of weighted median method (OR=1.454, 95% CI: 1.205-1.757, P < 0.001) and MR Egger regression analysis (OR=1.257, 95% CI: 0.925-1.707, P=0.163) were both greater than 1.000, consistent with the results of inverse variance weighting analysis in direction. Conclusions Childhood obesity increases the risk of developing NAFLD, necessitating enhanced early intervention and targeted health education to reduce the risk of NAFLD in adulthood.
