Objective:To evaluate the mediating effect of electrocardiographic (ECG) indicators in the association between short-term exposure to fine particulate matter (PM 2.5) and blood pressure and to explore the key PM 2.5 element constituents that produce the mediating effect. Methods:Based on a cross-sectional survey across 10 cities in the Beijing-Tianjin-Hebei region and surrounding areas, PM 2.5 and its element constituents were collected from the nearest air monitoring superstation. Blood pressure and ECG indicators of participants were obtained through physical examinations. A multivariate linear regression was used to evaluate the effect of short-term exposures to PM 2.5 on blood pressure. A mediation analysis was used to identify the mediating effect of ECG indicators in the association between exposure to PM 2.5 and its element constituents and blood pressure. Results:The age of the 1 793 participants was (65.1±13.3) years, and 885 (49.4%) were males. During the study period, the daily mean concentration of PM 2.5 was (70±45) μg/m 3, and the systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP) were (139±20), (82±11), (101±13), and (57±17) mmHg (1 mmHg=0.133 kPa), respectively. The results of the multivariate linear regression showed that for every 10 μg/m 3 increase in PM 2.5 on the same day (lag 0), DBP increased by 0.15 (95% CI: 0.02-0.28) mmHg, and PP decreased 0.18 (95% CI: 0.36-0.01) mmHg. The exposure to 14 elemental constituents, such as Ga, Co and Se, was associated with an increase in DBP, while the exposure to 17 elemental constituents, such as Cs, Se and Ag, was associated with a decrease in PP. At lag 0, the PM 2.5-induced increase in DBP was mediated by the QRS interval (mediation percentage of 18.98%), and the PM 2.5-induced decrease in PP was mediated by the QT interval (mediation percentage of -6.31%). The exposure to K, Br, Pb, Zn, Ca, Co, Pd, Cu, and As constituents was associated with increases in DBP mediated by prolonged QRS interval. The exposure to Pb, Zn, K, and As constituents was associated with decreases in PP mediated by prolonged QRS interval. Conclusion:ECG indicators such as QRS interval may mediate the association between short-term exposure to PM 2.5 and its element constituents and blood pressure.

Objective:To assess the effect of short-term exposures to atmospheric fine particulate matter (PM 2.5) and its components on cognitive function in middle-aged and older people aged 40-89 and identify key components that affect cognitive function. Methods:From October 2018 to March 2019, a cross-sectional survey of middle-aged and older people aged 40-89 was conducted across 10 cities in Beijing-Tianjin-Hebei and neighboring regions of China. Data on PM 2.5 and its components were collected from the nearest air supermonitoring stations to the residential addresses. The cognitive function was assessed using the Min-Mental State Examination (MMSE) scale. Multiple linear regression models were used to assess the effect of short-term exposures to PM 2.5 and its components on cognitive function in middle-aged and older people. The restricted cubic spline function was used to fit the exposure-response relationship between different components and changes in MMSE scores. Results:The age of the 1 978 respondents was (65.1±13.4) years, and 976 (49.34%) were males. During the study period, the daily mean concentration of PM 2.5 was (71.2±43.2) μg/m 3, and the MMSE score was (28.2±3.7). The results of the multiple linear regression model showed that short-term exposures to PM 2.5 and its components were associated with cognitive decline in middle-aged and older people after adjusting for confounding factors, and the effect was higher at lag 0-28 days. For an interquartile range (64.3 μg/m 3) increase in PM 2.5 at lag 0-28 d, the MMSE score decreased by 5.91 (95% CI: 0.04, 11.77). For an interquartile range increase in organic carbon (OC), antimony (Sb), chromium (Cr), zinc (Zn), tin (Sn), and cadmium (Cd), the MMSE scores of middle-aged and older people decreased by 5.71 (95% CI: 1.69, 9.73), 4.67 (95% CI: 2.50, 6.84), 4.49 (95% CI: 1.05, 7.92), 3.65 (95% CI: 0.89, 6.42), 2.76 (95% CI: 1.22, 4.30), and 1.72 (95% CI: 0.53, 2.92). Conclusions:Short-term exposures to atmospheric PM 2.5 and its components (OC, Sb, Cr, Zn, Sn, and Cd) are associated with cognitive decline in middle-aged and older people.

Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.

Objective:To evaluate the levels and source of cadmium exposure by dietary pathway among middle-aged and elderly people ≥40 in cadmium-contaminated areas of China.Methods:A total of 7 193 people aged 40-89 years from four typical cadmium-contaminated areas in China were selected as the study subjects. Food Frequency Questionnaire (FFQ), Total Diet Study (TDS) and a 3-day-24-hour dietary recall survey were conducted. Dietary cadmium intake and food sources through dietary pathways were assessed based on cadmium content in foods, consumption amounts and intake frequencies.Results:The mean age of the participants was 63.39±12.21 years, with 50.05% being males. The average monthly dietary cadmium intake was 7.39 μg/(kg·BW). Staple foods and vegetables were the primary sources of dietary cadmium intake, accounting for 57.51% and 32.48%, respectively. The monthly dietary cadmium intake in all surveyed regions did not exceed the Provisional Tolerable Monthly Intake (PTMI) recommended by the Joint FAO/WHO Expert Committee on Food Additives (JECFA).Conclusion:The monthly dietary cadmium intake among middle-aged and elderly people in cadmium-contaminated areas of China is relatively low, with the risk remaining at an acceptable level. Staple foods and vegetables are the most significant contributors to dietary cadmium intake.

Objective:To describe the body mass index (BMI) level and long-term trends of Chinese older adults aged 65 and above.Methods:Older adults aged 65 and above from six waves (2002-2018) of the China Longitudinal Healthy Longevity Survey were selected as the study population. Multiple cross-sectional design with six survey waves conducted in 2002, 2005, 2008, 2011, 2014, and 2018 was adopted, enrolling 15 647, 15 358, 15 622, 9 166, 6 302, and 12 417 participants, respectively. Additionally, a total of 13, 755 participants were included in the cohort study design. Relevant information was collected through questionnaires and physical examinations. The χ2 trend test was used to compare the changes in the rates of underweight and overweight/obesity over the years, and the linear mixed-e?ects model (LMM) was used to fit trajectory curves of BMI changes with advancing age in older adults. Results:The baseline ages of the participants included in 2002, 2005, 2008, 2011, 2014, and 2018 were (85.16±11.26), (84.23±11.83), (84.99±12.16), (81.10±11.86), (78.89±11.30), and (83.08±12.42) years, respectively, with a relatively high proportion of females and rural residents. In the cohort study, the 13 755 participants had a median ( Q1, Q3) follow-up time of 6.5 (5.2, 10.0) years, with a cumulative follow-up duration of 109 041 person-years. In each wave, males had higher BMI than females, urban residents had higher BMI than rural residents, and BMI gradually decreased with increasing age (all P<0.001). The mean BMI of older adults in China increased from (19.37±3.80) kg/m2 in 2002 to (22.04±4.01) kg/m2 in 2018 ( P<0.001). Across all survey years, the prevalence of underweight was consistently higher in women than in men and in rural areas than in urban areas, with an upward trend as age increased (all P<0.001). In 2018, the underweight rates in the 65-79, 80-89, 90-99, and ≥100-year-old age groups were 8.0%, 16.7%, 26.2%, and 35.5%, respectively. Meanwhile, the prevalence of overweight/obesity was higher in men than in women and in urban areas than in rural areas, showing a declining trend with advancing age (all P<0.001). The prevalence of underweight among the older adults decreased significantly from 45.2% in 2002 to 18.9% in 2018 ( P<0.001), while the prevalence of overweight/obesity increased from 11.0% in 1998 to 29.6% in 2018 ( P<0.001). The trajectory curves fitted by the LMM model showed that individuals born in later decades had higher BMI levels at the same age compared to earlier cohorts. Conclusion:From 2002 to 2018, the BMI level among Chinese older adults showed an increasing trend. The prevalence of underweight showed a declining trend, while the rates of obesity and overweight increased. However, the underweight rate remained notably high among the oldest old.

Objective:To determine the optimal cut-off value of serum cotinine for distinguishing smoking status among Chinese adults based on a large-scale national sample.Methods:A cross-sectional study was conducted among 8 987 Chinese adults aged 20-79 years from 152 administrative counties across 31 provinces during 2017-2018. Sociodemographic characteristics, lifestyle, smoking status, and health status were collected via questionnaires and physical examinations. Blood samples were analyzed for serum cotinine levels using liquid chromatography-mass spectrometry and for blood creatinine levels using the picric acid method. Receiver operating characteristic (ROC) curve analysis was performed with serum cotinine concentration as the test variable and self-reported smoking status as the state variable. The optimal cut-off value was determined based on the maximum Youden′s index, and the bootstrap method was used for repeated sampling (2 000 times) to evaluate the confidence interval of the cut-off value. The net reclassification index (NRI) was used to evaluate the discrimination ability of the cut-off value of this study, the cut-off value of the American population 1 (total population: 3.3 μg/L, men: 4.1 μg/L, women: 3.0 μg/L) and the cut-off value of the American population 2 (the recommended value of the United States Centers for Disease Control and Prevention for the total population: 10.0 μg/L) against the smoking status of the Chinese population. Statistical analyses were conducted using IBM SPSS 27 and Python 3.11, with a significance level of α=0.05.Results:The age of the research subjects was (49.2±15.2) years. Among them, males accounted for 49.8% (4 477); smokers accounted for 28.8% (2 586); the detection rate of serum cotinine was 94.6% (8 501), and the M ( Q1, Q3) concentration of serum cotinine was 0.9 (0.3, 85.4) μg/L. The ROC curve analysis results showed that the cut-off value (95% CI) of serum cotinine in the total population was 8.8 (6.7-11.7) μg/L, with the specificity (95% CI) about 93.6%(92.7%-94.3%), the sensitivity (95% CI) about 91.0%(89.7%-92.3%) and the area under the curve (AUC) (95% CI) about 0.93 (0.92-0.94). The cut-off value (95% CI) of cotinine for males was 17.1 (8.8-21.8) μg/L, with the specificity (95% CI) about 90.7%(87.9%-92.0%), the sensitivity (95% CI) about 89.4%(88.4%-92.2%) and the AUC (95% CI) about 0.92 (0.91-0.93). The cut-off value (95% CI) of cotinine for females was 7.4 (3.3-15.0) μg/L, with the specificity (95% CI) about 95.6%(92.7%-96.8%), the sensitivity (95% CI) about 87.6%(81.6%-92.8%) and the AUC (95% CI) about 0.92 (0.87-0.95). The NRI analysis results showed that compared with the cut-off value of the American population 2, the NRI of this study′s cut-off values in the total population, males and females were 0.020 ( P=0.015), 0.033 ( P=0.015) and 0.011 ( P=0.380), respectively, indicating that this study′s cutoff value could have better classification performance in the total population and males. Compared with the cut-off value of the American population 2, the NRI of the total population in this study was 0.001 ( P=0.285). Conclusion:The serum cotinine cut-off value based on the analysis of large sample data in China is more suitable for distinguishing the smoking status of Chinese adults.

In 2025, Chinese Medical Association commemorates its 110th anniversary. Over this century-spanning journey in medical advancement, human biomonitoring (HBM) has emerged as a pivotal tool in environmental medicine for assessing population exposure to environmental pollutants and associated health risks. Since the dawn of the 21st century, China has actively advanced its HBM technological framework, providing critical scientific support for chemical regulation policies and public health protection. Chinese Journal of Preventive Medicine has consistently chronicled progress in this field, publishing high-impact research and serving as a key platform for academic exchange and knowledge dissemination.Marking this milestone, this article systematically reviews the current state of global HBM development, elucidates its indispensable role in preventive medicine, and highlights advancements and technical innovations within China′s National Human Biomonitoring Program. It further examines persistent challenges and outlines future directions, offering scientific support for precision interventions in environmental health risks under the "Healthy China 2030" strategy.

Objective:To investigate the association between blood selenium levels and sex hormones in Chinese men aged 18-79 years.Methods:Data were derived from the China National Human Biomonitoring survey conducted in 2017-2018, with a final sample size of 5 414 men. General demographic characteristics, behavioral habits, and dietary frequency were collected through questionnaires and physical examinations. Fasting blood samples were collected to measure blood lead, serum testosterone, and estradiol levels. Complex sampling linear regression models were used to analyze the associations between blood selenium levels and testosterone, estradiol, and the testosterone/estradiol ratio, adjusting for confounding factors including age, education level, marital status, smoking status, alcohol consumption, seafood intake, soy product intake, protein supplement intake, BMI, and diabetes status.Results:The mean age of the 5 414 participants was (46.85±27.91) years; 4 774 (91.65%) were of Han ethnicity and 4 505 (86.68%) were married. The median ( Q1, Q3) blood selenium concentration in men was 97.80 (80.64, 116.99) μg/L. After adjusting for confounding factors, the complex sampling linear regression model revealed negative associations between blood selenium levels and both testosterone levels and the testosterone/estradiol ratio, with a significant linear trend ( Ptrend<0.05). Compared with the Q1 group, the β (95% CI) values for testosterone in the Q2, Q3, and Q4 groups were -0.02 (-0.06 to 0.02), -0.03 (-0.08 to 0.01), and -0.06 (-0.09 to -0.02), respectively. Similarly, the β (95% CI) values for the testosterone/estradiol ratio in the Q2, Q3, and Q4 groups were -0.01 (-0.03 to 0.02), -0.01 (-0.04 to 0.04), and -0.03 (-0.06 to -0.01), respectively. Subgroup analysis indicated stronger associations between blood selenium levels and testosterone/estradiol levels in non-smoking and obese men (BMI≥28 kg/m2). Conclusion:Blood selenium levels are negatively associated with testosterone levels and the testosterone/estradiol ratio in Chinese adult males.

Objective:To explore the association of blood and urinary cadmium levels with lipid profile levels and dyslipidemia in Chinese adults aged 18 to 79 years.Methods:Based on the China National Human Biomonitoring (CNHBM) program, a cross-sectional survey was conducted from 2017 to 2018 using a multi-stage stratified random sampling method, including a total of 10 713 adults aged 18 to 79 years. Data was obtained through questionnaires, physical examinations, biological sample collection, and laboratory testing. Multiple linear mixed effect model (MLMM) and generalized linear mixed effect model (GLMM) were used to analyze the association of blood and creatinine-corrected urinary cadmium levels with lipid profile levels as well as dyslipidemia among adults.Results:The age of 10 713 participants was (47.23±0.24) years, with 5 372 males accounting for 61.3% of the national population. The weighted mean±standard error (SE) of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) was (5.21±0.03), (1.86±0.03), (2.96±0.03), and (1.43±0.01) mmol/L, respectively. The prevalence rate of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, low HDL-C, and high LDL-C was 16.0%, 21.6%, 6.6%, 13.5%, and 10.0%, respectively. MLMM showed that, after adjusting for relevant confounders, log-transformed blood cadmium levels were positively associated with increased levels of TC, TG and LDL-C ( P<0.05). When blood cadmium levels were categorized into quartiles, compared to the lowest exposure group ( Q1), participants in the highest blood cadmium exposure group ( Q4) had increases of 0.19 (95% CI: 0.06, 0.32) mmol/L in TC and 0.25 (95% CI: 0.08, 0.43) mmol/L in TG. GLMM indicated that, after adjusting for confounders, higher blood cadmium exposure levels were associated with increased risks of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, and high LDL-C ( P<0.05). Further analysis by quartiles showed that, compared to the blood cadmium Q1 exposure group, the OR value (95% CI) for the Q4 group was 1.53 (1.12, 2.08) for hypercholesterolemia, 1.54 (1.09, 2.17) for hypertriglyceridemia, 2.24 (1.47, 3.40) for mixed hyperlipidemia, and 1.49 (1.07, 2.09) for high LDL-C. Conclusion:The cadmium internal exposure levels are associated with blood lipid profile levels as well as the incidence of dyslipidemia in Chinese adults aged 18 to 79.

Objective To develop an innovative recognition algorithm that aids physicians in the identification of pulmonary nodules. Methods Patients with pulmonary nodules who underwent thoracoscopic surgery at the Department of Thoracic Surgery, Affiliated Drum Tower Hospital of Nanjing University Medical School in December 2023, were enrolled in the study. Chest surface exploration data were collected at a rate of 60 frames per second and a resolution of 1 920×1 080. Frame images were saved at regular intervals for subsequent block processing. An algorithm database for lung nodule recognition was developed using the collected data. Results A total of 16 patients were enrolled, including 9 males and 7 females, with an average age of (54.9±14.9) years. In the optimized multi-topology convolutional network model, the test results demonstrated an accuracy rate of 94.39% for recognition tasks. Furthermore, the integration of micro-variation amplification technology into the convolutional network model enhanced the accuracy of lung nodule identification to 96.90%. A comprehensive evaluation of the performance of these two models yielded an overall recognition accuracy of 95.59%. Based on these findings, we conclude that the proposed network model is well-suited for the task of lung nodule recognition, with the convolutional network incorporating micro-variation amplification technology exhibiting superior accuracy. Conclusion Compared to traditional methods, our proposed technique significantly enhances the accuracy of lung nodule identification and localization, aiding surgeons in locating lung nodules during thoracoscopic surgery.