To understand the current application status and internal and external characteristics of national health management-related policies in China, and to provide references for improving the national health management policy system.

A content analysis method was adopted, and a two-dimensional framework of "core areas of national health management–policy tools" was constructed to quantitatively analyze the included documents.

A total of 102 national-level policy documents related to national health management were included. Among the 503 policy text codes, environment-oriented policy tools accounted for the highest proportion (61.63%), followed by supply-oriented (26.84%) and demand-oriented (11.53%) tools. The existing policies' attention to health fields, ranked from high to low, were health services and security (43.34%), healthy living (33.20%), healthy environment (19.48%), health industry (2.19%), and health level (1.79%).

The use of environment-oriented policy tools in national health management-related policies can be moderately reduced, while strengthening the formulation of demand-oriented policies, optimizing the internal structure of policy tools, and ensuring balanced coverage of different health fields.

To investigate active health participation (including health-related self-management and self-empowerment) and its determinants among community-dwelling adults, and to provide evidence for the development of relevant policies and effective chronic disease control and prevention services.

The data were derived from two surveys conducted among 1 598 community-dwelling adults (aged ≥18 years) recruited through multistage random sampling: the first in Jinan city, Shandong province (August–October 2022), and the second in Neijiang city, Sichuan province (April–May 2023). The surveys used a questionnaire on health knowledge, attitude, and practice (KAP) and health care utilization, the 10-item Kessler Psychological Distress Scale (K10), and the EuroQol-5 Dimensions (EQ-5D). Active health participation was assessed by self-reported health-related self-management and self-empowerment practices. Multiple logistic regression analysis was employed to identify influencing factors, based on the three dimensions of Andersen’s Behavioral Model for healthcare utilization.

Of the 1 598 participants with valid responses, 905 (56.6%) were classified as active health participants. Multiple binary logistic regression analysis showed that place of residence (towns vs. rural, odds ratio [OR] = 0.51, 95%confidence interval [CI]: 0.34–0.75), awareness of hypertension (no vs. yes, OR = 0.67, 95%CI: 0.53–0.86), average monthly household income (> 8 000 vs. < 2 000, OR = 2.76, 95%CI: 1.34–5.69), availability of free health screening programs (no vs. yes, OR = 0.49, 95%CI: 0.27–0.89), community health education programs (no vs. yes, OR = 0.27, 95%CI: 0.17–0.44), community provision of blood glucose and blood pressure testing (no vs. yes, OR = 0.63, 95%CI: 0.42–0.93), and individual EQ-5D score (OR = 0.23, 95%CI: 0.10–0.56) were significantly associated with active health participation.

The awareness of active health participation among community-dwelling adults in Sichuan and Shandong provinces remains relatively low and is primarily influenced by education level, economic income, availability of community health resources, and health-related quality of life. These findings highlight the urgent need to improve health awareness and address regional disparities in resource allocation.

To understand the characteristics of healthcare utilization outcomes among residents, analyze the influence of health literacy on these outcomes, and provide a reference for improving them.

From October 2022 to April 2023, a stratified, multi-stage, random, and convenient sampling method was used to select 6 153 residents aged 15–69 years in Jiangsu province for a questionnaire survey. Latent class analysis and multi-factor logistic regression were used to analyze the influencing factors of different categories of healthcare utilization outcomes.

The healthcare utilization outcomes of the surveyed population could be divided into two latent classes: a better outcome group (83.1%) and a worse outcome group (16.9%). Statistically significant differences in healthcare utilization outcomes were observed across different ages, genders, marital statuses, education levels, annual incomes, chronic disease statuses, and health literacy levels (all P < 0.05). Multi-factor logistic regression analysis showed that compared with those with high health literacy, aged 15–24 years, male, and without chronic diseases, the following groups had a higher risk of being in the worse outcome group: those with low health literacy (OR = 1.306, 95%CI: 1.013–1.683); those aged 25–34 years (OR = 1.620, 95%CI: 1.034–2.538), 45–54 years (OR = 1.938, 95%CI: 1.208–3.110), 55–64 years (OR = 2.501, 95%CI: 1.551–4.033), and 65–69 years (OR = 2.926, 95%CI: 1.703–5.027); females (OR = 1.402, 95%CI: 1.201–1.636); and those with chronic diseases (OR = 3.033, 95%CI: 2.612–3.523).

High health literacy has a positive impact on residents′ healthcare utilization outcomes, and improving residents′ health literacy is of great significance for improving these outcomes.

To assess the exposure to and health risks from endocrine-disrupting chemicals (EDCs) in primary and secondary school students.

The participants of this study were 330 primary and secondary school students who were selected at random from visitors to the Sleep Research Center of Shenzhen People′s Hospital between July and September of 2022. The students provided bedtime and next-morning urine samples and completed questionnaire surveys. A triple quadrupole-linear ion trap mass spectrometer was utilized to assess the concentrations of 34 EDCs, encompassing 7 organophosphate flame retardants (OPFRs), 3 parabens (PBs), 10 phthalates (PAEs), 4 benzophenones, 7 synthetic phenolic antioxidants (SPAs), and 3 bisphenols, in both bedtime and morning urine samples to estimate the students' daily intake (EDI) of these EDCs.

Most EDCs were detected at rates exceeding 40% in both bedtime and morning urine samples from 330 participants ultimately included in the analysis. The highest detection rates were observed for monomethyl phthalate (MMP), mono[2-(carboxymethyl)hexyl] phthalate (MMCHP), and mono [2-ethyl-5-carboxypentyl] phthalate (MECPP). Di (2-ethylhexyl) phthalate (DEHP) had the highest EDI, with the mean EDI from morning samples exceeded the RfD. Seventy-two students (21.8%) had a phthalate HI greater than one.

The cumulative exposure to PAEs among primary and secondary school students in Shenzhen is relatively high, posing potential health risks. To mitigate these risks, it is advisable to minimize contact with products containing PAEs.

To analyze the association between short-term ozone (O₃) exposure and emergency ambulance dispatches (EAD) in Dezhou city, Shandong province, and to provide scientific evidence for O₃ pollution control and public health interventions from a health perspective.

Daily all-cause EAD data recorded by the Dezhou 120 Emergency Dispatch Command Center from January 1, 2020, to December 31, 2022, as well as meteorological data and pollutant data from the China Meteorological Data Network and the China High Air Pollutants dataset during the same period, were collected and matched according to the calling address. A time-stratified case-crossover design was adopted to analyze the impact of short-term O₃ exposure on EAD in Dezhou city by integrating a distributed lag non-linear model (DLNM) with a conditional logistic regression model. Subgroup analyses were conducted to explore vulnerable populations.

The number of EAD in Dezhou city from January 1, 2020, to December 31, 2022, was 344 287, with 1 096 case days and 3 728 matched control days. After excluding the influence of average temperature and relative humidity, the time-stratified case-crossover analysis showed a positive correlation between short-term O₃ exposure lagged 0–7 days and the cumulative risk of EAD. For every interquartile range (IQR) increase in the daily maximum 8-hour average O₃ concentration, the cumulative risk of EAD increased by 8% (OR = 1.08, 95%CI: 1.04–1.11). The single-day lag effect analysis showed that the cumulative effect of short-term O₃ exposure on EAD risk was greatest on the day of exposure (OR = 1.06, 95%CI: 1.05–1.08), decreased rapidly within 2 days, and a potential harvesting effect appeared on days 2–4. Subgroup analyses showed that for every IQR increase in the daily maximum 8-hour average O₃ concentration, the cumulative risk of EAD increased by 9% (OR = 1.09, 95%CI: 1.04–1.13) in males, 6% (OR = 1.06, 95%CI: 1.01–1.11) in females, 6% (OR = 1.06, 95%CI: 0.99–1.13) in the < 35 age group, 6% (OR = 1.06, 95%CI: 1.01–1.11) in the 35–65 age group, 10% (OR = 1.10, 95%CI: 1.05–1.15) in the > 65 age group, 4% (OR = 1.04, 95%CI: 1.01–1.07) in the cold season, and 7% (OR = 1.07, 95%CI: 1.04–1.11) in the warm season. Sensitivity analyses showed that with 8-day and 9-day lags in short-term O₃ exposure, the cumulative risk of EAD increased by 8% (OR = 1.08, 95%CI: 1.04–1.11) and 8% (OR = 1.08, 95%CI: 1.05–1.12), respectively, for every IQR increase in the daily maximum 8-hour average O₃ concentration. When the degrees of freedom for the lag dimension in the model were 5 and 6, the cumulative risk of EAD increased by 7% (OR = 1.07, 95%CI: 1.04–1.11) for every IQR increase in the daily maximum 8-hour average O₃ concentration. After additionally adjusting for gaseous pollutants NO₂ and SO₂ in the model, the cumulative risk of EAD increased by 9% (OR = 1.09, 95%CI: 1.06–1.13) and 8% (OR = 1.08, 95%CI: 1.05–1.12), respectively, for every IQR increase in the daily maximum 8-hour average O₃ concentration. Changing the maximum lag days of O₃ and the degrees of freedom of the lag dimension in the model, as well as adjusting for gaseous pollutants NO₂ and SO₂ in the model, did not result in statistically significant differences from the main model results (all P > 0.05), indicating the robustness of the model.

Short-term O₃ exposure can increase the risk of EAD in Dezhou city, with greater impacts on males, individuals over 65 years of age, and EAD during the warm season.

To investigate the migration characteristics of lead (Pb), cadmium (Cd), chromium (Cr), mercury (Hg), arsenic (As), copper (Cu), zinc (Zn), and nickel (Ni) in soil and rice in Wanzhou district, Chongqing city, and to assess their potential health risks, providing data support for the formulation of scientific prevention and control strategies.

Based on previous soil monitoring data, five representative areas were selected in Wanzhou district, Chongqing city, in August - September 2023. A stratified sampling method was used to establish 25 sampling points. The geo-accumulation index and potential ecological risk index methods were used to evaluate soil pollution. At each sampling point, contiguous paddy fields were selected, and corresponding soil and rice samples were collected, with 25 samples for each. The migration characteristics of heavy metals and their potential impact on human health were analyzed using the bioconcentration factor and health risk assessment model.

A total of 25 soil samples were collected, mostly acidic. Except for zinc (Zn), the average values of other heavy metals did not exceed the soil background values. Cadmium (Cd) exceeded the risk screening value at three sampling points but did not exceed the risk control value; other heavy metals did not exceed the risk screening value. Mercury (Hg) had the largest coefficient of variation, > 1 (1.03), indicating its highly uneven distribution. The geo-accumulation index assessment showed no overall soil pollution. Ecological risk assessment indicated that Hg and Cd contributed the most to ecological hazards, at 44.65% and 36.76%, respectively. Among the 25 rice samples, Cr had the highest over-standard rate at 80.00%, followed by Hg, As, and Cd, all at 12.00%. Enrichment factor analysis showed that Cd and Hg had higher enrichment factors in rice, at 0.341 and 0.329, respectively. Health risk assessment showed that, except for As, other heavy metals posed low chronic health risks, but the combined health risk of heavy metals in rice may have chronic effects on human health (mean = 3.53).

There is a certain degree of Cd and Hg migration pollution in the soil and rice of Wanzhou district, Chongqing city. Arsenic (As) may have chronic health effects on humans, and there may be synergistic effects of multiple metals.

To assess iodine intake levels and their impact on thyroid volume in children aged 8–10 years in a district of Beijing city from 2022 to 2024.

From 2022 to 2024, 200 non-boarding students aged 8–10 years were randomly selected annually from five townships in the district, totaling 600 participants over the three years. Urine samples, household salt samples, and ultrasound-measured thyroid volumes were collected. Generalized estimating equations (GEE) models were used to analyze annual trends and conduct sensitivity analyses by sex.

The median urinary iodine concentrations (UICs) in children aged 8–10 years from 2022 to 2024 were 170.96, 157.35, and 163.10 µg/L, respectively, indicating overall stability in UICs. However, a slight increasing trend in UICs was observed in boys over the years (P = 0.032). The mean salt iodine content (SIC) from 2022 to 2024 was (17.76 ± 7.96), (16.78 ± 11.48), and (16.27 ± 9.08) mg/kg, respectively, showing slight variations across the years. GEE model results showed that, after controlling for other factors, boys had larger thyroid volumes than girls (β = 0.32, 95%CI: 0.10–0.49); increasing age had a positive and significant effect on thyroid volume (β = 0.56, 95%CI: 0.46–0.64). Compared to girls, boys had higher mean UICs (β = 5.68, 95%CI: 3.10–7.79); SIC had a significant positive effect on UICs (β = 0.08, 95%CI: 0.02–0.14). Sensitivity analyses by sex revealed that the effect of SIC on UICs was significant and positive in both boys (β = 0.56, 95%CI: 0.27–0.86) and girls (β = 1.20, 95%CI: 0.01–0.80), while the direct effect of SIC on thyroid volume was not significant in either boys (β = 0.17, 95%CI: –0.40–0.60) or girls (β = 0.19, 95%CI: –0.50–0.80).

In iodine-sufficient environments, thyroid volume is primarily influenced by physiological factors such as age and sex, with salt iodine intake having no significant effect on thyroid volume. However, SIC is positively correlated with UIC. Iodine monitoring can focus on UIC measurements, as changes in thyroid volume are relatively small under iodine-sufficient conditions.