OBJECTIVES: To analyze bone mass distribution and the factors affecting bone mass in a general Chinese Han cohort undergoing physical examinations at our center. METHODS: We retrospectively collected the data of bone mineral density (BMD) measurements from 30 599 healthy Han Chinese adults (age≥20 years) who underwent dual-energy X-ray absorptiometry scans at our hospital from July, 2013 to July, 2023. Basic parameters including height, body weight, and gender were recorded, and descriptive statistics and correlation analyses were performed using R software. RESULTS: In this cohort, the male individuals had a mean peak BMD of 1.00±0.12 g/cm² in the lumbar vertebrae, 0.94±0.14 g/cm² in the femoral neck, and 0.99±0.13 g/cm² in the total hip, significantly higher than the values in the female individuals [0.99±0.12 g/cm² in the lumbar vertebrae (P=0.022), 0.79±0.11 g/cm² in the femoral neck (P<0.001), and 0.88±0.11 g/cm² in the total hip (P<0.001)]. In the overall cohort, the BMD values of the lumbar spine and femur decreased with age after reaching their peak levels. There was a positive correlation between BMD value and body mass index (BMI) in both male and female individuals. The 2013-2014 period recorded the lowest BMD values in the lumbar, hip, and femoral neck, which tended to increase steadily in the following years (2015-2023). CONCLUSIONS Our data suggest that the BMD values vary among different populations, and future multi-center studies using more accurate BMD detection technology are warranted to capture the variation patterns of BMD with demographic characteristics of specific populations.
Humans ; Bone Density ; Absorptiometry, Photon ; Male ; Female ; Retrospective Studies ; Osteoporosis/diagnostic imaging* ; Adult ; Middle Aged ; Lumbar Vertebrae/diagnostic imaging* ; China/epidemiology* ; Femur Neck/diagnostic imaging* ; Aged ; Beijing/epidemiology* ; Young Adult

PURPOSE: Polytrauma is still a challenge for health care organizations. Today, the search for factors to reduce lethality continues. This study aims to describe the causes of death associated with polytrauma in 1 year. METHODS: This retrospective study analyzed autopsy data of trauma deaths in Moscow for the whole of 2017. We identified victims with polytrauma, taking into account the Berlin definition as the main inclusion criteria with penetrating and blunt trauma. Each forensic report had information about the pre-hospital and hospital stages of treatment and autopsy data. The exclusion criteria for this study were: isolated injury, forensic reports not related to the examination of entire corpses, and autopsy studies of children (<18 years old). Statistical analysis was performed according to basic principles, including a comparison of groups using the Chi-squared test with Bonferroni comparison test and Fisher's exact test. The critical level of significance (p value) in testing statistical hypotheses in this study was taken as 0.05. RESULTS: We analyzed 2337 forensic medical examinations of victims who died of trauma in Moscow in 2017, of which 41.5% (n = 969) were polytrauma deaths. Most of the victims (65.4%, n = 634) died on the scene, and only 30.0% were admitted to the hospital. The most frequent cause of death was bleeding (72.0%, n = 698), followed by traumatic brain injury (43.8%, n = 424). They accounted for the first peak (78.4%, p = 0.005) of deaths, occurring in the first hours. Then these causes of death in the first peak go down in a few hours, and the second peak of mortality appears in 3 - 7 days (p = 0.001). CONCLUSIONS This is the largest full-year autopsy study of polytrauma victims. Our data show that the main cause of polytrauma death is massive bleeding, with a lethality peak in the first hours after injury. The time distribution of polytrauma deaths has a bimodal pattern - the second period of polytrauma deaths occurs in 3 - 7 days.
Humans ; Retrospective Studies ; Male ; Female ; Moscow/epidemiology* ; Autopsy ; Multiple Trauma/mortality* ; Adult ; Adolescent ; Middle Aged ; Child ; Child, Preschool ; Cause of Death ; Young Adult ; Infant ; Aged ; Aged, 80 and over

BACKGROUND: Children's respiratory health demonstrates particular sensitivity to air pollution. Existing evidence investigating the association between short-term ozone (O₃) exposure and childhood pneumonia remains insufficient and inconsistent, especially in low- and middle-income countries (LMICs). METHOD: To provide more reliable and persuasive evidence, we implemented a multi-city, time-stratified case-crossover design with a large sample size, using data from seven representative children's hospitals across major geographical regions in China. To avoid the impact of the COVID-19 pandemic, individual-level medical records of inpatient children under 6 years of age diagnosed with pneumonia during 2016-2019 were collected. Conditional logistic regression models were fitted for each city, and city-specific estimates were pooled through a meta-analysis using a random-effects model. RESULTS: In total, the study included 137,470 pediatric pneumonia hospital admissions. The highest pooled estimate for O₃ occurred at lag0-1, with a 10 µg/m³ increase in O₃ associated with a 1.57% (95% CI: 0.67%-2.48%) higher risk of pediatric pneumonia hospital admissions. Stratified analyses indicated that the effects of O₃ were robust across different sexes, age groups, and admission seasons. We also observed a statistically significant increase in risk associated with O₃ concentrations exceeding the World Health Organization Air Quality Guidelines (WHO-AQGs). CONCLUSIONS This study revealed a significant positive association between O₃ and pediatric pneumonia hospital admissions. Our findings substantially strengthen the evidence base for the adverse health impacts of O₃, underscoring the importance of O₃ pollution control and management in reducing the public health burden of pediatric pneumonia.
Humans ; Ozone/analysis* ; China/epidemiology* ; Pneumonia/chemically induced* ; Child, Preschool ; Male ; Female ; Infant ; Cross-Over Studies ; Air Pollutants/analysis* ; Hospitalization/statistics & numerical data* ; Child ; Cities/epidemiology* ; Air Pollution/adverse effects* ; Infant, Newborn ; Environmental Exposure/adverse effects*

BACKGROUND: This cross-sectional study examined meal patterns based on daily energy intake distribution and their associations with nutrient and food intake, diet quality, and body mass index (BMI). METHODS: Body height, weight, habitual dietary intake and the Healthy Eating Index (HEI)-2020 score by eating occasion were assessed using the validated Meal-based Diet History Questionnaire among employees (465 males and 193 females aged 20-75 years) in the Tokyo Metropolitan Area. Meal patterns were extracted based on % energy intake from breakfast, lunch, dinner, and snacks using K-means clustering by sex. Dietary intake, HEI-2020 score, and BMI were then compared between sex-specific meal patterns. RESULTS: The identified patterns were "large lunch and dinner" (n = 299), "three meals-balanced" (n = 97), and "large dinner" (n = 69) patterns in males and "large dinner" (n = 79); "large afternoon snack" (n = 54) and "large lunch" (n = 60) patterns in females. The HEI-2020 scores were the highest for dinner, followed by breakfast, lunch, and snacks in any meal pattern. Males with the "large dinner" pattern had lower intakes of rice, bread, carbohydrates, dietary fibre, and thiamine; higher intake of alcoholic beverages; and higher HEI-2020 scores than those with other patterns. Females with a "large dinner" pattern had a lower intake of bread, confectionery, total and saturated fats, and carbohydrates; higher intake of fish, meat, and alcoholic beverages; higher HEI-2020 scores; and lower BMI. Thus, a meal pattern with higher energy intake distribution at dinner was associated with higher diet quality among males and females and lower BMI among females in Japanese workers. CONCLUSIONS These findings suggest that improving the quality of the meal with the highest energy contribution could help enhance overall dietary quality and metabolism.
Humans ; Female ; Male ; Middle Aged ; Adult ; Energy Intake ; Body Mass Index ; Cross-Sectional Studies ; Aged ; Meals ; Young Adult ; Tokyo ; Feeding Behavior ; Diet/statistics & numerical data*

BACKGROUND: The protective effectiveness of an N95 respirator depends on the filtration efficiency of the material from which the N95 respirator is made of, as well as the wearers' facial fit. The facial fit of an N95 respirator mainly depends on the degree of matching between the wearers' facial dimension characteristics and the N95 respirator. Quantitative fit testing objectively evaluates the fit of N95 respirators; however, it is not easy to promote because of the limitations of testing conditions. The aim of this study is to establish a fit prediction model of N95 respirator based on facial images. METHODS: Facial images and fit factor (FF) value of 5 N95 respirators were gathered from 299 medical staffs in 10 hospitals in Beijing. Face geometry measurement was based on 3D face modelling, and the American TSI-8038 Porta Count Pro+ was used to conduct quantitative fit test. Multiple linear regression analysis was employed to identify facial dimensional features that significantly influenced the fit of N95 respirators. Through matching training of facial image and FF values, a fit prediction model has been established, enabling rapid recommendation of N95 respirators meeting the fit standard via facial image recognition. RESULTS: A fit prediction model for N95 respirators based on facial images has been developed, which enables the rapid recommendation of N95 respirators with acceptable FF value for healthcare personnel. The model demonstrated an accuracy of 55.93%, a precision of 98.43%, a recall of 51.65%, and an F1 score of 0.68. CONCLUSIONS It is feasible to utilize computer-based facial recognition technology to rapidly recommend N95 respirators for medical personnel. Given the high level of accuracy achieved, the model demonstrates significant potential for practical application.
Humans ; Face/anatomy & histology* ; N95 Respirators/standards* ; Male ; Adult ; Female ; Middle Aged ; Beijing

OBJECTIVE: To assess health equity in the Yangtze River region to improve understanding of the correlation between hand, foot, and mouth disease (HFMD) and socioeconomic factors. METHODS: From 2014-2016, data on HFMD incidence, population statistics, economic indicators, and meteorology from 26 cities along the Yangtze River were analyzed. A multi-city random-effects meta-analysis was performed to study the relationship between temperature and HFMD transmission, and health equity was assessed with respect to socio-economic impact. RESULTS: Over the study period, 919,458 HFMD cases were reported, with Shanghai (162,303) having the highest incidence and Tongling (5,513) having the lowest. Males were more commonly affected (male-to-female ratio, 1.49:1). The exposure-response relationship had an M-shaped curve, with two HFMD peaks occurring at 4 °C and 26 °C. The relative risk had two peaks at 1.30 °C (1.834, 95% CI: 1.204-2.794) and 31.4 °C (1.143, 95% CI: 0.901-1.451), forming an M shape, with the first peak higher than the second. The most significant impact of temperature on HFMD was observed between -2 °C and 18.1 °C. The concentration index (0.2463) indicated moderate concentration differences, whereas the Theil index (0.0418) showed low inequality in distribution. CONCLUSION The incidence of HFMD varied across cities, particularly with changes in temperature. Economically prosperous areas showed higher risks, indicating disparities. Targeted interventions in these areas are crucial for mitigating the risk of HFMD.
Female ; Humans ; Male ; China/epidemiology* ; Cities/epidemiology* ; Hand, Foot and Mouth Disease/transmission* ; Incidence ; Risk Factors ; Temperature

OBJECTIVE: Recombination events are common and serve as the primary driving force of diverse human adenovirus (HAdV), particularly in children with acute respiratory tract infections (ARIs). Therefore, continual monitoring of these events is essential for effective viral surveillance and control. METHODS: Respiratory specimens were collected from children with ARIs between January 2022 and December 2023. The penton base, hexon, and fiber genes were amplified from HAdV-positive specimens and sequenced to determine the virus type. In cases with inconsistent typing results, genes were cloned into the pGEM-T vector to detect recombination events. Metagenomic next-generation sequencing (mNGS) was performed to characterize the recombinant HAdV genomes. RESULTS: Among 6,771 specimens, 277 (4.09%, 277/6,771) were positvie for HAdV, of which 157 (56.68%, 157/277) were successfully typed, with HAdV-B3 being the dominant type (91.08%, 143/157), and 14 (5.05%, 14/277) exhibited inconsistent typing results, six of which belonged to species B. The penton base genes of these six specimens were classified as HAdV-B7, whereas their hexon and fiber genes were classified as HAdV-B3, resulting in a recombinant genotype designated P7H3F3, which closely resembled HAdV-B114. Additionally, a partial gene encoding L1 52/55 kD was identified, which originated from HAdV-B16. CONCLUSION A novel recombinant, P7H3F3, was identified, containing sequences derived from HAdV-B3 and HAdV-B7, which is similar to HAdV-B114, along with additional sequences from HAdV-B16.
Humans ; Adenoviruses, Human/isolation & purification* ; Respiratory Tract Infections/epidemiology* ; Child, Preschool ; Child ; Recombination, Genetic ; Male ; Beijing/epidemiology* ; Infant ; Female ; Phylogeny ; Adenovirus Infections, Human/epidemiology* ; Acute Disease ; Genome, Viral

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

OBJECTIVE: To assess relationships between cold spells and genitourinary hospitalization risk. METHODS: Hospitalization records for genitourinary system diseases (GUDs) from 16 districts in Beijing (2013-2018) were analyzed. Cold spells were defined based on varying intensity thresholds. A two-stage analytical method was employed: first, generalized linear models assessed district-specific associations between cold spells and hospitalizations; second, random-effects meta-analysis aggregated the district-level results. Subgroup analyses were performed by admission type (emergency vs. outpatient), age, and sex. RESULTS: A total of 271,579 GUD-related hospitalizations were recorded. Cold spells (p1day2，daily mean temperature below the 1 ^st percentiles of the daily mean temperature distribution from January 1, 2013, to December 31, 2018, lasting for two or more consecutive days) were linked to a significant rise in hospitalization risks: 1.43 (95% CI: 1.32-1.56) for all GUDs, 1.35 (95% CI: 1.23-1.49) for urinary system diseases, and 1.46 (95% CI: 1.28-1.67) for renal failure, when compared to non-cold spell days. Emergency admissions showed higher risk increases than outpatient admissions. CONCLUSION Extreme cold spells significantly elevate hospitalization risks for GUDs. This highlights the urgent need for targeted public health interventions to mitigate cold-related health impacts, especially for vulnerable populations.
Humans ; Hospitalization/statistics & numerical data* ; Male ; Female ; Cold Temperature/adverse effects* ; Infant ; Child, Preschool ; Middle Aged ; Adult ; Child ; Aged ; Adolescent ; Young Adult ; Beijing/epidemiology* ; Female Urogenital Diseases/etiology* ; Male Urogenital Diseases/etiology* ; Infant, Newborn ; Risk Factors

OBJECTIVE: To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases, and to develop deep learning-based models for daily hospital admission prediction. METHODS: A multi-city study was conducted in Tokyo's 23 wards, Osaka City, and Nagoya City. Random forest models were employed to assess the synergistic short-term lag effects (lag0, lag3, and lag7) of climate and air pollutants on hospitalization for five cardiovascular diseases (CVDs) and two respiratory diseases (RDs). Furthermore, we developed hybrid deep learning models that integrated an autoencoder (AE) with a Long Short-Term Memory network (AE+LSTM) to predict daily hospital admissions. RESULTS: On the day of exposure (lag0), air pollutants, particularly nitrogen oxides (NO x), exhibited the strongest influence on hospital admissions for CVD and RD, with pronounced effects observed for hypertension (I10-I15), ischemic heart disease (I20), arterial and capillary diseases (I70-I79), and lower respiratory infections (J20-J22 and J40-J47). At longer lags (lag3 and lag7), temperature and precipitation were more influential predictors. The AE+LSTM model outperformed the standard LSTM, improving the prediction accuracy by 32.4% for RD in Osaka and 20.94% for CVD in Nagoya. CONCLUSION Our findings reveal the dynamic, time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions. This framework can inform early warning systems, enhance healthcare resource allocation, and support climate-adaptive public health strategies.
Humans ; Hospitalization/statistics & numerical data* ; Cardiovascular Diseases/epidemiology* ; Japan/epidemiology* ; Air Pollutants/analysis* ; Air Pollution/adverse effects* ; Cities/epidemiology* ; Climate ; Respiratory Tract Diseases/epidemiology* ; Deep Learning ; Male