Search

A decrease in population is an emerging challenge in China's urbanization trajectory. This study utilizes data from the Sixth and Seventh Population Censuses to identify Chinese cities experiencing population decline, focusing on prefecture-level cities. It employs 30 indicators relevant to nine Sustainable Development Goals (SDGs) concerning urban areas and populations to evaluate the progress of these shrinking cities in 2010 and 2020. A novel metric, "SDG population elasticity", is introduced to quantify the association between population reduction and SDG indexes. The study employs K-means++ clustering for 130 shrinking cities. The findings reveal that out of the 130 cities, 63 exhibit a downward trend in SDG index scores, predominantly in China's northeast and western regions. The Northeast region has negative SDG population elasticity, indicating a lag in sustainable development compared to that in other areas. Additionally, the research categorizes China's shrinking cities into four groups: cities with strong population elasticity feedback-significantly declining SDGs, cities with weak population elasticity feedback-slightly regressing SDGs, cities with high population loss-negative SDGs in decline, and cities with smart population decline-steady SDGs growth. These findings offer a foundation for crafting bespoke policies in shrinking cities to ensure a balanced approach to sustainable development and monitor advancement toward achieving the SDGs. [ABSTRACT FROM AUTHOR]

• Machine learning algorithms, particularly the stacked ensemble model, proved to be a valuable tool in predicting the risk of functional dependency among middle-aged and elderly Chinese adults. • A compact model was developed using a smaller set of predictors. It maintained both discrimination and accuracy, making it practical for routine clinical practice. • For ADL dependency, arthritis, age, self-report health, and waist circumference were identified as highly significant predictors. Conversely, cognitive function, age, living in rural areas, and performance in chair stand test emerged as highly ranked predictors for IADL dependency. To develop prediction models for assessing functional dependency in a middle-aged and older Chinese population. Adults ≥45 years old from the China Health and Retirement Longitudinal Study (CHARLS) and without functional dependency at baseline were included. Functional dependency was defined as needing any help in any basic activities of daily living (ADL) or instrumental activities of daily living (IADL). The outcomes were overall functional dependency, ADL and IADL dependency. Stacked ensemble models were constructed based on five selected machine learning models. Models were trained and tested in the 2011–2015 cohort, and were externally validated in the 2015–2018 cohort. SHapley Additive exPlanations (SHAP) was utilized to quantify the significance of predictors. In the training cohort, a total of 6,297 participants were included at baseline, 1,893 developed functional dependency during the follow-up period. The stacked ensemble model achieved the best performance in terms of discrimination ability for predicting overall functional dependency, ADL and IADL dependency, with AUCs of 0.750, 0.690 and 0.748, respectively; in external validation cohort, the corresponding AUCs were 0.725, 0.719 and 0.727, respectively. A compact model was further developed and maintained similar predictive performance. The stacked ensemble approach can serve as a useful tool for identifying the risk of functional dependency in a large Chinese population. For ADL dependency, arthritis, age, self-report health, and waist circumference were identified as highly significant predictors. Conversely, cognitive function, age, living in rural areas, and performance in chair stand test emerged as highly ranked predictors for IADL dependency. [ABSTRACT FROM AUTHOR]

Triclosan (TCS) is widely applied in personal care products (PCPs) as an antimicrobial preservative. Due to its toxicity and potential risk to human health, TCS has attracted mounting concerns in recent years. However, biomonitoring of TCS in large human populations remains limited in China. In this study, 1163 adults in South China were recruited and urinary TCS concentrations were determined. TCS was detected in 99.5% of urine samples, indicating broad exposure in the study population. Urinary concentrations of TCS ranged from below the limit of detection (LOD) to 270 μg/L, with a median value of 3.67 μg/L. Urinary TCS concentrations from individuals were all lower than the Biomonitoring Equivalents reference dose, suggesting relatively low health risk in the participants. TCS concentrations did not differ significantly between sexes or education levels (p > 0.05). Nevertheless, marital status and age were found to be positively influence TCS levels (p < 0.001). After adjustment for body mass index (BMI), age was determined to be positively associated with TCS concentrations (p < 0.05), particularly in the age group from 31 to 51 years old. This study provides a baseline of urinary TCS exposure in South China general adult populations. [Display omitted] • Adults from South China were widely exposed to triclosan. • Marital status and age were found to positively influence urinary triclosan levels. • After adjustment for BMI, age was determined to be positively associated with triclosan concentrations. • Estimates of human intake indicated that the health risk of exposure to triclosan for adults in South China was very low. [ABSTRACT FROM AUTHOR]

The study of intercity network structure from the perspective of flow space can effectively reveal the connection patterns, hierarchical laws, and spatial organization of cities. However, current studies mostly focus on a single real or virtual space, neglecting the comprehensive perspective. Furthermore, the research subject of network relationships is usually the complex original aligned network rather than the spatially cohesive network structure. In this study, spatial network structures are constructed and extracted based on the migration flow and attention flow, which represent people's objective behavior and subjective will, respectively. This study then reveals the association between virtual and real networks from three aspects: node location, node attributes, and local network structure characteristics. Results indicate that compared with the real network structure, the virtual network structure has a strong same-level node agglomeration and a significant node size difference. Spatial dislocations are observed in the high association of the various measures of China's real and virtual network structures. The degree of differences in network structures between virtual and real spaces varies spatially. This paper reveals the dynamics of urban development in different spaces, helping build a human-centered, high-quality space governance system for virtual and real spaces. • Spatial network structure considering the geographical proximity and interaction strength among cities is extracted. • Location, attribution, and structure-based association analysis method for non-aligned intercity networks is proposed. • The degree of differences in network structures between virtual and real spaces varies spatially. • The association pattern between real and virtual networks is spatially dislocated in different indicators. [ABSTRACT FROM AUTHOR]

Molecular analyses help to better understand the overall picture of characteristics, meteorological effects, sources, and secondary transformations of organic aerosols (OA). A two-year observation campaign was conducted in polluted central China during 2019–2021, and 130 compounds of molecular OA (quantified organic compounds, QOCs) were quantified. The average concentration of QOCs was 1971 ng/m3, showing the highest normalized QOCs in PM 2.5 (31 ng/μg) compared to others. Among the QOCs, the polar category contributed 84%, with the dominated abundant fatty acids observed. The enhanced acid ratios of malonic/succinic and octadecanoic/oleic in summer indicated higher aerosol age, significantly promoted by temperature. Three benzenetricarboxylic acids, mostly from secondary formation, also exhibited quite high concentrations in summer. The noticeable presence of carcinogenic polycyclic aromatic hydrocarbons (PAHs) (45% of ∑28PAHs) highlighted severe health risks associated with human exposure, particularly in winter (56 ng/m3, approximately 7 times that in summer). According to the random forest model assessments, meteorological conditions in summer were most conducive to eliminating pollutants, while that in winter contributed 19% of QOC concentration. The Positive Matrix Factorization analysis revealed that anthropogenic secondary organic aerosols (ASOA) and biogenic SOA (BSOA) jointly accounted for 32% of QOCs, followed by biomass burning (20%), coal combustion (17%), vehicle emissions (16%), and cooking (15%). ASOA was positively correlated with O 3 (r = 0.58) and aerosol acidity facilitated ASOA production at 40% < relative humidity <80%. On polluted days, BSOA increased as NO 2 and PM 2.5 increased, contributing to worsened aerosol pollution. In spring and summer, gas-phase oxidation contributed more saturated dicarboxylic acids (52 and 55%), while aqueous-phase conversion predominated in autumn and winter (59 and 66%). This study provides new information on particulate molecular organic compounds as well as the secondary transformation, which is of great significance for formulating the prevention and control measures of aerosol pollution. [Display omitted] • A total of 130 compounds were measured, covering 8 types of polar and 5 types of non-polar molecules. • Winter meteorological conditions were estimated to contribute 19% to organic components. • Anthropogenic SOA was significantly promoted by aerosol acidity (40% < RH < 80%) and O 3. • Aqueous-phase oxidation predominated in the formation of saturated dicarboxylic acids (55%). [ABSTRACT FROM AUTHOR]

Neonicotinoid insecticides can selectively interact with the unique nicotinic acetylcholine receptor subtypes in insects and are considered to be low toxic to mammals. However, there is still insufficient knowledge on human exposure to neonicotinoid insecticides, especially for children. This study aimed to investigate urinary concentrations and profiles of neonicotinoid insecticides in South China children and to analyze potential influencing factors. Six neonicotinoid insecticides, including imidacloprid (IMI), thiamethoxam (THM), acetamiprid (ACE), clothianidin (CLO), thiacloprid (THD) and dinotefuran (DIN), exhibited high detection frequencies (>90%) in urine samples collected from 305 children, suggesting broad exposure in South China children. The median concentrations were determined to be 0.13, 0.21, 0.01, 0.19, 0.002 and 1.64 μg/L, respectively. Among the target neonicotinoids, urinary concentrations of CLO and THM exhibited a significant and positive correlation between each other (p < 0.05), suggesting similar sources of these two chemicals. [Display omitted] • Neonicotinoid insecticides were frequently detected in urine samples from South China children. • DIN was the most abundant neonicotinoid insecticide in urine samples. • Urinary CLO positively correlated with THM, indicating similar exposure sources. [ABSTRACT FROM AUTHOR]