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China's diets are undergoing a profound transformation, and carbon storage loss generated by dietary structure change is increasingly serious, accompanied by concerns about sustainable diets and food supply–demand conflicts. This paper designed a dual 'material–environmental' framework based on the dietary structure classification, around which we conducted the heterogeneity analysis of food supply–demand patterns and land carbon loss, and then tracked hotspot diets of trade-generated carbon loss through the multi-regional input–output (MRIO) model. The research found that 31 provinces could be classified into five clusters with obvious spatial agglomeration patterns, most of which still had a high proportion of staches, but also showed an evolutionary trend towards diversified compositions. Driven by dietary structure, the national food supply–demand match under the material accessibility dimension showed barely balanced overall, while in terms of environmental effects, ecosystems lost significant amounts of carbon stocks, with losses of 331 and 950 Tg 1 1 Tg refers to teragram, a weight unit, 1 Tg = 106 t = 1012 g of vegetation carbon and soil organic carbon, respectively, which together accounted for 14 percent of the total carbon stocks in the vegetation and topsoil carbon pools. The clusters to which Henan, Jiangsu, Zhejiang and Guangdong belong were tracked as hot dietary clusters exhibiting hotspots in inter-regional trade, contributing to carbon loss in external provinces through trade linkages. Heilongjiang and Inner Mongolia were at a low level of supply–demand balance but played the role of a carbon storage loser, while Guangdong, Zhejiang, and Jiangsu not only possessed higher balance levels but also pulled more external carbon loss. China's food system should optimise internal cropping structures and monitor external land use conversion. It is equally important to track food consumption side rights and responsibilities. • The "Material-Environmental" framework to diagnose dietary sustainability was designed. • Provinces could be classified into five clusters with obvious spatial agglomeration patterns. • Land use changes driven by dietary transition have resulted in significant carbon losses of 1281 Tg. • Specific clusters were hotspot clusters that pulled carbon loss from external regions during inter-regional trade. • Diet sustainability enhancement based on land use environmental effects deserves attention. [ABSTRACT FROM AUTHOR]

China implemented the Targeted Poverty Alleviation (TPA) policy in 2015 to fight against poverty. In order to assess the health performance of the TPA policy, this study aims to evaluate the impact of the TPA policy on healthcare utilization among older adults who normally have higher vulnerability to poverty and diseases. Drawing on data from four waves of the China Health and Retirement Longitudinal Study (CHARLS), we investigated the impact of the TPA policy on older individuals' outpatient and inpatient utilization using the difference-in-differences (DID) approach. In total, 5285 older respondents were incorporated into a final sample. The results indicated that the implementation of the TPA policy had a significantly positive impact on increasing inpatient care utilization for poor older adults. However, its impact on outpatient service utilization was not significant. To ensure that the increased level of inpatient care utilization was not caused by deteriorating health status, we further analyzed the impact of the TPA policy on poor older adults' health outcomes. Results indicated that the TPA policy improved self-rated health and reduced the number of ADL limitations among older adults in registered poor households. The positive impact of the TPA policy on inpatient care utilization was found to be most beneficial for older adults in poor households who were female, coupled, and aged 70 years and above. The TPA policy in China improved healthcare access for economically disadvantaged older adults and contributed to the enhancement of their health outcomes. This evidence may have broad implications for other low- and middle-income countries aiming to reduce poverty and achieve health equity. • This study assessed the TPA policy's impact on healthcare utilization, focusing on older adults for the first time. • The TPA policy increased inpatient care utilization for older adults in poor households. • The TPA policy improved health outcomes for poor older adults. • Policy effect on inpatient care utilization is stronger for femle, coupled, or senior older adults. [ABSTRACT FROM AUTHOR]

Little is known about the association of ambient ozone with ovarian reserve. Based on a retrospective cohort study of 6008 women who attended a fertility center in Hubei, China, during 2018–2021, we estimated ozone exposure levels by calculating averages during the development of follicles (2-month [W1], 4-month [W2], 6-month [W3]) and 1-year before measurement (W4) according to Tracking Air Pollution in China database. We used multivariate logistic regression and linear regression models to investigate association of ozone exposure with anti-müllerian hormone (AMH), the preferred indicator of ovarian reserve. Each 10 μg/m3 increases in ozone were associated with 2.34% (0.68%, 3.97%), 2.08% (0.10%, 4.01%), 4.20% (1.67%, 6.67%), and 8.91% (5.79%, 11.93%) decreased AMH levels during W1-W4; AMH levels decreased by 15.85%, 11.90%, 16.92% in the fourth quartile during W1, W3, and W4 when comparing the extreme quartile, with significant exposure-response relationships during W4 (P < 0.05). Ozone exposure during W1 was positively associated with low AMH. Additionally, we detected significant effect modification by age, body mass index, and temperature in ozone-associated decreased AMH levels. Our findings highlight the potential adverse impact of ozone pollution on female ovarian reserve, especially during the secondary to small antral follicle stage and 1-year before measurement. [Display omitted] • Ambient ozone exposure was associated with diminished ovarian reserve. • Secondary to small antral follicle stage might be the susceptible exposure window. • Even below the current AQS, AMH levels decreased with increasing ozone exposure. • Age, BMI, and ambient temperature might modify the observed associations. [ABSTRACT FROM AUTHOR]

• A new Regional Geo-Statistics (RGS) Method is proposed to better extract remote sensing features for yield estimation. • Adding the surface reflectance bands to the vegetation index as features can improve the accuracy of yield estimation. • The multi-source data can realize the best yield estimation results. • LightGBM is capable of yield prediction on remote sensing data. • Quantitative analysis of the contribution of multi-source data. Timely and accurate estimation of maize yield is crucial for ensuring food security. This study integrated multi-source data (satellite, meteorological, and soil data) on Google Earth Engine (GEE) and used machine learning techniques to estimate summer maize yield across 469 counties in the Huang-Huai-Hai Plain of China from 2010 to 2020. A novel method for extracting features from remote sensing images was proposed called the Regional Geo-Statistics (RGS) Method. We compared its performance with the traditional county-level averages method and explained the impact and contributions of incorporating multi-source data on yield estimation models. Firstly, Enhanced Vegetation Index (EVI) and Near-Infrared Vegetation Reflectance (NIRv) were transformed into regional geostatistical vectors and county-level averages using GEE. Then, yield was estimated using LightGBM, RF and LASSO. The results highlighted the superiority of the RGS method, with LightGBM yielding the best model (R2 = 0.55, RMSE = 852.92 kg/ha, NRMSE = 13.66 %). Further improvements were achieved by gradually adding meteorological and soil variables, with R2 improvements of 0.03 and 0.20, respectively. The Comprehensive Factor Model (CFM), utilizing all data as features, achieved the best results (R2 = 0.76, RMSE = 629.33 kg/ha, NRMSE = 10.08 %). The interpretability analysis based on CFM model underscored the significance of soil-related variables, which contributed significantly (45.38 %) alongside remote sensing variables, emphasizing the crucial role of soil variables in maize yield estimation. This study presents a versatile and reliable method for integrating multi-source data for maize yield estimation, supporting agricultural management and food security. [ABSTRACT FROM AUTHOR]

• N-deficient citrus leaves and roots kept high abilities to detoxify ROS and MG. • N-deficiency (ND) affected ROS and MG metabolism more in roots than in leaves. • ND enhanced n distribution in roots and R/S, and delayed root senescence. • ND reduced MDA levels and electrolyte leakage in citrus leaves and roots. Nitrogen-deficiency (ND) usually occurs in some citrus orchard soils in China. The roles of reactive oxygen species (ROS) and methylglyoxal (MG) generation and their detoxification systems in ND tolerance of horticultural woody plants still need to be revealed. For the first time, we examined the effects of ND on ROS and MG generation and their detoxification systems in leaves and roots of Citrus sinensis seedlings. The objectives are to test the hypotheses that N-deficient leaves and roots can keep high abilities to scavenge ROS and MG, thereby protecting them from oxidative damage, and that ND-induced alterations of ROS and MG formation and their detoxification systems in leaves and roots are different. ND augmented superoxide anion production rate and MG concentrations, but it decreased malondialdehyde (MDA) concentrations and electrolyte leakage in leaves and roots. ND increased the activities of most enzymes involved in ROS (ascorbate-glutathione cycle-related enzymes, antioxidant enzymes, and sulfur metabolism-related enzymes) and MG (glyoxalases) detoxification expressed on a protein basis with a few exceptions, and the concentrations of ascorbate, phytochelatins, and total non-protein thiols in leaves and roots. These results suggested that nitrogen-deficient leaves and roots could keep high abilities to detoxify ROS and MG, and protect them from oxidative damage. Generally viewed, ND affected the production and removal of ROS and MG more in roots than in leaves. [ABSTRACT FROM AUTHOR]