Search Results (346)

Women’s decision-making autonomy is widely recognized as a critical determinant of maternal, newborn, and child health (MNCH). However, prevailing measures often conflate genuine autonomy with decisions made within traditional gender roles, risking an overstatement of women’s empowerment. This study examines the extent to which reported female decision-making autonomy reflects authentic agency versus role-based compliance in a patriarchal context. A cross-sectional study was conducted among 280 male household heads in Kakamega County, Kenya, whose partners were pregnant or recently postpartum. Using multi-stage cluster sampling and structured interviews, men reported on household and MNCH decision-making and their rationales, categorized as gender-role conformity, belief in gender equality, or other reasons. Although 40.4% reported that their partners made decisions independently, only 11.4% attributed it to a belief in women’s equality; 28% framed it within traditional gender roles. Men were over four times more likely to perceive women’s decisions as role-based than autonomous (AOR = 4.40; 95% CI: 2.48–5.78). Younger men (18–34) were more likely to report female decision-making (AOR = 5.54; 95% CI: 5.08–7.27), without necessarily endorsing egalitarian norms. Findings highlight the urgent need for gender-transformative MNCH interventions that move beyond surface-level autonomy to address deeper structural inequities. Full article

Introduction: Traumatic brain injury (TBI) is a leading cause of morbidity worldwide, with the Glasgow Coma Scale (GCS) serving as a tool to measure injury severity. This study aimed to investigate the relationship between GCS admission scores and various socio-demographic, clinical, injury-related, and hospital-related variables in patients with TBI across two tertiary care centers in Eastern Europe, a region that remains underrepresented in the literature. Methods: A retrospective observational study was conducted using data from 119 TBI patients admitted between March 2020 and June 2023 at Cluj County Emergency Hospital (Romania) and Saint Vincent Hospital (Poland). GCS scores were analyzed as both categorical and continuous variables. Statistical analyses included Wilcoxon and Kruskal–Wallis tests for group comparisons and Spearman correlations for continuous variables. Results: Most patients included suffered a mild TBI (GCS score between 13 and 15). There were significant associations between GCS scores and post-traumatic amnesia (p < 0.05), discharge status (p < 0.01), discharge destination (p < 0.01), and education level (p < 0.01). GCS scores at admission were linked to survival, absence of post-traumatic amnesia, higher education levels, and home discharge. No significant differences observed across sex, residence, employment status, injury type, cause, or mechanism of injury. A weak but significant negative correlation was observed between GCS and length of hospital stay (rho = −0.229, p > 0.05), while age showed a non-significant correlation. Conclusions: The GCS score at admission is significantly associated with various clinical and socio-demographic outcomes in TBI patients, supporting the utility of the GCS score as a prognostic tool. The predominance of mild cases and the absence of radiological data, such as cerebral contusions or epidural or subdural hematomas, limit the generalizability of the findings. Further studies with larger samples and comprehensive imaging data are necessary to validate these findings. Full article

Groundwater contamination by nitrates (NO₃⁻) and nitrites (NO₂⁻) is an urgent problem in rural areas of Eastern Europe, with profound public health and sustainability implications. This paper presents an integrated assessment of groundwater vulnerability and water quality in rural wells in the Ceanu Mare commune, Cluj County, Romania—a representative area of the Northern Transylvania Basin, characterized by diverse geological structures, intensive agricultural activities, and incomplete public water infrastructure. This study combines detailed hydrochemical analyses, household-level studies, and geological context to identify and quantify key factors influencing nitrate and microbial contamination in rural wells, providing a comprehensive perspective on water quality challenges in the central part of Romania. This study adopts a multidisciplinary approach, integrating detailed geotechnical investigations conducted through four strategically located boreholes. These are complemented by extensive hydrogeological and lithological characterization, as well as rigorous chemical and microbiological analyses of nearby wells. The results reveal persistently elevated concentrations of NO₃⁻ and NO₂⁻, commonly associated with inadequate livestock waste management and the proximity of manure storage areas. Microbiological contamination was also frequent. In this study, the NO₃⁻ levels in well water ranged from 39.7 to 48 mg/L, reaching up to 96% of the EU/WHO threshold (50 mg/L), while the NO₂⁻ concentrations varied from 0.50 to 0.69 mg/L, exceeding the legal limit (0.5 mg/L) in 87% of the sampled wells. Ammonium (NH₄⁺) was detected (0.25–0.34 mg/L) in all the wells, below the maximum allowed limit (0.5 mg/L) but indicative of ongoing organic pollution. All the well water samples were non-compliant for microbiological parameters, with E. coli detected in 100% of cases (5–13 CFU/100 mL). The regional clay–marl substrate offers only limited natural protection against pollutant infiltration, primarily due to lithological heterogeneity and discontinuities observed within the clay–marl layers in the study area. This research delivers a replicable model for rural groundwater assessment and addresses a critical gap in regional and European water safety studies. It also provides actionable recommendations for sustainable groundwater management, infrastructure development, and community risk reduction in line with EU water directives. Full article

Upgrading the industrial structure is an essential step for economic growth and the transformation of old and new development drivers. Counties situated at the rural–urban interface hold a comparative advantage in industrial upgrading compared to cities, converting agricultural resource dividends into economic value. However, whether agricultural innovation talent can facilitate this process requires further investigation. Based on a sample of 1771 Chinese counties, this study employs a quasi-natural experiment using China’s “World-Class Disciplines” construction program in agriculture and establishes a difference-in-differences (DID) model to examine the impact of agricultural innovation talent on county-level industrial structure upgrading. The results show that agricultural innovation talent significantly promotes industrial upgrading, with this effect being more pronounced in counties with smaller urban–rural income gaps, greater household savings, and higher levels of industrial sophistication. Spatial spillover effects are also evident, indicating regional knowledge diffusion. Knowledge empowerment emerges as the core mechanism: agricultural innovation talent drives industrial convergence, responds to supply–demand dynamics, and integrates digital and intelligent elements through knowledge creation, dissemination, and application, thereby supporting county-level industrial upgrading. The findings highlight the necessity of establishing world-class agricultural research and talent incubation platforms, particularly emphasizing the supportive role of universities and the knowledge-driven contributions of agricultural innovation talents to county development. Full article

National-scale forest inventories such as the Forest Inventory and Analysis (FIA) program in the United States are designed to provide data and estimates that meet target precision at the national and state levels. However, such design-based direct estimates are often not accurate at a smaller geographic scale due to the small sample size. Small area estimation (SAE) techniques provide precise estimates at small domains by borrowing strength from remotely sensed auxiliary information. This study combined the FIA direct estimates with gridded mean canopy heights derived from recently published Global Ecosystem Dynamics Investigation (GEDI) Level 3 data and Landsat data to improve county-level estimates of total and merchantable volume, aboveground biomass, and basal area in the states of Alabama and Mississippi, USA. Compared with the FIA direct estimates, the area-level SAE models reduced root mean square error for all variables of interest. The multi-state SAE models had a mean relative standard error of 0.67. In contrast, single-state models had relative standard errors of 0.54 and 0.59 for Alabama and Mississippi, respectively. Despite GEDI’s limited footprints, this study reveals its potential to reduce direct estimate errors at the sub-state level when combined with Landsat bands through the small area estimation technique. Full article

Soil organic carbon (OC) storage in crop rotation systems benefits soil productivity and global climate change. However, the regulatory mechanisms and pathways by which soil OC storage is affected under medium-term crop rotation at the aggregate level are not fully understood. Herein, fifteen soil samples from five cropping systems (abandoned farmland, continuous cropping of tobacco, tobacco–pea rotation, continuous cropping of dasheen, and dasheen–ryegrass rotation for over 10 years) were collected from soil at 0 to 20 cm depths in Miyi County, Sichuan Province, China. The soil aggregates and aggregate-associated OC, enzyme activities, and microbial biomass were evaluated. The effects of medium-term crop rotation on soil aggregate-associated OC content and biochemical properties varied between crop types. Specifically, tobacco–pea rotation significantly decreased the proportion of macro-aggregates (0.25–2 mm); the contents of OC, Ca-OC, aliphatic C, alcohols, and phenols; enzyme activities; and fungal biomass in the aggregate fractions, compared with those associated with the continuous cropping of tobacco. In contrast, dasheen–ryegrass rotation significantly increased the recalcitrant OC content, β-glucosidase and polyphenol oxidase activities, microbial biomass in mega-aggregates (>2 mm) and macro-aggregates, and the recalcitrant OC content and enzyme activity in microaggregates (0.053–0.25 mm) and slit clay (<0.053 mm), relative to those in the continuous cropping of dasheen. Moreover, for the continuous-cropping soils, the OC contents were positively correlated with POD activity but negatively correlated with other enzymes. For the rotational soils, the OC content was positively related to the Fe/Al-OC, aromatic-C, aliphatic-C, and microbial biomass contents but negatively related to the carbohydrate content. The increased OC content was driven by the microbial biomass in the aggregate fractions, and medium-term crop rotation changed the negative effect of microorganisms on the OC content into a positive effect at the aggregate level. Overall, medium-term crop rotation enhances OC storage by improving soil structural stability and microbial community dynamics. Full article

Heavy metal toxicity is an ecological concern in regions affected by processes like mining. This study underscores the potential of honey as a natural bioindicator for monitoring and assessing the levels of environmental contamination in mining-impacted areas. The study evaluated the physico-chemical characteristics, heavy metal content, and antimicrobial activity of honey samples collected from areas adjacent to former mining sites, as well as from protected areas within the same county in Romania. The results revealed significant differences between the two categories of locations. The samples from the protected areas showed higher levels of bioactive compounds (phenols and flavonoids) and exhibited stronger antibacterial activity. The heavy metal analysis indicated significantly higher concentrations of lead, cadmium, and iron in the honey samples from former mining areas compared to those from protected zones, suggesting pronounced industrial-origin contamination. The maximum recorded values were for Pb (0.607 mg/kg), Cd (0.02 mg/kg), Fe (12.131 mg/kg), Cu (0.545 mg/kg), and Zn (6.170 mg/kg). Their antimicrobial activity was tested against several bacterial and fungal strains, including Escherichia coli, Salmonella enteritidis, Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus epidermidis, Bacillus cereus, Listeria monocytogenes, Candida albicans, Aspergillus niger, Aspergillus flavus, Penicillium chrysogenum, Rhizopus stolonifer, Fusarium oxysporum, and Alternaria alternata. The antibacterial and antifungal activity were more pronounced in the honey samples from the protected areas. These findings support the use of honey as a bioindicator of environmental quality and highlight the influence of its geographical origin on its therapeutic and chemical properties. Full article

Agricultural producers play a crucial role in combating agricultural non-point source pollution, so improving their production behaviors and practices will be key to alleviating such pollution. This study employs the Theory of Planned Behavior and focuses on Huaxian County, a major grain-producing county in Anyang City, Henan Province. The study focuses on randomly selected sample farming households in townships within Hua County’s agricultural intensification zone. Through structural equation modeling, it has analyzed the impact of farmers’ individual characteristics, behavioral attitudes, subjective norms, and perceived behavioral control on their willingness to engage in pollution management, as well as the influence of such willingness on actual management behaviors. Research indicates that behavioral attitudes, subjective norms, and perceived behavioral control significantly and positively influence governance intention, and governance intention significantly and positively influences governance behavior. Behavioral attitude is the key latent variable (behavioral attitude > perceived behavioral control > subjective norm). That is, the economic benefits derived from agricultural non-point source pollution governance constitute the most critical factor influencing farmers’ willingness to participate in pollution governance. Furthermore, farmers’ willingness to participate in pollution control bridges the gap between their attitudinal inclination and actual behavioral implementation. Accordingly, this study can provide a theoretical basis and reference for the governance of non-point source pollution in county-level regions of Henan Province and similar major grain-producing areas and offer theoretical support for the sustainable development of agriculture. Full article

Coccidioidomycosis (Valley fever), caused by Coccidioides spp., is a fungal infection endemic to semi-arid regions of the Americas. Despite 80 years of disease recognition in New Mexico, there is limited disease awareness. We incorporated clinical, epidemiological, and ecological datasets to summarize the knowledge of Valley fever in New Mexico. We analyzed 1541 human cases from 2006 to 2023. On average, 86 cases were reported each year (4.1 cases per 100,000 population per year). The highest levels of incidence were in southwestern New Mexico. American Indian or Alaska Natives in New Mexico had a 1.9 times higher incidence rate of coccidioidomycosis than White people, and among age groups, older populations in New Mexico had the highest incidence rates. We analyzed 300 soil samples near Las Cruces, New Mexico, for the presence of Coccidioides and reported the first known positive soil samples collected from the state, the majority of which were from grassland-dominated sites and from animal burrows. Sequence analyses in clinical specimens, wild animals, and soil samples confirmed that Coccidioides posadasii is the main causative species of coccidioidomycosis in New Mexico. Environmental surveillance validated that locally acquired infections could occur in, but are not limited to, Catron, Doña Ana, Sierra, and Socorro Counties. Full article

Child and adolescent health plays a critical role in shaping future public health and intergenerational outcomes. In China, rising rates of myopia, obesity, mental health issues, and other common conditions highlight the need for continuous monitoring. Since 2016, the Chinese National Surveillance on Students’ Common Diseases and Risk Factors (CNSSCDRF) has provided comprehensive, nationwide data on student health. By 2022, the system had expanded to nearly all counties, tracking key indicators such as vision problems, overweight/obesity, dental caries, and health-risk behaviors across multiple administrative levels. This review outlines the surveillance methodology, including sampling, data collection, and analysis. Findings have directly informed school health policies and technical guidelines, supporting national goals such as those in the Healthy China 2030 Plan. Full article

The digitalization of rural areas has emerged as a crucial strategy for promoting economic development, yet the phenomenon of “digital suspension” poses a challenge, where the lack of digital integration in certain sectors may hinder economic progress. This study delves into this issue by identifying multiple configurations that drive county-level economic growth. More specifically, this study aims to explore how rural digitalization contributes to county-level economic growth through different combinations of environmental and subject-level factors. To address this issue, this study applies the fuzzy-set qualitative comparative analysis method, guided by systems thinking and ecological systems theory. The analysis is based on 89 case samples selected from China’s digital village pilot counties, using data from the China County-level Digital Rural Index Research Report jointly released by Peking University and Ali Research Institute, published in 2022, and other county-level statistical data. The study explores the complex causal mechanisms and configuration paths through which rural digitalization empowers county-level economic growth. This study found that (1) the conditions necessary to generate high county-level economic growth do not exist in the process of rural digitalization (at least not within the digital village pilot); (2) four configurations facilitate high county-level economic growth: digital governance-led configuration, dual promotion of digital governance and digital infrastructure, dual promotion of digital life and digital infrastructure, and dual promotion of digital life and digital economy; and (3) two configurations yield non-high county-level economic growth and exhibit asymmetrical relationships with those configurations conducive to high growth. These research findings not only broaden the application of systems thinking and ecological systems theory in the realm of rural digitalization but also offer practical insights into strategies for enhancing county-level economic growth. Full article

Skin aging is a complex process influenced by several factors, including UV exposure, environmental stressors, and lifestyle choices. The demand for effective, natural skincare products has driven research into plant-based oils rich in bioactive compounds. Rosehip oil has garnered attention for its high content of carotenoids, phenolics, and antioxidants, which are known for their anti-aging, photoprotective, and skin-rejuvenating properties. Despite the growing interest in rosehip oil, limited studies have investigated its efficacy on human skin using advanced imaging technologies. This study aims to fill this gap by evaluating the efficacy of cold-pressed Rosa canina seed oil on facial skin characteristics, specifically wrinkles, ultraviolet (UV) spot reduction, and erythema mitigation, using imaging technologies (the VISIA analysis system). Seed oil pressed from R. canina collected from the Băișoara area of Cluj County has been selected for this study due to its high carotenoid, phenolic, and antioxidant contents. The oil has also been analyzed for the content of individual carotenoids (i.e., lutein, lycopene, β Carotene, and zeaxanthin) using HPLC-DAD (High-Performance Liquid Chromatography—Diode Array Detector), along with lutein and zeaxanthin esters and diesters. After the preliminary screening of multiple Rosa species for carotenoid, phenolic, and antioxidant contents, the R. canina sample with the highest therapeutic potential was selected. A cohort of 27 volunteers (aged 30–65) underwent a five-week treatment protocol, wherein three drops of the selected rosehip oil were topically applied to the face daily. The VISIA imaging was conducted before and after the treatment to evaluate changes in skin parameters, including the wrinkle depth, UV-induced spots, porphyrins, and texture. Regarding the bioactivities, rosehip oil showed a significant total carotenoids content (28.398 μg/mL), with the highest levels in the case of the β-carotene (4.49 μg/mL), lutein (4.33 μg/mL), and zexanthin (10.88 μg/mL) contents. Results indicated a significant reduction in mean wrinkle scores across several age groups, with notable improvements in individuals with deeper baseline wrinkles. UV spots also showed visible declines, suggesting ideal photoprotective and anti-pigmentary effects attributable to the oil’s high vitamin A and carotenoid content. Porphyrin levels, often correlated with bacterial activity, decreased in most subjects, hinting at an additional antimicrobial or microbiome-modulatory property. However, skin responses varied, possibly due to individual differences in skin sensitivity, environmental factors, or compliance with sun protection. Overall, the topical application of R. canina oil appeared to improve the facial skin quality, reduce the appearance of age-related markers, and support skin health. These findings reinforce the potential use of rosehip oil in anti-aging skincare formulations. Further long-term, large-scale studies are warranted to refine dosing regimens, investigate mechanisms of action, and explore synergistic effects with other bioactive compounds. Full article

Intersectionality, especially with a race–class–gender focus, has been used to study many facets of women’s experiences. However, this framework has been underutilized in the study of breastfeeding prevalence. Our study is the first of its kind to use intersectionality to illuminate breastfeeding network prevalence disparities with empirical data. We use insights from this theory to examine breastfeeding patterns reported by women living on the Mississippi Gulf Coast. Mississippi makes an excellent site for such an examination, given its history of racial discrimination, entrenched poverty, and strikingly low rates of breastfeeding, particularly for African American women. We identify a series of factors that influence racial disparities in lactation network prevalence, that is, breastfeeding among friends and family of the women we surveyed. Our investigation relies on survey data drawn from a random sample of adult women who are representative of the Mississippi Gulf Coast population supplemented by a non-random oversample of African American women in this predominantly rural tri-county area. Results from the first wave of the CDC-funded 2019 Mississippi REACH Social Climate Survey reveal that Black-White differentials in breastfeeding network prevalence are significantly reduced for African American women who report (1) higher income levels and (2) more robust community support for breastfeeding. We conclude that breastfeeding is subject to two key structural factors: economic standing and community context. An appreciation of these intersecting influences on breastfeeding and long-term efforts to alter them could bring about greater breastfeeding parity among African American and White women in Mississippi and perhaps elsewhere. We end by identifying the practical implications of our findings and promising directions for future research. Full article

The Huang-Huai-Hai Plain is one of China’s primary winter wheat production regions, making accurate yield estimation critical for agricultural decision-making and national food security. In this study, a yield estimation framework was developed by integrating Sentinel-2 and Landsat-8 satellite data with the WOFOST crop growth model and deep learning techniques. Initially, a multi-scenario sample dataset was constructed using historical meteorological and agronomic data through the WOFOST model. Leaf Area Index (LAI) values were then derived from Landsat-8 and Sentinel-2 imagery, and a GRU (Gated Recurrent Unit) neural network was trained on the simulation samples to establish a relationship between LAI and yield. This trained model was applied to the remote sensing-derived LAI to generate initial yield estimates. To enhance accuracy, the results were further corrected using county-level statistical data, producing a spatially explicit winter wheat yield dataset for the Huang-Huai-Hai Plain from 2014 to 2022. Validation against statistical yearbook data at the county level demonstrated a correlation coefficient (r) of 0.659, a root mean square error (RMSE) of 578.34 kg/ha, and a mean relative error (MRE) of 6.63%. These results indicate that the dataset provides reliable regional-scale yield estimates, offering valuable support for agricultural planning and policy development. Full article

This study systematically investigates the mechanistic effects of multifactor interactions (including soil properties, climatic conditions, and cultivation practices) on the productivity parameters (grain yield, stover yield, dry biomass, harvest index) of maize cultivars of different maturity groups in the arid region of Xinjiang, China. Twelve representative maize-growing counties were selected as study sites, where we collected maize samples to measure HI, grain yield, stover yield, and soil physicochemical properties (e.g., organic matter content, total nitrogen, and available phosphorus). Additionally, climate data (effective accumulated temperature) and agronomic parameters (planting density) were integrated to comprehensively analyze the interactive effects of multiple environmental factors on HI using structural equation modeling (SEM). The results demonstrated significant varietal differences in HI across maturity periods. Specifically, early-maturing cultivars showed the highest average HI (0.58), significantly exceeding those of medium-maturing (0.55) and late-maturing varieties (0.54). Environmental analysis further revealed that soil phosphorus content (both available and total phosphorus), elevation, and organic matter content significantly positively affected HI, whereas soil bulk density and electrical conductivity exhibited negative impacts. Notably, HI exhibited a strong negative correlation with stover yield (R² = 0.49), but remained relatively stable across different dry matter (DM) and grain yield levels. Despite the strong positive correlation between DM and grain yield (R² = 0.81), the relative stability of HI suggests that yield improvement requires balanced optimization of both DM and partitioning efficiency. This study provides crucial theoretical foundations for optimizing high-yield maize cultivation systems, regulating fertilizer application rates and their ratios, and improving the configuration of planting density in arid regions. These findings offer practical guidance for sustainable agricultural development in similar environments. Full article