OBJECTIVE: Noncarious cervical lesions (NCCLs) are multifactorial and can be caused by the anatomical structure of the teeth, erosion, abrasion and abnormal occlusion. The aim of this case-control study was to explore the risk factors for NCCLs.
METHODS: Cone-beam computed tomography was used to determine whether a wedge-shaped defect existed at the cementoenamel junction. We compared 63 participants with NCCLs with 63 controls without NCCLs, matched for sex, age (±1 year) and toothbrushing-related factors (e.g., type of bristle and brushing patterns, frequency and strength). All participants were asked to complete a questionnaire about self-administered daily diet habits and health condition. Univariate and multivariate logistic regression analyses were conducted to determine the risk factors for NCCLs.
RESULTS: Significant variables in the univariate analysis (i.e., p < .2) included frequency of carbonated beverage consumption, sella-nasion-point B angle (SNB) and Frankfort-mandibular plane angle (FMA). Multivariate logistic regression demonstrated that the consumption frequency of carbonated beverages (odds ratio [OR] = 3.147; 95% confidence interval [CI], 1.039-9.532), FMA (OR = 1.100; 95% CI, 1.004-1.204) and SNB (OR = 0.896; 95% CI, 0.813-0.988) was independent influencing factors. The area under the receiver operating characteristic curve (AUC) value of regression Model 1 (established with the frequency of carbonated beverage consumption, FMA, SNB and sleep bruxism) was 0.700 (95% CI, 0.607-0.792; p < .001), and that of regression Model 2 (established using the frequency of carbonated beverage consumption, FMA and SNB) was 0.704 (95% CI, 0.612-0.796; p < .001).
CONCLUSIONS: The consumption frequency of carbonated beverages and FMA was risk factors for NCCLs; the higher the frequency of carbonated beverage consumption and FMA, the higher was the probability of NCCLs. SNB was a protective factor for NCCL occurrence; the larger the SNB, the lower was the probability of NCCL occurrence. These findings have further clarified the aetiology of NCCLs and provided clinicians with valuable insights into strategies for preventing the loss of dental tissue.

This study designs a double-bounded dichotomous questionnaire, and uses the Contingent Valuation Method (CVM) to estimate residents\' willingness to pay(WTP) for water pollution control along the Taihu Lake Basin. The results of the returned questionnaire show that 82.76% of the residents are willing to pay. CVM estimation results show that the average WTP of residents for water pollution control is 138.86 yuan/year. In addition, the influencing factors of WTP are explored using a Logistic regression model, and the heterogeneity of WTP among residents of different genders is analyzed. The study found that: (1) The younger the residents, the higher their WTP; (2) The higher the income, the higher the residents\' WTP for water pollution control; (3) Residents with higher educational level are more willing to pay; (4) The higher the degree of residents\' understanding of water pollution control policies, the higher the WTP; (5) The higher the degree of residents\' recognition of pro-environmental behavior, the higher the WTP; (6) Male residents\' WTP is mainly affected by cognitive factors such as their understanding of governance policies and their approval of pro-environmental behaviors, while female residents\' WTP is mainly affected by personal attributes, such as age, income, and the number of household laborers. Furthermore, this study proposes targeted measures to improve residents\' WTP from three aspects: the government enriches the channels for residents to participate in water pollution control, the social media enriches the popularization of water environment knowledge, and the school strengthens the education of environmental protection knowledge, considering the differences in residents\' characteristics. Therefore, this study can provide a theoretical reference and decision-making basis for encouraging residents to participate in water pollution control, promote the construction of a beautiful watershed, and provide a reference for other basins.

UNASSIGNED: To analyze the factors influencing myopia and construct a nomogram to forecast the risk of myopia among school-age children, providing a reference for identifying high-risk groups to aid prevention and control.
UNASSIGNED: This case-control study enrolled 3512 students from three primary schools in Shenzhen using random cluster sampling for a questionnaire survey, myopia screening and ocular biometric parameter measurement. Logistic regression was used to analyze the influencing factors of myopia, and a nomogram was constructed to forecast myopia risk. Bootstrap resampling was used to verify the practicability of the nomogram.
UNASSIGNED: Older age (odds ratio[OR] = 1.164; 95% confidence interval [CI]: 1.111-1.219), female sex (OR = 2.405; 95% CI: 2.003-2.887), maternal myopia (OR = 1.331; 95% CI: 1.114-1.589), incorrect posture during reading and writing (OR = 1.283; 95% CI: 1.078-1.528) and axial length (OR = 7.708; 95% CI: 6.044-8.288) are risk factors for myopia, whereas an increase in corneal radius (OR = 0.036; 95% CI: 0.025-0.052) is a protective factor against myopia. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.857, and the net benefit was high when the risk threshold of the decision curve analyses (DCA) ranged from 0.20 to 1.00. The measured values were consistent with the prediction.
UNASSIGNED: The nomogram was accurate in predicting the risk of myopia among schoolchildren. This study provides a reference for screening high-risk students and for individualized myopia prevention and control.
Older age, female sex, maternal myopia, incorrect posture during reading and writing, and prolonged axial length are risk factors for myopia among primary school students.The nomogram constructed based on age, sex, maternal myopia, incorrect posture during reading and writing, axial length and corneal radius showed good predictive accuracy and practicability.The nomogram constructed in this study can be used for individualized myopia risk assessment.

With reference to a stratified case-control (CC) procedure based on a binary variable of primary interest, we derive the expression of the distortion induced by the sampling design on the parameters of the logistic model of a secondary variable. This is particularly relevant when performing mediation analysis (possibly in a causal framework) with stratified case-control (SCC) data in settings where both the outcome and the mediator are binary. Despite being designed for parametric identification, our strategy is general and can be used also in a nonparametric context. With reference to parametric estimation, we derive the maximum likelihood (ML) estimator and the M-estimator of the joint outcome-mediator parameter vector. We then conduct a simulation study focusing on the main causal mediation quantities (i.e., natural effects) and comparing M- and ML estimation to existing methods, based on weighting. As an illustrative example, we reanalyze a German CC data set in order to investigate whether the effect of reduced immunocompetency on listeriosis onset is mediated by the intake of gastric acid suppressors.

UNASSIGNED: The incidence and diagnostic rate of rotator cuff tears (RCTs) have increased significantly. The purpose of this study was to investigate and analyze the risk factors for symptomatic RCTs to provide a basis for their prevention and treatment.
UNASSIGNED: We retrospectively analyzed the relevant clinical indicators of 193 randomized clinical trial (RCT) patients and 161 non-RCT patients hospitalized with shoulder pain as the main complaint from January 1, 2017, to August 31, 2021. Univariate analysis and multivariate logistic regression analysis were used to analyze the differences in potential risk factors between the two groups.
UNASSIGNED: Univariate analysis revealed that age (p < 0.001), body mass index (BMI) (p = 0.036), hypertension (p < 0.001), coronary heart disease (p = 0.028), history of shoulder trauma (p < 0.001), hyperlipidemia (p = 0.025), type III acromion (p = 0.012) and critical shoulder angle (CSA) (p < 0.001) increased the risk of RCTs. Multivariate logistic regression analysis revealed that age ≥ 60 years (OR = 2.61, 95% CI = 1.23 to 5.12), CSA ≥ 35° (OR = 4.24, 95% CI = 1.60 to 11.22), hypertension (OR = 2.34, 95% CI = 1.33 to 4.11) and history of shoulder trauma (OR = 5.20, 95% CI = 2.87 to 9.45) were independent risk factors for symptomatic RCTs.
UNASSIGNED: The results of this study showed that age ≥ 60 years, CSA ≥35°, hypertension and history of shoulder trauma are independent risk factors for symptomatic RCTs and can provide directions for further development of prevention and treatment strategies. Future studies need to clarify the mechanism underlying the association between these risk factors and symptomatic RCTs.

Landslide susceptibility zoning is necessary for landslide risk management. This study aims to conduct the landslide susceptibility evaluation based on a model coupled with information value (IV) and logistic regression (LR) for Badong County in Hubei Province, China. Through the screening of landslide predisposing factors based on correlation analysis, a spatial database including 11 landslide factors and 588 historical landslides was constructed in ArcGIS. The IV, LR and their coupled model were then developed. To validate the accuracy of the three models, the receiver operating characteristic curves (ROC) and the landslide density curves were correspondingly created. The results showed that the areas under the receiver operating characteristic curve (AUCs) of the three models were 0.758, 0.786 and 0.818, respectively. Moreover, the landslide density increased exponentially with the landslide susceptibility, but the coupled model exhibited a higher growth rate among the three models, indicating good performance of the proposed model in landslide susceptibility evaluation. The landslide susceptibility map generated by the coupled model demonstrated that the high and very high landslide susceptibility area mainly concentrated along rivers and roads. Furthermore, by counting the landslide numbers and analyzing the landslide susceptibility within each town in Badong County, it was discovered that Yanduhe, Xinling, Dongrangkou and Guandukou were the main landslide-prone areas. This research will contribute to landslide prevention and mitigation and serve as a reference for other areas.

Sand and gravel are amongst the most mined and consumed resources in the world, especially in the Global South where the demand for sand increases due to urbanization. Large parts of this extraction occur in rivers, with adverse environmental consequences. Mitigation of riverine sand and gravel mining (RSM) impacts on freshwater systems requires a robust understanding of the scale and controlling factors of RSM. However, very limited data exist on the occurrence of this process. This is especially true over larger spatial scales. Here we aim to bridge this gap and gain more insight into the occurrence of RSM at a subcontinental scale. More specifically, we (1) develop a systematic mapping procedure of RSM to collect the first large-scale dataset of RSM occurrence focusing on India as a case study. Using this dataset, we then (2) statistically analyze the factors potentially controlling spatial patterns of RSM across India. Factors were included that represent both the demand and supply of sand. Based on these results, we (3) develop a logistic regression model to estimate the probability of RSM occurrence. Overall, our work shows the enormous scale of RSM in India: of the 808 randomly selected and investigated river reaches (with lengths of ca. 10 km), 61.6 % showed clear evidence of RSM. Statistical analyses revealed that the presence of RSM is mainly linked to variables describing the demand for sand (e.g. distance to city, percentage of built-up area around the river reach), while variables relating to supply (e.g. soil texture, expected sediment discharge) showed much weaker correlations. Only rainfall variability was a clearly significant factor, which may relate to river reach accessibility. Based on these findings, we present a first model and map that predicts the susceptibility to RSM in India.

Landslides are one of the natural phenomena with more negative impacts on landscape, natural resources, and human health worldwide. Andean geomorphology, urbanization, poverty, and inequality make it more vulnerable to landslides. This research focuses on understanding explanatory landslide factors and promoting quantitative susceptibility mapping. Both tasks supply valuable knowledge for the Andean region, focusing on territorial planning and risk management support. This work addresses the following questions using the province of Azuay-Ecuador as a study area: (i) How do EFA and LR assess the significance of landslide occurrence factors? (ii) Which are the most significant landslide occurrence factors for susceptibility analysis in an Andean context? (iii) What is the landslide susceptibility map for the study area? The methodological framework uses quantitative techniques to describe landslide behavior. EFA and LR models are based on a historical inventory of 665 records. Both identified NDVI, NDWI, altitude, fault density, road density, and PC2 as the most significant factors. The latter factor represents the standard deviation, maximum value of precipitation, and rainfall in the wet season (January, February, and March). The EFA model was built from 7 latent factors, which explained 55% of the accumulated variance, with a medium item complexity of 1.5, a RMSR of 0.02, and a TLI of 0.89. This technique also identified TWI, fault distance, plane curvature, and road distance as important factors. LR\'s model, with AIC of 964.63, residual deviance of 924.63, AUC of 0.92, accuracy of 0.84, and Kappa of 0.68, also shows statistical significance for slope, roads density, geology, and land cover factors. This research encompasses a time-series analysis of NDVI, NDWI, and precipitation, including vegetation and weather dynamism for landslide occurrence. Finally, this methodological framework replaces traditional qualitative models based on expert knowledge, for quantitative approaches for the study area and the Andean region.

Monkeypox (Mpox) is an emerging zoonotic disease with the potential for severe complications. Early identification and diagnosis are essential to prompt treatment, control its spread, and reduce the risk of human-to-human transmission. This study aimed to develop a clinical diagnostic tool and describe the clinical and sociodemographic features of 19 PCR-confirmed Mpox cases during an outbreak in a nonendemic region of northwestern Mexico. The median age of patients was 35 years, and most were male. Mpox-positive patients commonly reported symptoms such as fever, lumbago, and asthenia, in addition to experiencing painful ulcers and a high frequency of HIV infection among people living with HIV (PLWH). Two diagnostic models using logistic regression were devised, with the best model exhibiting a prediction accuracy of 0.92 (95% CI: 0.8-1), a sensitivity of 0.86, and a specificity of 0.93. The high predictive values and accuracy of the top-performing model highlight its potential to significantly improve early Mpox diagnosis and treatment in clinical settings, aiding in the control of future outbreaks.

BACKGROUND: Deha-Prakriti (DP) is a unique contribution of Ayurveda, which distinguishes the population into three main groups viz., Vata, Pitta, and Kapha predominant individuals. Its assessment helps physicians to prescribe a suitable diet, daily regimen, and lifestyle that prevents non-communicable diseases. Amavata (Rheumatoid Arthritis) is a disease that needs personalized management approach.
OBJECTIVE: To evaluate the association of DP with Amavata (∼Rheumatoid Arthritis).
OBJECTIVE: To evaluate DP-based susceptibility in the manifestation of Amavata vis-à-vis Rheumatoid Arthritis.
METHODS: A case-control study was conducted from 18.04.2018 to 09.01.2020, involving 150 cases (patients of Amavata), and 150 controls (healthy volunteers), matching in age (between 18 to 50 years), and sex, selected from Jamnagar. CCRAS-PAS for both the groups, Health Assessment proforma of TRISUTRA project CSIR-AYURGENOMICS, were used. Logistic regression analyses were conducted to determine the relationship between DP and Amavata.
RESULTS: The proportion of people with Vata dosha in the case group (53.79%) was substantially higher (P < 0.0001) than in the control group (24.91%). Pitta (39.35%) and Kapha (36.27%) doshas were found to be more prevalent in the control group (P < 0.0001). There was a six-percent rise in the likelihood of developing Amavata with every unit increase in Vata percentage, according to logistic regression analysis.
CONCLUSIONS: Vata predominant DP has a significant association with Amavata. Vata predominant DP individuals are more susceptible to Amavata than Pitta and Kapha predominant DP individuals.