Association between triglyceride glucose index and H-type hypertension in postmenopausal women.

Background: Recent studies have reported better predictive performance of triglyceride glucose (TyG) index for cardiovascular events in women, however, whether this association persists in postmenopausal women is inconclusive. We investigated the association between TyG index and H-type hypertension (HHT) in postmenopausal women. Methods: 1,301 eligible women with hypertension were included in this cross-sectional study. Concomitant homocysteine levels >10 µmol/L were defined as H-type hypertension. The TyG index was calculated as ln [triglycerides (mg/dl) × fasting glucose (mg/dl)/2]. Multivariable logistic regression models and restricted cubic spline models were used to assess the association between TyG index and H-type hypertension in postmenopausal women, and subgroup analyses were performed for potential confounders. Results: Of the 1,301 hypertensive patients, 634 (48.7%) participants had H-type hypertension. In each adjusted model, TyG index was significantly associated with the risk of H-type hypertension. each 1-unit increase in TyG index was associated with an increased risk of H-type hypertension in all participants (OR = 1.6; 95% CI, 1.3-2.0; P < 0.001), and there was a linear relationship between TyG index and H-type hypertension (P for linear trend < 0.001). Conclusion: TyG index is positively associated with H-type hypertension in postmenopausal women, suggesting that TyG index may be a promising marker for H-type hypertension. By controlling lipid levels and blood glucose levels, it may help prevent H-type hypertension in postmenopausal women.

Satellite observed reversal in trends of spring phenology in the middle-high latitudes of the Northern Hemisphere during the global warming hiatus.

The start of the growing season (SOS) is essential to track the responses of vegetation to climate change. However, recent findings on whether the SOS in the middle-high latitudes of the Northern Hemisphere (NH) continued to advance or reversed during the global warming hiatus were not consistent. It is necessary to investigate the causes of this controversy and to examine the relationship between the SOS and preseason temperature trends. To this end, we first applied four widely used phenology extraction methods to derive the SOS from the GIMMS NDVI3g dataset and then used the ensemble empirical modal decomposition (EEMD) method to extract the nonlinear trends of the SOS and preseason temperature. Our results clarify, for the first time, that the limitations of the linear assumption-based trend analysis methods are an important but overlooked cause of the discrepancies among existing studies on whether the SOS was advanced or delayed in the NH (>30° N) during the global warming hiatus. We further revealed the range of the mismatches between the SOS and preseason temperature trends at the latitude, altitude and biome levels. Specifically, we discovered that the SOS in the NH (>30° N) obtained by the four phenology extraction methods showed a significant reversal from advance to delay during the global warming hiatus, and the corresponding average rate of change was very small. The area showing increasing preseason temperatures decreased during the global warming hiatus, but it always occupied most of the NH (>30° N). However, delayed SOS trends were dominant in the NH from 50° N to 60° N, above 3000 m and in biomes other than TBMF and BF. Accordingly, using an EEMD-like approach to evaluate the changes in the SOS and preseason temperature is necessary for improving our understanding of the changes in the SOS and their association with climate.

Association between body fat percentage and H-type hypertension in postmenopausal women.

Background: Previous studies have explored the relationship between body fat percentage (BFP) and hypertension or homocysteine. However, evidence on the constancy of the association remains inconclusive in postmenopausal women. The aim of this study was to investigate the association between BFP and H-type hypertension in postmenopausal women. Methods: This cross-sectional study included 1,597 eligible female patients with hypertension. Homocysteine levels ≥10 mmol/L were defined as H-type hypertension. BFP was calculated by measuring patients' physical parameters. Subjects were divided into 4 groups according to quartiles of BFP (Q1: 33.4% or lower, Q2: 33.4-36.1%, Q3: 36.1-39.1%, Q4: >39.1%). We used restricted cubic spline regression models and logistic regression analysis to assess the relationship between BFP and H-type hypertension. Additional subgroup analysis was performed for this study. Results: Among 1,597 hypertensive patients, 955 (59.8%) participants had H-type hypertension. There were significant differences between the two groups in age, BMI, educational background, marital status, exercise status, drinking history, WC, TG, LDL, Scr, BUN, and eGFR (P < 0.05). The prevalence of H-type hypertension in the Q1 to Q4 groups was 24.9, 25.1, 24.9, and 25.1%, respectively. After adjusting for relevant factors, we found that the risk of H-type hypertension in the Q4 group had a significantly higher than the Q1 group (OR = 3.2, 95% CI: 1.3-7.5). Conclusion: BFP was positively associated with the risk of H-type hypertension in postmenopausal women. Postmenopausal women should control body fat to prevent hypertension.

[Assessment on the ecological suitability in Zhuhai City, Guangdong, China, based on minimum cumulative resistance model].

Urban landscape has the characteristics of spatial heterogeneity. Because the expansion process of urban constructive or ecological land has different resistance values, the land unit stimulates and promotes the expansion of ecological land with different intensity. To compare the effect of promoting and hindering functions in the same land unit, we firstly compared the minimum cumulative resistance value of promoting and hindering functions, and then looked for the balance of two landscape processes under the same standard. According to the ecology principle of minimum limit factor, taking the minimum cumulative resistance analysis method under two expansion processes as the evaluation method of urban land ecological suitability, this research took Zhuhai City as the study area to estimate urban ecological suitability by relative evaluation method with remote sensing image, field survey, and statistics data. With the support of ArcGIS, five types of indicators on landscape types, ecological value, soil erosion sensitivity, sensitivity of geological disasters, and ecological function were selected as input parameters in the minimum cumulative resistance model to compute urban ecological suitability. The results showed that the ecological suitability of the whole Zhuhai City was divided into five levels: constructive expansion prohibited zone (10.1%), constructive expansion restricted zone (32.9%), key construction zone (36.3%), priority development zone (2.3%), and basic cropland (18.4%). Ecological suitability of the central area of Zhuhai City was divided into four levels: constructive expansion prohibited zone (11.6%), constructive expansion restricted zone (25.6%), key construction zone (52.4%), priority development zone (10.4%). Finally, we put forward the sustainable development framework of Zhuhai City according to the research conclusion. On one hand, the government should strictly control the development of the urban center area. On the other hand, the secondary urban center area such as Junchang and Doumen need improve the public infrastructure to relieve the imbalance between eastern and western development in Zhuhai City.

Spatially varying relationships between land-cover change and driving factors at multiple sampling scales.

Modeling the relationships between environment, human activity, and natural conditions is very important for understanding human-environment interactions. This study aims at examining how these relationships vary over spatial sampling scales and investigating the spatially varying relationships between land-cover changes and driving factors, as well as the variations in the relationships at different sampling scales in the Tibetan Autonomous Prefecture of Qinghai Province, P.R. China. Regular sampling methods are used first to generate eight sets of data points at different scales, and then the values for land-cover changes and the factors are extracted for these data points. Geographically weighted regression (GWR) model is applied to analyze the relationships between land-cover changes and the factors at different sampling scales. The results indicate that the influences of the factors (e.g. the signs, significances, and values of coefficients) change greatly over different sampling scales; similarly, for different types of land-cover changes, the contributions of the factors also vary. Generally, roads, rivers, and lakes contribute greatly to land-cover changes, while villages, temples, and elevations contribute less. A possible reason is that the densities of roads, rivers, and lakes is much greater than those of villages and temples, and the populations in temples and villages are too small to have much effect on land-cover changes. The results demonstrate that the sampling scales have an important influence on the relationships between land-cover change and the factors.

[Extracting municipal solid waste dumps based on high resolution images].

The dramatically increasing informal MSW dumps are endangering the urban environment. Remote sensing (RS) technologies are more efficient to monitor and manage municipal solid wastes (MSW) than traditional survey-based methods. In high spatial resolution remotely sensed images, these irregularly distributed dumps have complex compositions and strong heterogeneities, thus it is still hard to extract them automatically no matter the pixel-or object-based image analysis method is used. Therefore, based on the analysis of MSW characteristics, the present study develops a multiresolution strategy to extract MSW dumps by combining image features at both high resolution and resampled low heterogeneity images, while the high resolution images can provide detailed information and the low resolution images can suppress the strong heterogeneities of informal MSW dumps. Taking the QuickBird image covering part of Beijing as an example, this multi-resolution strategy produced a high accuracy (75%), indicating that this multi-resolution strategy is quite effective for extracting the open-air informal MSW dumps.

[Spatiotemporal differentiation of land cover change and grassland degradation pattern in Yangtze River headwaters area].

Based on field survey data, remote sensing images and statistical data, this paper analyzed the spatiotemporal differentiation of land use and grassland degradation patterns in Yangtze River headwaters area in 1987-2007, and discussed the main natural factors (elevation, position and slope) leading to the changes of this area's grassland ecological environment. In 1987-2007, the fragmentation of this area' s landscape patterns had an increasing trend, and natural environment and climate change were the main driving forces of land use pattern change. There existed significant differences in the areas of grassland degradation at different altitudes. Grassland degradation mainly occurred at altitudes 4800-5100 m. The grassland degradation area tended to increase with increasing elevation, and the proportions of the degradation area varied greatly over different slopes and aspects. The climate in the study area became warm and dry, and the spatial structure of regional land cover changed obviously. The distribution patterns of grassland degradation at different elevation, position and slope coincided with alpine environment and human disturbances, suggesting that alpine environment and climatic change were the decisive factors to the grassland ecosystem pattern in Yangtze River headwaters area.