Association between the triglyceride-glucose index and thyroid disorders: a cross-sectional survey and Mendelian randomization analysis.

BACKGROUND: Metabolic diseases are associated with thyroid disorders. Insulin resistance is the common pathological basis of metabolic diseases. We explored the relationship between the triglyceride-glucose (TyG) index, a simple insulin-resistance marker, and thyroid disorders. METHODS: Eligible TIDE (Thyroid Diseases, Iodine Status and Diabetes Epidemiology) subjects (n = 47,710) were screened with inclusion/exclusion criteria. Thyroid disorder prevalence among different TyG index groups was stratified by sex. Logistic regression evaluated the correlation between the TyG index and thyroid disorders. Multiple linear regression evaluated the association between the TyG index and TSH. Additionally, two-sample Mendelian randomization (MR) using published genome-wide association study data evaluated causality in the association between the TyG index and TSH. RESULTS: Men and women with greater TyG indices had a significantly greater prevalence of thyroid disorders than individuals with the lowest quartile (Q1) of TyG index (p < 0.05). Following adjustment for confounding factors, we observed that a greater TyG index significantly increased the risk of subclinical hypothyroidism in men and women (men: Q2: odds ratio (OR) [95% confidence interval (CI)] = 1.22 [1.07-1.38], p = 0.002; Q3: OR [95% CI] = 1.28 [1.12-1.45], p < 0.001; Q4: OR [95% CI] = 1.29 [1.12-1.50], p = 0.001; women: Q2: OR [95% CI] = 1.25 [1.12-1.39], p < 0.001; Q3: OR [95% CI] = 1.47 [1.31-1.64], p < 0.001; Q4: OR [95% CI] = 1.61 [1.43-1.82], p < 0.001). Only among women was the highest TyG index quartile associated with hypothyroidism (OR [95% CI] = 1.70 [1.15-2.50], p = 0.007). Additionally, in men, the association exists only in the more than adequate iodine intake population. In women, the relationship between the TyG index and thyroid disorders disappears after menopause. Furthermore, the TyG index exhibited a linear positive correlation with TSH levels. The MR analysis results revealed a causal relationship between a genetically determined greater TyG index and increased TSH (inverse-variance weighting (IVW): OR [95% CI] = 1.14 [1.02-1.28], p = 0.020); however, this causal relationship disappeared after adjusting for BMI in multivariable MR (MVMR) analysis (MVMR-IVW: OR 1.03, 95% CI 0.87-1.22, p = 0.739). CONCLUSIONS: A greater TyG index is associated with hypothyroidism and subclinical hypothyroidism and varies by sex and menopausal status. MR analysis demonstrated that the causal relationship between a genetically determined greater TyG index and elevated TSH levels is confounded or mediated by BMI.

Genome-Wide Association Studies on Chinese Wheat Cultivars Reveal a Novel Fusarium Crown Rot Resistance Quantitative Trait Locus on Chromosome 3BL.

Fusarium crown rot (FCR), primarily caused by Fusarium pseudograminearum, has emerged as a new threat to wheat production and quality in North China. Genetic enhancement of wheat resistance to FCR remains the most effective approach for disease control. In this study, we phenotyped 435 Chinese wheat cultivars through FCR inoculation at the seedling stage in a greenhouse. Our findings revealed that only approximately 10.8% of the wheat germplasms displayed moderate or high resistance to FCR. A genome-wide association study (GWAS) using high-density 660K SNP led to the discovery of a novel quantitative trait locus on the long arm of chromosome 3B, designated as Qfcr.hebau-3BL. A total of 12 significantly associated SNPs were closely clustered within a 1.05 Mb physical interval. SNP-based molecular markers were developed to facilitate the practical application of Qfcr.hebau-3BL. Among the five candidate FCR resistance genes within the Qfcr.hebau-3BL, we focused on TraesCS3B02G307700, which encodes a protein kinase, due to its expression pattern. Functional validation revealed two transcripts, TaSTK1.1 and TaSTK1.2, with opposing roles in plant resistance to fungal disease. These findings provide insights into the genetic basis of FCR resistance in wheat and offer valuable resources for breeding resistant varieties.

Changing trends in the global, regional, and national burden of iodine deficiency among adolescents and young adults: population-based study.

Iodine is a micronutrient required for the production of thyroid hormones, which regulate metabolism, growth, and neurodevelopment. Iodine deficiency among adolescents and young adults is a major global health issue. We analyzed data from the Global Burden of Disease 2019 database to calculate the prevalence, incidence, and disability-adjusted life-year (DALY) rates of iodine deficiency among adolescents and young adults. We explored the specific year with the most substantial changes in the trends of iodine deficiency among adolescents with annual percentage change (APC) by Joinpoint Regression analysis. Descriptive analyses were conducted to characterize the iodine deficiency burden according to age, sex, location, and sociodemographic index (SDI) quintiles. All measures are listed with 95% uncertainty intervals (UIs), and all rates are reported per 100,000 individuals. From 1990 to 2019, the iodine deficiency prevalence rate among adolescents decreased from 3082.43 (95% uncertainty interval [UI], 2473.01-3855.86) to 2190.84 (95% [UI], 1729.18-2776.16) per 100,000 population, with an AAPC of -1.15 (95% confidence interval [CI], -1.29 to -1.02). Regarding the SDI in 2019, the highest prevalence and DALY rates of iodine deficiency were reported in low-SDI countries. In 1990, Southeast Asia had the highest prevalence and DALYs rates for iodine deficiency among adolescents, while in 2019, Africa had the highest prevalence rate (3330.12). CONCLUSION: Globally, the iodine deficiency burden among adolescents has substantially decreased since 1990; however, low-SDI countries still bear a great burden. Implementation measures and monitoring systems should be strengthened to reduce the iodine deficiency burden, especially among adolescents. WHAT IS KNOWN: • Iodine deficiency can cause severe or irreversible developmental disorders, particularly in adolescents and young adults. • Universal Salt Iodization was implemented for ensuring appropriate iodine intake. WHAT IS NEW: • We found substantial declines in the prevalence rates of iodine deficiency among adolescents during the past three decades. Globally, the disability-adjusted life-year rate of iodine deficiency among adolescents decreased from 56.17 in 1990 to 35.38 in 2019. • Iodine deficiency among adolescents in low- sociodemographic index countries still bear a great burden.

Enhancement of broad-spectrum disease resistance in wheat through key genes involved in systemic acquired resistance.

Systemic acquired resistance (SAR) is an inducible disease resistance phenomenon in plant species, providing plants with broad-spectrum resistance to secondary pathogen infections beyond the initial infection site. In Arabidopsis, SAR can be triggered by direct pathogen infection or treatment with the phytohormone salicylic acid (SA), as well as its analogues 2,6-dichloroisonicotinic acid (INA) and benzothiadiazole (BTH). The SA receptor non-expressor of pathogenesis-related protein gene 1 (NPR1) protein serves as a key regulator in controlling SAR signaling transduction. Similarly, in common wheat (Triticum aestivum), pathogen infection or treatment with the SA analogue BTH can induce broad-spectrum resistance to powdery mildew, leaf rust, Fusarium head blight, and other diseases. However, unlike SAR in the model plant Arabidopsis or rice, SAR-like responses in wheat exhibit unique features and regulatory pathways. The acquired resistance (AR) induced by the model pathogen Pseudomonas syringae pv. tomato strain DC3000 is regulated by NPR1, but its effects are limited to the adjacent region of the same leaf and not systemic. On the other hand, the systemic immunity (SI) triggered by Xanthomonas translucens pv. cerealis (Xtc) or Pseudomonas syringae pv. japonica (Psj) is not controlled by NPR1 or SA, but rather closely associated with jasmonate (JA), abscisic acid (ABA), and several transcription factors. Furthermore, the BTH-induced resistance (BIR) partially depends on NPR1 activation, leading to a broader and stronger plant defense response. This paper provides a systematic review of the research progress on SAR in wheat, emphasizes the key regulatory role of NPR1 in wheat SAR, and summarizes the potential of pathogenesis-related protein (PR) genes in genetically modifying wheat to enhance broad-spectrum disease resistance. This review lays an important foundation for further analyzing the molecular mechanism of SAR and genetically improving broad-spectrum disease resistance in wheat.

Effects of iodine intake on gut microbiota and gut metabolites in Hashimoto thyroiditis-diseased humans and mice.

Hashimoto thyroiditis (HT) is an organ-specific autoimmune disease linked to iodine intake. Emerging evidence highlights the gut microbiota's role in HT pathogenesis via the microbiota-gut-thyroid axis. However, the process through which iodine intake modifies the microbiota and triggers HT remains unclear. This study examines how iodine affects gut dysbiosis and HT, recruiting 23 patients with HT and 25 healthy individuals to assess gut microbiota composition and metabolic features. Furthermore, we establish a spontaneously developed thyroiditis mouse model using NOD.H-2h4 mice highlighting the influence of iodine intake on HT progression. The butanoate metabolism significantly differs between these two groups according to the enrichment results, and butyric acid is significantly decreased in patients with HT compared with those in healthy individuals. Gut dysbiosis, driven by excessive iodine intake, disrupts TH17/Treg balance by reducing butyric acid. In summary, iodine intake alters intestinal microbiota composition and metabolic changes influencing the microbiota-gut-thyroid axis.

Selenium in the treatment of mild-to-moderate Graves' orbitopathy: a 5-year prospective controlled cohort study.

PURPOSE: Graves' orbitopathy (GO) is the main extrathyroidal manifestation of Graves' disease. However, limited studies have investigated the actual efficacy of selenium in GO therapy. This longitudinal study explored the effect of selenium on QOL and prognosis of patients with mild-to-moderate GO. METHODS: We conducted a 5-year prospective controlled cohort clinical trial to determine the effect of selenium on 74 patients with mild-to-moderate GO. Patients received selenium yeast or placebo orally for 6 months and were followed up at 6 months and at 5 years by biochemical examination, ophthalmologist evaluation and QOL questionnaire to assess oculopathy and QOL. RESULTS: (1) During a follow-up period of 3-6 months, in the selenium group, the symptoms of tearing, grittiness and conjunctival congestion improved (P < 0.01); clinical activity scores and total GO-QOL scores increased relative to baseline (P < 0.01); TRAb was decreased at the 6-month evaluation (P = 0.003); and patients treated with selenium had a higher rate of improvement and a lower rate of worsening than patients treated with placebo (P < 0.05). (2) Exploratory evaluations at 6 months after drug withdrawal confirmed the earlier results; further changes included alleviation of blurred vision and double vision symptoms in the selenium group (P < 0.01). (3) At the 5-year follow-up, compared with baseline, proptosis, clinical activity scores, TRAb level and total GO-QOL scores in both the selenium and placebo groups were significantly improved (P < 0.01). CONCLUSION: Six months of selenium supplementation may effectively change the early course of mild-to-moderate GO, but this regimen makes no difference in long-term outcomes.

Iodine-induced thyroid dysfunction: a scientometric study and visualization analysis.

Objective: Iodine is essential in thyroid hormone production. Iodine deficiency is associated with serious complications (i.e miscarriage and stillbirth), whereas excess can cause thyroid dysfunction (i.e hyperthyroidism, hypothyroidism, thyroid autoimmunity). We conducted this scientometric study to visualize hot spots and trends in iodine-induced thyroid dysfunction over past two decades. The aim of this paper was to help scholars quickly understand the development and potential trend in this field, and guide future research directions. Methods: Articles on iodine-induced thyroid dysfunction from 2000 to 2022 were retrieved from the Web of Science Core Collection (WoSCC) using the following search terms: (((((TS=(hypothyroid*)) OR TS=(hyperthyroid*)) OR TS= ("TSH deficiency")) OR TS= ("thyroid stimulating hormone deficiency")) AND TS=(Iodine)) NOT TS=(radioiodine). Only publications in English were selected. CiteSpace, VOSviewer, Tableau, Carrot2, and R software were used to analyze the contribution and co-occurrence relationships of different countries, institutes, keywords, references, and journals. Results: A total of 2986 publications from 115 countries and 3412 research institutions were included. From 2000 to 2022, research on iodine-induced thyroid dysfunction progressed over a three-stage development period: initial development (2000-2009), stable development (2010-2016), and rapid development (2016-2022) period. The Journal of Clinical Endocrinology and Metabolism had the most co-citations followed and China Medical University (n=76) had the most publications. The top three clusters of co-citation references were isolated maternal hypothyroxinemia, subclinical hyperthyroidism, and brain development. Various scientific methods were applied to reveal acknowledge structure, development trend and research hotspots in iodine-induced thyroid dysfunction. Conclusion: Our scientometric analysis shows that investigations related to pregnant women, epidemiology surveys, and iodine deficiency are promising topics for future iodine-induced thyroid dysfunction research and highlights the important role of iodine on thyroid function.

Asymmetry-enhanced attention network for Alzheimer's diagnosis with structural Magnetic Resonance Imaging.

BACKGROUND AND OBJECTIVE: With the aging of the global population becoming severe, Alzheimer's disease (AD) has become one of the world's most common senile diseases. Many studies have suggested that the brain's left-right asymmetry is one of the possible diagnostic landmarks for AD. However, most published approaches to classification problems may not adequately explore the asymmetry between the left and right hemispheres. At the same time, the relationship between asymmetry traits and other classifier features remains understudied. METHODS: In this paper, we proposed an asymmetry enhanced attention network (ASEAN) for AD diagnosis that effectively combines the anatomical asymmetry characteristics of the brain to enhance the accuracy and stability of classification tasks. First, we proposed a multi-scale asymmetry feature extraction module (MSAF) that can extract the asymmetry features of the brain from various scales. Second, we proposed an asymmetry refinement module (ARM) that considers the dependency between feature maps to suppress the irrelevant regions of the asymmetric feature maps. In addition, a parameter-free attention module was introduced to infer 4D attention weights and improve the network's representation capability. RESULTS: The proposed method achieved performance improvements on two databases: Alzheimer's Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarkers and Lifestyle (AIBL). For the classification tasks on ADNI, the proposed method achieves 92.1% accuracy, 96.2% sensitivity, and 91.3% specificity on the AD vs. CN (Cognitively Normal) task. Compared with state-of-the-art methods, the proposed method could achieve comparable results. CONCLUSION: The proposed model can extract long-range left-right brain similarity as complementary information and improve the model's diagnostic performance. A large number of experiments also support the model's validity. At the same time, this work provides a valuable reference for other neurological diseases, particularly those that exhibit left-right brain asymmetry during development.

Learning to segment subcortical structures from noisy annotations with a novel uncertainty-reliability aware learning framework.

Accurate segmentation of subcortical structures is an important task in quantitative brain image analysis. Convolutional neural networks (CNNs) have achieved remarkable results in medical image segmentation. However, due to the difficulty of acquiring high-quality annotations of brain subcortical structures, learning segmentation networks using noisy annotations is an inevitable topic. A common practice is to select images or pixels with reliable annotations for training, which usually may not make full use of the information from the training samples, thus affecting the performance of the learned segmentation model. To address the above problem, in this work, we propose a novel robust learning method and denote it as uncertainty-reliability awareness learning (URAL), which can make sufficient use of all training pixels. At each training iteration, the proposed method first selects training pixels with reliable annotations from the set of pixels with uncertain network prediction, by utilizing a small clean validation set following a meta-learning paradigm. Meanwhile, we propose the online prototypical soft label correction (PSLC) method to estimate the pseudo-labels of label-unreliable pixels. Then, the segmentation loss of label-reliable pixels and the semi-supervised segmentation loss of label-unreliable pixels are used to calibrate the total segmentation loss. Finally, we propose a category-wise contrastive regularization to learn compact feature representations of all uncertain training pixels. Comprehensive experiments are performed on two publicly available brain MRI datasets. The proposed method achieves the best Dice scores and MHD values on both datasets compared to several recent state-of-the-art methods under all label noise settings. Our code is available at https://github.com/neulxlx/URAL.

EA-Net: Edge-aware network for brain structure segmentation via decoupled high and low frequency features.

Automatic brain structure segmentation in Magnetic Resonance Image (MRI) plays an important role in the diagnosis of various neuropsychiatric diseases. However, most existing methods yield unsatisfactory results due to blurred boundaries and complex structures. Improving the segmentation ability requires the model to be explicit about the spatial localization and shape appearance of targets, which correspond to the low-frequency content features and the high-frequency edge features, respectively. Therefore, in this paper, to extract rich edge and content feature representations, we focus on the composition of the feature and utilize a frequency decoupling (FD) block to separate the low-frequency and high-frequency parts of the feature. Further, a novel edge-aware network (EA-Net) is proposed for jointly learning to segment brain structures and detect object edges. First, an encoder-decoder sub-network is utilized to obtain multi-level information from the input MRI, which is then sent to the FD block to complete the frequency separation. Further, we use different mechanisms to optimize both the low-frequency and high-frequency features. Finally, these two parts are fused to generate the final prediction. In particular, we extract the content mask and the edge mask from the optimization feature with different supervisions, which forces the network to learn the boundary features of the object. Extensive experiments are performed on two public brain MRI T1 scan datasets (the IBSR dataset and the MALC dataset) to evaluate the effectiveness of the proposed algorithm. The experiments show that the EA-Net achieves the best performance compared with the state-of-the-art methods, and improves the segmentation DSC score by 1.31% at most compared with the U-Net model and its variants. Moreover, we evaluate the EA-Net under different noise disturbances, and the results demonstrate the robustness and superiority of our method under low-quality noisy MRI. Code is available at https://github.com/huqian999/EA-Net.

Exogenous expression of barley HvWRKY6 in wheat improves broad-spectrum resistance to leaf rust, Fusarium crown rot, and sharp eyespot.

Systemic acquired resistance (SAR) is a broad-spectrum plant defense phenomena controlled by the salicylic acid receptor NPR1. Key regulators of the SAR signaling pathway showed great potentials to improve crop resistance to various diseases. In our previous investigation, a barley transcription factor gene HvWRKY6 was identified as downstream of NPR1 during SAR. However, the broad-spectrum resistance features and molecular mechanisms of HvWRKY6 remain to be explored. In this study, a transgenic wheat line exogenously expressing HvWRKY6 showed improved resistance to leaf rust, Fusarium crown rot (FCR), and sharp eyespot. The model pathogen Pseudomonas syringae pv. tomato DC3000 was employed to induce the SAR response in wheat plants' leaf region adjacent to the infiltration area. Transcriptome sequencing revealed activation of broad-spectrum defense responses by expressing HvWRKY6 in a pathogen-independent manner. Based on the differentially expressed genes in plant hormone signal transduction, we speculated that the enhanced resistance in HvWRKY6-OE wheat transgenic line was associated with activation of the salicylic acid pathway and suppression of the abscisic acid and jasmonic acid pathways. These findings suggest that the transgenic line HvWRKY6-OE might be applied for the genetic improvement of wheat to several fungal diseases; the underlying resistance mechanism was clarified.

Menopausal Impact on the Association Between Thyroid Dysfunction and Lipid Profiles: A Cross-Sectional Study.

Background: Both dyslipidemia and thyroid dysfunction have a high prevalence rate and are important risk factors for cardiovascular diseases. However, the relationship between blood lipids and thyroid dysfunction is still controversial. This study aims to analyze the blood lipids in people with different thyroid functions. Methods: A total of 80937 adults were included in this population-based cross-sectional TIDE survey, which collected demographic and clinical data on thyroid function, blood lipid levels and other metabolic indicators. After screening, the final analysis included 10,747 participants, who were divided into hypothyroidism (n=311), subclinical hypothyroidism (n=5015), hyperthyroidism (n=203), subclinical hyperthyroidism (n=118) and control (n=5100) groups. The risk of dyslipidemia was analyzed by a logistic regression model and divided into groups of female menopausal. Results: After full adjustment, significant associations were found between hypothyroidism and hypertriglyceridemia. Subclinical hypothyroidism was associated with a significantly higher risk of hypertriglyceridemia and hyper-low density lipoprotein cholesterolemia. Hyperthyroidism was significantly correlated with a reduced risk of hypercholesterolemia and hyper-low density lipoprotein cholesterolemia but positively correlated with the risk of low-high density lipoprotein cholesterolemia. There was no significant association between subclinical hyperthyroidism and blood lipids. Hypothyroidism increased the risk of hypertriglyceridemia in both premenopausal and postmenopausal females. Subclinical hypothyroidism was significantly associated with increased hypertriglyceridemia and low-high density lipoprotein cholesterolemia in premenopausal females. Hyperthyroidism was significantly associated with a reduced risk of hypercholesterolemia and hyper-low density lipoprotein cholesterolemia in premenopausal females and an increased risk of low-high density lipoprotein cholesterolemia in postmenopausal female. Conclusion: Abnormal thyroid function has an important effect on blood lipids and is closely related to female menopause.

The spatial association of social vulnerability with COVID-19 prevalence in the contiguous United States.

This study aims to examine the spatially varying relationships between social vulnerability factors and COVID-19 cases and deaths in the contiguous United States. County-level COVID-19 data and the Centers for Disease Control and Prevention social vulnerability index (SVI) dataset were analyzed using local Spearman's rank correlation coefficient. Results suggested that SVI and four social vulnerability themes have spatially varying relationships with COVID-19 cases and deaths, which means spatial heterogeneity is an essential factor that influences the relationship, and the strength of association varies significantly across counties. County hot spots that were subject to all four social vulnerability themes during the pandemic were also identified. Local communities and health authorities should pay immediate attention to the most influential social vulnerability factors that are dominant in their region and incorporate measures tailored to the specific groups of people who are under the greatest risk of being affected during the COVID-19 pandemic.

Association Between Gut Microbiota and Autoimmune Thyroid Disease: A Systematic Review and Meta-Analysis.

Background: Autoimmune thyroid disease (AITD) is characterized by thyroid dysfunction and deficits in the autoimmune system. Growing attention has been paid toward the field of gut microbiota over the last few decades. Several recent studies have found that gut microbiota composition in patients with AITD has altered, but no studies have conducted systematic reviews on the association between gut microbiota and ATID. Methods: We searched PubMed, Web of Science, Embase, and Cochrane databases without language restrictions and conducted a systematic review and meta-analysis of eight studies, including 196 patients with AITD. Results: The meta-analysis showed that the alpha diversity and abundance of certain gut microbiota were changed in patients with AITD compared to the controls. Chao1,the index of the microflora richness, was increased in the Hashimoto's thyroiditis group compared to controls (SMD, 0.68, 95%CI: 0.16 to 1.20), while it was decreased in the Graves' disease group (SMD, -0.87, 95%CI: -1.46 to -0.28). In addition, we found that some beneficial bacteria like Bifidobacterium and Lactobacillus were decreased in the AITD group, and harmful microbiota like Bacteroides fragilis was significantly increased compared with the controls. Furthermore, the percentage of relevant abundance of other commensal bacteria such as Bacteroidetes, Bacteroides, and Lachnospiraceae was increased compared with the controls. Conclusions: This meta-analysis indicates an association between AITD and alteration of microbiota composition at the family, genus, and species levels. Systematic Review Registration: PROSPERO, identifier CRD42021251557.

The Type 2 Deiodinase Thr92Ala Polymorphism Is Associated with Higher Body Mass Index and Fasting Glucose Levels: A Systematic Review and Meta-Analysis.

BACKGROUND: Type 2 deiodinase (Dio2) is a selenoenzyme that is mainly expressed in the endoplasmic reticulum of the central nervous system, brown adipose tissue, and placenta and is responsible for outer ring deiodination of thyroxine (T4) to form biologically active triiodothyronine (T3). The Thr92Ala polymorphism of Dio2 has been found to be a potential risk factor for various diseases beyond the hypothalamus-pituitary-thyroid (HPT) axis. METHODS: We searched the relevant studies in the PubMed, Embase, and Cochrane Library databases and Google Scholar. A systematic review and meta-analysis of studies on the Thr92Ala polymorphism and metabolic parameters beyond the HPT axis (e.g., BMI, fasting glycemic traits, plasma lipid levels, and hypertension risk) were performed. RESULTS: Six eligible studies that analyzed the relationship between the Thr92Ala polymorphism and metabolic parameters beyond the thyroid were identified. All selected studies excluded patients with thyroid dysfunction, and diabetic patients were also excluded when fasting glucose and fasting insulin levels were meta-analyzed. The Thr92Ala polymorphism was found to be a significant risk factor for higher BMI (Std. mean difference 0.31 (0.01, 0.60), p = 0.04) and higher fasting glucose levels (Std. mean difference 1.18 (0.05, 2.31), p = 0.04). However, fasting insulin levels, plasma lipid levels, and hypertension risk showed a nonsignificant association with the Thr92Ala polymorphism. CONCLUSION: Compared with euthyroid noncarriers (Thr/Thr), euthyroid Ala92-Dio2 carriers showed increased BMI levels, and Ala92-Dio2 carriers also had higher fasting plasma glucose levels than matched euthyroid nondiabetic noncarriers.

Hyperthyroidism Prevalence in China After Universal Salt Iodization.

Background: Universal salt iodization (USI) was implemented in mainland China in 1996. The prevalence of hyperthyroidism and its risk factors now require examination. Methods: Data were acquired from a nationwide Thyroid, Iodine, and Diabetes Epidemiological survey (TIDE 2015-2017) of 78,470 subjects from 31 provinces. Iodine status, and thyroid hormones and antibodies were measured. Results: After two decades of USI, the prevalence of overt hyperthyroidism (OH), Graves' disease (GD), severe subclinical hyperthyroidism (severe SCH), and mild subclinical hyperthyroidism (mild SCH) in mainland China was 0.78%, 0.53%, 0.22%, and 0.22%, respectively. OH and GD prevalence were higher in women than in men (OH: 1.16% vs. 0.64%, P<0.001; GD: 0.65% vs. 0.37%, P<0.001).Prevalence was significantly decreased after 60 years-of-age compared with 30-39 years-of-age (OH:0.61% vs. 0.81%, P<0.001; GD: 0.38% vs. 0.57%, P<0.001).Excessive iodine(EI) and deficient iodine(DI) were both related to increased prevalence of OH (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.68-2.59; OR1.35, 95%CI 1.07-1.72, respectively); however, only deficient iodine was associated with increased prevalence of GD (OR1.67, 95%CI 1.30-2.15). Increased thyroid peroxidase antibody and thyroglobulin antibody levels were significantly associated with prevalence of OH and GD, but not severe SCH and mild SCH. Although hyperthyroidism was more prevalent in women, the association disappeared after adjusting for other factors such as antibody levels. Conclusion: OH and GD prevalences in mainland China are stable after two decades of USI. Iodine deficiency, elevated thyroid antibody levels, and middle age are the main risk factors for OH and GD. The severe SCH population, rather than the mild SCH population, shows similar characteristics to the OH population.

Spatial Modeling and Analysis of Heat-Related Morbidity in Maricopa County, Arizona.

The objective of the present study was to examine the effects of a confluence of demographic, socioeconomic, housing, and environmental factors that systematically contribute to heat-related morbidity in Maricopa County, Arizona, from theoretical, empirical, and spatial perspectives. The present study utilized ordinary least squares (OLS) regression and multiscale geographically weighted regression (MGWR) to analyze health data, U.S. census data, and remotely sensed data. The results suggested that the MGWR model showed a significant improvement in goodness of fit over the OLS regression model, which implies that spatial heterogeneity is an essential factor that influences the relationship between these factors. Populations of people aged 65+, Hispanic people, disabled people, people who do not own vehicles, and housing occupancy rate have much stronger local effects than other variables. These findings can be used to inform and educate local residents, communities, stakeholders, city managers, and urban planners in their ongoing and extensive efforts to mitigate the negative impacts of extreme heat on human health in Maricopa County.

Optimization of residential green space for environmental sustainability and property appreciation in metropolitan Phoenix, Arizona.

Cities in arid and semi-arid regions have been exploring urban sustainability policies, such as lowering the vegetation coverage to reduce residential outdoor water use. Meanwhile, urban residents express concerns that such policies could potentially impact home prices regardless of the reduced water costs because studies have shown that there is a positive correlation between vegetation coverage and home values. On the other hand, lower vegetation coverage in arid and semi-arid desert regions could increase surface temperatures, and consequently increases energy costs. The question is therefore where the point in which residential outdoor water use can be minimized without overly increasing surface temperatures and negatively impacting home values. This study examines the impacts of spatial composition of different vegetation types on land surface temperature (LST), outdoor water use (OWU), and property sales value (PSV) in 302 local residential communities in the Phoenix metropolitan area, Arizona using remotely sensed data and regression analysis. In addition, the spatial composition of vegetation cover was optimized to achieve a relatively lower LST and OWU and maintain a relatively higher PSV at the same time. We found that drought-tolerant landscaping that is composed of mostly shrubs and trees adapted to the desert environment is the most water efficient way to reduce LST, but grass contributes to a higher PSV. Research findings suggest that different residential landscaping strategies may be better suited for different neighborhoods and goal sets can be used by urban planners and city managers to better design urban residential landscaping for more efficient water conservation and urban heat mitigation for desert cities.

Assessing environmental impacts and change in Myanmar's mangrove ecosystem service value due to deforestation (2000-2014).

Myanmar is one of the mangrove-richest countries in the world, providing valuable ecosystem services to people. However, due to deforestation driven primarily by agricultural expansion, Myanmar's mangrove forest cover has declined dramatically over the past few decades, while what remains is still under pressure. To support management planning, accurate quantification of mangrove forest cover changes on a national scale is needed. In this study, we quantified Myanmar's mangrove forest cover changes between 2000 and 2014 using remotely sensed data, examined the environmental impacts of such changes, and estimated the changes in the economic values of mangrove ecosystem services in the country. Results indicate that Myanmar had a net mangrove loss of 191,122 ha over the study period. Since 2000, Myanmar has been losing mangrove forest cover at an alarming rate of 14,619 ha/year (2.2%/year). The loss was predominant in Rakhine and Ayeyarwady. The observed mangrove forest cover loss has resulted in decreased evapotranspiration, carbon stock, and tree cover percentage. Due to deforestation, Myanmar also suffered a net loss of 2,397 million US$/year in its mangrove ecosystem service value (i.e. 28.7% decrease from 2000), in which maintenance of fisheries nursery populations and habitat and coastal protection were among those services that were greatly affected. We suggest that intensive reforestation and mangrove protection programs be implemented immediately. Agroforestry and community forestry programs are encouraged in areas that are under immense pressure from paddy field expansion, fuelwood extraction, charcoal production, and fish and shrimp farming activities. Potential alternative sustainable solutions should include intensive government-led private forest plantations or community-owned forest plantations to be developed with care by local farmers, nongovernmental organizations, and business owners.