Serum selenium concentration is associated with metabolic factors in the elderly: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Selenium is an essential micronutrient known for its antioxidant function. However, the association of serum selenium with lipid profiles and fasting glucose are inconsistent in populations with average intake of selenium. Furthermore, there were few studies conducted specifically for the elderly. This study examined the relationship of serum selenium concentration with serum lipids and fasting glucose in the Taiwanese elderly population.</p> <p>Methods</p> <p>This was a cross-sectional study of 200 males and females aged 65-85 years (mean 71.5 ± 4.6 years) from Taipei, Taiwan. Serum selenium was measured by inductively coupled plasma-mass spectrometer. The association between serum selenium and metabolic factors was examined using a multivariate linear regression analysis after controlling several confounders.</p> <p>Results</p> <p>The mean serum selenium concentration was 1.14 μmol/L, without significant difference between sexes. Total cholesterol, triglycerides, and LDL cholesterol increased significantly with serum selenium concentration (<it>P </it>< 0.001, <it>P </it>< 0.05 and <it>P </it>< 0.001, respectively) after adjusting for age, gender, anthropometric indices, lifestyle factors, and cardio-vascular risk factors in several linear regression models. Furthermore, there was a significantly positive association between serum selenium and serum fasting glucose concentrations (<it>P </it>< 0.05).</p> <p>Conclusions</p> <p>Total cholesterol, triglycerides, and LDL cholesterol, and fasting serum glucose concentrations increased significantly with serum selenium concentration in the Taiwanese elderly. The underlying mechanism warrants further research.</p

Statistical Aspects of Cost-Effectiveness Analysis of Vaccination for Alzheimer’s Disease

研究背景：阿茲海默症是一個退化性的慢性疾病，也是最常見的失智症原因，雖然有藥物可延緩疾病的退化，但目前並沒有根治的方法。自1990年代以來，阿茲海默症的免疫治療，陸續進入不同期的臨床試驗，但目前還尚未有成本效益方面的研究。然有關醫療成本效益常面臨疾病的治療過程，病人中斷治療，而出現設限狀態，但中斷治療後照護成本和疾病演化仍是繼續的情況下，若忽略此設限狀態的存在，將導致成本與效益的估計偏差。而且，因涉及疾病自然病史狀態之間的轉移，須利用較複雜馬可夫決策模式。此外，成本與效益之間的相關性亦常被忽略，本論文以阿茲海默症免疫治療成本效益分析為例，示範如何針對這些問題進行處理。 研究方法：本研究以文獻中估計所得的疾病自然史的轉移機率，以馬可夫決策模型模擬阿茲海默症的族群作為研究世代。比較的策略則分為為施打阿茲海默症疫苗的介入組與未施打的控制組，每組各為1000人，共追蹤6年，並得到此在未有設限狀態下之機率性成本效益分析之結果。繼而模擬存在某一設限機率下的資料，並以Direct (Lin)法與逆加權估計量法(inverse probability weighting, IPW)去校正設限狀態下的成本與效益的估計，效益面指標則分別以未考慮生活品質之存活人年及考慮生活品質之品質校正後存活人年，分別進行機率性成本效益分析，以付費意願(Willingness to pay) 10,000美元為閾值的情況下，看其成本效益接受曲線(cost-effectiveness acceptability curve, CEAC)去評估介入組相對於對照組具有成本效益的機率。 結果：(1)馬可夫決策模型的模擬結果，以品質校正後存活人年為效益指標時，介入組相對於控制組之ICER為$3000/品質人年(95$-12,000~$14,000)；增加淨效益(incremental net benefit; INB)為$2,729 (95% CI: -$1,003~$1,1634)；介入組具成本效益的機率為88.4%。(2)若考慮存在設限情況下，以Direct (Lin)與IPW所估計的成本，都比未考慮設限資料存在或沒有設限資料存在的直接估計值來的高。存活人年的增加成本效益比（incremental cost-effectiveness ratio; ICER）估計，以Direct (Lin)和IPW分別為$9,310/人年 (90$4402~$13,322)和$6,987/人年(90% CI: $937~$11,646)；品質校正後存活人年的ICER，以Direct (Lin)和IPW估計，分別為$12,885/品質人年 (90$5,808~$19,132)和$8,955/品質人年(90% CI: $1,066~$1,6319); 以IPW估計下，效益指標以存活人年和品質校正後存活人年來看時，介入組具有成本效益的機率分別為85%和59%; 若以Direct (Lin)估計下，以存活人年為效益指標時，介入組具有成本效益的機率為60.5%，以平均品質校正存活人年為效益指標時則為24%。 結論：透過阿茲海默症疫苗的成本效益分析，本論文示範如何利用馬可夫決策模式配合Direct (Lin)與IPW考慮設限資料下，如何解決未考慮設限資料存在而直接估計時，所造成的低估現象。Background: Alzheimer’s disease (AD) is a degenerative chronic disease, also the most common form of dementia. Although some current medications may delay the progression, it is not possible cure for AD. In 1990s, studies on immunotherapy for AD have been published. Since then, more immunotherapies with a clinical trial design entered the different stages. However, no economic valuation for the cost-effectiveness of immunotherapy for AD was performed. Vaccination against AD is illustrated to this study. However, the censored data are a common feature in clinical trials. If we ignore the censored problem, bias of estimation would occur because the cost and efficacy still accumulate after censoring. Additionally, the complicated Markov model would be applied to different status of disease nature course. Finally, the relationships between costs and effectiveness are often ignored. Therefore, this thesis used the cost-effectiveness analysis of vaccination for Alzheimer’s disease as an example to illustrate the methods how to resolve above problems. Methods: We used a Markov cost-effectiveness model to construct the nature course of AD. The micro-simulation was used to create a hypothetical cohort. The transition probabilities were extracted from previous Taiwanese studies. The treatment group is the participants with the uptake of vaccination and the control group is those without vaccination. The duration of follow-up is 6 years and each group consists of 1000 participants. First, the cost and effectiveness were measured without considering censoring data. Furthermore, they were measured by Direct (Lin) and Inverse probability weighting (IPW) to make allowance for censoring data. The outcome of interests included person years and quality-adjusted life year (QALY). Given the threshold of $10,000 of willingness-to-pay (WTP), we evaluate the probability of being cost-effectiveness for the treatment group by cost-effectiveness acceptability curve (CEAC). Results: (1) Without considering censored data, probabilistic analysis showed ICER was$3000 per QALY (95% CI: $-12,000~$14,000); INB was $2,729 (95$-1,003~11,634). Given the threshold of $10,000 of WTP, the probability of being cost-effective for the treatment group versus the control was 88.4$9,310 per person-year (90% CI: $4,402~$13,322) estimated by Direct (Lin) and $6,987 per person year (90$937~$11,646) estimated by IPW, respectively. The ICER of mean quality-adjusted survival time was$12,885 per QALY (90% CI: $5,808~$19,132) and $8,955 per QALY (90$1,066~16319) by Direct (Lin) or IPW, respectively. The mean survival time and QALY for AD were not cost-effective given the threshold of $10,000 of WTP. Given the threshold of$10,000 of WTP, the probability of being cost-effective for the treatment group were 85% and 59% in terms of mean survival time and QALY, respectively, by IPW estimation. The corresponding figures were 60.5% and 24% in terms of mean survival time and QALY, respectively, by Direct (Lin) estimation. Conclusions: By using Direct (Lin), IPW methods and Markov decision model, we demonstrated adjusting for censoring could adjust for censoring lead to downward estimation using an illustration of vaccination against AD

Child Growth Curves in High-Altitude Ladakh: Results from a Cohort Study

High prevalence of child underweight and stunting in high-altitude areas has often been reported. However, most previous studies on this topic were cross-sectional. Another critical concern is that using the World Health Organization (WHO) Child Growth Standards to evaluate child growth in high-altitude areas may lead to overestimations of underweight and stunting. Our study aimed to evaluate the long-term growth pattern of children (3 to 18 years) above the altitude of 3500 m in Ladakh, India. The participants&rsquo; body weight (BW), body height (BH), and body mass index (BMI) were measured annually according to the WHO Child Growth Standards for children under 5 years old and the WHO reference data for children aged 5 to 19 years. The generalized estimating equation (GEE) was used to estimate the means and z-scores of BW, BH, and BMI at different ages. A total of 401 children were enrolled from 2012 to 2018. Their mean z-scores of BW, BH, and BMI were &minus;1.47, &minus;1.44, and &minus;0.85 in 2012 and increased to &minus;0.74, &minus;0.92, and &minus;0.63 in 2018. This population&rsquo;s specific growth curve was also depicted, which generally fell below the 85th percentile of the WHO standards. This is the first cohort study about long-term child growth patterns in a high-altitude area. The detailed underlying mechanisms of our findings need future research on more representative data of high-altitude populations

Gender Differences with Dose–Response Relationship between Serum Selenium Levels and Metabolic Syndrome—A Case-Control Study

Few studies have investigated the association between selenium and metabolic syndrome. This study aimed to explore the associations between the serum selenium level and metabolic syndrome as well as examining each metabolic factor. In this case-control study, the participants were 1165 adults aged &#8805;40 (65.8 &#177; 10.0) years. Serum selenium was measured by inductively coupled plasma-mass spectrometry. The associations between serum selenium and metabolic syndrome were examined by multivariate logistic regression analyses. The least square means were computed by general linear models to compare the serum selenium levels in relation to the number of metabolic factors. The mean serum selenium concentration was 96.34 &#177; 25.90 &#956;g/L, and it was positively correlated with waist circumference, systolic blood pressure, triglycerides, fasting glucose, and homeostatic model assessment insulin resistance (HOMA-IR) in women, but it was only correlated with fasting glucose and HOMA-IR in men. After adjustment, the odds ratios (ORs) of having metabolic syndrome increased with the selenium quartile groups (p for trend: &lt;0.05), especially in women. The study demonstrated that the serum selenium levels were positively associated with metabolic syndrome following a non-linear dose&#8315;response trend. Selenium concentration was positively associated with insulin resistance in men and women, but it was associated with adiposity and lipid metabolism in women. The mechanism behind this warrants further confirmation

The Association between Total Protein and Vegetable Protein Intake and Low Muscle Mass among the Community-Dwelling Elderly Population in Northern Taiwan

Sarcopenia, highly linked with fall, frailty, and disease burden, is an emerging problem in aging society. Higher protein intake has been suggested to maintain nitrogen balance. Our objective was to investigate whether pre-sarcopenia status was associated with lower protein intake. A total of 327 community-dwelling elderly people were recruited for a cross-sectional study. We adopted the multivariate nutrient density model to identify associations between low muscle mass and dietary protein intake. The general linear regression models were applied to estimate skeletal muscle mass index across the quartiles of total protein and vegetable protein density. Participants with diets in the lowest quartile of total protein density (&lt;13.2%) were at a higher risk for low muscle mass (odds ratio (OR) 3.03, 95% confidence interval (CI) 1.37–6.72) than those with diets in the highest quartile (≥17.2%). Similarly, participants with diets in the lowest quartile of vegetable protein density (&lt;5.8%) were at a higher risk for low muscle mass (OR 2.34, 95% CI 1.14–4.83) than those with diets in the highest quartile (≥9.4%). Furthermore, the estimated skeletal muscle mass index increased significantly across the quartiles of total protein density (p = 0.023) and vegetable protein density (p = 0.025). Increasing daily intakes of total protein and vegetable protein densities appears to confer protection against pre-sarcopenia status

Estimating global burden of COVID-19 with disability-adjusted life years and value of statistical life metrics

Background: Global burden of COVID-19 has not been well studied, disability-adjusted life years (DALYs) and value of statistical life (VSL) metrics were therefore proposed to quantify its impacts on health and economic loss globally. Methods: The life expectancy, cases, and death numbers of COVID-19 until 30th April 2021 were retrieved from open data to derive the epidemiological profiles and DALYs (including years of life lost (YLL) and years loss due to disability (YLD)) by four periods. The VSL estimates were estimated by using hedonic wage method (HWM) and contingent valuation method (CVM). The estimate of willingness to pay using CVM was based on the meta-regression mixed model. Machine learning method was used for classification. Results: Globally, DALYs (in thousands) due to COVID-19 was tallied as 31,930 from Period I to IV. YLL dominated over YLD. The estimates of VSL were US$591 billion and US$5135 billion based on HWM and CVM, respectively. The estimate of VSL increased from US$579 billion in Period I to US$2160 billion in Period IV using CVM. The higher the human development index (HDI), the higher the value of DALYs and VSL. However, there exits the disparity even at the same level of HDI. Machine learning analysis categorized eight patterns of global burden of COVID-19 with a large variation from US$0.001 billion to US$691.4 billion. Conclusion: Global burden of COVID-19 pandemic resulted in substantial health and value of life loss particularly in developed economies. Classifications of such health and economic loss is informative to early preparation of adequate resource to reduce impacts

Review of epidemic, containment strategies, clinical management, and economic evaluation of COVID-19 pandemic

The spread of the emerging pathogen, named as SARS-CoV-2, has led to an unprecedented COVID-19 pandemic since 1918 influenza pandemic. This review first sheds light on the similarity on global transmission, surges of pandemics, and the disparity of prevention between two pandemics. Such a brief comparison also provides an insight into the potential sequelae of COVID-19 based on the inference drawn from the fact that a cascade of successive influenza pandemic occurred after 1918 and also the previous experience on the epidemic of SARS and MERS occurring in 2003 and 2015, respectively. We then propose a systematic framework for elucidating emerging infectious disease (EID) such as COVID-19 with a panorama viewpoint from natural infection and disease process, public health interventions (non-pharmaceutical interventions (NPIs) and vaccine), clinical treatments and therapies (antivirals), until global aspects of health and economic loss, and economic evaluation of interventions with emphasis on mass vaccination. This review not only concisely delves for evidence-based scientific literatures from the origin of outbreak, the spread of SARS-CoV-2 to three surges of pandemic, and NPIs and vaccine uptakes but also provides a new insight into how to apply big data analytics to identify unprecedented discoveries through COVID-19 pandemic scenario embracing from biomedical to economic viewpoints