Probiotic and selenium co-supplementation, and the effects on clinical, metabolic and genetic status in Alzheimer's disease: A randomized, double-blind, controlled trial

Background and aims: Combined probiotic and selenium supplementation may improve Alzheimer's disease (AD) by correcting metabolic abnormalities, and attenuating inflammation and oxidative stress. This study aimed to determine the effects of probiotic and selenium co-supplementation on cognitive function and metabolic status among patients with AD. Methods: This randomized, double-blind, controlled clinical trial was conducted among 79 patients with AD. Patients were randomly assigned to receive either selenium (200 μg/day) plus probiotic containing Lactobacillus acidophilus, Bifidobacterium bifidum, and Bifidobacterium longum (2 � 109 CFU/day each) (n = 27), selenium (200 μg/day) (n = 26) or placebo (n = 26) for 12 weeks. Results: Selenium supplementation, compared with the placebo, significantly reduced serum high sensitivity C-reactive protein (hs-CRP) (P < 0.001), insulin (P = 0.001), homeostasis model of assessment-insulin resistance (HOMA-IR) (P = 0.002), LDL-cholesterol (P = 0.04) and total-/HDL-cholesterol ratio (P = 0.004), and significantly increased total glutathione (GSH) (P = 0.001) and the quantitative insulin sensitivity check index (QUICKI) (P = 0.01). Compared with only selenium and placebo, probiotic and selenium co-supplementation resulted in a significant increase in mini-mental state examination score (+1.5 ± 1.3 vs. +0.5 ± 1.2 and �0.2 ± 1.1, respectively, P < 0.001). Probiotic plus selenium intake resulted in a significant reduction in hs-CRP (�1.6 ± 1.4 vs. �0.8 ± 1.0 and +0.1 ± 0.5 mg/L, respectively, P < 0.001), and a significant increase in total antioxidant capacity (+89.4 ± 129.6 vs. +20.0 ± 62.5 and �0.7 ± 27.2 mmol/L, respectively, P = 0.001) and GSH (+122.8 ± 136.5 vs. +102.2 ± 135.2 and +1.5 ± 53.2 μmol/L, respectively, P = 0.001) compared with only selenium and placebo. In addition, subjects who received probiotic plus selenium supplements had significantly lower insulin levels (�2.1 ± 2.5 vs. �1.0 ± 1.3 and +0.7 ± 2.0 μIU/mL, respectively, P < 0.001), HOMA-IR (�0.5 ± 0.6 vs. �0.2 ± 0.3 and +0.1 ± 0.4, respectively, P < 0.001), and higher QUICKI (+0.01 ± 0.01 vs. +0.005 ± 0.007 and �0.002 ± 0.01, respectively, P < 0.006) compared with only selenium and placebo. Additionally, probiotic and selenium co-supplementation resulted in a significant reduction in serum triglycerides (�17.9 ± 26.1 vs. �3.5 ± 33.9 and +0.3 ± 9.3 mg/dL, respectively, P = 0.02), VLDL- (�3.6 ± 5.2 vs. �0.7 ± 6.8 and +0.05 ± 1.8 mg/dL, respectively, P = 0.02), LDL- (�8.8 ± 17.8 vs. �8.1 ± 19.2 and +2.7 ± 19.0 mg/dL, respectively, P = 0.04) and total-/HDL-cholesterol (�0.3 ± 0.7 vs. �0.4 ± 0.9 and +0.3 ± 0.6, respectively, P = 0.005) compared with only selenium and placebo. Conclusions: Overall, we found that probiotic and selenium co-supplementation for 12 weeks to patients with AD improved cognitive function and some metabolic profiles. This study was registered in the Iranian website (www.irct.ir) for registration of clinical trials (http://www.irct.ir: IRCT20170612034497N5). © 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolis

Probiotic and selenium co-supplementation, and the effects on clinical, metabolic and genetic status in Alzheimer's disease: A randomized, double-blind, controlled trial

Background and aims: Combined probiotic and selenium supplementation may improve Alzheimer's disease (AD) by correcting metabolic abnormalities, and attenuating inflammation and oxidative stress. This study aimed to determine the effects of probiotic and selenium co-supplementation on cognitive function and metabolic status among patients with AD. Methods: This randomized, double-blind, controlled clinical trial was conducted among 79 patients with AD. Patients were randomly assigned to receive either selenium (200 μg/day) plus probiotic containing Lactobacillus acidophilus, Bifidobacterium bifidum, and Bifidobacterium longum (2 × 109 CFU/day each) (n = 27), selenium (200 μg/day) (n = 26) or placebo (n = 26) for 12 weeks. Results: Selenium supplementation, compared with the placebo, significantly reduced serum high sensitivity C-reactive protein (hs-CRP) (P < 0.001), insulin (P = 0.001), homeostasis model of assessment-insulin resistance (HOMA-IR) (P = 0.002), LDL-cholesterol (P = 0.04) and total-/HDL-cholesterol ratio (P = 0.004), and significantly increased total glutathione (GSH) (P = 0.001) and the quantitative insulin sensitivity check index (QUICKI) (P = 0.01). Compared with only selenium and placebo, probiotic and selenium co-supplementation resulted in a significant increase in mini-mental state examination score (+1.5 ± 1.3 vs. +0.5 ± 1.2 and −0.2 ± 1.1, respectively, P < 0.001). Probiotic plus selenium intake resulted in a significant reduction in hs-CRP (−1.6 ± 1.4 vs. −0.8 ± 1.0 and +0.1 ± 0.5 mg/L, respectively, P < 0.001), and a significant increase in total antioxidant capacity (+89.4 ± 129.6 vs. +20.0 ± 62.5 and −0.7 ± 27.2 mmol/L, respectively, P = 0.001) and GSH (+122.8 ± 136.5 vs. +102.2 ± 135.2 and +1.5 ± 53.2 μmol/L, respectively, P = 0.001) compared with only selenium and placebo. In addition, subjects who received probiotic plus selenium supplements had significantly lower insulin levels (−2.1 ± 2.5 vs. −1.0 ± 1.3 and +0.7 ± 2.0 μIU/mL, respectively, P < 0.001), HOMA-IR (−0.5 ± 0.6 vs. −0.2 ± 0.3 and +0.1 ± 0.4, respectively, P < 0.001), and higher QUICKI (+0.01 ± 0.01 vs. +0.005 ± 0.007 and −0.002 ± 0.01, respectively, P < 0.006) compared with only selenium and placebo. Additionally, probiotic and selenium co-supplementation resulted in a significant reduction in serum triglycerides (−17.9 ± 26.1 vs. −3.5 ± 33.9 and +0.3 ± 9.3 mg/dL, respectively, P = 0.02), VLDL- (−3.6 ± 5.2 vs. −0.7 ± 6.8 and +0.05 ± 1.8 mg/dL, respectively, P = 0.02), LDL- (−8.8 ± 17.8 vs. −8.1 ± 19.2 and +2.7 ± 19.0 mg/dL, respectively, P = 0.04) and total-/HDL-cholesterol (−0.3 ± 0.7 vs. −0.4 ± 0.9 and +0.3 ± 0.6, respectively, P = 0.005) compared with only selenium and placebo. Conclusions: Overall, we found that probiotic and selenium co-supplementation for 12 weeks to patients with AD improved cognitive function and some metabolic profiles. This study was registered in the Iranian website (www.irct.ir) for registration of clinical trial

Probiotic and selenium co-supplementation, and the effects on clinical, metabolic and genetic status in Alzheimer's disease: A randomized, double-blind, controlled trial

Background and aims: Combined probiotic and selenium supplementation may improve Alzheimer's disease (AD) by correcting metabolic abnormalities, and attenuating inflammation and oxidative stress. This study aimed to determine the effects of probiotic and selenium co-supplementation on cognitive function and metabolic status among patients with AD. Methods: This randomized, double-blind, controlled clinical trial was conducted among 79 patients with AD. Patients were randomly assigned to receive either selenium (200 μg/day) plus probiotic containing Lactobacillus acidophilus, Bifidobacterium bifidum, and Bifidobacterium longum (2 � 109 CFU/day each) (n = 27), selenium (200 μg/day) (n = 26) or placebo (n = 26) for 12 weeks. Results: Selenium supplementation, compared with the placebo, significantly reduced serum high sensitivity C-reactive protein (hs-CRP) (P &lt; 0.001), insulin (P = 0.001), homeostasis model of assessment-insulin resistance (HOMA-IR) (P = 0.002), LDL-cholesterol (P = 0.04) and total-/HDL-cholesterol ratio (P = 0.004), and significantly increased total glutathione (GSH) (P = 0.001) and the quantitative insulin sensitivity check index (QUICKI) (P = 0.01). Compared with only selenium and placebo, probiotic and selenium co-supplementation resulted in a significant increase in mini-mental state examination score (+1.5 ± 1.3 vs. +0.5 ± 1.2 and �0.2 ± 1.1, respectively, P &lt; 0.001). Probiotic plus selenium intake resulted in a significant reduction in hs-CRP (�1.6 ± 1.4 vs. �0.8 ± 1.0 and +0.1 ± 0.5 mg/L, respectively, P &lt; 0.001), and a significant increase in total antioxidant capacity (+89.4 ± 129.6 vs. +20.0 ± 62.5 and �0.7 ± 27.2 mmol/L, respectively, P = 0.001) and GSH (+122.8 ± 136.5 vs. +102.2 ± 135.2 and +1.5 ± 53.2 μmol/L, respectively, P = 0.001) compared with only selenium and placebo. In addition, subjects who received probiotic plus selenium supplements had significantly lower insulin levels (�2.1 ± 2.5 vs. �1.0 ± 1.3 and +0.7 ± 2.0 μIU/mL, respectively, P &lt; 0.001), HOMA-IR (�0.5 ± 0.6 vs. �0.2 ± 0.3 and +0.1 ± 0.4, respectively, P &lt; 0.001), and higher QUICKI (+0.01 ± 0.01 vs. +0.005 ± 0.007 and �0.002 ± 0.01, respectively, P &lt; 0.006) compared with only selenium and placebo. Additionally, probiotic and selenium co-supplementation resulted in a significant reduction in serum triglycerides (�17.9 ± 26.1 vs. �3.5 ± 33.9 and +0.3 ± 9.3 mg/dL, respectively, P = 0.02), VLDL- (�3.6 ± 5.2 vs. �0.7 ± 6.8 and +0.05 ± 1.8 mg/dL, respectively, P = 0.02), LDL- (�8.8 ± 17.8 vs. �8.1 ± 19.2 and +2.7 ± 19.0 mg/dL, respectively, P = 0.04) and total-/HDL-cholesterol (�0.3 ± 0.7 vs. �0.4 ± 0.9 and +0.3 ± 0.6, respectively, P = 0.005) compared with only selenium and placebo. Conclusions: Overall, we found that probiotic and selenium co-supplementation for 12 weeks to patients with AD improved cognitive function and some metabolic profiles. This study was registered in the Iranian website (www.irct.ir) for registration of clinical trials (http://www.irct.ir: IRCT20170612034497N5). © 2018 Elsevier Ltd and European Society for Clinical Nutrition and Metabolis

Global mortality from dementia: Application of a newmethod and results from the global burden of disease study 2019

INTRODUCTION: Dementia is currently one of the leading causes of mortality globally, and mortality due to dementia will likely increase in the future along with corresponding increases in population growth and population aging. However, large inconsistencies in coding practices in vital registration systems over time and between countries complicate the estimation of global dementia mortality. METHODS: We meta-analyzed the excess risk of death in those with dementia and multiplied these estimates by the proportion of dementia deaths occurring in those with severe, end-stage disease to calculate the total number of deaths that could be attributed to dementia. RESULTS: We estimated that there were 1.62 million (95% uncertainty interval [UI]: 0.41–4.21) deaths globally due to dementia in 2019. More dementia deaths occurred in women (1.06 million [0.27–2.71]) than men (0.56 million [0.14–1.51]), largely but not entirely due to the higher life expectancy in women (age-standardized female-to-male ratio 1.19 [1.10–1.26]). Due to population aging, there was a large increase in all-age mortality rates from dementia between 1990 and 2019 (100.1% [89.1–117.5]). In 2019, deaths due to dementia ranked seventh globally in all ages and fourth among individuals 70 and older compared to deaths from other diseases estimated in the Global Burden of Disease (GBD) study. DISCUSSION: Mortality due to dementia represents a substantial global burden, and is expected to continue to grow into the future as an older, aging population expands globally

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Global mortality from dementia : Application of a new method and results from the Global Burden of Disease Study 2019

Introduction Dementia is currently one of the leading causes of mortality globally, and mortality due to dementia will likely increase in the future along with corresponding increases in population growth and population aging. However, large inconsistencies in coding practices in vital registration systems over time and between countries complicate the estimation of global dementia mortality. Methods We meta-analyzed the excess risk of death in those with dementia and multiplied these estimates by the proportion of dementia deaths occurring in those with severe, end-stage disease to calculate the total number of deaths that could be attributed to dementia. Results We estimated that there were 1.62 million (95% uncertainty interval [UI]: 0.41-4.21) deaths globally due to dementia in 2019. More dementia deaths occurred in women (1.06 million [0.27-2.71]) than men (0.56 million [0.14-1.51]), largely but not entirely due to the higher life expectancy in women (age-standardized female-to-male ratio 1.19 [1.10-1.26]). Due to population aging, there was a large increase in all-age mortality rates from dementia between 1990 and 2019 (100.1% [89.1-117.5]). In 2019, deaths due to dementia ranked seventh globally in all ages and fourth among individuals 70 and older compared to deaths from other diseases estimated in the Global Burden of Disease (GBD) study. Discussion Mortality due to dementia represents a substantial global burden, and is expected to continue to grow into the future as an older, aging population expands globally.Peer reviewe

Use of multidimensional item response theory methods for dementia prevalence prediction : an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. Conclusions Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000–18: a geospatial modelling study

Background: More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels. Methods: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution. Findings: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000–257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution. Interpretation: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Funding: Bill &amp; Melinda Gates Foundation

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background: Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods: Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (>= 65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0-100 based on the 2.5th and 97.5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target-1 billion more people benefiting from UHC by 2023-we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings: Globally, performance on the UHC effective coverage index improved from 45.8 (95% uncertainty interval 44.2-47.5) in 1990 to 60.3 (58.7-61.9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2.6% [1.9-3.3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010-2019 relative to 1990-2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0.79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388.9 million (358.6-421.3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3.1 billion (3.0-3.2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968.1 million [903.5-1040.3]) residing in south Asia. Interpretation: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people-the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close-or how far-all populations are in benefiting from UHC