METHODS: We searched online databases for all related papers through the comprehensive international data bases of Institute of PubMed/ MEDLINE, ISI/WOS and Scopus up to December 2019, using relevant keywords. Overall, 14 studies were included in this systematic review and meta-analysis.
RESULTS: The total sample size of all selected studies was 399,550 individuals with age range of 6 to ≥65 years old. We found a significant positive association between skipping breakfast and Odds Ratio (OR) of depression (pooled OR: 1.39; 95% CI: 1.34-1.44), stress (pooled OR: 1.23; 95% CI: 1.04-1.43) and psychological distress (pooled OR: 1.55; 95% CI: 1.47-1.62). In contrast, there was no significant association between skipping breakfast and anxiety in all age cohort (pooled OR: 1.31; 95% CI: 0.97-1.65). However, subgroup analysis based on age stratification showed that there was a significant positive association between skipping breakfast and anxiety in adolescences (pooled OR: 1.51; 95% CI: 1.25-1.77).
CONCLUSION: In conclusion, skipping breakfast was positively associated with odds of depression, stress and psychological distress in all age groups and anxiety in adolescence, underlining impact of breakfast on mental health.
Methods: In this systematic review, we systematically searched the international databases including PubMed, Web of Sciences, and Scopus for scientifically related papers which have been published up until January 2018. For a more refined search, we used the Medical Subject Headings (MeSH) terms and Emtree. In terms of search protocol, no restrictions were placed on time and language. Two independent reviewers conducted the data refining processes. Validated form (PRISMA) was used to conduct quality assessment and data extraction.
Results: Eight cross sectional studies have been included in this review. Two of the studies were conducted in Asia and the remaining six studies were largely based in the United States and Canada. Food insecurity was associated with low levels of vitamin and mineral intakes such as vitamins E, A, B, and D and also zinc, calcium, magnesium, and iron. Most studies also reported insufficient energy, and micro and macronutrients intake among elderly people.
Conclusions: The findings of this review evidence a considerable amount of food insecurity and nutrient deficiency, including vitamins E, C, D, B 2, and B 12 and zinc, phosphorus, and calcium among elderly population. These findings could be used as reliable evidence by policy makers and future complementary analyses.
METHODS: The systematic review and meta-analysis were performed according to the previously published protocol. The PubMed, Web of Sciences, and Scopus databases were meticulously searched for relevant data, without time or language restriction, up to June 1, 2017. All clinical trials which assessed the effect of Se supplementation on antioxidant markers, including oxidative stress index (OSI), antioxidant potency composite (APC) index, plasma malonaldehyde (MDA), total antioxidant capacity (TAC), antioxidant enzymes (superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT)), and total antioxidant plasma (TAP), were included. The effect of Se supplementation on antioxidant markers was assessed using standardized mean difference (SMD) and 95% confidence interval (CI). The random-effect meta-analysis method was used to estimate the pooled SMD.
RESULTS: In total, 13 studies which assessed the effect of Se supplementation on antioxidant markers were included. The random-effect meta-analysis method showed that Se supplementation significantly increased GPX (SMD = 0.54; 95% CI = 0.21-0.87) and TAC (SMD = 0.39, 95% CI = 0.13, 0.66) levels and decreased MDA levels (SMD = - 0.54, 95% CI = - 0.78, - 0.30). The effect of Se supplementation on other antioxidant markers was not statistically significant (P > 0.05).
CONCLUSION: The findings showed that Se supplementation might reduce oxidative stress by increasing TAC and GPX levels and decreasing serum MDA, both of which are crucial factors for reduction of oxidative stress.
Methods: To assess the effects of Se on the inflammatory markers, following the PRISMA-P guidelines, we systematically searched ISI/WOS, PubMed/MEDLINE, and Scopus for studies that assessed the effect of Se supplementation on the inflammatory markers. Data extraction was performed by two independent investigators. Using the random effects or fixed-effects model depending on the results of heterogeneity tests was used to estimate the pooled standardized mean difference (SMD). Heterogeneity between studies was assessed using Cochran's Q test and I2 index.
Results: The initial search revealed 3,320 papers. After screening process and considering inclusion criteria, 7 publications were eligible for inclusion in the meta-analysis. The meta-analysis results showed that Se supplementation did not significantly affect CRP and hs-CRP concentrations (mean difference (MD) = -0.15; 95% CI: -0.55- 0.23; P = 0.43). Subgroup analysis of CRP type showed that Se supplementation significantly decreased hs-CRP level (pooled SMD = -0.44; 95% CI: -0.67-0.21). Moreover, no significant change was observed in NO level by continuing to take Se supplementation, (pooled SMD: 0.003, 95%CI: -0.26, 0.26).
Conclusions: This study revealed that Se supplementation would have desirable effects on cardio-metabolic indicators through affecting the levels of inflammatory markers. Given the importance of concerns, more attention should be given to more prospective studies with longer follow-up.
METHODS: We systematically searched PubMed/MEDLINE, ISI/WOS, and Scopus (from their commencements up to Jan 2016) for relevant studies examining the association between intake of selenium and glycemic indices. The data were extracted from relevant qualified studies and estimated using the random-effect or pooled model and standardized mean difference (SMD) with 95% confidence interval (CI).
RESULTS: Twelve articles published between 2004 and 2016 were included. In all the studies, the participants were randomly assigned to an intervention group (n = 757) or a control group(n = 684). All the studies were double blind, placebo controlled trials. Selenium supplementation resulted in a significant decrease in homeostasis model of assessment-estimated β-cell function (HOMA-B) (SMD: -0.63; 95%CI: -0.89 to -0.38) and a significant increase in quantitative insulin sensitivity check index (QUICKI) (SMD: by 0.74; 95%CI: 0.49 to 0.1) as compared with the controls. There were no statistically significant improvements in glycemic indices, such as fasting plasma glucose (FPG), insulin, homeostasis model of assessment-estimated insulin resistance (HOMA-IR), Hemoglobin A1c (HbA1c) and adiponectin.
CONCLUSION: This meta-analysis indicated that selenium supplementation significantly decreased HOMA-B and increased QUICKI score. There was no statistically significant improvement in FPG, insulin, HOMA-IR, HbA1c and adiponectin indices following selenium supplementation.
Methods: A systematic search was conducted through PubMed/Medline, Institute of Scientific Information, and Scopus, until 2017 based on the search terms of metabolic syndrome (MetS) and cardio metabolic risk factors. Random-effect model was used to perform a meta-analysis and estimate the pooled SE, SP and correlation coefficient (CC).
Results: A total of 41 full texts were selected for systematic review. The pooled SE of greater NC to predict MetS was 65% (95% CI 58, 72) and 77% (95% CI 55, 99) in adult and children, respectively. Additionally, the pooled SP was 66% (95% CI 60, 72) and 66% (95% CI 48, 84) in adult and children, respectively. According to the results of meta-analysis in adults, NC had a positive and significant correlation with fasting blood sugar (FBS) (CC: 0.16, 95% CI 0.13, 0.20), HOMA-IR (0.38, 95% CI 0.25, 0.50), total cholesterol (TC) (0.07 95% CI 0.02, 0.12), triglyceride (TG) concentrations (0.23, 95% CI 0.19, 0.28) and low density lipoprotein cholesterol (LDL-C) (0.14, 95% CI 0.07, 0.22). Among children, NC was positively associated with FBS (CC: 0.12, 95% CI 0.07, 0.16), TG (CC: 0.21, 95% CI 0.17, 0.25), and TC concentrations (CC: 0.07, 95% CI 0.02, 0.12). However, it was not significant for LDL-C.
Conclusion: NC has a good predictive value to identify some cardiometabolic risk factors. There was a positive association between high NC and most cardiometabolic risk factors. However due to high heterogeneity, findings should be declared with caution.
METHODS: We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units.
RESULTS: We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group.
CONCLUSIONS: As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.
OBJECTIVE: To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.
EVIDENCE REVIEW: The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.
FINDINGS: In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.
CONCLUSIONS AND RELEVANCE: In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.
OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019.
EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs).
FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles.
CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.
OBJECTIVE: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning.
EVIDENCE REVIEW: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence.
FINDINGS: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs).
CONCLUSIONS AND RELEVANCE: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.