Prevalence of metabolic syndrome in a Russian population: The Ural Eye and Medical Study and the Ural Very Old Study

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Abstract

Purpose

To examine prevalence and associated factors of the metabolic syndrome (MS) in populations in Russia.

Methods

Two population-based studies (Ural Eye and Medical Study (UEMS), Ural Very Old Study (UVOS)) were conducted in rural and urban regions in Bashkortostan/Russia and included participants aged 40+ years and 85+ years, respectively.

Results

Out of 5895 UEMS participants, 1572 individuals had MS (prevalence:26.7%; 95% confidence interval (CI):25.5,27.8). The criteria of waist circumference, blood pressure, hyperglycemia, serum high-density lipoprotein concentration and serum triglyceride concentration were fulfilled by 4269 (72.4%; 95%CI:71.3,73.6), 3168 (53.7%; 95%CI:52.5,55.1), 1375 (23.3%; 95%CI:22.4,24.6), 712 (13.3%; 95%CI:12.4,14.2), and 1527 (28.6%; 95%CI:27.4,29.8) individuals, respectively. Higher MS prevalence was associated with older age (odds ratio (OR):1.03; 95%CI:1.02,1.04; P < 0.001), female sex (OR:1.93; 95%CI:1.51,2.47; P < 0.001), higher body height (OR:1.03; 95%CI:1.01,1.04; P < 0.001), Russian ethnicity (OR:1.38; 95%CI:1.13,1.70; P = 0.002), lower ankle-brachial index (OR:0.19; 95%CI:0.11,0.30; P < 0.001), higher prevalence of lower backache (OR:1.29; 95%CI:1.08,1.52; P = 0.004), cardiovascular disease (OR:2.32; 95%CI:1.92,2.78; P < 0.001) and thyroid disease (OR:1.41; 95%CI:1.04,1.92; P = 0.03), lower international normalized ratio (OR:0.55; 95%CI:0.32,0.95; P = 0.03), lower prevalence of current smoking (OR:0.67; 95%CI:0.50,0.89; P = 0.006), and higher prevalence of alcohol consumption (OR:1.35; 95%CI:1.11,1.64; P = 0.003). Out of 1124 UVOS participants (age:88.2 ± 2.7 years; range:85–100 years), MS was present in 485 individuals (prevalence:43.1%; 95%CI:40.3,46.1). The criteria of waist circumference, blood pressure, hyperglycemia, serum high-density lipoprotein concentration and serum triglyceride concentration were fulfilled by 853 (75.9%; 95%CI:73.4,78.4), 1057 (94.0%; 95%CI:92.7,95.4), 320 (26.9%; 95%CI:24.3,29.5), 525 (46.7%; 95%CI:43.8,49.6), and 337 (30.0%; 95%CI:27.3,32.7, individuals, respectively. Higher MS prevalence was associated with female sex (OR:2.30; 95%CI:1.72,3.09; P < 0.001) and higher serum concentration of aspartate transaminase (OR:1.02; 95%CI:1.01,1.03; P = 0.007).

Conclusions

MS is common in Russia, increases with age up to about 70 years and then plateaus, is more common in women, and differs in its associated factors between middle-aged and very old populations.

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Most cited references 24

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A new equation to estimate glomerular filtration rate.

Andrew Levey, Lesley Stevens, Christopher H Schmid … (2009)

Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.

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Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Christopher J L Murray, Aleksandr Y Aravkin, Peng Zheng … (2021)

Summary Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding Bill & Melinda Gates Foundation.

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Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity.

K Alberti, Robert H. Eckel, Scott M. Grundy … (2009)

A cluster of risk factors for cardiovascular disease and type 2 diabetes mellitus, which occur together more often than by chance alone, have become known as the metabolic syndrome. The risk factors include raised blood pressure, dyslipidemia (raised triglycerides and lowered high-density lipoprotein cholesterol), raised fasting glucose, and central obesity. Various diagnostic criteria have been proposed by different organizations over the past decade. Most recently, these have come from the International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute. The main difference concerns the measure for central obesity, with this being an obligatory component in the International Diabetes Federation definition, lower than in the American Heart Association/National Heart, Lung, and Blood Institute criteria, and ethnic specific. The present article represents the outcome of a meeting between several major organizations in an attempt to unify criteria. It was agreed that there should not be an obligatory component, but that waist measurement would continue to be a useful preliminary screening tool. Three abnormal findings out of 5 would qualify a person for the metabolic syndrome. A single set of cut points would be used for all components except waist circumference, for which further work is required. In the interim, national or regional cut points for waist circumference can be used.

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Author and article information

Contributors

Mukharram M. Bikbov

Jost B. Jonas

Journal

Journal ID (nlm-ta): Metabol Open

Journal ID (iso-abbrev): Metabol Open

Title: Metabolism Open

Publisher: Elsevier

ISSN (Electronic): 2589-9368

Publication date PMC-release: 07 April 2022

Publication date Collection: June 2022

Publication date (Electronic): 07 April 2022

Volume: 14

Electronic Location Identifier: 100183

Affiliations

[a ]Ufa Eye Research Institute, Ufa, Bashkortostan, Russia

[b ]Privatpraxis Prof Jonas und Dr Panda-Jonas, Heidelberg, Germany

[c ]Department of Ophthalmology, Medical Faculty Mannheim. Heidelberg University, Mannheim, Germany

[d ]Institute of Molecular and Clinical Ophthalmology Basel, Switzerland

Author notes

[∗ ]Corresponding author. Department of Ophthalmology, Medical Faculty Mannheim, Theodor-Kutzerufer 1, 68167, Mannheim, Germany. Jost.Jonas@ 123456medma.uni-heidelberg.de

[∗∗ ]Corresponding author. Ufa Eye Research Institute, 90 Pushkin Street, Ufa, 450077, Bashkortostan, Russia. Bikbov.m@ 123456gmail.com

Article

Publisher Item ID: S2589-9368(22)00021-4 Publisher ID: 100183

DOI: 10.1016/j.metop.2022.100183

PMC ID: 9006857

SO-VID: c982ab1b-d004-4ec8-9ffe-26963c6ec927

License:

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Prevalence of metabolic syndrome in a Russian population: The Ural Eye and Medical Study and the Ural Very Old Study

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Most cited references 24

A new equation to estimate glomerular filtration rate.

Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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