0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Unfavorable social determinants of health and risk of mortality in adults with diabetes: findings from the National Health Interview Survey

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction

          Understanding the role of social determinants of health as predictors of mortality in adults with diabetes may help improve health outcomes in this high-risk population. Using population-based, nationally representative data, this study investigated the cumulative effect of unfavorable social determinants on all-cause mortality in adults with diabetes.

          Research design and methods

          We used data from the 2013–2018 National Health Interview Survey, linked to the National Death Index through 2019, for mortality ascertainment. A total of 47 individual social determinants of health were used to categorize participants in quartiles denoting increasing levels of social disadvantage. Poisson regression was used to report age-adjusted mortality rates across increasing social burden. Multivariable Cox proportional hazards models were used to assess the association between cumulative social disadvantage and all-cause mortality in adults with diabetes, adjusting for traditional risk factors.

          Results

          The final sample comprised 182 445 adults, of whom 20 079 had diabetes. In the diabetes population, mortality rate increased from 1052.7 per 100 000 person-years in the first quartile (Q1) to 2073.1 in the fourth quartile (Q4). In multivariable models, individuals in Q4 experienced up to twofold higher mortality risk relative to those in Q1. This effect was observed similarly across gender and racial/ethnic subgroups, although with a relatively stronger association for non-Hispanic white participants compared with non-Hispanic black and Hispanic subpopulations.

          Conclusions

          Cumulative social disadvantage in individuals with diabetes is associated with over twofold higher risk of mortality, independent of established risk factors. Our findings call for action to screen for unfavorable social determinants and design novel interventions to mitigate the risk of mortality in this high-risk population.

          Related collections

          Most cited references29

          • Record: found
          • Abstract: found
          • Article: not found

          Obesity Phenotypes, Diabetes, and Cardiovascular Diseases

          This review addresses the interplay between obesity, type 2 diabetes mellitus, and cardiovascular diseases. It is proposed that obesity, generally defined by an excess of body fat causing prejudice to health, can no longer be evaluated solely by the body mass index (expressed in kg/m 2 ) because it represents a heterogeneous entity. For instance, several cardiometabolic imaging studies have shown that some individuals who have a normal weight or who are overweight are at high risk if they have an excess of visceral adipose tissue—a condition often accompanied by accumulation of fat in normally lean tissues (ectopic fat deposition in liver, heart, skeletal muscle, etc). On the other hand, individuals who are overweight or obese can nevertheless be at much lower risk than expected when faced with excess energy intake if they have the ability to expand their subcutaneous adipose tissue mass, particularly in the gluteal-femoral area. Hence, excessive amounts of visceral adipose tissue and of ectopic fat largely define the cardiovascular disease risk of overweight and moderate obesity. There is also a rapidly expanding subgroup of patients characterized by a high accumulation of body fat (severe obesity). Severe obesity is characterized by specific additional cardiovascular health issues that should receive attention. Because of the difficulties of normalizing body fat content in patients with severe obesity, more aggressive treatments have been studied in this subgroup of individuals such as obesity surgery, also referred to as metabolic surgery. On the basis of the above, we propose that we should refer to obesities rather than obesity.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Social Determinants of Health and Diabetes: A Scientific Review

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

              Summary Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Funding Bill & Melinda Gates Foundation.
                Bookmark

                Author and article information

                Journal
                BMJ Open Diabetes Res Care
                BMJ Open Diabetes Res Care
                bmjdrc
                bmjdrc
                BMJ Open Diabetes Research & Care
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2052-4897
                2024
                30 January 2024
                : 12
                : 1
                : e003710
                Affiliations
                [1 ]Ringgold_3989Baylor College of Medicine , Houston, Texas, USA
                [2 ]Ringgold_167626Houston Methodist Academic Institute , Houston, Texas, USA
                [3 ]Ringgold_585599Combined Military Hospital Lahore , Lahore, Pakistan
                [4 ]Houston Methodist DeBakey Heart and Vascular Center , Houston, Texas, USA
                [5 ]Ringgold_21697TJ Samson Community Hospital , Glasgow, Kentucky, USA
                [6 ]Ringgold_4270AT Still University Kirksville College of Osteopathic Medicine , Kirksville, Missouri, USA
                [7 ]George Washington University Milken Institute School of Public Health , Washington, DC, USA
                [8 ]departmentHealth Policy , Ringgold_4905The London School of Economics and Political Science , London, UK
                [9 ]departmentCenter for Cardiovascular Computational Health and Precision Medicine , Ringgold_23534Houston Methodist Hospital , Houston, Texas, USA
                [10 ]departmentDivision of Cardiovascular Prevention and Wellness , Ringgold_540131Houston Methodist DeBakey Heart and Vascular Center , Houston, Texas, USA
                Author notes
                [Correspondence to ] Ryan Chang; rchang2019@ 123456gmail.com
                Author information
                http://orcid.org/0000-0001-9707-5823
                http://orcid.org/0000-0002-7292-577X
                Article
                bmjdrc-2023-003710
                10.1136/bmjdrc-2023-003710
                10828867
                38290988
                f7e73977-d044-4a5b-9df4-347a371c5f79
                © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 18 August 2023
                : 23 December 2023
                Categories
                Epidemiology/Health services research
                1506
                1867
                Custom metadata
                unlocked

                mortality,diabetes mellitus, type 2,public health,vulnerable populations

                Comments

                Comment on this article