The global diabetes burden continues to rise and disproportionately impacts low- and middle-income countries (LMICs) (Guariguata et al., 2014; International Diabetes Federation, 2020). In South Asia, approximately 90 million adults have diabetes, representing over 16% of total diabetes cases worldwide (International Diabetes Federation, 2020). Patients with diabetes in Asia and the Middle East only achieve recommended diabetes care targets (i.e., glycemia, blood pressure, cholesterol) less than 10% of the time (Anjana et al., 2021; Anjana et al., 2022; Shivashankar et al., 2015). As such, there is a need to address implementation gaps regarding diabetes care practices in these regions of the world.
Efforts to improve diabetes care in South Asia have demonstrated the effectiveness of national training programs (Department of Endocrinology Diabetes and Metabolism, 2011; World Diabetes Foundation, 2009) and multi-component diabetes care models (Ali et al., 2020; Shah et al., 2020; Bhurji et al., 2016; Kowalski et al., 2017; Misra et al., 2018; Ali et al., 2016; Shal et al., 2012). The determinants for sustaining these programs, however, remain unclear. With numerous identified health system-level challenges to developing and managing diabetes care models in LMICs (Karachaliou et al., 2020), further research is needed that examines how organizational characteristics can shape the implementation and sustainment of these care models.
In the originally published version of the article, the name of the 12th author was given as Venkat K. M. Narayan and is now changed to K. M. Venkat Narayan. Furthermore, in the authors’ contributions section, the initials VKMN are now changed to KMVN. The mentioned changes are corrected also online.
Introduction: Several interventions have been found to be effective for reversing prediabetes in adults. This systematic review and meta-analysis aims to compare the effectiveness of such interventions. Methods: MEDLINE, Embase, and Cochrane Library databases were searched for articles published between January 1, 2000 and June 27, 2018. RCTs in adults with prediabetes, testing nonsurgical interventions lasting for ≥3 months, and reporting the number of participants achieving normal glucose levels at intervention end were eligible. The pooled risk difference and number needed to treat for achieving normoglycemia were estimated using a random-effects, arm-based network meta-analysis. The strength of the evidence was assessed using Grading of Recommendations Assessment, Development, and Evaluation. Data were obtained in 2018 and analyzed in 2019 and 2021. Results: Of 54 studies included in the systematic review, 47 were meta-analyzed (n=26,460, mean age=53 years, 46% male, 31% White). Studies included 27 arms testing lifestyle modification interventions, 25 testing medications, 5 testing dietary supplements, and 10 testing Chinese medicine. There were 35 control/placebo arms. At a median follow-up of 1.6 years, more participants in the lifestyle modification groups achieved normoglycemia than those in the control (risk difference=0.18, number needed to treat=6). The strength of the evidence was strong for lifestyle modification. Over a median follow-up of 2.7 years, more participants receiving glucagon-like peptide-1 receptor agonists (risk difference=0.47, number needed to treat=2), α-glucosidase inhibitors (risk difference=0.29, number needed to treat=4), and insulin sensitizers (risk difference=0.23, number needed to treat=4) achieved normoglycemia than control. The strength of evidence was moderate for these medications. Discussion: Although several pharmacological approaches can reverse prediabetes, lifestyle modification provides the strongest evidence of effectiveness and should remain the recommended approach to address this condition.
Individuals with non-communicable diseases (NCDs) such as diabetes are susceptible to communicable diseases (CDs) as the current COVID-19 pandemic illustrates. The co-occurrence of diabetes as well as other co-morbid conditions with COVID-19 augurs greater risk for severe outcomes and mortality. Hence, NCD and CD pandemics are closely linked and require global efforts to thwart and disrupt their nexus before the next viral outbreaks occurs. This will require steadfast dedication and resolve to address NCDs previously committed to by the global community.
OBJECTIVE-To examine β-cell function across a spectrum of glycemia among Asian Indians, a population experiencing type 2 diabetes development at young ages despite low BMI. RESEARCH DESIGN AND METHODS-One-thousand two-hundred sixty-four individuals without known diabetes in the Diabetes Community Lifestyle Improvement Program in Chennai, India, had a 75-g oral glucose tolerance test,with glucose and insulinmeasured at 0, 30, and 120 min. Type 2 diabetes, isolated impaired fasting glucose (iIFG), isolated impaired glucose tolerance (iIGT), combined impaired fasting glucose and impaired glucose tolerance, and normal glucose tolerance (NGT) were defined by American Diabetes Association guidelines. Measures included insulin resistance and sensitivity (homeostasis model assessment of insulin resistance [HOMA-IR], modified Matsuda Index, 1/fasting insulin) and β-cell function (oral disposition index = [Δinsulin0-30/Δglucose0-30] × [1/fasting insulin]). RESULTS-Mean age was 44.2 years (SD, 9.3) and BMI 27.4 kg/m 2 (SD, 3.8); 341 individuals had NGT, 672 had iIFG, IGT, or IFG plus IGT, and 251 had diabetes. Patterns of insulin resistance or sensitivity were similar across glycemic categories. With mild dysglycemia, the absolute differences in age- and sex-adjusted oral disposition index (NGT vs. iIFG, 38%; NGT vs. iIGT, 32%) were greater than the differences in HOMA-IR (NGT vs. iIFG, 25%; NGT vs. iIGT, 23%; each P < 0.0001). Compared with NGT and adjusted for age, sex, BMI, waist circumference, and family history, the odds of mild dysglycemia were more significant per SD of oral disposition index (iIFG: odds ratio [OR], 0.36; 95% CI, 0.23-0.55; iIGT: OR, 0.37; 95% CI, 0.24-0.56) than per SD of HOMA-IR (iIFG: OR, 1.69; 95% CI, 1.23-2.33; iIGT: OR, 1.53; 95% CI, 1.11-2.11). CONCLUSIONS-Asian Indians with mild dysglycemia have reduced β-cell function, regardless of age, adiposity, insulin sensitivity, or family history. Strategies in diabetes prevention should minimize loss of β-cell function.
Background:
Diabetes is an important contributor to global morbidity and mortality. The contributions of population aging and macroeconomic changes to the growth in diabetes prevalence over the past 20 years are unclear.
Methods: We used cross-sectional data on age- and sex-specific counts of people with diabetes by country, national population estimates, and country-specific macroeconomic variables for the years 1990, 2000, and 2008. Decomposition analysis was performed to quantify the contribution of population aging to the change in global diabetes prevalence between 1990 and 2008. Next, age-standardization was used to estimate the contribution of age composition to differences in diabetes prevalence between high-income (HIC) and low-to-middle-income countries (LMICs). Finally, we used non-parametric correlation and multivariate first-difference regression estimates to examine the relationship between macroeconomic changes and the change in diabetes prevalence between 1990 and 2008.
Results: Globally, diabetes prevalence grew by two percentage points between 1990 (7.4 %) and 2008 (9.4 %). Population aging was responsible for 19 % of the growth, with 81 % attributable to increases in the age-specific prevalences. In both LMICs and HICs, about half the growth in age-specific prevalences was from increasing levels of diabetes between ages 45-65 (51 % in HICs and 46 % in LMICs). After age-standardization, the difference in the prevalence of diabetes between LMICs and HICs was larger (1.9 % point difference in 1990; 1.5 % point difference in 2008). We found no evidence that macroeconomic changes were associated with the growth in diabetes prevalence.
Conclusions: Population aging explains a minority of the recent growth in global diabetes prevalence. The increase in global diabetes between 1990 and 2008 was primarily due to an increase in the prevalence of diabetes at ages 45-65. We do not find evidence that basic indicators of economic growth, development, globalization, or urbanization were related to rising levels of diabetes between 1990 and 2008.
by
Spencer L. James;
Chris D. Castle;
Zachary Dingels;
Jack T. Fox;
Erin B. Hamilton;
Zichen Liu;
Nicholas L. S. Roberts;
Dillon O. Sylte;
Nathaniel J. Henry;
Kate E. LeGrand;
Michael Phillips;
Jae Shin;
Kabayam Venkat Narayan
Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
Aims: Type 2 diabetes is a heterogeneous disease and may manifest from multiple disease pathways. We examined insulin secretion and insulin resistance across two ethnicities with particularly high risk for diabetes yet with widely different distributions of weight class. Materials and Methods: In this population-based, cross-sectional study, Pima Indians from Southwestern United States (n = 865) and Asian Indians from Chennai, India (n = 2374) had a 75-g oral glucose tolerance test. We analysed differences in plasma glucose, plasma insulin, insulin resistance (HOMA-IR), and insulin secretion (ΔI0-30/ΔG0-30) across categories of body mass index (BMI) and glycemic status per American Diabetes Association criteria. Results: Pima Indians were younger (mean 27.4 ± SD 6.6, Asian: 33.9 ± 6.7 years) and had higher BMI (33.6 ± 8.1, Asian: 25.7 ± 4.9 kg/m2). Among normal weight participants (mean BMI: Pima 22.4 SE 0.2; Asian 22.2 SE 0.06 kg/m2), fasting glucose was higher in Asian Indians (5.2 vs Pima: 4.8 mmol/L, P =.003), adjusted for age and sex. Pima Indians were three times as insulin resistant as Asian Indians (HOMA-IR: 7.7 SE 0.1, Asian: 2.5 SE 0.07), while Asian Indians had three times less insulin secretion (Pima: 2.8 SE 1.0 vs Asian: 0.9 SE 1.0 pmol/mmol), a pattern evident across age, BMI, and glycemic strata. Conclusions: Metabolic differences between Pima and Asian Indians suggest heterogeneous pathways of type 2 diabetes in the early natural history of disease, with emphasis of insulin resistance in Pima Indians and emphasis of poor insulin secretion in Asian Indians.
Introduction:
Strong evidence shows lifestyle change and weight loss stimulated by counseling improve glycemic control and lower comorbidities for patients with diabetes, but it is unclear whether diet or physical activity counseling for patients with diabetes in ambulatory settings has actually been responsive to this evidence.
Methods:
Data from the 2005–2015 National Ambulatory Medical Care Surveys were used to assess trends in provider-reported diet or exercise counseling during ambulatory care visits. The data were pooled and multivariate logistic regression models were built, adjusting for patient-, provider-, and practice-level characteristics to examine whether the provision of counseling varied by these characteristics. Data were analyzed from September 2018 to December 2018.
Results:
There were 42,234 adults with diabetes and 272,094 adults without diabetes. The proportions of patients with provider-reported Type 2 diabetes who received any diet or exercise counseling were no different over time: 30% in 2005 (95% CI=25%, 35%) and 25% in 2015 (95% CI=18%, 31%). Lower proportions of those without diabetes received any counseling: 17% in 2005 (95% CI=14%, 19%) and 15% in 2015 (95% CI=11%, 18%). Adjusted models showed Hispanic patients had a higher likelihood of receiving diet or exercise counseling, compared with whites (OR=1.38, 95% CI=1.09, 1.75). Those aged 30–49 years were more likely to receive diet or exercise counseling, compared with those aged >75 years (OR=1.51, 95% CI=1.27, 1.80). Compared with rural areas and other providers, visits in a metropolitan area (OR=1.27, 95% CI=1.09, 1.47) or with an advanced practice provider (OR=1.66, 95% CI=1.00, 2.75) had higher likelihood of any diet or exercise counseling delivery.
Conclusions:
Less than 30% of Americans with diabetes receive diet or exercise counseling in ambulatory visits and this proportion has not changed significantly in a decade. Future interventions should focus on addressing this gap in counseling.