Background Structured lifestyle change education reduces the burden of cardiometabolic diseases such as diabetes. Delivery of these programs at worksites could overcome barriers to program adoption and improve program sustainability and reach; however, tailoring to the worksite setting is essential. Methods The Integrating Diabetes Prevention in Workplaces (INDIA-WORKS) study tested the implementation and effectiveness of a multi-level program for reducing cardiometabolic disease risk factors at 11 large and diverse worksites across India. Herein, we describe and classify program adaptations reported during in-depth interviews and focus group discussions with worksite managers, program staff, and peer educators involved in program delivery, and program participants and drop-outs. We used thematic analysis to identify key themes in the data and classified reported program adaptations using the FRAME classification system. Results Adaptations were led by worksite managers, peer educators, and program staff members. They occurred both pre- and during program implementation and were both planned (proactive) and unplanned (proactive and reactive). The most frequently reported adaptations to the individual-level intervention were curriculum changes to tailor lessons to the local context, make the program more appealing to the workers at the site, or add a wider variety of exercise options. Other content adaptations included improvements to the screening protocol, intervention scheduling, and outreach plans to tailor participant recruitment and retention to the sites. Environment-level content adaptations included expanding or leveraging healthy food and exercise options at the worksites. Challenges to adaptation included scheduling and worksite-level challenges. Participants discussed the need to continue adapting the program in the future to continue making it relevant for worksite settings and engaging for employees. Conclusion This study describes and classifies site-specific modifications to a structured lifestyle change education program with worksite-wide health improvements in India. This adds to the literature on implementation adaptation in general and worksite wellness in India, a country with a large and growing workforce with, or at risk of, serious cardiometabolic diseases. This information is key for program scale-up, dissemination, and implementation in other settings.

Background: No previous study has examined racial differences in recurrent acute myocardial infarction (AMI) in a community population. We aimed to examine racial differences in recurrent AMI risk, along with first AMI risk in a community population. Methods: The community surveillance of the Atherosclerosis Risk in Communities Study (2005–2014) included 470000 people 35–84 years old in 4 U.S. communities. Hospitalizations for recurrent and first AMI were identified from ICD-9-CM discharge codes. Poisson regression models were used to compare recurrent and first AMI risk ratios between Black and White residents. Results: Recurrent and first AMI risk per 1000 persons were 8.8 (95% CI, 8.3–9.2) and 20.7 (95 % CI, 20.0–21.4) in Black men, 6.8 (95% CI, 6.5–7.0) and 14.1 (95 % CI, 13.8–14.5) in White men, 5.3 (95% CI, 5.0–5.7) and 16.2 (95 % CI, 15.6–16.8) in Black women, and 3.1 (95% CI, 3.0–3.3) and 8.8 (95 % CI, 8.6–9.0) in White women, respectively. The age-adjusted risk ratios (RR) of recurrent AMI were higher in Black men vs. White men (RR, 1.58 95 % CI, 1.30–1.92) and Black women vs. White women (RR, 2.09 95 % CI, 1.64–2.66). The corresponding RRs were slightly lower for first AMI: Black men vs. White men, RR, 1.49 (95 % CI, 1.30–1.71) and Black women vs. White women, RR, 1.65 (95 % CI, 1.42–1.92) Conclusions: Large disparities exist by race for recurrent AMI risk in the community. The magnitude of disparities is stronger for recurrent events than for first events, and particularly among women.

Introduction The American Diabetes Association (ADA) recommends screening for prediabetes and diabetes (dysglycemia) starting at age 35, or younger than 35 years among adults with overweight or obesity and other risk factors. Diabetes risk differs by sex, race, and ethnicity, but performance of the recommendation in these sociodemographic subgroups is unknown. Methods Nationally representative data from the National Health and Nutrition Examination Surveys (2015-March 2020) were analyzed from 5,287 nonpregnant US adults without diagnosed diabetes. Screening eligibility was based on age, measured body mass index, and the presence of diabetes risk factors. Dysglycemia was defined by fasting plasma glucose ≥100mg/dL (≥5.6 mmol/L) or haemoglobin A1c ≥5.7% (≥39mmol/mol). The sensitivity, specificity, and predictive values of the ADA screening criteria were examined by sex, race, and ethnicity. Results An estimated 83.1% (95% CI=81.2-84.7) of US adults were eligible for screening according to the 2023 ADA recommendation. Overall, ADA’s screening criteria exhibited high sensitivity [95.0% (95% CI=92.7-96.6)] and low specificity [27.1% (95% CI=24.5-29.9)], which did not differ by race or ethnicity. Sensitivity was higher among women [97.8% (95% CI=96.6-98.6)] than men [92.4% (95% CI=88.3-95.1)]. Racial and ethnic differences in sensitivity and specificity among men were statistically significant (P=0.04 and P=0.02, respectively). Among women, guideline performance did not differ by race and ethnicity. Discussion The ADA screening criteria exhibited high sensitivity for all groups and was marginally higher in women than men. Racial and ethnic differences in guideline performance among men were small and unlikely to have a significant impact on health equity. Future research could examine adoption of this recommendation in practice and examine its effects on treatment and clinical outcomes by sex, race, and ethnicity.

Importance Hypertension is a major cause of morbidity and mortality worldwide. Previous efforts to characterize gaps in the hypertension care continuum—including diagnosis, treatment, and control—in India did not assess district-level variation. Local data are critical for planning, implementation, and monitoring efforts to curb the burden of hypertension. Objective To examine the hypertension care continuum in India among individuals aged 18 to 98 years. Design, Setting, and Participants The nationally representative Fifth National Family Health Survey study was conducted in 2 phases from June 17, 2019, to March 21, 2020, and from November 21, 2020, to April 30, 2021, among 1 895 297 individuals in 28 states, 8 union territories, and 707 districts of India. Exposures District and state of residence, urban classification, age (18-39, 40-64, and ≥65 years), sex, and household wealth quintile. Main Outcomes and Measures Hypertension was defined as a self-reported diagnosis or a newly measured blood pressure of 140/90 mm Hg or more. The proportion of individuals diagnosed (self-reported), the proportion of individuals treated among those diagnosed (self-reported medication use), and the proportion of individuals with blood pressure control among those treated (blood pressure <140/90 mm Hg [aged 18-79 years] or <150/90 mm Hg [aged ≥80 years]) were calculated based on national guidelines. Age-standardized estimates of treatment and control were also provided among the total with hypertension. To assess differences in the care continuum between or within states (ie, between districts), the variance was partitioned using generalized linear mixed models. Results Of the 1 691 036 adult respondents (52.6% women; mean [SD] age, 41.6 [16.5] years), 28.1% (95% CI, 27.9%-28.3%) had hypertension, of whom 36.9% (95% CI, 36.4%-37.3%) received a diagnosis. Among those who received a diagnosis, 44.7% (95% CI, 44.1%-45.3%) reported taking medication (corresponding to 17.7% [95% CI, 17.5%-17.9%] of the total with hypertension). Among those treated, 52.5% (95% CI, 51.7%-53.4%) had blood pressure control (corresponding to 8.5% [95% CI, 8.3%-8.6%] of the total with hypertension). There were substantial variations across districts in blood pressure diagnosis (range, 6.3%-77.5%), treatment (range, 8.7%-97.1%), and control (range, 2.7%-76.6%). Large proportions of the variation in hypertension diagnosis (94.7%), treatment (93.6%), and control (97.3%) were within states, not just between states. Conclusions and Relevance In this cross-sectional survey study of Indian adults, more than 1 in 4 people had hypertension, and of these, only 1 in 3 received a diagnosis, less than 1 in 5 were treated, and only 1 in 12 had blood pressure control. National mean values hide considerable state-level and district-level variation in the care continuum, suggesting the need for targeted, decentralized solutions to improve the hypertension care continuum in India.

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.

OBJECTIVE Diabetes prevalence is increasing rapidly in rural areas of low- and middle-income countries (LMICs), but there are limited data on the performance of health systems in delivering equitable and effective care to rural populations. We therefore assessed rural-urban differences in diabetes care and control in LMICs. RESEARCH DESIGN AND METHODS We pooled individual-level data from nationally representative health surveys in 42 countries. We used Poisson regression models to estimate age-adjusted differences in the proportion of individuals with diabetes in rural versus urban areas achieving performance measures for the diagnosis, treatment, and control of diabetes and associated cardiovascular risk factors. We examined differences across the pooled sample, by sex, and by country. RESULTS The pooled sample from 42 countries included 840,110 individuals (35,404 with diabetes). Compared with urban populations with diabetes, rural populations had ∼15–30% lower relative risk of achieving performance measures for diabetes diagnosis and treatment. Rural populations with diagnosed diabetes had a 14% (95% CI 5–22%) lower relative risk of glycemic control, 6% (95% CI −5 to 16%) lower relative risk of blood pressure control, and 23% (95% CI 2–39%) lower relative risk of cholesterol control. Rural women with diabetes had lower achievement of performance measures relating to control than urban women, whereas among men, differences were small. CONCLUSIONS Rural populations with diabetes experience substantial inequities in the achievement of diabetes performance measures in LMICs. Programs and policies aiming to strengthen global diabetes care must consider the unique challenges experienced by rural populations.

Introduction: There is a dearth of data on common multimorbidity clusters and the healthcare costs for individuals with mental health disorders. This study aimed to identify clinically meaningful physical-mental multimorbidity clusters, frequently occurring clusters of conditions, and healthcare utilization patterns and expenditure among patients attending a psychiatric outpatient clinic. Materials and Methods: Data were collected in the psychiatric outpatient department among patients aged 18 years and above in February-July 2019 (n = 500); follow-up data on non-communicable disease incidence were collected after 18 months. For analysis, morbidity clusters were defined using two approaches: 1) agglomerative hierarchical clustering method to identify clusters of diseases; and 2) non-hierarchical cluster k mean analysis to identify clusters of patients. Self-reported healthcare costs in these clusters were also calculated. Result: Two disease clusters were identified: using the 1st approach were; 1) hypertension, diabetes, and mood disorder; 2) Neurotic, stress-related, and somatoform disorders, and acid peptic disease. Three clusters of patients identified using the 2nd approach were identified: 1) those with mood disorders and cardiometabolic, musculoskeletal, and thyroid diseases; 2) those with neurotic, substance use, and organic mental disorders, cancer, and epilepsy; and 3) those with Schizophrenia. Patients in Cluster 1 were taking more than six medicines and had more hospital visits. Within 18 months, 41 participants developed either one or two chronic conditions, most commonly diabetes, hypertension, or thyroid disease. Conclusion: Cardiometabolic diseases are most commonly clustered with mood disorders. There is a need for blood pressure and sugar measurement in psychiatric clinics and mood disorder screening in cardiac, endocrinology, and primary care clinics.

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: The impact of Medicaid expansion on linkage to care, self-maintenance, and treatment among low-income adults with diabetes was examined. Methods: A difference-in-differences design was used on data from the Behavioral Risk Factor Surveillance System, 2008–2018. Analysis was restricted to states with diabetes outcomes and nonpregnant adults aged 18–64 years who were Medicaid eligible on the basis of income. Separate analyses were performed for early postexpansion (1, 2, 3) and late postexpansion years (4, 5). Analyses were performed from September 2019 to March 2020. Results: In comparing expansion with control states, low-income residents with diabetes had similar ages (48.9 vs 49.1 years) and similar proportions who were female (54.4% vs 55.0%) but were less likely to be Black, non-Hispanic (20.8% vs 29.2%, standardized difference= −16.3%). In expansion states, health insurance increased by 7.2 percentage points (95% CI=3.9, 10.4), and the ability to afford a physician increased by 5.5 percentage points (95% CI=1.9, 9.1) in the early years, but no difference was found in late years. Medicaid expansion led to a 5.3-percentage point increase in provider foot examinations in the early period (95% CI=0.14, 10.4) and a 7.2-percentage point increase in self-foot examinations in the late period (95% CI=1.1, 13.3). No statistically significant changes were detected in self-reported linkage to care, self-maintenance, or treatment. Conclusions: Although health insurance, ability to afford a physician visit, and foot examinations increased for Medicaid-eligible people with diabetes, there was no statistically significant difference found for other care continuum measures.

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.