Renal function as an effect modifier of intensive glucose control in delaying cognitive function decline among individuals with type 2 diabetes: A revisit to the ACCORD MIND trial.

AIM: Dysglycaemia accelerates cognitive decline. Intensive glucose control may help delay or prevent cognitive function decline (CFD). We aimed to determine how patient characteristics influence the effect of intensive glucose control [glycated haemoglobin (HbA1c) <6.0%] on delaying CFD in people with type 2 diabetes. RESEARCH DESIGN AND METHODS: In this post-hoc analysis of 2977 type 2 diabetes participants from the ACCORD MIND trial, we applied the causal forest and causal tree algorithms to identify the effect modifier of intensive glucose control in delaying CFD from 68 variables (demographics, disease history, medications, vitals and baseline biomarkers). The exposure was intensive versus standard glucose control (HbA1c <6.0% vs. 7.0%-7.9%). The main outcome was cognitive function changes from baseline to the 40th month follow-up, which were evaluated using the digit symbol substitution test, Rey auditory verbal learning test, mini-mental state examination and Stroop test. We used Cohen's d, a measure of standardized difference, to quantify the effect size of intensive glucose control on delaying CFD. RESULTS: Among all the baseline characteristics, renal function was the most significant effect modifier. Participants with urinary albumin levels <0.4 mg/dl [absolute function change (AFC): 0.51 in mini-mental state examination, 95% confidence interval (CI): 0.04, 0.98, Cohen's d: 0.25] had slower CFD with intensive glucose control. Patients with preserved renal function (estimated glomerular filtration rate between 60 and 90 ml/min/1.73 m2) were associated with small benefits (AFC: 1.28 in Stroop, 95% CI: 0.28, 2.27, Cohen's d: 0.12) when undergoing intensive glucose control. Conversely, participants with an estimated glomerular filtration rate <60 ml/min/1.73 m2 (AFC: -0.57 in the Rey auditory verbal learning test, 95% CI: -1.09, -0.05, Cohen's d: -0.30) exhibited faster CFD when undergoing intensive glucose control. Participants who were <60 years old showed a significant benefit from intensive glucose control in delaying CFD (AFC: 1.08 in the digit symbol substitution test, 95% CI: 0.06, 2.10, Cohen's d: 0.13). All p < .05. CONCLUSIONS: Our findings linked renal function with the benefits of intensive glucose control in delaying CFD, informing personalized HbA1c goals for those with diabetes and at risk of CFD.

Effect of a multicomponent quality improvement strategy on sustained achievement of diabetes care goals and macrovascular and microvascular complications in South Asia at 6.5 years follow-up: Post hoc analyses of the CARRS randomized clinical trial.

BACKGROUND: Diabetes control is poor globally and leads to burdensome microvascular and macrovascular complications. We aimed to assess post hoc between-group differences in sustained risk factor control and macrovascular and microvascular endpoints at 6.5 years in the Center for cArdiovascular Risk Reduction in South Asia (CARRS) randomized trial. METHODS AND FINDINGS: This parallel group individual randomized clinical trial was performed at 10 outpatient diabetes clinics in India and Pakistan from January 2011 through September 2019. A total of 1,146 patients with poorly controlled type 2 diabetes (HbA1c ≥8% and systolic BP ≥140 mm Hg and/or LDL-cholesterol ≥130 mg/dL) were randomized to a multicomponent quality improvement (QI) strategy (trained nonphysician care coordinator to facilitate care for patients and clinical decision support system for physicians) or usual care. At 2.5 years, compared to usual care, those receiving the QI strategy were significantly more likely to achieve multiple risk factor control. Six clinics continued, while 4 clinics discontinued implementing the QI strategy for an additional 4-year follow-up (overall median 6.5 years follow-up). In this post hoc analysis, using intention-to-treat, we examined between-group differences in multiple risk factor control (HbA1c <7% plus BP <130/80 mm Hg and/or LDL-cholesterol <100 mg/dL) and first macrovascular endpoints (nonfatal myocardial infarction, nonfatal stroke, death, revascularization [angioplasty or coronary artery bypass graft]), which were co-primary outcomes. We also examined secondary outcomes, namely, single risk factor control, first microvascular endpoints (retinopathy, nephropathy, neuropathy), and composite first macrovascular plus microvascular events (which also included amputation and all-cause mortality) by treatment group and whether QI strategy implementation was continued over 6.5 years. At 6.5 years, assessment data were available for 854 participants (74.5%; n = 417 [intervention]; n = 437 [usual care]). In terms of sociodemographic and clinical characteristics, participants in the intervention and usual care groups were similar and participants at sites that continued were no different to participants at sites that discontinued intervention implementation. Patients in the intervention arm were more likely to exhibit sustained multiple risk factor control than usual care (relative risk: 1.77; 95% confidence interval [CI], 1.45, 2.16), p < 0.001. Cumulatively, there were 233 (40.5%) first microvascular and macrovascular events in intervention and 274 (48.0%) in usual care patients (absolute risk reduction: 7.5% [95% CI: -13.2, -1.7], p = 0.01; hazard ratio [HR] = 0.72 [95% CI: 0.61, 0.86]), p < 0.001. Patients in the intervention arm experienced lower incidence of first microvascular endpoints (HR = 0.68 [95% CI: 0.56, 0.83), p < 0.001, but there was no evidence of between-group differences in first macrovascular events. Beneficial effects on microvascular and composite vascular outcomes were observed in sites that continued, but not sites that discontinued the intervention. CONCLUSIONS: In urban South Asian clinics, a multicomponent QI strategy led to sustained multiple risk factor control and between-group differences in microvascular, but not macrovascular, endpoints. Between-group reductions in vascular outcomes at 6.5 years were observed only at sites that continued the QI intervention, suggesting that practice change needs to be maintained for better population health of people with diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT01212328.

Association between low cognitive performance and diabetes-related health indicators across racial and ethnic groups in adults with diabetes.

AIM: To examine the associations between low cognitive performance (LCP) and diabetes-related health indicators (including body mass index [BMI], HbA1c, systolic blood pressure [SBP], low-density lipoprotein [LDL] and self-reported poor physical health) and whether these associations vary across racial/ethnic subgroups. METHODS: We identified adults aged 60 years or older with self-reported diabetes from the 2011-2014 National Health and Nutrition Examination Survey. Individuals with cognitive test scores in the lowest quartile were defined as having LCP. We used regression models to measure the associations of LCP with diabetes-related biometrics (BMI, HbA1c, SBP and LDL); and self-reported poor physical health. Moreover, we explored potential variations in these associations across racial/ethnic subgroups. RESULTS: Of 873 (261 with LCP) adults with diabetes, LCP was associated with higher HbA1c, SBP and LDL (adjusted difference: 0.41%, 5.01 mmHg and 5.08 mg/dL, respectively; P < .05), and greater odds of reporting poor physical health (adjusted odds ratio: 1.59, P < .05). The association between LCP and HbA1c was consistent across racial/ethnic groups, and notably pronounced in Hispanic and Other. BMI worsened with LCP, except for non-Hispanic Black. Excluding the Other group, elevated SBP was observed in people with LCP, with Hispanic showing the most significant association. LDL levels were elevated with LCP for Hispanic and Other. Physical health worsened with LCP for both non-Hispanic Black and Hispanic. CONCLUSIONS: We quantified the association between LCP and diabetes-related health indicators. These associations were more pronounced in Hispanic and Other racial/ethnic groups.

Where and what separates rural from urban hospital closures?

Despite the recent closure of several high-profile metropolitan hospitals, investigations into risk factors for metropolitan hospital closures have been limited. The goal of this study was to describe metropolitan hospitals that closed and compare them to metropolitan hospitals that remain open and micropolitan and rural hospitals that closed using American Hospital Association Annual Survey Data from 2010 to 2021. We independently verified hospitals reported as closed in the Annual Survey and examined the hospital characteristics associated with closure using bivariate statistics and logistic regression. We found that metropolitan hospitals that closed (n = 142) were more likely to be for-profit (66.9% vs. 29.7%, p < .0001; adjusted odds ratio [AOR]: 3.05, 95% confidence interval [CI]: 1.93, 4.81) and to come from a state that did not expand Medicaid (45.1% vs. 29.4%, p < .0001; AOR: 1.66, 95% CI: 1.16, 2.38). Policies tailored to metropolitan hospitals should be developed to identify at-risk hospitals and mitigate the effect of closures on patients, clinicians, and other stakeholders.

Advancing diabetes surveillance ecosystems: a case study of India.

Professional society and expert guidelines recommend the achievement of glycaemic, blood pressure, and cholesterol targets to prevent the microvascular and macrovascular complications of diabetes. The WHO Diabetes Compact recommends that countries meet and monitor these targets for diabetes management. Surveillance-ie, continuous, systematic measurement, analysis, and interpretation of data-is a crucial component of public health. In this Personal View, we use the case of India as an illustration of the challenges and future directions needed for a diabetes surveillance system that documents national progress and persistent gaps. To address the growing burdens of diabetes and cardiometabolic diseases, the Government of India has launched programmes such as the National Programme for Prevention and Control of Non-Communicable Diseases. Different surveys have provided estimates of the diabetes care continuum of awareness, treatment, and control at the national, state, and, very recently, district level. We reviewed the literature to analyse how these surveys have varied in both their data collection methods and the reported estimates of the diabetes care continuum. We propose an integrated surveillance and monitoring framework to augment decentralised decision making, leveraging the complementary strengths of different surveys and electronic health record databases, such as data obtained by the National Programme for Prevention and Control of Non-Communicable Diseases, and building on methodological advances in model-based small-area estimation and data fusion. Such a framework could aid state and district administrators in monitoring the progress of diabetes screening and management initiatives, and benchmarking against national and global standards in all countries.

Care fragmentation and readmission mortality and length of stay before and during the COVID-19 pandemic: data from the National Readmissions Database, 2018-2020.

IMPORTANCE: A quarter of all 30-day readmissions involve fragmented care, where patients return to a different hospital than their original admission; these readmissions are associated with increased in-hospital mortality and longer lengths-of-stay (LOS). The stress on healthcare systems at the beginning of the COVID-19 pandemic could worsen care fragmentation and related outcomes. OBJECTIVE: To compare fragmented readmissions in 2020 versus 2018-2019 and assess whether mortality and LOS in fragmented readmissions differed in the two time periods. DESIGN: Observational study SETTING: National Readmissions Database (NRD), 2018-2020 PARTICIPANTS: All adults (> 18 y/o) with 30-day readmissions MAIN OUTCOMES AND MEASURES: We examined the percentage of fragmented readmissions over 2018-2020. Using unadjusted and adjusted logistic and linear regressions, we estimated the associations between fragmented readmissions and in-hospital mortality and LOS. RESULTS: 24.0-25.7% of readmissions in 2018-2020 and 27.3%-31.0% of readmissions for COVID-19 were fragmented. 2018-2019 fragmented readmissions were associated with 18-20% higher odds of in-hospital mortality compared to nonfragmented readmissions. Fragmented readmissions for COVID-19 were associated with an 18% increase in in-hospital mortality (AOR 1.18, 95% CI 1.12, 1.24). The LOS of fragmented readmissions in March-November 2018-2019 were on average 0.81 days longer, while fragmented readmissions between March-November of 2020 were associated with a 0.88-1.03 day longer LOS. CONCLUSIONS AND RELEVANCE: A key limitation is that the NRD does not contain information on several patient/hospital-level factors that may be associated with the outcomes of interest. We observed increased fragmentation during COVID-19, but its impact on in-hospital mortality and LOS remained consistent with previous years.

Is Electronic Information Exchange Associated With Lower 30-Day Readmission Charges Among Medicare Beneficiaries?

OBJECTIVE: Fragmented readmissions, when admission and readmission occur at different hospitals, are associated with increased charges compared with nonfragmented readmissions. We assessed if hospital participation in health information exchange (HIE) was associated with differences in total charges in fragmented readmissions. DATA SOURCE: Medicare Fee-for-Service Data, 2018. STUDY DESIGN: We used generalized linear models with hospital referral region and readmission month fixed effects to assess relationships between information sharing (same HIE, different HIEs, and no HIE available) and total charges of 30-day readmissions among fragmented readmissions; analyses were adjusted for patient-level clinical/demographic characteristics and hospital-level characteristics. DATA EXTRACTION METHODS: We included beneficiaries with a hospitalization for acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, syncope, urinary tract infection, dehydration, or behavioral issues with a 30-day readmission for any reason. PRINCIPAL FINDINGS: In all, 279,729 admission-readmission pairs were included, 27% of which were fragmented (n=75,438); average charges of fragmented readmissions were $64,897-$71,606. Compared with fragmented readmissions where no HIE was available, the average marginal effects of same-HIE and different-HIE admission-readmission pairs were -$2329.55 (95% CI: -7333.73, 2674.62) and -$3905.20 (95% CI: -7592.85, -307.54), respectively. While the average marginal effects of different-HIE pairs were lower than those for no-HIE fragmented readmissions, the average marginal effects of same-HIE and different-HIE pairs were not significantly different from each other. CONCLUSIONS: There were no statistical differences in charges between fragmented readmissions to hospitals that share an HIE or that do not share an HIE compared with hospitals with no HIE available.

Fragmented Readmissions From a Nursing Facility in Medicare Beneficiaries.

Over one-third of Medicare beneficiaries discharged to nursing facilities require readmission. When those readmissions are to a different hospital than the original admission, or "fragmented readmissions," they carry increased risks of mortality and subsequent readmissions. This study examines whether Medicare beneficiaries readmitted from a nursing facility are more likely to have a fragmented readmission than beneficiaries readmitted from home among a 2018 cohort of Medicare beneficiaries, and examined whether this association was affected by a diagnosis of Alzheimer's Disease (AD). In fully adjusted models, readmissions from a nursing facility were 19% more likely to be fragmented (AOR 1.19, 95% CI 1.16, 1.22); this association was not affected by a diagnosis of AD. These results suggest that readmission from nursing facilities may contribute to care fragmentation for older adults, underscoring it as a potentially modifiable pre-hospital risk factor for fragmented readmissions.

Diabetes Disparities in the United States: Trends by Educational Attainment from 2001 to 2020.

INTRODUCTION: Tracking changes in socioeconomic disparities in diabetes in the U.S. is important to evaluate progress in health equity and guide prevention efforts. Disparities in diabetes prevalence by educational attainment from 2001 to 2020 were investigated. METHODS: Using a serial cross-sectional design, data from 33,220 adults aged 30-79 assessed in nine rounds of the National Health and Nutrition Examination Surveys between 2001 and 2020 were analyzed in 2023-2024. Diabetes was defined as self-reported prior diagnosis, elevated glycated hemoglobin (HbA1c≥6.5%), or use of diabetes medications. Marginalized age- and covariate-adjusted prevalence differences (PD) and prevalence ratios (PR) of diabetes by educational attainment (less than high school graduation, high school graduation, some college education or associate degree, or college graduation [reference]) by calendar period (2001-2004, 2005-2008, 2009-2012, 2013-2016, 2017-2020) were derived from logistic regression models. RESULTS: From 2001 to 2020, age-adjusted diabetes prevalence was consistently higher among adults without a college degree. Adults without a high school diploma exhibited the largest disparities in both 2001-2004 (PD 8.0%; 95%CI 5.6-10.5 and PR 2.1; 95%CI 1.5-2.6) and 2017-20 (PD 11.0%; 95%CI 6.7-15.2 and PR 2.1; 95%CI 1.5-2.7). Between 2001-2004 and 2017-2020, the absolute disparity in diabetes changed only among adults with a high school diploma (increase from PD 1.7%; 95%CI -0.5- 3.9 to PD 8.8% 95%CI 4.1-13.4, respectively), while the PR did not change in any group. Education-related disparities in diabetes were attenuated after accounting for socio-demographic factors and BMI. CONCLUSIONS: From 2001 to 2020, national education-related disparities in diabetes prevalence have shown no signs of narrowing.

Access to essential medicines for diabetes care: availability, price, and affordability in central Ethiopia.

BACKGROUND: Diabetes is a major global public health burden. Effective diabetes management is highly dependent on the availability of affordable and quality-assured essential medicines (EMs) which is a challenge especially in low-and-middle-income countries such as Ethiopia. This study aimed to assess the accessibility of EMs used for diabetes care in central Ethiopia's public and private medicine outlets with respect to availability and affordability parameters. METHODS: A cross-sectional study was conducted in 60 selected public and private medicine outlets in central Ethiopia from January to February 2022 using the World Health Organization/Health Action International (WHO/HAI) standard tool to assess access to EMs. We included EMs that lower glucose, blood pressure, and cholesterol as these are all critical for diabetes care. Availability was determined as the percentage of surveyed outlets per sector in which the selected lowest-priced generic (LPG) and originator brand (OB) products were found. The number of days' wages required by the lowest paid government worker (LPGW) to purchase a one month's supply of medicines was used to measure affordability while median price was determined to assess patient price and price markup difference between public procurement and retail prices. RESULTS: Across all facilities, availability of LPG and OB medicines were 34.6% and 2.5% respectively. Only two glucose-lowering (glibenclamide 5 mg and metformin 500 mg) and two blood pressure-lowering medications (nifedipine 20 mg and hydrochlorothiazide 25 mg) surpassed the WHO's target of 80% availability. The median price based on the least measurable unit of LPG diabetes EMs was 1.6 ETB (0.033 USD) in public and 4.65 ETB (0.095 USD) in private outlets. The cost of one month's supply of diabetes EMs was equivalent to 0.3 to 3.1 days wages in public and 1.0 to 11.0 days wages in private outlets, respectively, for a typical LPGW. Thus, 58.8% and 84.6% of LPG diabetes EMs included in the price analysis were unaffordable in private and public outlets, respectively. CONCLUSIONS: There are big gaps in availability and affordability of EMs used for diabetes in central Ethiopia. Policy makers should work to improve access to diabetes EMs. It is recommended to increase government attention to availing affordable EMs for diabetes care including at the primary healthcare levels which are more accessible to the majority of the population. Similar studies are also recommended to be conducted in different parts of Ethiopia.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities.

Background: Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse. Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders. Results: The mean annual exposure in Chennai and Delhi was 40 and 102 µg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi. Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Determinants of health and mortality in undiagnosed diabetes: A nationally representative US adult, 2011-2020.

AIM: This study examines the determinants of health and mortality associated with undiagnosed diabetes among a nationally representative sample of US adults. METHODS: Data are from the National Health and Nutrition Examination Survey between 2011 and 2012 and 2019-2020. Diabetes status is categorized into three groups: undiagnosed diabetes, diagnosed diabetes, and no diabetes. Multiple logistic regression is used to estimate the association between undiagnosed diabetes and three domains of risk factors, including sociodemographic and health behavioral and clinical factors. Cox proportional hazards models are performed to compare excess mortality risk between the three groups. RESULTS: Young adults, racial minorities, the foreign-born, and individuals with limited access to health care are more likely to be unaware of their diabetes. Moreover, adults without a family history of diabetes and chronic conditions have a higher chance of undiagnosed diabetes. No health behavioral factors are found to be associated with undiagnosed diabetes. Adults with undiagnosed diabetes have a lower risk of all-cause and cardiovascular disease mortality compared to those with diagnosed diabetes, but a higher risk of all-cause mortality than those with no diabetes. CONCLUSION: Targeted public health approaches should address sociodemographic and clinical factors to reduce the burden of undiagnosed diabetes.

Natural History of Type 2 Diabetes in Indians: Time to Progression.

OBJECTIVE: To describe the natural history of diabetes in Indians. RESEARCH DESIGN AND METHODS: Data are from participants older than 20 years in the Centre for Cardiometabolic Risk Reduction in South Asia longitudinal study. Glycemic states were defined per American Diabetes Association criteria. Markov models were used to estimate annual transition probabilities and sojourn time through states. RESULTS: Among 2,714 diabetes-free participants, 641 had isolated impaired fasting glucose (iIFG), and 341 had impaired glucose tolerance (IGT). The annual transition to diabetes for those with IGT was 13.9% (95% CI 12.0, 15.9) versus 8.6% (7.3, 9.8) for iIFG. In the normoglycemia ↔ iIFG → diabetes model, mean sojourn time in normoglycemia was 40.3 (34.6, 48.2) years, and sojourn time in iIFG was 9.7 (8.4, 11.4) years. For the normoglycemia ↔ IGT → diabetes model, mean sojourn time in normoglycemia was 34.5 (29.5, 40.8) years, and sojourn time in IGT was 6.1 (5.3, 7.1) years. CONCLUSIONS: Individuals reside in normoglycemia for 35-40 years; however, progression from prediabetes to diabetes is rapid.

Multiple cardiovascular risk factor care in 55 low- and middle-income countries: A cross-sectional analysis of nationally-representative, individual-level data from 280,783 adults.

The prevalence of multiple age-related cardiovascular disease (CVD) risk factors is high among individuals living in low- and middle-income countries. We described receipt of healthcare services for and management of hypertension and diabetes among individuals living with these conditions using individual-level data from 55 nationally representative population-based surveys (2009-2019) with measured blood pressure (BP) and diabetes biomarker. We restricted our analysis to non-pregnant individuals aged 40-69 years and defined three mutually exclusive groups (i.e., hypertension only, diabetes only, and both hypertension-diabetes) to compare individuals living with concurrent hypertension and diabetes to individuals with each condition separately. We included 90,086 individuals who lived with hypertension only, 11,975 with diabetes only, and 16,228 with hypertension-diabetes. We estimated the percentage of individuals who were aware of their diagnosis, used pharmacological therapy, or achieved appropriate hypertension and diabetes management. A greater percentage of individuals with hypertension-diabetes were fully diagnosed (64.1% [95% CI: 61.8-66.4]) than those with hypertension only (47.4% [45.3-49.6]) or diabetes only (46.7% [44.1-49.2]). Among the hypertension-diabetes group, pharmacological treatment was higher for individual conditions (38.3% [95% CI: 34.8-41.8] using antihypertensive and 42.3% [95% CI: 39.4-45.2] using glucose-lowering medications) than for both conditions jointly (24.6% [95% CI: 22.1-27.2]).The percentage of individuals achieving appropriate management was highest in the hypertension group (17.6% [16.4-18.8]), followed by diabetes (13.3% [10.7-15.8]) and hypertension-diabetes (6.6% [5.4-7.8]) groups. Although health systems in LMICs are reaching a larger share of individuals living with both hypertension and diabetes than those living with just one of these conditions, only seven percent achieved both BP and blood glucose treatment targets. Implementation of cost-effective population-level interventions that shift clinical care paradigm from disease-specific to comprehensive CVD care are urgently needed for all three groups, especially for those with multiple CVD risk factors.

Body mass index changes and their association with SARS-CoV-2 infection: a real-world analysis.

Objective: To study body mass index (BMI) changes among individuals aged 18-99 years with and without SARS-CoV-2 infection. Subjects/Methods: Using real-world data from the OneFlorida+ Clinical Research Network of the National Patient-Centered Clinical Research Network, we compared changes over time in BMI in an Exposed cohort (positive SARS-CoV-2 test between March 2020 - January 2022), to a contemporary Unexposed cohort (negative SARS-CoV-2 tests), and an age/sex-matched Historical control cohort (March 2018 - January 2020). Body mass index (kg/m2) was retrieved from objective measures of height and weight in electronic health records. We used target trial approaches to estimate BMI at baseline and change per 100 days of follow-up for Unexposed and Historical cohorts relative to the Exposed cohort by categories of sex, race-ethnicity, age, and hospitalization status. Results: The study sample consisted of 44,436 (Exposed cohort), 164,118 (Unexposed cohort), and 41,189 (Historical cohort). Cumulatively, 62% were women, 21.5% Non-Hispanic Black, 21.4% Hispanic and 5.6% Non-Hispanic Other. Patients had an average age of 51.9 years (SD: 18.9). At baseline, relative to the Exposed cohort (mean BMI: 29.3 kg/m2 [95%CI: 29.0, 29.7]), the Unexposed (-0.07 kg/m2 [95%CI; -0.12, -0.01]) and Historical controls (-0.27 kg/m2 [95%CI; -0.34, -0.20]) had lower BMI. Relative to no change in the Exposed over 100 days (0.00 kg/m2 [95%CI; -0.03,0.03]), the BMI of those Unexposed decreased (-0.04 kg/m2 [95%CI; -0.06, -0.01]) while the Historical cohort's BMI increased (+0.03 kg/m2 [95%CI;0.00,0.06]). BMI changes were consistent between Exposed and Unexposed cohorts for most population groups, except at start of follow-up period among Males and those 65 years or older, and in changes over 100 days among Males and Hispanics. Conclusions: In a diverse real-world cohort of adults, mean BMI of those with and without SARS-CoV2 infection varied in their trajectories. The mechanisms and implications of weight retention following SARS-CoV-2 infection remain unclear.

Access to telehealth and changes in diabetes care patterns during the pandemic: evidence from a large integrated health system in the Southeast USA.

INTRODUCTION: To examine the role of telehealth in diabetes care and management during versus pre-COVID-19 pandemic. RESEARCH DESIGN AND METHODS: We included adults (≥18 years) with prevalent diabetes as of January 1, 2018, and continuously enrolled at Kaiser Permanente Georgia through December 31, 2021 (n=22,854). We defined pre (2018-2019) and during COVID-19 (2020-2021) periods. Logistic generalized estimating equations (GEEs) assessed the within-subject change in adherence to seven annual routine care processes (blood pressure (BP), hemoglobin A1C (HbA1c), cholesterol, creatinine, urine-albumin-creatinine ratio (UACR), eye and foot examinations) pre versus during COVID-19 among telehealth users (ie, more than one telehealth visit per year per period) and non-telehealth users. Linear GEE compared mean laboratory measurements pre versus during COVID-19 by telehealth use. RESULTS: The proportion of telehealth users increased from 38.7% (2018-2019) to 91.5% (2020-2021). During (vs pre) the pandemic, adherence to all care processes declined in telehealth (range: 1.6% for foot examinations to 12.4% for BP) and non-telehealth users (range: 1.9% for foot examinations to 40.7% for BP). In telehealth users, average HbA1c (mean difference: 0.4% (95% CI 0.2% to 0.6%), systolic BP (1.62 mm Hg (1.44 to 1.81)), and creatinine (0.03 mg/dL (0.02 to 0.04)), worsened during (vs pre) COVID-19, while low density lipoprotein (LDL) cholesterol improved (-9.08 mg/dL (-9.77 to -8.39)). For UACR, odds of elevated risk of kidney disease increased by 48% (OR 1.48 (1.36-1.62)). Patterns were similar in non-telehealth users. CONCLUSIONS: Telehealth use increased during the pandemic and alleviated some of the observed declines in routine diabetes care and management.

Understanding Barriers and Facilitators to Integrated HIV and Hypertension Care in South Africa.

Background The burden of hypertension among people with HIV is high, particularly in low-and middle-income countries, yet gaps in hypertension screening and care in these settings persist. The objective of this study was to identify facilitators of and barriers to hypertension screening, treatment, and management among people with HIV seeking treatment in primary care clinics in Johannesburg, South Africa. Methods Using a cross-sectional study design, data were collected via interviews (n = 53) with people with HIV and hypertension and clinic managers and focus group discussions (n = 9) with clinic staff. A qualitative framework analysis approach guided by the Theoretical Domains Framework was used to identify and compare determinants of hypertension care across different stakeholder groups. Results Data from clinic staff and managers generated three themes characterizing facilitators of and barriers to the adoption and implementation of hypertension screening and treatment: 1) clinics have limited structural and operational capacity to support the implementation of integrated care models, 2) education and training on chronic care guidelines is inconsistent and often lacking across clinics, and 3) clinicians have the goal of enhancing chronic care within their clinics but first need to advocate for health system characteristics that will sustainably support integrated care. Patient data generated three themes characterizing existing facilitators of and barriers to clinic attendance and chronic disease self-management: 1) the threat of hypertension-related morbidity and mortality as a motivator for lifestyle change, 2) the emotional toll of clinic's logistical, staff, and resource challenges, and 3) hypertension self-management as a patchwork of informational and support sources. The main barriers to hypertension screening, treatment, and management were related to environmental resources and context (i.e., lack of enabling resources and siloed flow of clinic operations) the patients' knowledge and emotions (i.e., lack of awareness about hypertension risk, fear, and frustration). Clinical actors and patients differed in perceived need to prioritize HIV versus hypertension care. Conclusions The convergence of multi-stakeholder data regarding barriers to hypertension screening, treatment, and management highlight key areas for improvement, where tailored implementation strategies may address challenges recognized by each stakeholder group.

Association of pro-inflammatory cytokines, adipokines and hepatokine with incident diabetes in India: a nested case-control study within CARRS cohort.

AIMS: To study the association of pro-inflammatory markers with incident diabetes in India. METHODS: We did a nested case-control study within the CARRS (Centre for Ardiometabolic Risk Reduction in South Asia) cohort. Of the 5739 diabetes-free individuals at the baseline, 216 participants with incident diabetes and 432 age-, gender- and city-matched controls at 2-year follow-up were included. We measured high sensitive C-reactive protein (hsCRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 ( MCP-1), adiponectin, leptin and fetuin-A in the stored baseline blood samples. We did multivariate conditional logistic regression to estimate association of inflammatory markers (as quartiles) and incident diabetes. Covariates were baseline fasting plasma glucose (FPG) and lipids, body mass index (BMI), family history of diabetes, smoking and alcohol use. RESULTS: Baseline hsCRP and TNF-α were higher, and IL-6 and adiponectin were lower among cases vs. controls. In multivariate conditional logistic regression models, only quartile-3 (odds ratio [OR]: 2.96 [95% CI:1.39, 6.30]) and quartile-4 (OR: 2.58 [95% CI: 1.15, 5.79]) of TNF-α and quartile-4 of MCP-1 (OR: 2.55 [95% CI: 1.06, 6.16]) were positively associated with diabetes after adjusting for baseline FPG and BMI. These associations did not remain after adjusting for family history. High level (quartile-4) of IL-6 was negatively associated with diabetes after adjusting for all factors (OR: 0.18 [95% CI: 0.06, 0.55]). CONCLUSIONS: Higher TNF-α and MCP-1 levels and lower IL-6 were associated with higher risk of developing diabetes. Better understanding and potential methods of addressing these biomarkers, especially in relation to family history, are needed to address diabetes in South Asians.

Changes in Diabetes Care and Management Practices during the COVID-19 Pandemic.

Background: Evidence suggests diabetes management was negatively impacted early in the pandemic. However, the impact of the pandemic on key healthcare services for diabetes control and diabetes self-management practices is less known. We examined changes in diabetes care and management practices before and during the COVID-19 pandemic. Methods: Population-based data regarding 4 diabetes-related healthcare engagement and 4 self-management indicators were obtained from adults with diabetes surveyed in 19 US States and Washington DC through the Behavioral Risk Factor Surveillance System. Using logistic regression, we estimated changes in the prevalence of each indicator, overall and by sociodemographic subgroups, before (2019; n = 15,307) and during (2021; n = 13,994) the COVID-19 pandemic. Results: Between 2019 and 2021, the prevalence of biannual HbA1c tests reduced by 2.6 percentage points (pp, 95% CI :-4.8, -0.4), from 75.4-73.1%, and prevalence of annual eye exams fell by 4.0 pp (-6.2, -2.8), from 72.2-68.7%. The composite indicator of engagement with healthcare for diabetes control fell by 3.5 pp (-5.9, -1.1), from 44.9-41.9%. Reductions in engagement with healthcare were largely seen across sex, age, education, employment status, marital status, insurance status, and urbanicity; and were more pronounced among those aged 18-34 and the uninsured. Reductions in engagement with healthcare were seen in several states, with Delaware and Washington DC reporting the largest decrease. Of self-management behaviors, we only observed change in avoidance of smoking, an increase of 2.0 pp (0.4, 3.6) from 84.7-87.1%. Conclusions: The pandemic had mixed impacts on diabetes care and self-management. The findings suggest a deterioration of the uptake of evidence-based, preventive health services requiring laboratory services and clinical examination for diabetes control during the pandemic. On the other hand, smoking rates decreased, suggesting potential positive impacts of the pandemic on health behaviors in people with diabetes.