The Effect of City-Level Sugar-Sweetened Beverage Taxes on Longitudinal HbA1c and Incident Diabetes in Adults With Prediabetes.

OBJECTIVE: Prediabetes, which is a condition characterized by higher-than-normal blood glucose levels that are under the threshold for diabetes, impacts over one-third of U.S. adults. Excise taxes on sugar-sweetened beverages (SSBs) are a proposed policy intervention to lower population consumption of SSBs and generate revenue to support health-related programs, thus potentially delaying or preventing the development of diabetes in individuals with prediabetes. We leveraged data from Kaiser Permanente in California to examine the impact of SSB taxes in California on individual-level mean HbA1c levels and rates of incident diabetes. RESEARCH DESIGN AND METHODS: We compared two outcomes, mean HbA1c levels and rates of incident diabetes, among a matched cohort of adults with prediabetes who lived and did not live in SSB excise tax cities, using outcomes collected in the 6 years prior and 4 years following SSB tax implementation. We used multivariable linear mixed effects models to analyze longitudinal mean HbA1c and discrete-time survival models for incident diabetes. RESULTS: We included 68,658 adults in the analysis. In adjusted models, longitudinal mean HbA1c was 0.007% (95% CI 0.002, 0.011) higher in the tax cities compared with control individuals; while the estimated difference was statistically significant, it was not clinically significant (HbA1c <0.5%). There was no significant difference in the risk of incident diabetes between individuals living in tax and control cities. CONCLUSIONS: We found no clinically significant association between SSB taxes and either longitudinal mean HbA1c or incident diabetes among adults with prediabetes in the 4 years following SSB tax implementation.

Cost saving analysis of prediabetes intervention modalities in comparison with inaction using Markov state transition model-A multiregional case study.

BACKGROUND: Prediabetes management is a priority for policymakers globally, to avoid/delay type 2 diabetes (T2D) and reduce severe, costly health consequences. Countries moving from low to middle income are most at risk from the T2D "epidemic" and may find implementing preventative measures challenging; yet prevention has largely been evaluated in developed countries. METHODS: Markov cohort simulations explored costs and benefits of various prediabetes management approaches, expressed as "savings" to the public health care system, for three countries with high prediabetes prevalence and contrasting economic status (Poland, Saudi Arabia, Vietnam). Two scenarios were compared up to 15 y: "inaction" (no prediabetes intervention) and "intervention" with metformin extended release (ER), intensive lifestyle change (ILC), ILC with metformin (ER), or ILC with metformin (ER) "titration." RESULTS: T2D was the highest-cost health state at all time horizons due to resource use, and inaction produced the highest T2D costs, ranging from 9% to 34% of total health care resource costs. All interventions reduced T2D versus inaction, the most effective being ILC + metformin (ER) "titration" (39% reduction at 5 y). Metformin (ER) was the only strategy that produced net saving across the time horizon; however, relative total health care system costs of other interventions vs inaction declined over time up to 15 y. Viet Nam was most sensitive to cost and parameter changes via a one-way sensitivity analysis. CONCLUSIONS: Metformin (ER) and lifestyle interventions for prediabetes offer promise for reducing T2D incidence. Metformin (ER) could reduce T2D patient numbers and health care costs, given concerns regarding adherence in the context of funding/reimbursement challenges for lifestyle interventions.

Making prediabetes visible in primary health care: a qualitative study of health care professionals' perspectives.

BACKGROUND: People with prediabetes are at high risk of developing type 2 diabetes and its complications, such as cardiovascular diseases and premature mortality. Primary prevention and health maintenance are therefore imperative. Evidence has shown that prediabetes can be prevented or delayed with behavioural change, mainly in eating habits and physical activity. Interventions that use a person-centered approach can lead to improvements in self-management, quality of life, and health outcomes. Nevertheless, there is a need for further research that engages healthcare professionals and people with prediabetes in constructing and implementing preventive programs. The purpose of this study is to explore and describe how healthcare professionals perceive prediabetes, the current challenges in its detection and treatment, and what is needed to improve quality of care. METHODS: This qualitative study was conducted in Region Stockholm. A total of 26 primary health care professionals participated in individual interviews: 15 diabetes nurses and/or district nurses, five general practitioners, five dietitians, and one physiotherapist. Interview transcripts were analyzed with qualitative content analysis. RESULTS: The analysis revealed two main themes that emphasize the need to make prediabetes more visible in primary health care. Despite the healthcare professionals' engagement and their motivation to improve prediabetes care, ad hoc practices and the absence of clear screening guidelines and referral pathways made it harder to focus on primary prevention. Supporting professionals in implementing structured care for people with prediabetes might encourage more efficient interprofessional collaboration and contribute to better strategies for promoting behavioural change. CONCLUSIONS: Establishing prediabetes care guidelines, supporting health care professionals´ knowledge and skills in prediabetes care, and implementing interprofessional referral pathways are some steps to enhance prediabetes detection and care precedence in primary health care. These steps could lead to more preventive care and ensure patient safety and health care equity.

Clinical performance and health equity implications of the American Diabetes Association's 2023 screening recommendation for prediabetes and diabetes.

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.

Factors Influencing the Referral of Patients with Prediabetes to a Diabetes Prevention Program in the Bronx, New York.

INTRODUCTION: Disparate engagement in the Diabetes Prevention Program (DPP) may occur as early as the point of referral for certain subgroups, including Black and Hispanic men. We aimed to determine patient demographic and provider characteristics associated with referrals to a health system DPP in the Bronx, New York. METHODS: Patient and health system characteristics for DPP-eligible patients seen in primary care between July 1, 2015, and December 31, 2017, were obtained through the electronic health record. Generalized mixed-effects modeling was used to test the association between referral rate and clinical and sociodemographic variables. RESULTS: Of 26,727 eligible patients, 66% were female, 46% were Hispanic, and 39% were non-Hispanic Black. Only 10% (n = 2,785) of eligible patients were referred to DPP. In the adjusted analyses, lower odds of referral were observed for men versus women (OR = 0.60; 95% CI, 0.52-0.66), for non-Hispanic White versus Hispanic patients (OR = 0.53; 95% CI, 0.40-0.71), and for uninsured patients versus Medicaid patients (OR = 0.66; 95% CI, 0.54-0.80). The odds were higher for patients in the highest versus lowest hemoglobin A1c (OR = 2.49; 95% CI, 2.27-2.72) category; for those in the highest versus lowest body mass index categories (OR = 1.61; 95% CI, 1.45-1.79); for middle-aged patients (aged 45-64 y) versus those aged 18-26 y (OR =1.63; 95% CI, 1.33-2.00); and for patients being seen by a family versus an internal medicine physician (OR = 1.65; 95% CI, 1.22-2.22). CONCLUSION: We identified under-referral for men and highlighted other patient and health system factors associated with referral rates. Interventions to address bias in referrals and increase referrals for men at high risk for diabetes, not typically represented in DPP, are recommended.

Can Waist-to-Height Ratio and Health Literacy Be Used in Primary Care for Prioritizing Further Assessment of People at T2DM Risk?

BACKGROUND: To identify people at risk of type 2 diabetes. Primary health care needs efficient and noninvasive screening tools to detect individuals in need of follow-up to promote health and well-being. Previous research has shown people with lower levels of health literacy and/or well-being scores are vulnerable but may benefit from intervention and follow-up care. AIMS: This cross-sectional study, aimed to identify people at risk for type 2 diabetes by comparing the Finnish Diabetes Risk instrument with the waist-to-height ratio. Further, the difference was examined in health literacy and well-being scale scores in the countryside versus town areas, respectively. RESULTS: In total, 220, aged 18-75 years, participated. Thereof, 13.2% displayed biomarkers at prediabetes level of HbA1c (39-47 mmol/mol); none had undiagnosed diabetes. Of the participants, 73% were overweight or obese. Waist-to-height ratio demonstrated 93.1% of the prediabetes group at moderate to high health risk and 64.4% of the normal group, with an area under the curve of 0.759, sensitivity of 93.3%, and specificity of 63.1%. Residency did not influence prediabetes prevalence, health literacy, or well-being. CONCLUSION: Waist-to-height ratio and the Finnish Diabetes Risk instrument may be suitable for identifying who need further tests and follow-up care for health promotion in primary care.

Uptake, retention, and outcomes of the National Diabetes Prevention Program by enrollee characteristics and program type.

AIMS: To describe National Diabetes Prevention Program (NDPP) uptake, retention, and outcomes by enrollee characteristics and program type. METHODS: We studied 776 adult University of Michigan employees, dependents, and retirees with prediabetes and overweight or obesity who enrolled in one of four CDC-recognized NDPPs at no out-of-pocket cost. Programs included 1) an in-person classroom-based program led by certified diabetes educators in an endocrinology outpatient clinic; 2) an in-person classroom-based program led by trained peer instructors in community settings; 3) an in-person fitness-focused program led by trained lifestyle coaches; and 4) an online digital program led by personal health coaches with virtual group meetings. Data from the insurer and surveys were analyzed. RESULTS: Older individuals with hypertension and cardiovascular disease were more likely to enroll in classroom-based programs. Program time, location, and perceived focus on diet or physical activity influenced program selection. Retention, weight loss, and physical activity were greater among enrollees in in-person classroom-based programs. Changes in blood pressure, lipid levels, self-rated health, and health-related quality-of-life did not differ by program, nor did Type 2 diabetes mellitus incidence. CONCLUSIONS: Individuals with prediabetes who enrolled in a NDPP achieved health benefits regardless of the type of program they chose.

Nonalcoholic fatty liver disease (NAFLD) and associated mortality in individuals with type 2 diabetes, pre-diabetes, metabolically unhealthy, and metabolically healthy individuals in the United States.

BACKGROUND: The prevalence of nonalcoholic fatty liver disease (NAFLD) is high among subjects with type 2 diabetes (T2D). However, the prevalence and outcomes of NAFLD among individuals with pre-diabetes (PreD) and metabolically healthy and metabolically unhealthy individuals without T2D are not known. Our aim was to assess prevalence and mortality of NAFLD among these four groups. METHODS: The Third National Health and Nutrition Examination Survey (NHANES) III (1988-1994) with mortality data (follow up to 2019) via linkage to the National Death Index was utilized. NAFLD was defined by ultrasound and absence of other liver diseases and excess alcohol use. Pre-D was defined as fasting plasma glucose values of 100-125 mg/dL and/or HbA1c level between 5.7 %-6.4 % in the absence of established diagnosis of T2D. Metabolically healthy (MH) was defined if all of the following criteria were absent: waist circumference of ≥102 cm (men) or ≥ 88 cm (women) or BMI of ≥30; blood pressure (BP) ≥ 130/85 mmHg or using BP-lowering medication; triglyceride level ≥ 150 mg/dL or using lipid-lowering medication; lipoprotein cholesterol level of <40 mg/dL (men) or < 50 mg/dL (women); homeostasis model assessment of insulin resistance (HOMA-IR) score ≥ 2.5; C-reactive protein (CRP) level of >2 mg/L; Pre-D and T2D. Metabolically unhealthy (MU) individuals were defined as the presence of any component of metabolic syndrome but not having Pre-D and T2D. Competing risk analyses of cause-specific mortality were performed. FINDINGS: 11,231 adults (20-74y) were included: mean age 43.4 years; 43.9 % male; 75.4 % white, 10.8 % Black, and 5.4 % Mexican American, 18.9 % NAFLD, 7.8 % T2D; 24.7 % PreD; 44.3 % MU; and 23.3 % in MH individuals. In multivariable adjusted logistic model, as compared to MH individuals, the highest risk of having NAFLD were in T2D individuals (Odd Ratio [OR] = 10.88 [95 % confidence interval: 7.33-16.16]), followed by Pre-D (OR = 4.19 [3.02-5.81]), and MU (OR = 3.36 [2.39-4.71]). During a median follow up of 26.7 years (21.2-28.7 years), 3982 died. NAFLD subjects had significantly higher age-adjusted mortality than non-NAFLD (32.7 % vs. 28.7 %, p < .001). Among subjects with NAFLD, the highest age-standardized cumulative mortality was observed among those with T2D (41.3 %), followed by with Pre-D (35.1 %), MU subjects (30.0 %), and MH subjects (21.9 %) (pairwise p-values<.04 vs. MH). Multivariable adjusted cox models showed that NAFLD with T2D had a higher risk of all-causes and cardiac-specific deaths (Hazard Ratio [HR] = 4.71 [2.23-9.96] and HR = 20.01 [3.00-133.61]), followed by NAFLD with Pre-D (HR = 2.91 [1.41-6.02] and HR = 10.35 [1.57-68.08]) and metabolically unhealthy NAFLD (HR = 2.59 [1.26-5.33] and HR = 6.74 [0.99-46.03]) compared to metabolically healthy NAFLD. In addition to older age, independent predictors of mortality among NAFLD with T2D included high CRP, CVD, CKD, high FIB-4, and active smoking. Similarly, among NAFLD with PreD, high CRP, CKD, CVD, hypertension, and active smoking were associated with mortality. Finally, CVD and active smoking were predictors of mortality among metabolically unhealthy NAFLD, and active smoking was the only mortality risk among metabolically healthy NAFLD subjects. INTERPRETATION: Metabolic abnormality impacts both prevalence and outcomes of subjects with NAFLD.

Prevalence trends and disease burden of diabetes and prediabetes in Chinese adults of Shanghai.

BACKGROUND: To estimate secular trends and disease burden of diabetes and prediabetes among Chinese adults. METHODS: Three population-based surveys were performed among Chinese adults in Shanghai in 2002-2003 (n = 12 302), 2009 (n = 7414), and 2017 (n = 18 960). Diabetes and prediabetes were defined using the 1999 World Health Organization (WHO) criteria. Cochran-Armitage trend test was used to examine the trends in prevalence, awareness, and glycemic control status. Disability adjusted life years (DALYs) were estimated to evaluate the disease burden of diabetes-related complications using the population attribution fraction approach based on published data. RESULTS: The age-adjusted prevalence of diabetes increased during the 15-year period (p for trend <.001) and reached 23.0% (95% CI: 22.1 ~ 24.0%) in men and 15.7% (95% CI: 15.1 ~ 16.4%) among women in 2017. The prevalence of impaired glucose tolerance peaked in 2009, whereas that of impaired fasting glucose increased continuously (p for trend <.001). The awareness of diabetes was found to increase and the glycemic control rates decreased over the three surveys. The estimated DALYs of diabetes complications were found to have increased rapidly due to the increasing prevalence of diabetes and the decreasing glycemic control rates. CONCLUSIONS: Prediabetes and diabetes affect a considerable proportion of Chinese adults in Shanghai. Our results highlight the necessary to strengthen the community healthcare system in China to guarantee extensive management of diabetes and prediabetes.

Screening for Prediabetes and Diabetes: Clinical Performance and Implications for Health Equity.

INTRODUCTION: In 2021, the U.S. Preventive Services Task Force (USPSTF) recommended prediabetes and diabetes screening for asymptomatic adults aged 35-70 years with overweight/obesity, lowering the age from 40 years in its 2015 recommendation. The USPSTF suggested considering earlier screening in racial and ethnic groups with high diabetes risk at younger ages or lower BMI. This study examined the clinical performance of these USPSTF screening recommendations as well as alternative age and BMI cutoffs in the U.S. adult population overall, and separately by race and ethnicity. METHODS: Nationally representative data were collected from 3,243 nonpregnant adults without diagnosed diabetes in January 2017-March 2020 and analyzed from 2021 to 2022. Screening eligibility was based on age and measured BMI. Collectively, prediabetes and undiagnosed diabetes were defined by fasting plasma glucose ≥100 mg/dL or hemoglobin A1c ≥5.7%. The sensitivity, specificity, and predictive values of alternate screening criteria were examined overall, and by race and ethnicity. RESULTS: The 2021 criteria exhibited marginally higher sensitivity (58.6%, 95% CI=55.5, 61.6 vs 52.9%, 95% CI=49.7, 56.0) and lower specificity (69.3%, 95% CI=65.7, 72.2 vs 76.4%, 95% CI=73.3, 79.2) than the 2015 criteria overall, and within each racial and ethnic group. Screening at lower age and BMI thresholds resulted in even greater sensitivity and lower specificity, especially among Hispanic, non-Hispanic Black, and Asian adults. Screening all adults aged 35-70 years regardless of BMI yielded the most equitable performance across all racial and ethnic groups. CONCLUSIONS: The 2021 USPSTF screening criteria will identify more adults with prediabetes and diabetes in all racial and ethnic groups than the 2015 criteria. Screening all adults aged 35-70 years exhibited even higher sensitivity and performed most similarly by race and ethnicity, which may further improve early detection of prediabetes and diabetes in diverse populations.

Associations Between Preconception Glycemia and Preterm Birth: The Potential Role of Health Care Access and Utilization.

Background: Preconception diabetes is strongly associated with adverse birth outcomes. Less is known about the effects of elevated glycemia at levels below clinical cutoffs for diabetes. In this study, we estimated associations between preconception diabetes, prediabetes, and hemoglobin A1c (HbA1c) on the risk of preterm birth, and evaluated whether associations were modified by access to or utilization of health care services. Materials and Methods: We used data from Add Health, a US prospective cohort study with five study waves to date. At Wave IV (ages 24-32), glucose and HbA1c were measured. At Wave V (ages 32-42), women with a live birth reported whether the baby was born preterm. The analytic sample size was 1989. Results: The prevalence of preterm birth was 13%. Before pregnancy, 6.9% of women had diabetes, 23.7% had prediabetes, and 69.4% were normoglycemic. Compared to the normoglycemic group, women with diabetes had 2.1 (confidence interval [95% CI]: 1.5-2.9) times the risk of preterm birth, while women with prediabetes had 1.3 (95% CI: 1.0, 1.7) times the risk of preterm birth. There was a nonlinear relationship between HbA1c and preterm birth such that risk of preterm birth emerged after HbA1c = 5.7%, a standard cutoff for prediabetes. The excess risks of preterm birth associated with elevated HbA1c were four to five times larger among women who reported unstable health care coverage and among women who used the emergency room as usual source of care. Conclusion: Our findings replicate prior research showing strong associations between preconception diabetes and preterm birth, adding that prediabetes is also associated with higher risk. Policies and interventions to enhance access and utilization of health care among women before pregnancy should be examined.

Assessment of the effect of the COVID-19 pandemic on UK HbA1c testing: implications for diabetes management and diagnosis.

AIMS: The COVID-19 pandemic, and the focus on mitigating its effects, has disrupted diabetes healthcare services worldwide. We aimed to quantify the effect of the pandemic on diabetes diagnosis/management, using glycated haemoglobin (HbA1c) as surrogate, across six UK centres. METHODS: Using routinely collected laboratory data, we estimated the number of missed HbA1c tests for 'diagnostic'/'screening'/'management' purposes during the COVID-19 impact period (CIP; 23 March 2020 to 30 September 2020). We examined potential impact in terms of: (1) diabetes control in people with diabetes and (2) detection of new diabetes and prediabetes cases. RESULTS: In April 2020, HbA1c test numbers fell by ~80%. Overall, across six centres, 369 871 tests were missed during the 6.28 months of the CIP, equivalent to >6.6 million tests nationwide. We identified 79 131 missed 'monitoring' tests in people with diabetes. In those 28 564 people with suboptimal control, this delayed monitoring was associated with a 2-3 mmol/mol HbA1c increase. Overall, 149 455 'screening' and 141 285 'diagnostic' tests were also missed. Across the UK, our findings equate to 1.41 million missed/delayed diabetes monitoring tests (including 0.51 million in people with suboptimal control), 2.67 million screening tests in high-risk groups (0.48 million within the prediabetes range) and 2.52 million tests for diagnosis (0.21 million in the pre-diabetes range; ~70 000 in the diabetes range). CONCLUSIONS: Our findings illustrate the widespread collateral impact of implementing measures to mitigate the impact of COVID-19 in people with, or being investigated for, diabetes. For people with diabetes, missed tests will result in further deterioration in diabetes control, especially in those whose HbA1c levels are already high.

A simulation model estimates lifetime health and economic outcomes of screening prediabetes using the 1-h plasma glucose.

AIMS: The current method to diagnose impaired glucose tolerance (IGT) is based on the 2-h plasma glucose (2-hPG) value during a 75-g oral glucose tolerance test (OGTT). Robust evidence demonstrates that the 1-h post-load plasma glucose (1-hPG) ≥ 8.6 mmol/L in those with normal glucose tolerance is highly predictive of type 2 diabetes (T2D), micro and macrovascular complications and mortality. The aim of this study was to conduct a health economic analysis to estimate long-term cost-effectiveness of using the 1-hPG compared to the 2-hPG for screening and assessing the risk of diabetes over 35 years. The main outcome was cost per quality-adjusted life year (QALY) gained. METHODS: A Monte Carlo-based Markov simulation model was developed to forecast long-term effects of two screening strategies with regards to clinical and cost-effectiveness outcomes. The base case model included 20,000 simulated patients over 35-years follow-up. Transition probabilities on disease progression, mortality, effects on preventive treatments and complications were retrieved from landmark diabetes studies. Direct medical costs were sourced from published literature and inflated to 2019 Euros. RESULTS: In the lifetime analysis, the 1-hPG was projected to increase the number of years free from disease (2 years per patient); to delay the onset of T2D (1 year per patient); to reduce the incidence of T2D complications (0·6 RR-Relative Risk per patient) and to increase the QALY gained (0·58 per patient). Even if the 1-hPG diagnostic method resulted in higher initial costs associated with preventive treatment, long-term diabetes-related costs as well as complications costs were reduced leading to a lifetime saving of - 31225719.82€. The incremental cost-effectiveness ratio was - 8214.7€ per each QALY gained for the overall population. CONCLUSIONS: Screening prediabetes with the 1-hPG is feasible and cost-effective resulting in reduced costs per QALY. Notwithstanding, the higher initial costs of testing with the 1-hPG compared to the 2-hPG due to incremental preventive intervention, long-term diabetes and complications costs were reduced projecting an overall cost saving of - 8214.7€ per each QALY gained.

The assessment of neuropathic pain in patients with prediabetes.

AIMS: Neuropathic pain is associated with several clinical conditions, including anxiety, depression, sleep disorders, and decreased quality of life; however, less evaluated in prediabetes. This study aims to assess neuropathic pain through validated diagnostic tools in prediabetes. METHODS: One hundred and seventy-two patients with prediabetes and 170 controls were included in this cross-sectional study. The Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) Pain Scale and Douleur Neuropathique 4 Questions (DN4) were used to evaluate neuropathic pain. The Visual Analog Scale (VAS) was used to estimate pain intensity. RESULTS: Twenty-three (13.4%) and 12 (7%) patients with prediabetes were diagnosed with neuropathic pain using DN4 and LANSS questionnaires, respectively. Neuropathic pain rates of the patients were higher than controls with two pain scales (p < 0.001). VAS scores were higher in prediabetes group than in controls (p = 0.021). LANSS, DN4, and VAS scores were positively correlated with HbA1c level (r = 0.184, p = 0.016; r = 0.180, p = 0.018; r = 0.188, p = 0.014, respectively). LANNS and DN4 scores were higher in female patients than in males (p < 0.001). CONCLUSIONS: Neuropathic pain was increased in prediabetes by DN4 and LANNS questionnaires. An appropriate diagnosis of neuropathic pain in prediabetes may prevent patients from different pain-related clinical conditions.

Assessment of the risk factors associated with type 2 diabetes and prediabetes mellitus: A national survey in Vietnam.

This study aims to estimating the prevalence of type 2 diabetes and prediabetes among adult from 30 to 69 years old and assess the association of risk factor with the conditions. A total of 5244 aged 30 to 69 years old were participated in this cross-sectional study, using nationally representative sampling frame. All participants were taking blood sample to measure fasting blood glucose level and 2-hour postload oral glucose tolerance test by National Hospital of Endocrinology, Vietnam. Multinomial logistic regressions with baseline-category logit models were conducted to identify factors associated with diabetes and prediabetes among respondents. The prediabetes prevalence was in 17.9% and diabetes in 7.3%. Patients who were male (reference group vs female OR = 0.79; 95% CI: 0.64, 0.97), in the 50 to 59 years old group (OR = 1.60; 95% CI: 1.28, 2.00), have hypertension and WHR risk have higher prevalence to have prediabetes (OR = 1.31; 95% CI: 1.12, 1.53; OR = 1.37; 95% CI: 1.11, 1.70, respectively). Male patients (reference group vs female OR = 0.62; 95% CI: 0.45, 0.84), patients who were in 40 to 49; 50 to 59; 60 to 69 years old, those who were housewife (OR = 2.17; 95% CI: 1.43, 3.28; OR = 2.85; 95% CI: 1.91, 4.27; OR = 3.12; 95% CI: 2.08, 4.69; OR = 1.71; 95% CI: 1.22, 2.40, respectively). Diabetes have significant associated with participants have hypertension (OR = 1.19; 95% CI: 1.72, 2.70). The common factor directly related to prediabetes and diabetes in both genders is age. Other factors directly associated with prediabetes and diabetes include BMI, WHR, hypertension, educational level, and job.

Cost-effectiveness of community diabetes screening: Application of Akaike information criterion in rural communities of Nigeria.

Background: The prevalence of diabetes mellitus (DM) is increasing globally, and this requires several approaches to screening. There are reports of alternative indices for prediction of DM, besides fasting blood glucose (FBG) level. This study, investigated the ability of combination of biochemical and anthropometric parameters and orodental disease indicators (ODIs) to generate models for DM prediction, using Akaike information criterion (AIC) to substantiate health economics of diabetes screening. Methods: Four hundred and thirty-three subjects were enrolled in the study in Ndokwa communities, Delta State, Nigeria, and their glycaemic status was determined, using the CardioChek analyser® and previous data from the Prediabetes and Cardiovascular Complications Study were also used. The cost of screening for diabetes (NGN 300 = $0.72) in a not-for-profit organization/hospital was used as basis to calculate the health economics of number of individuals with DM in 1,000 participants. Data on the subjects' anthropometric, biochemical and ODI parameters were used to generate different models, using R statistical software (version 4.0.0). The different models were evaluated for their AIC values. Lowest AIC was considered as best model. Microsoft Excel software (version 2020) was used in preliminary analysis. Result: The cost of identifying <2 new subjects with hyperglycemia, in 1,000 people was ≥NGN 300,000 ($ 716). A total of 4,125 models were generated. AIC modeling indicates FBG test as the best model (AIC = 4), and the least being combination of random blood sugar + waist circumference + hip circumference (AIC ≈ 34). Models containing ODI parameters had AIC values >34, hence considered as not recommendable. Conclusion: The cost of general screening for diabetes in rural communities may appear high and burdensome in terms of health economics. However, the use of prediction models involving AIC is of value in terms of cost-benefit and cost-effectiveness to the healthcare consumers, which favors health economics.

Domains from the health belief model predict enrollment in the National Diabetes Prevention Program among insured adults with prediabetes.

AIMS: To examine enrollment in the National Diabetes Prevention Program (DPP) by insured adults with prediabetes according to domains of the Health Belief Model (HBM). METHODS: Between 2015 and 2019, University of Michigan employees, retirees, and dependents with prediabetes were offered the National DPP at no out-of-pocket cost. Individuals with prediabetes were identified and mailed letters encouraging them to enroll. We surveyed those who enrolled and a random sample of those who did not using the HBM as a framework to examine factors associated with enrollment. Analyses were performed using multivariable logistic regression models. RESULTS: Of 64,131 employees, retirees, and dependents, 8131 were identified with prediabetes and 776 (9.5%) enrolled in the National DPP. Of those surveyed, 532 of 776 National DPP enrollees and 945 of 2673 non-enrollees responded to the survey (adjusted response rates 74% and 43%, respectively). Among survey respondents, factors associated with National DPP enrollment included older age, female sex, higher BMI, prediabetes awareness, greater perceived benefits of health-protective action, and one or more cues to action. CONCLUSIONS: Optimizing National DPP enrollment among adults with prediabetes will require identifying individuals with prediabetes, increasing personal awareness of the diagnosis, increasing perceived benefits of enrollment, and providing strong cues to action.

Non-laboratory-based risk assessment model for case detection of diabetes mellitus and pre-diabetes in primary care.

INTRODUCTION: More than half of diabetes mellitus (DM) and pre-diabetes (pre-DM) cases remain undiagnosed, while existing risk assessment models are limited by focusing on diabetes mellitus only (omitting pre-DM) and often lack lifestyle factors such as sleep. This study aimed to develop a non-laboratory risk assessment model to detect undiagnosed diabetes mellitus and pre-diabetes mellitus in Chinese adults. METHODS: Based on a population-representative dataset, 1,857 participants aged 18-84 years without self-reported diabetes mellitus, pre-diabetes mellitus, and other major chronic diseases were included. The outcome was defined as a newly detected diabetes mellitus or pre-diabetes by a blood test. The risk models were developed using logistic regression (LR) and interpretable machine learning (ML) methods. Models were validated using area under the receiver-operating characteristic curve (AUC-ROC), precision-recall curve (AUC-PR), and calibration plots. Two existing diabetes mellitus risk models were included for comparison. RESULTS: The prevalence of newly diagnosed diabetes mellitus and pre-diabetes mellitus was 15.08%. In addition to known risk factors (age, BMI, WHR, SBP, waist circumference, and smoking status), we found that sleep duration, and vigorous recreational activity time were also significant risk factors of diabetes mellitus and pre-diabetes mellitus. Both LR (AUC-ROC = 0.812, AUC-PR = 0.448) and ML models (AUC-ROC = 0.822, AUC-PR = 0.496) performed well in the validation sample with the ML model showing better discrimination and calibration. The performance of the models was better than the two existing models. CONCLUSIONS: Sleep duration and vigorous recreational activity time are modifiable risk factors of diabetes mellitus and pre-diabetes in Chinese adults. Non-laboratory-based risk assessment models that incorporate these lifestyle factors can enhance case detection of diabetes mellitus and pre-diabetes.

Assessment of prevalence and risk factors of diabetes and pre-diabetes in South Africa.

BACKGROUND: Diabetes prevalence, as well as that of pre-diabetes, is rapidly increasing in South Africa. Individuals with pre-diabetes have a high risk of developing type 2 diabetes, which is reversible with a change in lifestyle. If left untreated, diabetes can lead to serious health complications. Our objective was to assess the prevalence of diabetes and pre-diabetes, and to investigate the associated risk factors of each in the South African population. METHOD: This study made use of the South African Demographic Health Survey 2016 data. The study participants included 6442 individuals aged 15 years and older. A generalized additive mixed model was employed to account for the complex survey design of the study as well as well spatial autocorrelation in the data. RESULTS: The observed prevalence of pre-diabetes and diabetes was 67% and 22%, respectively. Among those who had never been tested for diabetes prior to the survey, 10% of females and 6% of males were found to be diabetic, and 67% of both males and females were found to be pre-diabetic. Thus, a large proportion of the South African population remains undiagnosed. The model revealed both common and uncommon factors significantly associated with pre-diabetes and diabetes. This highlights the importance of considering diabetic status as a three-level categorical outcome, rather than binary. In addition, significant interactions between some of the lifestyle factors, demographic factors and anthropometric measures were revealed, which indicates that the effects each these factors have on the likelihood of an individual being pre-diabetic or diabetic is confounded by other factors. CONCLUSION: The risk factors for diabetes and pre-diabetes are many and complicated. Individuals need to be aware of their diabetic status before health complications arise. It is therefore important for all stakeholders in government and the private sector of South Africa to get involved in providing education and creating awareness about diabetes. Regular testing of diabetes, as well as leading a healthy lifestyle, should be encouraged.

Effectiveness and Cost-Effectiveness of Non-Pharmacological Interventions among Chinese Adults with Prediabetes: A Protocol for Network Meta-Analysis and CHIME-Modeled Cost-Effectiveness Analysis.

Patients with prediabetes who are at a high risk of progressing to diabetes are recommended early-stage intervention, according to guidelines. Non-pharmacological interventions are effective and cost-effective for glycemic control compared with medicines. We aim to explore which non-pharmacological interventions have the greatest potential effectiveness, cost-effectiveness, and feasibility in community-based diabetes management in China. We will perform a systematic review and network meta-analysis to compare the effectiveness of included non-pharmacological interventions, then use Chinese Hong Kong Integrated Modeling and Evaluation (CHIME) to model the yearly incidence of complications, costs, and health utility for the lifetime. Published studies (only randomized controlled trials (RCTs) and cluster RCTs with at least one study arm of any non-pharmacological intervention) will be retrieved and screened using several databases. Primary outcomes included blood glucose, glycated hemoglobin, incidence of type 2 diabetes mellitus, and achievement of normoglycemia. Health utilities and cost parameters are to be calculated using a societal perspective and integrated into the modified CHIME model to achieve quality-adjusted life-year (QALY) estimates and lifetime costs. QALYs and incremental cost-effectiveness ratio will then be used to determine effectiveness and cost-effectiveness, respectively. Our study findings can inform improved diabetes management in countries with no intervention programs for these patients.