Opportunities to Reduce Diabetes Risk in Women of Reproductive Age: Assessment and Treatment of Prediabetes within a Large Integrated Delivery System

Long-Term Exposure to Fine Particulate Matter and Fasting Blood Glucose and Diabetes in 20 Million Chinese Women of Reproductive Age

OBJECTIVE

Evidence of the associations between fine particulate matter (PM2.5) and diabetes risk from women of reproductive age, in whom diabetes may have adverse long-term health effects for both themselves and future generations, remains scarce. We therefore examined the associations of long-term PM2.5 exposure with fasting blood glucose (FBG) level and diabetes risk in women of reproductive age in China.

RESEARCH DESIGN AND METHODS

This study included 20,076,032 women age 20-49 years participating in the National Free Preconception Health Examination Project in China between 2010 and 2015. PM2.5 was estimated using a satellite-based model. Multivariate linear and logistic regression models were used to examine the associations of PM2.5 exposure with FBG level and diabetes risk, respectively. Diabetes burden attributable to PM2.5 was estimated using attributable fraction (AF) and attributable number.

RESULTS

PM2.5 showed monotonic relationships with elevated FBG level and diabetes risk. Each interquartile range (27 μg/m3) increase in 3-year average PM2.5 concentration was associated with a 0.078 mmol/L (95% CI 0.077, 0.079) increase in FBG and 18% (95% CI 16%, 19%) higher risk of diabetes. The AF attributed to PM2.5 exposure exceeding 5 μg/m3 was 29.0% (95% CI 27.5%, 30.5%), corresponding to an additional 78.6 thousand (95% CI 74.5, 82.6) diabetes cases. Subgroup analyses showed more pronounced diabetes risks in those who were overweight or obese, age >35 years, less educated, of minority ethnicity, registered as a rural household, and residing in western China.

CONCLUSIONS

We found long-term PM2.5 exposure was associated with higher diabetes risk in women of reproductive age in China.

Metformin prescription for U.S. veterans with prediabetes, 2010-2019

Affecting an estimated 88 million Americans, prediabetes increases the risk for developing type 2 diabetes mellitus (T2DM), and independently, cardiovascular disease, retinopathy, nephropathy, and neuropathy. Nevertheless, little is known about the use of metformin for diabetes prevention among patients in the Veterans Health Administration, the largest integrated healthcare system in the U.S. This is a retrospective observational cohort study of the proportion of Veterans with incident prediabetes who were prescribed metformin at the Veterans Health Administration from October 2010 to September 2019. Among 1,059,605 Veterans with incident prediabetes, 12,009 (1.1%) were prescribed metformin during an average 3.4 years of observation after diagnosis. Metformin prescribing was marginally higher (1.6%) among those with body mass index (BMI) ≥35 kg/m2, age <60 years, HbA1c≥6.0%, or those with a history of gestational diabetes, all subgroups at a higher risk for progression to T2DM. In a multivariable model, metformin was more likely to be prescribed for those with BMI ≥35 kg/m2 incidence rate ratio [IRR] 2.6 [95% confidence intervals (CI): 2.1-3.3], female sex IRR, 2.4 [95% CI: 1.8-3.3], HbA1c≥6% IRR, 1.93 [95% CI: 1.5-2.4], age <60 years IRR, 1.7 [95% CI: 1.3-2.3], hypertriglyceridemia IRR, 1.5 [95% CI: 1.2-1.9], hypertension IRR, 1.5 [95% CI: 1.1-2.1], Major Depressive Disorder IRR, 1.5 [95% CI: 1.1-2.0], or schizophrenia IRR, 2.1 [95% CI: 1.2-3.8]. Over 20% of Veterans with prediabetes attended a comprehensive structured lifestyle modification clinic or program. Among Veterans with prediabetes, metformin was prescribed to 1.1% overall, a proportion that marginally increased to 1.6% in the subset of individuals at highest risk for progression to T2DM.

Training the next generation of delivery science researchers: 10-year experience of a post-doctoral research fellowship program within an integrated care system

Introduction

Learning health systems require a workforce of researchers trained in the methods of identifying and overcoming barriers to effective, evidence-based care. Most existing postdoctoral training programs, such as NIH-funded postdoctoral T32 awards, support basic and epidemiological science with very limited focus on rigorous delivery science methods for improving care. In this report, we present the 10-year experience of developing and implementing a Delivery Science postdoctoral fellowship embedded within an integrated health care delivery system.

Methods

In 2012, the Kaiser Permanente Northern California Division of Research designed and implemented a 2-year postdoctoral Delivery Science Fellowship research training program to foster research expertise in identifying and addressing barriers to evidence-based care within health care delivery systems.

Results

Since 2014, 20 fellows have completed the program. Ten fellows had PhD-level scientific training, and 10 fellows had clinical doctorates (eg, MD, RN/PhD, PharmD). Fellowship alumni have graduated to faculty research positions at academic institutions (9), and research or clinical organizations (4). Seven alumni now hold positions in Kaiser Permanente's clinical operations or medical group (7).

Conclusions

This delivery science fellowship program has succeeded in training graduates to address delivery science problems from both research and operational perspectives. In the next 10 years, additional goals of the program will be to expand its reach (eg, by developing joint research training models in collaboration with clinical fellowships) and strengthen mechanisms to support transition from fellowship to the workforce, especially for researchers from underrepresented groups.

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.

A randomized controlled trial of a shared decision making intervention for diabetes prevention for women with a history of gestational diabetes mellitus: The Gestational diabetes Risk Attenuation for New Diabetes (GRAND study)

BACKGROUND

Gestational diabetes mellitus (GDM) is a risk factor for the development of type 2 diabetes. Metformin and lifestyle change through a Diabetes Prevention Program (DPP) are equally effective in preventing diabetes in patients with a GDM history, so women can choose a strategy based on their preferences. This study aims to test whether shared decision making (SDM) can help women with a history of GDM increase adoption of evidence-based strategies and lose weight to lower their risk of incident diabetes in real-world settings.

METHODS

This pragmatic randomized controlled trial (RCT) will test the effectiveness of SDM for diabetes prevention among 310 overweight/obese women with a history of GDM and prediabetes from two large health care systems (n = 155 from UCLA Health and n = 155 from Intermountain Healthcare). The primary outcome is the proportion of participants who lose ≥5% body weight at 12 months. Secondary outcomes include uptake of DPP and/or metformin and other patient-reported outcomes such as patient activation and health-related quality of life. Rates of GDM in a subsequent pregnancy will be an exploratory outcome. A descriptive analysis of costs related to SDM implementation will also be conducted.

CONCLUSION

This is the first RCT to examine the effectiveness of SDM on weight loss, lifestyle change and/or metformin use, and other patient-reported outcomes in participants with a GDM history at risk of developing diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03766256. Registered on 6 December 2018.

Triglyceride/Glucose Index (TyG Index) as a marker of glucose status conversion among reproductive-aged women in Jakarta, Indonesia: The Bogor cohort study (2011-2016)

BACKGROUND AND AIMS

Reproductive-aged women are prone to type 2 diabetes mellitus. This study aims to evaluate the optimal cut off point of Triglyceride/Glucose Index for predicting glucose status conversion among women of reproductive age.

METHODS

This study involved normoglycemic and prediabetes women aged 20-49 years from the Bogor Non-Communicable Diseases Cohort Study (West Java, Indonesia) conducted from 2011 to 2016. Statistical analysis was performed using Receiver Operating Characteristics curve analysis with STATA version 15.

RESULTS

Among prediabetes subjects (n = 371), the cut-off point of TyG index for regression from prediabetes to normoglycemic subjects was <4.51 [sensitivity, specificity, AUC (95%CI) 83.9%, 80.1%, 0.913 (0.875-0.943), respectively] and the cut-off point for progression from prediabetes to diabetes was >4.54 [80.0%, 73.1%, 0.858 (0.807-0.900)]. Among normoglycemic subjects (n = 1300), the cut-off point of TyG index for progression to prediabetes and diabetes were >4.44 [80.1%, 71.1%, 0.834 (0.812-0.854)] and >4.47 [80.6%, 80.8%, 0.909 (0.890-0.926)] respectively.

CONCLUSION

Based on sample of subjects evaluated between 2011 and 2016, TyG index appears to be a promising marker for glucose status conversion among reproductive-aged women in Jakarta, Indonesia.

Trends in Selected Chronic Conditions and Related Risk Factors Among Women of Reproductive Age: Behavioral Risk Factor Surveillance System, 2011-2017

Introduction: Chronic diseases in the United States are the leading drivers of disability, death, and health care costs. In women of reproductive age (WRA), chronic disease and related risk factors can also affect fertility and reproductive health outcomes. This analysis of trends from 2011 to 2017 adds additional indicators and updates an analysis covering 2001-2009. Methods: Data from the 2011-2017 Behavioral Risk Factor Surveillance System were analyzed for 265,544 WRA (18-44 years). To assess trends in 12 chronic conditions and related risk factors, we calculated annual prevalence estimates and adjusted prevalence ratios (APRs) with predicted marginals accounting for age, race, Hispanic ethnicity, education, and health care coverage. Results: From 2011 to 2017, prevalence decreased for current smoking (20.7%-15.9%; p < 0.001), gestational diabetes (3.1%-2.7%; p = 0.003), and high cholesterol (19.0%-16.7%; p < 0.001); prevalence increased for depression (20.4%-24.9%; p < 0.001) and obesity (24.6%-27.6%; p < 0.001). After adjustment, in 2017 WRA were more likely to report asthma (APR = 1.06; 95% confidence interval [CI] = 1.01-1.11), physical inactivity (APR = 1.08; 95% CI = 1.04-1.12), obesity (APR = 1.15; 95% CI = 1.11-1.19), and depression (APR = 1.29; 95% CI = 1.25-1.34) compared with 2011. They were less likely to report high cholesterol (APR = 0.89; 95% CI = 0.85-0.94) in 2015 compared with 2011, and current smoking (APR = 0.86; 95% CI = 0.82-0.89) and gestational diabetes (APR = 0.84; 95% CI = 0.75-0.94) in 2017 compared with 2011. Conclusions: Some chronic conditions and related risk factors improved, whereas others worsened over time. Research clarifying reasons for these trends may support the development of targeted interventions to promote improvements, potentially preventing adverse reproductive outcomes and promoting long-term health.

Effectiveness of Shared Decision-making for Diabetes Prevention: 12-Month Results from the Prediabetes Informed Decision and Education (PRIDE) Trial

IMPORTANCE

Intensive lifestyle change (e.g., the Diabetes Prevention Program) and metformin reduce type 2 diabetes risk among patients with prediabetes. However, real-world uptake remains low. Shared decision-making (SDM) may increase awareness and help patients select and follow through with informed options for diabetes prevention that are aligned with their preferences.

OBJECTIVE

To test the effectiveness of a prediabetes SDM intervention.

DESIGN

Cluster randomized controlled trial.

SETTING

Twenty primary care clinics within a large regional health system.

PARTICIPANTS

Overweight/obese adults with prediabetes (BMI ≥ 24 kg/m2 and HbA1c 5.7-6.4%) were enrolled from 10 SDM intervention clinics. Propensity score matching was used to identify control patients from 10 usual care clinics.

INTERVENTION

Intervention clinic patients were invited to participate in a face-to-face SDM visit with a pharmacist who used a decision aid (DA) to describe prediabetes and four possible options for diabetes prevention: DPP, DPP ± metformin, metformin only, or usual care.

MAIN OUTCOMES AND MEASURES

Primary endpoint was uptake of DPP (≥ 9 sessions), metformin, or both strategies at 4 months. Secondary endpoint was weight change (lbs.) at 12 months.

RESULTS

Uptake of DPP and/or metformin was higher among SDM participants (n = 351) than controls receiving usual care (n = 1028; 38% vs. 2%, p < .001). At 12-month follow-up, adjusted weight loss (lbs.) was greater among SDM participants than controls (- 5.3 vs. - 0.2, p < .001).

LIMITATIONS

Absence of DPP supplier participation data for matched patients in usual care clinics.

CONCLUSIONS AND RELEVANCE

A prediabetes SDM intervention led by pharmacists increased patient engagement in evidence-based options for diabetes prevention and was associated with significantly greater uptake of DPP and/or metformin at 4 months and weight loss at 12 months. Prediabetes SDM may be a promising approach to enhance prevention efforts among patients at increased risk.

TRIAL REGISTRATION

This study was registered at clinicaltrails.gov (NCT02384109)).

Review of Metformin Use for Type 2 Diabetes Prevention

CONTEXT

Prediabetes is prevalent and significantly increases lifetime risk of progression to type 2 diabetes. This review summarizes the evidence surrounding metformin use for type 2 diabetes prevention.

EVIDENCE ACQUISITION

Articles published between 1998 and 2017 examining metformin use for the primary indication of diabetes prevention available on MEDLINE.

EVIDENCE SYNTHESIS

Forty articles met inclusion criteria and were summarized into four general categories: (1) RCTs of metformin use for diabetes prevention (n=7 and n=2 follow-up analyses); (2) observational analyses examining metformin use in heterogeneous subgroups of patients with prediabetes (n=9 from the Diabetes Prevention Program, n=1 from the biguanides and the prevention of the risk of obesity [BIGPRO] trial); (3) observational analyses examining cost effectiveness of metformin use for diabetes prevention (n=11 from the Diabetes Prevention Program, n=1 from the Indian Diabetes Prevention Program); and (4) real-world assessments of metformin eligibility or use for diabetes prevention (n=9). Metformin was associated with reduced relative risk of incident diabetes, with the strongest evidence for use in those at highest risk (i.e., aged <60 years, BMI ≥35, and women with histories of gestational diabetes). Metformin was also deemed cost effective in 11 economic analyses. Recent studies highlighted low rates of metformin use for diabetes prevention in real-world settings.

CONCLUSIONS

Two decades of evidence support metformin use for diabetes prevention among higher-risk patients. However, metformin is not widely used in real-world practice, and enhancing the translation of this evidence to real-world practice has important implications for patients, providers, and payers.

Using Neighborhood-Level Census Data to Predict Diabetes Progression in Patients with Laboratory-Defined Prediabetes

CONTEXT

Research on predictors of clinical outcomes usually focuses on the impact of individual patient factors, despite known relationships between neighborhood environment and health.

OBJECTIVE

To determine whether US census information on where a patient resides is associated with diabetes development among patients with prediabetes.

DESIGN

Retrospective cohort study of all 157,752 patients aged 18 years or older from Kaiser Permanente Northern California with laboratory-defined prediabetes (fasting plasma glucose, 100 mg/dL-125 mg/dL, and/or glycated hemoglobin, 5.7%-6.4%). We assessed whether census data on education, income, and percentage of households receiving benefits through the US Department of Agriculture's Supplemental Nutrition Assistance Program (SNAP) was associated with diabetes development using logistic regression controlling for age, sex, race/ethnicity, blood glucose levels, and body mass index.

MAIN OUTCOME MEASURE

Progression to diabetes within 36 months.

RESULTS

Patients were more likely to progress to diabetes if they lived in an area where less than 16% of adults had obtained a bachelor's degree or higher (odds ratio [OR] =1.22, 95% confidence interval [CI] = 1.09-1.36), where median annual income was below $79,999 (OR = 1.16 95% CI = 1.03-1.31), or where SNAP benefits were received by 10% or more of households (OR = 1.24, 95% CI = 1.1-1.4).

CONCLUSION

Area-level socioeconomic and food assistance data predict the development of diabetes, even after adjusting for traditional individual demographic and clinical factors. Clinical interventions should take these factors into account, and health care systems should consider addressing social needs and community resources as a path to improving health outcomes.