Review of the performance of methods to identify diabetes cases among vital statistics, administrative, and survey data

BMI Trajectories in Late Middle Age, Genetic Risk, and Incident Diabetes in Older Adults: Evidence From a 26-Year Longitudinal Study

This study investigated the association between body mass index (BMI) trajectories in late middle age and incident diabetes in later years. A total of 11,441 participants aged 50-60 years from the Health and Retirement Study with at least 2 self-reported BMI records were included. Individual BMI trajectories representing average BMI changes per year were generated using multilevel modeling. Adjusted risk ratios (ARRs) and 95% confidence intervals (95% CIs) were calculated. Associations between BMI trajectories and diabetes risk in participants with different genetic risks were estimated for 5,720 participants of European ancestry. BMI trajectories were significantly associated with diabetes risk in older age (slowly increasing vs. stable: ARR = 1.31, 95% CI: 1.12, 1.54; rapidly increasing vs. stable: ARR = 1.5, 95% CI: 1.25, 1.79). This association was strongest for normal-initial-BMI participants (slowly increasing: ARR = 1.34, 95% CI: 0.96, 1.88; rapidly increasing: ARR = 2.06, 95% CI: 1.37, 3.11). Participants with a higher genetic liability to diabetes and a rapidly increasing BMI trajectory had the highest risk for diabetes (ARR = 2.15, 95% CI: 1.67, 2.76). These findings confirmed that BMI is the leading risk factor for diabetes and that although the normal BMI group has the lowest incidence rate for diabetes, people with normal BMI are most sensitive to changes in BMI.

Multicausal analysis of mortality due to diabetes mellitus in Spain, 2016-2018

OBJECTIVES

This study aimed to assess multicausal mortality due to diabetes from 2016-2018 in Spain. Specific objectives were to quantify the occurrence of diabetes as an underlying cause or as any registered cause on the death certificate.

MATERIALS AND METHODS

A cross-sectional descriptive study taking a multicausal approach.

RESULTS

Diabetes appears as an underlying cause of 2.3% of total deaths in Spain, and as any cause in 6.2%. In patients in whom Diabetes appears as an underlying cause on the death certificates, the 15 most frequent immediate causes are cardiovascular diseases in men(prevalence ratio 1,59)and women (PR1,31). In men, the causes associated with diabetes as any cause were skin diseases(prevalence ratio 1.33), followed by endocrine diseases(prevalence ratio 1.26)and genitourinary diseases (prevalence ratio1.14). In women, the causes associated with the presence of diabetes as any cause were endocrine (prevalence ratio 1.13)and genitourinary (prevalence ratio 1.04)diseases.

CONCLUSIONS

In patients in whom diabetes appears as an underlying cause on the death certificates, the 15 most frequent immediate causes are cardiovascular diseases. In men, the causes associated with the presence of diabetes as any cause of death are skin, endocrine and genitourinary diseases. In women, the causes associated with diabetes as any cause are endocrine and genitourinary.

Excess diabetes-related deaths: The role of comorbidities through different phases of the COVID-19 pandemic

BACKGROUND AND AIMS

Diabetes confers an excess risk of death to COVID-19 patients. Causes of death are now available for different phases of the pandemic, encompassing different viral variants and COVID-19 vaccination. The aims of the present study were to update multiple causes of death data on diabetes-related mortality during the pandemic and to estimate the impact of common diabetic comorbidities on excess mortality.

METHODS AND RESULTS

Diabetes-related deaths in 2020-2021 were compared with the 2018-2019 average; furthermore, age-standardized rates observed during the pandemic were compared with expected figures obtained from the 2008-2019 time series through generalized estimating equation models. Changes in diabetes mortality associated with specific comorbidities were also computed. Excess diabetes-related mortality was +26% in 2020 and +18% in 2021, after the initiation of the vaccination campaign. The presence of diabetes and hypertensive diseases was associated with the highest mortality increase, especially in subjects aged 40-79 years, +41% in 2020 and +30% in 2021.

CONCLUSION

The increase in diabetes-related deaths exceeded that observed for all-cause mortality, and the risk was higher when diabetes was associated with hypertensive diseases. Notably, the excess mortality decreased in 2021, after the implementation of vaccination against COVID-19.

Mortality differentials by previous diagnosis of diabetes and glycemic status in the United States

AIMS

This study examines mortality differences associated with current glycemic status in mortality by current glycemic status among adults with a previously diagnosed diabetes. Using previous clinical diagnosis of diabetes (diagnosed diabetes) and laboratory measures of hemoglobin A1c (HbA1c) measured at baseline, we estimated mortality differentials simultaneously by diagnosed diabetes and baseline glycemic status in the United States.

METHODS

Data were from 39,491 adults aged 30-84 years assessed in the National Health and Nutrition Examination Survey (NHANES) III and continuous NHANES 1999-2014 linked to mortality data. We categorized participants into four mutually exclusive groups based on diagnosed diabetes and glycemic control measured by HbA1c ≥6.5 % at baseline. Relative hazard ratio (HR) of all-cause death among these four groups were estimated using Cox proportional models.

RESULTS

There was no significant difference in mortality by glycemic control status among adults with diagnosed diabetes. The same finding was observed among adults without diagnosed diabetes. Adults with diagnosed diabetes had higher mortality than adults without diagnosed diabetes independent of their baseline glycemic control.

CONCLUSIONS

Once diagnosed with diabetes, US adults with normal- and hyper-glycemia showed no significant difference in all-cause mortality. This finding emphasizes the importance of primary prevention interventions among adults with a sign of early-stage diabetes.

National Trends in the Achievement of Recommended Strategies for Stroke Prevention in U.S. Adults With Type 2 Diabetes, 2001-2018

OBJECTIVE

To assess the national prevalence of and trends in achieving current guideline-recommended treatment goals and pharmacotherapies for primary and secondary prevention of stroke among U.S. adults with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

We performed serial cross-sectional analyses in 4,834 adults aged ≥45 years with T2D who participated in the 2001-2018 National Health and Nutrition Examination Survey. With stratification by stroke history, we estimated the proportion of adults with T2D who achieved current guideline-recommended strategies for stroke prevention. Preventive strategies for stroke were benchmarked against diabetes care and cardiovascular risk reduction guidelines.

RESULTS

Overall in 2001-2018, among those without stroke history, the proportion who achieved primary stroke prevention strategies ranged from 8.4% (95% CI 6.8-10.1) for aspirin/clopidogrel treatment in those with a higher cardiovascular disease risk to 80.5% (78.8-82.2) for nonsmoking. Among those with stroke history, the proportion who achieved secondary stroke prevention strategies ranged from 11.8% (8.7-14.8) for weight control to 80.0% (74.9-84.9) for glycemic control. From 2001 to 2018, among those without stroke history, there was a significant increase in statin therapy (Ptrend < 0.0001), smoking abstinence (Ptrend = 0.01), and ACE inhibitor/angiotensin receptor blocker treatment for hypertension (Ptrend = 0.04) but a substantial decline in weight control (Ptrend < 0.001). Among those with stroke history, only statin therapy (Ptrend = 0.01) increased significantly over time.

CONCLUSIONS

During 2001-2018, the achievement of some current guideline-recommended strategies for stroke prevention among U.S. adults with T2D improved but remains a challenge overall. Efforts are needed to improve implementation of strategies for stroke prevention in this population.

The association between oil spill cleanup-related total hydrocarbon exposure and diabetes

BACKGROUND

Although evidence suggests relationships between some crude oil components and glycemic dysregulation, no studies have examined oil spill-related chemical exposures in relation to type 2 diabetes mellitus (DM) risk. This study examined the relationship between total hydrocarbon (THC) exposure among workers involved in the 2010 Deepwater Horizon (DWH) oil spill and risk of DM up to 6 years afterward.

METHODS

Participants comprised 2660 oil-spill cleanup or response workers in the prospective GuLF Study who completed a clinical exam and had no self-reported DM diagnosis prior to the spill. Maximum THC exposure was estimated with a job-exposure matrix based on interview data and personal measurements taken during cleanup operations. We defined incident DM by self-reported physician diagnosis of DM, antidiabetic medication use, or a measured hemoglobin A1c value ≥ 6.5%. We used log binomial regression to estimate risk ratios (RRs) for DM across ordinal categories of THC exposure. The fully adjusted model controlled for age, sex, race/ethnicity, education, employment status, and health insurance status. We also stratified on clinical body mass index categories.

RESULTS

We observed an exposure-response relationship between maximum daily ordinal THC exposure level and incident DM, especially among overweight participants. RRs among overweight participants were 0.99 (95% CI: 0.37, 2.69), 1.46 (95% CI: 0.54, 3.92), and 2.11 (95% CI: 0.78, 5.74) for exposure categories 0.30-0.99 ppm, 1.00-2.99 ppm, and ≥3.00 ppm, respectively (ptrend = 0.03).

CONCLUSION

We observed suggestively increasing DM risk with increasing THC exposure level among overweight participants, but not among normal weight or obese participants.

Role and mechanism(s) of incretin-dependent therapies for treating diabetes mellitus

Diabetes mellitus (DM) is a worldwide ailment which leads to chronic complications like cardiac disorders, renal perturbations, limb amputation and blindness. Type one diabetes (T1DM), Type two diabetes (T2DM), Another types of diabetes, such as genetic errors in function of β-cell and action of insulin, cystic fibrosis, chemical-instigated diabetes or following tissue transplantation), and pregnancy DM (GDM). In response to nutritional ingestion, the gut may release a pancreatic stimulant that affects carbohydrate metabolism. The duodenum produces a 'chemical excitant' that stimulates pancreatic output, and researchers have sought to cure diabetes using gut extract injections, coining the word 'incretin' to describe the phenomena. Incretins include GIP and GLP-1. The 'enteroinsular axis' is the link between pancreas and intestine. Nutrient, neuronal and hormonal impulses from intestine to cells secreting insulin were thought to be part of this axis. In addition, the hormonal component, incretin, must meet two requirements: (1) it secreted by foods, mainly carbohydrates, and (2) it must induce an insulinotropic effect which is glucose-dependent. In this review, we clarify the ability of using incretin-dependent treatments for treating DM.

Mortality attributable to type 2 diabetes mellitus in Latin America and the Caribbean: a comparative risk assessment analysis

INTRODUCTION

We quantified the proportion and the absolute number of deaths attributable to type 2 diabetes mellitus (T2DM) in Latin America and the Caribbean (LAC) using an estimation approach.

RESEARCH DESIGN AND METHODS

We combined T2DM prevalence estimates from the NCD Risk Factor Collaboration, relative risks between T2DM and all-cause mortality from a meta-analysis of cohorts in LAC, and death rates from the Global Burden of Disease Study 2019. We estimated population-attributable fractions (PAFs) and computed the absolute number of attributable deaths in 1990 and 2019 by multiplying the PAFs by the total deaths in each country, year, sex, and 5-year age group.

RESULTS

Between 1985 and 2014 in LAC, the proportion of all-cause mortality attributable to T2DM increased from 12.2% to 16.9% in men and from 14.5% to 19.3% in women. In 2019, the absolute number of deaths attributable to T2DM was 349 787 in men and 330 414 in women. The highest death rates (deaths per 100 000 people) in 2019 were in Saint Kitts and Nevis (325 in men, 229 in women), Guyana (313 in men, 272 in women), and Haiti (269 in men, 265 in women).

CONCLUSIONS

A substantial burden of all deaths is attributed to T2DM in LAC. To decrease the mortality attributable to T2DM in LAC, policies are needed to strengthen early diagnosis and management, along with the prevention of complications.

Association of Statin Therapy Initiation With Diabetes Progression: A Retrospective Matched-Cohort Study

IMPORTANCE

Statin therapy has been associated with increased insulin resistance; however, its clinical implications for diabetes control among patients with diabetes is unknown.

OBJECTIVE

To assess diabetes progression after initiation of statin use in patients with diabetes.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective matched-cohort study using new-user and active-comparator designs to assess associations between statin initiation and diabetes progression in a national cohort of patients covered by the US Department of Veterans Affairs from fiscal years 2003-2015. Patients included were 30 years or older; had been diagnosed with diabetes during the study period; and were regular users of the Veterans Affairs health system, with records of demographic information, clinical encounters, vital signs, laboratory data, and medication usage.

INTERVENTIONS

Treatment initiation with statins (statin users) or with H2-blockers or proton pump inhibitors (active comparators).

MAIN OUTCOMES AND MEASURES

Diabetes progression composite outcome comprised the following: new insulin initiation, increase in the number of glucose-lowering medication classes, incidence of 5 or more measurements of blood glucose of 200 mg/dL or greater, or a new diagnosis of ketoacidosis or uncontrolled diabetes.

RESULTS

From the 705 774 eligible patients, we matched 83 022 pairs of statin users and active comparators; the matched cohort had a mean (SD) age of 60.1 (11.6) years; 78 712 (94.9%) were men; 1715 (2.1%) were American Indian/Pacific Islander/Alaska Native, 570 (0.8%) were Asian, 17 890 (21.5%) were Black, and 56 633 (68.2 %) were White individuals. Diabetes progression outcome occurred in 55.9% of statin users vs 48.0% of active comparators (odds ratio, 1.37; 95% CI, 1.35-1.40; P < .001). Each individual component of the composite outcome was significantly higher among statin users. Secondary analysis demonstrated a dose-response relationship with a higher intensity of low-density lipoprotein-cholesterol lowering associated with greater diabetes progression.

CONCLUSIONS AND RELEVANCE

This retrospective matched-cohort study found that statin use was associated with diabetes progression, including greater likelihood of insulin treatment initiation, significant hyperglycemia, acute glycemic complications, and an increased number of prescriptions for glucose-lowering medication classes. The risk-benefit ratio of statin use in patients with diabetes should take into consideration its metabolic effects.

Insomnia symptoms are associated with an increased risk of type 2 diabetes mellitus among adults aged 50 and older

PURPOSE

To evaluate the association of the different degrees of insomnia symptoms with subsequent incidence of type 2 diabetes mellitus (T2DM).

METHODS

The data were extracted from Health and Retirement Study 2006-2014 waves. The association of insomnia symptoms with T2DM incidence was evaluated by the competing risk model with cumulative incidence function (death was considered a competing event) and Cox proportional hazard model with the Kaplan-Meier method. Population attributable fraction (PAF) was calculated. All analyses related to our study were conducted between November 2020 and January 2021.

RESULTS

A total of 14,112 patients were included in this study, with an average follow-up of 6.4 years, and the incidence density was 17.9 per 1000 person-years. Insomnia symptoms were positively associated with T2DM incidence compared with those with no insomnia symptoms, regardless of competing risk model (≥ 1 symptoms: sub-distribution hazard ratio (SHR) 1.13; 95% confidence interval (CI) 1.02-1.26; P-trend = 0.012) and Cox proportional hazard model (≥ 1 symptoms: hazard ratio (HR) 1.13; 95% CI 1.02-1.26; P-trend = 0.013). The cumulative incidence function (Gray's test, p < 0.001) and Kaplan-Meier estimate (log-rank test, p < 0.001) also presented this positive relationship. This positive association was more apparent in women and participants with ages from 50 to 65 years. The PAF was 4.1% with 95% CI (0.7-7.9%).

CONCLUSIONS

Insomnia symptoms may be an important risk factor for the development of T2DM, which is unbiased by the death competing risk. These findings suggest that management of sleep problems may be an important part of strategies to prevent T2DM.

Analysis of Time Trends in Alzheimer's Disease and Related Dementias Using Partitioning Approach

BACKGROUND

Understanding the dynamics of epidemiologic trends in Alzheimer's disease (AD) and related dementias (ADRD) and their epidemiologic causes is vital to providing important insights into reducing the burden associated with these conditions.

OBJECTIVE

To model the time trends in age-adjusted AD/ADRD prevalence and incidence-based mortality (IBM), and identify the main causes of the changes in these measures over time in terms of interpretable epidemiologic quantities.

METHODS

Trend decomposition was applied to a 5%sample of Medicare beneficiaries between 1991 and 2017.

RESULTS

Prevalence of AD was increasing between 1992 and 2011 and declining thereafter, while IBM increased over the study period with a significant slowdown in its rate of growth from 2011 onwards. For ADRD, prevalence and IBM increased through 2014 prior to taking a downwards turn. The primary determinant responsible for declines in prevalence and IBM was the deceleration in the increase and eventual decrease in incidence rates though changes in relative survival began to affect the overall trends in prevalence/IBM in a noticeable manner after 2008. Other components showed only minor effects.

CONCLUSION

The prevalence and IBM of ADRD is expected to continue to decrease. The directions of these trends for AD are not clear because AD incidence, the main contributing component, is decreasing but at a decreasing rate suggesting a possible reversal. Furthermore, emerging treatments may contribute through their effects on survival. Improving ascertainment of AD played an important role in trends of AD/ADRD over the 1991-2009/10 period but this effect has exhausted itself by 2017.

A primer on quantitative bias analysis with positive predictive values in research using electronic health data

OBJECTIVE

In health informatics, there have been concerns with reuse of electronic health data for research, including potential bias from incorrect or incomplete outcome ascertainment. In this tutorial, we provide a concise review of predictive value-based quantitative bias analysis (QBA), which comprises epidemiologic methods that use estimates of data quality accuracy to quantify the bias caused by outcome misclassification.

TARGET AUDIENCE

Health informaticians and investigators reusing large, electronic health data sources for research.

SCOPE

When electronic health data are reused for research, validation of outcome case definitions is recommended, and positive predictive values (PPVs) are the most commonly reported measure. Typically, case definitions with high PPVs are considered to be appropriate for use in research. However, in some studies, even small amounts of misclassification can cause bias. In this tutorial, we introduce methods for quantifying this bias that use predictive values as inputs. Using epidemiologic principles and examples, we first describe how multiple factors influence misclassification bias, including outcome misclassification levels, outcome prevalence, and whether outcome misclassification levels are the same or different by exposure. We then review 2 predictive value-based QBA methods and why outcome PPVs should be stratified by exposure for bias assessment. Using simulations, we apply and evaluate the methods in hypothetical electronic health record-based immunization schedule safety studies. By providing an overview of predictive value-based QBA, we hope to bridge the disciplines of health informatics and epidemiology to inform how the impact of data quality issues can be quantified in research using electronic health data sources.

A nationwide analysis of the excess death attributable to diabetes in Brazil

BACKGROUND

Data on mortality burden and excess deaths attributable to diabetes are sparse and frequently unreliable, particularly in low and middle-income countries. Estimates in Brazil to date have relied on death certificate data, which do not consider the multicausal nature of deaths. Our aim was to combine cohort data with national prevalence and mortality statistics to estimate the absolute number of deaths that could have been prevented if the mortality rates of people with diabetes were the same as for those without. In addition, we aimed to estimate the increase in burden when considering undiagnosed diabetes.

METHODS

We estimated self-reported diabetes prevalence from the National Health Survey (PNS) and overall mortality from the national mortality information system (SIM). We estimated the diabetes mortality rate ratio (rates of those with vs without diabetes) from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), an ongoing cohort study. Joining estimates from these three sources, we calculated for the population the absolute number and the fraction of deaths attributable to diabetes. We repeated our analyses considering both self-reported and unknown diabetes, the latter estimated based on single point-in-time glycemic determinations in ELSA-Brasil. Finally, we compared results with diabetes-related mortality information from death certificates.

RESULTS

In 2013, 65 581 deaths, 9.1% of all deaths between the ages of 35-80, were attributable to known diabetes. If cases of unknown diabetes were considered, this figure would rise to 14.3%. In contrast, based on death certificates only, 5.3% of all death had diabetes as the underlying cause and 10.4% as any mentioned cause.

CONCLUSIONS

In this first report of diabetes mortality burden in Brazil using cohort data to estimate diabetes mortality rate ratios and the prevalence of unknown diabetes, we showed marked underestimation of the current burden, especially when unknown cases of diabetes are also considered.

Prevalence of diagnosed diabetes in American Indian and Alaska Native adults, 2006-2017

INTRODUCTION

The objective of this study was to examine recent trends in diagnosed diabetes prevalence for American Indian and Alaska Native (AI/AN) adults aged 18 years and older in the Indian Health Service (IHS) active clinical population.

RESEARCH DESIGN AND METHODS

Data were extracted from the IHS National Data Warehouse for AI/AN adults for each fiscal year from 2006 (n=729 470) through 2017 (n=1 034 814). The prevalence of diagnosed diabetes for each year and the annual percentage change were estimated for adults overall, as well as by sex, age group, and geographic region.

RESULTS

After increasing significantly from 2006 to 2013, diabetes prevalence for AI/AN adults in the IHS active clinical population decreased significantly from 2013 to 2017. Prevalence was 14.4% (95% CI 13.9% to 15.0%) in 2006; 15.4% (95% CI 14.8% to 16.0%) in 2013; and 14.6% (95% CI 14.1% to 15.2%) in 2017. Trends for men and women were similar to the overall population, as were those for all age groups. For all geographic regions, prevalence either decreased significantly or leveled off in recent years.

CONCLUSIONS

Diabetes prevalence in AI/AN adults in the IHS active clinical population has decreased significantly since 2013. While these results cannot be generalized to all AI/AN adults in the USA, this study documents the first known decrease in diabetes prevalence for AI/AN people.

Prevalence of diabetes mellitus at the end of life: An investigation using individually linked cause-of-death and medical register data

AIMS

Although diabetes mellitus at the end of life is associated with complex care, its end-of-life prevalence is uncertain. Our aim is to estimate diabetes prevalence in the end-of-life population, to evaluate which medical register has the largest added value to cause-of-death data in detecting diabetes cases, and to assess the extent to which reporting of diabetes as a cause of death is associated with disease severity.

METHODS

Our study population consisted of deaths in the Netherlands (2015-2016) included in Nivel Primary Care Database (Nivel-PCD; N = 18,162). The proportion of deaths with diabetes (Type 1 or 2) within the last two years of life was calculated using individually linked cause-of-death, general practice, medication, and hospital discharge data. Severity status of diabetes was defined with dispensed medicines.

RESULTS

According to all data sources combined, 28.7% of the study population had diabetes at the end of life. The estimated end-of-life prevalence of diabetes was 7.7% using multiple cause-of-death data only. Addition of general practice data increased this estimate the most (19.7%-points). Of the cases added by primary care data, 76.3% had a severe or intermediate status.

CONCLUSIONS

More than one fourth of the Dutch end-of-life population has diabetes. Cause-of-death data are insufficient to monitor this prevalence, even of severe cases of diabetes, but could be enriched particularly with general practice data.

The prevalence of undiagnosed type 2 diabetes and prediabetes in Eastern Mediterranean region (EMRO): A systematic review and meta-analysis

BACKGROUND

Previous studies of diabetes in Eastern Mediterranean Region (EMRO) did not assess the prevalence of either unknown diabetes or prediabetes. We conducted a systematic review and meta-analysis to estimate the prevalence of undiagnosed type 2 diabetes and prediabetes as well as variations by region in EMRO, using the relevant publications since 2000.

METHODS

We carried out a comprehensive electronic search on electronic databases from January 1, 2000 to March 1, 2018. We selected cross-sectional and cohort studies reporting the prevalence of undiagnosed type 2 diabetes, prediabetes, or both. Two independent reviewers initially screened the eligible articles; then, synthesized the target data from full papers. Random- or fixed-effect models, subgroup analysis on Human Development Index (HDI), and publication year and sensitivity analysis to minimize the plausible effect of outliers were used.

RESULTS

Amongst 849 identified citations, 55 articles were entered into meta-analysis, involving 567,025 individuals. The forest plots estimated 5.46% (confidence intervals [CI]: 4.77-6.14) undiagnosed diabetic and 12.19% (CI: 10.13-14.24) prediabetics in EMRO. Low HDI countries and high HDI countries had the highest (7.25%; CI: 4.59-9.92) and the lowest (3.98%; CI: 3.11-4.85) undiagnosed diabetes prevalence, respectively. Very high HDI countries and low HDI countries had the highest (13.50%; CI: 8.43-18.57) and the lowest (7.45%; 1.20-13.71) prediabetes prevalence, respectively. In addition, meta-regression analysis showed a statistically significant association between publication year and prevalence of prediabetes (Reg Coef = 0.059, P = 0.014). But such finding was not observed for undiagnosed diabetes and publication year (Reg Coef = 0.034, P = 0.124), prediabetes and HDI (Reg Coef = 0.128, P = 0.31) and undiagnosed diabetes and HDI (Reg Coef = - 0.04, P = 0.96).

CONCLUSION

The prevalence of undiagnosed diabetes and prediabetes was high and increasing. The notion of universal health coverage is a priority; that is the integration of the primary, secondary and tertiary health levels, as well as employing the available action plans. Therefore, future studies, using identical screening tool and diagnostic criteria, are warranted to make an accurate picture of diabetes in EMRO.

Trends in overall, cardiovascular and cancer-related mortality among individuals with diabetes reported on death certificates in the United States between 2007 and 2017

AIMS/HYPOTHESIS

The determination of diabetes as underlying cause of death by using the death certificate may result in inaccurate estimation of national mortality attributed to diabetes, because individuals who die with diabetes generally have other conditions that may contribute to their death. We investigated the trends in age-standardised mortality due to diabetes as underlying or contributing cause of death and cause-specific mortality from cardiovascular disease (CVD), complications of diabetes and cancer among individuals with diabetes listed on death certificates in the USA from 2007 to 2017.

METHODS

Using the US Census and national mortality database, we calculated age-standardised mortality due to diabetes as underlying or contributing cause of death and cause-specific mortality rates among adults over 20 years with diabetes listed on death certificates. A total of 2,686,590 deaths where diabetes was underlying or contributing cause of death were analysed. We determined temporal mortality rate patterns by joinpoint regression analysis with estimates of annual percentage change (APC).

RESULTS

Age-standardised diabetes mortality rates compared among underlying cause of death, contributing cause of death and all-cause mortality were 32.2 vs 75.7 vs 105.1 per 100,000 individuals during the study period. The age-standardised mortality rates due to diabetes as underlying or contributing cause of death declined from 112.2 per 100,000 individuals in 2007 to 104.3 per 100,000 individuals in 2017 with the most pronounced decline noted from 2007 to 2014 (APC -1.4%; 95% CI -1.9%, -1.0%) and stabilisation in decline from 2014 to 2017 (APC 1.1%; 95% CI -0.6%, 2.8%). In terms of cause-specific mortality among individuals with diabetes listed on death certificates, the age-standardised mortality rates for CVD declined at an annual rate of 1.2% with a marked decline of 2.3% between 2007 and 2014. Age-standardised diabetes-specific mortality rates as underlying cause of death decreased from 2007 to 2009 (APC -4.5%) and remained stable from 2009 to 2017. Age-standardised mortality rates for cancer steadily decreased with an average APC of -1.4% (95% CI -1.8%, -1.0%) during the 11-year period. Mortality in the subcategory of CVD demonstrated significant differences.

CONCLUSIONS/INTERPRETATION

Current national estimates capture about 30% of all-cause mortality among individuals with diabetes listed as underlying or contributing cause of death on death certificates. The age-standardised mortality due to diabetes as underlying or contributing cause of death and cause-specific mortality from CVD in individuals with diabetes listed as underlying or contributing cause of death plateaued from 2014 onwards except for hypertensive heart disease and heart failure.

Public health monitoring of hypertension, diabetes and elevated cholesterol: comparison of different data sources

Background

Three data sources are generally used in monitoring health on the population level. Health interview surveys (HISs) are based on participants' self-report. Health examination surveys (HESs) yield more objective data, and also persons who are unaware of their elevated risks can be detected. Medical records (MRs) and other administrative registers also provide objective data, but their availability, coverage and quality vary between countries. We summarized studies comparing self-reported data with (i) measured data from HESs or (ii) MRs. We aimed to describe differences in feasibility and comparability of different data sources for monitoring (i) elevated blood pressure or hypertension (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol.

Methods

We conducted a literature search to identify studies, which validated self-reported measures against objective measures. We found 30 studies published since the year 2000 fulfilling our inclusion criteria (targeted to adults and comparing prevalence among the same persons).

Results

Hypertension and elevated total cholesterol were prone to be under-estimated in HISs. The under-estimate was more pronounced, when the HIS data were compared with HES data, and lower when compared with MRs. For diabetes, the HISs and the objective methods resulted in fairly similar prevalence rates.

Conclusion

The three data sources measure different manifestations of the risk factors and cannot be expected to yield similar prevalence rates. Using HIS data only may lead to under-estimation of elevated risk factor levels or disease prevalence. Whenever possible, information from the three data sources should be evaluated and combined.

Identifying diabetes cases in health administrative databases: a validation study based on a large French cohort

OBJECTIVES

In the French national health insurance information system (SNDS) three diabetes case definition algorithms are applied to identify diabetic patients. The objective of this study was to validate those using data from a large cohort.

METHODS

The CONSTANCES cohort (Cohorte des consultants des Centres d'examens de santé) comprises a randomly selected sample of adults living in France. Between 2012 and 2014, data from 45,739 participants recorded in a self-administrated questionnaire and in a medical examination were linked to the SNDS. Two gold standards were defined: known diabetes and pharmacologically treated diabetes. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) and kappa coefficients (k) were estimated.

RESULTS

All three algorithms had specificities and NPV over 99%. Their sensitivities ranged from 73 to 77% in algorithm A, to 86 and 97% in algorithm B and to 93 and 99% in algorithm C, when identifying known and pharmacologically treated diabetes, respectively. Algorithm C had the highest k when using known diabetes as the gold standard (0.95). Algorithm B had the highest k (0.98) when testing for pharmacologically treated diabetes.

CONCLUSIONS

The SNDS is an excellent source for diabetes surveillance and studies on diabetes since the case definition algorithms applied have very good test performances.

Considerations in Epidemiologic Definitions of Undiagnosed Diabetes

Accurately quantifying undiagnosed type 2 diabetes is an important challenge for conducting diabetes surveillance and identifying the potential missed opportunities for preventing complications. However, there has been little focused attention on how undiagnosed diabetes is defined in epidemiologic surveys and how limitations in methods used to ascertain undiagnosed diabetes may impact our understanding of the magnitude of this important public health problem. This Perspective highlights weaknesses in how undiagnosed diabetes is quantified in epidemiologic research and the biases and caveats that should be considered when using estimates of undiagnosed diabetes to influence public health policy.

Maternal diabetes mellitus and timing of pubertal development in daughters and sons: a nationwide cohort study

OBJECTIVE

To study the association between maternal diabetes and timing of pubertal development in daughters and sons.

DESIGN

Prospective cohort study.

SETTING

Not applicable.

PATIENT(S)

A total of 15,822 mother-child pairs included in the Danish National Birth Cohort and the Puberty Cohort with prospectively collected, register-based and self-reported information on maternal diabetes and self-reported information on pubertal development.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Adjusted mean monthly difference in age at attaining pubertal milestones in children born of mothers with diabetes compared with children born of mothers without diabetes.

RESULT(S)

A total of 502 children were born of mothers with diabetes during pregnancy. In daughters exposed to gestational diabetes mellitus, we observed advanced onset in all pubertal milestones. The associations were statistically significant with regard to pubic hair Tanner stage 2 (-4.8 months) (95% confidence interval [CI] -7.7, -2.0), pubic hair Tanner stage 3 (-2.2 months) (95 % CI -4.4, 0.0), pubic hair Tanner stage 5 (-6.0 months) (95% CI -10.8, -1.2), and menarche (-2.5 months) (95 % CI -4.9, 0.0). We observed no tendencies between maternal type 1 or type 2 diabetes mellitus and pubertal development in daughters. We observed no associations between maternal diabetes and pubertal development in sons.

CONCLUSION(S)

Our findings suggest that gestational diabetes mellitus may accelerate the pubertal development in daughters. Our results did not support an association between type 1 or type 2 diabetes mellitus and daughters' pubertal development, as well as between any type of maternal diabetes and sons' pubertal development.

Prevalence and management of diabetes in immigrants resident in the Lombardy Region: the importance of ethnicity and duration of stay

AIMS

To describe the prevalence and management of diabetes among immigrants according to ethnic group and duration of stay, compared to Italian citizens.

METHODS

Diabetic immigrant and Italian residents aged 20-69 years in the administrative database of the Lombardy Region. Immigrants were classified by region of origin and as long-term residents (LTR) and short-term residents (STR). Age- and sex-adjusted prevalence and indicators of diabetes management were calculated for immigrants by region of origin and by length of stay using Cox proportional models.

RESULTS

In 2010 19,992 immigrants (mean age 49.1 ± 10.8, 53.7% males) and 195,049 Italians (mean age 58.7 ± 9.3, 61.1 males) with diabetes were identified. Immigrants had a higher adjusted diabetes prevalence than Italians (OR 1.48; 95% CI 1.45-1.50). STR received significantly fewer recommended cardiovascular drugs (antiplatelets, statins and ACE-inhibitors/ARBs) than Italians, although prescription was higher among LTR from some ethnic groups. Immigrants were less likely to be seen by a diabetologist and to do at least one HbA1c test per year. Although the recommended tests/visits were more often done for the LTR than the STR, in the majority of ethnic groups these indicators were still far from optimal.

CONCLUSION

The prevalence and management of diabetes differ between immigrants and Italians, although some improvement can be seen among LTR.

All-cause mortality in adults with and without type 2 diabetes: findings from the national health monitoring in Germany

OBJECTIVE

To estimate age-specific and sex-specific all-cause mortality among adults with and without type 2 diabetes (T2D) in Germany.

RESEARCH DESIGN AND METHODS

The German National Health Interview and Examination Survey 1998 (GNHIES98) included a mortality follow-up (median follow-up time 12.0 years) of its nationwide sample representative of the population aged 18-79 years. After exclusion of participants with type 1 diabetes, age- and sex-stratified mortality rates (MR) were calculated for 330 GNHIES98 participants with diagnosed T2D (self-reported diagnosis or antidiabetic medication), 245 with undiagnosed T2D (no diagnosed T2D, glycated hemoglobin A1c ≥6.5% (≥48 mmol/mol)), and 5975 without T2D. Mortality rate ratios (MRR) comparing MR of persons with and without T2D were estimated. Age-/sex-standardized MR and MRR were calculated including persons aged 45 years or older. MRR were used to estimate the number of years of life lost (YLL) due to diagnosed diabetes in 2010.

RESULTS

Over 75 994 person-years, 73 persons with undiagnosed T2D, 103 with diagnosed T2D, and 425 persons without T2D died. MRR were significantly higher in younger age groups, except for analyses limited to women or diagnosed T2D. Age- and sex-standardized MRR (95% CI) among persons aged 45 years or older were 1.96 (1.41 to 2.71) for undiagnosed, 1.68 (1.26 to 2.23) for diagnosed, and 1.82 (1.45 to 2.28) for total (undiagnosed or diagnosed) T2D. Sex-stratified analysis revealed similar age-standardized MRR for undiagnosed (1.56 (0.79 to 3.06)) and diagnosed T2D (1.56 (1.03 to 2.37)) among women, and a higher age-standardized MRR for undiagnosed (2.06 (1.43 to 2.97)) than diagnosed T2D (1.70 (1.10 to 2.63)) among men. YLL due to diagnosed diabetes in Germany in 2010 were 164 600 (35 000 to 279 300) among women and 169 900 (28 300 to 328 300) among men.

CONCLUSIONS

In Germany, age- and sex-standardized all-cause mortality is almost twice as high for adults with T2D as for adults without T2D. The T2D-associated excess risk of mortality appears to be most pronounced in younger adults and among men unaware of their T2D.

Trends in dietary intake among adults with type 2 diabetes: NHANES 1988-2012

BACKGROUND

Dietary recommendations for adults with diabetes are to follow a healthy diet in appropriate portion sizes. We determined recent trends in energy and nutrient intakes among a nationally representative sample of US adults with and without type 2 diabetes.

METHODS

Participants were adults aged ≥20 years from the cross-sectional National Health and Nutrition Examination Surveys, 1988-2012 (N = 49 770). Diabetes was determined by self-report of a physician's diagnosis (n = 4885). Intake of energy and nutrients were determined from a 24-h recall by participants of all food consumed. Linear regression was used to test for trends in mean intake over time for all participants and by demographic characteristics.

RESULTS

Among adults with diabetes, overall total energy intake increased between 1988-1994 and 2011-2012 (1689 kcal versus 1895 kcal; Ptrend < 0.001) with evidence of a plateau between 2003-2006 and 2011-2012. In 2007-2012, energy intake was greater for younger than older adults, for men than women, and for non-Hispanic whites versus non-Hispanic blacks. There was no change in the percentage of calories from carbohydrate, total fat or protein. Percentage of calories from saturated fat was similar across study periods but remained above recommendations (11.2% in 2011-2012). Fibre intake significantly decreased and remained below recommendations (Ptrend = 0.002). Sodium, cholesterol and calcium intakes increased. There was no change in energy intake among adults without diabetes and dietary trends were similar to those with diabetes.

CONCLUSIONS

Future data are needed to confirm a plateau in energy intake among adults with diabetes, although the opportunity exists to increase fibre and reduce saturated fat.

Correcting hazard ratio estimates for outcome misclassification using multiple imputation with internal validation data

OBJECTIVE

Outcome misclassification may occur in observational studies using administrative databases. We evaluated a two-step multiple imputation approach based on complementary internal validation data obtained from two subsamples of study participants to reduce bias in hazard ratio (HR) estimates in Cox regressions.

METHODS

We illustrated this approach using data from a surveyed sample of 6247 individuals in a study of statin-diabetes association in Quebec. We corrected diabetes status and onset assessed from health administrative data against self-reported diabetes and/or elevated fasting blood glucose (FBG) assessed in subsamples. The association between statin use and new onset diabetes was evaluated using administrative data and the corrected data. By simulation, we assessed the performance of this method varying the true HR, sensitivity, specificity, and the size of validation subsamples.

RESULTS

The adjusted HR of new onset diabetes among statin users versus non-users was 1.61 (95% confidence interval: 1.09-2.38) using administrative data only, 1.49 (0.95-2.34) when diabetes status and onset were corrected based on self-report and undiagnosed diabetes (FBG ≥ 7 mmol/L), and 1.36 (0.92-2.01) when corrected for self-report and undiagnosed diabetes/impaired FBG (≥ 6 mmol/L). In simulations, the multiple imputation approach yielded less biased HR estimates and appropriate coverage for both non-differential and differential misclassification. Large variations in the corrected HR estimates were observed using validation subsamples with low participation proportion. The bias correction was sometimes outweighed by the uncertainty introduced by the unknown time of event occurrence.

CONCLUSION

Multiple imputation is useful to correct for outcome misclassification in time-to-event analyses if complementary validation data are available from subsamples. Copyright © 2017 John Wiley & Sons, Ltd.

Validity of type 2 diabetes diagnosis in a population-based electronic health record database

Background

The increasing burden of type 2 diabetes mellitus makes the continuous surveillance of its prevalence and incidence advisable. Electronic health records (EHRs) have great potential for research and surveillance purposes; however the quality of their data must first be evaluated for fitness for use. The aim of this study was to assess the validity of type 2 diabetes diagnosis in a primary care EHR database covering more than half a million inhabitants, 97% of the population in Navarra, Spain.

Methods

In the Navarra EPIC-InterAct study, the validity of the T90 code from the International Classification of Primary Care, Second Edition was studied in a primary care EHR database to identify incident cases of type 2 diabetes, using a multi-source approach as the gold standard. The sensitivity, specificity, positive predictive value, negative predictive value and the kappa index were calculated. Additionally, type 2 diabetes prevalence from the EHR database was compared with estimations from a health survey.

Results

The sensitivity, specificity, positive predictive value and negative predictive value of incident type 2 diabetes recorded in the EHRs were 98.2, 99.3, 92.2 and 99.8%, respectively, and the kappa index was 0.946. Overall prevalence of type 2 diabetes diagnosed in the EHRs among adults (35–84 years of age) was 7.2% (95% confidence interval [CI] 7.2–7.3) in men and 5.9% (95% CI 5.8–5.9) in women, which was similar to the prevalence estimated from the health survey: 8.5% (95% CI 7.1–9.8) and 5.5% (95% CI 4.4–6.6) in men and women, respectively.

Conclusions

The high sensitivity and specificity of type 2 diabetes diagnosis found in the primary care EHRs make this database a good source for population-based surveillance of incident and prevalent type 2 diabetes, as well as for monitoring quality of care and health outcomes in diabetic patients.

Deaths Attributable to Diabetes in the United States: Comparison of Data Sources and Estimation Approaches

Objective

The goal of this research was to identify the fraction of deaths attributable to diabetes in the United States.

Research Design and Methods

We estimated population attributable fractions (PAF) for cohorts aged 30–84 who were surveyed in the National Health Interview Survey (NHIS) between 1997 and 2009 (N = 282,322) and in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2010 (N = 21,814). Cohort members were followed prospectively for mortality through 2011. We identified diabetes status using self-reported diagnoses in both NHIS and NHANES and using HbA1c in NHANES. Hazard ratios associated with diabetes were estimated using Cox model adjusted for age, sex, race/ethnicity, educational attainment, and smoking status.

Results

We found a high degree of consistency between data sets and definitions of diabetes in the hazard ratios, estimates of diabetes prevalence, and estimates of the proportion of deaths attributable to diabetes. The proportion of deaths attributable to diabetes was estimated to be 11.5% using self-reports in NHIS, 11.7% using self-reports in NHANES, and 11.8% using HbA1c in NHANES. Among the sub-groups that we examined, the PAF was highest among obese persons at 19.4%. The proportion of deaths in which diabetes was assigned as the underlying cause of death (3.3–3.7%) severely understated the contribution of diabetes to mortality in the United States.

Conclusion

Diabetes may represent a more prominent factor in American mortality than is commonly appreciated, reinforcing the need for robust population-level interventions aimed at diabetes prevention and care.

Validity of hospital discharge records to identify pregestational diabetes in an Italian population

AIMS

In recent years, the prevalence of pregestational diabetes (PGDM) and the concern about the possibility of adverse pregnancy outcomes in affected women have been increasing. Routinely collected health data represent a timely and cost-efficient approach in PGDM epidemiological research. This study aims to evaluate the reliability of hospital discharge (HD) coding to identify a population-based cohort of pregnant women with PGDM and to assess trends in prevalence in two provinces of Northern Italy.

METHODS

We selected all deliveries occurred in the period 1997-2010 with ICD-9-CM codes for PGDM in HD record and we matched up to 5 controls from mothers without diabetes. We used Diabetes Registers (DRs) as the gold standard for validation analysis.

RESULTS

We selected 3800 women, 653 with diabetes and 3147 without diabetes. The agreement between HD records and DRs was 90.7%, with K=0.58. We detected 350 false positives and only 1 false negative. Sensitivity was 99.3%, specificity 90.0%, positive predictive value 46.4% and negative predictive value 99.9%. Of the false positives, 48.6% had gestational diabetes and 2.3% impaired glucose tolerance. After the validation process, PGDM prevalence decreased from 4.4 to 2.0 per 1000 deliveries.

CONCLUSIONS

Our results show that HD facilitate detection of almost all PGDM cases, but they also include a large number of false positives, mainly due to gestational diabetes. This misclassification causes a large overestimation of PGMD prevalence. Our findings require accuracy evaluation of ICD-9-CM codes, before they can be widely applied to epidemiological research and public health surveillance related to PGDM.

Ethnic admixture affects diabetes risk in native Hawaiians: the Multiethnic Cohort

BACKGROUND/OBJECTIVES

Obesity and diabetes rates are high in Native Hawaiians (NHs) who commonly have mixed ancestries. People of Asian ancestry experience a high risk of type 2 diabetes despite the relatively low body weight. We evaluated the impact of ethnic admixture on diabetes risk among NHs in the Multiethnic Cohort (MEC).

SUBJECTS/METHODS

On the basis of self-reports, 11 521 eligible men and women were categorized into NH/white, NH/other, NH alone, NH/Asian and the most common three ancestry admixture, NH/Chinese/white. Cox proportional hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated with the NH/white category as the reference group; covariates included known confounders-that is, body mass index (BMI), dietary and other lifestyle factors.

RESULTS

The NH alone category had the highest proportion of overweight and obese individuals and the NH/Asian category the lowest proportion. During 12 years of follow-up after cohort entry at 56 years, 2072 incident cases were ascertained through questionnaires and health plan linkages. All NH categories had higher HRs than the NH/white category before and after adjustment for BMI. In the fully adjusted models, the NH/Asian category showed the highest risk (HR=1.45; 95% CI: 1.27-1.65), followed by NH/other (HR=1.20; 95% CI: 1.03-1.39), NH/Chinese/white (HR=1.19; 95% CI: 1.04-1.37) and NH alone (HR=1.19; 95% CI: 1.03-1.37). The elevated risk by Asian admixture was more pronounced in normal weight than overweight/obese individuals.

CONCLUSIONS

These findings indicate that Asian admixture in NHs is associated with a higher risk for type 2 diabetes independent of known risk factors and suggest a role for ethnicity-related genetic factors in the development of this disease.

Effect of change in coding rules on recording diabetes in hospital administrative datasets

AIM

During 2008-2011 Australian Coding Standards mandated a causal relationship between diabetes and inpatient care as a criterion for recording diabetes as a comorbidity in hospital administrative datasets. We aim to measure the effect of the causality mandate on recorded diabetes and associated inter-hospital variations.

METHOD

For patients with diabetes, all admissions between 2004 and 2013 to all New South Wales acute public hospitals were investigated. Poisson mixed models were employed to derive adjusted rates and variations.

RESULTS

The non-recorded diabetes incidence rate was 20.7%. The causality mandate increased the incidence rate four fold during the change period, 2008-2011, compared to the pre- or post-change periods (32.5% vs 8.4% and 6.9%). The inter-hospital variation was also higher, with twice the difference in the non-recorded rate between hospitals with the highest and lowest rates (50% vs 24% and 27% risk gap). The variation decreased during the change period (29%), while the rate continued to rise (53%). Admission characteristics accounted for over 44% of the variation compared with at most two per cent attributable to patient or hospital characteristics. Contributing characteristics explained less of the variation within the change period compared to pre- or post-change (46% vs 58% and 53%). Hospital relative performance was not constant over time.

CONCLUSION

The causality mandate substantially increased the non-recorded diabetes rate and associated inter-hospital variation. Longitudinal accumulation of clinical information at the patient level, and the development of appropriate adoption protocols to achieve comprehensive and timely implementation of coding changes are essential to supporting the integrity of hospital administrative datasets.

How Reliable Are Current Data for Assessing the Actual Prevalence of Chronic Obstructive Pulmonary Disease?

Background

Estimating COPD occurrence is perceived by the scientific community as a matter of increasing interest because of the worldwide diffusion of the disease. We aimed to estimate COPD prevalence by using administrative databases from a city in central Italy for 2002–2006, improving both the sensitivity and the reliability of the estimate.

Methods

Multiple sources were used, integrating the hospital discharge register (HDR), clinical charts, spirometry and the cause-specific mortality register (CMR) in a longitudinal algorithm, to reduce underestimation of COPD prevalence. Prevalence was also estimated on the basis of COPD cases confirmed through spirometry, to correct misclassification. Estimating such prevalence relied on using coefficients of validation, derived as the positive predictive value (PPV) for being an actual COPD case from clinical and spirometric data at the Institute of Clinical Physiology of the National Research Council.

Results

We found that sensitivity of COPD prevalence increased by 37%. The highest estimate (4.43 per 100 residents) was observed in the 5-year period, using a 3-year longitudinal approach and combined data from three sources. We found that 17% of COPD cases were misclassified. The above estimate of COPD prevalence decreased (3.66 per 100 residents) when coefficients of validation were applied. The PPV was 80% for the HDR, 82% for clinical diagnoses and 91% for the CMR.

Conclusions

Adjusting the COPD prevalence for both underestimation and misclassification of the cases makes administrative data more reliable for epidemiological purposes.

Mortality rates and the causes of death related to diabetes mellitus in Shanghai Songjiang District: an 11-year retrospective analysis of death certificates

BACKGROUND

China is one of the countries with the highest prevalence of diabetes in the world. We analysed all the death certificates mentioning diabetes from 2002 to 2012 in Songjiang District of Shanghai to estimate morality rates and examine cause of death patterns.

METHODS

Mortality data of 2654 diabetics were collected from the database of local CDC. The data set comprises all causes of death, contributing causes and the underlying cause, thereby the mortality rates of diabetes and its specified complications were analysed.

RESULTS

The leading underlying causes of death were various cardiovascular diseases (CVD), which collectively accounted for about 30% of the collected death certificates. Diabetes was determined as the underlying cause of death on 28.7%. The trends in mortality showed that the diabetes related death rate increased about 1.78 fold in the total population during the 11-year period, and the death rate of diabetes and CVD comorbidity increased 2.66 fold. In all the diabetes related deaths, the proportion of people dying of ischaemic heart disease or cerebrovascular disease increased from 18.0% in 2002 to 30.5% in 2012. But the proportions attributed directly to diabetes showed a downtrend, from 46.7-22.0%.

CONCLUSIONS

The increasing diabetes related mortality could be chiefly due to the expanding prevalence of CVD, but has nothing to do with diabetes as the underlying cause. Policy makers should pay more attention to primary prevention of diabetes and on the prevention of cardiovascular complications to reduce the burden of diabetes on survival.

Vital Signs: Predicted Heart Age and Racial Disparities in Heart Age Among U.S. Adults at the State Level

INTRODUCTION

Cardiovascular disease is a leading cause of morbidity and mortality in the United States. Heart age (the predicted age of a person's vascular system based on their cardiovascular risk factor profile) and its comparison with chronological age represent a new way to express risk for developing cardiovascular disease. This study estimates heart age and differences between heart age and chronological age (excess heart age) and examines racial, sociodemographic, and regional disparities in heart age among U.S. adults aged 30-74 years.

METHODS

Weighted 2011 and 2013 Behavioral Risk Factor Surveillance System data were applied to the sex-specific non-laboratory-based Framingham risk score models, stratifying the results by age and race/ethnic group, educational and income level, and state. These results were then translated into age-standardized heart age values, mean excess heart age was calculated, and the findings were compared across groups.

RESULTS

Overall, average predicted heart age for adult men and women was 7.8 and 5.4 years older than their chronological age, respectively. Statistically significant (p<0.05) racial/ethnic, sociodemographic, and regional differences in heart age were observed: heart age among non-Hispanic black men (58.7 years) and women (58.9 years) was greater than other racial/ethnic groups, including non-Hispanic white men (55.3 years) and women (52.5 years). Excess heart age was lowest for men and women in Utah (5.8 and 2.8 years, respectively) and highest in Mississippi (10.1 and 9.1 years, respectively).

CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE

The predicted heart age among U.S. adults aged 30-74 years was significantly higher than their chronological age. Use of predicted heart age might 1) simplify risk communication and motivate more persons to live heart-healthy lifestyles and better comply with recommended therapeutic interventions, and 2) motivate communities to implement programs and policies that support cardiovascular health.

A prediction model to estimate completeness of electronic physician claims databases

OBJECTIVES

Electronic physician claims databases are widely used for chronic disease research and surveillance, but quality of the data may vary with a number of physician characteristics, including payment method. The objectives were to develop a prediction model for the number of prevalent diabetes cases in fee-for-service (FFS) electronic physician claims databases and apply it to estimate cases among non-FFS (NFFS) physicians, for whom claims data are often incomplete.

DESIGN

A retrospective observational cohort design was adopted.

SETTING

Data from the Canadian province of Newfoundland and Labrador were used to construct the prediction model and data from the province of Manitoba were used to externally validate the model.

PARTICIPANTS

A cohort of diagnosed diabetes cases was ascertained from physician claims, insured resident registry and hospitalisation records. A cohort of FFS physicians who were responsible for the diagnosis was ascertained from physician claims and registry data.

PRIMARY AND SECONDARY OUTCOME MEASURES

A generalised linear model with a γ distribution was used to model the number of diabetes cases per FFS physician as a function of physician characteristics. The expected number of diabetes cases per NFFS physician was estimated.

RESULTS

The diabetes case cohort consisted of 31,714 individuals; the mean cases per FFS physician was 75.5 (median = 49.0). Sex and years since specialty licensure were significantly associated (p < 0.05) with the number of cases per physician. Applying the prediction model to NFFS physician registry data resulted in an estimate of 18,546 cases; only 411 were observed in claims data. The model demonstrated face validity in an independent data set.

CONCLUSIONS

Comparing observed and predicted disease cases is a useful and generalisable approach to assess the quality of electronic databases for population-based research and surveillance.

Multiple causes of death analysis of chronic diseases: the example of diabetes

BACKGROUND

Identifying a single disease as the underlying cause of death (UCOD) is an oversimplification of the clinical-pathological process leading to death. The multiple causes of death (MCOD) approach examines any mention of a disease in death certificates. Taking diabetes as an example, the study investigates: patterns of death certification, differences in mortality figures based on the UCOD and on MCOD, factors associated to the mention of diabetes in death certificates, and potential of MCOD in the analysis of the association between chronic diseases.

METHODS

The whole mortality archive of the Veneto Region-Italy was extracted from 2008 to 2010. Mortality rates and proportional mortality were computed for diabetes as the UCOD and as MCOD. The position of the death certificate where diabetes was mentioned was analyzed. Conditional logistic regression was applied with chronic liver diseases (CLD) as the outcome and diabetes as the exposure variable. A subset of 19,605 death certificates of known diabetic patients (identified from the archive of exemptions from medical charges) was analyzed, with mention of diabetes as the outcome and characteristics of subjects as well as other diseases reported in the certificate as predictors.

RESULTS

In the whole mortality archive, diabetes was mentioned in 12.3 % of death certificates, and selected as the UCOD in 2.9 %. The death rate for diabetes as the UCOD was 26.8 × 10(5) against 112.6 × 10(5) for MCOD; the UCOD/MCOD ratio was higher in males. The major inconsistencies of certification were entering multiple diseases per line and reporting diabetes as a consequence of circulatory diseases. At logistic regression the mention of diabetes was associated with the mention of CLD (mainly non-alcohol non-viral CLD). In the subset of known diabetic subjects, diabetes was reported in 52.1 %, and selected as the UCOD in 13.4 %. The probability of reporting diabetes was higher with coexisting circulatory diseases and renal failure and with long duration of diabetes, whereas it was lower in the presence of a neoplasm.

CONCLUSIONS

The use of MCOD makes the analysis of mortality data more complex, but conveys more information than usual UCOD analyses.

[Mortality follow-up of the German Health Interview and Examination Survey for Adults (DEGS) : methods and first results]

OBJECTIVES

Within the framework of the German Health Interview and Examination Survey for Adults (DEGS), the Robert Koch Institute (RKI) conducted a nationwide mortality follow-up study. As there is no national mortality register in Germany, mortality and causes of death were investigated individually and under observance of state-specific data protection conditions.

METHODS

The German Health Interview and Examination Survey 1998 (GNHIES98) provided the database including 7,124 participants aged 18-79 years. A total of 6,979 participants of GNHIES98 (98 %) who consented to be re-contacted were invited between October 2008 and October 2011 to also participate in the first data collection wave of DEGS (DEGS1). In this context, the vital status and the causes of death for deceased participants were assessed. Age- and sex-specific probabilities of survival and death rates were calculated and grouped by main causes of death according to ICD-10 groups.

RESULTS

A total of 671 individuals (285 women, 386 men) died between the two survey contacts. For all deceased persons the date of death and for 539 (80.3 %) the causes of death could be determined. With a median follow-up time of 12.0 years, 8,0742.5 person years were available for survival analysis. The crude overall death rate amounted to 8.3 per 1,000 persons-years (women: 7.2; men: 9.5). Among 539 persons with available information on causes of death, 209 (38.8 %) were attributable to cardiovascular diseases, 188 (34.9 %) to cancer, 135 (25.0 %) to other causes, and seven (1.3 %) could not be unambiguously assigned.

CONCLUSIONS

A mortality follow-up was successfully integrated in the longitudinal component of DEGS as part of the national health monitoring at the RKI. Death rates and cause-specific mortality in relation to highly prevalent chronic diseases and risk factors provide essential information for assessing the potential of prevention and quality of care among adults in Germany. This requires a regular and complete conduction of mortality follow-ups.

Random blood glucose: a robust risk factor for type 2 diabetes

CONTEXT

Although random blood glucose (RBG) values are common in clinical practice, the role of elevated RBG values as a risk factor for type 2 diabetes is not well described.

OBJECTIVE

This study aimed to examine nondiagnostic, RBG values as a risk factor for type 2 diabetes

DESIGN

This was a cross-sectional study of National Health and Nutrition Examination Surveys (NHANES) participants (2005-2010).

PARTICIPANTS

Nonfasting NHANES participants (n = 13 792) without diagnosed diabetes were included.

PRIMARY OUTCOME

The primary outcome was glycemic status (normal glycemia, undiagnosed prediabetes, or undiagnosed diabetes) using hemoglobin HbA1C as the criterion standard.

ANALYSIS

Multinomial logistic regression examined associations between diabetes risk factors and RBG values according to glycemic status. Associations between current U.S. screening strategies and a hypothetical RBG screening strategy with undiagnosed diabetes were examined.

RESULTS

In unadjusted analyses, a single RBG ≥ 100 mg/dL (5.6 mmol/L) was more strongly associated with undiagnosed diabetes than any single risk factor (odds ratio [OR], 31.2; 95% confidence interval [CI], 21.3-45.5) and remained strongly associated with undiagnosed diabetes (OR, 20.4; 95% CI, 14.0-29.6) after adjustment for traditional diabetes risk factors. Using RBG < 100 mg/dL as a reference, the adjusted odds of undiagnosed diabetes increased significantly as RBG increased. RBG 100-119 mg/dL (OR 7.1; 95% CI 4.4-11.4); RBG 120-139 mg/dL (OR 30.3; 95% CI 20.0-46.0); RBG ≥ 140 mg/dL (OR 256; 95% CI 150.0-436.9). As a hypothetical screening strategy, an elevated RBG was more strongly associated with undiagnosed diabetes than current United States Preventative Services Task Force guidelines (hypertension alone; P < .0001) and similar to American Diabetes Association guidelines (P = .12).

CONCLUSIONS

A single RBG ≥ 100 mg/dL is more strongly associated with undiagnosed diabetes than traditional risk factors. Abnormal RBG values are a risk factor for diabetes and should be considered in screening guidelines.

Diabetes among US- and foreign-born blacks in the USA

OBJECTIVE

Little is known about diabetes status among US blacks by nativity. This study aims to measure differences in diabetes among US blacks by region of birth and examines potential explanations for subgroup differences.

DESIGN

Data from 47,751 blacks aged 25-74 pooled from the 2000-2013 waves of the National Health Interview Survey were analyzed. Logistic regression models predicted self-reported diabetes. The roles of education, income, body mass index (BMI), smoking, and duration of US residence were explored.

RESULTS

Compared to the US-born, foreign-born blacks had significantly lower reported diabetes prevalence (8.94% vs. 11.84%) and diabetes odds ratio [OR: 0.75; 95% confidence interval (CI): 0.62, 0.89], adjusting for socio-demographic characteristics. Further inclusion of education, income, household size, and smoking did not appreciably change the OR (0.77; 95% CI: 0.61, 0.86). Including an adjustment for BMI entirely eliminated the foreign-born advantage (OR 0.93; 95% CI: 0.78, 1.11). The foreign-born from the Caribbean/Americas had similar diabetes odds compared to the African-born. Among the foreign-born, an increased duration of US residence was associated with a higher diabetes odds, but these associations did not reach statistical significance (p > 0.05).

CONCLUSION

The healthy immigrant advantage extended to diabetes among US blacks, a finding that is explained by lower levels of overweight/obesity among the foreign-born compared to the US-born. Nonetheless, more than 71.4% of the foreign-born were overweight or obese. Understanding the mechanisms through which exposure to the US environment leads to higher obesity and diabetes risk may aid prevention efforts for the rapidly growing foreign-born black subpopulation.

Trends in diabetes incidence among 7 million insured adults, 2006-2011: the SUPREME-DM project

An observational cohort analysis was conducted within the Surveillance, Prevention, and Management of Diabetes Mellitus (SUPREME-DM) DataLink, a consortium of 11 integrated health-care delivery systems with electronic health records in 10 US states. Among nearly 7 million adults aged 20 years or older, we estimated annual diabetes incidence per 1,000 persons overall and by age, sex, race/ethnicity, and body mass index. We identified 289,050 incident cases of diabetes. Age- and sex-adjusted population incidence was stable between 2006 and 2010, ranging from 10.3 per 1,000 adults (95% confidence interval (CI): 9.8, 10.7) to 11.3 per 1,000 adults (95% CI: 11.0, 11.7). Adjusted incidence was significantly higher in 2011 (11.5, 95% CI: 10.9, 12.0) than in the 2 years with the lowest incidence. A similar pattern was observed in most prespecified subgroups, but only the differences for persons who were not white were significant. In 2006, 56% of incident cases had a glycated hemoglobin (hemoglobin A1c) test as one of the pair of events identifying diabetes. By 2011, that number was 74%. In conclusion, overall diabetes incidence in this population did not significantly increase between 2006 and 2010, but increases in hemoglobin A1c testing may have contributed to rising diabetes incidence among nonwhites in 2011.

Active life expectancy of Americans with diabetes: risks of heart disease, obesity, and inactivity

AIMS

Few researchers have studied whether diabetes itself is responsible for high rates of disability or mortality, or if factors associated with diabetes contribute importantly. We estimated associations of diabetes, heart disease, obesity, and physical inactivity with life expectancy (LE), the proportion of life with disability (DLE), and disability in the last year of life.

METHODS

Data were from the Panel Study of Income Dynamics (1999-2011 and 1986, African American and white women and men ages 55+, n=1,980, 17,352 person-years). Activities of daily living defined disability. Multinomial logistic Markov models estimated disability transition probabilities adjusted for age, sex, race/ethnicity, education, and the health factors. Microsimulation measured outcomes.

RESULTS

White women and men exemplify results. LE was, for women: 3.5 years less with diabetes than without (95% confidence interval, 3.1-4.0), 11.1 less (10.3-12.0) adding heart disease, 21.9 less with all factors (15.3-28.5), all p<0.001. Corresponding results for men: 1.7 years (0.9-2.3, not significant), 8.2 (6.8-9.5) and 18.1 (15.6-20.6), both p<0.001. DLE was, for women: 23.5% (21.7-25.4) with no risk factors, 27.1% (25.7-28.6) with diabetes alone, 34.6% (33.1-36.1) adding heart disease, 52.9% (38.9-66.8) with all factors, all p<0.001; for men: 13.2% (11.7-14.6), 16.3% (14.8-17.8, p<0.01); and 22.1% (20.5-23.7), 36.4% (25.0-47.8), both p<.001. Among people with diabetes, those with other conditions were much less likely to have no disability in the final year of life.

CONCLUSIONS

Much of the disability and mortality with diabetes was due to heart disease, obesity, and inactivity, risks that can be modified by health behaviors and medical care.

Is diabetes color-blind? Growth of prevalence of diagnosed diabetes in children through 2030

Diabetes knows no age and affects millions of individuals. Preventing diabetes in children is increasingly becoming a major health policy concern and focus. The objective of this study is to project the number of children, aged 0-17 years, with diagnosed diabetes in the United States through 2030, accounting for changing demography, and diabetes and obesity prevalence rates. The study team combined historic diabetes and obesity prevalence data with US child population estimates and projections. A times-series regression model was used to forecast future diabetes prevalence and to account for the relationship between the forecasted diabetes prevalence and the lagged prevalence of childhood obesity. Overall, the prevalence of diagnosed diabetes is projected to increase 67% from 0.22% in 2010 to 0.36% in 2030. Lagged obesity prevalence in Hispanic boys and non-Hispanic black girls was significantly associated with increasing future diabetes prevalence. The study results showed that a 1% increase in obesity prevalence among Hispanic boys from the previous year was significantly associated with a 0.005% increase in future prevalence of diagnosed diabetes in children (P ≤ 0.01). Likewise, a unit increase in obesity prevalence among non-Hispanic black girls was associated with a 0.003% increase in future diabetes prevalence (P < 0.05). Obesity rates for other race/ethnicity combinations were not associated with increasing future diabetes prevalence. To mitigate the continued threat posed by diabetes, serious discussions need to focus on the pediatric population, particularly non-Hispanic black girls and Hispanic boys whose obesity trends show the strongest associations with future diabetes prevalence in children.

Diabetes in US women on the rise independent of increasing BMI and other risk factors; a trend investigation of serial cross-sections

BACKGROUND

The epidemic of diabetes continues leaving an enormous and growing burden of chronic disease to public health. This study investigates this growing burden of diabetes independent of increasing BMI in a large population based female sample, 2006-2010.

METHODS

Serial cross-sectional data using the Behavioral Risk Factor Surveillance System (BRFSS) 2006-2010 surveys from 1,168,418 women. Diabetes was assessed by self-report of a physician diagnosis, and body mass index (BMI) was calculated based on self-reported height and weight.

RESULTS

Almost 60% of women responders had a BMI > 25 (defined as overweight or obese). Diabetes was reported in 16% of respondents whose BMI > 25, and in 4% of respondents with reported BMI ≤ 25. Overall, 11% of the women in this sample reported being diagnosed with diabetes, of whom 83% had a BMI > 25. BMI, physical activity, age, and race were each independently associated with diabetes (p-value < 0.05). The odds of reported diabetes increased each year independent of BMI, physical activity, age, and race.

CONCLUSIONS

After adjusting for age, race, physical activity, and year of survey response, results indicate a threefold increase in diabetes among respondents with a BMI > 25 (OR = 3.57; 95% CI = 3.52-3.63). Potentially more alarming was a notable increase in odds of diabetes across the years of study among women, implying a near 30 percent projected increase in odds of diabetes diagnoses by 2020. This is likely due to advances in diagnosis and treatment but also highlights a burden of disease that will have a growing and sustained impact on public health and healthcare systems.

Disparity in diabetes risk across Native Hawaiians and different Asian groups: the multiethnic cohort

We evaluated the impact of body mass index (BMI) and lifestyle risk factors on ethnic disparity in diabetes incidence among 89 198 Asian, Native Hawaiian, and white participants of the Multiethnic Cohort who completed multiple questionnaires. After 12 years of follow-up, 11 218 new cases were identified through self-report and health plan linkages. BMI was lowest in Chinese/Koreans, Japanese, and Filipinos (22.4, 23.5, and 23.9 kg/m(2)). Using Cox regression, the unadjusted hazard ratios were 1.9 (Chinese/Korean), 2.1 (Japanese, Mixed-Asian), 2.2 (Filipino), 2.5 (Native Hawaiian), and 2.6 (part-Asian) as compared with whites. With BMI added, the risk for Japanese, Filipinos, Chinese/Koreans, and mixed-Asians increased (8%-42%) but declined in part-Asians and Native Hawaiians (17%-31%). When lifestyle and dietary factors were also included, the risk was attenuated in all groups (6%-14%). Despite their lower BMI, Asian Americans have a higher diabetes risk than whites, but dietary and lifestyle factors do not account for the excess risk.

In-hospital mortality among patients with type 2 diabetes mellitus and acute myocardial infarction: results from the national inpatient sample, 2000-2010

Background

Case‐fatality rates in acute myocardial infarction (AMI) have significantly decreased; however, the prevalence of diabetes mellitus (DM), a risk factor for AMI, has increased. The purposes of the present study were to assess the prevalence and clinical impact of DM among patients hospitalized with AMI and to estimate the impact of important clinical characteristics associated with in‐hospital mortality in patients with AMI and DM.

Methods and Results

We used the National Inpatient Sample to estimate trends in DM prevalence and in‐hospital mortality among 1.5 million patients with AMI from 2000 to 2010, using survey data‐analysis methods. Clinical characteristics associated with in‐hospital mortality were identified using multivariable logistic regression. There was a significant increase in DM prevalence among AMI patients (year 2000, 22.2%; year 2010, 29.6%, P_trend<0.0001). AMI patients with DM tended to be older and female and to have more cardiovascular risk factors. However, age‐standardized mortality decreased significantly from 2000 (8.48%) to 2010 (4.95%) (P_trend<0.0001). DM remained independently associated with mortality (adjusted odds ratio 1.069, 95% CI 1.051 to 1.087; P<0.0001). The adverse impact of DM on in‐hospital mortality was unchanged over time. Decreased death risk over time was greatest among women and elderly patients. Among younger patients of both sexes, there was a leveling off of this decrease in more recent years.

Conclusions

Despite increasing DM prevalence and disease burden among AMI patients, in‐hospital mortality declined significantly from 2000 to 2010. The adverse impact of DM on mortality remained unchanged overall over time but was age and sex dependent.