Extended Family History of Diabetes and Autoimmune Diseases in Children With and Without Type 1 Diabetes

OBJECTIVE

To determine the extended family history of diabetes or autoimmune diseases in families with and without children having type 1 diabetes.

RESEARCH DESIGN AND METHODS

Three hundred case families and 381 control families were interviewed using structured questionnaires.

RESULTS

The proportion of case children having at least one relative with type 1 diabetes outside the nuclear family was higher than that of control children (50.3 vs. 31.8%, P < 0.001). The proportions of case and control children having relatives with type 2 diabetes or gestational diabetes were similar. Other autoimmune diseases occurred more frequently among the case children (9.7 vs. 1.1%, P < 0.001), in the case nuclear families (22.0 vs. 12.9%, P = 0.002) and in relatives outside the case nuclear family (72.0 vs. 62.2%, P = 0.007).

CONCLUSIONS

Type 1 diabetes and autoimmune diseases not only cluster in the nuclear families of children with type 1 diabetes but are also overrepresented in their extended families.First degree relatives of patients with type 1 diabetes clearly have an increased disease risk (1–5), but little information is available about the occurrence of type 1 diabetes outside the nuclear family (6). It is also unclear whether type 2 diabetes and gestational diabetes are more frequently present in the families of children with type 1 diabetes (7–9). Type 1 diabetes is known to be associated with other autoimmune diseases, but there is a scarcity of data on the frequency of autoimmune diseases among other family members (10).     

Pediatric Endocrinologists' Management of Children With Type 2 Diabetes

OBJECTIVE

To understand physician behaviors and attitudes in managing children with type 2 diabetes.

RESEARCH DESIGN AND METHODS

A survey was mailed to a nationwide sample of pediatric endocrinologists (PEs).

RESULTS

A total of 40% of PEs surveyed responded (211 of 527). Concordance with current monitoring guidelines varied widely, ranging from 36% (foot care) to 93% (blood pressure monitoring). Given clinical vignettes addressing hyperlipidemia, hypertension, and microalbuminuria, only 34% of PEs were fully concordant with current treatment guidelines. Reported barriers included concerns about patient adherence, insufficient scientific evidence about treatment, and lack of familiarity with current recommendations. Providers aged ≤45 years or in clinical practice <10 years reported significantly more aggressive management behaviors and had higher concordance with guidelines.

CONCLUSIONS

Screening and management of pediatric type 2 diabetes varied widely among PEs, suggesting opportunities for quality improvement. More aggressive management of type 2 diabetes among younger providers may be related to recent training when type 2 diabetes was more common.The incidence of type 2 diabetes in children is increasing (1), and children with type 2 diabetes are at high risk to develop diabetes-related complications, including hyperlipidemia, hypertension, and microalbuminuria (2–4). Despite limited scientific evidence, several consensus statements on the assessment and management of pediatric type 2 diabetes have been developed (4–6). Current understanding of physician management of pediatric type 2 diabetes is limited (7–10). We conducted a survey to better understand pediatric endocrinologists'' (PEs'') behaviors and attitudes related to the management of pediatric type 2 diabetes.     

Cost-Effectiveness of Bariatric Surgery for Severely Obese Adults With Diabetes

OBJECTIVE

To analyze the cost-effectiveness of bariatric surgery in severely obese (BMI ≥35 kg/m²) adults who have diabetes, using a validated diabetes cost-effectiveness model.

RESEARCH DESIGN AND METHODS

We expanded the Centers for Disease Control and Prevention–RTI Diabetes Cost-Effectiveness Model to incorporate bariatric surgery. In this simulation model, bariatric surgery may lead to diabetes remission and reductions in other risk factors, which then lead to fewer diabetes complications and increased quality of life (QoL). Surgery is also associated with perioperative mortality and subsequent complications, and patients in remission may relapse to diabetes. We separately estimate the costs, quality-adjusted life-years (QALYs), and cost-effectiveness of gastric bypass surgery relative to usual diabetes care and of gastric banding surgery relative to usual diabetes care. We examine the cost-effectiveness of each type of surgery for severely obese individuals who are newly diagnosed with diabetes and for severely obese individuals with established diabetes.

RESULTS

In all analyses, bariatric surgery increased QALYs and increased costs. Bypass surgery had cost-effectiveness ratios of $7,000/QALY and $12,000/QALY for severely obese patients with newly diagnosed and established diabetes, respectively. Banding surgery had cost-effectiveness ratios of $11,000/QALY and $13,000/QALY for the respective groups. In sensitivity analyses, the cost-effectiveness ratios were most affected by assumptions about the direct gain in QoL from BMI loss following surgery.

CONCLUSIONS

Our analysis indicates that gastric bypass and gastric banding are cost-effective methods of reducing mortality and diabetes complications in severely obese adults with diabetes.In recent years, bariatric surgery has emerged as a popular treatment to reduce body weight and improve obesity-related complications, particularly in the diabetic population. Several studies have shown that surgery can lead to significant weight loss, with excess body weight reduced by >50% (1,2). Although weight loss declines over time, the Swedish Obese Subjects (SOS) Study found significant weight loss even 10 years after surgery (3,4). In addition to sustained weight loss, bariatric surgery may provide additional benefits to people with diabetes. Among severely obese patients with diabetes, bariatric surgery often leads to diabetes remission, with remission rates that are as high as 80% in the short run (1) and that remain significant in the long run (3,4).Although the evidence suggests that bariatric surgery is a successful long-term treatment of obesity for people with diabetes, it is an expensive procedure. The average cost of surgery exceeds $13,000 (5), with additional costs possible in the months following surgery (6). This raises the question of whether bariatric surgery is cost-effective for severely obese people with diabetes.Several studies have estimated the cost-effectiveness of bariatric surgery and found that surgery is either cost-effective (7–10) or that it leads to cost savings over time (6,11–13). The existing studies tend to be relatively simple, and only two (10,13) focus on people with diabetes. The studies generally do not model the microvascular complications associated with diabetes, the effect of surgery on blood pressure and cholesterol levels, or the resulting outcomes.This study used the Centers for Disease Control and Prevention (CDC)-RTI Diabetes Cost-Effectiveness Model to analyze the cost-effectiveness of bariatric surgery in severely obese adults with diabetes. We separately estimated the cost-effectiveness of gastric bypass surgery relative to usual diabetes care and the cost-effectiveness of gastric banding surgery relative to usual diabetes care. Gastric bypass and gastric banding are the two forms of bariatric surgery most commonly studied (1). We examined the cost-effectiveness of each type of surgery for severely obese people who are newly diagnosed with diabetes (no more than 5 years after diagnosis) and for people with established diabetes (at least 10 years after diagnosis).     

Adverse Outcomes After Noncardiac Surgery in Patients With Diabetes: A nationwide population-based retrospective cohort study

OBJECTIVE

To investigate whether diabetes affects perioperative complications or mortality and to gauge its impact on medical expenditures for noncardiac surgeries.

RESEARCH DESIGN AND METHODS

With the use of reimbursement claims from the Taiwan National Health Insurance system, we performed a population-based cohort study of patients with and without diabetes undergoing noncardiac surgeries. Outcomes of postoperative complications, mortality, hospital stay, and medical expenditures were compared between patients with and without diabetes.

RESULTS

Diabetes increased 30-day postoperative mortality (odds ratio 1.84 [95% CI 1.46–2.32]), particularly among patients with type 1 diabetes or uncontrolled diabetes and patients with preoperative diabetes-related comorbidities, such as eye involvement, peripheral circulatory disorders, ketoacidosis, renal manifestations, and coma. Compared with nondiabetic control patients, coexisting medical conditions, such as renal dialysis (5.17 [3.68–7.28]), liver cirrhosis (3.59 [2.19–5.88]), stroke (2.87 [1.95–4.22]), mental disorders (2.35 [1.71–3.24]), ischemic heart disease (2.08 [1.45–2.99]), chronic obstructive pulmonary disease (1.96 [1.29–2.97]), and hyperlipidemia (1.94 [1.01–3.76]) were associated with mortality for patients with diabetes undergoing noncardiac surgery. Patients with diabetes faced a higher risk of postoperative acute renal failure (3.59 [2.88–4.48]) and acute myocardial infarction (3.65 [2.43–5.49]). Furthermore, diabetes was associated with prolonged hospital stay (2.30 [2.16–2.44]) and increased medical expenditures (1.32 [1.25–1.40]).

CONCLUSIONS

Diabetes increases postoperative 30-day mortality, complications, and medical expenditures in patients undergoing in-hospital noncardiac surgeries.Diabetes is a common chronic disease that causes widespread disability and death, with a global prevalence of 2.8% in 2000 and an estimated prevalence of 4.4% in 2030 (1). In the U.S., the national burden of diabetes was estimated to be $245 billion in 2012 (2). The epidemiology, pathogenesis, prevention, and treatment of diabetes have been well established over the past 2 centuries (3).Diabetes is an independent determinant of increased risk of perioperative complications and mortality in cardiovascular surgeries (4,5), yet how extensively diabetes affects postoperative mortality and complications in noncardiac surgeries has not been determined. Some studies indicated that survival outcomes and perioperative complications in noncardiac surgeries do not differ between patients with and without diabetes (6,7), whereas other research showed conflicting data about whether diabetes increased perioperative complications, mortality, hospital stay, and health care expenditures (8–16).Previous studies were limited by several factors, including a focus on a single type of noncardiac surgery (6,8,10,12,14), small sample size (6,7,9,13), inappropriate selection of nondiabetes control subjects (6–16), inadequate adjustment for potential confounders (7,9–12,15), and reporting of a single outcome after surgery (10,16). It remains unclear whether coexisting medical conditions, types of diabetes, glycemic control, and diabetes-related comorbidities affect postoperative outcomes in patients with diabetes.This study used Taiwan National Health Insurance Program reimbursement claims to investigate postoperative complications, 30-day mortality, length of hospital stay, and medical expenditures after adjustment by propensity score-matched pair method in patients with diabetes undergoing noncardiac surgeries. We also investigated the impact of coexisting medical conditions and diabetes-related comorbidities on postoperative 30-day mortality among patients with diabetes.     

Impact of Metabolic Syndrome Compared With Impaired Fasting Glucose on the Development of Type 2 Diabetes in a General Japanese Population: The Hisayama study

OBJECTIVE

We examined whether metabolic syndrome predicts incident type 2 diabetes more effectively than impaired fasting glucose (IFG) in a general Japanese population.

RESEARCH DESIGN AND METHODS

A total of 1,935 nondiabetic subjects aged 40–79 years were followed-up prospectively for a mean of 11.8 years.

RESULTS

During the follow-up, 286 subjects developed type 2 diabetes. Compared with those without metabolic syndrome, the multivariate-adjusted hazard ratio (HR) for incident type 2 diabetes was significantly higher in subjects of both sexes with metabolic syndrome, even after adjustment for confounding factors, age, family history of diabetes, total cholesterol, alcohol intake, smoking habits, and regular exercise (men: HR 2.58 [95% CI 1.85–3.59]; women: 3.69 [2.58–5.27]). The multivariate-adjusted HR of metabolic syndrome for type 2 diabetes was slightly lower in men and similar in women compared with that of IFG. The multivariate-adjusted HR for type 2 diabetes rose progressively as the number of metabolic syndrome components increased in both subjects with and without IFG. In stratified analysis, the multivariate-adjusted risk of type 2 diabetes was significantly higher in subjects with metabolic syndrome alone (2.37 [1.45–3.88]) or IFG alone (3.49 [2.57–4.74]) and markedly increased in subjects with both metabolic syndrome and IFG (6.76 [4.75–9.61]) than in subjects with neither metabolic syndrome nor IFG. Furthermore, the multivariate-adjusted risk for type 2 diabetes was also significantly higher in subjects with both metabolic syndrome and IFG than in those with either one alone (both P < 0.001).

CONCLUSIONS

Our findings suggest that metabolic syndrome significantly increases the risk of incident type 2 diabetes, independent of IFG, and is therefore a valuable tool to identify individuals at high risk of type 2 diabetes.Metabolic syndrome consists of a clustering of cardiovascular risk factors, such as central obesity, elevated blood pressure, glucose intolerance, and dyslipidemia, and individuals with this condition have an elevated risk of developing cardiovascular diseases (1–5) and type 2 diabetes in different ethnic populations (1–4,6–11). Thus, the concept of metabolic syndrome could be used to reduce the incidence of these diseases worldwide. However, a number of experts in the field of diabetes have questioned whether the idea of metabolic syndrome is useful and valuable (12–14). Because all of the criteria sets for metabolic syndrome have included the component of impaired fasting glucose (IFG), which is a powerful predictor of type 2 diabetes, detractors have questioned whether the more complex definition of metabolic syndrome is better than a simple measurement of fasting plasma glucose (FPG). However, reported findings concerning this issue are controversial: a cohort study has shown that the ability of metabolic syndrome to predict type 2 diabetes was superior to that of IFG alone (3), whereas in other studies, the value of metabolic syndrome was comparable or inferior to that of IFG alone (2,6,7). Furthermore, most of these epidemiological studies were performed in Western populations, and this subject has not been assessed sufficiently in Asian populations.The purpose of the present study was to investigate the association between metabolic syndrome and the development of type 2 diabetes in a prospective study of a defined Japanese population, taking into account comprehensive risk factors. In addition, we compared which of the two measures, metabolic syndrome or IFG, better predicted incident type 2 diabetes.     

Extended Family History of Type 1 Diabetes and Phenotype and Genotype of Newly Diagnosed Children

OBJECTIVE

To determine the frequency of newly diagnosed diabetic children with first- and second-degree relatives affected by type 1 diabetes and to characterize the effects of this positive family history on clinical markers, signs of β-cell autoimmunity, and HLA genotype in the index case.

RESEARCH DESIGN AND METHODS

Children (n = 1,488) with type 1 diabetes diagnosed under 15 years of age were included in a cross-sectional study from the Finnish Pediatric Diabetes Register. Data on family history of diabetes and metabolic decompensation at diagnosis were collected using a questionnaire. Antibodies to β-cell autoantigens (islet cell antibodies, insulin autoantibodies, GAD antibodies, and antibodies to the islet antigen 2 molecule) and HLA genotypes were analyzed.

RESULTS

A total of 12.2% of the subjects had a first-degree relative with type 1 diabetes (father 6.2%, mother 3.2%, and sibling 4.8%) and 11.9% had an affected second-degree relative. Children without affected relatives had lower pH (P < 0.001), higher plasma glucose (P < 0.001) and β-hydroxybutyrate concentrations (P < 0.001), a higher rate of impaired consciousness (P = 0.02), and greater weight loss (P < 0.001). There were no differences in signs of β-cell autoimmunity. The familial cases carried the HLA DR4-DQ8 haplotype more frequently than sporadic cases (74.0 vs. 67.0%, P = 0.02).

CONCLUSIONS

When the extended family history of type 1 diabetes is considered, the proportion of sporadic diabetes cases may be reduced to <80%. A positive family history for type 1 diabetes associates with a less severe metabolic decompensation at diagnosis, even when only second-degree relatives are affected. Autoantibody profiles are similar in familial and sporadic type 1 diabetes, suggesting similar pathogenetic mechanisms.Familial clustering of type 1 diabetes is a conspicuous feature; the risk of developing type 1 diabetes is 8–15-fold higher in first-degree relatives (1–6) and twofold in second-degree relatives (1,7). Despite this, the vast majority of children are diagnosed with the sporadic form of diabetes. The proportion of children with an affected first-degree relative at the time of diagnosis is ∼10–12% (7–13), and after decades of follow-up, this frequency increases to >20% (8,14,15). Fathers transmit the disease to their offspring more often than mothers (3,16). Accordingly, at diagnosis, 4–7% of children have a father with type 1 diabetes whereas only 1.5–3% have an affected mother (7–12,17). Fewer reports exist on type 1 diabetes in the extended family. Depending on the definition of second-degree relatives and length of time from the diagnosis of the index case, 5–16% of children with type 1 diabetes have an affected second-degree relative (1,5,11,17–19).Familial and sporadic type 1 diabetes have been suggested to differ in terms of pathogenetic mechanisms (20,21). The risk-associated HLA genotypes have been observed more often in familial type 1 diabetes (8,20,22,23), although not all studies have found significant differences (24). Two studies have noticed no differences in diabetes-associated autoantibodies, e.g., insulin autoantibodies (IAAs) (8), GAD antibodies (GADAs) (8), or islet cell antibodies (ICAs) (8,20). A recent study from Israel reported, however, higher frequencies of IAAs and a higher number of positive antibody responses among familial cases (13). In families with prior experience of type 1 diabetes in a first-degree relative, the clinical status of the child at diagnosis is less severe (8,13,21).Data on the possible pathogenetic differences between familial and sporadic type 1 diabetes are still inconsistent and based on a positive family history in first-degree relatives only. To further our understanding of familial clustering of type 1 diabetes, we used data from the large, nationwide Finnish Pediatric Diabetes Register for a cross-sectional observational study. Since the knowledge of the effects of an extended family history on the diabetes of the index case is lacking, we included information on second-degree relatives (grandparents and siblings of parents). β-Cell autoimmunity, metabolic decompensation at diagnosis, and HLA genetics were compared in children with familial or sporadic type 1 diabetes. We postulated to see a stronger genetic susceptibility to type 1 diabetes and a milder metabolic decompensation in children with a positive family history for type 1 diabetes, whereas no differences were expected in the autoantibody profile.     

Racial and Ethnic Differences in an Estimated Measure of Insulin Resistance Among Individuals With Type 1 Diabetes

OBJECTIVE

Insulin resistance is greater in racial/ethnic minorities than in non-Hispanic whites (NHWs) for those with and without type 2 diabetes. Because previous research on insulin resistance in type 1 diabetes was limited to NHWs, racial/ethnic variation in an estimated measure of insulin resistance in type 1 diabetes was determined.

RESEARCH DESIGN AND METHODS

The sample included 79 individuals with type 1 diabetes diagnosed at age <18 years (32.9% NHWs, 46.8% non-Hispanic black [NHB], 7.6% other/mixed, and 12.7% Hispanic) and their families. Estimated glucose disposal rate (eGDR) (milligrams per kilogram per minute; a lower eGDR indicates greater insulin resistance) was calculated using A1C, waist circumference, and hypertension status.

RESULTS

Mean current age was 13.5 years (range 3.2–32.5) and diabetes duration was 5.7 years (0.1–19.9). eGDR was inversely associated with age. Compared with that in NHWs, age-adjusted eGDR was significantly lower among nonwhites (NHB, other/mixed, and Hispanic: Δ = −1.83, P = 0.0006). Age-adjusted eGDR was negatively associated with body fat, triglycerides, urinary albumin/creatinine, acanthosis nigricans, parental obesity, and parental insulin resistance and positively related to HDL and sex hormone–binding globulin. In multivariable analysis, lower eGDR was significantly associated with older age, nonwhite race/ethnicity, acanthosis, and lower HDL.

CONCLUSIONS

Minorities with type 1 diabetes are significantly more insulin resistant, as measured by eGDR, than NHWs. Exploring potential mechanisms, including disparities in care and/or physiological variation, may contribute to preventing racial/ethnic differences in insulin resistance–associated outcomes.Insulin resistance is common in type 2 diabetes (1) and seems to play a role in the natural history (2) and risk of complications (3) in type 1 diabetes as well. Measurement of insulin resistance in type 1 diabetes is difficult because methods used in nondiabetic and type 2 individuals, e.g., insulin or homeostasis model assessment (4), cannot be used in hypoinsulinemia. The euglycemic-hyperinsulinemic clamp has been used; however, it is labor-intensive and invasive and therefore is not suitable for population-based studies. In response, a derived measure of insulin resistance, the estimated glucose disposal rate (eGDR), has been developed using clinical measures and is strongly correlated with clamp-measured insulin resistance (5).Consistent with clamp studies in type 1 diabetes (2), lower eGDR is associated with older age (6), longer duration of diabetes (6), greater adiposity (6), family history of type 2 diabetes (5), poor glycemic control (5), and elevated lipids (6). Low eGDR predicts incident retinopathy (3), nephropathy (3,6), neuropathy (7), and cardiovascular disease in type 1 diabetes (3,6). These findings are primarily based on non-Hispanic white (NHW) adults.Previous research shows racial/ethnic differences in insulin resistance for healthy individuals and those with type 2 diabetes. For example, minority adults with and without type 2 diabetes were more insulin resistant than their NHW counterparts (1,8). Similarly, in nondiabetic youth, minorities were more insulin resistant than NHWs (9,10). Despite these findings, to our knowledge, there are no data on insulin resistance in minorities with type 1 diabetes.Therefore, we sought to determine 1) whether racial/ethnic differences in insulin resistance, as measured by eGDR, exist in type 1 diabetes and 2) whether the association of eGDR with factors traditionally related to insulin resistance differed by race/ethnicity. It was hypothesized that insulin resistance is greater in minorities than in whites and that associations with insulin resistance are consistent across race/ethnicity.     

Minimal Contribution of Fasting Hyperglycemia to the Incidence of Type 2 Diabetes in Subjects With Normal 2-h Plasma Glucose

OBJECTIVE

To assess the relative contribution of increased fasting and postload plasma glucose concentrations to the incidence of type 2 diabetes in subjects with a normal 2-h plasma glucose concentration.

RESEARCH DESIGN AND METHODS

A total of 3,450 subjects with 2-h plasma glucose concentration <140 mg/dl at baseline were followed up in the San Antonio Heart Study (SAHS) and the Botnia Study for 7–8 years. The incidence of type 2 diabetes at follow-up was related to the fasting, 1-h, and 2-h plasma glucose concentrations.

RESULTS

In subjects with 2-h plasma glucose <140 mg/dl, the incidence of type 2 diabetes increased with increasing fasting plasma glucose (FPG) and 1-h and 2-h plasma glucose concentrations. In a multivariate logistic analysis, after adjustment for all diabetes risk factors, the FPG concentration was a strong predictor of type 2 diabetes in both the SAHS and the Botnia Study (P < 0.0001). However, when the 1-h plasma glucose, but not 2-h plasma glucose, concentration was added to the model, FPG concentration was no longer a significant predictor of type 2 diabetes in both studies (NS). When subjects were matched for the level of 1-h plasma glucose concentration, the incidence of type 2 diabetes markedly increased with the increase in 1-h plasma glucose, but the increase in FPG was not associated with a significant increase in the incidence of type 2 diabetes.

CONCLUSIONS

An increase in postload glycemia in the normal range is associated with an increase in the incidence of type 2 diabetes. After controlling for 1-h plasma glucose concentration, the increase in FPG concentration is not associated with an increase in the incidence of type 2 diabetes.Impaired fasting glucose (IFG) was introduced in 1997 by the American Diabetes Association (ADA) (1), and, analogous with impaired glucose tolerance (IGT), it was meant to represent an intermediate stage in the transition from normal glucose tolerance (NGT) to overt type 2 diabetes. Both IFG and IGT indicate an increased risk for future type 2 diabetes (2–4). Previously (5–7), we have shown that the 1-h plasma glucose concentration has better predictive power than either fasting plasma glucose (FPG) or 2-h plasma glucose, suggesting that the 1-h plasma glucose concentration may have greater utility in identifying subjects at increased risk for type 2 diabetes in routine clinical practice.Previous studies have reported that IFG and IGT represent separate clinical entities, which are characterized by distinct metabolic abnormalities (8–13). Subjects with IGT manifest insulin resistance in skeletal muscle (9–12) and impaired β-cell function (both early and late phases of insulin secretion) (10,14–16), whereas subjects with IFG are characterized by increased hepatic insulin resistance (9,16), impaired early insulin response (12), and decreased non–insulin-dependent glucose clearance (15). Because of the prominent role of progressive β-cell failure in the development of hyperglycemia (17), the impairment in β-cell function in subjects with IGT represents a major pathogenic factor for their increased risk for future type 2 diabetes. Although the increase in fasting plasma glucose is associated with a decrease in first-phase insulin secretion (11–13,18), subjects with IFG have robust second-phase insulin secretion, and, when related to their prevailing level of insulin resistance, they have second-phase insulin secretion comparable with that of subjects with NGT (12,13). Thus, impaired β-cell function cannot fully explain the increased incidence of type 2 diabetes associated with the increase in FPG concentration, e.g., in subjects with isolated IFG.Previously we have shown a strong correlation between insulin resistance in skeletal muscle and liver (16). Thus, a strong correlation between FPG and postload plasma glucose concentrations is anticipated. Therefore, we hypothesized that the increased type 2 diabetes risk associated with the increase in FPG, at least in part, is due to the increased postprandial plasma glucose concentration associated with the increase in FPG and is not due to the increase in FPG per se. The aim of this study was to test this hypothesis.     

Maternal but Not Paternal Association of Ambulatory Blood Pressure With Albumin Excretion in Young Offspring With Type 1 Diabetes

OBJECTIVE

Familial predisposition to hypertension has been associated with the development of diabetic nephropathy in adults, but there are limited data in adolescents. Our aim was to assess whether parental ambulatory blood pressure (ABP) was associated with ABP and albumin excretion in young offspring with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Twenty-four-hour ABP monitoring was performed in 509 young offspring (mean ± SD age 15.8 ± 2.3 years) with type 1 diabetes, 311 fathers, and 444 mothers. Systolic (SBP) and diastolic blood pressure (DBP) measurements during 24 h, daytime, and nighttime were calculated. Three early morning urinary albumin-to-creatinine ratios (ACRs), A1C, and anthropometric parameters were available for the offspring.

RESULTS

All paternal ABP parameters, except for nighttime SBP, were independently related to the offspring''s ABP (24-h SBP β = 0.18, 24-h DBP β = 0.22, daytime SBP β = 0.25, daytime DBP β = 0.23, and nighttime DBP β = 0.18; all P < 0.01). Maternal 24-h DBP (β = 0.19, P = 0.004), daytime DBP (β = 0.09, P = 0.04), and nighttime SBP (β = 0.24 P = 0.001) were related to the corresponding ABP parameter in the offspring. Significant associations were found between the offspring''s logACR and maternal ABP. The association with 24-h DBP (β = 0.16, P = 0.02), daytime DBP (β = 0.16 P = 0.02), and nighttime DBP (β = 0.15 P = 0.03) persisted even after adjustment for the offspring''s ABP. Mothers of offspring with microalbuminuria had higher ABP than mothers of offspring without microalbuminuria (all P < 0.05).

CONCLUSIONS

In this cohort, parental ABP significantly influenced offspring blood pressure, therefore confirming familial influences on this trait. In addition, maternal ABP, particularly DBP, was closely related to ACR in the offspring, suggesting a dominant effect of maternal genes or an effect of the intrauterine environment on microalbuminuria risk.Microalbuminuria remains the best predictive marker for the development of overt diabetic nephropathy and represents an independent risk factor for cardiovascular disease (CVD) (1). Evidence indicating that the risk for the development of microalbuminuria and diabetic nephropathy is partly genetic and may relate to the inheritance of genes associated with CVD is accumulating (2). Several studies have shown familial aggregation of renal disease in type 1 diabetes (2,3), and a family history of hypertension, dyslipidemia, insulin resistance, type 2 diabetes, or a cluster of these cardiovascular risk factors has been associated with an increased risk of diabetic nephropathy (2,4).In particular, several lines of evidence have highlighted the fact that predisposition to hypertension might be a risk factor for the development and progression of diabetic nephropathy in individuals with type 1 diabetes (4–8), and, therefore, the inheritance of blood pressure–related genes might also contribute to abnormal albumin excretion and renal damage. Parental hypertension has been associated with changes in renal hemodynamics (9) and with the development of diabetic nephropathy in the offspring with diabetes (5–8). However, the relationship between family history of hypertension and albuminuria has not been confirmed in all studies (10) and in the majority of studies, confirmation has been based on a single blood pressure assessment in the parents (7,8) or on a questionnaire-based history of parental hypertension. In addition, the effect of parental blood pressure, as was that of other heritable factors, has been mainly investigated in adults with diabetes, whereas it has been seldom studied in children and adolescents (11,12).Understanding the role of such a familial/genetic effect of blood pressure on renal disease would be particularly important in adolescents with type 1 diabetes, who represent a vulnerable group at risk of vascular complications (13). In particular, the identification of familial/genetic factors predisposing to diabetic nephropathy and the understanding of their interplay with glycemic control and the hormonal and metabolic changes of puberty could help in identifying subjects at higher risk for diabetes complications, who therefore require more intensive treatment to prevent them. The aim of the present study was to assess whether parental ambulatory blood pressure (ABP) was related to variations in the same trait and in albumin excretion rates in young offspring with childhood-onset type 1 diabetes.     

Predictors of Overweight During Childhood in Offspring of Parents With Type 1 Diabetes

OBJECTIVE

To study which perinatal factors affect the risk of childhood overweight in offspring with a first-degree relative (FDR) with type 1 diabetes and to determine whether maternal diabetes is an independent contributor to overweight risk.

RESEARCH DESIGN AND METHODS

Data on a child''s weight and height were collected at age 2, 5, and 8 years from 1,214 children participating in the prospective BABYDIAB study. All children had an FDR with type 1 diabetes, including 783 whose mothers had type 1 diabetes. Overweight was defined as BMI percentile ≥90. Data on birth size, breast-feeding, maternal age, and smoking during pregnancy were collected by questionnaires. Risk estimates were calculated by logistic regression analyses.

RESULTS

Breastfeeding duration and birth size both contributed significantly to overweight risk at all age intervals. Full breast-feeding >4 months or any breast-feeding >6 months reduced risk of overweight (aged 8 years: odds ratio 0.3 [95% CI 0.2–0.7], P = 0.004; and 0.3 [0.1–0.6], P = 0.001). Large-for-gestational-age status increased risk of overweight (aged 8 years: 2.4 [1.4–4.3], P = 0.002). Importantly, no evidence was found for an independent contribution of maternal type 1 diabetes to childhood overweight.

CONCLUSIONS

Our findings indicate that maternal type 1 diabetes is not an independent risk factor for overweight during childhood in offspring of type 1 diabetic mothers but that factors associated with maternal type 1 diabetes, such as short breast-feeding duration and high birth size, predispose children to overweight during childhood.The increasing prevalence of overweight and obesity in children is a major health problem, as obesity-related medical conditions affect almost every organ system in the body (1). Gestational and perinatal factors have been shown to influence weight in childhood. Among these, maternal diabetes during pregnancy has been associated with an increased prevalence of childhood obesity (2–6). This has led to the hypothesis that in utero exposure to increased concentrations of glucose and insulin leads to increased risk of obesity and insulin resistance later in life (2). Previous studies (3–5) have been small or retrospective in design. Moreover, it is not clear whether maternal diabetes as such, or factors such as birth size and breast-feeding, which are affected by maternal diabetes, modify obesity risk.Here, we have examined weight and BMI during childhood in a cohort of 1,214 children whose mothers or fathers have type 1 diabetes and who were followed from age ≤3 months. The aim of the analysis was to determine which gestational and perinatal factors may increase the risk of childhood obesity and whether maternal diabetes is an independent contributor to obesity risk.     

Pregnancy-Induced Rise in Serum C-Peptide Concentrations in Women With Type 1 Diabetes

OBJECTIVE

The purpose of this study was to investigate whether pregnancy induces increased insulin production as a marker of improved β-cell function in women with long-term type 1 diabetes.

RESEARCH DESIGN AND METHODS

This was a prospective study of 90 consecutive pregnant women with type 1 diabetes. At 8, 14, 21, 27, and 33 weeks blood samples were drawn for measurements of A1C, C-peptide, and serum glucose. C-peptide (detection limit: 6 pmol/l) was considered stimulated at a corresponding serum glucose concentration ≥5.0 mmol/l. GAD antibody concentration was determined at 8 and 33 weeks in 35 women.

RESULTS

C-peptide concentrations gradually increased throughout pregnancy regardless of serum glucose concentrations in the 90 women with a median duration of diabetes of 17 years (range 1–36 years). Among 35 women with paired recordings of stimulated C-peptide, C-peptide production was detectable in 15 (43%) at 8 weeks and in 34 (97%) at 33 weeks (P < 0.0001), and median C-peptide gradually increased from 6 to 11 pmol/l (P = 0.0004) with a median change of 50% (range −50 to 3,271%) during pregnancy. GAD antibodies were present in 77% with no change from 8 to 33 weeks (P = 0.85). Multivariate regression analysis revealed a positive association between the absolute increase in C-peptide concentrations during pregnancy and decreased A1C from 8 to 33 weeks (P = 0.003).

CONCLUSIONS

A pregnancy-induced increase in C-peptide concentrations in women with long-term type 1 diabetes was demonstrated, even in women with undetectable C-peptide concentrations in early pregnancy. This increase is suggestive of improved β-cell function and was associated with improvement in glycemic control during pregnancy.Previously it has been shown that individuals with long-term type 1 diabetes have scattered β-cells in the pancreas (1) that retain the ability to develop new β-cells, probably by neogenesis from exocrine duct cells (2,3).Pregnancy is a unique event in which the fetus usually survives to full term without rejection by the maternal immune system, which apparently accepts the foreign fetus (4). During normal pregnancy, mild suppression of the maternal immune system occurs to tolerate the allogenic fetus (5). This requires substantial changes in the maternal immune system over a programmed period. Pregnancy is associated with partial suppression of the immune inflammatory system so that autoimmune diseases often go into remission during pregnancy (5).During normal pregnancy, growth-promoting factors are expressed in increased amounts, and the pancreas responds to the additional demand forinsulin by an enlargement of existing islets of Langerhans and hyperplasia of the insulin-producing β-cells (6,7), up-regulation of insulin synthesis and secretion (6), and increased sensitivity of β-cells to glucose stimulation (6). Increased mitotic activity has been seen both in vivo and in vitro in islets exposed to growth hormone. Receptors for growth hormone are expressed in islet cells and are upregulated during pregnancy (8).In small series of women with long-term type 1 diabetes, even with previously undetectable C-peptide secretion, occurrence of maternal insulin production in pregnancy has been observed (9–11). This phenomenon may be a consequence of rejuvenated β-cell function due to pregnancy-induced growth-promoting factors and suppression of the immune system (9), but improved metabolic control may also play a role in newly diagnosed type 1 diabetes (12) as well as in type 1 diabetes beyond the initial remission phase (10,13).The aim of this study was to investigate whether pregnancy induces increased C-peptide concentration as a marker of possible β-cell regeneration in a large unselected cohort of women with long-term type 1 diabetes. In addition, possible factors related to increased C-peptide concentration were investigated.     

Active Care Management Supported by Home Telemonitoring in Veterans With Type 2 Diabetes: The DiaTel randomized controlled trial

OBJECTIVE

We compared the short-term efficacy of home telemonitoring coupled with active medication management by a nurse practitioner with a monthly care coordination telephone call on glycemic control in veterans with type 2 diabetes and entry A1C ≥7.5%.

RESEARCH DESIGN AND METHODS

Veterans who received primary care at the VA Pittsburgh Healthcare System from June 2004 to December 2005, who were taking oral hypoglycemic agents and/or insulin for ≥1 year, and who had A1C ≥7.5% at enrollment were randomly assigned to either active care management with home telemonitoring (ACM+HT group, n = 73) or a monthly care coordination telephone call (CC group, n = 77). Both groups received monthly calls for diabetes education and self-management review. ACM+HT group participants transmitted blood glucose, blood pressure, and weight to a nurse practitioner using the Viterion 100 TeleHealth Monitor; the nurse practitioner adjusted medications for glucose, blood pressure, and lipid control based on established American Diabetes Association targets. Measures were obtained at baseline, 3-month, and 6-month visits.

RESULTS

Baseline characteristics were similar in both groups, with mean A1C of 9.4% (CC group) and 9.6% (ACM+HT group). Compared with the CC group, the ACM+HT group demonstrated significantly larger decreases in A1C at 3 months (1.7 vs. 0.7%) and 6 months (1.7 vs. 0.8%; P < 0.001 for each), with most improvement occurring by 3 months.

CONCLUSIONS

Compared with the CC group, the ACM+HT group demonstrated significantly greater reductions in A1C by 3 and 6 months. However, both interventions improved glycemic control in primary care patients with previously inadequate control.Within the Veterans Health Administration, ∼500,000 veterans receive care for diabetes annually; diabetes is a leading cause of morbidity and mortality and a major contributor to health care cost (1,2). Sampling data from 2009 indicate that ∼28% of veterans nationally have suboptimal glycemic control with A1C ≥8% (3). Increases in A1C levels above the normal range in patients with diabetes are associated with progressive increases in morbidity and mortality due to micro- and macrovascular disease (4). Intensive glycemic control can reduce microvascular complications in both type 1 and type 2 diabetes (5,6). However, recent studies have not demonstrated that intensive glycemic control for 3–6 years with achieved A1C targets from 6.4 to 6.9% reduces macrovascular complications in patients with long-standing type 2 diabetes (7–9). In contrast, intensive glycemic control initiated early in the course of either type 1 or type 2 diabetes appears to reduce the risk of subsequent macrovascular complications significantly even when glycemic control later deteriorates (10,11).Home-based telemedicine has been examined as a tool for management of chronic diseases (12), including diabetes (13–19). This approach can obviate geographic barriers; provide automated education, feedback, and data transmission; and facilitate provider-to-patient communication (12). However, outcomes with home telemonitoring in diabetes and other chronic diseases have been variable (12). Of several randomized controlled trials (RCTs) using home telemonitoring in diabetes care (13–19), only two have reported significant improvement in A1C (17,18). Neither of these trials included active medication management by a provider in response to real-time transmission of self-monitored blood glucose (SMBG) data or have specifically targeted patients not meeting glycemic control goals in response to pharmacological therapy under conditions of usual care.The present study compared the efficacy of home telemonitoring coupled with active medication management by a nurse practitioner (ACM+HT intervention) with a lower-intensity care coordination intervention (CC intervention) consisting of monthly telephone contact with a diabetes nurse educator. Our study specifically targeted veterans with A1C levels ≥8% after ≥1 year receiving pharmacological therapy under conditions of usual care.     

Determinants of Maternal Triglycerides in Women With Gestational Diabetes Mellitus in the Metformin in Gestational Diabetes (MiG) Study

OBJECTIVE

Factors associated with increasing maternal triglyceride concentrations in late pregnancy include gestational age, obesity, preeclampsia, and altered glucose metabolism. In a subgroup of women in the Metformin in Gestational Diabetes (MiG) trial, maternal plasma triglycerides increased more between enrollment (30 weeks) and 36 weeks in those treated with metformin compared with insulin. The aim of this study was to explain this finding by examining factors potentially related to triglycerides in these women.

RESEARCH DESIGN AND METHODS

Of the 733 women randomized to metformin or insulin in the MiG trial, 432 (219 metformin and 213 insulin) had fasting plasma triglycerides measured at enrollment and at 36 weeks. Factors associated with maternal triglycerides were assessed using general linear modeling.

RESULTS

Mean plasma triglyceride concentrations were 2.43 (95% CI 2.35–2.51) mmol/L at enrollment. Triglycerides were higher at 36 weeks in women randomized to metformin (2.94 [2.80–3.08] mmol/L; +23.13% [18.72–27.53%]) than insulin (2.65 [2.54–2.77] mmol/L, P = 0.002; +14.36% [10.91–17.82%], P = 0.002). At 36 weeks, triglycerides were associated with HbA_1c (P = 0.03), ethnicity (P = 0.001), and treatment allocation (P = 0.005). In insulin-treated women, 36-week triglycerides were associated with 36-week HbA_1c (P = 0.02), and in metformin-treated women, they were related to ethnicity.

CONCLUSIONS

At 36 weeks, maternal triglycerides were related to glucose control in women treated with insulin and ethnicity in women treated with metformin. Whether there are ethnicity-related dietary changes or differences in metformin response that alter the relationship between glucose control and triglycerides requires further study.Maternal metabolism in late pregnancy is catabolic, with increasing insulin resistance, decreased adipose tissue lipoprotein lipase (LPL) activity, and increased lipolysis (1). These processes combine to ensure the availability of maternal fuels such as glucose, fatty acids, and ketone bodies for fetal use (1). It is recognized that gestational age, maternal obesity (2), and preeclampsia (3) are associated with increases in lipids during pregnancy. Gestational diabetes mellitus (GDM) is also associated with abnormalities in maternal lipid metabolism (4–6), which may contribute to the elevated fat mass seen at birth in infants of women with GDM (7–10).Maternal glucose control and the pharmacological therapies used for treatment of GDM have the potential to influence these changes in maternal lipids (11). Insulin suppresses adipose tissue lipolysis and might be expected to reduce circulating triglycerides (12). Metformin reduces insulin resistance, but it has also been suggested to influence lipid metabolism (13), independent of glycemic control. In type 2 diabetes, metformin treatment is associated with a reduction in plasma triglyceride, total cholesterol, LDL cholesterol (13), and VLDL cholesterol concentrations (14). Metformin treatment in type 2 diabetes is also associated with increases in LPL mass level and LDL cholesterol particle size (15) and with a reduction in the release of free fatty acids from adipose tissue (16).We have recently examined maternal lipids in the Metformin in Gestational Diabetes (MiG) trial and found that maternal fasting plasma triglycerides and measures of glucose control at 36 weeks were the strongest predictors of customized birth weight >90th percentile (17). Interestingly, triglycerides increased more from randomization to 36 weeks'' gestation in women allocated to metformin than in those allocated to treatment with insulin, but there was no difference in customized birth weights or other neonatal anthropometry measures between the groups; there were also no differences in cord blood triglycerides (17). The aim of this study was to examine the known and putative determinants of maternal triglyceride concentrations and determine whether the difference seen in maternal plasma triglycerides at 36 weeks was due to treatment or other factors that may have differed between treatment groups.     

Nonlaboratory-Based Risk Assessment Algorithm for Undiagnosed Type 2 Diabetes Developed on a Nation-Wide Diabetes Survey

OBJECTIVE

To develop a New Chinese Diabetes Risk Score for screening undiagnosed type 2 diabetes in China.

RESEARCH DESIGN AND METHODS

Data from the China National Diabetes and Metabolic Disorders Study conducted from June 2007 to May 2008 comprising 16,525 men and 25,284 women aged 20–74 years were analyzed. Undiagnosed type 2 diabetes was detected based on fasting plasma glucose ≥7.0 mmol/L or 2-h plasma glucose ≥11.1 mmol/L in people without a prior history of diabetes. β-Coefficients derived from a multiple logistic regression model predicting the presence of undiagnosed type 2 diabetes were used to calculate the New Chinese Diabetes Risk Score. The performance of the New Chinese Diabetes Risk Score was externally validated in two studies in Qingdao: one is prospective with follow-up from 2006 to 2009 (validation 1) and another cross-sectional conducted in 2009 (validation 2).

RESULTS

The New Chinese Diabetes Risk Score includes age, sex, waist circumference, BMI, systolic blood pressure, and family history of diabetes. The score ranges from 0 to 51. The area under the receiver operating curve of the score for undiagnosed type 2 diabetes was 0.748 (0.739–0.756) in the exploratory population, 0.725 (0.683–0.767) in validation 1, and 0.702 (0.680–0.724) in validation 2. At the optimal cutoff value of 25, the sensitivity and specificity of the score for predicting undiagnosed type 2 diabetes were 92.3 and 35.5%, respectively, in validation 1 and 86.8 and 38.8% in validation 2.

CONCLUSIONS

The New Chinese Diabetes Risk Score based on nonlaboratory data appears to be a reliable screening tool to detect undiagnosed type 2 diabetes in Chinese population.Prevalence of type 2 diabetes is increasing dramatically worldwide. In China, the prevalence of type 2 diabetes increased from 5.5% in 2000–2001 (1) to 9.7% in 2007–2008 (2). Nearly 60% of individuals with type 2 diabetes had not been diagnosed previously (2). Mortality in individuals with previously undiagnosed type 2 diabetes was, however, as high as in those with known type 2 diabetes; both were higher than in people without type 2 diabetes (3). Obesity, hypertension, and dyslipidemia are also frequently clustered in an individual with undiagnosed type 2 diabetes (2,4,5). Early detection of type 2 diabetes and intervention may reduce exposure to long-term hyperglycemia and prevent or delay chronic diabetes complications. The currently used diagnostic tool for type 2 diabetes is 75-g oral glucose tolerance test (OGTT) and A1C (6). The OGTT is, however, time consuming, and the fasting status cannot be assured. The A1C test is less standard and relatively expensive. Consequently, their use in mass screening has been limited. Risk score developed based on demographic, anthropometric, and clinical information without a laboratory test has been proved to be a useful and cheap tool for a stepwise screening strategy for undiagnosed type 2 diabetes (7–17). This approach is particularly useful in China, considering a large population and an already high and still increasing prevalence of undiagnosed type 2 diabetes.A simple Chinese diabetes risk score has been reported based on data collected in Qingdao (7). Considering the diversity in economic development, culture, living environment, and dietary factors in different areas of China, we tried to develop a New Chinese Diabetes Risk Score for undiagnosed type 2 diabetes using the data of the China National Diabetes and Metabolic Disorders Study (exploratory population) that was conducted in 12 provinces and autonomous regions in addition to the municipalities of Beijing and Shanghai from June 2007 to May 2008. The performance of the New Chinese Diabetes Risk Score developed in this study is validated in two external studies in Qingdao. One of the two studies is prospective (validation 1) and the other cross-sectional (validation 2). The results of the validation of the indexed score are also compared with previously published diabetes risk scores that derived from Chinese (7), Caucasian (9,11,13,14,18), and other Asian populations (15,16,19,20).     

Effectiveness of a Computerized Insulin Order Template in General Medical Inpatients With Type 2 Diabetes: A cluster randomized trial

OBJECTIVE

To determine whether an electronic order template for basal-bolus insulin ordering improves mean blood glucose in hospitalized general medical patients with hyperglycemia and type 2 diabetes.

RESEARCH DESIGN AND METHODS

We randomly assigned internal medicine resident teams on acute general medical floors to the use of an electronic insulin order template or usual insulin ordering. We measured diabetes care parameters for 1 month on all patients with type 2 diabetes and blood glucose <60 mg/dl or >180 mg/dl treated by these physicians.

RESULTS

Intervention group patients (n = 65) had mean glucose of 195 ± 66 mg/dl. Control group patients (n = 63) had mean glucose of 224 ± 57 mg/dl (P = 0.004). In the intervention group, there was no increase in hypoglycemia.

CONCLUSIONS

Access to a computer insulin order template was associated with improved mean glucose levels without increasing hypoglycemia in patients with type 2 diabetes.Physiological, basal-bolus insulin prescribing is safe, effective (1), and the standard of care in hospitalized patients with type 2 diabetes and hyperglycemia (2). Yet only about half of such patients are prescribed basal insulin in the hospital (3). Order templates to support basal-bolus insulin prescribing (usually as part of a comprehensive inpatient diabetes quality improvement program) have been effective in improving glycemia in observational trials (4–8). Randomized trials have shown more modest effects (9,10). Knowledge of appropriate insulin ordering is a barrier to ordering basal-bolus insulin among inpatient providers (11–13).We tested the hypothesis that giving internal medicine residents access to an electronic insulin order template would be more effective than usual insulin ordering in lowering mean blood glucose in medical inpatients with type 2 diabetes.     

Peri-Conceptional A1C and Risk of Serious Adverse Pregnancy Outcome in 933 Women With Type 1 Diabetes

OBJECTIVE

To study the association between peri-conceptional A1C and serious adverse pregnancy outcome (congenital malformations and perinatal mortality).

RESEARCH DESIGN AND METHODS

Prospective data were collected in 933 singleton pregnancies complicated by type 1 diabetes.

RESULTS

The risk of serious adverse outcome at different A1C levels was compared with the background population. The risk was significantly higher when peri-conceptional A1C exceeded 6.9%, and the risk tended to increase gradually with increasing A1C. Women with A1C exceeding 10.4% had a very high risk of 16%. Congenital malformation rate increased significantly at A1C above 10.4%, whereas perinatal mortality was increased even at A1C below 6.9%.

CONCLUSIONS

These results support recent guidelines of preconceptional A1C levels <7% in women with type 1 diabetes.Recently, guidelines for management of pregnancy in women with pregestational diabetes have recommended pregestational A1C values <7.0% (1,2) and <6.1% (3). Previous studies have reported information of early A1C including 116–691 pregnancies (4–10). We aimed to study whether there is a threshold value for peri-conceptional A1C in women with type 1 diabetes below which the risk of serious adverse pregnancy outcome (congenital malformation and perinatal mortality) is not increased.     

Educational Disparities in Mortality Among Adults With Diabetes in the U.S.

OBJECTIVE

To measure relative and absolute educational disparities in mortality among U.S. adults with diabetes and to compare their magnitude with disparities observed within the nondiabetic population.

RESEARCH DESIGN AND METHODS

A total of 85,867 individuals (5,007 with diabetes), aged 35–84 years, who participated in the National Health Interview Survey from 1986 to 1996 were followed for mortality through 31 December 2002. Relative and absolute educational disparities in all-cause, cardiovascular disease (CVD), and non-CVD mortality were measured.

RESULTS

In relative terms, the risk of all-cause mortality was 28% higher in diabetic adults with the lowest versus the highest position on the educational scale (relative index of inequality 1.28 [95% CI 1.08–1.53]). This inverse relationship reflected marked disparities in CVD mortality and was found in all age, sex, and race/ethnicity groups except Hispanics. Although substantial, this relative educational gradient in mortality among adults with diabetes was smaller than in the nondiabetic population. In absolute terms, diabetic adults with the lowest position on the educational scale suffered 503 excess deaths per 10,000 person-years of follow-up compared with those with the highest position. These absolute disparities were stronger than in the nondiabetic population. The results were even more striking for CVD mortality.

CONCLUSIONS

The risk of mortality differs substantially according to educational level among individuals with diabetes in the U.S. Although relative educational disparities in mortality are weaker in adults with versus without diabetes, their absolute impact is greater and translates into a major mortality burden.In the U.S., >20 million adults have diabetes, and the prevalence is expected to rise substantially in the coming decades (1,2). Diabetes complications impose an enormous burden on public health, and people with diabetes have an age-adjusted mortality rate approximately twice as high as those without (3).The public health burden of diabetes is unevenly distributed across socioeconomic strata. First, diabetes is more common in ethnic minorities and people of low education and income level (4,5). Second, in people with diabetes, socioeconomic position (SEP) may influence major determinants of health, such as access to care, quality of care, and health behaviors (6). Correspondingly, SEP may have a profound impact on the morbidity and mortality associated with diabetes. In Europe, socioeconomic health disparities have been reported among people with diabetes in various settings (5,6); though, two large record linkage studies (7,8) found that the magnitude of socioeconomic differentials in survival was weaker in people with diabetes than in the general population, a result that has remained largely unexplained. In the U.S., only few studies have focused on SEP-related disparities among people with diabetes and then only in selected subpopulations (9–12), making it difficult to determine the impact of such disparities at the population level and their public health importance.To fully monitor health disparities, the general consensus is that both relative and absolute measures are required (13,14). The objective of this study was to quantify relative and absolute educational disparities in mortality within the U.S. diabetic population according to cause of death and across age, sex, and race/ethnicity strata and to compare the magnitude of these disparities to those found in the nondiabetic population.     

Personal and Relationship Challenges of Adults With Type 1 Diabetes: A qualitative focus group study

OBJECTIVE

Little is known about the psychosocial challenges of adults living with type 1 diabetes or its impact on partner relationships. This qualitative study was undertaken to gain better understanding of these issues.

RESEARCH DESIGN AND METHODS

Four focus groups were held, two with adult type 1 diabetic patients (n = 16) and two with partners (n = 14). Two broad questions were posed: “What are the emotional and interpersonal challenges you have experienced because you have (your partner has) type 1 diabetes?” and “How does the fact that you have (your partner has) type 1 diabetes affect your relationship with your partner, positively and/or negatively?” Sessions were recorded and transcribed, and analyzed by a team of four researchers, using constant comparative methods to identify core domains and concepts.

RESULTS

Four main domains were identified: 1) impact of diabetes on the relationship, including level of partner involvement, emotional impact of diabetes on the relationship, and concerns about child-rearing; 2) understanding the impact of hypoglycemia; 3) stress of potential complications; and 4) benefits of technology. Themes suggest that, although partner involvement varies (very little to significant), there exists significant anxiety about hypoglycemia and future complications and sources of conflict that may increase relationship stress. Partner support is highly valued, and technology has a positive influence.

CONCLUSIONS

Adults with type 1 diabetes face unique emotional and interpersonal challenges. Future research should focus on gaining a better understanding of how they cope and the effect of psychosocial stressors and coping on adherence, quality of life, and glycemic control.Studies of people with type 1 diabetes have focused on children and young adults and describe many emotional and interpersonal challenges. Youth are at increased risk for psychiatric, eating, and substance abuse disorders, interpersonal problems, nonadherence, and poor quality of life (1,2). “Emerging” adults must address the responsibilities of intensive self-care (e.g., healthcare access) while managing normative challenges (e.g., jobs) (3,4).Little is known about common psychosocial challenges of adults with type 1 diabetes. Type 1 diabetes is a challenging disease. Those diagnosed as children live with the disease for most of their lives. All are vulnerable to complications that affect quality of life (5). Self-care is demanding, requiring frequent testing, insulin adjustment, and hypervigilance against hypoglycemia. Studies show the negative effects on quality of life of male sexual dysfunction (6) and of frequent or traumatic severe hypoglycemia episodes (7). The odds of depression are two times higher for adults with type 1 diabetes (8), and disordered eating and insulin omission are concerns (9). Effective coping skills are important; they relate to better glycemic control (10,11) and regimen adherence (10,12). Personal models of type 1 diabetes that are more negative (e.g., less perceived control) relate to poorer coping and clinic attendance (13). Overall, the literature on psychosocial challenges and factors affecting the outcomes of adult type 1 diabetic patients is lacking.One area studied is the effect of family support on outcomes. Greater family conflict for youth with type 1 diabetes, and less family support for adults, predicts poorer adherence (14,15). For adults with type 2 diabetes, greater marital satisfaction relates to lower risk of developing metabolic syndrome (16), better marital quality relates to better quality of life and adherence (17–19), and nonsupportive partner behaviors relate to poorer medication adherence (20). Also, partners of people with type 2 diabetes may experience as much, or more, distress as the patient (21).One would expect similar significant effects on important relationships of adult type 1 diabetic patients. One study found that those who achieved improved glycemic control with continuous glucose monitoring also reported that their “significant other” encouraged and participated with them (22). One study of spouses of patients who had recently experienced severe hypoglycemia found greater distress and marital conflict than spouses whose partners had not, and even more fear of hypoglycemia than the patients (23). Generally, little is known about these intra- and interpersonal challenges.We adopted a qualitative approach to better understand the unique psychosocial challenges of adults with type 1 diabetes, and patient/partner perspectives on how diabetes impacts their relationships (24). We chose focus groups, not individual interviews, because data are obtained from the communication between participants, as they share experiences and comment on different perspectives. Also, sometimes participants are more open when less inhibited members explore difficult topics, and more open in a group format (25).     

Glycemic Control and Cardiovascular Disease in 7,454 Patients With Type 1 Diabetes: An observational study from the Swedish National Diabetes Register (NDR)

OBJECTIVE

We assessed the association between A1C and cardiovascular diseases (CVDs) in an observational study of patients with type 1 diabetes followed for 5 years.

RESEARCH DESIGN AND METHODS

A total of 7,454 patients were studied from the Swedish National Diabetes Register (aged 20–65 years, diabetes duration 1–35 years, followed from 2002 to 2007).

RESULTS

Hazard ratios (HRs) for fatal/nonfatal coronary heart disease (CHD) per 1% unit increase in baseline or updated mean A1C at Cox regression analysis were 1.31 and 1.34 and 1.26 and 1.32, respectively, for fatal/nonfatal CVD (all P < 0.001 after adjustment for age, sex, diabetes duration, blood pressure, total and LDL cholesterol, triglycerides, BMI, smoking, and history of CVD). HRs were only slightly lower for CHD (P = 0.002) and CVD (P = 0.002–0.007) after also adjusting for albuminuria. Adjusted 5-year event rates of CHD and CVD increased progressively with higher A1C, ranging from 5 to 12%, as well as when subgrouped by shorter (1–20 years) or longer (21–35 years) duration of diabetes. A group of 4,186 patients with A1C 5–7.9% (mean 7.2) at baseline showed risk reductions of 41% (95% confidence intervals: 15–60) (P = 0.005) for fatal/nonfatal CHD and 37% (12–55) (P = 0.008) for CVD, compared with 3,268 patients with A1C 8–11.9% (mean 9.0), fully adjusted also for albuminuria.

CONCLUSIONS

This observational study of patients in modern everyday clinical practice demonstrates progressively increasing risks for CHD and CVD with higher A1C, independently of traditional risk factors, with no J-shaped risk curves. A baseline mean A1C of 7.2% showed considerably reduced risks of CHD and CVD compared with A1C 9.0%, emphasizing A1C as a strong independent risk factor in type 1 diabetes.Patients with type 1 diabetes have long been considered to have increased risks of cardiovascular disease (CVD) and mortality (1,2), and this has recently been confirmed in two studies (3,4) from the General Practice Research Database in the U.K. Based on data from 1992 to 1999, risks of CVD and mortality were four to eight times higher in men and women with type 1 diabetes than nondiabetic individuals (3,4).While the association between glycemia and microvascular complications is established (5,6), there have been no long-term randomized clinical studies satisfactorily examining the relationship with macrovascular complications in type 1 diabetes, and epidemiological studies have shown conflicting results (7–14). The Epidemiology of Diabetes Interventions and Complications (EDIC) Study showed that patients who had previously been subjected to intensive glucose control during the Diabetes Control and Complications Trial (DCCT) had a considerably lower risk of CVD than patients receiving standard treatment (1983–1993) (7). A small study from Finland on late-onset type 1 diabetic patients without albuminuria showed increased risk of coronary heart disease (CHD) with poor glycemic control (9), but the EURODIAB Prospective Complications Study (PCS), the Pittsburgh Epidemiology of Diabetes Complications (EDC) Study, and the Wisconsin Epidemiologic Study of Diabetic Retinopathy did not demonstrate a significant relationship between glycemia and CHD after controlling for other cardiovascular risk factors (10–13). However, a recent study (14) from the Pittsburgh EDC showed that change in A1C was related to coronary artery disease, whereas baseline A1C was not.With this background, we assessed the association between A1C and CHD, stroke, and CVD in a large cohort of patients with type 1 diabetes, aged 20–65 years, treated in everyday clinical practice from 2002 to 2007. Data were used from the Swedish National Diabetes register (NDR), a quality-assurance tool in diabetes care with nationwide coverage with recently published reports regarding type 1 and type 2 diabetes (15–17).     

Body Composition Is Normal in Term Infants Born to Mothers With Well-Controlled Gestational Diabetes Mellitus

OBJECTIVE

This study aims to describe body composition in term infants of mothers with gestational diabetes mellitus (GDM) compared with infants of mothers with normal glucose tolerance (NGT).

RESEARCH DESIGN AND METHODS

This cross-sectional study included 599 term babies born at Royal Prince Alfred Hospital, Sydney, Australia. Neonatal body fat percentage (BF%) was measured within 48 h of birth using air-displacement plethysmography. Glycemic control data were based on third-trimester HbA_1c levels and self-monitoring blood glucose levels. Associations between GDM status and BF% were investigated using linear regression adjusted for relevant maternal and neonatal variables.

RESULTS

Of 599 babies, 67 (11%) were born to mothers with GDM. Mean ± SD neonatal BF% was 7.9 ± 4.5% in infants with GDM and 9.3 ± 4.3% in infants with NGT, and this difference was not statistically significant after adjustment. Good glycemic control was achieved in 90% of mothers with GDM.

CONCLUSIONS

In this study, neonatal BF% did not differ by maternal GDM status, and this may be attributed to good maternal glycemic control.Fetal growth and development is affected through the altered intrauterine environment of gestational diabetes mellitus (GDM) (1,2). An accurate method to characterize overgrowth is by estimation of body composition, which includes fat mass (FM) and fat-free mass (FFM) (3,4). Previous studies have shown that increases in FM are present in infants of GDM pregnancies, regardless of their weight for gestational age (1,5). The gold-standard method of measuring body composition changes is air-displacement plethysmography (ADP) (4,6,7). The aim of this study was to describe body composition and anthropometric measurements at birth in term infants of women with GDM compared with infants of mothers with normal glucose tolerance (NGT) levels.