Dietary Patterns and Risk for Diabetes: The Multiethnic Cohort

OBJECTIVE

The high diabetes incidence among Japanese Americans and Native Hawaiians cannot be explained by BMI. Therefore, we examined the influence of three dietary patterns of “fat and meat,” “vegetables,” and “fruit and milk” on diabetes risk in the Hawaii component of the Multiethnic Cohort with 29,759 Caucasians, 35,244 Japanese Americans, and 10,509 Native Hawaiians.

RESEARCH DESIGN AND METHODS

Subjects aged 45–75 years completed a baseline food frequency questionnaire. After 14 years of follow-up, 8,587 subjects with incident diabetes were identified through self-reports or health plan linkages. Risk was assessed using Cox regression stratified by age and adjusted for ethnicity, BMI, physical activity, education, total energy, smoking, alcohol intake, marital status, and hypertension.

RESULTS

Fat and meat was significantly associated with diabetes risk in men (hazard ratio 1.40 [95% CI 1.23–1.60], P_trend < 0.0001) and women (1.22 [1.06–1.40], P_trend = 0.004) when extreme quintiles were compared. Except in Hawaiian women, the magnitude of the risk was similar across ethnic groups although not always significant. After stratification by BMI, fat and meat remained a predictor of disease primarily among overweight men and among overweight Japanese women. Vegetables lowered diabetes risk in men (0.86 [0.77–0.95], P_trend = 0.004) but not in women, whereas fruit and milk seemed to be more beneficial in women (0.85 [0.76–0.96], P_trend = 0.005) than in men (0.92 [0.83–1.02], P_trend = 0.04).

CONCLUSIONS

Foods high in meat and fat appear to confer a higher diabetes risk in all ethnic groups, whereas the effects of other dietary patterns vary by sex and ethnicity.Native Hawaiians have extremely high rates of obesity and diabetes, but despite their relatively low body weight, individuals with Japanese ancestry are also disproportionately affected by diabetes (1). Among the >44,000 Japanese Americans, 14,000 Native Hawaiians, and 35,000 Caucasians in the Hawaii component of the Multiethnic Cohort (MEC), a previous analysis had found diabetes incidence rates of 15.5, 12.5, and 5.8 per 1,000 person-years, respectively, that could not be explained by BMI (2). Dietary patterns have been identified as additional predictors of disease but have only rarely been investigated prospectively among non-Caucasian populations (3–5). The most commonly identified patterns are the so-called “western,” “unhealthy,” or “conservative” pattern (3–11), which is high in meat, high-fat foods, and sweets, and the “prudent” or “healthy” pattern, rich in fruit and vegetables (3–8,10,12,13). With the goal to contribute to the prevention of diabetes, we examined the effect of three dietary patterns, “fat and meat,” “vegetables,” and “fruit and milk,” which had been previously identified in the MEC, on diabetes risk (14).     

Leaky channels make weak muscles

Mutations in the skeletal muscle voltage-gated calcium channel (Ca_V1.1) have been associated with hypokalemic periodic paralysis, but how the pathogenesis of this disorder relates to the functional consequences of mutations was unclear. In this issue of the JCI, Wu and colleagues recapitulate the disease by generating a novel knock-in Ca_V1.1 mutant mouse and use this model to investigate the cellular and molecular features of pathogenesis. They demonstrated an aberrant muscle cell current conducted through the Ca_V1.1 voltage-sensor domain (gating pore current) that explains an abnormally depolarized muscle membrane and the failure of muscle action potential firing during challenge with agents known to provoke periodic paralysis. Their work advances understanding of molecular and cellular mechanisms underlying an inherited channelopathy. Ion channels are ubiquitous membrane proteins that confer selective ionic permeability to the plasmalemma or intracellular membranes and enable a wide variety of important physiological processes, including membrane excitability, synaptic transmission, signal transduction, cell volume regulation, and transcellular ion transport. The vital nature of ion channels is reflected by the existence of inherited disorders caused by mutations in genes that encode these proteins (1–5). These “channelopathies” represent more than 50 human genetic diseases, including several affecting skeletal muscle contraction, such as the periodic paralyses and nondystrophic myotonias (see “Muscle channelopathies”).     

Hoofbeats,zebras, and insights into insulin resistance

In this issue of the JCI, Semple and colleagues report phenotypic evaluation of patients with a germline mutation in the gene encoding serine/threonine kinase AKT2 (see the related article beginning on page 315). Their findings support the idea that the postreceptor actions of insulin in the liver — suppression of gluconeogenesis and stimulation of lipogenesis — are mediated through divergent pathways that can be uncoupled. The results appear to refine the arrangement of crucial steps along these pathways and show how comprehensive study of the phenotype, “deep phenotyping,” of patients who carry rare mutations might complement other types of experiments to elucidate complex pathways and mechanisms. “When you hear hoofbeats, think horses, not zebras” is the quintessential maxim of clinical medicine. But in clinical investigation, the “zebras” — rare conditions that recapitulate, often to an extreme, the components of a common disease — can help to understand the “horse” or common complex phenotype. Extending the metaphor, the current pandemic of obesity and insulin resistance is a veritable stampede that threatens to flatten global medical care infrastructures. A multifaceted approach is required to understand the mechanisms underlying this pandemic, ranging from the strategic use of model systems to population studies and clinical trials. Within this methodological spectrum is the evolving discipline of clinical phenomics, which uses objective and systematic acquisition of phenotypic data (i.e., deep phenotyping) of selected informative patients (1). Phenomic evaluation of patients with rare genetic disorders is a potential tool to help solve the puzzle of insulin resistance and its downstream metabolic consequences, such as hyperglycemia, hepatosteatosis and dyslipidemia, elevated triglyceride (TG) levels, and depressed HDL cholesterol levels.     

Prevalence of the Metabolic Syndrome Among U.S. Workers

OBJECTIVE

Differences in the prevalence of cardiovascular disease (CVD) and its risk factors among occupational groups have been found in several studies. Certain types of workers (such as shift workers) may have a greater risk for metabolic syndrome, a precursor of CVD. The objective of this study was to assess the differences in prevalence and risk of metabolic syndrome among occupational groups using nationally representative data of U.S. workers.

RESEARCH DESIGN AND METHODS

Data from 8,457 employed participants (representing 131 million U.S. adults) of the 1999–2004 National Health and Nutrition Examination Survey were used. Unadjusted and age-adjusted prevalence and simple and multiple logistic regression analyses were conducted, adjusting for several potential confounders (BMI, alcohol drinking, smoking, physical activity, and sociodemographic characteristics) and survey design.

RESULTS

Of the workers, 20% met the criteria for the metabolic syndrome, with “miscellaneous food preparation and food service workers” and “farm operators, managers, and supervisors” having the greatest age-adjusted prevalence (29.6–31.1%) and “writers, artists, entertainers, and athletes,” and “engineers, architects, scientists” the lowest (8.5–9.2%). In logistic regression analyses “transportation/material moving” workers had significantly greater odds of meeting the criteria for metabolic syndrome relative to “executive, administrative, managerial” professionals (odds ratio 1.70 [95% CI 1.49–2.52]).

CONCLUSIONS

There is variability in the prevalence of metabolic syndrome by occupational status, with “transportation/material moving” workers at greatest risk for metabolic syndrome. Workplace health promotion programs addressing risk factors for metabolic syndrome that target workers in occupations with the greatest odds may be an efficient way to reach at-risk populations.According to the Centers for Disease Control and Prevention, approximately one-third of Americans met the criteria for metabolic syndrome from 2003 to 2006 (1). Metabolic syndrome is a condition defined by the clustering of risk factors associated with obesity that raise the risk of cardiovascular disease and type 2 diabetes (2). Specifically, these risk factors are a large waist circumference (i.e., central adiposity), high level of triglycerides, low level of HDL cholesterol, high blood pressure, and high fasting blood glucose levels (2).Research suggests that there may be differences in the prevalence of metabolic syndrome by occupation type. For example, studies have shown a high prevalence of metabolic risk factors among shift workers (3). Differences in the prevalence of metabolic syndrome among occupational groups have also been observed among workers in Spain (4). We have found a high prevalence of obesity among certain occupations such as “farming, forestry, fishing” and “transportation/material moving” occupations in the U.S. (5). However, the prevalence of the metabolic syndrome by occupation in the U.S. population is unknown. To address this gap, in the current study we examined the prevalence of the metabolic syndrome in 40 major U.S. occupational groups using nationally representative data.     

Access to health care and control of ABCs of diabetes

OBJECTIVE

To examine the relationship between access to health care and diabetes control.

RESEARCH DESIGN AND METHODS

Using data from the National Health and Nutrition Examination Survey, 1999–2008, we identified 1,221 U.S. adults (age 18–64 years) with self-reported diabetes. Access was measured by current health insurance coverage, number of times health care was received over the past year, and routine place to go for health care. Diabetes control measures included the proportion of people with A1C >9%, blood pressure ≥140/90 mmHg, and non-HDL cholesterol ≥130 mg/dL.

RESULTS

An estimated 16.0% of known diabetic adults were uninsured. Diabetes control profiles were worse among uninsured than among insured persons (A1C >9% [34.1 vs. 16.5%, P = 0.002], blood pressure ≥140/90 mmHg [31.8 vs. 22.8%, P < 0.05], and non-HDL cholesterol ≥130 mg/dL [67.1 vs. 65.4%, P = 0.7]). Compared with insured persons, uninsured persons were more likely to have A1C >9% (multivariate-adjusted odds ratio 2.4 [95% CI 1.2–4.7]). Compared with those who reported four or more health care visits in the past year, those who reported no health care visits were more likely to have A1C >9% (5.5 [1.2–26.3]) and blood pressure ≥140/90 mmHg (1.9 [1.1–3.4]).

CONCLUSIONS

In people with diabetes, lack of health care coverage is associated with poor glycemic control. In addition, low use of health care service is associated with poor glucose and blood pressure control.In 2010, an estimated 25.8 million people in the U.S. had diabetes (1). People with diabetes are at high risk of a heart attack, a stroke, and other micro- or macrovascular complications (2). While diabetes poses a huge health and economic burden to society, effective diabetes control and management such as control of ABCs of diabetes—glycemic control (A1C control [“A”]), blood pressure control (“B”), and lipid control (cholesterol control [“C”])—can decrease the diabetes burden through prevention or delay of complications (2).In 2008, 46 million people, or 15.4% of the population in the U.S., lacked health care insurance coverage (3), and between January and September 2010, the estimated number was up to 49.5 million (4). Access to health care, including insurance coverage, plays a crucial role in the receipt of preventive services (5). Both lack of insurance coverage and inadequate coverage have been associated with lower use of preventive services (6,7). In addition, absence of a physician or usual source of care is a barrier to the control of hypertension (8). Furthermore, lack of health insurance is associated with an increased risk of overall health decline among late-middle-age adults (9). On the contrary, in a randomized controlled trial, access to Medicaid was found to be beneficial to both physical and mental health outcomes (10).While preventive care practices and diabetes control can delay or prevent complications of diabetes (2), optimal preventive care and control depend on access to health care (11,12). Uninsured people with diabetes are less likely to receive needed care and to effectively manage their disease than those who are insured, and those with inadequate coverage have difficulty obtaining needed care (11,12). Those with insurance coverage are more likely to maintain glycemic control than those without (13,14). Despite these findings, we are unaware of any studies that have examined the relationship between access to health care and control of ABCs of diabetes among persons with diabetes.Therefore, we explored the relationship between access to health care and multiple diabetes control outcomes. Specifically, we examined how insurance coverage, frequency of health care use, and routine place to go for health care affected glycemic control, blood pressure control, and lipid control in a representative sample of U.S. adults with self-reported diabetes.     

Maternal Glucose Tolerance in Pregnancy Affects Fetal Insulin Sensitivity

OBJECTIVE

Offspring of mothers with impaired glucose tolerance are far more likely to develop type 2 diabetes. We tested the hypothesis that maternal glucose tolerance in pregnancy affects fetal insulin sensitivity or β-cell function.

RESEARCH DESIGN AND METHODS

In a prospective singleton pregnancy cohort study, we analyzed glucose, insulin, and proinsulin concentrations in maternal blood at the 50-g oral glucose tolerance test (OGTT) at 24–28 weeks of gestation and in venous cord blood (n = 248). The cord blood glucose-to-insulin ratio and proinsulin concentration were used as indicators of fetal insulin sensitivity and the proinsulin-to-insulin ratio was used as an indicator of fetal β-cell function.

RESULTS

Higher OGTT blood glucose levels were associated with significantly lower cord plasma glucose-to-insulin ratios (r = −0.31, P < 0.001) and higher proinsulin concentrations (r = 0.31, P < 0.001) but not with proinsulin-to-insulin ratios. In a comparison of gestational diabetic (n = 26) versus euglycemic pregnancy, cord blood glucose-to-insulin ratios were substantially lower (geometric mean 10.1 vs. 20.0 mg/dl/μU/ml; P < 0.001), whereas proinsulin concentrations were much higher (24.4 vs. 13.8 pmol/l; P < 0.001), despite similar cord blood glucose concentrations indicating adequate management of diabetes. The differences remained significant after controlling for prepregnancy and fetal adiposity, family history of diabetes, gestational age, and other potential confounders. Significant changes in the glucose-to-insulin ratio and proinsulin concentration were also observed in obese (n = 31) mothers, but the differences became not statistically significant after adjustment for maternal glucose tolerance and fetal adiposity.

CONCLUSIONS

Maternal glucose intolerance may impair fetal insulin sensitivity (but not β-cell function) and consequently “program” the susceptibility to type 2 diabetes.The metabolic syndrome and type 2 diabetes have become a worldwide epidemic of concern (1,2). The rapid rise of the epidemic over recent decades points to the predominant role of preventable “environmental” influences. The question is, what factors at what time points are critically important targets for effective interventions? There is an increasing recognition that the fetal environment may “program” susceptibility to the metabolic syndrome and related disorders (3,4). This suggests an opportunity for early interventions to halt the increasing occurrence of the metabolic syndrome if we could know more about the targets and mechanisms of metabolic programming in early life.Maternal metabolic status affects the fetal environment and plausibly has the potential to program the metabolic function axis of the offspring during critical developmental stages through various mechanisms (e.g., epigenetic changes) (5). Indeed, independent of the type of diabetes (pregestational type 1 or type 2 or gestational), offspring of diabetic mothers are far more likely to develop metabolic syndrome and type 2 diabetes (6–10). Most cases (∼90%) of diabetes in pregnancy are gestational diabetes mellitus (11). Mild gestational glucose intolerance not meeting the criteria for the diagnosis of gestational diabetes mellitus has also been associated with adverse pregnancy outcomes and elevated cord blood C-peptide levels (12). Obesity is closely associated with impaired glucose tolerance (2,13), and, recently, increased insulin resistance was observed among neonates of obese mothers (14). Taken together, these observations suggest that impaired glucose tolerance in pregnancy may program the propensity to development of the metabolic syndrome. However, there is a dearth of prospective pregnancy cohort data to demonstrate what metabolic parameters are programmed in utero. We aimed to test the hypothesis that maternal glucose tolerance in pregnancy affects fetal insulin sensitivity or β-cell function. Such a relationship may underlie the long-term predisposition to the metabolic syndrome and related disorders in offspring of diabetic mothers.     

Restoration of hypoglycemia awareness after islet transplantation

OBJECTIVE—To determine the impact of islet transplantation (ITx) on hypoglycemia awareness in patients with unstable type 1 diabetes and its relation to islet function.RESEARCH DESIGN AND METHODS—A total of 31 ITx recipients were studied. Hypoglycemia unawareness was assessed using the Clarke hypoglycemic score (0 = no hypoglycemia; ≥4 = hypoglycemia unawareness). Subjects were grouped based on graft function: off-insulin (n = 8), graft dysfunction (on-insulin and stimulated C-peptide ≥0.3 ng/ml, n = 13), and graft failure (stimulated C-peptide <0.3 ng/ml, n = 10, evaluated 11.5 ± 14.5 months after graft failure).RESULTS—The hypoglycemia score improved after ITx when compared with baseline values (before vs. after: 5.29 ± 1.51 vs. 1.35 ± 1.92, P < 0.001). This result was sustained even after patient stratification based on islet function (pre vs. post off-insulin: 5.63 ± 2.00 vs. no hypoglycemia reported; graft dysfunction: 5.31 ± 1.49 vs. 1.15 ± 1.63, P < 0.001; and graft failure: 5.00 ± 1.16 vs. 2.70 ± 2.26, P = 0.014).CONCLUSIONS—The improved metabolic control achieved with ITx can restore hypoglycemia awareness in patients with type 1 diabetes, persisting even after islet graft failure.Occurrence of hypoglycemia is the major limitation of intensive control aimed at A1C normalization in patients with type 1 diabetes. Frequent hypoglycemic episodes are particularly common in subjects with unstable type 1 diabetes and can lead to hypoglycemia unawareness. Although islet transplantation (ITx) prevents severe hypoglycemia (1) and restores some counterregulatory hormone secretion (2), data showing its effects on restitution of hypoglycemia awareness are not conclusive (2,3).The aim of this study was to determine if the optimal metabolic control achieved by ITx can restore hypoglycemia awareness and whether or not these effects persist after islet graft failure.     

Diabetic Neuropathy: A cross-sectional study of the relationships among tests of neurophysiology

OBJECTIVE

To determine the relationships among large, small, and autonomic fiber neurophysiological measures in a cross-sectional study of patients with diabetes.

RESEARCH DESIGN AND METHODS

We assessed 130 individuals: 25 healthy subjects and 105 subjects with diabetes. Subjects were classified by the presence or absence of neuropathy by physical examination. All subjects underwent autonomic testing, nerve conduction studies, quantitative sensory testing, and nerve-axon reflex vasodilation in addition to quantifiable neurological examination and symptom scores. Correlation and cluster analysis were used to determine relationships between and among different neurophysiological testing parameters.

RESULTS

Results of neurophysiological tests were abnormal in patients with clinical evidence of diabetic neuropathy compared with results in healthy control subjects and in those without neuropathy (P < 0.01, all tests). The correlations among individual tests varied widely, both within (r range <0.5–>0.9, NS to <0.001) and between test groups (r range <0.2–>0.5, NS to <0.01). A two-step hierarchical cluster analysis revealed that neurophysiological tests do not aggregate by typical “small,” “large,” or “autonomic” nerve fiber subtypes.

CONCLUSIONS

The modest correlation coefficients seen between the different testing modalities suggest that these techniques measure different neurophysiological parameters and are therefore not interchangeable. However, the data suggest that only a small number of neurophysiological tests are actually required to clinically differentiate individuals with neuropathy from those without. The natural clustering of both patients and healthy control subjects suggests that variations in the population will need to be considered in future studies of diabetic neuropathy.Microvascular complications of diabetes, which include retinopathy, neuropathy, and nephropathy are major contributors to morbidity and mortality. Although neuropathy severity is related to duration and degree of glycemic control, individual subjects may have widely disparate clinical presentations despite similar risk factors. Neuropathy progression preferentially affecting nerve fiber subtypes may explain some clinical heterogeneity, but different neurophysiological tests are required to identify dysfunction of different nerve populations in diabetes.Nerve conduction studies, assessing large myelinated fibers, are widely used both in clinical practice and as end points in longitudinal investigations of diabetic neuropathy (1,2). Damage to small thinly and unmyelinated nerves or autonomic fibers can be measured by quantitative sensory testing, autonomic testing, and laser Doppler flowmetry (3–6). To date, few investigators have examined the relationships between different measures of neurophysiological function in diabetic and other peripheral neuropathies (4,7–10).A cross-sectional study of diabetic neuropathy was used to determine the relationships among large, small, and autonomic fiber neurophysiological measures. We hypothesized that measures assessing similar neurophysiological functions would correlate and cluster together along typical nerve fiber subtypes (small, large, or autonomic). In addition, we determined the sensitivity and specificity of these neurophysiological measures using the Neuropathy Disability Score (NDS) as a gold standard (11). Because this clinical measure is weighted toward large fiber assessment, we hypothesized that neurophysiological tests of large fiber function would have higher sensitivity and specificity than measures of small fiber or autonomic function.     

Fitness and freezing: vector biology and human health

Microbes transmitted to mammals by arthropods contend with many factors that could impede survival. To survive, host fitness with infection must outweigh costs. In this issue of the JCI, Neelakanta et al. demonstrate that ticks infected with Anaplasma phagocytophilum show enhanced fitness against freezing injury owing to induced expression of tick “antifreeze glycoprotein.” This allows A. phagocytophilum to successfully propagate and survive to cause disease in nonnatural hosts, such as humans. How an intracellular microbe with a small genome subverts host cell function for survival provides insight into the control of some cellular function programs and underscores how vector biology can have an impact on human health. Emergence and reemergence of infectious diseases is often attributed to many factors, most of which are influenced by human activities, for example, climate change, environmental change, changes in human demographics and behaviors, and the rise of global trade and travel (1). Perhaps not surprisingly, pathogens evolve or acquire genetic mechanisms that enhance fitness under circumstances of human intervention, such as increasing resistance to potent antimicrobial pharmacologic agents. Emerging infectious disease is most likely to be caused by zoonotic or vector-borne agents (1). This is readily understood for zoonotic and vector-borne RNA viruses (such as tick-borne encephalitis viruses, West Nile virus, and the viruses that cause yellow fever, dengue fever, and Crimean-Congo hemorrhagic fever), which undergo frequent genetic change and thus have repeated opportunities to improve fitness (1). However, the substantial evolution of fitness needed to emerge (or reemerge) as a significant health concern in humans is surprising in the context of vector transmission for organisms with less flexible genomes, few opportunities for genetic exchange, and the need to contend with protective mechanisms in at least two distinct hosts. Yet drug-resistant malaria, African and American trypanosomiasis, Lyme disease, and rickettsial infections such as Rocky Mountain spotted fever (RMSF) and human granulocytic anaplasmosis (HGA) have emerged or reemerged to increase in prevalence over the past few decades (2). While considerable investigation is being conducted for some vector-borne emerging diseases and pathogens, bacteria of the order Rickettsiales and their resulting human diseases are understudied, in part because they are obligate intracellular pathogens, which makes biological study difficult, and in part because it is extremely difficult to establish definitive diagnosis, which makes clinical study a challenge (3). Vector biologists who study arthropod-transmitted pathogens understand the role of the vector not only in transmission, but also in disease “ecology.” In this issue of the JCI, Neelakanta et al. demonstrate a new paradigm as to how a tick-borne pathogen can manipulate its arthropod host to foster vector survival and indirectly, pathogen transmission, mammalian reservoir maintenance, and, inevitably, human disease (4).     

Whiplash in individuals with known pre–accident, clinical neck status

In whiplash studies, there may be interpretation difficulties: are post–whiplash findings, when present, a consequence of the whiplash trauma, or did they exist prior to trauma? In the Vågå headache epidemiology study (1995–1997), there was a headache history and detailed physical/neurological findings from the face/head/neck in 1838 18–65–year-old parishioners. In September 2001, four years after the Vågå study, a search through the Health Centre files divulged six cases with whiplash trauma in the intervening period. These parishioners could thus be their own controls. Two females did not develop new complaints. In the four parishioners with apparently new, subjective complaints, i. e., headache, neck pain, and a feeling of stiffness in the neck, there were corresponding findings as regards various parameters: shoulder area skin–roll test, changes in two, possible changes in two; range of motion, neck, changes in two, borderline changes in one; “features indicative of cervical abnormality” (“CF”), changes in all four; the mean, post–whiplash stage value was: 3.6+, against 1.6+ prior to accident (Vågå: only 0.93%, “CF” exceeding 3+). In the two without new complaints, the mean “CF” value was 1.0+. The number of cases is small, but the similarity of the symptoms—and signs—following whiplash injury may suggest an element of organic origin in the whiplash syndrome.Key words: Headache, Whiplash, Neck sprain, Skin–roll test, Mechanical precipitation of headache     

Visceral Adiposity Index: A reliable indicator of visceral fat function associated with cardiometabolic risk

OBJECTIVE

To individuate a novel sex-specific index, based on waist circumference, BMI, triglycerides, and HDL cholesterol, indirectly expressing visceral fat function.

RESEARCH DESIGN AND METHODS

Visceral adiposity index (VAI) was first modeled on 315 nonobese healthy subjects. Using two multiple logistic regression models, VAI was retrospectively validated in 1,498 primary care patients in comparison to classical cardio- and cerebrovascular risk factors.

RESULTS

All components of metabolic syndrome increased significantly across VAI quintiles. VAI was independently associated with both cardiovascular (odd ratio [OR] 2.45; 95% CI 1.52–3.95; P < 0.001) and cerebrovascular (1.63; 1.06–2.50; P = 0.025) events. VAI also showed significant inverse correlation with insulin sensitivity during euglycemic-hyperinsulinemic clamp in a subgroup of patients (R_s = −0.721; P < 0.001). By contrast, no correlations were found for waist circumference and BMI.

CONCLUSIONS

Our study suggests VAI is a valuable indicator of “visceral adipose function” and insulin sensitivity, and its increase is strongly associated with cardiometabolic risk.Visceral obesity (1) is associated with increased adipocytokine production, proinflammatory activity (2), deterioration of insulin sensitivity (3), increased risk of developing diabetes, “high-triglyceride/low–HDL cholesterol dyslipidemia,” hypertension, atherosclerosis, and higher mortality rate (4–7). The identification of a routinely applicable indicator for the evaluation of visceral adipose function, with higher sensitivity and specificity than classical parameters (such as waist circumference [WC], BMI, and lipids), could be useful for cardiometabolic risk assessment. We here extrapolate a novel sex-specific index based on WC, BMI, triglycerides (TGs), and HDL (visceral adiposity index [VAI]), able to estimate the visceral adiposity dysfunction associated with cardiometabolic risk.     

Fear of injury with physical activity is greater in adults with diabetes than in adults without diabetes

OBJECTIVE

Physical activity is a cornerstone of treatment for diabetes, yet people with diabetes perform less moderate and vigorous physical activity (MVPA) than people without diabetes. In contrast, whether differences in walking activity exist has been understudied. Diabetes-specific barriers to physical activity are one possible explanation for lower MVPA in diabetes. We hypothesized that people with diabetes would perform less walking and combined MVPA and would be less likely to anticipate increasing physical activity if barriers were theoretically absent, compared with people without diabetes.

RESEARCH DESIGN AND METHODS

We surveyed 1,848 randomly selected rural Colorado adult residents by telephone from 2002 to 2004. Respondents reported weekly walking and MVPA duration and their likelihood of increasing physical activity if each of seven barriers was theoretically absent.

RESULTS

People with diabetes (n = 129) had lower odds of walking and MVPA than people without diabetes (walking: adjusted odds ratio 0.62 [95% CI 0.40–0.95]; MVPA: adjusted odds ratio 0.60 [0.36–0.99]; ≥10 vs. <10 min/week, adjusted for age, sex, BMI, and ethnicity). Respondents with diabetes reported fear of injury as a barrier to physical activity more often than respondents without diabetes (56 vs. 39%; P = 0.0002), although this relationship was attenuated after adjusting for age and BMI (adjusted odds ratio 1.36 [0.93–1.99]).

CONCLUSIONS

Although walking is a preferred form of activity in diabetes, people with diabetes walk less than people without diabetes. Reducing fear of injury may potentially increase physical activity for people with diabetes, particularly in older and more overweight individuals.Physical activity is considered a cornerstone of diabetes treatment (1), yet people with diabetes are less physically active than people without diabetes, especially with regard to moderate and vigorous physical activity (MVPA) (2–4). Although MVPA optimally promotes cardiovascular health for people with diabetes, regular walking activity is associated with reduced cardiovascular mortality (5,6) and is the preferred activity of people with diabetes (3,7). To our knowledge, only two studies have compared walking activity by diabetes status using population-based samples (3,8). In summary, a handful of studies have demonstrated that diabetes is related to lower MVPA levels, but we need additional data to assess whether diabetes status is also related to lower walking activity levels.Identifying and removing barriers to physical activity is important because of the strong relationship between physical inactivity and cardiovascular disease in people with type 2 diabetes and the likely cardiovascular benefits for people with type 1 diabetes (5,6). Some barriers have been identified that may be considered diabetes specific, including “fear of hypoglycemia” (9,10), the presence of “bad feet due to diabetes” (11), and an “unwillingness to exercise in the presence of people who do not have type 2 diabetes” (12). In the laboratory setting, diabetes is associated with impaired submaximal exercise performance and greater perceived effort during low-intensity exercise (13). While these potential diabetes-specific barriers to physical activity have been identified, this area has been understudied.Other barriers to physical activity exist in people with type 2 diabetes, including lack of social support, lack of knowledge of the types of exercise to perform, health problems, pain/difficulty taking part in exercise, lack of local exercise facilities, and aversion to exercising in poor weather (12). Although several studies have identified barriers to physical activity in people with type 2 diabetes, only one study used population-based sampling (14), only one assessed whether usual activity levels influence barriers (12), and differences in barriers by diabetes status (diabetes vs. no diabetes) were not compared.The current study compares barriers to physical activity by diabetes status in a rural, biethnic population-based sample within two strata of physical activity: “less active” (<150 min weekly MVPA) and “more active” (≥150 min weekly MVPA). Because walking activity differences by diabetes status have been understudied, we also compared walking and MVPA differences in participants with and without diabetes. We hypothesized that people with diabetes would perform less walking and MVPA and would be less likely to anticipate increasing physical activity if barriers were theoretically absent, compared with people without diabetes.     

Lessons learned at the intersection of immunology and neuroscience

Neurobiologists and immunologists study concepts often signified with identical terminology. Scientists in both fields study a structure known as the synapse, and each group analyzes a subject called memory. Is this a quirk of human language, or are there real similarities between these two physiological systems? Not only are the linguistic concepts expressed in the words “synapse” and “memory” shared between the fields, but the actual molecules of physiologic importance in one system play parallel roles in the other: complement, the major histocompatibility molecules, and even “neuro”-transmitters all have major impacts on health and on disease in both the brain and the immune system. Not only are the same molecules found in diverse roles in each system, but we have learned that there is real “hard-wired” crosstalk between nerves and lymphoid organs. This issue of the JCI highlights some of the lessons learned from experts who are working at this scintillating intersection between immunology and neuroscience. A few of us have the treasured opportunity to work at the interface of neuroscience and immunology. The nervous system and the immune system have distinctly different anatomic structures populated by very different cell types, yet the goals of each system have much in common. Both the nervous and immune systems are sensory: they sense changes in the environment and provide integrated responses that allow for survival. Just as the retina can be triggered by a few photons, the T cell receptor can signal with engagement of a single molecule and can form an immune synapse with engagement of as few as ten molecules (1). Both the nervous system and the immune system are also effectors: each system comprises efferent connections that masterfully orchestrate a response to what is sensed. Then there are the shared concepts between these two systems: we have neural synapses that integrate the strength of electrical signals between ensembles of neurons, allowing for processing of information from neural nets. Likewise, the immune system, using an architecture with some similarity to the neural synapse, integrates inputs from a variety of cell types with its own synapse on phagocytes, T cells, B cells, and NK cells. The intersections between the brain and the immune system are even more astonishing: some of the classic neurotransmitters, such as the quintessential inhibitory molecule for neural synapses, GABA, also have an inhibitory function on immune synapses. And the most well-known molecules of the immune system are active within the nervous system: both the classical complement cascade and MHC molecules play stunning roles in axonal guidance and synaptic elimination (refs. 2, 3, and Figure ​Figure11). Open in a separate windowFigure 1Shared concepts of the immune and nervous systems.The immune and nervous systems are both physically linked, as demonstrated by innervation of the spleen and other lymphoid organs, and share a common construction. Many signaling entities, such as the MHC molecules, complement, and GABA are active in both systems, and the similar physical makeup of immune and neurological synapses suggests that they both derive from a shared ancestral cellular connection.These overlaps make “pathway analysis,” a favorite tool of systems biologists and bioinformaticians, the target of a rude trick: molecules do not know whether they are in the “neurobiology club” or the “immunology club.” Molecules have their own language: chemistry! We scientists who use pathway analysis describe molecules with words, but molecules are the essence of chemistry and our language can mask their actual roles. The correct language for neurobiology and immunology is not English or French or Spanish or Russian. The operative language is chemistry. So although we tend to think that complement and the MHC molecules are immunological, we should remember that this is a historical illusion that was shaped because we learned about their roles in immunity first, before we realized that they also play a remarkable part in the nervous system (2, 3). The illusion arose because we think in language and live creating our histories, while molecules engage in chemistry using a language of their own and without a history as we humans know it. The chemistry for both MHC and complement is congruent in the immune system and the nervous system, and this is true for a wide range of other molecules.     

Perceived impact of diabetes genetic risk testing among patients at high phenotypic risk for type 2 diabetes

OBJECTIVE

Rapid advances in diabetes genetic epidemiology may lead to a new era of “personalized medicine” based on individual genetic risk assessment. There is minimal experience to guide how best to clinically implement such testing so that results (e.g., “higher” or “lower” relative genetic risk) improve rather than reduce patient motivation for behavior change.

RESEARCH DESIGN AND METHODS

Between November 2009 and May 2010, we conducted in-depth interviews with 22 overweight participants at high phenotypic risk for type 2 diabetes to explore perceptions of diabetes genetic risk testing compared with currently available prediction using nongenetic risk factors (e.g., family history, abnormal fasting glucose, obesity). We used hypothetical scenarios to specifically investigate the impact of both “higher” and “lower” relative genetic risk results on participants’ views about diabetes prevention.

RESULTS

Many participants conferred a unique value on personal genetic risk information relative to nongenetic risk based on the perceived scientific certainty and durability of genetic results. In contrast, other participants considered their genetic risk within the overall context of their other measured risk factors. Reactions to diabetes genetic test results differed by current motivation levels. Whereas most subjects reported that “higher” risk results would motivate behavior change, subjects with lower current motivation often reported that “lower” genetic risk results would further reduce their motivation to engage in diabetes prevention behaviors.

CONCLUSIONS

To be effective, future clinical implementation of type 2 diabetes genetic risk testing should be individualized based on each patient’s risk perception and current level of motivation to prevent diabetes.Evidence from landmark clinical trials such as the Diabetes Prevention Program has shown that type 2 diabetes can be prevented in high-risk patients by lifestyle changes that result in modest weight loss and increased physical activity (1,2). Patients can be identified as at increased type 2 diabetes risk based on easily available phenotypic markers such as fasting glucose levels, abnormal blood pressure or lipid levels, overweight, and family history (3). Despite available risk stratification tools and effective interventions, however, few patients successfully adopt and sustain the lifestyle changes necessary to prevent diabetes (4,5).The contribution of heritable (rather than environmental) factors to type 2 diabetes has been estimated to be as high as 40% (6). Current approaches to defining diabetes risk using genome-wide association scans have identified over three dozen genetic loci present at >5% allelic frequency, which are each associated with a small but significant increased risk for type 2 diabetes (7). At present, combining all known, validated risk alleles provides only modest additional risk prediction after accounting for traditional phenotypic risk factors (8–11). Rapid advances in DNA sequencing technology, increased ability to identify rare risk loci, and identification of alternative heritable factors (e.g., copy number variation, epigenetic marks) hold promise that future iterations of diabetes genetic risk testing may provide a more robust assessment of an individual’s heritable risk for diabetes (12–14).Despite limitations of current diabetes genetic testing, the concept of “personalized genetic profiling” has gained increasing popularity and is a stated focus of research within the National Institutes of Health (NIH) (15). There are currently four clinical trials registered with clinicaltrials.gov that are addressing the clinical implementation of diabetes genetic testing ({"type":"clinical-trial","attrs":{"text":"NCT01034319","term_id":"NCT01034319"}}NCT01034319, {"type":"clinical-trial","attrs":{"text":"NCT00849563","term_id":"NCT00849563"}}NCT00849563, {"type":"clinical-trial","attrs":{"text":"NCT01060540","term_id":"NCT01060540"}}NCT01060540, {"type":"clinical-trial","attrs":{"text":"NCT01186354","term_id":"NCT01186354"}}NCT01186354). Before such testing becomes more widely implemented into clinical practice, it is critically important to better understand how patients at risk for diabetes perceive individualized diabetes genetic risk results (16,17).The rise of direct-to-consumer genetic testing reflects an assumption that personal genetic information can motivate healthy behavior change (18,19). Although this assumption remains unproven, a recent survey of patients without type 2 diabetes provides some evidence that test results could motivate patients: nearly three-quarters (71%) of survey respondents reported that they would be “much more motivated” to make preventive lifestyle changes upon receipt of a higher genetic risk diabetes genetic testing result (20). This very optimistic anticipated reaction to genetic test results suggests that individuals may value genetic risk results differently than nongenetic risk results, although reasons for this anticipated impact are not clearly understood and require further study.Accurate measurement of an individual’s diabetes genetic risk could potentially provide significant clinical utility by identifying patients at particularly high risk for developing type 2 diabetes. Genetic testing may be a double-edged sword, however. Although higher genetic risk results may increase perceived risk and motivate individuals to adopt lifestyle changes, lower genetic risk results may decrease perceived risk and thus reduce motivation to adopt healthy lifestyle changes. Alternatively, higher genetic risk test results may induce a sense of genetic fatalism that undermines motivation to change behavior (21).We conducted in-depth, semistructured interviews with participants at increased phenotypic risk for diabetes to gain insight into how they perceived diabetes genetic risk information. Participants were presented with hypothetical diabetes genetic risk results that placed them at “higher” or “lower” diabetes genetic risk. Responses were analyzed within the context of each participant’s current motivation and attitude toward diabetes risk reduction. Our study was designed to 1) investigate whether (and how) perceptions of genetic risk differed from traditional phenotypic risk factors and 2) examine the relationship between current diabetes prevention behaviors and response to genetic test results.     

Prevalence of Type 1 Diabetes Autoantibodies (GADA, IA2, and IAA) in Overweight and Obese Children

OBJECTIVE

Little is known about the prevalence of β-cell autoantibodies in children with excess body weight. The prevalence of type 1 diabetes autoantibodies and its relation with hyperglycemia was analyzed in 686 overweight/obese children and adolescents.

RESEARCH DESIGN AND METHODS

All children underwent an oral glucose tolerance test, and anti-GAD, anti-IA2, and anti-IAA autoantibodies were measured. Autoantibody prevalence was evaluated in 107 normal-weight children for comparison.

RESULTS

A single autoantibody was present in 2.18% of overweight/obese subjects and 1.86% normal-weight subjects (P = NS). Postload glycemia was significantly higher in antibody-positive children (133 ± 69.9 vs. 105.4 ± 17.7 mg/dl, P < 0.0001) compared with autoantibody-negative subjects. No difference in autoantibody distribution was seen when our cohort was stratified by age, sex, SDS-BMI, pubertal stage, and homeostasis model assessment–insulin resistance (HOMA-IR).

CONCLUSIONS

The 2.18% prevalence of type 1 diabetes autoantibodies is similar to that reported in nonobese children. This study provided evidence that excess body weight and insulin resistance do not influence autoantibody frequency.Over the last 60 years, a striking increase in the incidence of childhood type 1 diabetes has been observed consistently in almost all populations. EURODIAB (1) reported an overall increase of 3.2% per annum in Europe between 1989 and 1998. There have also been considerable changes in childhood nutrition, which have resulted in changes in growth. Increased weight, height, and BMI in children have all been associated with a higher risk of type 1 diabetes (2). The so-called “accelerator hypothesis” argues that obesity causing overworked β-cells underlies both type 1 and type 2 diabetes and that these “types” are only distinguished by how the body responds to this growth-induced β-cell stress. This hypothesis therefore attributes the rise in type 1 diabetes to an increase in child obesity (3). A variation of the hypothesis suggests that, once initiated, islet autoimmunity progresses more rapidly in the context of “overload” of the β-cells due to increased insulin resistance (4).Sardinia has one of the highest incidences of type 1 diabetes worldwide, second only to Finland (5). Moreover, Sardinian children and adolescents are experiencing the same increase in obesity as other European populations (6). To date, little is known on the prevalence of autoantibodies against β-cells in children with excess body weight.The aim of our study was to analyze the prevalence of type 1 diabetes autoantibodies in a cohort of Sardinian overweight/obese children and adolescents and to evaluate their distribution in relation to the presence of glucose abnormalities.     

No loss of chance of diabetic retinopathy screening by endocrinologists with a digital fundus camera

OBJECTIVE

To compare the efficacy of the diabetic retinopathy (DR) screening with digital camera by endocrinologists with that by specialist and resident ophthalmologists in terms of sensitivity, specificity, and level of “loss of chance.”

RESEARCH DESIGN AND METHODS

In a cross-sectional study, 500 adult diabetic patients (1,000 eyes) underwent three-field retinal photography with a digital fundus camera following pupillary dilatation. Five endocrinologists and two ophthalmology residents underwent 40 h of training on screening and grading of DR and detection of associated retinal findings. A κ test compared the accuracy of endocrinologist and ophthalmology resident screening with that performed by experienced ophthalmologists. Screening efficiency of endocrinologists was evaluated in terms of “loss of chance,” i.e., missed diagnoses that required ophthalmologist referrals.

RESULTS

The mean weighted κ of DR screening performed by endocronologists was similar to that of ophthalmology residents (0.65 vs. 0.73). Out of 456 DR eyes, both endocrinologists and ophthalmology residents misdiagnosed only stage 1 DR (36 and 14, respectively), which did not require ophthalmologist referral. There were no significant differences between endocrinologists and ophthalmology residents in terms of diabetic maculopathy and incidental findings except for papillary cupping and choroidal lesions, which were not the main purpose of the study or of the training.

CONCLUSIONS

The endocrinologist with specific training for DR detection using a three-field digital fundus camera with pupillary dilatation can perform a reliable DR screening without any loss of chance for the patients when compared with identical evaluation performed by experienced ophthalmologists.Diabetic retinopathy (DR) is one of the main causes of blindness in industrialized nations (1). The worldwide prevalence of diabetes in adults is estimated to rise to 7.7%, affecting 439 million adults by 2030 (2). In France, the increasing number of patients with diabetes, coupled with the lack of a national screening program, results in a steady rise in the visual handicaps related to the disease (3).Annual screening of DR is recommended as an effective approach to prevent visual loss related to diabetes (4,5). Currently, digital nonmydriatic fundus photography is increasingly used as a method of screening for ophthalmologists worldwide (5–7). According to consensus classifications (4,5), DR at a stage higher than 1 needs further ophthalmological management. Despite these recommendations, only 30% of the diabetic patients in France undergo DR screening each year. Partly, this is due to the lack of ophthalmologists and insufficient awareness about the visual consequences of the disease (3,8). The situation is slowly changing after implementation of telemedical screening networks using digital fundus photography (9–11). Further increase in screening coverage can be achieved with the involvement of allied medical professionals.Since the 1980s, the concept of “loss of chance” has emerged in medicine and law. The misdiagnosis during DR screening can lead to a loss of chance for patients requiring referral to an ophthalmologist for further examinations and management (12,13).Two studies have shown that screening performed by an endocrinologist using an ophthalmoscope (14) and a mydriatic camera (15), respectively, were reliable, although they didn’t evaluate the loss of chance. Furthermore, no endocrinologists’ team approach was evaluated so far.This clinical research trial has been designed to compare the efficacy of the DR screening with digital camera by a team of previously trained endocrinologists (7) with that of residents and specialist ophthalmologists, in terms of sensitivity, specificity and level of “loss of chance.”