Diabetic Drivers Research Articles

Gut microbiota in insulin resistance: a bibliometric analysis.

Insulin resistance (IR) is considered the pathogenic driver of diabetes, and can lead to obesity, hypertension, coronary artery disease, metabolic syndrome, and other metabolic disorders. Accumulating evidence indicates that the connection between gut microbiota and IR. This bibliometric analysis aimed to summarize the knowledge structure of gut microbiota in IR. Articles and reviews related to gut microbiota in IR from 2013 to 2022 were retrieved from the Web of Science Core Collection (WoSCC), and the bibliometric analysis and visualization were performed by Microsoft Excel, Origin, R package (bibliometrix), Citespace, and VOSviewer. A total of 4 749 publications from WoSCC were retrieved, including 3 050 articles and 1 699 reviews. The majority of publications were from China and USA. The University Copenhagen and Shanghai Jiao Tong University were the most active institutions. The journal of Nutrients published the most papers, while Nature was the top 1 co-cited journal, and the major area of these publications was molecular, biology, and immunology. Nieuwdorp M published the highest number of papers, and Cani PD had the highest co-citations. Keyword analysis showed that the most frequently occurring keywords were "gut microbiota", "insulin-resistance", "obesity", and "inflammation". Trend topics and thematic maps showed that serum metabolome and natural products, such as resveratrol, flavonoids were the research hotspots in this field. This bibliometric analysis summarised the hotspots, frontiers, pathogenesis, and treatment strategies, providing a clear and comprehensive profile of gut microbiota in IR. The online version contains supplementary material available at 10.1007/s40200-023-01342-x.

METHANOLIC EXTRACT OF Ficus platyphylla LEAF MODULATES WEIGHT, BLOOD GLUCOSE LEVEL AND SERUM LIPID PROFILES IN WISTAR ALBINO RATS

Excessive weight gain following the prolonged elevation of blood glucose and lipids is the major driver of obesity, diabetes, and related conditions. This study, therefore, aims to evaluate the effect of Ficus platyphylla leaves extract on body weight, blood glucose levels, and serum lipids of albino rats. Methanolic extract from a sample of the plant’s leaves was first prepared and subjected to phytochemical screening. Doses of 100 mg/kg, 200 mg/kg, and 400 mg/kg were administered to three groups of rats daily while a fourth (control group) received distilled water for 21 days. Phytochemical screening revealed the presence of alkaloids, flavonoids, saponins, tannins, and steroids. A significant (p<0.05) reduction in body weight was observed in the rats administered 100 and 200 mg/kg extract but the reduction is not statistically significant in the 400 mg/kg group. All treatments led to a significant reduction in blood glucose, total cholesterol, triglycerides, and low-density lipoprotein levels with a concomitant rise in high-density lipoprotein cholesterol levels. Our findings demonstrate that the methanolic extract of Ficus platyphylla leaves has an ameliorative effect on body weight, blood glucose, and lipids, and hence the plant could be beneficial to obese and diabetic patients.

A Machine Learning-Based Intelligent Vehicular System (IVS) for Driver’s Diabetes Monitoring in Vehicular Ad-Hoc Networks (VANETs)

Diabetes is a chronic disease that is escalating day by day and requires 24/7 continuous management. It may cause many complications, precisely when a patient moves, which may risk their and other drivers’ and pedestrians’ lives. Recent research shows diabetic drivers are the main cause of major road accidents. Several wireless non-invasive health monitoring sensors, such as wearable continuous glucose monitoring (CGM) sensors, in combination with machine learning approaches at cloud servers, can be beneficial for monitoring drivers’ diabetic conditions on travel to reduce the accident rate. Furthermore, the emergency condition of the driver needs to be shared for the safety of life. With the emergence of the vehicular ad-hoc network (VANET), vehicles can exchange useful information with nearby vehicles and roadside units that can be further communicated with health monitoring sources via GPS and Internet connectivity. This work proposes a novel approach to the health care of drivers’ diabetes monitoring using wearable sensors, machine learning, and VANET technology. Several machine learning (ML) algorithms assessed the proposed prediction model using the cross-validation method. Performance metrics precision, recall, accuracy, F1-score, sensitivity, specificity, MCC, and AROC are used to validate our method. The result shows random forest (RF) outperforms and achieves the highest accuracy compared to other algorithms and previous approaches ranging from 90.3% to 99.5%.

Sugar and stops in drivers with insulin-dependent type 1 diabetes

BackgroundDiabetes is a major public health challenge, affecting millions of people worldwide. Abnormal physiology in diabetes, particularly hypoglycemia, can cause driver impairments that affect safe driving. While diabetes driver safety has been previously researched, few studies link real-time physiologic changes in drivers with diabetes to objective real-world driver safety, particularly at high-risk areas like intersections. To address this, we investigated the role of acute physiologic changes in drivers with type 1 diabetes mellitus (T1DM) on safe stopping at stop intersections. Methods18 T1DM drivers (21–52 years, μ = 31.2 years) and 14 controls (21–55 years, μ = 33.4 years) participated in a 4-week naturalistic driving study. At induction, each participant’s personal vehicle was instrumented with a camera and sensor system to collect driving data (e.g., GPS, video, speed). Video was processed with computer vision algorithms detecting traffic elements (e.g., traffic signals, stop signs). Stop intersections were geolocated with clustering methods, state intersection databases, and manual review. Videos showing driver stop intersection approaches were extracted and manually reviewed to classify stopping behavior (full, rolling, and no stop) and intersection traffic characteristics. ResultsMixed-effects logistic regression models determined how diabetes driver stopping safety (safe vs. unsafe stop) was affected by 1) disease and 2) at-risk, acute physiology (hypo- and hyperglycemia). Diabetes drivers who were acutely hyperglycemic (≥ 300 mg/dL) had 2.37 increased odds of unsafe stopping (95% CI: 1.26–4.47, p = 0.008) compared to those with normal physiology. Acute hypoglycemia did not associate with unsafe stopping (p = 0.537), however the lower frequency of hypoglycemia (vs. hyperglycemia) warrants a larger sample of drivers to investigate this effect. Critically, presence of diabetes alone did not associate with unsafe stopping, underscoring the need to evaluate driver physiology in licensing guidelines. ConclusionThis study links acute, abnormal physiologic fluctuations in drivers with diabetes to driver safety based on unsafe stopping at stop-controlled intersections, providing recommendations for clinicians aimed at improving patient safety, fair licensing guidelines, and targets for developing advanced driver assistance systems.

Mitochondrial TrxR2 regulates metabolism and protects from metabolic disease through enhanced TCA and ETC function

Mitochondrial dysfunction is a key driver of diabetes and other metabolic diseases. Mitochondrial redox state is highly impactful to metabolic function but the mechanism driving this is unclear. We generated a transgenic mouse which overexpressed the redox enzyme Thioredoxin Reductase 2 (TrxR2), the rate limiting enzyme in the mitochondrial thioredoxin system. We found augmentation of TrxR2 to enhance metabolism in mice under a normal diet and to increase resistance to high-fat diet induced metabolic dysfunction by both increasing glucose tolerance and decreasing fat deposition. We show this to be caused by increased mitochondrial function which is driven at least in part by enhancements to the tricarboxylic acid cycle and electron transport chain function. Our findings demonstrate a role for TrxR2 and mitochondrial thioredoxin as metabolic regulators and show a critical role for redox enzymes in controlling functionality of key mitochondrial metabolic systems.

Does gender affect the driving performance of young patients with diabetes?

Recent evidence suggests that poor glycemic control among young patients with type 1 diabetes mellitus (T1DM) has negative cognitive and physical effects, whose extent is gender-dependent. For example, female patients with diabetes present more physical and cognitive limitations than male patients in terms of cognitive adjustment, quality of decision making, and functioning. Studies about traffic safety report that diabetic drivers are at increased risk of being involved in road crashes, especially when driving in a state of hypoglycemia under which their blood glucose level is too low. We have recently demonstrated that acute hyperglycemia (when the blood glucose level is too high) can also lead to poor driving performance among T1DM young adult patients. Against this background, the objective of the present study was to find out whether gender affects the driving performance of young drivers with diabetes. Twenty-six T1DM drivers participated in a counterbalanced crossover experiment. While being monitored by an eye tracker, they drove a driving simulator and twice navigated through the nine hazardous scenarios: once under a normal blood glucose (euglycemia) level and once high blood glucose (hyperglycemia) level. The first main result is that young female drivers are more affected by diabetes than young male drivers, regardless of momentary glycemic changes. The second main result is that poor glycemic control substantially deteriorates hazard perception and driving performance of young males with diabetes. Thus, it is argued that an uncontrolled state of a high blood glucose level may be more hazardous for young males with diabetes since it negatively impacts their driving performance.

Prevalence of Diabetes and Its Relationship With Body Mass Index Among Elderly People in a Rural Area of Northeastern State of India.

BackgroundDiabetes and its complications are a major public health concern in elderly populations. However, there is little population-based data on diabetes and its risk factors among the elderly population living in rural areas of India. The objective of this population-based study was to assess the prevalence of diabetes in the elderly population and its relationship with body mass index (BMI).MethodologyA population-based, cross-sectional study was conducted among elderly individuals (≥60 years) during the period 2013-2016 in rural areas of Dibrugarh district of Assam. Multi-stage sampling design was adopted to select the study participants. Data on socio-demographic profile and diagnosis/treatment history of diabetes were collected using pre-designed and pre-tested questionnaire. Fasting blood sugar was tested. Weight and height were measured to calculate BMI. Multivariate logistic regression analysis was performed to assess the relationship between diabetes and BMI.ResultsData were collected from 430 (male: 210, female: 220) individuals. The overall prevalence of diabetes was 7.9% (male: 7.1%, female: 8.6%). Higher level of education was associated with increased prevalence of diabetes. Prevalence of diabetes increased as the BMI of participants increased. Prevalence of diabetes among obese individuals (BMI ≥25 kg/m2) was 30.4% compared to only 5% among normal weight individuals. Obesity was associated with eight-fold higher risk of diabetes compared with the individuals of normal weight in multivariate analysis.ConclusionsThe study reveals nearly 8% population-based prevalence of diabetes in rural elderly people in the study district. Our study provides epidemiological evidence that obesity is a major driver of diabetes among rural elderly people.

Mucosal-associated invariant T cells promote inflammation and intestinal dysbiosis leading to metabolic dysfunction during obesity

Obesity is associated with low-grade chronic inflammation promoting insulin-resistance and diabetes. Gut microbiota dysbiosis is a consequence as well as a driver of obesity and diabetes. Mucosal-associated invariant T cells (MAIT) are innate-like T cells expressing a semi-invariant T cell receptor restricted to the non-classical MHC class I molecule MR1 presenting bacterial ligands. Here we show that during obesity MAIT cells promote inflammation in both adipose tissue and ileum, leading to insulin resistance and impaired glucose and lipid metabolism. MAIT cells act in adipose tissue by inducing M1 macrophage polarization in an MR1-dependent manner and in the gut by inducing microbiota dysbiosis and loss of gut integrity. Both MAIT cell-induced tissue alterations contribute to metabolic dysfunction. Treatment with MAIT cell inhibitory ligand demonstrates its potential as a strategy against inflammation, dysbiosis and metabolic disorders.

Mechanisms, regulation and functions of the unfolded protein response.

Cellular stress induced by the abnormal accumulation of unfolded or misfolded proteins at the endoplasmic reticulum (ER) is emerging as a possible driver of human diseases, including cancer, diabetes, obesity and neurodegeneration. ER proteostasis surveillance is mediated by the unfolded protein response (UPR), a signal transduction pathway that senses the fidelity of protein folding in the ER lumen. The UPR transmits information about protein folding status to the nucleus and cytosol to adjust the protein folding capacity of the cell or, in the event of chronic damage, induce apoptotic cell death. Recent advances in the understanding of the regulation of UPR signalling and its implications in the pathophysiology of disease might open new therapeutic avenues.

Metabolic Health, Insulin, and Breast Cancer: Why Oncologists Should Care About Insulin.

Studies investigating the potential link between adult pre-menopausal obesity [as measured by body mass index (BMI)] and triple-negative breast cancer have been inconsistent. Recent studies show that BMI is not an exact measure of metabolic health; individuals can be obese (BMI > 30 kg/m2) and metabolically healthy or lean (BMI < 25 kg/m2) and metabolically unhealthy. Consequently, there is a need to better understand the molecular signaling pathways that might be activated in individuals that are metabolically unhealthy and how these signaling pathways may drive biologically aggressive breast cancer. One key driver of both type-2 diabetes and cancer is insulin. Insulin is a potent hormone that activates many pathways that drive aggressive breast cancer biology. Here, we review (1) the controversial relationship between obesity and breast cancer, (2) the impact of insulin on organs, subcellular components, and cancer processes, (3) the potential link between insulin-signaling and cancer, and (4) consider time points during breast cancer prevention and treatment where insulin-signaling could be better controlled, with the ultimate goal of improving overall health, optimizing breast cancer prevention, and improving breast cancer survival.

Associations of serum low-density lipoprotein and systolic blood pressure levels with type 2 diabetic patients with and without peripheral neuropathy: systemic review, meta-analysis and meta-regression analysis of observational studies

BackgroundCompositional abnormalities in lipoproteins and cardiovascular risk factors play an important role in the progression of diabetic peripheral neuropathy (DPN). This systematic review aimed to estimate the predicting value of low-density lipoprotein (LDL) and systolic blood pressure (SBP) level in type-2 diabetes mellitus (T2DM) patients with and without peripheral neuropathy. We also tried to determine whether LDL and SBP are associated with an increased collision risk of DPN.MethodsA systematic search was conducted for eligible publications which explored the LDL and SBP level in T2DM patients with and without peripheral neuropathy. The quality of the included studies was assessed by the QUADAS-2 tool. The standardized mean difference (SMD) with 95% CI of LDL and SBP level were pooled to assess the correlation between LDL and SBP level with DPN. We performed random effects meta-regression analyses to investigate factors associated with an increased collision risk of DPN.ResultsThere was a significant association between LDL and SBP with poor prognosis of DPN in those included studies (I2 = 88.1% and I2 = 84.9%, respectively, Both P < 0.001). European T2DM patients have higher serum level of LDL in compare with the European DPN patients (SMD = 0.16, 95% CI: − 0.06 - 0.38; P < 0.001). SBP level was associated with a 2.6-fold decrease in non-DPN patients of T2DM (SMD = − 2.63, 95% CI: − 4.00 - -1.27, P < 0.001). Old age European T2DM patients have significantly high risk for diabetes drivers. Furthermore, the results of the case-control study design model are more precise to show the accuracy of SBP in Asian T2DM patients.ConclusionOur finding supports the LDL and SBP status could be associated with increased risk of peripheral neuropathy in T2DM patients.

An early warning system for diabetic automobile drivers with peripheral neuropathy

Purpose People with Type 2 diabetes exhibit peripheral neuropathy that results in the progressive loss of sensation in their feet. This may adversely affect their ability to drive as there is the potential for their foot to slip off the accelerator or brake pedals, with unwanted consequences including traffic accidents. This research aimed to develop a prototype for an adaptive haptic foot device for diabetic drivers experiencing peripheral neuropathy that can serve as an early warning system for foot slip during driving. Methods A prototype system was designed in the laboratory which consisted of four force sensing resistors, four light emitting diodes and an eccentric rotating mass all connected and programmed through an Arduino Uno. The prototype was tested under controlled conditions and validated against recommended specifications. The system was then installed in a Ford Falcon GT 2005 and tested under controlled road conditions. Results The results indicated that the haptic device was effective in sensing foot locations and providing instant audio and video feedback to the driver. Conclusion This research has successfully designed and fabricated a haptic feedback device that can be used as an early warning system for diabetic automobile drivers with peripheral neuropathy. IMPLICATIONS FOR REHABILITATION A haptic foot prototype device capable of generating warning signals to diabetic drivers whose foot could slip off the brake or accelerator pedals has been developed. The prototype includes force sensing receivers integrated with eccentric rotating mass system, a haptic controller breakout board, and Arduino software. The system is very easy to use and provides highly reliable audio and visual feedback which are good alerting mechanisms for older automobile drivers.

Acute Hyperglycemia may impair driving skills of young T1DM patients

Diabetic drivers are at increased risk to be involved in road crashes. While there is a large body of evidence regarding the effects of hypoglycemia on driving, very little is known about the effects of hyperglycemia on driving. The goal of this study was, therefore, to evaluate the effects of acute hyperglycemia (AH) on type 1 diabetes mellitus (T1DM) drivers in comparison to euglycemic state. Eighteen T1DM drivers were asked to navigate twice through nine hazardous scenarios in a driving simulator during euglycemia and AH (mean glucose level 138±34 and 321±29 mg\dL respectively) in a counterbalanced crossover design. Driving performance was continually monitored for driving data and eye tracking data. During euglycemia, participants maintained a longer headway distance (Mean=50.46+26.2m) compared to AH (40.87+20.15m P&lt;0.005). Under a state of euglycemia, participants had a fewer number of brakes per kilometers driven (4.31+3.867) compared to AH (6.69+5.192 P&lt;0.05). This study provides evidence to the negative effects of acute hyperglycemia on driving performance.

Added sugar: Nutritional knowledge and consumption pattern of a principal driver of obesity and diabetes among undergraduates in UAE

BackgroundRecently, youth intake of added sugar has been growing. The incidence of obesity and type 2 diabetes Mellitus (T2DM) has risen dramatically in parallel with these changes. Excess added sugar is a key risk factor for weight gain and T2DM in many cohort studies. The current study was implemented to examine the nutritional knowledge, attitude and practice pattern among UAE undergraduates. MethodRandom sampling was used to approach 400 undergraduate students from UAE. The data analysis was performed by using SPSS version 24. A correlation analysis was performed using Pearson and Spearman correlation tests. Statistical analysis was conducted using Chi-square test, T-test, and Kruskal Wallis test. ResultsAdded sugar consumption is widely prevalent among university students in UAE. Only 19% of the enrolled sample scored high nutritional knowledge level and 56% of the students were considered heavy consumers. White sugar was the preferred added sweeteners among 90% of the sample. ConclusionOur study outcomes recommend that strategies that can successfully reduce added sugar might be a significant stage concerning reversing the devastating escalating trends in diabetes, obesity, and promoting health of all populations in UAE.

The diabetic driver.

The diabetic driver.

PCV63 - ECONOMIC BURDEN ASSOCIATED WITH SECONDARY CARDIOVASCULAR (CV) EVENTS – A SYSTEMATIC LITERATURE REVIEW

Significant burden incurred during first CV event occurrence has been widely observed. This review aimed to identify economic burden associated with subsequent CV events in patients with a prior myocardial infarction (MI) or broader cardiovascular diseases. A systematic search was undertaken in Embase®, MEDLINE® and the Cochrane library to identify relevant English publications of last 10 years (2008–2017). Studies providing data on cost and resource use associated with secondary CV events (MI/revascularisation/stroke/unstable angina [UA]) were included. Sixteen studies (20 publications) met the inclusion criteria. Of these, 12 studies were conducted in US, two in Asia and one each in UK and Sweden. Data sources for studies included claims database (N=13), national registers, data warehouse and survey (one each). Overall, patients were aged 53.5-75.3 years and the proportion of females varied from 15.8%-54.0%. Higher cost and resource utilization were observed with secondary events compared to the first event (%increase in costs [UK] for MI, UA and stroke – 1-6 months: 9%, 25%, 28%; 7-36 months: 65%, 37%, 14%). However, the US study suggested that the sequence of the event had little bearing on the overall cost. Coronary Artery Bypass Graft was associated with higher costs among all secondary CV events, followed by MI. Across all the events, direct costs and associated resource utilization were higher during the first year compared to subsequent years. CV-related costs generally decrease after the acute period, however, two studies observed that costs remained higher than pre-CV event costs for a longer duration (3 years). Length of hospital stay (LOS) was observed as the major cost driver and presence of diabetes the important predictor for higher costs. Secondary CV events pose a significant burden on patients with history of CVD, mainly due to longer LOS. Additional evidence in patients with a prior MI is required.

Affect Regulation and Effortful Control in Bingeing/Purging Eating Disorders: A Daily Diary study

Although the effect of lower extremity pathology and surgical intervention on automobile driving function has been a topic of contemporary interest, we are unaware of any analysis of the effect of lower extremity diabetic sensorimotor neuropathy on driving performance. The objective of the present case-control investigation was to assess the mean brake response time in diabetic drivers with lower extremity neuropathy compared with that of a control group and a brake response safety threshold. The driving performances of participants were evaluated using a computerized driving simulator with specific measurement of the mean brake response time and frequency of abnormally delayed brake responses. We analyzed a control group of 25 active drivers with neither diabetes nor lower extremity neuropathy and an experimental group of 25 active drivers with type 2 diabetes and lower extremity neuropathy. The experimental group demonstrated a 37.89% slower mean brake response time (0.757 ± 0.180 versus 0.549 ± 0.076 second; p < .001), with abnormally delayed responses occurring at a greater frequency (57.5% versus 3.5%; p < .001). Independent of a comparative statistical analysis, the observed mean brake response time in the experimental group was slower than the reported safety brake response threshold of 0.70 second. The results of the present investigation provide original data with respect to abnormally delayed brake responses in diabetic patients with lower extremity neuropathy and might raise the potential for impaired driving function in this population.

Glyoxalase 1 Modulation in Obesity and Diabetes.

Significance: Obesity and type 2 diabetes mellitus are increasing globally. There is also increasing associated complications, such as non-alcoholic fatty liver disease (NAFLD) and vascular complications of diabetes. There is currently no licensed treatment for NAFLD and no recent treatments for diabetic complications. New approaches are required, particularly those addressing mechanism-based risk factors for health decline and disease progression. Recent Advances: Dicarbonyl stress is the abnormal accumulation of reactive dicarbonyl metabolites such as methylglyoxal (MG) leading to cell and tissue dysfunction. It is a potential driver of obesity, diabetes, and related complications that are unaddressed by current treatments. Increased formation of MG is linked to increased glyceroneogenesis and hyperglycemia in obesity and diabetes and also down-regulation of glyoxalase 1 (Glo1)-which provides the main enzymatic detoxification of MG. Glo1 functional genomics studies suggest that increasing Glo1 expression and activity alleviates dicarbonyl stress; slows development of obesity, related insulin resistance; and prevents development of diabetic nephropathy and other microvascular complications of diabetes. A new therapeutic approach constitutes small-molecule inducers of Glo1 expression-Glo1 inducers-exploiting a regulatory antioxidant response element in the GLO1 gene. A prototype Glo1 inducer, trans-resveratrol (tRES)-hesperetin (HESP) combination, in corrected insulin resistance, improved glycemic control and vascular inflammation in healthy overweight and obese subjects in clinical trial. Critical Issues: tRES and HESP synergize pharmacologically, and HESP likely overcomes the low bioavailability of tRES by inhibition of intestinal glucuronosyltransferases. Future Directions: Glo1 inducers may now be evaluated in Phase 2 clinical trials for treatment of NAFLD and vascular complications of diabetes.

Diabetic Driving Studies—Part 1: Brake Response Time in Diabetic Drivers With Lower Extremity Neuropathy

Although the effect of lower extremity pathology and surgical intervention on automobile driving function has been a topic of contemporary interest, we are unaware of any analysis of the effect of lower extremity diabetic sensorimotor neuropathy on driving performance. The objective of the present case-control investigation was to assess the mean brake response time in diabetic drivers with lower extremity neuropathy compared with that of a control group and a brake response safety threshold. The driving performances of participants were evaluated using a computerized driving simulator with specific measurement of the mean brake response time and frequency of abnormally delayed brake responses. We analyzed a control group of 25 active drivers with neither diabetes nor lower extremity neuropathy and an experimental group of 25 active drivers with type 2 diabetes and lower extremity neuropathy. The experimental group demonstrated a 37.89% slower mean brake response time (0.757 ± 0.180 versus 0.549 ± 0.076 second; p < .001), with abnormally delayed responses occurring at a greater frequency (57.5% versus 3.5%; p < .001). Independent of a comparative statistical analysis, the observed mean brake response time in the experimental group was slower than the reported safety brake response threshold of 0.70 second. The results of the present investigation provide original data with respect to abnormally delayed brake responses in diabetic patients with lower extremity neuropathy and might raise the potential for impaired driving function in this population.

Diabetic Driving Studies—Part 2: A Comparison of Brake Response Time Between Drivers With Diabetes With and Without Lower Extremity Sensorimotor Neuropathy

We have previously demonstrated an abnormally delayed mean brake response time and an increased frequency of abnormally delayed brake responses in a group of neuropathic drivers with diabetes compared with a control group of drivers with neither diabetes nor lower extremity neuropathy. The objective of the present case-control study was to compare the mean brake response time between 2 groups of drivers with diabetes with and without lower extremity sensorimotor neuropathy. The braking performances of the participants were evaluated using a computerized driving simulator with specific measurement of the mean brake response time and the frequency of the abnormally delayed brake responses. We compared a control group of 25 active drivers with type 2 diabetes without lower extremity neuropathy and an experimental group of 25 active drivers with type 2 diabetes and lower extremity neuropathy from an urban U.S. podiatric medical clinic. The experimental group demonstrated an 11.49% slower mean brake response time (0.757 ± 0.180 versus 0.679 ± 0.120 second; p < .001), with abnormally delayed reactions occurring at a greater frequency (57.5% versus 35.0%; p < .001). Independent of a comparative statistical analysis, diabetic drivers with neuropathy demonstrated a mean brake response time slower than a suggested safety threshold of 0.70 second, and diabetic drivers without neuropathy demonstrated a mean brake response time faster than this threshold. The results of the present investigation provide evidence that the specific onset of lower extremity sensorimotor neuropathy associated with diabetes appears to impart a negative effect on automobile brake responses.