Smoking is associated with impaired long-term glucose metabolism in patients with type 1 diabetes mellitus

Prevalence of LDL-hypercholesterolemia and other cardiovascular risk factors in young people with type 1 diabetes

BACKGROUND

Mortality and morbidity in people with Type 1 diabetes (T1D) is mainly caused by cardiovascular disease (CVD). Early treatment of cardiovascular risk factors (CVRFs) is of great importance.

OBJECTIVE

To analyze the prevalence of LDL-hypercholesterolemia and other CVRFs in youth with T1D.

METHODS

Clinical and laboratory parameters, and vascular thickness measurement were obtained in youth with T1D (age 6-18 years, T1D duration >1 year) attending a diabetes clinic. LDL-hypercholesterolemia, microalbuminuria and arterial hypertension were defined as CVRFs.

RESULTS

A total of 333 youth (48% girls; age: 13.3 years [10.3-15.5], median [interquartile range]) participated in the study. The T1D duration was 5.9 years [3.5-9.4] with HbA1c of 7.4% [6.8-8.0]. Intima media thickness (N=223) was 538.0 µm [470.0-618.0]). LDL-hypercholesterolemia was present in 30 participants (9%; 18 girls; age: 14.3 years [11.2-15.7]). None of the participants had persistent microalbuminuria, although 59 (18.3%) had elevated albumin excretion in a random urine specimen. LDL-hypercholesterolemia was associated with increased blood pressure (p<0.05), insulin requirement (p<0.05), HbA1c (p<0.05), triglyceride (p<0.001) and total cholesterol (p<0.001), and a family history of premature CVD (p<0.001), but negatively correlated with HDL cholesterol levels (p<0.05). Sex, pubertal status, duration of diabetes, type of therapy, and physical activity did not differ between participants with and without LDL- hypercholesterolemia. Arterial hypertension was present in 11 participants (3.3%; 4 girls; age: 14.1 years [11.1-16.1]).

CONCLUSION

LDL-hypercholesterolemia affected 9% of youth with T1D in this cohort and was associated with other CVRFs. A holistic therapeutic concept for these young people is essential.

Smoking and diabetes interplay: A comprehensive review and joint statement

Evidence shows that smoking increases the risk of pre-diabetes and diabetes in the general population. Among persons with diabetes, smoking has been found to increase the risk of all-cause mortality and aggravate chronic diabetic complications and glycemic control. The current paper, which is a joint position statement by the French-Speaking Society on Tobacco (Société Francophone de Tabacologie) and the French-Speaking Society of Diabetes (Société Francophone du Diabète), summarizes the data available on the association between smoking and diabetes and on the impact of smoking and smoking cessation among individuals with type 1, type 2, and gestational diabetes mellitus. It also provides evidence-based information about the pharmacological and behavioral strategies for smoking cessation in these patients.

Tobacco use patterns and clinical outcomes in the T1D exchange

AIMS

This study examined associations between tobacco use and diabetes outcomes using the T1D Exchange Registry.

METHODS

Adult participants (N = 933) completed standardized questionnaires including self-reported outcomes: past year serious hypoglycemic and diabetic ketoacidosis episodes, diabetes self-care, diabetes distress, and self-monitoring of blood glucose. Chart-extracted outcomes included HbA1c, nephrology and neuropathy diagnoses, and BMI. We examined the relation of tobacco use status (never, former, current) and frequency of use (daily versus less than daily) to these outcomes.

RESULTS

The majority had never used tobacco (55%, n = 515); 27% (n = 252) were former users and 18% (n = 166) were current users (with 31% using daily). Tobacco status was associated with HbA1c, BMI, self-care, distress, and blood glucose monitoring frequency. Across most outcomes, current users evidenced worse values relative to never users, and former users were largely similar to never users. Daily use was associated with significantly worse outcomes on HbA1c, diabetes self-care, and distress scores relative to less than daily use.

CONCLUSIONS

These cross-sectional comparisons suggest that current tobacco use is associated with worse status on important clinical diabetes indicators. Former users did not evidence these deleterious associations. Findings point to potential diabetes-specific motivators that could inform tobacco cessation interventions.

Pathway Analysis of Global Metabolomic Profiles Identified Enrichment of Caffeine, Energy, and Arginine Metabolism in Smokers but Not Moist Snuff Consumers

Existing US epidemiological data demonstrate that consumption of smokeless tobacco, particularly moist snuff, is less harmful than cigarette smoking. However, the molecular and biochemical changes due to moist snuff consumption relative to smoking remain incompletely understood. We previously reported that smokers (SMK) exhibit elevated oxidative stress and inflammation relative to moist snuff consumers (MSC) and non-tobacco consumers (NTC), based on metabolomic profiling data of saliva, plasma, and urine from MSC, SMK, and NTC. In this study, we investigated the effects of tobacco consumption on additional metabolic pathways using pathway-based analysis tools. To this end, metabolic pathway enrichment analysis and topology analysis were performed through pair-wise comparisons of global metabolomic profiles of SMK, MSC, and NTC. The analyses identified >8 significantly perturbed metabolic pathways in SMK compared with NTC and MSC in all 3 matrices. Among these differentially enriched pathways, perturbations of caffeine metabolism, energy metabolism, and arginine metabolism were mostly observed. In comparison, fewer enriched metabolic pathways were identified in MSC compared with NTC (5 in plasma, none in urine and saliva). This is consistent with our transcriptomics profiling results that show no significant differences in peripheral blood mononuclear cell gene expression between MSC and NTC. These findings, taken together with our previous biochemical, metabolomic, and transcriptomic analysis results, provide a better understanding of the relative changes in healthy tobacco consumers, and demonstrate that chronic cigarette smoking, relative to the use of smokeless tobacco, results in more pronounced biological changes, which could culminate in smoking-related diseases.

The prevalence of retinopathy in patients with type 1 diabetes treated with education-based intensified insulin therapy and its association with parameters of glucose control

AIM

Prevalence of retinopathy (DR) in patients with type 1 diabetes treated with education-based intensified insulin therapy (EBIIT) and its association with parameters of glucose control.

METHODS

151 patients with mean diabetes duration of 14.3 years [SD ± 5.8]) were analyzed. Eyes were examined using standardized 7 field ETDRS (Early Treatment Diabetic Retinopathy Study) settings and images analyzed by a professional external reading center. The glucose exposure over time was defined as HbA1c years, i.e. the sum of the differences between annual mean HbA1c (in %) minus the ideal HbA1c of 6.0% (42 mmol/mol) for each diabetes year (e.g. HbA1c of 8% (64 mmol/mol) over 6 years gives an excess HbA1c of 2.0% (22 for mmol/mol) for 6 years, resulting in 12 HbA1c years (or 131 for mmol/mol)).

RESULTS

The median (interquartile range) of individual mean HbA1c was 7.3% (6.8-7.8) [56 mmol/mol (51-62)]. and the median HbA1c years was 16.8 (9.1-29.1) [183 mmol/mol (99-319)]. No evidence for DR was found in 59 patients (39%), stage 1 DR in 43 (28.5%), stage 2 in 41 (27.2%), stage 3 in 7 (4.6%) and proliferative DR stage 4 in 1 patient. The best correlation between severity of DR and diabetes control measures was found for HbA1c years (Pearson r = 0.41, p < 0.001).

CONCLUSIONS

In type 1 diabetes EBIIT is associated with good diabetes control and a low prevalence of DR. The cumulative glucose exposure over time given as HbA1c years is the best predictor for development of DR. ClinicalTrials.gov Identifier: NCT02307110.

The Role of Continuous Glucose Monitoring, Diabetes Smartphone Applications, and Self-Care Behavior in Glycemic Control: Results of a Multi-National Online Survey

Background: This study investigated the determinants (with a special emphasis on the role of diabetes app use, use of continuous glucose monitoring (CGM) device, and self-care behavior) of glycemic control of type 1 and type 2 diabetes mellitus (DM). Methods: A web-based survey was conducted using diabetes Facebook groups, online patient-forums, and targeted Facebook advertisements (ads). Demographic, CGM, diabetes app use, and self-care behavior data were collected. Glycemic level data were categorized into hyperglycemia, hypoglycemia, and good control. Multinomial logistic regression stratified by diabetes type was performed. Results: The survey URL was posted in 78 Facebook groups and eight online forums, and ten targeted Facebook ads were conducted yielding 1854 responses. Of those owning smartphones (n = 1753, 95%), 1052 (62.6%) had type 1 and 630 (37.4%) had type 2 DM. More than half of the type 1 respondents (n = 549, 52.2%) and one third the respondents with type 2 DM (n = 210, 33.3%) reported using diabetes apps. Increased odds of experiencing hyperglycemia were noted in persons with type 1 DM with lower educational status (Adjusted Odds Ratio (AOR) = 1.7; 95% Confidence Interval (CI): 1.21–2.39); smokers (1.63, 95% CI: 1.15–2.32), and high diabetes self-management concern (AOR = 2.09, 95% CI: 1.15–2.32). CGM use (AOR = 0.66, 95% CI: 0.44–1.00); “general diet” (AOR = 0.86, 95% CI: 0.79–0.94); and “blood glucose monitoring” (AOR = 0.88, 95%CI: 0.80–0.97) self-care behavior reduced the odds of experiencing hyperglycemia. Hypoglycemia in type 1 DM was reduced by using CGM (AOR = 0.24, 95% CI: 0.09–0.60), while it was increased by experiencing a high diabetes self-management concern (AOR = 1.94, 95% CI: 1.04–3.61). Hyperglycemia in type 2 DM was increased by age (OR = 1.02, 95% CI: 1.00–1.04); high self-management concern (AOR = 2.59, 95% CI: 1.74–3.84); and poor confidence in self-management capacity (AOR = 3.22, 2.07–5.00). Conversely, diabetes app use (AOR = 0.63, 95% CI: 0.41–0.96) and “general diet” self-care (AOR = 0.84, 95% CI: 0.75–0.94), were significantly associated with the reduced odds of hyperglycemia. Conclusion: Diabetes apps, CGM, and educational interventions aimed at reducing self-management concerns and enhancing dietary self-care behavior and self-management confidence may help patients with diabetes to improve glycemic control.

Mediation of the association of smoking and microvascular complications by glycemic control in type 1 diabetes

Studies have demonstrated the adverse effects of smoking on the risk of microvascular complications; however, few have also examined the potential mediating effects of glycemic control. Using data from the Diabetes Control and Complications Trial (DCCT 1983–1993), we describe the acute and long-term risks of smoking on glycemic control and microvascular complications in a well-characterized cohort of participants with type 1 diabetes. The DCCT recorded self-reported smoking behaviors, glycemic exposure based on HbA1c, and complications status. Generalized linear mixed models were used to assess whether time-dependent measurements of smoking predict HbA1c levels. Cox proportional hazard models were used to assess time-dependent smoking exposures as predictors of retinopathy and nephropathy. During a mean of 6.5 years of follow-up, current smokers had consistently higher HbA1c values and were at a higher risk of retinopathy and nephropathy compared with former and never smokers. These risk differences were attenuated after adjusting for HbA1c suggesting that the negative association of smoking on glycemic control is partially responsible for the adverse association of smoking on the risk of complications in type 1 diabetes. These findings support the potential for a beneficial effect of smoking cessation on complications in type 1 diabetes.

Smoking and diabetes: dangerous liaisons and confusing relationships

The combined harmful effects of cigarette smoking and hyperglycemia can accelerate vascular damage in patients with diabetes who smoke, as is well known. Can smoking cause diabetes? What are the effects of smoking on macro and microvascular complications? Now growing evidence indicates that regular smokers are at risk of developing incident diabetes. Since the prevalence rates of smoking in patients with diabetes are relatively similar to those of the general population, it is essential to address the main modifiable risk factor of smoking to prevent the onset of diabetes and delay the development of its complications. Quitting smoking shows clear benefits in terms of reducing or slowing the risk of cardiovascular morbidity and mortality in people with diabetes. Does quitting smoking decrease the incidence of diabetes and its progression? What are the effects of quitting smoking on complications? The current evidence does not seem to unequivocally suggest a positive role for quitting in patients with diabetes. Quitting smoking has also been shown to have a negative impact on body weight, glycemic control and subsequent increased risk of new-onset diabetes. Moreover, its role on microvascular complications of the disease is unclear. What are the current smoking cessation treatments, and which ones are better for patients with diabetes? Stopping smoking may be of value for diabetes prevention and management of the disease and its macrovascular and microvascular complications. Unfortunately, achieving long-lasting abstinence is not easy and novel approaches for managing these patients are needed. This narrative review examines the evidence on the impact of smoking and smoking cessation in patients with diabetes and particularly in type 2 diabetes mellitus and its complications. In addition, management options and potential future directions will be discussed.

Dose-dependent effect of smoking on risk of coronary heart disease, heart failure and stroke in individuals with type 1 diabetes

AIMS/HYPOTHESIS

The aim of this study was to assess the potential dose-dependent effects of smoking on the risk of CHD, heart failure and stroke in individuals with type 1 diabetes.

METHODS

The study included 4506 individuals with type 1 diabetes who were participating in the Finnish Diabetic Nephropathy (FinnDiane) study. Intensity of smoking was estimated by packs per day and cumulative smoking by pack-years. Cox regression analyses were used to estimate the risk of incident CHD, heart failure or stroke during follow-up.

RESULTS

One pack per day significantly increased the risk of incident CHD in current smokers compared with never smokers (HR 1.45 [95% CI 1.15, 1.84]), after adjustment for age, sex, HbA_1c, hypertension, duration of diabetes and BMI. The risk of CHD in former smokers was similar to the risk in never smokers. The risk of incident heart failure was 1.43 (95% CI 1.03, 1.97) in current smokers per one pack per day and 1.37 (95% CI 1.05, 1.77) in former smokers, while the risk of incident stroke was 1.70 (95% CI 1.26, 2.29) and 1.49 (95% CI 1.14, 1.93), respectively. After further adjustments for lipids, however, the difference in the risk of heart failure in current and former smokers was no longer significant. Cumulative smoking data were similar to smoking intensity data.

CONCLUSIONS/INTERPRETATION

There is a dose-dependent association between smoking and cardiovascular disease in individuals with type 1 diabetes. In men in particular, the risk of incident stroke remains high even after smoking cessation and is increased in current and former smokers independently of other risk factors.

Review of biomarkers to assess the effects of switching from cigarettes to modified risk tobacco products

Context: One approach to reducing the harm caused by cigarette smoking, at both individual and population level, is to develop, assess and commercialize modified risk alternatives that adult smokers can switch to. Studies to demonstrate the exposure and risk reduction potential of such products generally involve the measuring of biomarkers, of both exposure and effect, sampled in various biological matrices.Objective: In this review, we detail the pros and cons for using several biomarkers as indicators of effects of changing from conventional cigarettes to modified risk products.Materials and methods: English language publications between 2008 and 2017 were retrieved from PubMed using the same search criteria for each of the 25 assessed biomarkers. Nine exclusion criteria were applied to exclude non-relevant publications.Results: A total of 8876 articles were retrieved (of which 7476 were excluded according to the exclusion criteria). The literature indicates that not all assessed biomarkers return to baseline levels following smoking cessation during the study periods but that nine had potential for use in medium to long-term studies.Discussion and conclusion: In clinical studies, it is important to choose biomarkers that show the biological effect of cessation within the duration of the study.

Smoke exposure and cardio-metabolic profile in youth with type 1 diabetes

BACKGROUND

To evaluate the relationship between smoking and metabolic parameters in patients affected by type 1 diabetes (T1D).

PATIENTS AND METHODS

We enrolled 104 children and young adults (50 females and 54 males) with T1D (aged 16.4 ± 8.6 years). The subjects were divided into three groups according to their smoking habits: no smoking (NS), passive smoking (PS), active smoking (AS). The physical examination of the participants included nutritional status assessment by anthropometry and pubertal stage according to Marshall and Tanner as well as blood pressure measurement. In all patients, metabolic blood assays including fasting blood glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, and triglycerides were measured. Insulin resistance was determined by glucose disposal rate (eGDR). Physical activity was also recorded.

RESULTS

Significant differences in biochemical and functional parameters among the three groups were demonstrated, in particular for systolic (p = 0.002) and diastolic pressure (p = 0.02) and eGDR (p = 0.039). No differences in daily insulin dose (p = 0.75) and glycated hemoglobin (p = 0.39) were observed. AS group had significantly higher blood pressure (p < 0.05) and lower eGDR (p ≤ 0.001) compared to NS and PS. Significant difference was also detected between PS and NS in systolic and diastolic (p = 0.02) pressure and eGDR (p = 0.01). In a multivariable model adjusted for age, gender, BMI and physical activity, smoking habits did not maintain any independent association with metabolic parameters.

CONCLUSION

This is the first study in a Mediterranean population, looking at tobacco smoke and cardio-metabolic factors in youth with T1D. The relationship between smoking and unfavorable metabolic profile was demonstrated. On the basis of these findings, smoking tobacco should be considered an important modifiable risk factor for young patients with diabetes mellitus, highlighting the need for intensified smoking prevention and cessation programs.

Cigarette Smoking, Diabetes, and Diabetes Complications: Call for Urgent Action

PURPOSE OF REVIEW

This review aimed to examine the latest evidence linking cigarette smoking and cessation to risk of incident diabetes and its complications.

RECENT FINDINGS

Abundant evidence has demonstrated that smoking is associated with increased risk of type 2 diabetes and cardiovascular disease among diabetic patients, while its relationship with microvascular complications is more limited to diabetic nephropathy and neuropathy in type 1 diabetes. In addition, diabetes risk remains high in the short term after smoking cessation, while it reduces gradually in the long term. Risk of cardiovascular complications also substantially decreases after quitting smoking, but results for microvascular complications are not consistent. Smoking is associated with increased risks of incident diabetes in the general population and cardiovascular complications among diabetic patients. Although the short-term post-cessation diabetes risk needs to be acknowledged, this review calls for urgent action to implement population-wide policies and individual pharmaceutical and lifestyle interventions (if evidence accumulated in future) to aid smoking cessation and prevent diabetes and its complications.

Relationship of cardiometabolic parameters in non-smokers, current smokers, and quitters in diabetes: a systematic review and meta-analysis

BACKGROUND

Smoking is associated with increased macrovascular and microvascular complications in people with diabetes. In addition to other concomitant vascular perturbations, it also seems to influence the cardiometabolic parameters, which may partly explain the accelerated rate of vascular complications in smokers with diabetes. While smoking cessation is advocated as a universal component of the management of diabetes, there is some anecdotal evidence that HbA1c could increase following smoking cessation. The aim of this review is to explore the relationship between smoking and its cessation on cardiometabolic parameters in diabetes.

METHODS

Searches were conducted on Medline, EMBASE and CINAHL up to March 2016. After screening 6866 studies (Additional file 1), 14 observational studies with a total of 98,978 participants' with either type 1 or type 2 diabetes were selected for review. Narrative synthesis and meta-analyses were carried out to explore the relationship between smoking and its cessation.

RESULTS

Meta-analysis showed that the pooled mean difference of HbA1c between non-smokers and smokers was -0.61% (95% CI -0.88 to -0.33, p < 0.0001). The difference in LDL cholesterol between non-smokers and smokers was -0.11 mmol/l (95% CI -0.21 to -0.01, p = 0.04). The difference in HDL cholesterol between non-smokers and smokers was 0.12 mmol/l (95% CI 0.08-0.15, p < 0.001). However, there was no statistically significant difference in blood pressure between the two groups. The difference in HbA1c between quitters and continued smokers was not statistically significant -0.10% (95% CI -0.42 to 0.21, p = 0.53). However, a narrative synthesis revealed that over a period of 10 years, the HbA1c was comparable between non-smokers and quitters.

CONCLUSION

Non-smokers have a statistically significant lower HbA1c and more favourable lipid profile compared to smokers. Smoking cessation does not lead to an increase in HbA1c in long-term and may reduce vascular complications in diabetes by its favourable impact on lipid profile.

Type 1 diabetes & cardiovascular disease

Individuals with type 1 diabetes mellitus (T1DM) have a high risk of developing cardiovascular disease (CVD), but some risk factors can be mediated by lifestyle modification and medication. NPs should understand evidence-based management approaches to counsel patients with T1DM on appropriate self-management interventions to reduce the likelihood of CVD.

Smoking and progression of diabetic nephropathy in patients with type 1 diabetes

AIMS

To evaluate the effect of cumulative smoking on the development of diabetic nephropathy.

METHODS

Study included 3613 patients with type 1 diabetes, participating in the Finnish Diabetic Nephropathy Study. The 12-year cumulative risk of microalbuminuria, macroalbuminuria and end-stage renal disease (ESRD) was estimated for current, ex- and nonsmokers. Cox regression analyses, with multivariable adjustments for other risk factors for diabetic nephropathy, were used to evaluate the risk at different stages of diabetic nephropathy based on the cumulative amount of smoking in pack-years.

RESULTS

The 12-year cumulative risk of microalbuminuria was 18.9 % (95 % CI 14.6-23.0, P < 0.0001) for current smokers and 15.1 % (10.3-19.6, P = 0.087) for ex-smokers, compared with 10.0 % (7.8-12.1) for nonsmokers. The corresponding risks of macroalbuminuria were 14.4 % (95 % CI 10.8-17.9, P < 0.0001), 6.1 % (3.5-8.6, P = 0.082) and 4.7 % (3.0-6.4), respectively. The 12-year cumulative risk of ESRD was 10.3 % (95 % CI 8.4-12.4, P < 0.0001) for current smokers and 10.0 % (7.9-12.3, P < 0.0001) for ex-smokers, compared with 5.6 % (4.6-6.7) for nonsmokers. In the current smokers, one pack-year increased the risk of macroalbuminuria with a HR of 1.025 (1.010-1.041) and the risk of ESRD with a HR of 1.014 (1.001-1.026) compared with nonsmokers, in the fully adjusted model. In the ex-smokers, the risk of macroalbuminuria and ESRD was no different from the risk in nonsmokers after multivariable adjustment.

CONCLUSIONS

Current smoking is a risk factor for the progression of diabetic nephropathy and the risk increases with the increasing dose of smoking. Ex-smokers seem to carry a similar risk of progression of diabetic nephropathy as nonsmokers.

Acquired Cystic Fibrosis Transmembrane Conductance Regulator Dysfunction in Chronic Bronchitis and Other Diseases of Mucus Clearance

Chronic obstructive pulmonary disease (COPD) is a major public health problem. No therapies alter the natural history of the disease. Chronic bronchitis is perhaps the most clinically troublesome phenotype. Emerging data strongly suggest that cigarette smoke and its components can lead to acquired cystic fibrosis transmembrane conductance regulator (CFTR) dysfunction. Findings in vitro, in animal models, and in smokers with and without COPD also show acquired CFTR dysfunction, which is associated with chronic bronchitis. This abnormality is also present in extrapulmonary organs, suggesting that CFTR dysfunction may contribute to smoking-related systemic diseases.

Association of diet and lifestyle with glycated haemoglobin in type 1 diabetes participants in the EURODIAB prospective complications study

BACKGROUND/OBJECTIVES

Diet and lifestyle advice for type 1 diabetes (T1DM) patients is based on little evidence and putative effects on glycaemic control. Therefore, we investigated the longitudinal relation between dietary and lifestyle variables and HbA1c levels in patients with type 1 diabetes.

SUBJECTS/METHODS

A 7-year prospective cohort analysis was performed in 1659 T1DM patients (52% males, mean age 32.5 years) participating in the EURODIAB Prospective Complications Study. Baseline dietary intake was assessed by 3- day records and physical activity, smoking status and alcohol intake by questionnaires. HbA1c during follow-up was centrally assessed by immunoassay. Analysis of variance (ANOVA) and restricted cubic spline regression analyses were performed to assess dose-response associations between diet and lifestyle variables and HbA1c levels, adjusted for age, sex, lifestyle and body composition measures, baseline HbA1c, medication use and severe hypoglycaemic attacks.

RESULTS

Mean follow-up of our study population was 6.8 (s.d. 0.6) years. Mean HbA1c level was 8.25% (s.d. 1.85) (or 66.6 mmol/mol) at baseline and 8.27% (s.d. 1.44) at follow-up. Physical activity, smoking status and alcohol intake were not associated with HbA1c at follow-up in multivariable ANOVA models. Baseline intake below the median of vegetable protein (<29 g/day) and dietary fibre (<18 g/day) was associated with higher HbA1c levels. Restricted cubic splines showed nonlinear associations with HbA1c levels for vegetable protein (P (nonlinear)=0.008) and total dietary fibre (P (nonlinear)=0.0009).

CONCLUSIONS

This study suggests that low intake of vegetable protein and dietary fibre are associated with worse glycaemic control in type 1 diabetes.

In adult patients with type 1 diabetes healthy lifestyle associates with a better cardiometabolic profile

BACKGROUND/AIMS

Little is known about lifestyle habits of adults with type 1 diabetes (T1D) and their association with cardiometabolic risk (CMR) factors. The aims of the present study were to determine the prevalence of adults with T1D who adopted a healthy lifestyle and to explore the association between a healthy lifestyle and the cardiometabolic profile.

METHODS AND RESULTS

This is a cross-sectional analysis of 115 adults with T1D. Participants wore a motion sensor and completed a 3-day food record. The following CMR factors were assessed: body mass index, waist circumference, body composition (iDXA), glycated hemoglobin, lipids and blood pressure. Insulin resistance was estimated (estimated glucose disposal rate). Participants were classified according to the number of healthy lifestyle habits adopted (ranging from 0 to 3): regular physical activity (physical activity level ≥1.7), good diet quality (Canadian Healthy Eating Index score >80) and none-smoking status. The proportion of participants who adopted 3, 2, 1 or 0 lifestyle habits were 11%, 30%, 37%, and 23%, respectively. As the number of healthy lifestyle habits adopted increased, participants had significantly lower body mass index, waist circumference, body fat, total cholesterol, non-HDL-cholesterol, triglycerides and systolic blood pressure (p < 0.05). In addition, a trend for lower estimated insulin resistance was observed (p = 0.06). For each increase of one healthy lifestyle habit, body mass index decreased by 1.9 kg/m(2), waist circumference by 4.0 cm for men and 4.8 cm for women and trunk fat by 3.6% for men and 4.1% for women.

CONCLUSIONS

These results suggest the importance of a healthy lifestyle among adults with T1D in order to control CMR factors.

Continued smoking abstinence in diabetic patients in primary care: a cluster randomized controlled multicenter study

AIMS

To assess the effectiveness of an intensive smoking cessation intervention based on the transtheoretical model of change (TTM) in diabetic smokers attending primary care.

METHODS

A cluster randomized controlled clinical trial was designed in which the unit of randomization (intervention vs. usual care) was the primary care team. An intensive, individualized intervention using motivational interview and therapies and medications adapted to the patient's stage of change was delivered. The duration of the study was 1 year.

RESULTS

A total of 722 people with diabetes who were smokers (345 in the intervention group and 377 in the control group) completed the study. After 1 year, continued abstinence was recorded in 90 (26.1%) patients in the intervention group and in 67 (17.8%) controls (p=0.007). In patients with smoking abstinence, there was a higher percentage in the precontemplation and contemplation stages at baseline in the intervention group than in controls (21.2% vs. 13.7%, p=0.024). When the precontemplation stage was taken as reference (OR=1.0), preparation/action stage at baseline showed a protective effect, decreasing 3.41 times odds of continuing smoking (OR=0.293 95% CI 0.179-0.479, p<0.001). Contemplation stage at baseline also showed a protective effect, decreasing the odds of continuing smoking (OR=0.518, 95% CI 0.318-0.845, p=0.008).

CONCLUSIONS

An intensive intervention adapted to the individual stage of change delivered in primary care was feasible and effective, with a smoking cessation rate of 26.1% after 1 year.

Tobacco smoking, epilepsy, and seizures

Tobacco smoking is considered the greatest risk factor for death caused by noncommunicable diseases. In contrast to extensive research on the association between tobacco smoking and diseases such as heart attack, stroke, and cancers, studies on the association between tobacco smoking and seizures or epilepsy are insufficient. The exact roles tobacco smoking and nicotine use play in seizures or epilepsy have not been well reviewed. We reviewed available literature and found that 1) there are vast differences between tobacco smoke and nicotine based on their components and their effects on seizures or epilepsy; 2) the seizure risk in acute active tobacco smokers, women who smoke during pregnancy, electronic cigarette smokers, and the role of smoking in sudden unexplained/unexpected death in epilepsy remain unclear; 3) seizure risks are higher in acute secondhand smokers, chronic active smokers, and babies whose mothers smoke; 4) tobacco smoke protects against seizures in animal models whereas nicotine exerts mixed effects in animals; and 5) tobacco smoking agents can be noneffective, proconvulsant, or anticonvulsant. Finally, the opportunities for future research on this topic is discussed.