Objective measurements of activity patterns in people with newly diagnosed Type 2 diabetes demonstrate a sedentary lifestyle

Accelerometer-derived physical activity and sedentary behaviors in individuals with newly diagnosed type 2 diabetes: A cross-sectional study from the Danish nationwide DD2 cohort

Introduction

Habitual physical activity behaviors of individuals with new-onset type 2 diabetes are largely unknown. We aimed to investigate accelerometer-derived physical activity behaviors in individuals with newly diagnosed type 2 diabetes. We also examined sociodemographic and health-related correlates of a high-risk physical activity profile.

Methods

This cross-sectional study used data from 768 participants enrolled in an intervention study nested within the Danish Centre for Strategic Research in Type 2 diabetes (DD2) cohort. Physical activity was assessed by 24-h dual monitor accelerometry. Prevalence ratios of having a high-risk physical activity profile were estimated using Poisson regression adjusted for age and sex.

Results

Study participants spent on average 9.7 (25th and 75th percentiles, 8.3; 11.1) hours/day sitting, walked for 1.1 (0.8; 1.6) hours/day and accumulated 4,000 (2,521; 5,864) steps/day. Still, 62% met the recommendations for physical activity. Characteristics associated with a high-risk physical activity profile (observed in 24.5% of participants) included older age, higher body mass index (BMI), unemployment, retirement, comorbidities, and current smoking. Hence, participants aged 60-69, 70-79 and 80+ years had prevalence ratios of 2.12 (95% CI 1.31; 3.42), 1.99 (1.18; 3.34) and 3.09 (1.42; 6.75) for a high-risk activity profile, respectively, versus participants <50 years. BMI values of 30-39 and 40+ were associated with 1.83 (1.06; 3.15) and 3.38 (1.88; 6.05) higher prevalence ratios compared to normal-weight. Unemployment or retirement was associated with 1.62 (1.09; 2.41) and 2.15 (1.37; 3.39) times higher prevalence ratios, compared to individuals in the working force. Having a Charlson Comorbidity Index score of 1-2 or 3+ was associated with 1.36 (1.03-1.79) and 1.90 (1.27-1.84) higher prevalence ratios, while current smoking was associated with a prevalence ratio of 1.72 (1.25; 2.35) compared to never smokers.

Conclusion

This study shows that 62% of individuals with newly diagnosed type 2 diabetes met the recommendations for physical activity. Still, the majority of participants were also highly sedentary and accumulated very few daily steps, emphasizing the need for focusing on both increasing physical activity and reducing sedentary behaviors in the prevention of diabetes-related complications. Individuals with a high-risk physical activity profile were characterized by more obesity, socioeconomic inequalities, advanced age and comorbidities.Trial registration number: NCT02015130.

Effects of break in sedentary behaviour on blood glucose control in diabetic patients. Systematic review

INTRODUCTION

One of the main goals of prescribing physical activity for people with type 2 diabetes is to reduce hyperglycaemia, as it is a risk factor for the development of chronic complications. As less time spent each day in sedentary behaviour would lead to higher glucose consumption by skeletal muscle tissue, this could have significant positive effects on blood glucose control parameters. For this reason, the aim of this study was to analyse the information from different protocols for breaking sedentary behaviour and the association with blood glucose control parameters in patients with type 2 diabetes.

MATERIAL AND METHODS

A systematic search was carried out for randomised controlled studies on this topic published in the scientific literature. The following databases were considered: PubMed, Cochrane, EBSCO, WoS, ScienceDirect and Medline.

RESULTS

24 studies were identified and analysed using the COVIDENCE platform. Seven articles were selected for the final analysis, comprising 138 patients. The results show that breaks in sedentary behaviour with light physical activity in people with type 2 diabetes are effective in reducing insulin resistance, the area under the glucose curve, fasting and postprandial blood glucose, and blood glucose variability.

CONCLUSIONS

Acute interruption of sedentary behaviour, through light-intensity and short-duration exercise, can improve blood glucose indicators in patients with type 2 diabetes, including short term blood glucose variability.

The Physical Activity Assessment of Adults With Type 2 Diabetes Using Accelerometer-Based Cut Points: Scoping Review

Background

Incorporating physical activity into lifestyle routines is recommended for individuals with type 2 diabetes. Accelerometers offer a promising method for objectively measuring physical activity and for assessing interventions. However, the existing literature for accelerometer-measured physical activity among middle-aged and older adults with type 2 diabetes is lacking.

Objective

This study aims to identify research studies in which accelerometer-based cut points were used to classify the physical activity intensity of middle-aged to older adults with type 2 diabetes as sedentary, light, moderate, vigorous, and very vigorous, and to determine if validated accelerometer cut points specifically for this population exist.

Methods

We followed the Joanna Briggs Institute methodology for scoping reviews. Between June 23 and July 12, 2020, two reviewers independently screened records from four databases (PubMed, Web of Science, Embase, Engineering Village) and the ActiGraph Corp web site for eligible studies that included patients with type 2 diabetes with a sample mean age ≥50 years, used research-grade accelerometers, applied cut points to categorize objectively measured physical activity, and were available in English. We excluded studies reporting exclusively steps or step counts measured by accelerometers or pedometers and conference abstracts or other sources that did not have a full text available. Data extraction was completed using Microsoft Excel. Data for the following variables were tabulated based on frequency distributions: study design, accelerometer type, device placement, epoch length, total wear time, and cut points used. Study aims and participant demographic data were summarized.

Results

A total of 748 records were screened at the abstract level, and 88 full-text articles were assessed for eligibility. Ultimately, 46 articles were retained and analyzed. Participants’ mean ages ranged from 50 to 79.9 years. The ActiGraph accelerometer and the Freedson et al and Troiano et al counts-per-minute cut points were the most frequently used across the literature. Freedson et al and Troiano et al counts-per-minute cut points for light, moderate, and vigorous activity correspond to <1952, 1952-5724, and ≥5725, and 100-2019, 2020-5998, and ≥5999, respectively. The Lopes et al cut points were developed by calibrating the ActiGraph in middle-aged and older adults with overweight/obesity and type 2 diabetes. These counts-per-minute thresholds are ≥200 (light), ≥1240 (moderate), and ≥2400 (vigorous), and were applied in 1 interventional study.

Conclusions

An assortment of accelerometer cut points have been used by researchers to categorize physical activity intensity for middle-aged and older adults with diabetes. Only one set of cut points was validated and calibrated in our population of interest. Additional research is warranted to address the need for diabetes-specific cut points to inform public health recommendations. This includes confirmation that the Lopes et al cut points reflect clinically meaningful changes in physical activity for adults with diabetes who have comorbidities other than overweight/obesity and the development of relative intensity cut points that may be more suitable for those with suboptimal physical functioning.

Glucose variability and low bone turnover in people with type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is related to an increased fracture risk and low bone turnover. However, the mechanisms are not elucidated. In the present study we investigate the association between glycemic variability and bone turnover markers.

METHODS

100 participants with T2D and 100 age and gender matched controls were included in this cross-sectional study. All participants with T2D were equipped with a continuous glucose monitoring (CGM) sensor for 3 days (CGMS iPro Continuous Glucose Recorder; Medtronic MiniMed). The dawn glucose levels were defined as a morning period starting 1 h before breakfast ending 1 h post ingestion. On all participants serum (s)-C-terminal cross-linked telopeptide of type-I collagen (CTX), s-procollagen type 1 amino terminal propeptide (P1NP), and s-sclerostin were measured.

RESULTS

Participants with T2D displayed significantly lower levels of the bone resorption marker s-CTX and the bone formation marker s-P1NP compared to controls. S-CTX was significantly negatively associated with the mean amplitude of glycemic excursions (MAGE) and the dawn glucose levels whereas s-P1NP only was significantly negatively associated with the dawn glucose levels while it was borderline significantly associated with MAGE (p = 0.05). S-CTX and s-P1NP were significantly lower among the 50% with the highest dawn glucose levels compared to the 50% lowest dawn glucose levels also after adjustment for age, gender, glycated hemoglobin A1c (HbA1c), and body mass index (BMI).

CONCLUSION

We observed that the amplitude of glycemic excursions and rise in dawn glucose was negatively associated with bone turnover markers. Future research is needed to determine whether reduction of the amplitude of glycemic excursions increase bone turnover markers.

Low physical activity is associated with impaired endothelial function in patients with type 2 diabetes and controls after 5 years of follow-up

BACKGROUND

The long-term association between physical activity and endothelial function has not previously been investigated in patients with type 2 diabetes. Therefore, we aimed to evaluate the relationship between physical activity and endothelial function, assessed by peripheral arterial tonometry, in patients with type 2 diabetes and non-diabetic controls after 5 years of follow-up.

METHODS

We included 51 patients with newly diagnosed type 2 diabetes and 53 sex- and age matched controls. Participants underwent baseline clinical characterization including objective measurement of physical activity level using accelerometery. After 5 years of follow-up, participants were re-examined, and endothelial function was assessed as natural logarithm of reactive hyperemia index (lnRHI).

RESULTS

Physical activity at baseline was associated with lnRHI after 5 years of follow-up in both patients with type 2 diabetes and controls. An increase of 1 standard deviation (SD) in daytime physical activity corresponded to a 6.7 % increase in RHI (95 % confidence interval: 1.1;12.5 %, p = 0.02). We found no difference in lnRHI between patients with diabetes and controls (0.67 ± 0.29 vs. 0.73 ± 0.31, p = 0.28).

CONCLUSIONS

Daytime physical activity is associated with endothelial function after 5 years of follow-up in patients with type 2 diabetes and controls.

Descriptive Epidemiology of Interruptions to Free-Living Sitting Time in Middle-Age and Older Adults

National guidelines recommend physically active interruptions to sitting time, however, the characteristics of these interruptions are broadly stated and ill-defined. A robust methodology for population surveillance for such interruptions is needed.

PURPOSE

To describe the frequency and characteristics (i.e., duration, stepping time, and estimated intensity) of all interruptions and physically active interruptions to adults' free-living sitting time (i.e., transitions from sitting to upright posture) across segments of the population.

METHODS

Australian Diabetes, Obesity and Lifestyle (AusDiab) study participants (321 men; 406 women; mean ± SD 58.0 ± 10.3 years) wore the activPAL3TM for ≥1 valid day. The characteristics of interruptions from laboratory studies demonstrating health benefits were selected to define active interruptions (≥5 min upright and/or ≥ 2 min stepping) and ambulatory interruptions (≥2 min stepping). The frequency and characteristics of all, active, and ambulatory interruptions were described and compared by age, gender, diabetes status, and body mass index.

RESULTS

Adults averaged 55.0 ± 21.8 interruptions per day, but only 20.3 ± 6.7 were active and 14.0 ± 5.4 were ambulatory. Median (25th, 75th percentile) duration was 2.6 (0.9, 7.8) minutes, stepping time was 0.8 (0.3, 2.0) minutes, and estimated energy expenditure was 4.3 (1.4, 12.5) MET-min. Those who were older, had obesity, or had diabetes had significantly (p < 0.05) fewer interruptions of all types and less stepping time during active interruptions than their counterparts (Cohen's d < 0.2).

CONCLUSION

Free-living interruptions were often less active than interruptions performed in effective acute laboratory studies and their content varied widely between population groups. Monitoring all interruptions as well as those that are more active is advisable to provide a comprehensive understanding of free-living sedentary behavior.

Incidence of low back pain and potential risk factors among pharmacists: A population-based cohort study in Taiwan

Low back pain (LBP) is one of the most common symptoms of work-related musculoskeletal disorders in pharmacists. This can impede the physical functions of the body and lead to incapacitation, resulting in significant social and economic burden. This study aimed to investigate the incidence and risk factors that correlate with LBP in Taiwanese pharmacists.A retrospective cohort study was conducted among all registered pharmacists aged 20 to 40 years using the National Health Insurance Research Database (2000-2013) in Taiwan. The LBP diagnosis was confirmed with one episode of hospitalization or at least three claimed outpatient visits for LBP. Data on workplace characteristics as well as comorbidities were also collected for the analyses. A Cox proportional hazard regression was used to estimate the risk factors for LBP.The incidence rate of LBP among pharmacists was 16.60% in this study. Older pharmacists (28.49%; P < .01) and those who worked at district hospitals (23.51%; P < .01) showed a higher proportion of LBP. Furthermore, after adjustment for selected potential confounding factors, female pharmacists [adjusted hazard ratio (aHR): 1.12, 95% confidence interval (95% CI): 1.01-1.24, P = .0354] and pharmacists with diabetes (aHR: 1.55; 95% CI: 1.20-2.01; P = .0008) and gout (aHR: 1.70; 95% CI: 1.37-2.09; P < .0001) had significantly higher risks of LBP.In conclusion, age was positively correlated with LBP, and the workplace was an important factor in the development of LBP in pharmacists. We suggest that pharmacists who work in district hospitals should pay more attention to the development of LBP.

Low Physical Activity in Patients with Complicated Type 2 Diabetes Mellitus Is Associated with Low Muscle Mass and Low Protein Intake

Objective: In order to promote physical activity (PA) in patients with complicated type 2 diabetes, a better understanding of daily movement is required. We (1) objectively assessed PA in patients with type 2 diabetes, and (2) studied the association between muscle mass, dietary protein intake, and PA. Methods: We performed cross-sectional analyses in all patients included in the Diabetes and Lifestyle Cohort Twente (DIALECT) between November 2016 and November 2018. Patients were divided into four groups: <5000, 5000–6999, 7000–9999, ≥ 10,000 steps/day. We studied the association between muscle mass (24 h urinary creatinine excretion rate, CER) and protein intake (by Maroni formula), and the main outcome variable PA (steps/day, Fitbit Flex device) using multivariate linear regression analyses. Results: In the 217 included patients, the median steps/day were 6118 (4115–8638). Of these patients, 48 patients (22%) took 7000–9999 steps/day, 37 patients (17%) took ≥ 10,000 steps/day, and 78 patients (36%) took <5000 steps/day. Patients with <5000 steps/day had, in comparison to patients who took ≥10,000 steps/day, a higher body mass index (BMI) (33 ± 6 vs. 30 ± 5 kg/m², p = 0.009), lower CER (11.7 ± 4.8 vs. 14.8 ± 3.8 mmol/24 h, p = 0.001), and lower protein intake (0.84 ± 0.29 vs. 1.08 ± 0.22 g/kg/day, p < 0.001). Both creatinine excretion (β = 0.26, p < 0.001) and dietary protein intake (β = 0.31, p < 0.001) were strongly associated with PA, which remained unchanged after adjustment for potential confounders. Conclusions: Prevalent insufficient protein intake and low muscle mass co-exist in obese patients with low physical activity. Dedicated intervention studies are needed to study the role of sufficient protein intake and physical activity in increasing or maintaining muscle mass in patients with type 2 diabetes.

Is There an Association between Diabetes and Neck and Back Pain? Results of a Case-Control Study

We aimed to assess if subjects with diabetes exhibit higher prevalence of chronic back pain than age-sex-province of residence-matched non-diabetic controls. We also aimed to identify predictors for chronic neck pain (CNP) or chronic low back pain (CLBP) among subjects with diabetes. A case control study was conducted using data obtained from the Spanish National Health Survey 2017. Multivariable conditional and unconditional logistic regression models were constructed. A total of 2095 diabetes sufferers and 2095 non-diabetic matched controls were analyzed. The prevalence of CNP and CLBP was 27.3% and 34.8%, respectively, in diabetes sufferers and 22.1% and 29.0% in non-diabetes controls (both, p < 0.001). After multivariable analysis, the ORs showed significantly higher adjusted risk of CNP (OR 1.34; 95% CI 1.19–1.51) and CLBP (OR 1.19, 95% CI 1.09–1.31) in diabetes cases. Diabetes sufferers with CNP or CLBP showed higher use of pain medication and higher prevalence of migraine/frequent headache than controls. Female sex, worse self-rated health and use of pain medication were predictors for CNP and CLBP in subjects with diabetes. CNP and CLBP are significantly more prevalent in diabetes sufferers than in controls. Current results can help to design better preventive and educational strategies for these highly prevalent and burdensome pains among diabetic patients.

Physical behaviors and chronotype in people with type 2 diabetes

INTRODUCTION

Previous investigations have suggested that evening chronotypes may be more susceptible to obesity-related metabolic alterations. However, whether device-measured physical behaviors differ by chronotype in those with type 2 diabetes (T2DM) remains unknown.

RESEARCH DESIGN AND METHODS

This analysis reports data from the ongoing Chronotype of Patients with Type 2 Diabetes and Effect on Glycaemic Control (CODEC) observational study. Eligible participants were recruited from both primary and secondary care settings in the Midlands area, UK. Participants were asked to wear an accelerometer (GENEActiv, ActivInsights, Kimbolton, UK) on their non-dominant wrist for 7 days to quantify different physical behaviors (sleep, sedentary, light, moderate-to-vigorous physical activity (MVPA), intensity gradient, average acceleration and the acceleration above which the most active continuous 2, 10, 30 and 60 min are accumulated). Chronotype preference (morning, intermediate or evening) was assessed using the Morningness-Eveningness Questionnaire. Multiple linear regression analyses assessed whether chronotype preference was associated with physical behaviors and their timing. Evening chronotypes were considered as the reference group.

RESULTS

635 participants were included (age=63.8±8.4 years, 34.6% female, body mass index=30.9±5.1 kg/m²). 25% (n=159) of the cohort were morning chronotypes, 52% (n=330) intermediate and 23% (n=146) evening chronotypes. Evening chronotypes had higher sedentary time (28.7 min/day, 95% CI 8.6 to 48.3) and lower MVPA levels (-9.7 min/day, -14.9 to -4.6) compared to morning chronotypes. The intensity of the most active continuous 2-60 min of the day, average acceleration and intensity gradient were lower in evening chronotypes. The timing of physical behaviors also differed across chronotypes, with evening chronotypes displaying a later sleep onset and consistently later physical activity time.

CONCLUSIONS

People with T2DM lead a lifestyle characterized by sedentary behaviors and insufficient MVPA. This may be exacerbated in those with a preference for 'eveningness' (ie, go to bed late and get up late).

Association between Chronic Pain and Diabetes/Prediabetes: A Population-Based Cross-Sectional Survey in Saudi Arabia

Background. Diabetes is a debilitating chronic health condition that is associated with certain pain syndromes. The present study sought to evaluate chronic pain and its association with diabetes mellitus at a population level. Methods. A population-based cross-sectional questionnaire survey study was conducted in Al-Kharj, Saudi Arabia, from January 2016 to June 2016. Participants from both private and governmental institutions were selected following a multistage sampling technique and using a cluster sampling method. Anthropometric measurements were taken, including body weight, height, body mass index (BMI) and waist circumference. A blood sample was also drawn from each respondent for fasting blood sugar, HbA1c, and fasting lipid profile. A P value of less than 0.05 indicated statistical significance. Results. A total of 1003 subjects were included for final analysis. Compared to prediabetic and nondiabetic individuals, diabetic subjects had a higher prevalence of lower limb pain (11.1%), back pain (8.9%), abdominal pain (6.7%), and neck pain (4.4%) (X2 = 27.792, P=0.015). In a multiple logistic regression model, after adjusting for age, gender, education level, cholesterol, and smoking status, diabetic/prediabetic patients had a significantly higher prevalence of chronic pain ((OR) = 1.931 (95% CI = 1.536–2.362), P=0.037). Increased age was also significantly associated with chronic pain ((OR) = 1.032 (95% CI = 1.010–1.054, P=0.004). Conclusion. Results of this study found a significant association between diabetes and prediabetes and chronic pain symptoms. Prospective studies are needed to explore temporality of such association.

Association between Chronic Pain and Diabetes/Prediabetes: A Population-Based Cross-Sectional Survey in Saudi Arabia

BACKGROUND

Diabetes is a debilitating chronic health condition that is associated with certain pain syndromes. The present study sought to evaluate chronic pain and its association with diabetes mellitus at a population level.

METHODS

A population-based cross-sectional questionnaire survey study was conducted in Al-Kharj, Saudi Arabia, from January 2016 to June 2016. Participants from both private and governmental institutions were selected following a multistage sampling technique and using a cluster sampling method. Anthropometric measurements were taken, including body weight, height, body mass index (BMI) and waist circumference. A blood sample was also drawn from each respondent for fasting blood sugar, HbA1c, and fasting lipid profile. A P value of less than 0.05 indicated statistical significance.

RESULTS

A total of 1003 subjects were included for final analysis. Compared to prediabetic and nondiabetic individuals, diabetic subjects had a higher prevalence of lower limb pain (11.1%), back pain (8.9%), abdominal pain (6.7%), and neck pain (4.4%) (X ² = 27.792, P = 0.015). In a multiple logistic regression model, after adjusting for age, gender, education level, cholesterol, and smoking status, diabetic/prediabetic patients had a significantly higher prevalence of chronic pain ((OR) = 1.931 (95% CI = 1.536-2.362), P = 0.037). Increased age was also significantly associated with chronic pain ((OR) = 1.032 (95% CI = 1.010-1.054, P = 0.004).

CONCLUSION

Results of this study found a significant association between diabetes and prediabetes and chronic pain symptoms. Prospective studies are needed to explore temporality of such association.

Objectively Measured Physical Activity in Older Adults With and Without Diabetes

In Brief People with known diabetes were found to be 20% less active than people without diabetes as measured by objective accelerometers. A threshold of 6,000 steps per day was associated with the lowest risk of prevalent diabetes. The study also emphasizes the use of objective techniques to measure physical activity in subjects with diabetes.

How to Use Blockchain for Diabetes Health Care Data and Access Management: An Operational Concept

INTRODUCTION

Patients with diabetes often generate large amounts of data specifically related to the disease and to their general health. Cross-institutional sharing of patient health care data is complex, and as a consequence, data are not always available to the health care provider treating the patient. Accommodating this challenge could lead to better clinical effectiveness and improve clinical research. This work aims to present an approach for a blockchain-based platform for sharing health care data. The approach considers privacy concerns, data sharing, and patients as the center for governing their own data.

METHODS

The concept of this blockchain-based platform consists of using the NEM multi-signature blockchain contracts for access control of data management and the sharing and encryption of data to allow privacy and control of health care data. The architecture is built around cryptography, tokens, and multi-signature contracts. The multi-signature contract enables several entities to administrate the activity of an account and control the assets of one account. Multi-signature generates a contract that assigns the rights and powers of a certain account to other accounts; this contract can be edited to allow or remove entities.

DISCUSSION

Using blockchain could lead to improvements in diabetes data management. In the coming years, this technology should be implemented in existing small-scale diabetes health care system to explore its real-world benefits and challenges.

CONCLUSION

This new approach could potentially lead to more efficient sharing of data between institutions and utilization of new types of data and research possibilities.

Objective Measurement of Physical Activity in Adults With Newly Diagnosed Type 1 Diabetes and Healthy Individuals

Aims: Physical activity (PA) has many benefits in type 1 diabetes mellitus (type 1 DM). However, PA levels in people with type 1 DM have not previously been measured accurately. We aimed to compare objectively measured PA in adults recently diagnosed with type 1 DM and healthy adults.

Methods: Accelerometer data from 65 healthy adults [mean (SD) age 31 (13), 29% men] were compared with data from 50 people with type 1 DM [mean (SD) age 33 (10), 64% men], time since diagnosis <3months, HbA1c 76 ± 25 mmol/mol) in the EXTOD (Exercise for Type 1 Diabetes) pilot study. Briefly, EXTOD investigated the feasibility of recruiting recently diagnosed adults with type 1 DM into a yearlong exercise intervention. Multiple-regression models were used to investigate the association between diabetes status and activity outcomes.

Results: Adults recently diagnosed with type 1 DM spent on average a quarter less time in moderate-to-vigorous-physical-activity (MVPA) per day than healthy adults [after adjusting for confounders, predicted values: type 1 DM adults: [mean (SD)] 37.4 mins/day (9.1) Healthy adults: 52.9 mins/day (11.0)]. No difference in MVPA between the groups was seen at the weekend, but adults with type 1 DM spent more time in light physical activity (LPA), and less time in sedentary behavior. Time spent in sedentary or LPA during weekdays did not differ between groups.

Summary: Adults recently diagnosed with type 1 DM do less MVPA. Health care workers should encourage these people to engage in more PA. Further studies are needed to assess PA in people with type 1 DM of longer duration.

[Comorbidity of type 2 diabetes mellitus and low back pain]

Diabetes mellitus (DM) and back pain are widespread and often develop simultaneously. In patients with DM 2 type, the incidence of back pain is increased. The association of DM with the severity of pain and the frequency of its chronization and recurrence has been revealed. The most likely mechanism of such an association is the lesion of intervertebral discs mediated by the accumulation of advanced glycation end-products (EGP). In DM the concentration of EGP increases significantly; they initiate ectopic calcification, a decrease in cell density in the end plates, and changes in vertebras. Cells of the pulpous nuclei begin to produce pro-inflammatory cytokines and chemokines that trigger the processes of angio- and neurogenesis. Dorsopathies develop due to other etiological factors, but the mechanisms of systemic inflammation are similar. Thus, DM and back pain are comorbid pathologies with common elements in pathogenesis. To prevent the development of dorsopathy in DM 2 type it is considered promising to use drugs that reduce the intensity of accumulation of AGP and inhibitors of pro-inflammatory cytokines, for example, symptomatic slow acting drugs.

Health outcomes associated with reallocations of time between sleep, sedentary behaviour, and physical activity: a systematic scoping review of isotemporal substitution studies

Background

During a 24-h day, each given period is spent in either sedentary behaviour, sleeping, light physical activity (LPA), or moderate-to-vigorous physical activity (MVPA). In epidemiological research most studies have traditionally analysed the associations of these behaviours in isolation from each other; that is, without taking into account the displacement of time spent in the remaining behaviours. In recent years, there has been a growing interest in exploring how all the behaviours across the energy expenditure spectrum influence health outcomes. A statistical model used to investigate these associations is termed an isotemporal substitution model (ISM). Considering the increasing number of ISM-based studies conducted in all age groups, the present paper aimed to: (i) review and summarise findings from studies that employed ISM in sleep, sedentary behaviour, and physical activity research; (ii) appraise the methodological quality of the studies; and (iii) suggest future research directions in this area.

Methods

A systematic search of ten databases was performed. The Newcastle–Ottawa scale was used to assess the methodological quality of the included studies.

Results

Fifty-six studies met the inclusion criteria, all being of moderate or high methodological quality. Associations were reported for exchanged time varying from one minute to 120 min/day across the studies, with 30 min/day being the most common amount of time reallocated. In total, three different ISM methodologies were used. The most commonly studied health outcomes in relation to isotemporal substitutions were mortality, general health, mental health, adiposity, fitness, and cardiometabolic biomarkers. It seems that reallocations of sedentary time to LPA or MVPA are associated with significant reduction in mortality risk. Current evidence appears to consistently suggest that reductions in mortality risk are greater when time spent sedentary is replaced with higher intensities of physical activity. For adiposity, it seems that reallocating sedentary time to physical activity may be associated with reduced body mass index, body fat percentage, and waist circumference in all age groups, with the magnitude of associations being greater for higher intensities of physical activity. While there is a relatively large body of evidence reporting beneficial associations between the reallocation of time from sedentary behaviour to LPA or MVPA and cardiometabolic biomarkers among adults, there is a lack of studies among children, adolescents, and older adults. Although some studies investigated general health, mental health, and fitness outcomes, further investigation of these topics is warranted. In general, it seems that the strongest association with health outcomes is observed when time is reallocated from sedentary behaviour to MVPA. Most studies did not account for sleep time, which is a major limitation of the current evidence.

Conclusions

The current evidence indicates that time reallocation between sleep, sedentary behaviour, LPA, and MVPA may be associated with a number of health outcomes. Future studies should employ longitudinal designs, take into account all movement behaviours, and examine a wider range of health, psychological, social, economic, and environmental outcomes.

Electronic supplementary material

The online version of this article (10.1186/s12966-018-0691-3) contains supplementary material, which is available to authorized users.

Use of Mobile Devices to Measure Outcomes in Clinical Research, 2010-2016: A Systematic Literature Review

Background

The use of mobile devices in clinical research has advanced substantially in recent years due to the rapid pace of technology development. With an overall aim of informing the future use of mobile devices in interventional clinical research to measure primary outcomes, we conducted a systematic review of the use of and clinical outcomes measured by mobile devices (mobile outcomes) in observational and interventional clinical research.

Method

We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles on clinical research published between January 2010 and May 2016 in which mobile devices were used to measure study outcomes. We screened each publication for specific inclusion and exclusion criteria. We then identified and qualitatively summarized the use of mobile outcome assessments in clinical research, including the type and design of the study, therapeutic focus, type of mobile device(s) used, and specific mobile outcomes reported.

Results

The search retrieved 2,530 potential articles of interest. After screening, 88 publications remained. Twenty-five percent of the publications (n = 22) described mobile outcomes used in interventional research, and the rest (n = 66) described observational clinical research. Thirteen therapeutic areas were represented. Five categories of mobile devices were identified: (1) inertial sensors, (2) biosensors, (3) pressure sensors and walkways, (4) medication adherence monitors, and (5) location monitors; inertial sensors/accelerometers were most common (reported in 86% of the publications). Among the variety of mobile outcomes, various assessments of physical activity were most common (reported in 74% of the publications). Other mobile outcomes included assessments of sleep, mobility, and pill adherence, as well as biomarkers assessed using a mobile device, including cardiac measures, glucose, gastric reflux, respiratory measures, and intensity of head-related injury.

Conclusion

Mobile devices are being widely used in clinical research to assess outcomes, although their use in interventional research to assess therapeutic effectiveness is limited. For mobile devices to be used more frequently in pivotal interventional research – such as trials informing regulatory decision-making – more focus should be placed on: (1) consolidating the evidence supporting the clinical meaningfulness of specific mobile outcomes, and (2) standardizing the use of mobile devices in clinical research to measure specific mobile outcomes (e.g., data capture frequencies, placement of device). To that aim, this manuscript offers a broad overview of the various mobile outcome assessments currently used in observational and interventional research, and categorizes and consolidates this information for researchers interested in using mobile devices to assess outcomes in interventional research.

Non-locomotive physical activity intervention using a tri-axial accelerometer reduces sedentary time in type 2 diabetes

OBJECTIVES

The purpose of this study is to examine whether the use of a tri-axial accelerometer can reduce sedentary time and increase non-locomotive physical activity (N-LPA), and to investigate the effect of this intervention on parameters of glucose and fat metabolism in patients with type 2 diabetes.

METHODS

Thirty-eight patients with type 2 diabetes (Age: 61.8 ± 1.4 years, BMI: 24.8 ± 0.6, HbA_1c: 6.6 ± 0.1 %) participated in this 12-week randomized controlled study, and 31 patients were included in the final analyses. Patients were randomly assigned to one of three groups: control, N-LPA or locomotive physical activity (LPA). Patients in the N-LPA and LPA groups were asked to increase their N-LPA and LPA, respectively, using tri-axial accelerometer feedback. Glucose and fat metabolic parameters were evaluated before and after 12-week intervention.

RESULTS

Only the N-LPA intervention significantly reduced sedentary time (p < 0.05) and increased N-LPA (p < 0.05). However, these changes were insufficient to improve parameters associated with glucose and fat metabolism (p > 0.05), despite a significant positive correlation between the change in sedentary time and HbA_1c levels (p < 0.05).

CONCLUSION

Our results showed that the N-LPA intervention using a tri-axial accelerometer successfully reduced sedentary time in patients with type 2 diabetes, however that induced no significant improvement of glucose and fat metabolism. Further research is required to determine the degree of reduction in sedentary time and increase in N-LPA needed to improve glucose and fat metabolism.

Impact of accelerometer and pedometer use on physical activity and glycaemic control in people with Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Self-directed pedometer use increases physical activity levels in the general population; however, evidence of benefit for Type 2 diabetes is unclear and has not been systematically reviewed for accelerometers.

AIM

To examine the impact of using physical activity monitoring devices (pedometers and accelerometers) on free-living physical activity and HbA_1c levels in people with Type 2 diabetes.

METHODS

We conducted a systematic literature review. Bibliographic databases included Medline, Embase, Web of Science, CINAHL, SportDiscus and the Cochrane Central Register of Controlled Trials. We included controlled trials evaluating interventions based on the use of pedometers or accelerometers to promote physical activity in people with Type 2 diabetes. Primary outcomes were physical activity (min/week or steps) and HbA_1c [mmol/mol (%)]. Secondary outcomes were weight, blood pressure and lipid profile.

RESULTS

Twelve trials (1458 participants) were identified, of which nine studied pedometers and three accelerometers. Random-effects meta-analysis showed an overall increase in physical activity (standardized mean difference 0.57, 95% CI 0.24, 0.91) in the intervention groups. Accelerometers and pedometers produced a similar effect size. No significant differences were observed in HbA_1c , BMI, blood pressure or lipid profile.

CONCLUSIONS

People with Type 2 diabetes, provided with an accelerometer or pedometer, substantially increased their free-living physical activity. There is no evidence that monitor use alone improves HbA_1c or other clinical outcomes. Further trials are needed to compare the relative effects of activity monitors within differing complex interventions.

Plasma levels of MASP-1, MASP-3 and MAp44 in patients with type 2 diabetes: influence of glycaemic control, body composition and polymorphisms in the MASP1 gene

Mounting evidence indicates that adverse activation of the complement system plays a role in the development of diabetic vascular complications. Plasma levels of the complement proteins mannan-binding lectin (MBL) and its associated serine proteases (MASP-1 and MASP-2) are elevated in diabetes. We hypothesized that single nucleotide polymorphisms (SNPs) in the MASP1 gene may contribute to altered plasma levels of the belonging gene products; MASP-1, MASP-3 and mannan-binding lectin-associated protein of 44 kDa (MAp44) in patients with type 2 diabetes. To investigate this, we compared plasma levels of MASP-1, MASP-3 and MAp44 in 100 patients with type 2 diabetes and 100 sex- and age-matched controls. Ten carefully selected SNPs were analysed using TaqMan^® genotyping assay. Additionally, we included a streptozotocin-induced diabetes mouse model to directly examine the effect of inducing diabetes on MASP-1 levels. MASP-1 levels were significantly higher among patients with type 2 diabetes compared with healthy controls (P = 0·017). Five SNPs (rs874603, rs72549254, rs3774275, rs67143992, rs850312) in the MASP1 gene were associated with plasma levels of MASP-1, MASP-3 and MAp44. In the diabetes mouse model, diabetic mice had significantly higher MASP-1 levels than control mice (P = 0·003). In conclusion, MASP-1 levels were higher among patients with type 2 diabetes and diabetic mice. The mechanism behind this increase remains elusive.

Mapping the association between back pain and type 2 diabetes: A cross-sectional and longitudinal study of adult Spanish twins

BACKGROUND

Back pain and type 2 diabetes often co-occur, resulting in greater impact on people's health and complexity in their care. Plausible causal mechanisms for this association have been proposed, yet the nature of the link remains unclear. We therefore explored the direction of the association between type 2 diabetes and chronic back pain in twins, controlling for genetics and early environmental confounding.

METHODS

2,096 and 1,098 twins were included in the cross-sectional and longitudinal analyses, respectively. Any or severe (≥ 9) low back pain (LBP), neck pain (NP), and spinal pain (concurrent LBP and NP) and type 2 diabetes were investigated. Sequential analyses were performed using logistic regression. Firstly, twins were analysed unpaired (adjusted age and gender): total sample analyses. Then, to control for genetic and shared environmental factors, a co-twin case-control analysis was performed including monozygotic and dizygotic twin pairs discordant for back pain (cross-sectional only).

RESULTS

In the cross-sectional total sample analyses, type 2 diabetes was associated with chronic spinal pain (OR 1.61; 95%CI 1.12 to 2.31), severe chronic spinal pain (OR 3.33; 95%CI 1.47 to 7.53), chronic NP (OR 1.37; 95%CI 1.01 to 1.85), severe chronic NP (OR 2.28; 95%CI 1.24 to 4.21), and severe chronic LBP (OR 1.63; 95%CI 1.00 to 2.64). After further adjustment for genetic and shared environmental factors, none of the associations remained significant. The longitudinal analyses indicated that the presence of type 2 diabetes did not increase the risk of future back pain, or vice-versa, after two to four years.

CONCLUSIONS

Chronic back pain (spinal pain, NP, or LBP) was associated with the prevalence of type 2 diabetes. Associations are stronger for severe cases of pain. Future research should investigate the temporal relationships between these conditions with longer follow up in twins.

Prediction of excessive weight gain in insulin treated patients with type 2 diabetes

BACKGROUND

Weight gain is an ongoing challenge when initiating insulin therapy in patients with type 2 diabetes mellitus (T2DM). However, if prediction of insulin-associated weight gain was possible on an individual level, targeted initiatives could be implemented to reduce weight gain. The aim of the present study was to identify predictors of weight gain in insulin-treated patients with T2DM.

METHODS

In all, 412 individuals with T2DM were, in addition to metformin or placebo, randomized into 18-month treatment groups with three different insulin analog treatment regimens (biphasic, aspart, detemir). Participants with excessive weight gain were defined as the group with weight gain in the 4th quartile (>6.2 kg).We developed a pattern classification method to predict individuals prone to excessive weight gain.

RESULTS

Over the 18-month treatment period, median weight gain among all 412 patients was 2.4 kg (95% prediction interval [PI] -5.6, 12.4 kg), whereas median weight gain for those in the upper 4th quartile (n = 103) was 8.9 kg (95% PI 6.3, 15.2 kg). No clinical baseline data were strong predictors of excessive weight gain. However, the weight gain during the first 3 months of the trial and the subsequent dose of insulin yielded a useful predictor for weight gain at the 18-month follow-up. Combining these two predictors into a prediction model with other clinical available information produced a receiver operating characteristic area under the curve of 0.80.

CONCLUSIONS

We have developed a prediction model that could help identify a substantial proportion of individuals with T2DM prone to large weight gain during insulin therapy.

Adding exercise or subtracting sitting time for glycaemic control: where do we stand?

While regular structured exercise is a well-established (though arguably under-utilised) cornerstone in the prevention and management of type 2 diabetes, population adherence to recommended exercise guidelines remains stubbornly low. Indeed, most adults are exposed to environmental settings (at work, in automobile travel and in the domestic environment) that may not only limit their physical activity, but also promote sitting for prolonged periods of time. However, recent experimental evidence indicates that reducing and breaking up sitting time may also be a useful strategy to improve glycaemic control. In this issue of Diabetologia, Duvivier and colleagues report findings which suggest that reducing sitting time with standing and light-intensity activity could be a potential alternative to structured exercise for improving glycaemic control in type 2 diabetes patients. We review and discuss the findings of this study, its potential clinical implications, and a number of knowledge gaps and opportunities that could be considered in the interest of future research. The findings from Duvivier and colleagues should encourage healthcare practitioners, researchers and type 2 diabetes patients to consider the whole spectrum of physical activity, from sedentary behaviour through to structured exercise.

Sitting Less and Moving More: Improved Glycaemic Control for Type 2 Diabetes Prevention and Management

Epidemiological evidence indicates that excessive time spent in sedentary behaviours (too much sitting) is associated with an increased risk of type 2 diabetes (T2D). Here, we highlight findings of experimental studies corroborating and extending the epidemiological evidence and showing the potential benefits for T2D of reducing and breaking up sitting time across the whole day. We also discuss future research opportunities and consider emerging implications for T2D prevention and management. This new evidence is stimulating an expansion of diabetes-related physical activity guidelines-suggesting that in addition to moderate-vigorous physical activity, reducing and regularly interrupting prolonged sitting time is likely to have important and varied benefits across the spectrum of diabetes risk.

Low Physical Activity Is Associated With Increased Arterial Stiffness in Patients Recently Diagnosed With Type 2 Diabetes

AIMS

Several studies have indicated that low physical activity is associated with increased risk of cardiovascular disease (CVD) and all-cause mortality among patients with diabetes. The association between physical activity and subclinical cardiovascular changes preceding clinical events remains to be elucidated. We investigated the relationship between physical activity and arterial stiffness, an independent predictor of CVD, in patients with type 2 diabetes and controls.

METHODS

We included 100 patients with type 2 diabetes and 100 sex- and age-matched controls in a cross-sectional study. Arterial stiffness (carotid-femoral pulse wave velocity, cfPWV) was measured using the SphygmoCor device (AtCor Medical, Sydney, Australia). Physical activity was assessed by an accelerometer (counts per minute (cpm), Actiheart (CamNtech, Cambridge, UK)) worn by the participants for up to 6 days. High vs. low levels of physical activity was defined according to the median level of activity (cpm = 31).

RESULTS

Sixty-five patients and 65 controls were included in the final analysis (median age 59 years, 55% men, median diabetes duration 1.9 years). Participants with low physical activity had higher cfPWV compared to participants with high physical activity: (i) Patients and controls combined: 9.3±1.7 m/s vs. 7.8±1.5 m/s, P < 0.001; (ii) Patients with diabetes: 9.5±1.8 m/s vs. 8.3±1.6 m/s, P = 0.02 and C) Controls: 9.0±1.4 m/s vs. 7.7±1.4 m/s, P < 0.01). The difference remained significant after adjustment for other determinants of cfPWV including whole body fat percentage (P < 0.01). No significant interaction between diabetes and the effect of low activity was seen.

CONCLUSIONS

Low physical activity is associated with increased arterial stiffness in patients recently diagnosed with type 2 diabetes and in healthy controls.

CLINICAL TRIALS REGISTRATION

Trial Number NCT00674271.

Benefits for Type 2 Diabetes of Interrupting Prolonged Sitting With Brief Bouts of Light Walking or Simple Resistance Activities

OBJECTIVE

To determine whether interrupting prolonged sitting with brief bouts of light-intensity walking (LW) or simple resistance activities (SRA) improves postprandial cardiometabolic risk markers in adults with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

In a randomized crossover trial, 24 inactive overweight/obese adults with T2D (14 men 62 ± 6 years old) underwent the following 8-h conditions on three separate days (with 6-14 days washout): uninterrupted sitting (control) (SIT), sitting plus 3-min bouts of LW (3.2 km · h(-1)) every 30 min, and sitting plus 3-min bouts of SRA (half-squats, calf raises, gluteal contractions, and knee raises) every 30 min. Standardized meals were consumed during each condition. Incremental areas under the curve (iAUCs) for glucose, insulin, C-peptide, and triglycerides were compared between conditions.

RESULTS

Compared with SIT, both activity-break conditions significantly attenuated iAUCs for glucose (SIT mean 24.2 mmol · h · L(-1) [95% CI 20.4-28.0] vs. LW 14.8 [11.0-18.6] and SRA 14.7 [10.9-18.5]), insulin (SIT 3,293 pmol · h · L(-1) [2,887-3,700] vs. LW 2,104 [1,696-2,511] and SRA 2,066 [1,660-2,473]), and C-peptide (SIT 15,641 pmol · h · L(-1) [14,353-16,929] vs. LW 11,504 [10,209-12,799] and SRA 11,012 [9,723-12,301]) (all P < 0.001). The iAUC for triglycerides was significantly attenuated for SRA (P < 0.001) but not for LW (SIT 4.8 mmol · h · L(-1) [3.6-6.0] vs. LW 4.0 [2.8-5.1] and SRA 2.9 [1.7-4.1]).

CONCLUSIONS

Interrupting prolonged sitting with brief bouts of LW or SRA attenuates acute postprandial glucose, insulin, C-peptide, and triglyceride responses in adults with T2D. With poor adherence to structured exercise, this approach is potentially beneficial and practical.

Musculoskeletal pain in people with and without type 2 diabetes in Taiwan: a population-based, retrospective cohort study

Background

Musculoskeletal pain in people with type 2 diabetes is a common issue even to this day. The study aimed to explore the 10-year cumulative incidence of musculoskeletal pain, the mean number of doctor visits for musculoskeletal pain, and the mean number of doctor visits for musculoskeletal pain by location in people with type 2 diabetes, compared with respective values for people without diabetes.

Methods

The study utilized a population-based retrospective cohort study design. The subjects were randomly obtained from the Taiwan National Health Insurance Research Database. The diabetic group included 6586 people with type 2 diabetes aged 18–50 years, while the non-diabetic group consisted of 32,930 age- and sex-matched people. Based on the medical records of individuals with musculoskeletal pain in the two groups from 2001 to 2010, the 10-year cumulative incidence of musculoskeletal pain, the mean number of doctor visits for musculoskeletal pain, and the mean number of doctor visits for musculoskeletal pain by location were calculated and compared, with the aim of identifying differences between the two groups.

Results

Showed that people in the diabetic group had a higher 10-year cumulative incidence of and a higher mean number of doctor visits for musculoskeletal pain than the non-diabetic group (p < 0.05). The relative risk (RR) of the 10-year cumulative incidence of musculoskeletal pain in the two groups was the highest (RR = 1.39) for people between 30 and 39 years of age. The mean number of doctor visits for musculoskeletal pain by location was significantly different between the two groups. However, the mean number of doctor visits for limb pain registered the largest difference between the two groups.

Conclusion

People with type 2 diabetes aged 18–50 years had a higher 10-year cumulative incidence of and a higher mean number of doctor visits for musculoskeletal pain than the non-diabetic group. Musculoskeletal pain might directly or indirectly interfere with or decrease the physical activity levels of people with diabetes. Therefore, it is important to detect and treat musculoskeletal pain early in order to promote physical activity and optimize blood sugar control.

Association Between Daily Time Spent in Sedentary Behavior and Duration of Hyperglycemia in Type 2 Diabetes

Exercise and sedentary behavior have different physiologic effects, which have yet to be fully explained. Time spent in sedentary behavior has been associated with glucose intolerance in adults at risk for type 2 diabetes, but these data have come largely from cross-sectional studies that have not explored this relationship in adults with diabetes. The specific aim of this study was to examine the relationship between time spent in sedentary behavior and glucose levels in adults diagnosed with type 2 diabetes over 3-5 days.

METHODS

Using continuous and concurrent data gathered from wrist accelerometry and a Continuous Glucose-Monitoring Sensor (CGMS), we conducted a longitudinal, descriptive study involving 86 patients with type 2 diabetes.

RESULTS

More time spent in sedentary behavior was predictive of significant increases in time spent in hyperglycemia (B = 0.12, p < .05).

CONCLUSIONS

These findings highlight the relationship between time spent sedentary and time spent in hyperglycemia, as identified through our use of objective, continuous data collection methods for both sedentary behavior and glucose levels across multiple days (Actiwatch, CGMS). For patients with type 2 diabetes, these findings emphasize the need for the development of individualized interventions aimed at decreasing the amount of time spent in hyperglycemia by reducing sedentary time.

Glycemic variability is associated with reduced cardiac autonomic modulation in women with type 2 diabetes

OBJECTIVE

To investigate the sex differences in cardiac autonomic modulation in patients with newly diagnosed type 2 diabetes and to determine whether cardiac autonomic modulation is associated with glycemic variability.

RESEARCH DESIGN AND METHODS

We investigated a cohort consisting of 48 men and 39 women with non-insulin-treated type 2 diabetes and a known duration of diabetes <5 years. All patients were equipped with a continuous glucose monitoring sensor for 3 days, and the mean amplitude of glycemic excursions (MAGE) was calculated to obtain individual glycemic variability. Cardiac autonomic modulation was quantified by analysis of heart rate variability (HRV) in time and frequency domains and during cardiovascular reflex tests (response to standing [RS], deep breathing [expiration-inspiration], and Valsalva maneuver).

RESULTS

Sex differences in age- and heart rate-adjusted HRV measures were observed in both active and passive tests. Low frequency (LF; P = 0.036), LF/high frequency (HF; P < 0.001), and RS (P = 0.006) were higher in men, whereas expiration-inspiration (P < 0.001), but not HF, was higher in women. In women, reduced cardiac autonomic modulation as assessed by the standard deviation of normal-to-normal intervals (P = 0.001), the root mean square of successive differences (P = 0.018), LF (P < 0.001), HF (P = 0.005), total power (P = 0.008), RS ratio (P = 0.027), and expiration-to-inspiration ratio (P = 0.006) was significantly associated with increased glycemic variability as assessed by MAGE. This was not the case in men. The association in women persisted in a multivariate regression analysis controlling for weight, mean heart rate, blood pressure (systolic), and triglycerides.

CONCLUSIONS

In patients with newly diagnosed and well-controlled type 2 diabetes, increased glycemic variability was associated with reduced cardiac autonomic modulation in women but not in men.

Accelerometer-derived sedentary and physical activity time in overweight/obese adults with type 2 diabetes: cross-sectional associations with cardiometabolic biomarkers

Objective

To examine the associations of sedentary time and physical activity with biomarkers of cardiometabolic health, including the potential collective impact of shifting mean time use from less- to more-active behaviours (cross-sectionally, using isotemporal substitution), in adults with type 2 diabetes.

Methods

Participants with overweight/obese body mass index (BMI; ≥25 kg/m²) (n = 279; 158 men, mean [SD] age = 58.2 [8.6] years) wore Actigraph GT1M accelerometers (waking hours; seven days) to assess moderate- to vigorous-intensity physical activity (MVPA), light-intensity activity, and sedentary time (segregated into non-prolonged [accumulated in bouts <30min] and prolonged [accumulated in bouts ≥30 min]). Cross-sectional associations with waist circumference, BMI, fasting blood (HbA_1c, glucose, triacylglycerols, high-density lipoprotein cholesterol), and blood pressure of these activity variables (30 min/day increments) were examined adjusted for confounders and wear then, if significant, examined using isotemporal substitution modelling.

Results

Waist circumference and BMI were significantly (p<0.05) associated with more prolonged sedentary time and less light-intensity activity. Light intensity activity was also significantly associated with lower fasting plasma glucose (relative rate: 0.98, 95% CI: 0.97, 1.00; p<0.05). No biomarker was significantly associated with non-prolonged sedentary time or MVPA. Lower mean prolonged sedentary time (−30 min/day) with higher mean light intensity time (+30 min/day) was significantly associated with lower waist circumference (β = −0.77, 95% CI: −1.33, −0.22 cm). Lower mean prolonged sedentary time (−30 min/day) with either 30 min/day higher mean non-prolonged sedentary time (β = −0.35, 95%CI: −0.70, −0.01 kg/m²) or light-intensity time (β = −0.36, −0.61, −0.11 kg/m²) was associated with significantly lower average BMI.

Conclusions

Significantly improved mean levels of waist circumference and BMI were observed when shifting time from prolonged sedentary to non-prolonged sedentary or light-intensity activity (cross-sectionally). Lifestyle interventions in overweight/obese adults with type 2 diabetes might consider targeting shifts in these non-MVPA activities to more rigorously evaluate their potential cardiometabolic benefit in this population.

Lifestyle factors associated with type 2 diabetes and use of different glucose-lowering drugs: cross-sectional study

Aims

To examine the lifestyle profile among persons with and without Type 2 diabetes mellitus (DM) and among users of different glucose-lowering drugs.

Methods

We used questionnaire data from a Danish health survey and identified presence of Type 2 DM and use of medications through medical databases. We calculated age- and gender-standardized prevalence ratios (PRs) of lifestyle factors according to Type 2 DM and different glucose-lowering drugs.

Results

Of 21,637 survey participants aged 25–79 years, 680 (3%) had Type 2 DM (median age 63 years) with a median diabetes duration of 5 years. Participants with Type 2 DM had a substantially higher prevalence of obesity (36% vs. 13%, PR: 3.1, 95% confidence interval (CI): 2.8–3.6), yet more reported to eat a very healthy diet (25% vs. 21%, PR: 1.2, 95% CI: 1.0–1.4) and to exercise regularly (67% vs. 53%, PR: 1.3, 95% CI: 1.2–1.4). Also, fewer were current smokers or had high alcohol intake. When compared with metformin users, obesity was substantially less prevalent in users of sulfonylurea (PR: 0.5, 95% CI: 0.4–0-8), and insulin and analogues (PR: 0.4, 95% CI: 0.3–0.7). Tobacco smoking was more prevalent in sulfonylurea users (PR: 1.4, 95% CI: 0.9–2.1) compared with metformin users. We found no material differences in physical exercise, diet or alcohol intake according to type of glucose-lowering drug.

Conclusions

Type 2 DM patients are substantially more obese than other individuals, but otherwise report to have a healthier lifestyle. Metformin use is strongly associated with obesity, whereas sulfonylurea use tends to be associated with tobacco smoking.

A novel model enhances HbA1c-based diabetes screening using simple anthropometric, anamnestic, and demographic information

BACKGROUND

The sensitivity of HbA1c is not optimal for the screening of patients with latent diabetes. We hypothesize that simple healthcare information could improve accuracy.

METHODS

We retrospectively analyzed data, including HbA1c, from multiple years from the National Health and Nutrition Examination Survey (NHANES) database (2005-2010). The data were used to create a logistic regression classification model for screening purposes.

RESULTS

The study evaluated data for 5381 participants, including 404 with undiagnosed diabetes. The HbA1c screening data were supplemented with information about age, waist circumference, and physical activity in the HbA1c+ model. Alone, HbA1c alone had a receiver operating characteristics (ROC) curve for the area under the curve (AUC) of 0.808 (95% confidence interval [CI] 0.792-0.834). The HbA1c+ model had an ROC AUC of 0.851 (95% CI 0.843-0.872). There was a significant difference in the AUC between our model and using HbA1c without supplementary information (P < 0.05).

CONCLUSIONS

We have developed a novel screening model that could help improve screening for type 2 diabetes with HbA1c. It seems beneficial to systematically add additional patient healthcare information in the process of screening with HbA1c.

Improved diabetes screening using an extended predictive feature search

BACKGROUND

Screening entire populations for diabetes is not cost-effective. Hence, an efficient screening process must select those people who are at high risk for diabetes. In this study, we investigated whether screening procedures could be improved using an extended predictive feature search.

MATERIALS AND METHODS

In order to develop our model and identify persons with diabetes (prevalence) we used data from years of the National Health and Nutrition Examination Survey (2005-2010), which has not been explored for this purpose before. We calculated all combinations of predictors in order to identify the optimal subset, and we used a linear logistic classification model to predict diabetes. V-fold cross-validation was used for the process of including variables and for validating the final models. This new model was compared with two established models.

RESULTS

In total, 5,398 participants were included in this study. Among these, 478 participants had unidentified diabetes. The established models had a receiver operating characteristics curve for the area under the curve (AUC) of 0.74 and 0.71 compared with an AUC of 0.78 for the new model, showing a significant difference (P<0.05). A proposed cutoff point for the established models yielded respective sensitivities/specificities of 63%/72% and 40%/72% compared with the new model, which had a sensitivity/specificity of 70%/72%.

CONCLUSIONS

Our data indicate that simple healthcare and economic information such as ratio of family income to poverty can add value in deciding who is at risk of unknown diabetes by using extended investigations of predictor combinations.

Use of technology when assessing adherence to diabetes self-management behaviors

During the last several decades, a proliferation of sophisticated technology has taken place to facilitate diabetes self-management and improve health outcomes. Blood glucose monitors, insulin pumps, and continuous glucose monitors have significant data storage capacity, which can be used to summarize diabetes health management and outcomes. In the absence of technology errors or failures, and in the context of the multiple psychosocial factors associated with nonadherence, these data have the potential to elucidate diabetes care because they reflect actual patient behaviors. This review provides a summary of the diabetes adherence literature in the context of current American Diabetes Association Clinical Practice Recommendations with a focus on studies that have used objective methods (ie, data derived from technology) to assess diabetes care provider and patient adherence in the areas of glucose monitoring; insulin administration and antihyperglycemic medications; medical nutrition therapy; and physical activity.

Heart rate variability in neurorehabilitation patients with severe acquired brain injury

INTRODUCTION

Acquired brain injury (ABI) cause neural deficits. In addition to motor and cognitive deficits, the autonomic nervous system may be affected. This has been shown for neurorehabilitation patients with traumatic brain injury (TBI) by means of reduced heart rate variability (HRV). It was hypothesized that patient groups with other ABI aetiology (mainly stroke, subarachnoid haemorrhage and anoxia) would also present reduced HRV.

METHODS

Patients consecutively admitted and severely ABI injured were considered for HRV measurements. HRV was extracted as a mean of four 5-minute ECG recordings at 6 pm, 10 pm, 2 am and 6 am the following day (scheduled resting periods). One 5-minute HRV recording from a sex- and age-matched group of healthy volunteers constituted control data. Standard deviation of normal-to-normal intervals (SDNN) and low frequency (LF) were primary HRV variables.

RESULTS

Of 71 admitted patients, HRV was extracted from 49 patients. Patient SDNN and LF were reduced compared to controls (SDNN: 13 ms (CI = [10.8; 15.3]) vs 40.3 ms (CI = [36.6; 44.2]), p < 0.0001; LF: 29.4 ms² (CI = [19.8; 43.7]) vs 518 ms² (CI = [419; 639]), p < 0.0001). HRV appeared identical across ABI aetiology.

CONCLUSION

It was found that HRV was considerably reduced in an heterogenic ABI patient group admitted for neurorehabilitation.