scholarly journals Which Green Space Metric Best Predicts a Lowered Odds of Type 2 Diabetes?

2021 ◽  
Vol 18 (8) ◽  
pp. 4088
Author(s):  
Soumya Mazumdar ◽  
Shanley Chong ◽  
Thomas Astell-Burt ◽  
Xiaoqi Feng ◽  
Geoffrey Morgan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Road Network ◽  
Green Space ◽  
Estimating Equation ◽  
The Novel ◽  
Individual Level ◽  
Circular Buffer ◽  
Area Metric ◽  
The Individual

The choice of a green space metric may affect what relationship is found with health outcomes. In this research, we investigated the relationship between percent green space area, a novel metric developed by us (based on the average contiguous green space area a spatial buffer has contact with), in three different types of buffers and type 2 diabetes (T2D). We obtained information about diagnosed T2D and relevant covariates at the individual level from the large and representative 45 and Up Study. Average contiguous green space and the percentage of green space within 500 m, 1 km, and 2 km of circular buffer, line-based road network (LBRN) buffers, and polygon-based road network (PBRN) buffers around participants’ residences were used as proxies for geographic access to green space. Generalized estimating equation regression models were used to determine associations between access to green space and T2D status of individuals. It was found that 30%–40% green space within 500 m LBRN or PBRN buffers, and 2 km PBRN buffers, but not within circular buffers, significantly reduced the risk of T2D. The novel average green space area metric did not appear to be particularly effective at measuring reductions in T2D. This study complements an existing research body on optimal buffers for green space measurement.

Fluctuations in Self-Reported Symptoms Predict Objective Physical Activity in Adults With Type 2 Diabetes

2021 ◽  
pp. 263501062110158
Author(s):  
Bingqian Zhu ◽  
Pei Chen ◽  
Min Jung Kim ◽  
Xiangfang Chen ◽  
Laurie Quinn ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Energy Expenditure ◽  
Moderate Intensity ◽  
Individual Level ◽  
Moderate Intensity Physical Activity ◽  
Intensity Physical Activity ◽  
The Individual ◽  
Restorative Sleep

Purpose The purpose of this study was to examine the association between self-reported symptoms including fatigue and sleep disturbance with moderate-intensity physical activity among adults with type 2 diabetes. Methods This report was a secondary analysis of a cross-sectional study. Data from 53 participants with at least 6 days of repeated measures were used. Daytime physical activity and energy expenditure were assessed using a wrist-worn accelerometer at the free-living setting. Fatigue upon awakening was measured using a 0 to 10 scale. Sleep (eg, restorative sleep, sleep duration, and sleep efficiency) was measured using the Consensus Sleep Diary for Morning. Data were analyzed using linear mixed models by including within- and between-person effects. Results Participants were predominantly females (54.7%) with a mean age of 60.3 years. Controlling for the covariates, at the individual level (within-person), fluctuations in restorative sleep and fatigue upon awakening predicted moderate-intensity PA. Similarly, at the individual level, fluctuations in restorative sleep and fatigue upon awakening predicted average hourly energy expenditure. However, at the group level (between-person), no significant associations were found between fatigue and restorative sleep with moderate-intensity physical activity. Conclusions The study findings suggest that within-person fluctuations in fatigue and restorative sleep upon awakening predict daytime moderate-intensity physical activity. At the individual level, reducing fluctuations in fatigue and restorative sleep might encourage participation in physical activity. More research is warranted to uncover the underlying causes of fluctuations in fatigue and restorative sleep. Meanwhile, diabetes care and education specialists should pay attention to the within-person fluctuations of fatigue and sleep.

scholarly journals Lifetime risk and years lost to type 1 and type 2 diabetes in Denmark, 1996–2016

2021 ◽  
Vol 9 (1) ◽  
pp. e001065
Author(s):  
Bendix Carstensen ◽  
Pernille Falberg Rønn ◽  
Marit Eika Jørgensen
Keyword(s):  
Type 2 Diabetes ◽  
Population Level ◽  
Lifetime Risk ◽  
Individual Level ◽  
Number Of Patients ◽  
Incidence And Mortality ◽  
The Difference ◽  
The Individual

IntroductionLifetime risk and lifetime lost to diabetes are measures of current diabetes burden in a population. We aimed at quantifying these measures in the Danish population.Research design and methodsWe modeled incidence and mortality of type 1 diabetes (T1D) and type 2 diabetes (T2D) and non-diabetes mortality based on complete follow-up of the entire population of Denmark in 1996–2016. A multistate model with these transition rates was used to assess the lifetime risk of diabetes, as well as the difference in expected lifetime between persons with type 1 and T2D and persons without.ResultsIn 2016, the lifetime risk of T1D was 1.1% and that for T2D 24%, the latter a 50% increase from 1996. For 50-year-old persons, the lifetime lost was 6.6 years for T1D and 4.8 years for T2D. These figures have been declining over the study period.At 2016, the total foreseeable lives lost in Denmark among patients with T1D were 182 000 years, and those among patients with T2D were 766 000 years, corresponding to 6.6 and 3.0 years per person, respectively.ConclusionAt the individual level, improvements in the disease burden for both T1D and T2D have occurred. At the population level, the increasing number of patients with T2D has contributed to a large increase in the total loss of lifetime.

scholarly journals The Effect of Surrounding Greenness on Type 2 Diabetes Mellitus: A Nationwide Population-Based Cohort in Taiwan

2020 ◽  
Vol 18 (1) ◽  
pp. 267
Author(s):  
Hui-Ju Tsai ◽  
Chia-Ying Li ◽  
Wen-Chi Pan ◽  
Tsung-Chieh Yao ◽  
Huey-Jen Su ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Population Based ◽  
Research Database ◽  
Individual Level ◽  
The Relationship

This study determines whether surrounding greenness is associated with the incidence of type 2 diabetes Mellitus (T2DM) in Taiwan. A retrospective cohort study determines the relationship between surrounding greenness and the incidence of T2DM during the study period of 2001–2012 using data from the National Health Insurance Research Database. The satellite-derived normalized difference vegetation index (NDVI) from the global MODIS database in the NASA Earth Observing System is used to assess greenness. Cox proportional hazard models are used to determine the relationship between exposure to surrounding greenness and the incidence of T2DM, with adjustment for potential confounders. A total of 429,504 subjects, including 40,479 subjects who developed T2DM, were identified during the study period. There is an inverse relationship between exposure to surrounding greenness and the incidence of T2DM after adjustment for individual-level covariates, comorbidities, and the region-level covariates (adjusted HR = 0.81, 95% CI: 0.79–0.82). For the general population of Taiwan, greater exposure to surrounding greenness is associated with a lower incidence of T2DM.

scholarly journals Low health literacy is associated with higher risk of type 2 diabetes: a cross-sectional study in Germany

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Daniel Tajdar ◽  
Dagmar Lühmann ◽  
Regina Fertmann ◽  
Tim Steinberg ◽  
Hendrik van den Bussche ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Health Literacy ◽  
Statistical Models ◽  
Cross Sectional Study ◽  
Diabetes Risk ◽  
Sectional Study ◽  
Cross Sectional ◽  
Low Health Literacy ◽  
The Individual

Abstract Background Low health literacy is believed to be associated with behaviours that increase the risk of type 2 diabetes. But there is limited knowledge on the relation between health literacy (HL) and diabetes risk, and whether improving HL could be a potential prevention strategy. Therefore, the main purpose of this study was to examine the link between HL and diabetes risk among non-diabetic adults. Methods We used data from the Hamburg Diabetes Prevention Survey, a population-based cross-sectional study in Germany. One thousand, two hundred and fifty-five non-diabetic subjects aged 18–60 years were eligible. The German Diabetes Risk Score (GDRS, ranging 0 to 123 points) was used to determine the individual risk of type 2 diabetes. The short version of the European Health Literacy Questionnaire (HLS-EU-Q16, ranging 0 to 16 points) was applied to assess the individual self-reported HL. Subjects were asked to self-estimate their diabetes risk, which was then compared with the calculated GDRS. Descriptive statistics were calculated to investigate group differences in the GDRS and self-estimated diabetes risk. Linear as well as logistic regression models were performed to analyse potential influencing variables of the GDRS as well as incorrect self-estimated diabetes risk. In three nested statistical models for each outcome, these analyses were adjusted for age, gender, educational level and the presence of chronic conditions. Results According to the criteria of the GDRS, 996 (79.4%) subjects showed “low risk”, 176 (14.0%) “still low risk”, 53 (4.2%) “elevated risk”, and 30 (2.4%) “high to very high risk” to develop type 2 diabetes within the next 5 years. In the statistical models including all control variables, subjects with “inadequate HL” scored 2.38 points higher on the GDRS (95% CI 0.378 to 4.336; P = 0.020) and had a 2.04 greater chance to estimate their diabetes risk incorrectly (OR 2.04; 95% CI 1.33 to 3.14; P = 0.001) compared to those with “sufficient HL”. Conclusion The risk of type 2 diabetes is increased in people with inadequate self-reported HL. People with high diabetes risk and inadequate HL might be provided with educational programs to improve diabetes knowledge and reduce behavioural risk factors.

scholarly journals Type 2 diabetes therapeutic strategies: why don't we see the «ELEPHANT» in the room?

2016 ◽  
Vol 19 (4) ◽  
pp. 341-349 ◽  
Author(s):  
Shmuel Levit ◽  
Shmuel Giveon ◽  
Yury I. Philippov ◽  
Ivan Panchev Domuschiev ◽  
Amir Zivony
Keyword(s):  
Type 2 Diabetes ◽  
Traditional Approach ◽  
Treatment Method ◽  
Past Century ◽  
The Novel ◽  
Energy Effect ◽  
Practical Utilization ◽  
Recommended Treatment ◽  
Reversible Condition

During the past two decades, the unequivocally recommended treatment method of Type 2 diabetes mellitus was insulin administration and intensification in the earliest possible stage of the diagnosis. This approach is not only unfounded but was never scientifically proven. Yet, it has been zealously advocated to medical professionals. In fact, a sound body of evidence disproves this long-standing treatment approach. This method is a cornerstone of, what we now know to be two great illusions of past century, namely, glucocentrism and intensification. Numerous recently published studies provide alarming data regarding serious side effects of blind intensification and insulin overdosing in T2DM. They raise major concerns and call for revision of the traditional approach. Since insulin is an integral and deeply rooted part of the intensification agenda of treating T2DM, it has now suffered a serious drawback. Alternatively, in this review authors present the novel Gravicentric (Energy) concept of T2DM acceptance and therapy. They offer a new classification of anti-diabetes drugs based on their energy effect and present their Gravicentric Algorithm for wide practical utilization. For that reason, the "ELEPHANT" abbreviation was found as a helpful reminder. Viewing T2DM as disease of energy balance together with anti – energy drugs implementation provide medical doctors an unique opportunity to transform T2DM from "slowly – progressive" disease to rapidly reversible condition, which it actually is.

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