scholarly journals Sleeping Duration, Napping and Snoring in Association with Diabetes Control among Patients with Diabetes in Qatar

2021 ◽  
Vol 18 (8) ◽  
pp. 4017
Author(s):  
Hiba Bawadi ◽  
Asma Al Sada ◽  
Noof Al Mansoori ◽  
Sharifa Al Mannai ◽  
Aya Hamdan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Glycemic Control ◽  
Sleep Duration ◽  
Vegetable Intake ◽  
Activity Level ◽  
Poor Glycemic Control ◽  
Age And Gender ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
And Gender

Background: Poor glycemic control is associated with chronic life-threatening complications. Several studies have revealed that sleep status is associated with glycemic control. Aim: to examine the association between sleep duration, quality and glycemic control among adults with diabetes. Methods: Data on 2500 participants aged 18–60 years were collected from the Qatar Biobank (QBB). Sleep duration and quality were assessed by a self-completed health and lifestyle questionnaire, and glycemic control was assessed using HbA1c. Logistic regression was used to assess the association between sleep duration, napping, snoring and poor glycemic control. Results: After adjusting for age and gender, sleep duration was not associated with poor glycemic control. Lack of association persisted after controlling for smoking, physical activity, education, BMI, fruit and vegetable intake, insulin and medication use. However, sleeping for long hours at night (≥8 h) had a trend in increasing the risk of poor glycemic control (OR = 1.28; 95% CI: 0.94–1.74). Napping was positively associated with poor glycemic control. After adjusting for age and gender, patients who reported “sometimes, frequently, or always” napping had more than 30% increased risk of poor control as compared to patients who reported “never/rarely” napping. Snoring was not associated with poor glycemic control among the study sample when adjusted for age and gender (p = 0.61). Other factors were found to be associated with a better glycemic control such as female, high educational and high physical activity level. Conclusions: our results suggest that napping may be an independent risk factor for a poor glycemic control in diabetes; further investigations are required.

scholarly journals Sleeping Duration, Napping and Snoring in Association with Diabetes Control among Patients with Diabetes in Qatar

2021 ◽  
Author(s):  
Noof Al Mansoori ◽  
Hiba Bawadi ◽  
Zumin Shi ◽  
Abdelhamid Kerkadi ◽  
Aya Hamdan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Glycemic Control ◽  
Sleep Duration ◽  
Vegetable Intake ◽  
Causal Link ◽  
Activity Level ◽  
Poor Glycemic Control ◽  
Age And Gender ◽  
Increased Risk ◽  
And Gender

Background: Poor glycemic control is associated with chronic life-threatening complications. Several studies have revealed that sleep status is associated with glycemic control. Aim: to examine the association between sleep duration, quality and glycemic control among adults with diabetes. Methods: Data on 2500 participants aged 18–60 years were collected from the Qatar Biobank (QBB). Sleep duration and quality were assessed by a self-completed health and lifestyle questionnaire, and glycemic control was assessed using HbA1c. Logistic regression was used to assess the association between sleep duration, napping, snoring and poor glycemic control. Results: After adjusting for age and gender, sleep duration was not associated with poor glycemic control. Lack of association persisted after controlling for smoking, physical activity, education, BMI, fruit and vegetable intake, insulin and medication use. However, sleeping for long hours at night (8 h) had a trend in increasing the risk of poor glycemic control (OR = 1.28; 95% CI: 0.94–1.74). Napping was positively associated with poor glycemic control. After adjusting for age and gender, patients who reported “sometimes, frequently, or always” napping had more than 30% increased risk of poor control as compared to patients who reported “never/rarely” napping. Snoring was not associated with poor glycemic control among the study sample when adjusted for age and gender (p = 0.61). Other factors were found to be associated with a better glycemic control such as female, high educational and high physical activity level. Conclusions: our results suggest that napping may be an independent risk factor for a poor glycemic control in diabetes. Further research is needed to establish the causal link between sleep and impaired glucose metabolism. These findings may open up new strategies for targeted intervention to improve the duration and quality of sleep.

Self-Referent Thoughts in Exercise: The Self-Perception in Exercise Questionnaire

1997 ◽  
Vol 13 (3) ◽  
pp. 195-205 ◽  
Author(s):  
Marit Sorensen
Keyword(s):  
Physical Activity ◽  
Pilot Study ◽  
Physical Activity Level ◽  
Convergent Validity ◽  
English Language ◽  
Lifestyle Changes ◽  
Activity Level ◽  
Language Version ◽  
Social Comfort ◽  
And Gender

Adherence to lifestyle changes - beginning to exercise, for example - is assumed to be mediated by self-referent thoughts. This paper describes a pilot study and three studies conducted to develop and validate a questionnaire for adults to determine their self-perceptions related to health-oriented exercise. The pilot study identified items pertinent to the domains considered important in this context, and began the process of selecting items. Study 2 examined the factor structure, reduced the number of items, determined the internal consistency of the factors, and explored the discriminative validity of the questionnaire as to physical activity level and gender. Four factors with a total of 24 items were accepted, measuring mastery of exercise, body perception, social comfort/discomfort in the exercise setting, and perception of fitness. All subscales had acceptable internal consistencies. Preliminary validity was demonstrated by confirming hypothesized differences in scores as to gender, age, and physical activity level. The third study examined and demonstrated convergent validity with similar existing subscales. The fourth study examined an English-language version of the questionnaire, confirming the existence of the factors and providing preliminary psychometric evidence of the viability of the questionnaire.

836-P: Cannabis Use in Adults with Type 1 Diabetes (T1D) Is Associated with Poor Glycemic Control and Increased Risk for Diabetic Ketoacidosis (DKA)

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 836-P ◽  
Author(s):  
VIRAL N. SHAH ◽  
DANIEL D. TAYLOR ◽  
NICOLE C. FOSTER ◽  
ROY BECK ◽  
HALIS K. AKTURK ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Diabetic Ketoacidosis ◽  
Cannabis Use ◽  
Poor Glycemic Control ◽  
Increased Risk

scholarly journals Factors Associated with Poor Glycemic Control Amongst Rural Residents with Diabetes in Korea

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 391
Author(s):  
Junhee Ahn ◽  
Youngran Yang
Keyword(s):  
Physical Activity ◽  
Blood Glucose ◽  
Glycemic Control ◽  
Fasting Blood Glucose ◽  
Regular Physical Activity ◽  
Poor Glycemic Control ◽  
Rural Residents ◽  
Factors Associated ◽  
The Poor ◽  
Positive Urine

(1) Background: Glycemic control is an effective way to reduce the cardiovascular complications of diabetes. The purpose of this study was to identify the factors associated with poor glycemic control amongst rural residents with diabetes in Korea. (2) Methods: This cross-sectional analysis was conducted amongst a total of 522 participants who had completed baseline health examinations for the Korean Genome and Epidemiology Study (KoGES) Rural Cohort from 2005 to 2011. The subjects were divided into two groups: the good glycemic control group (GCG) (glycosylated hemoglobin (HbA1C) < 7%) and the poor GCG (HbA1C ≥ 7%). Logistic regression was used to examine the role of sociodemographics, health-related behavior, comorbidity and diabetes-related and clinical factors in poor glycemic control amongst rural residents with diabetes. (3) Results: In total, 48.1% of participants were in the poor GCG. Poor GCG was significantly associated with drinking (odds ratio (OR) = 0.42, 95% CI = 0.24–0.71), lack of regular physical activity (OR = 1.68, 95% CI = 1.03–2.76), fasting blood glucose (FBG) > 130 mg/dL (OR = 7.80, 95% CI = 4.35–13.98), diabetes for > 7 years (OR = 1.79, 95% CI = 1.08–2.98), cholesterol ≥ 200 mg/dL (OR = 1.73, 95% CI = 1.05–2.84) and positive urine glucose (OR = 6.24, 95% CI = 1.32–29.44). (4) Conclusion: Intensive glucose control interventions should target individuals amongst rural residents with diabetes who do not engage in regular physical activity, have been diagnosed with diabetes for more than seven years and who have high fasting-blood glucose, high cholesterol levels and glucose-positive urine.

scholarly journals Later sleep timing predicts accelerated summer weight gain among elementary school children: a prospective observational study

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jennette P. Moreno ◽  
Javad Razjouyan ◽  
Houston Lester ◽  
Hafza Dadabhoy ◽  
Mona Amirmazaheri ◽  
...  
Keyword(s):  
Physical Activity ◽  
Observational Study ◽  
Sleep Duration ◽  
Obesity Prevention ◽  
Prospective Observational Study ◽  
Light Exposure ◽  
Activity Level ◽  
Activity Levels ◽  
School Year ◽  
Children’S Sleep

Abstract Objectives and background Social demands of the school-year and summer environment may affect children’s sleep patterns and circadian rhythms during these periods. The current study examined differences in children’s sleep and circadian-related behaviors during the school-year and summer and explored the association between sleep and circadian parameters and change in body mass index (BMI) during these time periods. Methods This was a prospective observational study with 119 children ages 5 to 8 years with three sequential BMI assessments: early school-year (fall), late school-year (spring), and beginning of the following school-year in Houston, Texas, USA. Sleep midpoint, sleep duration, variability of sleep midpoint, physical activity, and light exposure were estimated using wrist-worn accelerometry during the school-year (fall) and summer. To examine the effect of sleep parameters, physical activity level, and light exposure on change in BMI, growth curve modeling was conducted controlling for age, race, sex, and chronotype. Results Children’s sleep midpoint shifted later by an average of 1.5 h during summer compared to the school-year. After controlling for covariates, later sleep midpoints predicted larger increases in BMI during summer, (γ = .0004, p = .03), but not during the school-year. Sleep duration, sleep midpoint variability, physical activity levels, and sedentary behavior were not associated with change in BMI during the school-year or summer. Females tended to increase their BMI at a faster rate during summer compared to males, γ = .06, p = .049. Greater amounts of outdoor light exposure (γ = −.01, p = .02) predicted smaller increases in school-year BMI. Conclusions Obesity prevention interventions may need to target different behaviors depending on whether children are in or out of school. Promotion of outdoor time during the school-year and earlier sleep times during the summer may be effective obesity prevention strategies during these respective times.

scholarly journals Physical Activity and Quality of Life in Hemodialysis Patients and Healthy Controls: A Cross-Sectional Study

2021 ◽  
Vol 18 (4) ◽  
pp. 1978
Author(s):  
Tjaša Filipčič ◽  
Špela Bogataj ◽  
Jernej Pajek ◽  
Maja Pajek
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Everyday Life ◽  
Habitual Physical Activity ◽  
Healthy Controls ◽  
Age And Gender ◽  
Comorbidity Score ◽  
Sf 36 ◽  
And Gender

Hemodialysis (HD) patients have lower functional abilities compared to healthy people, and this is associated with lower physical activity in everyday life. This may affect their quality of life, but research on this topic is limited. Therefore, the present study aimed to determine the relationship between habitual physical activity and quality of life in HD patients and healthy controls. Ninety-three HD patients and 140 controls participated in the study. Quality of life was assessed using a 36-item medical outcomes study short-form health survey (SF-36). Human Activity Profile (HAP) was used to assess habitual physical activity. The adjusted activity score (AAS) from HAP, age, gender, fat tissue index (FTI), lean tissue index (LTI), and Davies comorbidity score were analyzed as possible predictors of the Physical Component Summary (PCS) of the SF-36. Three sequential linear models were used to model PCS. In Model 1, PCS was regressed by gender and age; in Model 2 the LTI, FTI, and Davies comorbidity scores were added. Model 3 also included AAS. After controlling for age and gender (ModelHD 1: p = 0.056), LTI, FTI, and Davies comorbidity score effects (ModelHD 2: p = 0.181), the AAS accounted for 32% of the variation in PCS of HD patients (ModelHD 3: p < 0.001). Consequently, the PCS of HD patients would increase by 0.431 points if the AAS increased by one point. However, in healthy controls, AAS had a lower impact than in the HD sample (B = 0.359 vs. 0.431), while the corresponding effects of age and gender (ModelH 1: p < 0.001), LTI, FTI, and Davies comorbidity score (ModelH 2: p < 0.001) were adjusted for. The proportion of variation in PCS attributed to AAS was 14.9% (ModelH 3: p < 0.001). The current study results showed that physical activity in everyday life as measured by the HAP questionnaire is associated to a higher degree with the quality of life of HD patients than in healthy subjects. Routine physical activity programs are therefore highly justified, and the nephrology community should play a leading role in this effort.

scholarly journals Associations between objectively measured physical activity, sedentary behaviour and time in bed among 75+ community-dwelling Danish older adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Behaviour ◽  
Sleep Duration ◽  
Activity Level ◽  
Time In Bed ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity ◽  
Vector Magnitude

Abstract Background Older adults are recommended to sleep 7–8 h/day. Time in bed (TIB) differs from sleep duration and includes also the time of lying in bed without sleeping. Long TIB (≥9 h) are associated with self-reported sedentary behavior, but the association between objectively measured physical activity, sedentary behavior and TIB is unknown. Methods This study was based on cross-sectional analysis of the Healthy Ageing Network of Competence (HANC Study). Physical activity and sedentary behaviour were measured by a tri-axial accelerometer (ActiGraph) placed on the dominant wrist for 7 days. Sedentary behavior was classified as < 2303 counts per minute (cpm) in vector magnitude and physical activity intensities were categorized, as 2303–4999 and ≥ 5000 cpm in vector magnitude. TIB was recorded in self-reported diaries. Participants were categorized as UTIB (usually having TIB 7–9 h/night: ≥80% of measurement days), STIB (sometimes having TIB 7–9 h/night: 20–79% of measurement days), and RTIB (rarely having TIB 7–9 h/night: < 20% of measurement days). Multinominal regression models were used to calculate the relative risk ratios (RRR) of being RTIB and STIB by daily levels of physical activity and SB, with UTIB as the reference group. The models were adjusted for age, sex, average daily nap length and physical function. Results Three hundred and fourty-one older adults (median age 81 (IQR 5), 62% women) were included with median TIB of 8 h 21 min (1 h 10 min)/day, physical activity level of 2054 (864) CPM with 64 (15) % of waking hours in sedentary behavior. Those with average CPM within the highest tertile had a lower RRR (0.33 (0.15–0.71), p = 0.005) for being RTIB compared to those within the lowest tertile of average CPM. Accumulating physical activity in intensities 2303–4999 and ≥ 5000 cpm/day did not affect the RRR of being RTIB. RRR of being RTIB among highly sedentary participants (≥10 h/day of sedentary behavior) more than tripled compared to those who were less sedentary (3.21 (1.50–6.88), p = 0.003). Conclusions For older adults, being physically active and less sedentary was associated with being in bed for 7–9 h/night for most nights (≥80%). Future longitudinal studies are warranted to explore the causal relationship sbetween physical activity and sleep duration.

scholarly journals Physical activity benefits of attending a senior center depend largely on age and gender: a study using GPS and accelerometry data

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Oriol Marquet ◽  
Monika Maciejewska ◽  
Xavier Delclòs-Alió ◽  
Guillem Vich ◽  
Jasper Schipperijn ◽  
...  
Keyword(s):  
Physical Activity ◽  
Senior Center ◽  
Age And Gender ◽  
And Gender

scholarly journals Prevalence of Malnutrition (Overweight and Underweight) in Children Aged 10-13 Years in Schools in Manipal and Utopia, Karnataka

2020 ◽  
Vol 10 (1) ◽  
pp. 94
Author(s):  
Fatemeh Jahani
Keyword(s):  
Physical Activity ◽  
Statistical Analysis ◽  
Activity Level ◽  
Normal Height ◽  
Major Health Problem ◽  
Major Health ◽  
Severe Stunting ◽  
Increased Risk ◽  
Child Eating ◽  
Height For Age

Background. Malnutrition is a major health problem in India. It mostly affects children of school going age with serious health problems putting them at an increased risk for developing chronic diseases later in life. This study aims to study the prevalence of malnutrition (overweight and underweight) in children aged 10-13 years in schools in Manipal and Utopia, Karnataka. Materials and Methods. In this study, a total 400 students were studied. Their anthropometric measurements like height, weight, BMI and MUAC, dietary pattern, physical activity level, and child eating behavior. Questionnaire was used to note the student&rsquo;s information. The data collected was subjected to statistical analysis using SPSS version 21, Diet Cal, and Anthroplus1.0.4. Results. It was observed that in the childhood category 10-13 years there were 222 (55.5%) male and 178(44.5%) female. According to the BMI for age 53.4% of them falls under the normal category; 22.3% falls under the mild wasting category; About 18.3% falls under the obese category and 8% falls under the moderate wasting category. There is no students falling under the severe wasting and overweight category according to the BAZ classification. When the height for age was done for all the children, about 36.3% falls under normal height; About 35.5% falls under mild stunting; 19.3% falls under the moderate stunting; 8.3% falls under the severe stunting category; and 1% falls under tall category according to the HAZ classification. Conclusions. In conclusion, mild stunting and wasting was observed among children. There are no students falling under the severe wasting and overweight category according to the BAZ classification.

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