Menstrual Cycle Characteristics Across the Reproductive Lifespan, Lifestyle Factors and Risk of Type 2 Diabetes

2020 ◽  
Author(s):  
Yi-Xin Wang ◽  
Zhilei Shan ◽  
Mariel Arvizu ◽  
An Pan ◽  
JoAnn E. Manson ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Menstrual Cycle ◽  
Lifestyle Factors

scholarly journals Associations of Menstrual Cycle Characteristics Across the Reproductive Life Span and Lifestyle Factors With Risk of Type 2 Diabetes

2020 ◽  
Vol 3 (12) ◽  
pp. e2027928
Author(s):  
Yi-Xin Wang ◽  
Zhilei Shan ◽  
Mariel Arvizu ◽  
An Pan ◽  
JoAnn E. Manson ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Menstrual Cycle ◽  
Life Span ◽  
Lifestyle Factors ◽  
Reproductive Life ◽  
Reproductive Life Span

scholarly journals Differing Contributions of Classical Risk Factors to Type 2 Diabetes in Multi-Ethnic Malaysian Populations

2018 ◽  
Vol 15 (12) ◽  
pp. 2813
Author(s):  
Noraidatulakma Abdullah ◽  
Nor Abdul Murad ◽  
John Attia ◽  
Christopher Oldmeadow ◽  
Mohd Kamaruddin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Family History ◽  
Characteristic Curve ◽  
Lifestyle Factors ◽  
Predictive Utility ◽  
Family History Of Diabetes ◽  
History Of

The prevalence of type 2 diabetes is escalating rapidly in Asian countries, with the rapid increase likely attributable to a combination of genetic and lifestyle factors. Recent research suggests that common genetic risk variants contribute minimally to the rapidly rising prevalence. Rather, recent changes in dietary patterns and physical activity may be more important. This nested case-control study assessed the association and predictive utility of type 2 diabetes lifestyle risk factors in participants from Malaysia, an understudied Asian population with comparatively high disease prevalence. The study sample comprised 4077 participants from The Malaysian Cohort project and included sub-samples from the three major ancestral groups: Malay (n = 1323), Chinese (n = 1344) and Indian (n = 1410). Association of lifestyle factors with type 2 diabetes was assessed within and across ancestral groups using logistic regression. Predictive utility was quantified and compared between groups using the Area Under the Receiver-Operating Characteristic Curve (AUC). In predictive models including age, gender, waist-to-hip ratio, physical activity, location, family history of diabetes and average sleep duration, the AUC ranged from 0.76 to 0.85 across groups and was significantly higher in Chinese than Malays or Indians, likely reflecting anthropometric differences. This study suggests that obesity, advancing age, a family history of diabetes and living in a rural area are important drivers of the escalating prevalence of type 2 diabetes in Malaysia.

scholarly journals Distinct Relevance of Nightly Sleep Duration to Metabolic, Anthropometric, and Lifestyle Factors in Patients with Type 2 Diabetes

2021 ◽  
Author(s):  
Hitomi Nakayama ◽  
Yasushi Yamada ◽  
Kentaro Yamada ◽  
Shimpei Iwata ◽  
Nobuhiko Wada ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Sleep Duration ◽  
Lifestyle Factors

scholarly journals Association between sugar-sweetened and artificially sweetened soft drinks and type 2 diabetes: systematic review and dose–response meta-analysis of prospective studies

2014 ◽  
Vol 112 (5) ◽  
pp. 725-734 ◽  
Author(s):  
D. C. Greenwood ◽  
D. E. Threapleton ◽  
C. E. L. Evans ◽  
C. L. Cleghorn ◽  
C. Nykjaer ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Dose Response ◽  
Prospective Studies ◽  
Meta Analysis ◽  
Lifestyle Factors ◽  
Soft Drinks ◽  
Reverse Causality ◽  
Increased Risk ◽  
Causal Pathway

The intake of sugar-sweetened soft drinks has been reported to be associated with an increased risk of type 2 diabetes, but it is unclear whether this is because of the sugar content or related lifestyle factors, whether similar associations hold for artificially sweetened soft drinks, and how these associations are related to BMI. We aimed to conduct a systematic literature review and dose–response meta-analysis of evidence from prospective cohorts to explore these issues. We searched multiple sources for prospective studies on sugar-sweetened and artificially sweetened soft drinks in relation to the risk of type 2 diabetes. Data were extracted from eleven publications on nine cohorts. Consumption values were converted to ml/d, permitting the exploration of linear and non-linear dose–response trends. Summary relative risks (RR) were estimated using a random-effects meta-analysis. The summary RR for sugar-sweetened and artificially sweetened soft drinks were 1·20/330 ml per d (95 % CI 1·12, 1·29,P< 0·001) and 1·13/330 ml per d (95 % CI 1·02, 1·25,P= 0·02), respectively. The association with sugar-sweetened soft drinks was slightly lower in studies adjusting for BMI, consistent with BMI being involved in the causal pathway. There was no evidence of effect modification, though both these comparisons lacked power. Overall between-study heterogeneity was high. The included studies were observational, so their results should be interpreted cautiously, but findings indicate a positive association between sugar-sweetened soft drink intake and type 2 diabetes risk, attenuated by adjustment for BMI. The trend was less consistent for artificially sweetened soft drinks. This may indicate an alternative explanation, such as lifestyle factors or reverse causality. Future research should focus on the temporal nature of the association and whether BMI modifies or mediates the association.

scholarly journals Modelling the Interplay between Lifestyle Factors and Genetic Predisposition on Markers of Type 2 Diabetes Mellitus Risk

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0131681 ◽  
Author(s):  
Celia G. Walker ◽  
Ivonne Solis-Trapala ◽  
Christina Holzapfel ◽  
Gina L. Ambrosini ◽  
Nicholas R. Fuller ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Genetic Predisposition ◽  
Lifestyle Factors ◽  
Diabetes Mellitus Risk

scholarly journals An Accurate Risk Score Based on Anthropometric, Dietary, and Lifestyle Factors to Predict the Development of Type 2 Diabetes

Diabetes Care ◽  
2007 ◽  
Vol 30 (3) ◽  
pp. 510-515 ◽  
Author(s):  
M. B. Schulze ◽  
K. Hoffmann ◽  
H. Boeing ◽  
J. Linseisen ◽  
S. Rohrmann ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Lifestyle Factors

scholarly journals Empowering Patients for Healthy Nutrition, Physical Activity, and Self-Care Using the Diabetes Score Questionnaire

2021 ◽  
Vol 27 (4) ◽  
pp. 131-136
Author(s):  
Muhammad Jawad Hashim ◽  
Halla Mustafa
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Lifestyle Change ◽  
Lifestyle Factors ◽  
Health Care Center ◽  
Healthy Nutrition ◽  
Patients With Diabetes

<b><i>Objectives:</i></b> Lifestyle factors such as nutrition and physical activity play an important role in the management of diabetes mellitus. Unfortunately, adherence to lifestyle change remains low among patients with diabetes. The aim of this study was to evaluate the effectiveness of the Diabetes Score questionnaire in a clinical setting. <b><i>Methods:</i></b> The Diabetes Score is a 10-item shared decision-making tool designed to empower lifestyle change in individuals with diabetes. It yields an intuitive score from 0 to 100 based on a patient’s adherence to lifestyle recommendations. An observational study was conducted at an ambulatory health care center. After obtaining written informed consent, adult patients with type 2 diabetes mellitus were interviewed by a trained researcher using the Diabetes Score questionnaire. Patients’ Diabetes Score values were analyzed in reference to their glycemic control and other clinical and demographic factors. <b><i>Results:</i></b> A total of 60 individuals with type 2 diabetes participated in the study. The mean age was 56 years (minimum 43 years, maximum 70 years) with 60% being males. Higher Diabetes Scores correlated with better glycemic control (hemoglobin A1C; <i>r</i> = −0.23, <i>p</i> = 0.044) indicating the effect of lifestyle factors such as healthy nutrition, smaller portion sizes, active lifestyle, and aerobic exercise. The questionnaire showed internal consistency (alpha 0.66), construct validity, and high patient satisfaction (98%). <b><i>Conclusion:</i></b> Diabetes Score, a behavioral lifestyle questionnaire, correlates with glycemic control in type 2 diabetes. Diabetes Score can be used in clinical settings for measuring, discussing, and setting targets for lifestyle change among patients with diabetes.

scholarly journals Cumulative intake of artificially sweetened and sugar-sweetened beverages and risk of incident type 2 diabetes in young adults: the Coronary Artery Risk Development In Young Adults (CARDIA) Study

2019 ◽  
Vol 110 (3) ◽  
pp. 733-741 ◽  
Author(s):  
Kristin M Hirahatake ◽  
David R Jacobs ◽  
James M Shikany ◽  
Luohua Jiang ◽  
Nathan D Wong ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Young Adults ◽  
Coronary Artery ◽  
Weight Change ◽  
Lifestyle Factors ◽  
Sweetened Beverage ◽  
Dieting Behavior ◽  
Baseline Bmi

ABSTRACT Background Epidemiological evidence has demonstrated a positive association between artificially sweetened beverage (ASB) and sugar-sweetened beverage (SSB) consumption and type 2 diabetes (T2D) risk. However, research informing this topic in young adults is limited. Objective This study examined the association between ASB, SSB, and total sweetened beverage (TSB; combined ASB and SSB) consumption and T2D risk in young adults. Methods A prospective analysis of 4719 Black and White men and women aged 18–30 y at baseline was conducted from the Coronary Artery Risk Development in Young Adults (CARDIA) study. Each participant's beverage intake was assessed using the CARDIA Diet History at baseline and at study Years 7 and 20. Multivariable Cox proportional hazards regression models were used to examine cumulative average ASB, SSB, and TSB intakes and risk of T2D. Results During the 30-y follow-up period, 680 participants developed T2D. ASB consumption was associated with a 12% greater risk of T2D per serving/day (HR 1.12, 95% CI 1.04–1.20) in a model adjusted for lifestyle factors, diet quality, and dieting behavior. Further adjustments for baseline BMI (HR 1.07, 95% CI 0.99–1.14) and weight change during follow-up (HR 1.04, 95% CI 0.97–1.12) attenuated the association. SSB and TSB consumption as continuous variables per 1 serving/day of intake were associated with 6% and 5% increased risks of T2D, respectively (HRSSB 1.06, 95% CI 1.01–1.10; HRTSB 1.05, 95% CI 1.01–1.09), in the model accounting for lifestyle factors, dieting behavior, baseline BMI, and weight change. Results were consistent when the exposures were modeled in categories of consumption and quintiles. Conclusions In young adults, long-term ASB, SSB, and TSB consumption were associated with increased risks of T2D. However, the estimates for ASB were attenuated when accounting for weight changes.

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