Chronic Disease Prevention

Dietz, William H.; Douglas, Clifford E; Brownson, Ross C.

doi:10.1001/jama.2016.14370

Cited by 76 publications

(32 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our analysis of the association of T2DM-related mortality and lifestyle-related risk factors, high BMI was excluded due to data quality limitations and high collinearity with dietary risk factors, low physical activity, and smoking. High BMI was excluded because it is often a product of poor dietary habits and physical inactivity [ 29 ], and its importance to several chronic NCDs, including T2DM, has been highlighted previously [ 29 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

Sex differences and risk factors for diabetes mellitus - an international study from 193 countries

et al. 2018

View full text Add to dashboard Cite

BackgroundIncreases in overweight and obesity among youths have resulted in the diagnosis of Type 2 diabetes mellitus (T2DM) at earlier ages. The impact of lifestyle-related factors has been implicated; however, its relation to morbidity and mortality and sex differences remain unclear. We aimed to document the changes in risk factors and sex differences associated with T2DM-related morbidity and mortality during 1995–2015.MethodWe used mortality rates and morbidity estimates from the Global Burden of Diseases Study 2016 using Disability-Adjusted Life Years (DALY). Multiple linear regression analyses were used to determine associations between T2DM-related mortality and related risk factors. DALYs were grouped by country income level, and were stratified by sex.ResultsIncreases in mortality were observed for both sexes, and females tended to have higher mortality rates per 100,000 persons. Body mass index (BMI) continued to be the leading risk factor for T2DM-related mortality, and increases in BMI were more common in low- and middle-income countries (LIC and MIC). Low physical activity was strongly associated with mortality rates, followed by dietary risks and smoking (2.4; 1.4; 0.8 per 100,000 persons, respectively). Similar patterns were observed after adjustments for income level, sex, and age. DALYs continued to show increasing trends across all income levels during 1995–2015 (high-income (HIC):16%; MIC: 36%; LIC: 12%). Stratification by sex showed similar results; males had fewer T2DM DALYs than females, though a greater increase was observed among males.ConclusionOverall, T2DM related mortality was higher among females. Compared to in HIC, there appeared to be a considerable increase in the burden of T2DM in MIC and LIC, where BMI is the leading risk factor for T2DM-related mortality. Prevention programs should emphasize related risk factors according to the existing standard of care.

show abstract

Section: Discussionmentioning

confidence: 99%

Sex differences and risk factors for diabetes mellitus - an international study from 193 countries

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Chronic diseases, such as cardiovascular disease, diabetes, and cancers, are the leading cause of death in Australia ( 1 ) and worldwide ( 2 ). Physical inactivity, poor diet, smoking, and alcohol use are consistently identified as major behavioral risk factors for chronic disease ( 3 – 5 ). More recently, sedentary behavior and poor sleep have also emerged as key risk factors for poor health.…”

Section: Introductionmentioning

confidence: 99%

Clustering of Multiple Risk Behaviors Among a Sample of 18-Year-Old Australians and Associations With Mental Health Outcomes: A Latent Class Analysis

Champion

Mather

Spring

et al. 2018

Front. Public Health

View full text Add to dashboard Cite

IntroductionRisk behaviors commonly co-occur, typically emerge in adolescence, and become entrenched by adulthood. This study investigated the clustering of established (physical inactivity, diet, smoking, and alcohol use) and emerging (sedentary behavior and sleep) chronic disease risk factors among young Australian adults, and examined how clusters relate to mental health.MethodsThe sample was derived from the long-term follow-up of a cohort of Australians. Participants were initially recruited at school as part of a cluster randomized controlled trial. A total of 853 participants (Mage = 18.88 years, SD = 0.42) completed an online self-report survey as part of the 5-year follow-up for the RCT. The survey assessed six behaviors (binge drinking and smoking in the past 6 months, moderate-to-vigorous physical activity/week, sitting time/day, fruit and vegetable intake/day, and sleep duration/night). Each behavior was represented by a dichotomous variable reflecting adherence to national guidelines. Exploratory analyses were conducted. Clusters were identified using latent class analysis.ResultsThree classes emerged: “moderate risk” (moderately likely to binge drink and not eat enough fruit, high probability of insufficient vegetable intake; Class 1, 52%); “inactive, non-smokers” (high probabilities of not meeting guidelines for physical activity, sitting time and fruit/vegetable consumption, very low probability of smoking; Class 2, 24%), and “smokers and binge drinkers” (high rates of smoking and binge drinking, poor fruit/vegetable intake; Class 3, 24%). There were significant differences between the classes in terms of psychological distress (p = 0.003), depression (p < 0.001), and anxiety (p = 0.003). Specifically, Class 3 (“smokers and binge drinkers”) showed higher levels of distress, depression, and anxiety than Class 1 (“moderate risk”), while Class 2 (“inactive, non-smokers”) had greater depression than the “moderate risk” group.DiscussionResults indicate that risk behaviors are prevalent and clustered in 18-year old Australians. Mental health symptoms were significantly greater among the two classes that were characterized by high probabilities of engaging in multiple risk behaviors (Classes 2 and 3). An examination of the clustering of lifestyle risk behaviors is important to guide the development of preventive interventions. Our findings reinforce the importance of delivering multiple health interventions to reduce disease risk and improve mental well-being.

show abstract

“…The rapid growth of chronic diseases brings heavy burden on healthcare and society. The major risk factors of these diseases come from tobacco smoking, alcohol consumption, unhealthy diet, and lack of physical activity [1–3]. …”

Section: Introductionmentioning

confidence: 99%

Association between Nine Types of TCM Constitution and Five Chronic Diseases: A Correspondence Analysis Based on a Sample of 2,660 Participants

Zhu

Shi

Wang

et al. 2017

Evidence-Based Complementary and Alternative Medicine

View full text Add to dashboard Cite

Objective The purpose of this study was to explore the association of nine types of Traditional Chinese Medicine (TCM) constitution with the five chronic diseases: hypertension, hyperlipidemia, diabetes mellitus, heart disease, and obesity. Methods Chi-squared test was performed to investigate the distribution characteristics of TCM constitutions in the participants with the five chronic diseases in questionnaire. Correspondence analysis was used to explore the correlation between them. Results A total of 2,660 participants (1,400 males; 1,260 females) were included in this study. The mean age was 52.54 ± 13.92. Of them, 600 were of gentleness type accounting for 22.56%. Proportions of gentleness type in the chronic diseases (16.00%~23.70%) were less than that in general population (32.14%). The gentleness type and yin-deficiency type were significantly correlated with hypertension and diabetes mellitus, qi-deficiency type was correlated with heart disease, phlegm-dampness type was associated with obesity, and dampness-heat type was correlated with hyperlipidemia. Conclusions The correlations between TCM constitution types and the five chronic diseases were different. This may have a significant implication for TCM practice, and even the people with gentleness type should not be ignored in health management.

show abstract

Chronic Disease Prevention

Cited by 76 publications

References 4 publications

Sex differences and risk factors for diabetes mellitus - an international study from 193 countries

Sex differences and risk factors for diabetes mellitus - an international study from 193 countries

Clustering of Multiple Risk Behaviors Among a Sample of 18-Year-Old Australians and Associations With Mental Health Outcomes: A Latent Class Analysis

Association between Nine Types of TCM Constitution and Five Chronic Diseases: A Correspondence Analysis Based on a Sample of 2,660 Participants

Contact Info

Product

Resources

About