A meta-analysis of passive smoking and risk of developing Type 2 Diabetes Mellitus

Wei, Xiaomin; Meng, En; Sung, Yunsick

doi:10.1016/j.diabres.2014.09.019

Cited by 58 publications

(41 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Furthermore, the present study found the occurrence of undiagnosed diabetes was significantly higher among those participants with current smoking practices, which is also supported by previous studies conducted elsewhere. 19,20 Several reasons have been suggested to elaborate these associations. It has been established that smoking is a possible risk factor for insulin resistance as well as worsen glucose metabolism.…”

Section: Discussionmentioning

confidence: 99%

Undiagnosed diabetes mellitus and related factors in East Gojjam (NW Ethiopia) in 2016: a community-based study

Wondemagegn¹,

Bizuayehu²,

Abie³

et al. 2017

J Public Health Res

View full text Add to dashboard Cite

IntroductionCurrently, diabetes is the second most common non-communicable disease (NCD) in Ethiopia. Its burden is 4.8% in this country, even though three quarter of its population live with undiagnosed diabetes mellitus (DM), which causes complications like heart failure, blood vessels, eyes, kidneys and nerves damages. Early detection of DM is vital for a timely intervention to prevent these life threatening complications. The aim of this study was to assess the prevalence of undiagnosed DM and related factors in East Gojjam, North West Ethiopia, in 2016.Materials and methodsA community-based cross-sectional study was conducted among 757 individuals in East Gojjam from June to September 2016. The sampled population was selected using multi-stage cluster sampling method. Basic data were collected in Amharic (local language) and a pretested interviewer administered the questionnaire. Peripheral blood samples were collected by puncturing the ring finger in order to measure fasting blood glucose. Univarite and multivariate logistic regressions analysis were performed using Statistical Package for Social Sciences (SPSS) software version 20.0.ResultsThe percentage of undiagnosed DM in the study area was 11.5% (95%CI=9.2, 13.7). The prevalence was 11.3% among male vs. 11.8% among female; 13.4% in urban areas vs. 10.3% in rural areas. The occurrence of undiagnosed DM was mainly associated with older age (AOR=5.99, 95%CI=1.54, 23.24), family history of diabetes (AOR=9.86, 95%CI=4.25, 22.89), history of gestational diabetes (AOR=3.01, 95%CI=1.17, 8.39) and sedentary behaviour >4 hours per day (AOR=2.13, 95%CI=1.04, 4.34). Being non-smoker (AOR=0.05, 95%CI=0.01, 0.17) and unmarried (AOR=0.09, 95%CI=0.02, 0.42) were also predictive characteristics for undiagnosed DM in the study area.ConclusionsIn conclusion, this study revealed a relatively high prevalence of undiagnosed DM in the study area. The occurrence of undiagnosed DM was significantly higher when associated with the age of the participants, their marital status, history of hypertension, diabetes family history, history of gestational diabetes mellitus, current smoking practices and sedentary behaviour. Thus, efforts have to be made, particularly by the individuals involved in health practice, to early detect the disease and thereby initiate a suitable therapeutic service, before complications ariseSignificance for public healthCurrently, diabetes is the second most common non-communicable disease in Ethiopia. Its burden is 4.8% in this country, though three quarter of its population live with undiagnosed diabetes mellitus (DM), which could lead to several complications such as heart failure, blood vessels, eyes, kidneys, and nerves damages. Evidence shows that the disease is increasing through time. Early detection of DM is vital for a timely intervention to prevent life-threatening complications. Efforts should be made by politicians, decision makers and other healthy institutions to implement screening modality and early interventions.

show abstract

Section: Discussionmentioning

confidence: 99%

Undiagnosed diabetes mellitus and related factors in East Gojjam (NW Ethiopia) in 2016: a community-based study

Wondemagegn¹,

Bizuayehu²,

Abie³

et al. 2017

J Public Health Res

View full text Add to dashboard Cite

show abstract

“…4-6 In addition, several studies reported that diabetes risk was increased in individuals who had recently quitted smoking, raising a concern about elevated diabetes risk with smoking cessation. 7-16 Therefore, quantifying the association between duration since smoking cessation and diabetes risk will provide direct evidence for clinical practice and public health policy.…”

Section: Introductionmentioning

confidence: 99%

Relation of active, passive, and quitting smoking with incident type 2 diabetes: a systematic review and meta-analysis

Pan

Wang

Talaei

et al. 2015

The Lancet Diabetes & Endocrinology

453

310

View full text Add to dashboard Cite

Background Cigarette smoking remains the leading avoidable cause of disease burden worldwide, and observational studies have linked various smoking behaviors (active and passive smoking and smoking cessation) with risk of type 2 diabetes. We did a meta-analysis of prospective studies assessing the relation of various smoking behaviors and diabetes risk. Methods We systematically searched MEDLINE and EMBASE databases (up to 3 May 2015) with manual searches of the references of retrieved publications and relevant reviews. We included prospective studies that reported risk of type 2 diabetes by baseline smoking status. Relative risks (RRs) and 95% confidence intervals (CIs) were pooled using random-effects models, and subgroup analyses were performed by participant and study characteristics. Findings The search yielded 88 prospective studies with nearly 6 million participants and 295446 incident cases. Compared with never smoking, the pooled RR (95% CI) of type 2 diabetes was 1·37 (1·33-1·42) for current smoking (84 studies), 1·14 (1·10-1·18) for former smoking (47 studies), and 1·22 (1·10-1·35) for passive smoking (7 studies). The associations persisted in all subgroups, and a dose-response relation was found for current smoking and diabetes risk: the RRs (95% CIs) were 1·21 (1·10-1·33), 1·34 (1·27-1·41) and 1·57 (1·47-1·66) for light, moderate, and heavy smokers, respectively, compared with never smokers. We estimated that 10·3% in men and 2·2% in women of type 2 diabetes cases (approximately 25 million) were attributable to cigarette smoking worldwide if smoking is causally related to diabetes. Compared to never smokers, the pooled RR (95% CI) from 10 studies was 1·54 (1·36-1·74) in new quitters (<5 years), and 1·11 (1·02-1·20) in long-term quitters (≥10 years). Interpretation Active and passive smoking are associated with significantly increased risks of type 2 diabetes. The risk of diabetes is elevated in new quitters, but decreases substantially as the time since quitting increases.

show abstract

“…Recently, a metaanalysis suggested that passive smoking is a risk factor of diabetes even in those who were not themselves active smokers [56]. However, both passive and active smoking is associated with diabetes in the elderly population [54]; whereas in men aged 25 years or over, morbid obesity and smoking were significantly associated with diabetes in Southern California American Indians [57].…”

Section: Discussionmentioning

confidence: 99%

Principal Component Regression Analysis of Nutrition Factors and Physical Activities with Diabetes

Wang¹,

Liu²,

Xie³

et al. 2017

J Biom Biostat

View full text Add to dashboard Cite

The associations of nutrition factors and physical activities with adult diabetes are inconsistent; while most of these factors are inter correlated. The aims of this study are to overcome the disturbance of the multicollinearity of the risk factors and examine the associations of these factors with diabetes using the principal component analysis (PCA) and regression analysis with principal component scores (PCS). Totally, 659 adults with diabetes and 2827 non-diabetic were selected from the 2012 Health Information National Trends Survey (HINTS 4, Cycle 2). PCA was utilized to deal with multicollinearity of the risk factors. Weighted univariate and multiple logistic regression analyses were used to estimate the associations of potential factors and PCS with diabetes. The odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. The first 3 PCs for nutrition factors and physical activities could explain 70% variances. The first principal component (PC 1 ) is a measure of nutrition factors (fruit and vegetables consumption), PC 2 is a measure for physical activities (moderate exercise and strength training), and PC3 is about calorie information use and soda use. Weighted multiple logistic regression showed that African Americans, middle aged adults (45-64 years), elderly (65+), never married, and with lower education were associated with increased odds of diabetes. After adjusting for others factors, the PC 1 showed marginal association with diabetes (OR=0.84, 95% CI=0.70-1.01); while PC 2 and PC 3 revealed significant associations with diabetes (OR=0.73, 95% CI=0.61-0.86 and OR=0.85, 95% CI=0.74-0.99, respectively). In conclusion, PCA can be used to reduce the indicators in complex survey data. The first 3 PCs of nutrition factors and physical activities were associated with diabetes. Promotion of health food and physical activities should be encouraged to help decrease the prevalence of diabetes.

show abstract

A meta-analysis of passive smoking and risk of developing Type 2 Diabetes Mellitus

Cited by 58 publications

References 16 publications

Undiagnosed diabetes mellitus and related factors in East Gojjam (NW Ethiopia) in 2016: a community-based study

Undiagnosed diabetes mellitus and related factors in East Gojjam (NW Ethiopia) in 2016: a community-based study

Relation of active, passive, and quitting smoking with incident type 2 diabetes: a systematic review and meta-analysis

Principal Component Regression Analysis of Nutrition Factors and Physical Activities with Diabetes

Contact Info

Product

Resources

About