The Association Between Passive Smoking and Type 2 Diabetes

Global trends in deaths and disability-adjusted life years of diabetes attributable to second-hand smoke and the association with smoke-free policies

OBJECTIVES

The diabetic burden attributable to second-hand smoke (SHS) is a global public health challenge. We sought to explore the diabetic burden attributable to SHS by age, sex, and socioeconomic status during 1990-2019 and to evaluate the health benefit of smoke-free policies on this burden.

STUDY DESIGN

Cross-sectional study.

METHODS

The diabetic burden attributable to SHS was extracted from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 dataset. Country-level smoke-free policies were obtained from the World Health Organization Global Health Observatory. The deaths or disability-adjusted life years (DALYs) were quantified, and the average annual percentage changes were calculated. Hierarchical linear mixed models were applied to evaluate the health effects.

RESULTS

From 1990 to 2019, the absolute number of global deaths and DALYs of diabetes attributable to SHS has doubled, and the age-standardised rate has significantly increased. The disease burden was higher in females than in males and increased with increasing age. The SHS-related diabetic burden varied across regions and countries. Age-standardised death or DALY rates first increased and then decreased with increased Socio-demographic Index (SDI), peaking in the 0.60-0.70 range. In low to low-middle, and middle to high-middle SDI countries, SHS-related diabetic deaths and DALYs were significantly lower in countries with more than 3 smoke-free public places than in countries with 0-2 smoke-free public places.

CONCLUSIONS

More attention should be paid to females and the elderly, who bear a heavy SHS-related diabetic burden. Banning smoking in public places was associated with reduced burden of SHS-attributable diabetes, especially in low to middle social development countries.

Health effects associated with exposure to secondhand smoke: a Burden of Proof study

Despite a gradual decline in smoking rates over time, exposure to secondhand smoke (SHS) continues to cause harm to nonsmokers, who are disproportionately children and women living in low- and middle-income countries. We comprehensively reviewed the literature published by July 2022 concerning the adverse impacts of SHS exposure on nine health outcomes. Following, we quantified each exposure-response association accounting for various sources of uncertainty and evaluated the strength of the evidence supporting our analyses using the Burden of Proof Risk Function methodology. We found all nine health outcomes to be associated with SHS exposure. We conservatively estimated that SHS increases the risk of ischemic heart disease, stroke, type 2 diabetes and lung cancer by at least around 8%, 5%, 1% and 1%, respectively, with the evidence supporting these harmful associations rated as weak (two stars). The evidence supporting the harmful associations between SHS and otitis media, asthma, lower respiratory infections, breast cancer and chronic obstructive pulmonary disease was weaker (one star). Despite the weak underlying evidence for these associations, our results reinforce the harmful effects of SHS on health and the need to prioritize advancing efforts to reduce active and passive smoking through a combination of public health policies and education initiatives.

Evaluation of the Relationship Between Smoking and Insulin Resistance: A Case-Control Study

Introduction: In recent years, there has been a surge in research focusing on the link between smoking and insulin resistance in the context of obesity and diabetes. In this study, our objective was to investigate the relationship between smoking and insulin resistance.

Materials and Methods: This is a case-control study. The case and control groups were formed using the hospital patient information database and clinically randomized using data obtained, including age, gender, height, and weight. The case group for this study consisted of smokers, whereas the control group consisted of non-smokers. Chi-square tests were used to compare numbers and rates, and independent sample t-tests were used for the averages. Binary logistic regression analysis was performed between the case and control groups.

Results: According to logistic regression analysis, the odds ratio for non-smokers was 0.59 (0.31-1.14). The risk of insulin resistance is decreased by 41% non-significantly in non-smokers. The odds ratio for age was 1.03 (1.01-1.05). When the age variable increases by one unit, the risk of insulin resistance increase by 1.03 times.

Conclusion: Our study found no significant relationship between smoking and insulin resistance in healthy individuals. The relationship between smoking and insulin resistance, as reported in the scientific literature, may be suggestive of an association in which smoking exacerbates insulin resistance as a result of other contributing factors rather than serving as a direct causal factor. Further studies are warranted to elucidate the potential mechanisms underlying this association fully.

Prevalence of diabetes in the USA from the perspective of demographic characteristics, physical indicators and living habits based on NHANES 2009-2018

OBJECTIVE

To determine differences in DM in the U.S. population according to demographic characteristics, physical indicators and living habits.

METHODS

23 546 participants in the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) who were 20 year of age or older and not pregnant. All analyses used weighted samples and considered the stratification and clustering of the design. Specific indicators include length of leg (cm), BMI (kg/cm²), TCHOL (mg/dL), fasting plasma glucose (mg/dL) and comparison of means and the proportion of participants with DM.

RESULTS

The prevalence of DM in the USA has been rising modestly in the past decade, and were consistent and robust for the observed differences in age, sex, and ethnicity. Compared with white participants, black participants and Mexican-American were both more likely (P<0.001) to have diabetes: 14.6% (CI, 13.6% to 15.6%) among black participants, 10.6% (CI, 9.9% to 11.3%) among white participants, and 13.5% (CI, 11.9% to 15.2%) among Mexican-American participants. The prevalence of diabetes is increasing with age, males peaked around the 60s, and women around the 70s. The overall mean leg length and TCHOL was lower in diabetics than in non-diabetics (1.07 cm, 18.67 mg/dL, respectively), while mean BMI were higher in diabetics than in non-diabetics (4.27 kg/cm2). DM had the greatest effect on decline of TCHOL in white participants (23.6 mg/dL), less of an effect in black participants (9.67 mg/dL), and the least effect in Mexican-American participants (8.25 mg/dL). Notably, smoking had great effect on percent increment of DM in whites (0.2%), and have little effect on black and Mexican-Americans.

CONCLUSIONS

DM is more common in the general population than might be clinically recognized, and the prevalence of DM was associated to varying degrees with many indicators of demographic characteristics, physical indicators, and living habits. These indicators should be linked with medical resource allocation and scientific treatment methods to comprehensively implement the treatment of DM.

Type-2 Diabetes Mellitus (T2DM): Spatial-temporal Patterns of Incidence, Mortality and Attributable Risk Factors from 1990 to 2019 among 21 World Regions

PURPOSE

Type-2 diabetes Mellitus (T2DM) is one of the leading causes of death and disability worldwide. This study examines temporal patterns of the global, regional, and national burden of T2DM in the last three decades.

DATA AND METHODS

The estimates of age, sex and location-wise incident cases, deaths, prevalent cases, and disability-adjusted-life-years (DALYs) and risk factors for 21 regions and 204 countries are retrieved from the Global Burden of Disease 2019 study from 1990 to 2019. Socio-demographic index (SDI) is used as the indicator of the development status of countries, and quadratic regression is employed to examine the relationship between country-level age-standardized rates and SDI.

RESULTS

Globally, incident cases of T2DM more than doubled from 8.4 million[95% uncertainty interval, 7.8-9.1 million] in 1990 to 21.7 million[20.0-23.5 million] in 2019, and deaths more than doubled from 606,407[573,069-637,508] to 1.5 million[1.4-1.6 million] between 1990 and 2019. Global T2DM prevalence increased from 148.4 million[135.5-162.6 million] in 1990 to 437.9 million[402.0-477.0 million] in 2019. In 2019, global age-standardized prevalence rate stood at 5282.8/100,000[4853.6-5752.1], varying from 2174.5/100,000[1924.3-2470.5] in Mongolia to 19876.8/100,000[18211.1-21795.3] in American Samoa. SDI exhibited inverted-U shaped relationship with country-level age-standardised rates. Globally, high body-mass-index (51.9%), ambient particulate matter pollution (13.6%), smoking (9.9%) and secondhand smoke (8.7%) were the major contributing risk factors towards T2DM DALYs in 2019.

CONCLUSION

With ubiquitously rising prevalent cases globally, particularly in low and middle-income countries and regions, T2DM requires immediate attention and targeted policy response worldwide centered on lifestyle interventions (e.g., physical activity, smoking, diet, and obesity), air pollution control and cost-effective timely treatment.

Risk of Gestational Diabetes Due to Maternal and Partner Smoking

Pregnant women are among the most vulnerable to environmental exposure to tobacco smoke (EET); which has been linked to problems in the mothers’ health; one of the most frequent is gestational diabetes (GD). For this reason, there are specific interventions and prevention strategies designed to reduce this exposure risk. However, currently, they are mostly aimed only at aiding the pregnant women with smoking cessation during pregnancy and do not assess or address the risk from passive exposure due to partner smoking. The aim of this work is to study the exposure to EET of pregnant women considering active and passive smoking and to evaluate its effect on the development of GD. This is an observational case-control study within a retrospective cohort of pregnant women. Information on smoking habits was obtained from both personal interviews and recorded medical history. In total, 16.2% of mothers and 28.3% of partners declared having been active smokers during pregnancy; 36.5% of the women presented EET during pregnancy when both active and passive smoking were considered. After adjustments, the association with the EET and GD of the mother was (aOR 1.10 95% CI: 0.64–1.92); for the EET of the partner, it was (aOR 1.66 95% CI: 1.01–2.77); for both partners, it was (aOR 1.82 95% CI: 1.15–2.89), adjusted by the mother’s age and body mass index. There is a lack of education regarding the effects of passive exposure to tobacco smoke. It is essential that pregnant women and their partners are educated on the risks of active and passive smoking; this could improve the effectiveness of other GD prevention strategies.

Burden of disease from second-hand tobacco smoke exposure at home among adults from European Union countries in 2017: an analysis using a review of recent meta-analyses

Smoke-free legislation reduced second-hand smoke (SHS) exposure in public places, and indirectly promoted private smoke-free settings. Nevertheless, a large proportion of adults is still exposed to SHS at home. The aim of this paper is to quantify the burden of disease due to home SHS exposure among adults in the 28-European Union (EU) countries for year 2017. The burdens by gender from lung cancer, chronic obstructive pulmonary disease (COPD), breast cancer, ischemic heart disease (IHD), stroke, asthma, and diabetes were estimated in an original research analysis using the comparative risk assessment method. Relative risks of death/diseases by gender for adults exposed to SHS at home compared to not exposed ones were estimated updating existing meta-analyses. Prevalence of home SHS exposure by gender was estimated using a multiple imputation procedure based on Eurobarometer surveys. Data on mortality and disability adjusted life years (DALYs) were obtained from the Global Burden of Disease, Injuries and Risk Factors Study. In 2017, 526,000 DALYs (0.36% of total DALYs) and 24,000 deaths (0.46% of total deaths) were attributable to home SHS exposure in the 28-EU countries, mainly from COPD and IHD. South-Eastern EU countries showed the highest burden, with proportion of DALYs/deaths attributable to SHS exposure on total higher than 0.50%/0.70%, whereas northern EU-countries showed the lowest burden, with proportions of DALYs/deaths lower than 0.25%/0.34%. The burden from SHS exposure is still significant in EU countries. More could be done to raise awareness of the health risks associated with SHS exposure at home.

Effects of passive smoking and its duration on the prevalence of prediabetes and type 2 diabetes mellitus in Chinese women

Several studies have shown that active smoking is a risk factor for type 2 diabetes mellitus (T2DM). However, the effects of passive smoking on T2DM remains unknown. In this study, we investigated the effects of passive smoking and its duration on the prevalence of prediabetes and T2DM. According to passive smoking status, participants were divided into Group A (passive smokers) and Group B (controls). Furthermore, Group A was divided into three subgroups according to the duration of passive smoking: Group A1 (≤10 years), Group A2 (10–20 years), and Group A3 (>20 years). We found that the prevalence of impaired glucose tolerance (IGT) in Group A (26.6%), Group A2 (28%), and Group A3 (37.8%) was significantly higher than that in Group B (19.6%), and the prevalence gradually increased with an increase in the duration of passive smoking. Multiple logistic regression analysis showed that passive smoking for >10 years was a risk factor for impaired fasting glucose (IFG), IGT, and T2DM. Therefore, passive smoking not only increases the prevalence of IGT in a time-dependent manner, but also a risk factor for IFG, IGT, and T2DM when its duration is over 10 years.

Common risk factors for major noncommunicable disease, a systematic overview of reviews and commentary: the implied potential for targeted risk reduction

Noncommunicable disease now contributes to the World Health Organization top 10 causes of death in low-, middle- and high-income countries. Particular examples include stroke, coronary heart disease, dementia and certain cancers. Research linking clinical and lifestyle risk factors to increased risk of noncommunicable disease is now well established with examples of confirmed risk factors, including smoking, physical inactivity, obesity and hypertension. However, despite a need to target our resources to achieve risk reduction, relatively little work has examined the overlap between the risk factors for these main noncommunicable diseases. Our high-level review draws together the evidence in this area. Using a systematic overview of reviews, we demonstrate the likely commonality of established risk factors having an impact on multiple noncommunicable disease outcomes. For example, systematic reviews of the evidence on physical inactivity and poor diet found each to be associated with increased risk of cancers, coronary heart disease, stroke, diabetes mellitus and dementia. We highlight the potential for targeted risk reduction to simultaneously impact multiple noncommunicable disease areas. These relationships now need to be further quantified to allow the most effective development of public health interventions in this area.

Secondhand smoke, obesity, and risk of type II diabetes among California teachers

PURPOSE

To examine if secondhand smoke (SHS) is associated with elevated risk of type II diabetes among California teachers. We also aim to determine if overall and central obesity are mediators or effect modifiers of this association.

METHODS

Using data from the California Teachers Study, conducted in 1995-2013 in California public schools, we obtained information on SHS exposure among 39,887 lifetime nonsmokers. The association between SHS and incident diabetes after 17 years of follow-up was assessed using Cox regression models. The mediation and modification effects of BMI and waist circumference on this association were tested.

RESULTS

At baseline, 70.2% of the nonsmokers reported exposure to SHS. Higher intensity, duration, and intensity-years of exposure to SHS were associated with higher multivariate adjusted risk of incident diabetes in a dose-response manner (hazard ratio = 1.28; 95% confidence interval, 1.11-1.48 for highest quartile vs. lowest quartile of exposure; P = .001 for trend). Participant's waist circumference (measured 2 years after baseline) could explain greater than 50% of the association between SHS and diabetes.

CONCLUSIONS

SHS exposure is associated with increased risk of type II diabetes among nonsmokers of California teachers with obesity being a potentially important mediator but not an effect modifier for this association.

Prevalence and risk factors of type 2 diabetes in insomnia sufferers: a study on 1311 individuals referred for sleep examinations

BACKGROUND

Several studies have investigated the particular relationship between insomnia and type 2 diabetes. However, few studies have investigated the prevalence and risk factors for type 2 diabetes in insomnia sufferers. The aim of this study was to examine the prevalence and risk factors of type 2 diabetes in a large sample of insomnia sufferers.

METHODS

Data from 1311 insomnia sufferers recruited from the research database of the Erasme Hospital sleep laboratory were analyzed. Only individuals with a diagnosis of type 2 diabetes according to the diagnostic criteria of the American Diabetes Association at admission were included in the diabetes group. Logistic regression analyses were conducted to examine clinical and demographic risk factors of type 2 diabetes in insomnia sufferers.

RESULTS

The prevalence of type 2 diabetes in insomnia sufferers is 21.13%. Multivariate logistic regression analysis revealed that significant risk factors of type 2 diabetes in insomnia sufferers were as follows: being male, Z-drugs use, high blood pressure, hypertriglyceridemia, alcohol consumption of ≥4 units/day, BMI ≥25 & <30 kg/m², BMI ≥30 kg/m², age ≥50 years, C-reactive protein ≥4.5 mg/L, a sleep duration of <6.5 h, apnea-hypopnea index ≥15/hour, periodic limb movements index ≥26/hour, and severe complaints of early morning awakening.

CONCLUSION

Type 2 diabetes is a common pathology in insomnia sufferers. In this subpopulation, most of the risk factors for type 2 diabetes are reversible, which justifies better prevention and management of this pathology in order to avoid its negative consequences.

Diabetes and Overall Survival among Breast Cancer Patients in the U.S. Military Health System

Background: Although research suggests that type II diabetes mellitus (DM-2) is associated with overall and breast cancer-specific decreased survival, most prior studies of breast cancer survival investigated the effect of preexisting DM-2 without assessing the effect of DM-2 diagnosed at or after breast cancer diagnosis. This study examined the relationship between DM-2 diagnosed before and after breast cancer diagnosis and overall survival.Methods: This study uses linked Department of Defense cancer registry and medical claims data from 9,398 women diagnosed with breast cancer between 1998 and 2007. Cox proportional hazards models were used to assess the association between DM-2 and overall survival.Results: Our analyses showed that women with DM-2 diagnosed before breast cancer diagnosis tended to have a higher risk of mortality compared with women without diabetes [HR = 1.17; 95% confidence interval (CI), 0.95-1.44] after adjustment for potential confounders. Similarly, patients diagnosed with DM-2 at or after breast cancer diagnosis had increased mortality compared with women without DM-2 (HR = 1.39; 95% CI, 1.16-1.66). The similar tendency was also observed among most subgroups when results were stratified by race, menopausal status, obesity, tumor hormone receptor status, and stage.Conclusions: Using data from a health system that provides universal health care to its beneficiaries, this study showed an increased risk of death associated with DM-2, regardless of whether it was diagnosed before or at/after breast cancer diagnosis.Impact: These results suggest the potential effects of factors independent of the timing of DM-2 clinical diagnosis on the association of DM-2 with overall survival. Cancer Epidemiol Biomarkers Prev; 27(1); 50-57. ©2017 AACR.

Passive smoking as an independent risk factor for gestational diabetes that synergizes with prepregnancy obesity in urban Chinese women

There are high-priority public health and legislative efforts around the world to reduce smoking and to reduce the spaces where smoking is allowable. These efforts are aimed at minimizing not only the adverse health effects of active smoking but also the adverse health effects of passive cigarette smoke exposure. While many cultures and societies make protection of a pregnant woman and her about-to-be-born-newborn a priority, the importance of protecting them from passive smoking that is prevalent in many modern societies has not been reported. The article by Leng et al, "Passive smoking increased risk of gestational diabetes mellitus independently and synergistically with prepregnancy obesity in Tianjin, China," newly published in Diabetes Metabolism Research and Reviews, provides evidence that passive smoke inhalation during pregnancy makes gestational diabetes more likely, bringing with it negative health consequences for the mother and her baby. This study will hopefully add support to public health officials' efforts to curb cigarette use, especially in public domains.

Association of Education and Smoking Status on Risk of Diabetes Mellitus: A Population-Based Nationwide Cross-Sectional Study

Background: Exposure to smoke, including environmental tobacco smoke (ETS), is a well-known risk factor for diabetes. Low socioeconomic status, especially lack of education, is also a risk factor for diabetes. Therefore, we assessed the association of demographic, socioeconomic, clinical, and behavior risk factor-related variables and smoking status, including ETS exposure, with the prevalence of diabetes. Methods: Data were from the 2007–2013 Korea National Health and Nutritional Evaluation Survey (KNHANES). Multivariable logistic regression examined associations between various lifestyle and health factors and the prevalence of diabetes while controlling for potential confounding variables. Subgroup analysis was performed according to smoking status to determine factors associated with diabetes. Results: Of 19,303 individuals analyzed, 1325 (11.4%) had diabetes. Greater average age, male sex, lower educational level, unemployment, and coexisting health problems were significantly associated with diabetes. Individuals with only elementary, middle, or high school level education had significantly greater odds ratios (p < 0.05) compared to college graduates; smokers and nonsmokers exposed to ETS had significantly greater OR (p < 0.05) than nonsmokers unexposed to ETS. Subgroup analysis of diabetics according to smoking status revealed significant associations (p < 0.05) for diabetic nonsmokers exposed to ETS with female sex, single status, elementary level education, urban residence, National Health Insurance (NHI), hypertension, a lack of alcohol intake, and a lack of moderate physical activity. For diabetic smokers, there were significant associations (p < 0.05) with elementary education, urban residence, a lack of moderate physical activity, a lack of alcohol intake, and NHI. Conclusions: The results suggested that smoking status, as well as ETS exposure, was associated with a higher prevalence of diabetes, especially in populations with less education. Thus, we should direct efforts for controlling diabetes toward individuals with lower levels of education and those who are smokers and nonsmokers exposed to ETS.

Passive smoking increased risk of gestational diabetes mellitus independently and synergistically with prepregnancy obesity in Tianjin, China

BACKGROUND

Passive smoking increased type 2 diabetes mellitus risk, but it is uncertain whether it also increased gestational diabetes mellitus (GDM) risk. We aimed to examine the association of passive smoking during pregnancy and its interaction with maternal obesity for GDM.

METHODS

From 2010 to 2012, 12 786 Chinese women underwent a 50-g 1-hour glucose challenge test at 24 to 28 weeks of gestation and further underwent a 75-g 2-hour oral glucose tolerance test if the glucose challenge test result was ≥7.8 mmol/L. GDM was defined by the International Association of Diabetes and Pregnancy Study Group's cut points. Self-reported passive smoking during pregnancy was collected by a questionnaire. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs). Additive interaction between maternal obesity and passive smoking was estimated using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). Significant RERI > 0, AP > 0, or S > 1 indicated additive interaction.

RESULTS

A total of 8331 women (65.2%) were exposed to passive smoking during pregnancy. More women exposed to passive smoking developed GDM than nonexposed women (7.8% versus 6.3%, P = 0.002) with an adjusted OR of 1.29 (95%CI, 1.11 to 1.50). Compared with nonobesity and nonpassive smoking, prepregnancy obesity and passive smoking was associated with GDM risk with an adjusted OR of 3.09 (95%CI, 2.38-4.02) with significant additive interaction (P < .05 for RERI and AP).

CONCLUSIONS

Passive smoking during pregnancy increased GDM risk in Chinese women independently and synergistically with prepregnancy obesity.

The Negative Relationship between Bilirubin Level and Diabetic Retinopathy: A Meta-Analysis

Objectives

Findings on the relationship between total bilirubin level (TBL) and diabetic retinopathy (DR) are inconsistent. Thus, we carried out a meta-analysis to investigate the relationship between TBL and the risk of DR.

Methods

Relevant studies were selected from six databases up to 31 May 2016 using a search strategy. The relevant data were extracted from the included studies according to the inclusion and exclusion criteria, and the mean value with standard errors or odds ratio (OR) with 95% confidence intervals (CIs) were calculated. We compared TBL in patients with DR with that in patients with diabetes but without retinopathy (NDR), and analyzed the dose-response relationship between TBL and the risk of DR.

Results

Twenty-four studies were selected in this meta-analysis. Twenty studies were included to calculate the pooled SMD, and the results showed that TBL in the DR group was lower than that in the NDR group (SMD: –0.52, 95% CI: –0.67, –0.38). Nine studies were included to calculate the pooled ORs, and the results showed that there was a significant negative relationship between TBL and the risk of DR (OR: 0.19, 95% CI: 0.14, 0.25). Six studies were included to investigate the dose-response relationship between TBL and the risk of DR, and we found a nonlinear relationship between TBL and the risk of DR. The results of our meta-analysis were found to be reliable using subgroup and sensitivity analyses.

Conclusions

The results of our meta-analysis indicate that higher TBL may be protective against DR in subjects with diabetes, and TBL could be used as a biomarker to predict the risk of DR.

Association of Atmospheric Particulate Matter and Ozone with Gestational Diabetes Mellitus

BACKGROUND

Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, evidence of the association is very limited, and no study has estimated the effects of ozone.

OBJECTIVE

Our aim was to determine the association of prenatal exposures to particulate matter ≤ 2.5 μm (PM2.5) and ozone (O3) with GDM.

METHODS

We used Florida birth vital statistics records to investigate the association between the risk of GDM and two air pollutants (PM2.5 and O3) among 410,267 women who gave birth in Florida between 2004 and 2005. Individual air pollution exposure was assessed at the woman's home address at time of delivery using the hierarchical Bayesian space-time statistical model. We further estimated associations between air pollution exposures during different trimesters and GDM.

RESULTS

After controlling for nine covariates, we observed increased odds of GDM with per 5-μg/m3 increase in PM2.5 (ORTrimester1 = 1.16; 95% CI: 1.11, 1.21; ORTrimester2 = 1.15; 95% CI: 1.10, 1.20; ORPregnancy = 1.20; 95% CI: 1.13, 1.26) and per 5-ppb increase in O3 (ORTrimester1 = 1.09; 95% CI: 1.07, 1.11; ORTrimester2 = 1.12; 95% CI: 1.10, 1.14; ORPregnancy = 1.18; 95% CI: 1.15, 1.21) during both the first trimester and second trimester as well as the full pregnancy in single-pollutant models. Compared with the single-pollutant model, the ORs for O3 were almost identical in the co-pollutant model. However, the ORs for PM2.5 during the first trimester and the full pregnancy were attenuated, and no association was observed for PM2.5 during the second trimester in the co-pollutant model (OR = 1.02; 95% CI: 0.98, 1.07).

CONCLUSION

This population-based study suggests that exposure to air pollution during pregnancy is associated with increased risk of GDM in Florida, USA.

CITATION

Hu H, Ha S, Henderson BH, Warner TD, Roth J, Kan H, Xu X. 2015. Association of atmospheric particulate matter and ozone with gestational diabetes mellitus. Environ Health Perspect 123:853-859; http://dx.doi.org/10.1289/ehp.1408456.

Prevalence of and Risk Factors for Type 2 Diabetes Mellitus in Vietnam: A Systematic Review

This systematic review examined trends in the prevalence of type 2 diabetes mellitus (T2DM) and identified its risk factors among adults in Vietnam. PubMed, Web of Science, Wiley Online Library, and Scopus databases were searched to identify relevant literature. The search yielded 10 studies, including 2 national surveys and 8 regional investigations. National prevalence estimates of T2DM were 2.7% in 2002 and 5.4% in 2012. The estimates for the northern region were 1.4% in 1994 and 3.7% in 2012 and those for the southern region were 3.8% in 2004, 7.0% in 2008, and 12.4% in 2010. The major determinants of T2DM included older age, urban residence, high levels of body and abdominal fat, physical inactivity, sedentary lifestyle, genetic factors, and hypertension. The prevalence rate by gender was variable in both national and regional studies. There was insufficient information available on some potentially important risk factors such as smoking, dietary intake, income, and educational level. Our review signifies a rapidly growing prevalence of T2DM in Vietnam and suggests that extra effort is required to prevent and control this disease.