The Joint Effects of Smoking and Alcohol Drinking on Lipid-Related Indices among Chinese Males-Comparing Exercise and Non-Exercise Groups

Serum zinc levels and body composition variability as trajectory for hyperlipidemic and dyslipidemic effect among welders exposed to welding fumes and smoking: A biomarker for cardiovascular health

Welding is a common method for joining metals by heating them to the welding temperature. Exposure to welding fumes has a serious effect on the health of welders. This study examined serum zinc variability and body composition as route for hyperlipidemia and dyslipidemia in welders exposed to welding fumes and smoking, exploring the possibilities for the risk of possible cardiovascular disease. The experimental case control design was adopted in the study. Forty apparently healthy adult males were randomly selected comprising of twenty control group (non-smokers and smokers without welding experience) and twenty experimental group (non-smokers and smokers with welding experience) welders. Data obtained were represented as Mean ± SEM while comparison of means across group was done by one-way ANOVA followed by Tukey's multiple comparison for post hoc test at p-value < 0.05 level of significance using Graph Pad prism version 8. The data obtained showed that the body mass index (BMI) of smokers (non-welders and welders) were slightly reduced while that of non-smoking welders was increased compared to the control. The serum zinc level increased among the smoking welders, while the smoking non-welders and non-smoking welders decreased when compared to the control group (p < 0.05). Exposure to welding fumes has been shown to increase total cholesterol levels compared to the control. Weld fumes significantly (p < 0.05) increased high-density lipoproteins (HDL) levels among smoking non-welders compared to the control group, while, HDL was reduced in non-smoking welders and smoking welders, respectively (p < 0.05). Triglyceride levels significantly (p < 0.05) increased in all experimental groups compared to control levels (p < 0.05). Exposure to welding fumes and smoking caused significant changes in serum zinc, HDL and triglycerides levels with implications for the formation of plaques around the arteries interfering with the effective flow of blood through the vascular system, with implications of hyperlipidemia and dyslipidemia. This study recommends that further studies should be done using biomarkers from urine or toe nails.

Diet quality in association to lipidaemic profile in adults of families at high-risk for type 2 diabetes in Europe: The Feel4Diabetes study

BACKGROUND AND AIMS

The role of diet in blood lipids is scarcely investigated in adults at risk of Type 2 Diabetes Mellitus (T2DM) and even less studied regarding their socioeconomic status (SES). This study aimed to investigate the associations of diet quality with blood lipids in adults from families at high-risk for developing T2DM from six European countries, considering their SES.

METHODS AND RESULTS

In total 2049 adults (67% women) from relatively low-SES regions and high T2DM risk families were enrolled. Dietary habits, sedentary behaviour and sociodemographic characteristics were assessed using standardised questionnaires. The associations of tertiles of healthy diet score (HDS) with blood lipids were tested by univariate analysis of variance (UNIANOVA). HDL-Cholesterol (HDL-C) was positively (B 1.54 95%CI 0.08 to 2.99) and LDL-Cholesterol (LDL-C) (B -4.15 95%CI -7.82 to -0.48), ratio of total cholesterol to HDL-C (B -0.24 95%CI -0.37 to -0.10), ratio of LDL-C to HDL-C (B -0.18 95%CI -0.28 to -0.08) and Atherogenic Index of Plasma (B -0.03 95%CI -0.06 to 0.00) inversely associated with the highest tertile of diet score compared to the lowest tertile independently of age, sex, Body Mass Index, total screen time and smoking. In sub-analysis of education (<14 and ≥ 14 years of education), these findings were only significant in the high-SES group.

CONCLUSION

While diet quality was poorer in the low-SES group, an association between diet quality and lipidemic profile was not found, as increased central obesity and smoking prevalence might have confounded this association. These findings indicate the need for tailor-made interventions, guided by the specific risk factors identified per population sub groups.

Joint effects of self-reported sleep and modifiable physical activity on risk of dyslipidaemia in women aged 45-55 years: a cross-sectional study

OBJECTIVES

Modifiable physical activity (PA) plays an important role in dyslipidaemia risk in middle-aged women with sleep problems, especially perimenopausal women. We aimed to explore the joint effects of sleep and PA on the risk of dyslipidaemia in women aged 45-55 years, and the extent to which PA moderated the effect of sleep on the risk of dyslipidaemia.

DESIGN

A cross-sectional study.

SETTING

This study was based on the survey of Chronic Disease and Nutrition Monitoring in Adults in Inner Mongolia in 2015.

PARTICIPANTS

721 women aged 45-55 years were included.

OUTCOME MEASUREMENT

PA was measured by the Global Physical Activity Questionnaire. Sleep was measured by questionnaire formulated by the Chinese Center for Disease Control and Prevention. Multivariate logistic regression analyses were performed to determine the joint effects of sleep and PA on dyslipidaemia risk. OR and 95% CI were reported.

RESULTS

Among all participants, 60.6% had sleep problems, 29.0% had low PA and 41.1% had dyslipidaemia. Women with sleep problems had higher dyslipidaemia risk than women without sleep problems, irrespective of low, moderate or high PA, with OR (95% CI) of 4.24 (2.40 to 7.49), 3.14 (1.80 to 5.49) and 2.04 (1.20 to 3.48), respectively. PA could not completely attenuate the negative association between sleep and dyslipidaemia risk. With PA increased from low to high, the OR of dyslipidaemia decreased by 2.20. Women with sleep problems and low PA had higher risks of high total cholesterol, high triglyceride, low high-density lipoprotein cholesterol and high low-density lipoprotein cholesterol than women without sleep problems and high PA, with OR (95% CI) of 2.51 (1.18 to 5.35), 2.42 (1.23 to 4.74), 2.88 (1.44 to 5.74) and 2.52 (1.12 to 5.70), respectively.

CONCLUSIONS

Among women aged 45-55 years, the joint effects of self-reported sleep and PA on dyslipidaemia risk were more marked for sleep than for PA. Modifiable PA is a widely accessible and effective intervention to reduce the dyslipidaemia risk in women with sleep problems, particularly among perimenopausal women.

Four-Way Decomposition of Effect of Alcohol Consumption and Body Mass Index on Lipid Profile

Background: Both obesity and alcohol consumption are strongly associated with dyslipidemia; however, it remains unclear whether their joint effect on lipid profiles is through mediation, interaction, or a combination of the two. Methods: In total, 9849 subjects were selected from the 2009 panel of China Health and Nutrition Survey (CHNS). A four-way decomposition method was used to validate the pathways of drinking and body mass index (BMI) on lipids (total cholesterol, TC; triglyceride, TG; low-density lipoprotein cholesterol, LDL-C; high-density lipoprotein cholesterol, HDL-C; apolipoprotein A, APO-A; and apolipoprotein B, APO-B). Results: According to four-way decomposition, the total effects of drinking on lipids were found to be statistically significant, except for LDL-C. The components due to reference interaction were 0.63, 0.48, 0.60, −0.39, −0.30, and 0.20 for TC, TG, LDL-C, HDL-C, APO-A and APO-B, respectively (p < 0.05 for all). The effect size of pure indirect effect and mediated interaction were 0.001~0.006 (p > 0.05 for all). Further, linear regression models were used to examine the effect of BMI on lipid profiles in drinkers and non-drinkers. The associations of BMI and lipids were higher in all drinkers than in non-drinkers (0.069 versus 0.048 for TC, 0.079 versus 0.059 for TG, 0.057 versus 0.037 for LDL-C, −0.045 versus −0.029 for HDL-C, −0.024 versus −0.011 for APO-A and 0.026 versus 0.019 for APO-B, p interaction <0.05 for all). Conclusions: The joint effect of alcohol consumption and obesity on lipid profiles is through interaction rather than mediation. Alcohol consumption amplifies the harmful effect of BMI on lipid profiles. Greater attention should be paid to lipid health and cardiovascular risk in obese individuals regarding alcohol consumption. For obese individuals, we do not recommend alcohol consumption.

Effect of cigarette smoking on smoking biomarkers, blood pressure and blood lipid levels among Sri Lankan male smokers

Study purpose

The aim of this study was to determine the fractional exhaled nitric oxide (FeNO) levels, exhaled breath carbon monoxide (eCO) levels, blood pressure, blood lipid levels between smokers and non-smokers and to determine the association of smoking intensity with the above parameters.

Methods

This descriptive study was conducted in selected periurban areas of the Colombo District, Sri Lanka. Adult male current tobacco smokers (n=360), aged between 21 and 60 years were studied and compared with anthropometrically matched male non-smokers (n=180). Data were collected by interviewer-administered questionnaire, clinical assessment and measurement of FeNO by FENO monitor and eCO bySmokerlyser.

Results

Smokers had significantly lower mean FeNO levels and higher mean eCO values compared with non-smokers. Presentation of palpitations was higher among the smokers and a significantly positive correlation was identified between palpitations and eCO levels. There was a significantly positive correlation between the systolic blood pressure of smokers with the duration of smoking (DS), Brinkman Index (BI), Body Mass Index (BMI) and there was a significantly negative correlation with FeNO levels. The mean arterial pressure was positively correlated with the DS, BI and BMI. There was a significantly negative correlation between FeNO and the number of cigarettes smoked per day, DS and BI of smokers. Significantly higher total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), very LDL-C, TC: HDL ratio and low high density lipoprotein cholesterol (HDL-C) level was observed among smokers compared with the non-smokers.

Conclusions

Tobacco smoking was found to impact blood pressure and serum lipid levels thus enhancing the cardiovascular risk among smokers. The levels of eCO and FeNO are useful biomarkers for determining the intensity of smoking. The results indicate the necessity for urgent measures to stop cigarette smoking in Sri Lanka.

Predictors of the Prevalence of Dyslipidemia and Influencing Factors for Young Health Examination Cohort: A Cross-Sectional Survey

Objectives: The objective of this study was to estimate the prevalence of dyslipidemia and associated influencing factors in young adults in the southeastern coastal area of China. Methods: This study adopted a cross-sectional survey and included 7,859 young people who underwent examinations at three hospitals in Wenzhou, Zhejiang Province, China. All subjects completed a questionnaire in the form of face-to-face interviews and underwent anthropometric measurements and biochemical tests. The continuous data are presented as the means ± standard deviations and were compared using Student's t-tests. The categorical variables are presented as proportions. The influencing factors associated with dyslipidemia were evaluated through a multivariate logistic regression. Results: The prevalence of dyslipidemia among young adults aged 18-45 years in the southeastern coast of China was high with 7.1, 15.0, 22.9, and 4.0% for high-total cholesterol (TC), high-triglyceride (TG), low-high-density lipoprotein cholesterol (HDL-C), and high-low-density lipoprotein cholesterol (LDL-C). Among those with dyslipidemia, a statistically significant difference in sex was observed, and all types of dyslipidemia were associated with smoking and alcohol consumption. However, those with high-TG, high-LDL, and low-HDL levels did not significantly differ in education level or occupation. The presence of dyslipidemia was significantly associated with increased age, the male sex (OR: 1.85, 95% CI: 1.39-2.21), smoking (OR: 2.02, 95% CI: 1.98-2.13), alcohol consumption (OR: 1.33, 95% CI: 1.16-1.63), overweight or obesity (OR: 2.01, 95% CI: 1.79-2.41), and intellectual work (OR: 1.36, 95% CI: 1.11-1.72). Conclusion: The prevalence of dyslipidemia among young adults aged 18-45 years in the southeastern coast of China was high. To prevent dyslipidemia at an early age, it is essential to conduct effective intervention programs targeting risk factors and to implement routine screening programs.