Association of aldehydes exposure with obesity in adults.

Environmental pollutants may play a role in the aetiology of obesity beyond conventional factors. The associations between environmental exposure to aldehydes and obesity remain unclear. The objective of this study is to determine whether aldehyde exposure is associated with obesity in adults. We analysed data from 1977 participants in the National Health and Nutrition Examination Survey (NHANES) 2013-2014 aged ≥ 18 years. Obesity was assessed through body mass index (BMI) measurements. Generalized linear regression and restricted cubic spline models were analysed to assess the association between aldehydes and outcomes. After multivariable adjustment, isopentanaldehyde was inversely associated with obesity, while no significant association was observed between any other aldehydes and obesity. Compared with the lowest quartile, the adjusted odds ratio (OR) of obesity with a 95% confidence interval (CI) for the highest quartile was 0.50 (0.35, 0.70) for isopentanaldehyde. Analyses using a restricted cubic spline indicated that the association between isopentanaldehyde and obesity is nonlinear. Threshold effect analysis demonstrated that the inflection point of isopentanaldehyde was 1.26 ng/ml. Each 1-fold increase in isopentanaldehyde exhibited an 18% decrease in the odds of obesity (OR 0.82, 95% CI 0.79-1.09) on the left side of the inflection point and an 81% decrease (OR 0.19, 95% CI 0.08-0.45) on the right side of the inflection point. Similar associations were also observed among isopentanaldehyde and abdominal obesity, BMI, and waist circumference. These cross-sectional results show a nonlinear and inverse association between isopentanaldehyde and obesity.

Association of aldehyde exposure with cardiovascular disease.

The effect of aldehyde exposure on the cardiovascular system remains unclear. The objective of this study was to determine whether aldehyde exposure is associated with the prevalence of cardiovascular disease (CVD). We analyzed associations between aldehydes and CVD using data from 1962 adult participants in the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2014. Multivariable logistic regression and restricted cubic spline models were used to examine the association between aldehydes and CVD. The prevalence of CVD was 10.3%. After adjusting for confounding factors, including age, sex, education level, race, diabetes mellitus, smoking, alcohol use, hypertension, body mass index, the poverty-income ratio, physical activity, energy intake, high-density cholesterol (HDL) and low-density cholesterol (LDL), compared with the lowest quartiles, the odds ratios (ORs) with 95% confidence intervals (CIs) for CVD across the quartiles were 0.52 (0.31, 0.87), 0.73 (0.43, 1.22), and 1.13 (0.68, 1.86) for benzaldehyde and 1.48 (0.87, 2.52), 1.70 (1.01, 2.92), and 2.13 (1.19, 3.86) for isopentanaldehyde. There was no significant association between other aldehydes and CVD. The restricted cubic spline plot showed a J-curve relationship between benzaldehyde and CVD. The inflection point for the curve was found at a benzaldehyde level of 0.98 ng/ml. The ORs (95% CIs) for CVD were 0.51 (0.31, 0.86) and 1.58 (1.15, 2.17) on the left and right sides of the inflection point, respectively. Our results demonstrate a J-curve relationship between benzaldehyde and CVD. Isopentanaldehyde is positively associated with CVD. Further study is warranted to verify this association and to elucidate its underlying mechanisms.

Association of acrylamide and glycidamide haemoglobin adduct levels with diabetes mellitus in the general population.

The frequency and duration of exposure to acrylamide (AA) from the environment and diet are associated with a range of adverse health effects. However, whether long-term AA exposure is related to diabetes mellitus (DM) remains unknown. Data from 3577 adults in the National Health and Nutrition Examination Survey (NHANES) 2005-2006 and 2013-2016 aged ≥ 20 years was analysed. The main analyses applied multivariate logistic regression and restricted cubic spline models to investigate the associations between DM and AA haemoglobin biomarkers, including haemoglobin adducts of acrylamide and glycidamide (HbAA and HbGA), the sum of HbAA and HbGA (HbAA + HbGA), and the ratio of HbGA to HbAA (HbGA/HbAA) levels. After multivariable adjustment, the odds ratios (95% confidence intervals) for DM comparing the highest with the lowest AA haemoglobin biomarker quartiles were 0.71 (0.55, 0.93), 0.92 (0.71, 1.18), 0.80 (0.62, 1.03) and 1.95 (1.51, 2.51) for HbAA, HbGA, HbAA + HbGA and HbGA/HbAA, respectively. The restricted cubic spline model demonstrated that HbAA was linearly and inversely associated with risk of DM (P for trend = 0.013), while HbGA/HbAA was nonlinearly and positively associated with the prevalence of DM (P for trend <0.001). These results support for epidemiological evidence that the HbAA and HbGA/HbAA are significantly associated with DM. Further studies are warranted to infer the causal role of AA exposure in the prevalence of DM.

Cobalt exposure in relation to cardiovascular disease in the United States general population.

Cobalt exposure has adverse health effects on the cardiovascular system in occupational and laboratory studies, but these effects have not been assessed in the general population. We aimed to determine whether serum cobalt levels had relationship with the prevalence of cardiovascular disease (CVD) in the general population. Using data from the National Health and Nutrition Examination Survey (NHANES) (2015-2016), we performed the cross-sectional study. We analyzed the baseline characteristics of 3389 participants (1623 men and 1766 women). Generalized linear models and restricted cubic spline plots curve were undertaken to elucidate the relationship. Stratified subgroup analysis was tested to exclude interaction between different variates and cobalt. Our results showed that the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for CVD prevalence across the quartiles of cobalt were 0.94 (0.67, 1.30), 1.55 (1.15, 2.10), and 1.74 (1.28, 2.35) compared with lowest quartile. The restricted cubic spline curve also suggested nonlinear and positive association between cobalt and CVD (P for nonlinearity = 0.007). In summary, our cross-sectional results verify that higher cobalt levels are associated with a higher prevalence of cardiovascular disease.