Among 10 sociodemographic and lifestyle variables, smoking is strongly associated with biomarkers of acrylamide exposure in a representative sample of the U.S. Population

Reconstructing population exposures to acrylamide from human monitoring data using a pharmacokinetic framework

BACKGROUND

Acrylamide toxicity involves several metabolic pathways. Thus, a panel of blood and urinary biomarkers for the evaluation of acrylamide exposure was deemed appropriate.

OBJECTIVE

The study was designed to evaluate daily acrylamide exposure in US adults via hemoglobin adducts and urinary metabolites using a pharmacokinetic framework.

METHODS

A cohort of 2798 subjects aged 20-79 was selected from the National Health and Nutrition Examination Survey (NHANES, 2013-2016) for analysis. Three acrylamide biomarkers including hemoglobin adducts of acrylamide in blood and two urine metabolites, N-Acetyl-S-(2-carbamoylethyl)cysteine (AAMA) and N-Acetyl-S-(2-carbamoyl-2-hydroxyethyl)-l-cysteine (GAMA) were used to estimate daily acrylamide exposure using validated pharmacokinetic prediction models. Multivariate regression models were also used to examine key factors in determining estimated acrylamide intake.

RESULTS

The estimated daily acrylamide exposure varied across the sampled population. Estimated acrylamide daily exposure was comparable among the three different biomarkers (median: 0.4-0.7 μg/kg/d). Cigarette smoking emerged as the leading contributor to the acquired acrylamide dose. Smokers had the highest estimated acrylamide intake (1.20-1.49 μg/kg/d) followed by passive smokers (0.47-0.61) and non-smokers (0.45-0.59). Several covariates, particularly, body mass index and race/ethnicity, played roles in determining estimated exposures.

DISCUSSION

Estimated daily acrylamide exposures among US adults using multiple acrylamide biomarkers were similar to populations reported elsewhere providing additional support for using the current approach in assessing acrylamide exposure. This analysis assumes that the biomarkers used indicate intake of acrylamide into the body, which is consistent with the substantial known exposures due to diet and smoking. Although this study did not explicitly evaluate background exposure arising from analytical or internal biochemical factors, these findings suggest that the use of multiple biomarkers may reduce uncertainties regarding the ability of any single biomarker to accurately represent actual systemic exposures to the agent. This study also highlights the value of integrating a pharmacokinetic approach into exposure assessments.

Effectiveness and determinants of smoking cessation in the Saudi Arabian Region of Jazan: A cross-sectional study

INTRODUCTION

Smoking cessation has significant health benefits. The purpose of this study is to assess the efficacy and related factors of smoking cessation therapies in the Jazan Region of Saudi Arabia.

METHODS

This is a cross-sectional study that took place at smoking cessation clinics in primary healthcare centers between January 2019 and January 2020.

RESULTS

This study enrolled a total of 103 people. The success rate for quitting smoking was 36% at three months, with a 13% relapse rate at six months. Age (p=0.017), occupation (p=0.046), daily cigarette intake (p=0.015), and number of visits (p=0.001) were all found to be significant determinants of smoking cessation. In the multivariate analysis, only the number of visits increased the likelihood to quit smoking (AOR=0.31; 95% CI: 0.15-0.63). Self-efficacy was cited as the primary reason for quitting smoking by 71% of the participants, whereas family support, smoking cessation therapies, and friends' support were cited as predictive variables by 18%, 10%, and 1% of the participants, respectively.

CONCLUSIONS

Smokers who received the smoking cessation intervention package were three times more likely to succeed in giving up smoking when compared to those who received the routine service. Regular follow-up during smoking cessation interventions significantly enhanced the quit rate. It is recommended that pharmacotherapy strategies and intense therapy performed face-to-face with a cessation counselor be combined to improve the quit rate.

Machine learning prediction of exposure to acrylamide based on modelling of association between dietary exposure and internal biomarkers

The ubiquitous occurrence of acrylamide in various thermal processing food products poses a potential health risk for the public. An accurate exposure assessment is crucial to the risk evaluation of acrylamide. Machine learning emerging as a powerful computational tool for prediction was employed to establish the association between internal exposure and dietary exposure to acrylamide among a Chinese cohort of middle-aged and elderly population (n = 1,272). Five machine learning regression models were constructed and compared to predict the daily dietary acrylamide exposure based on urinary biomarkers including N-acetyl-S-(2-carbamoylethyl)-L-cysteine (AAMA), N-acetyl-S-(2-carbamoylethyl)-L-cysteine-sulfoxide (AAMA-sul), N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine (GAMA), and N-acetyl-S-(1-carbamoyl-2-hydroxyethyl)-L-cysteine (iso-GAMA). Other important covariates such as age, gender, physical activities, and total energy intake were also considered as predictors in the models. Average dietary intake of acrylamide among Chinese elderly participants was 8.9 μg/day, while average urinary contents of AAMA, AAMA-sul, GAMA, and iso-GAMA were 52.2, 19.1, 4.4, and 1.7 nmol/g Ucr (urine creatinine), respectively. Support vector regression (SVR) model showed the best prediction performance with a R of 0.415, followed by light gradient boosting machine (LightGBM) model (R = 0.396), adjusted multiple linear regression (MLR) model (R = 0.378), neural networks (NN) model (R = 0.365), MLR model (R = 0.363), and extreme gradient boosting (XGBoost) model (R = 0.337). The present study firstly correlated dietary exposure with internal exposure to acrylamide among Chinese elderly population, providing an innovative perspective for the exposure assessment of acrylamide.

Associations of Hemoglobin Adducts of Acrylamide and Glycidamide with Prevalent Metabolic Syndrome in a Nationwide Population-Based Study

Environmental and dietary exposures to acrylamide (AA) have been linked with various metabolic-related outcomes, but the results are mixed. However, the association between long-term exposure to AA and the prevalence of metabolic syndrome (MetS) remains unknown. In this study, we aimed to assess the relationship between hemoglobin adducts of AA, biomarkers of internal exposure to AA, and MetS prevalence among a U.S. nationwide population. MetS patients were defined by meeting three or more of the following five characteristics: elevated blood pressure, high fasting glucose, abdominal obesity, hypertriglyceridemia, and lower high-density lipoprotein cholesterol (HDL-C). Multivariate-adjusted logistic regression models and restricted cubic spline models were used to analyze the associations between AA hemoglobin biomarkers and MetS prevalence. A total of 1552 MetS cases were documented. After adjustment for the potential confounders, the odds ratios (95% confidence intervals) of MetS prevalence in the highest quartile of AA hemoglobin biomarkers were 0.60 (0.40-0.89), 1.26 (0.84-1.89), 0.93 (0.71-1.21), and 1.61 (1.18-2.20) for HbAA, HbGA, the sum of HbAA and HbGA (HbAA + HbGA), and the ratio of HbGA to HbAA (HbGA/HbAA), compared with the lowest quartile, respectively. HbAA was significantly and inversely associated with blood pressure, fasting glucose, abdominal obesity, hypertriglyceridemia, and low HDL-C, while the HbGA/HbAA ratio was also positively associated with abdominal obesity, hypertriglyceridemia, and low HDL-C. The restricted cubic spline models revealed a positive relationship between the HbGA/HbAA ratio and the prevalence of MetS, while the HbAA level was inversely associated with MetS prevalence. Our current findings provided epidemiological evidence that HbAA and the HbGA/HbAA ratio were significantly associated with MetS prevalence among general U.S. adults. Further studies should be conducted to examine the association between internal exposure to AA and MetS prevalence.

The Association Between Exposure to Acrylamide and Mortalities of Cardiovascular Disease and All-Cause Among People With Hyperglycemia

Background

Acrylamide is a common environmental volatile organic compound that humans are frequently exposed to in their daily lives. However, whether exposure to acrylamide is associated with long-term survival in patients with hyperglycemia remains largely unknown.

Methods and Results

A total of 3,601 hyperglycemic people were recruited in this study, including 1,247 people with diabetes and 2,354 people with pre-diabetes, who enrolled in the National Health and Nutrition Examination survey (2003–2004, 2005–2006, and 2013–2014). The acrylamide exposure was measured by the serum hemoglobin adduct of acrylamide (HbAA) and glycidamide (HbGA), and the ratio of HbAA and HbGA (HbAA/HbGA) was calculated, which were all categorized into quintiles. The National Death Index was used to identify the participants' death information until 2015. Cox proportional hazards (CPHs) regression models were performed to examine the survival relationship between these biomarkers and mortality. During the 28,652 person-year follow-up, 268 deaths due to the cardiovascular disease (CVD) were documented. After adjustment for multiple confounders, compared with participants in the lowest quintile of HbAA/HbGA, the participants in the highest quintile were more likely to die due to CVD (hazard ratio [HR] = 1.61, 95% CI: 1.09–2.39) and all-cause (HR = 1.59, 95% CI: 1.25–2.01). Moreover, subgroup analysis showed that the highest quintile of HbAA/HbGA in the people with diabetes or pre-diabetes was related to mortalities risk of CVD (HRdiabetes = 1.92, 95% CI: 1.11–3.31; HRpre−diabetes = 1.78, 95% CI: 1.01–3.14) and all-cause mortality (HRdiabetes = 1.81, 95% CI: 1.27–2.58; HRpre−diabetes = 1.59, 95% CI: 1.14–2.20). Additionally, no significant association between the levels of HbAA or HbGA and CVD mortality was observed among people with diabetes or pre-diabetes.

Conclusion

Higher levels of HbAA/HbGA are associated with greater mortalities of CVD and all-cause among hyperglycemic people.

Review of the state of the art of acrylamide human biomonitoring

Human biomonitoring (HBM) is a very useful tool for assessing human exposure to acrylamide (AA). In the framework of the Human Biomonitoring Initiative (HBM4EU) AA was included in its second list of priority substances due to the potential threat to human health. HBM data on AA are scarce, but the use of specific and sensitive biomarkers represents a reliable indicator of exposure. In this review an overview of available knowledge on HBM of AA is provided in terms of: i) preferred exposure biomarkers and matrices for the HBM of AA; ii) analytical methods for determining its biomarkers of exposure in the most used specimens; iii) current HBM data available; and iv) tools for interpreting HBM data for AA in relation to risk assessment. Finally, future trends in this field are discussed.

Hemoglobin adducts of acrylamide in human blood - What has been done and what is next?

Acrylamide forms in many commonly consumed foods. In animals, acrylamide causes tumors, neurotoxicity, developmental and reproductive effects. Acrylamide crosses the placenta and has been associated with restriction of intrauterine growth and certain cancers. The impact on human health is poorly understood and it is impossible to say what level of dietary exposure to acrylamide can be deemed safe as the assessment of exposure is uncertain. The determination of hemoglobin (Hb) adducts from acrylamide is increasingly being used to improve the exposure assessment of acrylamide. We aim to outline the literature on Hb adduct levels from acrylamide in humans and discuss methodological issues and research gaps. A total of 86 studies of 27,966 individuals from 19 countries were reviewed. Adduct levels were highest in occupationally exposed individuals and smokers. Levels ranged widely from 3 to 210 pmol/g Hb in non-smokers and this wide range suggests that dietary exposure to acrylamide varies largely. Non-smokers from the US and Canada had slightly higher levels as compared with non-smokers from elsewhere, but differences within studies were larger than between studies. Large studies with exposure assessment of acrylamide and related adduct forming compounds from diet during early-life are encouraged for the evaluation of health effects.

Association between Acrylamide Hemoglobin Adduct Levels and Depressive Symptoms in US Adults: NHANES 2013-2016

Acrylamide (AA) is widely present in heat-processed carbohydrate-rich food, cigarette smoke, and the environment. Prolonged exposure to AA may cause central nervous system damage. However, few epidemiologic studies assessed the association between hemoglobin adduct levels of AA or its metabolite glycidamide (GA) and depressive symptoms. We included 3595 US adults (≥18 years) from the National Health and Nutrition Examination Survey (NHANES) 2013-2016. Data for hemoglobin adduct levels from AA and GA (HbAA and HbGA) were used as a measure of internal dose. Depressive symptom data were from mental health questionnaires and measured by nine-item Patient Health Questionnaire (PHQ-9) scores. Results of logistic regression models showed a positive association between HbAA in quartile 4 and depressive symptoms with ORs and 95% CI of 2.47 (1.29, 4.77) [OR_{continuous HbAA} and 95% CI: 1.006 (1.000, 1.013)], but an inverse association was detected in quartiles 2 and 3 of HbGA/HbAA [0.62 (0.38, 0.99) and 0.54 (0.32, 0.92), respectively]. Especially, an association between HbAA and depressive symptoms was strengthened in smokers, in age 18-39 and 40-59 years and BMI 25-30 kg/m² groups. Further explorations are needed to study the found associations between HbAA, HbGA, and depressive symptoms.

Associations of acrylamide with non-alcoholic fatty liver disease in American adults: a nationwide cross-sectional study

BACKGROUND

Acrylamide (AA) is a toxicant to humans, but the association between AA exposure and the risk of non-alcoholic fatty liver disease (NAFLD) remains unclear. In this study, our objective is to examine the cross-sectional association between AA exposure and the risk of NAFLD in American adults.

METHODS

A total of 3234 individuals who took part in the National Health and Nutrition Examination Survey (NHANES) 2003-2006 and 2013-2016 were enrolled in the study. NAFLD was diagnosed by the U.S. Fatty Liver Index. Multivariable logistic regression models were applied to estimate the association between AA and NAFLD in the whole group and the non-smoking group.

RESULTS

We discovered that in the whole group, serum hemoglobin adducts of AA (HbAA) were negatively associated with the prevalence of NAFLD after adjustment for various covariables (P for trend < 0.001). Compared with individuals in the lowest HbAA quartiles, the odds ratios (ORs) with 95% confidence intervals (CIs) in the highest HbAA quartiles were 0.61 (0.46-0.81) and 0.57 (0.36-0.88) in the whole group and the non-smoking group, respectively. In contrast, HbGA/HbAA showed a significantly positive correlation with the prevalence of NAFLD in both groups (P for trend < 0.001). In addition, HbGA was not significantly associated with NAFLD in the whole group or the non-smoking group.

CONCLUSIONS

HbAA is negatively associated with NAFLD whereas HbGA/HbAA is positively associated with NAFLD in adults in the U.S. Further studies are needed to clarify these relationships.

Acrylamide-Hemoglobin Adduct Levels in a Japanese Population and Comparison with Acrylamide Exposure Assessed by the Duplicated Method or a Food Frequency Questionnaire

The levels of hemoglobin adducts of acrylamide (AA-Hb), a biomarker of acrylamide exposure, have not been reported for Japanese subjects. Herein, we determined the AA-Hb levels in a Japanese population and compared them with the estimated dietary intake from the duplicate diet method (DM) and a food frequency questionnaire (FFQ). One-day DM samples, FFQ, and blood samples were collected from 89 participants and analyzed for acrylamide. AA-Hb was analyzed using liquid chromatography tandem mass spectrometry and the N-alkyl Edman method. Participants were divided into tertiles of estimated acrylamide intake and geometric means (GMs) of AA-Hb adjusted for sex and smoking status. A stratified analysis according to smoking status was also performed. The average AA-Hb levels for all participants, never, past, and current smokers were 46, 38, 65, and 86 pmol/g Hb, respectively. GMs of AA-Hb levels in all participants were significantly associated with tertiles of estimated acrylamide intake from DM (p for trend = 0.02) and FFQ (p for trend = 0.04), although no association with smokers was observed. AA-Hb levels reflected smoking status, which were similar to values reported in Western populations, and they were associated with estimated dietary intake of acrylamide when adjusted for sex and smoking status.

Association of acrylamide hemoglobin biomarkers with obesity, abdominal obesity and overweight in general US population: NHANES 2003-2006

Exposure to chemical contaminants is considered as one of risk factors to the current epidemic of obesity. Acrylamide (AA) is a ubiquitous chemical contaminant in environmental waste, mainstream cigarette smoke and carbohydrate-rich foods, and widely used in industrial manufacturers and cosmetics. Few studies have highlighted the association of daily exposure to AA with obesity-related outcomes. We analyzed data from 8364 participants who aged 20-85years and were recruited in National Health and Nutrition Examination Surveys (NHANES) 2003-2006. We established the model of PROC Survey Logistic regressions via using AA biomarkers in blood, hemoglobin adducts of acrylamide and glycidamide (HbAA and HbGA), as the measure of internal exposure to AA, and assessing obesity, abdominal obesity and overweight with body mass index (BMI) or waist circumference (WC). After the adjustment of sociodemographic variables, lifestyle behaviors, and health-related factors, the ratio of HbGA to HbAA (HbGA/HbAA) was significantly associated with obesity (p for trend<0.0001). The odd ratios (ORs) with 95% confidence intervals (CIs) of HbGA/HbAA across increasing quartiles were 1.740 (1.413-2.144), 2.604 (2.157-3.144), and 2.863 (2.425-3.380) compared with the lowest quartile. HbGA was positively associated with obesity [OR (95% CI): 1.226 (1.041-1.443), 1.283 (1.121-1.468), and 1.398 (1.165-1.679); p for trend=0.0004], while HbAA was inversely associated with obesity [OR (95% CI): 0.839 (0.718-0.980), 0.713 (0.600-0.848), and 0.671 (0.554-0.811); p for trend<0.0001]. Negative associations were found between the sum of HbAA and HbGA (HbAA+HbGA) and the body weight outcomes. Similar associations were also observed between the hemoglobin biomarkers of AA and abdominal obesity as well as overweight. Thus, the hemoglobin adducts of AA as long-term internal exposure biomarkers are strongly associated with obesity-related outcomes in a population of US adults.

The influence of demographic, physical, behavioral, and dietary factors on hemoglobin adduct levels of acrylamide and glycidamide in the general U.S. population

PURPOSE

This study aims to better understand the individual characteristics and dietary factors that affect the relationship between estimated consumption of acrylamide and measured acrylamide hemoglobin adduct levels (HbAA) and glycidamide hemoglobin adduct levels (HbGA).

METHODS

Acrylamide levels in individual food items, estimated by the U.S. Food and Drug Administration, were linked to data collected in the 2003-2004 National Health and Nutrition Examination Survey. Multivariable linear regression was used to evaluate the relationship between estimated consumption of acrylamide and HbAA.

RESULTS

A significant association between acrylamide intake and HbAA was observed, after adjustment for gender, race/ethnicity, smoking status, age, and BMI (R² = 0.34). Across quartiles of acrylamide consumption, HbAA and HbGA levels increased monotonically. Among nonsmokers, an evaluation of three heavily consumed, high AA concentration foods showed a positive trend between the consumed amount of fried potatoes and HbAA in children, adolescents, and adults. A significant positive trend between the consumed amount of potato chips or coffee was indicated in adolescents, adults, and seniors.

CONCLUSIONS

Consumption of some individual foods affects HbAA concentrations more strongly and in an age-dependent manner. Our results suggest that effective dietary guidelines for controlling acrylamide intake should be subpopulation specific.

Dietary and lifestyle determinants of acrylamide and glycidamide hemoglobin adducts in non-smoking postmenopausal women from the EPIC cohort

PURPOSE

Acrylamide was classified as 'probably carcinogenic' to humans in 1994 by the International Agency for Research on Cancer. In 2002, public health concern increased when acrylamide was identified in starchy, plant-based foods, processed at high temperatures. The purpose of this study was to identify which food groups and lifestyle variables were determinants of hemoglobin adduct concentrations of acrylamide (HbAA) and glycidamide (HbGA) in 801 non-smoking postmenopausal women from eight countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

METHODS

Biomarkers of internal exposure were measured in red blood cells (collected at baseline) by high-performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS) . In this cross-sectional analysis, four dependent variables were evaluated: HbAA, HbGA, sum of total adducts (HbAA + HbGA), and their ratio (HbGA/HbAA). Simple and multiple regression analyses were used to identify determinants of the four outcome variables. All dependent variables (except HbGA/HbAA) and all independent variables were log-transformed (log2) to improve normality. Median (25th-75th percentile) HbAA and HbGA adduct levels were 41.3 (32.8-53.1) pmol/g Hb and 34.2 (25.4-46.9) pmol/g Hb, respectively.

RESULTS

The main food group determinants of HbAA, HbGA, and HbAA + HbGA were biscuits, crackers, and dry cakes. Alcohol intake and body mass index were identified as the principal determinants of HbGA/HbAA. The total percent variation in HbAA, HbGA, HbAA + HbGA, and HbGA/HbAA explained in this study was 30, 26, 29, and 13 %, respectively.

CONCLUSIONS

Dietary and lifestyle factors explain a moderate proportion of acrylamide adduct variation in non-smoking postmenopausal women from the EPIC cohort.

Challenges and Lessons Learned in Generating and Interpreting NHANES Nutritional Biomarker Data

For the past 45 y, the National Center for Health Statistics at the CDC has carried out nutrition surveillance of the US population by collecting anthropometric, dietary intake, and nutritional biomarker data, the latter being the focus of this publication. The earliest biomarker testing assessed iron and vitamin A status. With time, a broad spectrum of water- and fat-soluble vitamins was added and biomarkers for other types of nutrients (e.g., fatty acids) and bioactive dietary compounds (e.g., phytoestrogens) were included in NHANES. The cross-sectional survey is flexible in design, and biomarkers may be measured for a short period of time or rotated in and out of surveys depending on scientific needs. Maintaining high-quality laboratory measurements over extended periods of time such that trends in status can be reliably assessed is a major goal of the testing laboratories. Physicians, health scientists, and policy makers rely on the NHANES reference data to compare the nutritional status of population groups, to assess the impact of various interventions, and to explore associations between nutritional status and health promotion or disease prevention. Focusing on the continuous NHANES, which started in 1999, this review uses a "lessons learned" approach to present a series of challenges that are relevant to researchers measuring biomarkers in NHANES and beyond. Some of those challenges are the use of multiple related biomarkers instead of a single biomarker for a specific nutrient (e.g., folate, vitamin B-12, iron), adhering to special needs for specimen collection and handling to ensure optimum specimen quality (e.g., vitamin C, folate, homocysteine, iodine, polyunsaturated fatty acids), the retrospective use of long-term quality-control data to correct for assay shifts (e.g., vitamin D, vitamin B-12), and the proper planning for and interpretation of crossover studies to adjust for systematic method changes (e.g., folate, vitamin D, ferritin).

Sociodemographic and lifestyle variables are compound- and class-specific correlates of urine phytoestrogen concentrations in the U.S. population

Isoflavones and lignans are plant-derived dietary compounds generally believed to be beneficial to human health. We investigated the extent to which sociodemographic (age, sex, race-ethnicity, education, and income) and lifestyle variables (smoking, alcohol consumption, BMI, physical activity, and dietary supplement use) were correlates of spot urine concentration for daidzein, genistein, O-desmethylangolensin (DMA), equol, enterodiol, and enterolactone in the U.S. population aged ≥ 20 y (NHANES 2003-2006). We performed correlation analyses with continuous variables and calculated stratified unadjusted geometric means for each sociodemographic and lifestyle variable. We used bivariate significance testing and covariate adjustment by use of multiple regression models to identify influential variables and used β coefficients to estimate relative effects. Urine creatinine was also included in our analyses because of its use in correcting for variable dilution in spot urine samples. We observed many significant (P < 0.05) associations with the sociodemographic and lifestyle variables that withstood covariate adjustment. Smoking was a significant correlate of urine DMA and enterolactone, with concentrations at least 25% lower in smokers vs. nonsmokers. Consumers of 1 daily alcoholic drink vs. none were estimated to have 18-21% lower urine equol and DMA concentrations. A 25% increase in BMI was associated with a 21% lower urine enterolactone concentration, and increasing physical activity was associated with a >6% higher urine enterolactone concentration. Dietary supplement use was not significantly associated with any of the urine phytoestrogens. Overall, we found that relationships between sociodemographic and lifestyle variables and urine phytoestrogen concentration were highly compound and class specific.