Cigarette smoking is a leading cause of premature mortality, attributable to chronic exposure to toxic compounds in cigarette smoke, including tobacco-specific nitrosamines, which are known carcinogens. This research ...Cigarette smoking is a leading cause of premature mortality, attributable to chronic exposure to toxic compounds in cigarette smoke, including tobacco-specific nitrosamines, which are known carcinogens. This research aims to assess the association between NNAL, a metabolite of the tobacco-specific nitrosamine NNK, and mortality. Data from 14,766 U.S. adults aged 21 - 79 in the National Health and Nutrition Examination Survey (2007-2014) included smoking status and urinary NNAL concentration at the time of examination. These data were linked to participants’ subsequent mortality status as recorded in the public-use Linked Mortality File (through 2015). Cox proportional hazards regression models assessed the relative risk of all-cause, cancer, cardiovascular disease (CVD), and other-causes mortality for increasing levels of natural log (creatinine-adjusted NNAL). In the whole sample, a unit increase in log (NNAL) is associated with a 20% higher risk of all-cause (HR = 1.20;95% CI: 1.16 - 1.24), cancer (HR = 1.20;95% CI: 1.14 - 1.26), CVD (HR = 1.21;95% CI: 1.12 - 1.31) and other-causes (HR = 1.20;95% CI: 1.15 - 1.25) mortality. Among current smokers, a unit increase in log (NNAL) is associated with 44% higher cancer mortality risk (HR = 1.44;95% CI: 1.08 - 1.92) and a 96% higher CVD mortality risk (HR = 1.96;95% CI: 1.20 - 3.20). Risks of all-cause and other-causes mortality, but neither cancer nor CVD mortality, were positively associated with NNAL among never and former smokers. Inferences are limited by the observational nature of the data, and by the focus on a single biomarker of tobacco-related exposure. The findings suggest that urinary NNAL concentration is acting as a proxy for exposure to the toxicants in cigarette smoke rather than as a biomarker of disease-specific mortality risk.展开更多
美国国家健康与营养调查(NHANES,National Health and Nutrition Examination Survey)是一项旨在评估美国成人和儿童健康和营养状况的研究计划,该调查的独特之处在于它结合了访谈和体检。NHANES是国家卫生统计中心(NCHS,National center...美国国家健康与营养调查(NHANES,National Health and Nutrition Examination Survey)是一项旨在评估美国成人和儿童健康和营养状况的研究计划,该调查的独特之处在于它结合了访谈和体检。NHANES是国家卫生统计中心(NCHS,National center for Health Statistics)的主要计划,是国家营养监测的基石,为营养和健康政策的制定提供了大量数据。NHANES项目信息及调查数据会在网站上及时更新且向公众免费开放。本文通过介绍NHANES项目相关内容及数据提取方法,方便需要的研究者快速高效地获取自己需要地数据。展开更多
BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is the most common chronic liver disease,affecting over 30% of the United States population.Early patient identification using a simple method is highly desirable.AIM...BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is the most common chronic liver disease,affecting over 30% of the United States population.Early patient identification using a simple method is highly desirable.AIM To create machine learning models for predicting NAFLD in the general United States population.METHODS Using the NHANES 1988-1994.Thirty NAFLD-related factors were included.The dataset was divided into the training(70%)and testing(30%)datasets.Twentyfour machine learning algorithms were applied to the training dataset.The bestperforming models and another interpretable model(i.e.,coarse trees)were tested using the testing dataset.RESULTS There were 3235 participants(n=3235)that met the inclusion criteria.In the training phase,the ensemble of random undersampling(RUS)boosted trees had the highest F1(0.53).In the testing phase,we compared selective machine learning models and NAFLD indices.Based on F1,the ensemble of RUS boosted trees remained the top performer(accuracy 71.1%and F10.56)followed by the fatty liver index(accuracy 68.8% and F10.52).A simple model(coarse trees)had an accuracy of 74.9% and an F1 of 0.33.CONCLUSION Not every machine learning model is complex.Using a simpler model such as coarse trees,we can create an interpretable model for predicting NAFLD with only two predictors:fasting C-peptide and waist circumference.Although the simpler model does not have the best performance,its simplicity is useful in clinical practice.展开更多
Objectives: The goal of this study was to determine the association of rice consumption with nutrient intake and diet quality in a recent nationally representative sample of US adults. Methods: NHANES data (2005-2010)...Objectives: The goal of this study was to determine the association of rice consumption with nutrient intake and diet quality in a recent nationally representative sample of US adults. Methods: NHANES data (2005-2010) were used to assess the association of rice consumption by adults (19+ yrs;N = 14,386) with nutrient intake and diet quality. 24-hour dietary intakes were used to calculate usual intake (UI) of rice consumption using the National Cancer Institute methodology. Rice consumption groups were 0.25 to 0.5 to <1.0, and >1.0 oz. eq. of UI of rice. Diet quality (using the Healthy Eating Index-2005 [HEI-2005]) was calculated. Covariate adjusted least square means ± SE were determined and quartile trends across the rice consumption categories were examined. Results: Significant (p < 0.001) positive trends (β coefficient across rice consumption categories) were seen for sodium (118.99 mg), dietary fiber (0.57 g), folate (58.24 μg DFE), magnesium (11.83 mg), iron (0.97 mg) and potassium (29.45 mg). Significant negative trends (p < 0.0001) were seen for intakes of saturated fatty acids (-1.75 g), added sugars (-1.31 g);and calcium (-40.46 mg). HEI-2005 also showed a positive trend (p < 0.0001) with rice consumption (5.5 points). HEI-2005 component scores for total fruit (0.07), whole fruit (0.11), dark green/orange vegetables (0.25), total grains (0.10), meat/beans (0.24), and oils (0.15) were higher (p < 0.01) in rice consumers than non-consumers. HEI-2005 component scores for saturated fatty acids (0.63), solid fats, added sugars, and alcohol (1.22) were higher suggesting more favorable intake, but sodium (-0.24) was lower. Conclusion: Overall, consumption of rice should be encouraged to improve nutrient intake and diet quality. Nutrition education can provide ways to reduce sodium added to rice dishes.展开更多
Objectives: The relationship between sleep disturbances and cardiovascular disease (CVD) is not well established. This study assesses the association between sleep disturbances and CVD, and the effect of sleep duratio...Objectives: The relationship between sleep disturbances and cardiovascular disease (CVD) is not well established. This study assesses the association between sleep disturbances and CVD, and the effect of sleep duration on the relationship between sleep disturbances and CVD among adults in the United States (US). Design: Cross-sectional analysis. Setting: NHANES (National Health and Nutrition Examination Survey). Participants: A total of 5660 adults were included from the 2015-2016 cycle of the NHANES survey. Measurements: The main outcome was the presence of any CVD and included self-reported angina, congestive heart failure, coronary heart disease, hypertension and myocardial infarction. Associations between sleep disturbances and sleep duration with CVD were analyzed using logistic regression. Stratified models by sleep duration were used to assess effect modification. Results: We included 5660 participants (52.2% males), 32.7% of the participants reported having a disturbed sleep and 38% reported a CVD. Compared to those who did not report any sleep disturbances, those with sleep disturbance had 85% higher odds of CVD (OR 1.85, 95% CI 1.43 - 2.39). Similarly, there were 40% higher odds of CVD (OR 1.40, 95% CI 1.01 - 1.95) among those with shorter sleep duration compared with those that slept for 6 to 9hours. However, there was no evidence of effect modification by sleep duration. Conclusions: Our findings show that sleep disturbance is associated with higher odds of CVD. Clinicians and other healthcare providers need to consider the consequence of sleep disturbances and implement strategies in the treatment of patients with or at high risk of CVD.展开更多
Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are found in some consumer products due to their heat resistance and durability. However, there is potential for these substances to bioaccumulate in humans. It is ...Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are found in some consumer products due to their heat resistance and durability. However, there is potential for these substances to bioaccumulate in humans. It is relevant to investigate biological effects of these chemicals, as studies have suggested early life exposure may impact human developmental outcomes such as infant birth weight and youth adiposity. The objective of the current study was to determine if a relationship exists between increasing levels of certain PFAS and anthropometrics in adolescents ages 12 - 18. The three PFAS examined were: perfluorodecanoic acid (PFDeA), 2-(N-methyl-perfluoroctane sulfonamido) acetic acid (Me-PFOSA-AcOH), and perfluoroundecanoic acid (PFUA). The data was obtained from the National Health and Nutrition Examination Survey (NHANES) from the years 2011-2012 (<em>N </em>= 287) and 2013-2014 (<em>N</em> = 344). An additional analysis combined data from 3 NHANES survey cycles using sampling weights for the years 2011-2016 (<em>N</em> = 875) to generate a larger sample size of detectable PFAS. PFAS concentrations were classified as above or below the lower limit of detection (LLOD) to evaluate differences in weight, waist circumference, BMI (body mass index), and height using Student’s t-tests. These same anthropometric outcomes were examined as continuous variables in linear regression models and were stratified by sex. In the 2013-2014 dataset, there were significant inverse associations between female concentrations of PFUA and PFDeA with waist circumference (PFUA<em> β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;"><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span></span></span>0.056;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.106, <span style="white-space:nowrap;"><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span></span>0.005;PFDeA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.06;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.10, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.02), weight-for-age z-score (PFUA <em>β </em>= <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.40;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.74, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.05;PFDeA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.38;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.64, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.12), and BMI-for-age z-score (PFUA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.48;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.86, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.10;PFDeA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.45;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.73, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.16). In the 2011-2012 dataset, males displayed a significant inverse relationship between PFDeA and waist circumference (<em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.08;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.14, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.02), weight-for-age z-score (<em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.49;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.88, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.11), and BMI-for-age z-score (<em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.44;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.84, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.05). In the combined analysis of NHANES years 2011-2016, there were significant inverse associations with PFUA and PFDeA and weight-for-age z-score, waist circumference, and BMI-for-age z-score. In the given sample years, there was no compelling evidence for a relationship between any of the perfluoroalkyl chemicals and height, nor between Me-PFOSA-AcOH and any of the body measures after adjusting for age, sex, and race/ethnicity. This suggests that PFUA and PFDeA exposure in adolescents may be related to smaller waist circumference, weight, and BMI, but longitudinal studies are recommended to confirm these findings.展开更多
Introduction: There has been an interest to explore whether serum leptin plays any role in the pathogenesis of chronic liver disease. We conducted a case-control study to evaluate the relationship between unexplained ...Introduction: There has been an interest to explore whether serum leptin plays any role in the pathogenesis of chronic liver disease. We conducted a case-control study to evaluate the relationship between unexplained elevations in ALT and serum leptin in NHANES III participants. Methods: A total of 6343 adults who had fasting serum leptin and ALT measured as part of NHANES III constituted our study group. From this database, we have constructed cohorts of patients with unexplained elevations in ALT according to published criteria and compared their serum leptin levels to matched controls without liver disease and matched controls with hepatitis C. Leptin was also compared between patients with unexplained elevations in ALT with and without metabolic syndrome. Results: Serum leptin in 288 patients with unexplained elevations in ALT was 13.3 ±9.9 ng/mL and was not significantly different than 720 controls without liver disease (13.6 ±11.9 ng/mL, P = 0.6). Serum leptin in another group of patients with unexplained elevations in ALT and hepatitis C controls was also not significantly different (8.0 ±4.8 vs. 8.8 ±7.4 ng/mL, respectively, P = 0.5). There was no independent relationship between the presence of metabolic syndrome and serum leptin in individuals with unexplained elevations in ALT (P = 0.8). Conclusions: Individuals with unexplained elevations in ALT did not have higher levels of serum leptin than the matched controls. As unexplained elevations in ALT may signify the presence of non-alcoholic fatty liver disease in NHANES III participants, our data provide indirect evidence against a role for serum leptin in the pathogenesis of nonalcoholic fatty liver disease.展开更多
Monoterpenes are organic compounds which have been studied for their medicinal benefits.However,the association between monoterpene exposure and metabolic parameters in humans is unknown.We investigated the connection...Monoterpenes are organic compounds which have been studied for their medicinal benefits.However,the association between monoterpene exposure and metabolic parameters in humans is unknown.We investigated the connection between three specific monoterpenes(α-pinene,β-pinene,and limonene),glucose homeostasis biomarkers,lipid profiles,and metabolic syndrome(MS)in 1627 adults from the National Health and Nutrition Examination Survey(NHANES)2013–2014.We found serum levels ofα-pinene andβ-pinene were positively associated with fasting glucose,total cholesterol,triglyceride,and apolipoprotein B.In addition,increased levels of limonene andΣmonoterpene(sum of three monoterpene chemicals)were linked to higher insulin,β-cell function,total cholesterol,low density lipoprotein cholesterol(LDL-C),triglycerides,and apolipoprotein B.Participants with all three monoterpenes above the 50th percentile had notably higher values for total cholesterol and triglycerides compared to those with all three monoterpenes below the 50th percentile(P for trend<0.001).Regarding MS,higher serum concentrations ofα-pinene were linked to an increased risk of high-density lipoprotein cholesterol(HDL-C)insufficiency and hypertriglyceridemia.Elevated concentrations ofβ-pinene were associated with a higher prevalence of hypertriglyceridemia.Moreover,increased levels of limonene andΣmonoterpene were connected to a higher risk of MS,larger waist circumference,low HDL-C,hypertriglyceridemia,and higher blood pressure according to MS criteria.In conclusion,serum monoterpenes levels were linked to glucose regulation,lipid profiles,and indicators of MS.Further studies are necessary to clarify the potential causal relationships.展开更多
目的探讨预后营养指数(prognostic nutritional index,PNI)与脑卒中患者抑郁风险的关系,为脑卒中患者预后管理提供参考。方法选取美国国家健康和营养调查(National Health and Nutrition Examination Survey,NHANES)数据库2017—2020年...目的探讨预后营养指数(prognostic nutritional index,PNI)与脑卒中患者抑郁风险的关系,为脑卒中患者预后管理提供参考。方法选取美国国家健康和营养调查(National Health and Nutrition Examination Survey,NHANES)数据库2017—2020年收录的脑卒中后幸存者作为研究对象,评估其抑郁情况并计算PNI,采用多因素logistic回归分析PNI对脑卒中患者抑郁风险的影响。结果共纳入443例研究对象,包括男性220例,女性223例,平均年龄(65.22±12.44)岁,共检出抑郁95例(21.44%)。脑卒中后抑郁患者PNI指数为(47.23±7.01)分,低于非抑郁患者的(49.59±5.51)分,组间差异有统计学意义(P<0.05)。多因素logistic回归结果显示,在调整性别、年龄、教育水平、婚姻状态、吸烟史等混杂因素后,PNI评分升高对脑卒中后抑郁有明显的保护作用(OR=0.929,95%CI:0.892~0.968,P<0.05)。结论PNI评分升高对降低脑卒中患者抑郁风险具有一定作用,维持良好的营养状态和免疫功能对于预防脑卒中患者抑郁、改善预后效果具有重要意义。展开更多
文摘Cigarette smoking is a leading cause of premature mortality, attributable to chronic exposure to toxic compounds in cigarette smoke, including tobacco-specific nitrosamines, which are known carcinogens. This research aims to assess the association between NNAL, a metabolite of the tobacco-specific nitrosamine NNK, and mortality. Data from 14,766 U.S. adults aged 21 - 79 in the National Health and Nutrition Examination Survey (2007-2014) included smoking status and urinary NNAL concentration at the time of examination. These data were linked to participants’ subsequent mortality status as recorded in the public-use Linked Mortality File (through 2015). Cox proportional hazards regression models assessed the relative risk of all-cause, cancer, cardiovascular disease (CVD), and other-causes mortality for increasing levels of natural log (creatinine-adjusted NNAL). In the whole sample, a unit increase in log (NNAL) is associated with a 20% higher risk of all-cause (HR = 1.20;95% CI: 1.16 - 1.24), cancer (HR = 1.20;95% CI: 1.14 - 1.26), CVD (HR = 1.21;95% CI: 1.12 - 1.31) and other-causes (HR = 1.20;95% CI: 1.15 - 1.25) mortality. Among current smokers, a unit increase in log (NNAL) is associated with 44% higher cancer mortality risk (HR = 1.44;95% CI: 1.08 - 1.92) and a 96% higher CVD mortality risk (HR = 1.96;95% CI: 1.20 - 3.20). Risks of all-cause and other-causes mortality, but neither cancer nor CVD mortality, were positively associated with NNAL among never and former smokers. Inferences are limited by the observational nature of the data, and by the focus on a single biomarker of tobacco-related exposure. The findings suggest that urinary NNAL concentration is acting as a proxy for exposure to the toxicants in cigarette smoke rather than as a biomarker of disease-specific mortality risk.
文摘美国国家健康与营养调查(NHANES,National Health and Nutrition Examination Survey)是一项旨在评估美国成人和儿童健康和营养状况的研究计划,该调查的独特之处在于它结合了访谈和体检。NHANES是国家卫生统计中心(NCHS,National center for Health Statistics)的主要计划,是国家营养监测的基石,为营养和健康政策的制定提供了大量数据。NHANES项目信息及调查数据会在网站上及时更新且向公众免费开放。本文通过介绍NHANES项目相关内容及数据提取方法,方便需要的研究者快速高效地获取自己需要地数据。
文摘BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is the most common chronic liver disease,affecting over 30% of the United States population.Early patient identification using a simple method is highly desirable.AIM To create machine learning models for predicting NAFLD in the general United States population.METHODS Using the NHANES 1988-1994.Thirty NAFLD-related factors were included.The dataset was divided into the training(70%)and testing(30%)datasets.Twentyfour machine learning algorithms were applied to the training dataset.The bestperforming models and another interpretable model(i.e.,coarse trees)were tested using the testing dataset.RESULTS There were 3235 participants(n=3235)that met the inclusion criteria.In the training phase,the ensemble of random undersampling(RUS)boosted trees had the highest F1(0.53).In the testing phase,we compared selective machine learning models and NAFLD indices.Based on F1,the ensemble of RUS boosted trees remained the top performer(accuracy 71.1%and F10.56)followed by the fatty liver index(accuracy 68.8% and F10.52).A simple model(coarse trees)had an accuracy of 74.9% and an F1 of 0.33.CONCLUSION Not every machine learning model is complex.Using a simpler model such as coarse trees,we can create an interpretable model for predicting NAFLD with only two predictors:fasting C-peptide and waist circumference.Although the simpler model does not have the best performance,its simplicity is useful in clinical practice.
文摘Objectives: The goal of this study was to determine the association of rice consumption with nutrient intake and diet quality in a recent nationally representative sample of US adults. Methods: NHANES data (2005-2010) were used to assess the association of rice consumption by adults (19+ yrs;N = 14,386) with nutrient intake and diet quality. 24-hour dietary intakes were used to calculate usual intake (UI) of rice consumption using the National Cancer Institute methodology. Rice consumption groups were 0.25 to 0.5 to <1.0, and >1.0 oz. eq. of UI of rice. Diet quality (using the Healthy Eating Index-2005 [HEI-2005]) was calculated. Covariate adjusted least square means ± SE were determined and quartile trends across the rice consumption categories were examined. Results: Significant (p < 0.001) positive trends (β coefficient across rice consumption categories) were seen for sodium (118.99 mg), dietary fiber (0.57 g), folate (58.24 μg DFE), magnesium (11.83 mg), iron (0.97 mg) and potassium (29.45 mg). Significant negative trends (p < 0.0001) were seen for intakes of saturated fatty acids (-1.75 g), added sugars (-1.31 g);and calcium (-40.46 mg). HEI-2005 also showed a positive trend (p < 0.0001) with rice consumption (5.5 points). HEI-2005 component scores for total fruit (0.07), whole fruit (0.11), dark green/orange vegetables (0.25), total grains (0.10), meat/beans (0.24), and oils (0.15) were higher (p < 0.01) in rice consumers than non-consumers. HEI-2005 component scores for saturated fatty acids (0.63), solid fats, added sugars, and alcohol (1.22) were higher suggesting more favorable intake, but sodium (-0.24) was lower. Conclusion: Overall, consumption of rice should be encouraged to improve nutrient intake and diet quality. Nutrition education can provide ways to reduce sodium added to rice dishes.
文摘Objectives: The relationship between sleep disturbances and cardiovascular disease (CVD) is not well established. This study assesses the association between sleep disturbances and CVD, and the effect of sleep duration on the relationship between sleep disturbances and CVD among adults in the United States (US). Design: Cross-sectional analysis. Setting: NHANES (National Health and Nutrition Examination Survey). Participants: A total of 5660 adults were included from the 2015-2016 cycle of the NHANES survey. Measurements: The main outcome was the presence of any CVD and included self-reported angina, congestive heart failure, coronary heart disease, hypertension and myocardial infarction. Associations between sleep disturbances and sleep duration with CVD were analyzed using logistic regression. Stratified models by sleep duration were used to assess effect modification. Results: We included 5660 participants (52.2% males), 32.7% of the participants reported having a disturbed sleep and 38% reported a CVD. Compared to those who did not report any sleep disturbances, those with sleep disturbance had 85% higher odds of CVD (OR 1.85, 95% CI 1.43 - 2.39). Similarly, there were 40% higher odds of CVD (OR 1.40, 95% CI 1.01 - 1.95) among those with shorter sleep duration compared with those that slept for 6 to 9hours. However, there was no evidence of effect modification by sleep duration. Conclusions: Our findings show that sleep disturbance is associated with higher odds of CVD. Clinicians and other healthcare providers need to consider the consequence of sleep disturbances and implement strategies in the treatment of patients with or at high risk of CVD.
文摘Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are found in some consumer products due to their heat resistance and durability. However, there is potential for these substances to bioaccumulate in humans. It is relevant to investigate biological effects of these chemicals, as studies have suggested early life exposure may impact human developmental outcomes such as infant birth weight and youth adiposity. The objective of the current study was to determine if a relationship exists between increasing levels of certain PFAS and anthropometrics in adolescents ages 12 - 18. The three PFAS examined were: perfluorodecanoic acid (PFDeA), 2-(N-methyl-perfluoroctane sulfonamido) acetic acid (Me-PFOSA-AcOH), and perfluoroundecanoic acid (PFUA). The data was obtained from the National Health and Nutrition Examination Survey (NHANES) from the years 2011-2012 (<em>N </em>= 287) and 2013-2014 (<em>N</em> = 344). An additional analysis combined data from 3 NHANES survey cycles using sampling weights for the years 2011-2016 (<em>N</em> = 875) to generate a larger sample size of detectable PFAS. PFAS concentrations were classified as above or below the lower limit of detection (LLOD) to evaluate differences in weight, waist circumference, BMI (body mass index), and height using Student’s t-tests. These same anthropometric outcomes were examined as continuous variables in linear regression models and were stratified by sex. In the 2013-2014 dataset, there were significant inverse associations between female concentrations of PFUA and PFDeA with waist circumference (PFUA<em> β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;"><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span></span></span>0.056;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.106, <span style="white-space:nowrap;"><span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span></span>0.005;PFDeA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.06;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.10, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.02), weight-for-age z-score (PFUA <em>β </em>= <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.40;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.74, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.05;PFDeA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.38;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.64, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.12), and BMI-for-age z-score (PFUA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.48;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.86, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.10;PFDeA <em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.45;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.73, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.16). In the 2011-2012 dataset, males displayed a significant inverse relationship between PFDeA and waist circumference (<em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.08;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.14, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.02), weight-for-age z-score (<em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.49;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.88, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.11), and BMI-for-age z-score (<em>β</em> = <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.44;95% CI, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.84, <span style="white-space:nowrap;"><span style="white-space:nowrap;">−</span></span>0.05). In the combined analysis of NHANES years 2011-2016, there were significant inverse associations with PFUA and PFDeA and weight-for-age z-score, waist circumference, and BMI-for-age z-score. In the given sample years, there was no compelling evidence for a relationship between any of the perfluoroalkyl chemicals and height, nor between Me-PFOSA-AcOH and any of the body measures after adjusting for age, sex, and race/ethnicity. This suggests that PFUA and PFDeA exposure in adolescents may be related to smaller waist circumference, weight, and BMI, but longitudinal studies are recommended to confirm these findings.
文摘Introduction: There has been an interest to explore whether serum leptin plays any role in the pathogenesis of chronic liver disease. We conducted a case-control study to evaluate the relationship between unexplained elevations in ALT and serum leptin in NHANES III participants. Methods: A total of 6343 adults who had fasting serum leptin and ALT measured as part of NHANES III constituted our study group. From this database, we have constructed cohorts of patients with unexplained elevations in ALT according to published criteria and compared their serum leptin levels to matched controls without liver disease and matched controls with hepatitis C. Leptin was also compared between patients with unexplained elevations in ALT with and without metabolic syndrome. Results: Serum leptin in 288 patients with unexplained elevations in ALT was 13.3 ±9.9 ng/mL and was not significantly different than 720 controls without liver disease (13.6 ±11.9 ng/mL, P = 0.6). Serum leptin in another group of patients with unexplained elevations in ALT and hepatitis C controls was also not significantly different (8.0 ±4.8 vs. 8.8 ±7.4 ng/mL, respectively, P = 0.5). There was no independent relationship between the presence of metabolic syndrome and serum leptin in individuals with unexplained elevations in ALT (P = 0.8). Conclusions: Individuals with unexplained elevations in ALT did not have higher levels of serum leptin than the matched controls. As unexplained elevations in ALT may signify the presence of non-alcoholic fatty liver disease in NHANES III participants, our data provide indirect evidence against a role for serum leptin in the pathogenesis of nonalcoholic fatty liver disease.
基金This study would not have been possible without the collective efforts and support of numerous individuals and organizations.This study was funded by grants from the Ministry of Science and Technology of Taiwan NSC 110-2314-B-385-001-MY3.
文摘Monoterpenes are organic compounds which have been studied for their medicinal benefits.However,the association between monoterpene exposure and metabolic parameters in humans is unknown.We investigated the connection between three specific monoterpenes(α-pinene,β-pinene,and limonene),glucose homeostasis biomarkers,lipid profiles,and metabolic syndrome(MS)in 1627 adults from the National Health and Nutrition Examination Survey(NHANES)2013–2014.We found serum levels ofα-pinene andβ-pinene were positively associated with fasting glucose,total cholesterol,triglyceride,and apolipoprotein B.In addition,increased levels of limonene andΣmonoterpene(sum of three monoterpene chemicals)were linked to higher insulin,β-cell function,total cholesterol,low density lipoprotein cholesterol(LDL-C),triglycerides,and apolipoprotein B.Participants with all three monoterpenes above the 50th percentile had notably higher values for total cholesterol and triglycerides compared to those with all three monoterpenes below the 50th percentile(P for trend<0.001).Regarding MS,higher serum concentrations ofα-pinene were linked to an increased risk of high-density lipoprotein cholesterol(HDL-C)insufficiency and hypertriglyceridemia.Elevated concentrations ofβ-pinene were associated with a higher prevalence of hypertriglyceridemia.Moreover,increased levels of limonene andΣmonoterpene were connected to a higher risk of MS,larger waist circumference,low HDL-C,hypertriglyceridemia,and higher blood pressure according to MS criteria.In conclusion,serum monoterpenes levels were linked to glucose regulation,lipid profiles,and indicators of MS.Further studies are necessary to clarify the potential causal relationships.
文摘目的探讨预后营养指数(prognostic nutritional index,PNI)与脑卒中患者抑郁风险的关系,为脑卒中患者预后管理提供参考。方法选取美国国家健康和营养调查(National Health and Nutrition Examination Survey,NHANES)数据库2017—2020年收录的脑卒中后幸存者作为研究对象,评估其抑郁情况并计算PNI,采用多因素logistic回归分析PNI对脑卒中患者抑郁风险的影响。结果共纳入443例研究对象,包括男性220例,女性223例,平均年龄(65.22±12.44)岁,共检出抑郁95例(21.44%)。脑卒中后抑郁患者PNI指数为(47.23±7.01)分,低于非抑郁患者的(49.59±5.51)分,组间差异有统计学意义(P<0.05)。多因素logistic回归结果显示,在调整性别、年龄、教育水平、婚姻状态、吸烟史等混杂因素后,PNI评分升高对脑卒中后抑郁有明显的保护作用(OR=0.929,95%CI:0.892~0.968,P<0.05)。结论PNI评分升高对降低脑卒中患者抑郁风险具有一定作用,维持良好的营养状态和免疫功能对于预防脑卒中患者抑郁、改善预后效果具有重要意义。