1
|
Koós N, Vahid F, Bohn T. Protective effect of provitamin A dietary carotenoid intake on overweight/obesity and their relation to inflammatory and oxidative stress biomarkers - a case-control study. Food Funct 2024; 15:5510-5526. [PMID: 38690968 DOI: 10.1039/d3fo05648a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
This investigation assessed associations between dietary carotenoid intake and the odds of overweight/obesity, as well as inflammatory/oxidative stress biomarkers, in 851 participants with overweight/obesity (BMI ≥25 kg m-2) and 754 normal-weight controls. A 124-item food-frequency-questionnaire (FFQ) and food composition databases were employed to estimate carotenoid intake. Binary logistic regressions assessed the association of carotenoid intake with the odds of overweight/obesity, adjusting for several potential confounders. Multiple linear regression models revealed associations between carotenoid intake and biomarkers (anthropometrics, blood lipids, inflammation, antioxidant status). Logistic regression models adjusted for various confounders and fruits and vegetables showed protective associations for provitamin A carotenoids (i.e., β-carotene + α-carotene + β-cryptoxanthin; odds ratio (OR): 0.655, p = 0.041) and astaxanthin (OR: 0.859, p = 0.017). Similarly adjusted multiple linear regressions revealed significant associations between several carotenoids and lower levels of interleukin (IL)-6, IL-1β, and TNF-α and increased IL-10 and total antioxidant capacity. Further analysis revealed that lycopene was significantly associated with increased odds of overweight/obesity (OR: 1.595, p = 0.032) in a model adjusted for various confounders and vegetables (i.e., unadjusted for fruits). A protective association between the sum of provitamin A carotenoid and astaxanthin dietary intake and the odds of having overweight/obesity was found. The findings that carotenoids other than lycopene were not or inversely associated with the odds of overweight/obesity may point toward differentiating effects of various carotenoids or their associations with different food groups. Provitamin A rich food items including fruits and vegetables appear to be a prudent strategy to reduce inflammation and the odds of having overweight/obesity.
Collapse
Affiliation(s)
- Natália Koós
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| | - Farhad Vahid
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| | - Torsten Bohn
- Nutrition and Health Research Group, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| |
Collapse
|
2
|
Zhang Y, Spitzer BW, Zhang Y, Wallace DA, Yu B, Qi Q, Argos M, Avilés-Santa ML, Boerwinkle E, Daviglus ML, Kaplan R, Cai J, Redline S, Sofer T. Untargeted Metabolome Atlas for Sleep Phenotypes in the Hispanic Community Health Study/Study of Latinos. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.17.24307286. [PMID: 38798578 PMCID: PMC11118618 DOI: 10.1101/2024.05.17.24307286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Sleep is essential to maintaining health and wellbeing of individuals, influencing a variety of outcomes from mental health to cardiometabolic disease. This study aims to assess the relationships between various sleep phenotypes and blood metabolites. Utilizing data from the Hispanic Community Health Study/Study of Latinos, we performed association analyses between 40 sleep phenotypes, grouped in several domains (i.e., sleep disordered breathing (SDB), sleep duration, timing, insomnia symptoms, and heart rate during sleep), and 768 metabolites measured via untargeted metabolomics profiling. Network analysis was employed to visualize and interpret the associations between sleep phenotypes and metabolites. The patterns of statistically significant associations between sleep phenotypes and metabolites differed by superpathways, and highlighted subpathways of interest for future studies. For example, some xenobiotic metabolites were associated with sleep duration and heart rate phenotypes (e.g. 1H-indole-7-acetic acid, 4-allylphenol sulfate), while ketone bodies and fatty acid metabolism metabolites were associated with sleep timing measures (e.g. 3-hydroxybutyrate (BHBA), 3-hydroxyhexanoylcarnitine (1)). Heart rate phenotypes had the overall largest number of detected metabolite associations. Many of these associations were shared with both SDB and with sleep timing phenotypes, while SDB phenotypes shared relatively few metabolite associations with sleep duration measures. A number of metabolites were associated with multiple sleep phenotypes, from a few domains. The amino acids vanillylmandelate (VMA) and 1-carboxyethylisoleucine were associated with the greatest number of sleep phenotypes, from all domains other than insomnia. This atlas of sleep-metabolite associations will facilitate hypothesis generation and further study of the metabolic underpinnings of sleep health.
Collapse
Affiliation(s)
- Ying Zhang
- Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Brian W Spitzer
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Yu Zhang
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Danielle A Wallace
- Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Maria Argos
- Department of Epidemiology and Biostatistics, School of Public Health, University of Illinois Chicago, Chicago, IL, USA
- Department of Environmental Health, School of Public Health, Boston University, Boston, MA, USA
| | - M Larissa Avilés-Santa
- Division of Clinical and Health Services Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, USA
| | - Eric Boerwinkle
- Department of Epidemiology, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Robert Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jianwen Cai
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Susan Redline
- Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Tamar Sofer
- Division of Sleep Medicine and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| |
Collapse
|
3
|
Wei B, Tan W, He S, Yang S, Gu C, Wang S. Association between drinking status and risk of kidney stones among United States adults: NHANES 2007-2018. BMC Public Health 2024; 24:820. [PMID: 38491490 PMCID: PMC10941453 DOI: 10.1186/s12889-024-18307-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Accepted: 03/07/2024] [Indexed: 03/18/2024] Open
Abstract
OBJECTIVE This study aimed to investigate the relationship between drinking status and kidney stones occurrence among United States (US) adults who consume alcohol. METHODS We conducted a cross-sectional analysis using data from the National Health and Nutrition Examination Survey (NHANES 2007-2018). Questionnaires yielded information on alcohol consumption and kidney health. Drinking status was categorized into four groups-former, mild, moderate, and heavy-based on alcohol consumption patterns. The aim was to explore the relationship between drinking status and the prevalence of kidney stones occurrence. For this analysis, we examined a group of individuals diagnosed with kidney stones. With survey weights applied, the total weight of the group was 185,690,415. RESULTS We used logistic regression to measure the relationship between drinking status and the likelihood of developing kidney stones. In a fully adjusted model, former drinkers were less likely to have previously experienced kidney stones (OR 0.762, 95% CI 0.595-0.977, P < 0.05). In subgroup analysis, heavy alcohol consumption was associated with a significantly reduced likelihood of kidney stones occurrence in various populations. The adjusted odds ratios (with 95% confidence intervals) of kidney stones risk for heavy alcohol consumption were 0.745 (0.566-0.981) for young individuals, 0.566 (0.342-0.939) for older individuals, 0.708 (0.510-0.981) for individuals of white race, 0.468 (0.269-0.817) for individuals with underweight/normal BMI, 0.192 (0.066-0.560) for widowed people, 0.538 (0.343-0.843) for smoking individuals, 0.749 (0.595-0.941) for individuals without a cancer history, and 0.724 (0.566-0.925) for individuals without a stroke history. CONCLUSIONS In US adults who consume alcohol, a negative linear relationship is apparent between drinking status and the prevalence of kidney stones, with heavy drinking showing a lower prevalence compared to former drinkers. However, the causal relationship between drinking status and kidney stones requires further investigation in future research endeavors.
Collapse
Affiliation(s)
- Baian Wei
- The Second School of Clinical Medical , Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Wenyue Tan
- The Second School of Clinical Medical , Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Shuien He
- The Second School of Clinical Medical , Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Shijian Yang
- The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510120, China
| | - Chiming Gu
- The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510120, China
| | - Shusheng Wang
- The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, 510120, China.
| |
Collapse
|
4
|
Deng MG, Liu F, Wang K, Zhang MJ, Feng Q, Liu J. Association between dietary flavonoid intake and depressive symptoms: A cross-sectional research. Gen Hosp Psychiatry 2024; 86:75-84. [PMID: 38134552 DOI: 10.1016/j.genhosppsych.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 12/24/2023]
Abstract
OBJECTIVE To investigate the relationship between dietary flavonoid intake and depression symptoms in American adults. METHODS Data sets were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007-2008, 2009-2010, and 2017-2018 survey cycles. Both males and females aged 18 years and older with complete information about dietary flavonoid intake (isoflavones, anthocyanidins, flavan-3-ols, flavanones, flavones, and flavonols), depression symptoms, and covariates were included. Logistic regression models were conducted to calculate the odds ratio (OR) of single dietary flavonoid subclass intake on depression, and the restricted cubic spline (RCS) models were utilized to explore the corresponding dose-response relationships. Additionally, we implemented the weighted quantile sum (WQS) regression and quantile g-computation (qgcomp) models to estimate the mixed effects of six flavonoid subclasses and identify the predominant types. RESULTS After multivariable adjustments, people with higher consumption of flavanones (OR: 0.68, 95% CI: 0.52-0.90, p = 0.008), flavones (OR: 0.63, 95% CI: 0.46-0.87, p = 0.007), flavonols (OR: 0.66, 95% CI: 0.49-0.89, p = 0.008), and total flavonoids (OR: 0.69, 95% CI: 0.50-0.95, p = 0.024) had lower odds of depression symptoms. Meanwhile, significant dose-response relationships were supported by the RCS models. However, no obvious associations between isoflavones, anthocyanidins, flavan-3-ols, and the odds of suffering from depression symptoms were found by the logistic regression models and RCS models. As for the mixed effect, the WQS and qgcomp models both demonstrated that the mixture of six flavonoid subclasses was inversely related to the odds ratios of depression symptoms, and flavones, flavanones, and anthocyanidins were the top 3 contributors. CONCLUSION Our study implied dietary flavonoid intake was associated with the decreased probability of depression symptoms in U.S. adults, among which flavones, flavanones, and anthocyanidins may occupy the predominant roles.
Collapse
Affiliation(s)
- Ming-Gang Deng
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan 430012, Hubei, China; Department of Psychiatry, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei, China.
| | - Fang Liu
- School of Public Health, Wuhan University, Wuhan 430071, Hubei, China
| | - Kai Wang
- Department of Public Health, Wuhan Fourth Hospital, Wuhan 430033, Hubei, China
| | - Min-Jie Zhang
- School of Public Health, Wuhan University, Wuhan 430071, Hubei, China
| | - Qianqian Feng
- School of Public Health, Wuhan University, Wuhan 430071, Hubei, China
| | - Jiewei Liu
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan 430012, Hubei, China; Department of Psychiatry, Wuhan Hospital for Psychotherapy, Wuhan 430012, Hubei, China.
| |
Collapse
|