Evidence map›Paper›PMID 37913907›Full record

ArticleThe Journal of nutrition2024

Alcohol Consumption and the Diversity of the Oral Microbiome in Postmenopausal Women.

Samantha J Maley, Yihua Yue, Kaelyn F Burns, Kathleen M Hovey, Jean Wactawski-Wende, Jo L Freudenheim, Daniel I McSkimming, Michael J LaMonte, Chris A Andrews, Yijun Sun and 2 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Samantha J MaleyDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Yihua YueDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Kaelyn F BurnsDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Kathleen M HoveyDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Jean Wactawski-WendeDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Jo L FreudenheimDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Daniel I McSkimmingInterdisciplinary Unit in Data Science & Analytics, The State University of New York at Buffalo State University, Buffalo, NY, United States.
Michael J LaMonteDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States.
Chris A AndrewsDepartment of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, United States.
Yijun SunDepartment of Microbiology and Immunology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States.
Michael BuckDepartment of Biochemistry, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States.
Amy E MillenDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, United States. Electronic address: aemillen@buffalo.edu.
University at Buffalo, State University of New York · USUniversity of Michigan–Ann Arbor · US

Funding

Oral Microbiome and Periodontitis: A Prospective Study in Postmenopausal WomenR01DE024523 · NIDCR · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI WACTAWSKI-WENDE, JEAN · 2014 to 2018
$3.8M
BONE MINERAL DENSITY AS A PREDICTOR OF PERIODONTITISR01DE013505 · NIDCR · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI WACTAWSKI-WENDE, JEAN · 2002 to 2005
$1.9M
VANGUARD CENTER FOR WOMEN'S HEALTH INITIATIVEN01WH032122 · WH · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI TREVISAN, MAURIZIO · 1993 to 2000
$927k
NIDCR NIH HHS R01 DE013505NIDCR NIH HHS R01 DE024523WHI NIH HHS N01 WH032122
6 · The paper itself

Abstract

backgroundAlcohol reduces neutrophil function and decreases salivary flow, which could affect the composition of the oral microbiome.

objectiveWe hypothesized that the α- and β-diversity of the oral microbiome and the relative abundance of bacterial taxa would differ by frequency and type of alcohol consumption.

methodsWe used a food frequency questionnaire to assess the frequency of consumption of beer, wine, and liquor (drinks/week) in a sample of 1179 postmenopausal women in the Osteoporosis and Periodontal Disease Study. Women were categorized as nondrinkers, drinking <1 drink/wk, ≥1 to <7 drinks/wk, or ≥7 drinks/wk for total alcohol consumption and for beer, wine, and liquor consumption. The composition and diversity of the oral microbiome was assessed from subgingival plaque samples using 16S ribosomal RNA amplicon sequencing. Permutational multivariate analysis of variance (PERMANOVA) was used to examine β-diversity (between-sample diversity) in the microbiome between alcohol consumption categories. Analysis of covariance was used to examine the mean α-diversity (within-sample diversity), assessed by the Shannon index (species evenness), Chao1 index (species richness), and observed operational taxonomic unit (OTU) count and the mean relative abundance of 245 bacterial taxa across alcohol consumption categories.

resultsOver half of the participants (67%) consumed alcohol, with 14% reporting ≥1 drink/d. The β-diversity across categories of total alcohol consumption, but not categories of alcohol type, was statistically significantly different (P for PERMANOVA = 0.016). Mean α-diversity measures were statistically significantly higher (P < 0.05) in the highest category of total alcohol and wine consumption compared to nondrinkers; no significant associations were found for beer or liquor consumption. The relative abundance of 1 OTU, Selenomonassp._oral_taxon_133, was significantly lower in the highest level of total alcohol consumption compared to nondrinkers after adjustment for multiple comparisons.

conclusionsAlcohol consumption was associated with the diversity and composition of the subgingival microbiome.

Indexed as

MicrobiotaWineAlcohol DrinkingAlcoholic BeveragesEthanolFemaleHumansPostmenopauseEthanolalcoholdietepidemiologymicrobiomenutritionoral healthperiodontal disease

Identifiers

PMID37913907
PMCPMC10808818
OpenAlexW4388037479

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.