Evidence map›Paper›PMID 37995949›Full record

Observational studyAmerican journal of preventive medicine2024

Social and Behavior Factors of Alzheimer's Disease and Related Dementias: A National Study in the U.S.

David Ciciora, Elizabeth Vásquez, Edward Valachovic, Lifang Hou, Yinan Zheng, Hua Xu, Xiaoqian Jiang, Kun Huang, Kelley Pettee Gabriel, Hong-Wen Deng and 2 more

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in American journal of preventive medicine, 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
1.1field-weighted citation impact, top 22% 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, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  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 8 institutions in 1 country.

David CicioraDepartment of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, New York.
Elizabeth VásquezDepartment of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, New York.
Edward ValachovicDepartment of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, New York.
Lifang HouDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Yinan ZhengDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Hua XuSection of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, Connecticut.
Xiaoqian JiangMcWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas.
Kun HuangDepartment of Biostatistics and Health Data Science, Indiana University School of Medicine and IUPUI Fairbanks School of Public Health, Regenstrief Institute, Indianapolis, Indiana.
Kelley Pettee GabrielDepartment of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama.
Hong-Wen DengTulane Division/Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, Louisiana.
Mary P GallantZuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, Massachusetts.
Kai ZhangDepartment of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York. Electronic address: kzhang9@albany.edu.
Albany State University · USNorthwestern University · USRegenstrief Institute · USThe University of Texas Health Science Center at Houston · USTulane University · USUniversity of Alabama at Birmingham · USUniversity of Massachusetts Lowell · USYale University · US

Funding

Tulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Tanika Nicole Kelly · 2016 to 2026
$25.3M
Trans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI YU-PING WANG · 2017 to 2026
$24.3M
Intensive Lifestyle Intervention, Metabolomics, and Risk of Frailty Fracture in Overweight or Obese Patients with Type 2 DiabetesR01AG068232 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI JOHNSON, KAREN C, ZHAO, QI · 2021 to 2025
$3.1M
Identification of Metabolomic Profiles for Sarcopenia Traits in Older Whites and BlacksR01AG061917 · NIA · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI SHEN, HUI, ZHAO, QI · 2019 to 2023
$3.0M
Epigenomic landscape of individual- and neighborhood-level social disadvantages and cardiovascular health disparityR01AG081244 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI HOU, LIFANG, LIU, LEI · 2022 to 2025
$2.2M
NIA NIH HHS R01 AG061917NIA NIH HHS R01 AG068232NIA NIH HHS R01 AG081244NIA NIH HHS U19 AG055373NIGMS NIH HHS P20 GM109036
6 · The paper itself

Abstract

introductionConsiderable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated.

methodsThis observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by their relative contribution to the model performance. Stratified ranking was also performed based on a county's level of disadvantage. Shapley Additive exPlanations (SHAP) provided marginal contributions for each variable.

resultsThe top three ranked predictors at the county level were insufficient sleep, consuming less than one serving of fruits/vegetables per day among adults, and having less than a high school diploma. In both disadvantaged and non-disadvantaged counties, demographic variables such as sex and race were important in predicting ADRD. Lifestyle factors ranked highly in non-disadvantaged counties compared to more environmental factors in disadvantaged counties.

conclusionsThis ranked list of factors can provide a guided approach to ADRD primary prevention strategies in the U.S., as the effects of sleep, diet, and education on ADRD can be further developed. While sleep, diet, and education are important nationally, differing prevention strategies could be employed based on a county's level of disadvantage.

Indexed as

Alzheimer DiseaseAdultHumansLife StyleResearch DesignRisk Factors

Identifiers

PMID37995949
PMCPMC12037269
OpenAlexW4388914384

What OpenQuestion holds

Textmetadata
LicenceTDM
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.