Evidence map›Paper›PMID 29321397›Full record

ArticleJournal of atherosclerosis and thrombosis2018

Associations between Socioeconomic Status and the Prevalence and Treatment of Hypercholesterolemia in a General Japanese Population: NIPPON DATA2010.

Naoko Fujiyoshi, Hisatomi Arima, Atsushi Satoh, Toshiyuki Ojima, Nobuo Nishi, Nagako Okuda, Aya Kadota, Takayoshi Ohkubo, Atsushi Hozawa, Naoki Nakaya and 6 more

Open access · diamondAbstract read
In one paragraph

Article in Journal of atherosclerosis and thrombosis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
7.5field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 22 citations in OpenAlex.

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  7. Prediction of hypercholesterolemia using machine learning techniques.Journal of diabetes and metabolic disorders · 2023
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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

16 authors at 8 institutions in 1 country.

Naoko FujiyoshiDepartment of Public Health, Shiga University of Medical Science.
Hisatomi ArimaDepartment of Public Health, Shiga University of Medical Science.
Atsushi SatohDepartment of Public Health, Shiga University of Medical Science.
Toshiyuki OjimaDepartment of Community Health and Preventive Medicine, Hamamatsu University School of Medicine.
Nobuo NishiInternational Center for Nutrition and Information, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition.
Nagako OkudaDepartment of Health and Nutrition, University of Human Arts and Sciences.
Aya KadotaDepartment of Public Health, Shiga University of Medical Science.
Takayoshi OhkuboDepartment of Hygiene and Public Health Teikyo University School of Medicine.
Atsushi HozawaDepartment of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University.
Naoki NakayaDepartment of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University.
Akira FujiyoshiDepartment of Public Health, Shiga University of Medical Science.
Tomonori OkamuraDepartment of Preventive Medicine and Public Health, Keio University.
Hirotsugu UeshimaDepartment of Public Health, Shiga University of Medical Science.
Akira OkayamaResearch Institute of Strategy for Prevention.
Katsuyuki MiuraDepartment of Public Health, Shiga University of Medical Science.
NIPPON DATA2010 Research Group
Shiga University of Medical Science · JPFukuoka University · JPTohoku Medical Megabank Organization · JPHamamatsu University School of Medicine · JPKeio University · JPNational Institute of Biomedical Innovation, Health and Nutrition · JPShiga University · JPUniversity of Human Arts and Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo investigate associations between socioeconomic status (SES) and the prevalence and treatment status of hypercholesterolemia in a general Japanese population.

methodsIn 2010, we established a cohort study of 2417 adults (age 20-91 yr) from 300 randomly selected areas across Japan who participated in the National Health and Nutrition Survey of Japan. We cross-sectionally examined an association between SES and (1) prevalence of hypercholesterolemia in 2417 participants (999 men and 1418 women) and (2) not receiving medication for hypercholesterolemia in 654 participants (215 men and 439 women). SES included employment status, marital status, length of education, and household expenditures. Hypercholesterolemia was defined as a total serum cholesterol level of ≥6.21 mmol/L (240 mg/dL) or the use of lipid-lowering medications.

resultsThe overall prevalence of hypercholesterolemia was 21.5% in men and 31.0% in women. In men, the lowest quintile of household expenditures was associated with a higher prevalence of hypercholesterolemia (28.3%) compared with the upper 4 quintiles (19.9%) (multivariable-adjusted odds ratio 1.66; 95% confidence interval [CI] 1.16-2.38). Among participants with hypercholesterolemia, 55.4% of men and 55.1% of women were not receiving medication. Unmarried men were more likely to be untreated (75.0%) than married men (50.9%) (multivariable-adjusted odds ratio 2.53;95%CI 1.05-6.08). SES had no significant effects in women.

conclusionIn a general population of Japanese men, low household expenditures were associated with a higher prevalence of hypercholesterolemia, and unmarried men with hypercholesterolemia were less likely to receive medication.

Indexed as

Social ClassAdultAgedAged, 80 and overCross-Sectional StudiesFemaleHealth SurveysHumansHypercholesterolemiaJapanLipid MetabolismMaleMenopauseMiddle AgedMultivariate AnalysisOdds RatioHypercholesterolemiaJapanRisk factorSocioeconomic statusTreatment

Identifiers

PMID29321397
PMCPMC6055037
OpenAlexW2783068487

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.