Evidence map›Paper›PMID 34551767›Full record

ArticleLipids in health and disease2021

Time series decomposition into dyslipidemia prevalence among urban Chinese population: secular and seasonal trends.

Jiahui Lao, Yafei Liu, Yang Yang, Peng Peng, Feifei Ma, Shuang Ji, Yujiao Chen, Fang Tang

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

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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

8 authors at 4 institutions in 1 country.

Jiahui LaoDepartment of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.
Yafei LiuDepartment of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.
Yang YangDepartment of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.
Peng PengSchool of Public Health, Weifang Medical University, Weifang, China.
Feifei MaSchool of Public Health, Weifang Medical University, Weifang, China.
Shuang JiSchool of Public Health, Weifang Medical University, Weifang, China.
Yujiao ChenSchool of Public Health, Weifang Medical University, Weifang, China.
Fang TangDepartment of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China. tangfangsdu@gmail.com.
Weifang Medical University · CNShandong Provincial QianFoShan Hospital · CNShandong First Medical University · CNShandong University · CN

Funding

academic promotion programme of shandong first medical university 2019LJ005national natural science foundation of china 71804093shandong provincial key research and development program 2020RKB14114shandong provincial medical and health science and technology development project SQ20170087
6 · The paper itself

Abstract

backgroundPrevious epidemiological studies have indicated the seasonal variability of serum lipid levels. However, little research has explicitly examined the separate secular and seasonal trends of dyslipidemia. The present study aimed to identify secular and seasonal trends for the prevalence of dyslipidemia and the 4 clinical classifications among the urban Chinese population by time series decomposition.

methodsA total of 306,335 participants with metabolic-related indicators from January 2011 to December 2017 were recruited based on routine health check-up systems. Multivariate direct standardization was used to eliminate uneven distributions of the age, sex, and BMI of participants over time. Seasonal and trend decomposition using LOESS (STL decomposition) was performed to break dyslipidemia prevalence down into trend component, seasonal component and remainder component.

resultsA total of 21.52 % of participants were diagnosed with dyslipidemia, and significant differences in dyslipidemia and the 4 clinical classifications were observed by sex (P <0.001). The secular trends of dyslipidemia prevalence fluctuated in 2011-2017 with the lowest point in September 2016. The dyslipidemia prevalence from January to March and May to July was higher than the annual average (λ = 1.00, 1.16, 1.06, 1.01, 1.02, 1.03), with the highest point in February. Different seasonal trends were observed among the 4 clinical classifications. Compared to females, a higher point was observed among males in February, which was similar to participants aged < 55 years (vs. ≥ 55 years) and participants with a BMI ≤ 23.9 (vs. BMI > 23.9).

conclusionsThere were significant secular and seasonal features for dyslipidemia prevalence among the urban Chinese population. Different seasonal trends were found in the 4 clinical classifications of dyslipidemia. Precautionary measures should be implemented to control elevated dyslipidemia prevalence in specific seasons, especially in the winter and during traditional holidays.

Indexed as

SeasonsAgedAsian PeopleChinaCitiesDyslipidemiasFemaleHumansMaleMiddle AgedMultivariate AnalysisPrevalenceTime FactorsTriglyceridesUrban PopulationTriglyceridesDyslipidemiaHDL-C hypolipidemiaHypercholesterolemiaHypertriglyceridemiaMixed hyperlipidemiaSeasonal trendsSecular trendsTime series decomposition

Identifiers

PMID34551767
PMCPMC8459537
OpenAlexW3199527703

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.