Evidence map›Paper›PMID 31711454›Full record

ArticleBMC public health2019

Prevalence and risk factors for dyslipidemia among adults in rural and urban China: findings from the China National Stroke Screening and prevention project (CNSSPP).

Sampson Opoku, Yong Gan, Wenning Fu, Dajie Chen, Emmanuel Addo-Yobo, Diana Trofimovitch, Wei Yue, Feng Yan, Zhihong Wang, Zuxun Lu

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
123citing papers in PubMed, 4 pooled it
18.3field-weighted citation impact, top 1% 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

123 citing papers in PubMed, 4 syntheses or guidelines pooled it, 204 citations in OpenAlex.

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63 more citing papers are in PubMed but not listed here.

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

10 authors at 6 institutions in 2 countries.

Sampson OpokuDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, China.
Yong GanDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, China.
Wenning FuDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, China.
Dajie ChenDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, China.
Emmanuel Addo-YoboDepartment of Internal Medicine, SUNY Upstate Medical University, New York, USA.
Diana TrofimovitchDepartment of Internal Medicine, East Tennessee State University, Johnson City, Tennessee, USA.
Wei YueDepartment of Neurology, Tianjin Huanhu Hospital, Tianjin, China.
Feng YanDepartment of Neurosurgery, Xuanwu Hospital, Capital medical University, Beijing, China.
Zhihong WangDepartment of Neurology, Shenzhen Second People's Hospital, Shenzhen University, Shenzhen, Guangdong, China.
Zuxun LuDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, China. zuxunlu@yahoo.com.
Huazhong University of Science and Technology · CNCapital Medical University · CNEast Tennessee State University · USShenzhen Second People's Hospital · CNSUNY Upstate Medical University · USTianjin Huanhu Hospital · CN

Funding

Innovation committee of shenzhen science and technology KJYY20170413162318686The China Postdoctoral Science Foundation funded project 2018M630870The Fundamental Research Funds for the Central Universities, Huazhong University of Science and Technology, Wuhan, China 2016YXMS215
6 · The paper itself

Abstract

backgroundDyslipidemia is a modifiable risk factor for cardiovascular disease (CVD). We investigated the prevalence and associated risk factors of dyslipidemia- raised total cholesterol (TC), raised triglycerides (TG), raised low-density lipoprotein (LDL-C), low high-density lipoprotein (HDL-C), and raised non-high-density lipoprotein (non-HDL-C) in rural and urban China.

methodsWe analyzed data from 136,945 participants aged 40-100 years of the CNSSPP project for 2014. Dyslipidemia was defined by the NCEP-ATP III and the 2016 Chinese guidelines for the management of dyslipidemia in adults. Complete data on demographic, metabolic and lifestyle characteristics were used. Chi-square tests and multivariable logistic regression were used to obtain age- and sex-adjusted prevalence and risk factors for dyslipidemia among participants.

resultsA total of 53.1% participants lived in rural areas. The prevalence of dyslipidemia was similar among rural and urban participants (43.2% vs. 43.3%). Regarding the components of dyslipidemia: urban compared with rural participants had a higher prevalence of low HDL-C (20.8% vs. 19.2%), whereas the prevalence of raised LDL-C (7.8% vs. 8.3%), raised TC (10.9% vs.11.8%) and raised non-HDL-C (10.0% vs. 10.9%) were lower in urban residents, (all p < 0.001). Women were more likely to have raised TC than men (adjusted OR [AOR] =1.83, 95% confidence interval [CI]:1.75-1.91), raised LDL-C (AOR = 1.55, 95% CI: 1.47-1.63) and high non-HDL-C (AOR = 1.52 95% CI: 1.45-1.59) (all p < 0.001). Compared with rural, urban participants had higher odds of dyslipidemia: low HDL-C (AOR = 1.04, 95% CI: 1.01-1.07), and raised TG (AOR = 1.06, 95% CI: 1.04-1.09). Hypertension and current drinker were less likely to get low HDL-C with AOR 0.93 (95% CI: 0.90-0.96) and AOR 0.73 (95% CI: 0.70-75), respectively. Overweight, obesity, central obesity and diabetes had higher odds of all dyslipidemias (p < 0.001).

conclusionsLow HDL-C was higher in urban areas, whereas the remaining dyslipidemia types were more common in rural areas. Dyslipidemia was more common in women in both areas of residence. Overweight, obesity, central obesity and diabetes were associated with dyslipidemias. The need to intensify intervention programs to manage dyslipidemia and risk factors should be prioritized.

Indexed as

Health StatusAdultAgedCardiovascular DiseasesChinaComorbidityDiabetes Mellitus, Type 2DyslipidemiasFemaleHumansHypertensionMaleMiddle AgedObesityPrevalenceRisk FactorsTriglyceridesDyslipidemiaPrevalenceRisk factorsRuralUrban

Identifiers

PMID31711454
PMCPMC6849283
OpenAlexW2988708112

What OpenQuestion holds

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LicenceCC BY
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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.