Evidence map›Paper›PMID 38654317›Full record

ArticleBMC public health2024

Sex differences and dietary patterns in the association of air pollutants and hypertension.

Chen Zhang, Yuanyuan Wang, Wei Xie, Jingxian Zhang, Ting Tian, Qianrang Zhu, Xinyu Fang, Jing Sui, Da Pan, Hui Xia and 3 more

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

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.3field-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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Associations of exposure to PMBMC public health · 2025
    Pooled it
  2. Review
  3. Review
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

13 authors at 2 institutions in 1 country.

Chen ZhangKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China.
Yuanyuan WangKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China.
Wei XieInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, 210009, Nanjing, China.
Jingxian ZhangInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, 210009, Nanjing, China.
Ting TianInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, 210009, Nanjing, China.
Qianrang ZhuInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, 210009, Nanjing, China.
Xinyu FangInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, 210009, Nanjing, China.
Jing SuiKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China.
Da PanKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China.
Hui XiaKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China.
Shaokang WangKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China.
Guiju SunKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China. gjsun@seu.edu.cn.
Yue DaiKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, 210009, Nanjing, China. 18915999341@163.com.
Southeast University · CNJiangsu Provincial Center for Disease Control and Prevention · CN

Funding

National Natural Science Foundation of China 82173509
6 · The paper itself

Abstract

backgroundHypertension is one of the major public health problems in China. Limited evidence exists regarding sex differences in the association between hypertension and air pollutants, as well as the impact of dietary factors on the relationship between air pollutants and hypertension. The aim of this study was to investigate the sex-specific effects of dietary patterns on the association between fine particulate matter (PM

methodsA total of 3189 adults from the 2015 China Adult Chronic Disease and Nutrition Surveillance in Jiangsu Province were included in this study. PM

resultsAfter adjusting for confounding variables, we found that males were more sensitive to long-term exposure to PM

conclusionsOur findings suggested that sex differences existed in the association between dietary patterns, air pollutants and hypertension. Furthermore, we found that adherence to traditional southern pattern may mitigate the risk of long-term PM

Indexed as

Air PollutantsHypertensionOzoneParticulate MatterAdultAgedChinaDietEnvironmental ExposureFemaleHumansMaleMiddle AgedSex FactorsAir PollutantsOzoneParticulate MatterDietary patternHypertensionO3PM2.5Sex differences

Identifiers

PMID38654317
PMCPMC11040935
OpenAlexW4395033573

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.