Air pollution, residential greenness, and metabolic dysfunction biomarkers: analyses in the Chinese

Liu et al. BMC Public Health (2022) 22:885

https://doi.org/10.1186/s12889-022-13126-8

RESEARCH ARTICLE

Air pollution, residential greenness,

and metabolic dysfunction biomarkers: analyses

in the Chinese Longitudinal Healthy Longevity

Survey

Linxin Liu1

, Lijing L. Yan2,3,4, Yuebin Lv5

, Yi Zhang5

, Tiantian Li5

, Cunrui Huang1

, Haidong Kan6

, Junfeng Zhang7

,

Yi Zeng8,9, Xiaoming Shi5,10 and John S. Ji1*

Abstract

Background: We hypothesize higher air pollution and fewer greenness exposures jointly contribute to metabolic

syndrome (MetS), as mechanisms on cardiometabolic mortality.

Methods: We studied the samples in the Chinese Longitudinal Healthy Longevity Survey. We included 1755 par￾ticipants in 2012, among which 1073 were followed up in 2014 and 561 in 2017. We used cross-sectional analysis

for baseline data and the generalized estimating equations (GEE) model in a longitudinal analysis. We examined the

independent and interactive efects of fne particulate matter (PM2.5) and Normalized Diference Vegetation Index

(NDVI) on MetS. Adjustment covariates included biomarker measurement year, baseline age, sex, ethnicity, education,

marriage, residence, exercise, smoking, alcohol drinking, and GDP per capita.

Results: At baseline, the average age of participants was 85.6 (SD: 12.2; range: 65–112). Greenness was slightly higher

in rural areas than urban areas (NDVI mean: 0.496 vs. 0.444; range: 0.151–0.698 vs. 0.133–0.644). Ambient air pollu￾tion was similar between rural and urban areas (PM2.5 mean: 49.0 vs. 49.1; range: 16.2–65.3 vs. 18.3–64.2). Both the

cross-sectional and longitudinal analysis showed positive associations of PM2.5 with prevalent abdominal obesity (AO)

and MetS, and a negative association of NDVI with prevalent AO. In the longitudinal data, the odds ratio (OR, 95%

confdence interval-CI) of PM2.5 (per 10 μg/m3

increase) were 1.19 (1.12, 1.27), 1.16 (1.08, 1.24), and 1.14 (1.07, 1.21)

for AO, MetS and reduced high-density lipoprotein cholesterol (HDL-C), respectively. NDVI (per 0.1 unit increase) was

associated with lower AO prevalence [OR (95% CI): 0.79 (0.71, 0.88)], but not signifcantly associated with MetS [OR

(95% CI): 0.93 (0.84, 1.04)]. PM2.5 and NDVI had a statistically signifcant interaction on AO prevalence (pinteraction: 0.025).

The association between PM2.5 and MetS, AO, elevated fasting glucose and reduced HDL-C were only signifcant in

rural areas, not in urban areas. The association between NDVI and AO was only signifcant in areas with low PM2.5, not

under high PM2.5.

Conclusions: We found air pollution and greenness had independent and interactive efect on MetS components,

which may ultimately manifest in pre-mature mortality. These study fndings call for green space planning in urban

areas and air pollution mitigation in rural areas.

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which

permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the

original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or

other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line

to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory

regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this

licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco

mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Open Access

*Correspondence: [email protected]

1

Vanke School of Public Health, Tsinghua University, Beijing, China

Full list of author information is available at the end of the article