Promoted Relationship of Cardiovascular Morbidity with Air Pollutants in a Typical Chinese Urban Area
Citation: Tong L, Li K, Zhou Q (
Promoted Relationship of Cardiovascular Morbidity with Air Pollutants in a Typical Chinese Urban Area
Ling Tong 0
Kai Li 0
Qixing Zhou 0
Qinghua Sun, The Ohio State University, United States of America
0 1 School of Environmental Science and Engineering, Tianjin University , Tianjin , China , 2 Department of Industrial Engineering, Nankai University , Tianjin , China , 3 Key Laboratory of Pollution Process and Environmental Criteria (Ministry of Education), College of Environmental Science and Engineering, Nankai University , Tianjin , China
Background: A large number of studies about effects of air pollutants on cardiovascular mortality have been conducted; however, those investigating association between air pollutants and cardiovascular morbidity are limited, especially in developing countries. Methods: A time-series analysis on the short-term association between outdoor air pollutants including particulate matter (PM) with diameters of 10 mm or less (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) and cardiovascular morbidity was conducted in Tianjin, China based on 4 years of daily data (2008-2011). The morbidity data were stratified by sex and age. The effects of air pollutants during the warm season and the cool season were also analyzed separately. Results: Each increase in PM10, SO2, and NO2 by increments of 10 mg/m3 in a 2-day average concentration was associated with increases in the cardiovascular morbidity of 0.19% with 95 percent confidence interval (95% CI) of 0.08-0.31, 0.43% with 95% CI of 0.03-0.84, and 0.52% with 95% CI of 20.09-1.13, respectively. The effects of air pollutants were more evident in the cool season than those in the warm season, females and the elderly were more vulnerable to outdoor air pollution. Conclusions: All estimated coefficients of PM10, SO2 and NO2 are positive but only the effect of SO2 implied statistical significance at the 5% level. Moreover, season, sex and age might modify health effects of outdoor air pollutants. This work may bring inspirations for formulating local air pollutant standards and social policy regarding cardiovascular health of residents.
As the largest harbor in northern China, Tianjin is a
fastgrowing and economically developed city. It has an area of
approximately 11,919 km2 and a population of 10 million. A
continental monsoonal climate featuring hot and humid summer,
and dry and cold winter is typical here. The mean annual
temperature and precipitation is 13.1uC and 389.4 mm,
respectively. It is wetter in summer than in winter. The domestic heating
season is generally between November and March. The average
wind speeds range from 16 to 24 km/h. A comprehensive
industrial system including integrated machinery, electronics,
petroleum and chemicals, metallurgy, textiles and vehicles has
been built in this city. The industrial prosperity brings about severe
air pollution problems. From 2008 to 2011, both daily
concentrations of PM10 and SO2 (80.2 mg/m3 and 148.1 mg/m3,
respectively) exceeded the Class I levels of the Chinese national
standards (daily average: 50 mg/m3 for both PM10 and SO2) 
and the standards of the World Health Organization (WHO)
(daily average: 50 mg/m3 and 24 mg/m3 for PM10 and SO2,
respectively) . Air pollution exerts tremendous burdens to public
health, ranking as the 13th leading cause of mortality .
There are numerous studies of similar questions that have been
conducted in North America and Western Europe. Several years
ago, the Health Effects Institute sponsored some studies under the
acronym PAPA (http://pubs.healtheffects.org/types.php?type=1
for published reports), including "Public Health and Air Pollution
in Asia (PAPA): Coordinated Studies of Short-Term Exposure to
Air Pollution and Daily Mortality in Two Indian Cities" and
"Public Health and Air Pollution in Asia (PAPA): Coordinated
Studies of Short-Term Exposure to Air Pollution and Daily
Mortality in Four Cities". Pathophysiologic mechanisms of air
pollutant-induced cardiovascular morbidity and mortality are also
being studied widely , besides, some studies on the
associations between air pollutants and cardiovascular diseases
have been conducted in terms of epidemiology . However,
investigations on the relationship between air pollutants and
cardiovascular morbidity are scarce at present , especially in
Asian countries where, arguably, both living conditions and health
indicators may be quite different.
This study presents an investigation of this issue in a typical
Chinese city to increase our understanding of cardiovascular
health risks associated with polluted air and provide some scientific
basis for establishment of public health and environmental
protection policies .
Materials and Methods
2.1. Subject Data
Daily air pollution data on PM10, SO2 and NO2 were obtained
from the website of the Tianjin Environmental Monitoring
Centre. Daily mean temperature and relative humidity were
obtained from the China Meteorological Data Sharing Service
System (Data S1).
Daily cardiovascular morbidity data from 1 January 2008 to 31
November 2011 was collected from the Centers for Disease
Control and Prevention of Urban Districts in Tianjin, China
(Nankai, Heping, Hexi, Hedong and Hongqiao districts), covering
around 77000 local residents (SI). Information of patients
including those under the age of 18 was anonymized and were
validated each year by China CDC. They were coded according
to the ICD-10 (the 10th revision of International Classification of
Diseases) and classified into cardiovascular causes including
cerebral infarction, primary diagnosed hypertension, cerebral
hemorrhage, acute myocardial infarction and subarachnoid
hemorrhage . They were also stratified by sex and age (0
18, 1844, 4564, and $65 years) . The ethical committee of
the coordinating center of five urban CDCs in Tianjin approved
the study (Full name is "CDC biomedical ethics council").
Air pollutant concentrations and meteorological measures
including temperature and humidity are shown in Table 1 and 2.
2.2. Statistical methods
All analyses were conducted with statistical software package
SAS version 9.1. Time-series analysis was utilized to explore
modification effects of season, age and sex on the association
between air pollutants and morbidity in Tianjin from 2008 to
2011. In detail, the generalized linear model with natural splines
(ns) functions of time, weather conditions accommodate nonlinear
and non-monotonic relationships of morbidity with time,
temperature and relative humidity were utilized for the analysis . In
the basic model, morbidity outcomes were included without air
pollution variables. Residuals of the basic models were examined
to determine whether there were discernible patterns and
autocorrelation by means of residual plots and partial
autocorrelation function (PACF) plots. Day of the week (DOW) was
considered as a dummy variable in the basic modes. After the
establishment of the basic model, PM10 and covariates
(temperature, humidity, and SO2 and NO2 concentrations) were
introduced into it and their effects were analyzed. The selection
of df (degrees of freedom) for time trends was done with the PACF
[17,18]. 4 df per year for time trends were used in our basic
models for cardiovascular morbidity. In addition, we used 3 df
(during whole period of study) for temperature and humidity. This
modeling procedure was carried out for each series studied and the
core models were assessed with plots of model residuals and fitted
values as well as plots of the estimated partial autocorrelation
The estimated pollution log-relative rate b is obtained through
fitting of the following log-linear generalized linear model:
logE(Yt) = bZt + DOW + ns(time, df) + ns(temperature/
humidity, 3) + intercept (1)
Where E(Yt) and b represent the expected morbidity numbered
at day t and the log-relative rate of morbidity corresponding to a
unit increase of air pollutants, respectively; Zt indicates pollutant
concentrations at day t; DOW is dummy variable for day of the
week; ns (time, df) is the ns function of calendar time with 4 df to
adjust for seasonality and other time-varying influences on
admissions (e.g. influenza epidemics and longer-term trends);
and ns (temperature/humidity, 3) is the ns function for
temperature and humidity with 3 df.
The data were stratified by sex and age. We analyzed the
associations for the warm season (April-September), the cool
season (October-March) and the entire year, respectively (Kan et
al., 2008b). The basic models of seasonal analyses were different
from those of the whole-period in terms of df for time trends. The
effects were quantified on the basis of the percentage change in
risk per 10 mg/m3 increase in the concentration of each pollutant.
The statistical significance was defined as p,0.05.
3.1. Time series plot of the morbidity, exposure-response
relationships, ACF and PACF of morbidity
The time series plot of cardiovascular morbidity from 2008 to
2011 in Tianjin is shown in Fig. 1. Fig. 2 demonstrates the
exposureresponse relationships for PM10, SO2 and NO2 (2-day
moving average of air pollutant concentration (lag 01)) with
cardiovascular mortality during 20082011 in Tianjin. In Fig. 3,
ACF and PACF of cardiovascular morbidity are depicted as
original data (log). ACF and PACF of cardiovascular morbidity as
original data (log+Difference) are shown in Fig. 4. Fig. 5 gives
ACF and PACF of residual after modeling (basic model).
3.2. Effects by sexes and ages
As shown in Table 3, the percent increases associated with air
pollutant concentrations varied by sex or age groups. The effect
estimates of pollutants among females were greater than those
among males, especially the estimate for NO2 was thrice as much
as that among males, although their between-sex differences were
insignificant statistically. The effects among those $65 were
greater than those in the other two groups.
3.3. Effects by seasons
The daily average morbidity in the warm and cool season was
51.860.5 and 50.960.6, respectively. For the entire period, the
Warm season (n = 732)
Cool season (n = 698)
Entire period (n = 1430)
oil are responsible for 66% and 30% of energy supply, respectively
. Crude oil dominated by PM with fine fractions carries more
toxic substance and is easier to penetrate into the circulation
system of humans than coal. The main components of other PM
sources such as raise dust and sand dust are less toxic inorganic
Generally speaking, the smoking habit exerted much more
oxidative and inflammatory influences on males than air pollution
. In China, smoking is much more prevalent among men than
women , this may have affected male health to a greater
degree than environmental factors, therefore we suspect females
were more sensitive to smoking than males. As for age, older
people $65 were more vulnerable to air pollution (especially SO2)
than people in the other two age groups. In terms of their
occupation, percent increase of myocardial infarction exposed to
welding and soldering fumes in the Copenhagen male study
PM10 in developed countries are mainly discharged from
various automobiles including large amount of secondary organic
aerosols. In Tianjin, ground dust, vehicle, cement dust and
incineration are the primary PM10 sources . Coal and crude
Figure 2. Exposure-response relationships (smoothing plots) of air pollutants against cardiovascular morbidity. The x-axis is the
pollutant concentrations; the y-axis is the estimated percent change in cardiovascular mortality; the solid blue lines indicate the estimated mean
percent change in daily mortality outcomes with the dashed lines representing the 95% CI.
Figure 3. ACF and PACF of cardiovascular morbidity (log) and (log+difference). The x-axis is the lag number.
population was 1.1 (95%CI, 0.62.2) , much higher than the
effect estimates on males in this study (Table 3). This is mainly
attributed to the higher concentration PM exposure with more
toxicity in the workplace than public environment.
Though not measured in this study, other factors such as
underlying diet could also have affected our observed results.
Because nutrients with natural chelating properties, including
antioxidants, herbs, minerals, essential amino acids and fiber, can
detoxify human bodies, they can protect humans from oxidative
stress of free radicals derived from air pollutants to some extent.
Vitamins C, E and A in majority of plant and fish foods favored by
residents in Tianjin as an important coastal city can interfere with
or scavenge reactive oxygen species within cells . To better
understand the modification effects of living habits, socioeconomic
and demographic factors on the associations, more individual
features (smoking and eating habit, occupation, education
attainment levels, physical activity, socioeconomic status, etc.)
should be taken into consideration in the future.
As for seasonal effects, some studies indicated that high
temperatures in the warm season and low temperatures in the
cold season are associated with increased cardiovascular mortality
[17,2729]. It is likely that they can also affect cardiovascular
morbidity. Therefore, morbidity data were stratified by the warm
and cool season defined as April-September and the cool season
defined as October-March, respectively. Therefore, this research
also demonstrated that the effect estimates of air pollutants in
Tianjin might be modified by seasons. Exposure patterns may
contribute to this season-specific observation. Personal exposure
was reduced by decreased time spent outdoors caused by heavy
rain. In contrast, people are more likely to go outdoors and open
windows in the cool season with the drier and less variable in
Tianjin. The effect estimates of SO2 and NO2 in the cool season
were much higher than those in the warm season. Significant
associations were observed for PM10 and SO2 in the cool season
(0.24 (0.20, 0.28) and 0.66 (0.35, 0.97), respectively), while the
effect of SO2 in the warm season was insignificant. It may be
caused by coal combustion accounting for the largest proportion of
heat supply in the cool season. Besides, the significant Pearson
correlation coefficient between PM10 and SO2 (0.197, p,0.01)
might partially explain this phenomenon. NO2 was mainly
Mean daily morbidity
0.25 (0.10, 0.39) ,0.001
0.13 (0.01, 0.25) 0.042
0.07 (20.05, 0.21) 0.687
0.12 (20.16, 0.39) 0.844
0.20 (0.09, 0.30) ,0.001
0.47 (0.10, 0.85) 0.019
0.39 (0.21, 0.58) ,0.001
0.11 (20.02, 0.24) 0.566
0.21 (20.10, 0.53) 0.947
0.47 (0.09, 0.85) 0.001
0.57 (0.07, 1.06) 0.022
0.17 (20.16, 0.50) 0.892
0.42 (20.19, 1.03) 0.601
0.26 (0.02, 0.51) 0.009
0.53 (0.31, 0.76) ,0.001
a Current day temperature and humidity (lag 0) and 2-day moving average of air pollutant concentration (lag 01) with 3df of temperature and humidity were used.
Table 4. Mean percent increase (95% CI) of cardiovascular morbidity outcomes associated with 10-mg/m3 increase in air pollutant
concentrations by season, 20082011a.
0.15 (20.19, 0.50) p = 0.869
0.24 (0.01, 0.47) p = 0.046
0.21 (20.20, 0.63) p = 0.667
0.24 (0.20, 0.28)* p,0.001
0.66 (0.35, 0.97)* p = 0.001
0.71 (0.15, 1.27) p = 0.033
0.19 (0.08, 0.31) p = 0.016
0.43 (0.03, 0.84) p = 0.037
0.52 (20.09, 1.13) p = 0.424
a We used current day temperature and humidity (lag 0) and 2-day moving average of air pollutant concentration (lag 01), and applied 3df to temperature and humidity.
*Significantly different from the warm season (p,0.05).
0.153 (20.191, 0.498)
0.153 (20.191, 0.498)
0.154 (20.190, 0.499)
0.153 (20.191, 0.498)
0.156 (20.189, 0.502)
0.153 (20.192, 0.498)
0.158 (20.187, 0.504)
0.152 (20.192, 0.497)
a We used 2-day moving average (lag 01) of PM10 concentration, and current day temperature and humidity (lag0).
released from vehicle emission and partially from coal combustion,
which may account for the insignificant relationship between NO2
and morbidity. The constituents of the complex mix of PM10 may
vary by seasons, different from the gaseous pollutants (SO2 and
There are some limitations in our analyses. Ozone was not
included in our studies due to a lack of monitoring. Our ability to
separate the independent effect of each pollutant was limited by
high correlations between PM and gaseous pollutants including
SO2 and NO2 in Tianjin. Moreover, the role of each specific
component of air pollution should be examined to determine the
combination of particles responsible for the increases in
environment-induced health concerns. These investigations are
paramount for policy makers to carry out improved interventions that
will impact health hazards related with air pollutants, especially on
the increased risks of cardiovascular morbidity.
0.151 (20.194, 0.495)
In summary, we found that PM10 and SO2 were significantly
associated with cardiovascular morbidity in the cool season in
Tianjin in this time-series analysis. The mean percent increases
(95% CI) of cardiovascular morbidity outcomes per 10 mg/m3
increase in PM10 and SO2 concentrations by season were 0.24
(0.20, 0.28) and 0.66 (0.35, 0.97), respectively. Besides
modification effect of a season, individual features (sexes, ages) might also
interfere with the effect estimates of air pollutants. Females were
more sensitive than males to air pollutants. The effects of air
pollutants on elder people ($65) were greater than those ,65.
These data can enable policy makers to enforce or improve
existing legislation that control air pollution after weighing the
disadvantages of potentially slowing rapid economic development.
Cubic nature spline
0.153 (20.191, 0.498)
a Current day temperature and humidity (lag 0) and 2-day moving average of PM10 (lag 1) are used, 3 df for temperature and humidity is applied.
We cordially thank the Centers for Disease Control and Prevention of
Urban Districts in Tianjin for assisting us to collect medical data.
Performed the experiments: LT. Analyzed the data: KL LT QZ. Wrote the
paper: LT QZ KL.
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