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Air Pollution

Interactions Between Air Pollution and Obesity on Blood Pressure and Hypertension in Chinese Children

Dong, Guang-Huia,b; Wang, Jingc; Zeng, Xiao-Wena,b; Chen, Lihuad; Qin, Xiao-Dib; Zhou, Yangb; Li, Mengb; Yang, Mingane; Zhao, Yangf; Ren, Wan-Huig; Hu, Qian-Shengb

Author Information
doi: 10.1097/EDE.0000000000000336


Childhood hypertension has become a widely investigated topic within the past decade due to its increasing prevalence,1 and the strong relation of hypertension with environmental factors, such as air pollution and obesity suggests that the hypertension prevalence will be escalating.2 Accumulating evidence suggests that both short-term and long-term exposure to ambient air pollutants may increase blood pressure and result in a hypertensive response.3–7 Also, the association of higher blood pressure with obesity has been documented in numerous reports.8–10 A recent clinical controlled study conducted on 348 participants ages ≥25 years in the United States showed that particles with an aerodynamic diameter ≤2.5 (PM2.5) exposure at lags 2 and 3 was associated with an increased risk for elevated pulse pressure among those who were determined to be obese according to their body mass index (BMI),11 indicating obesity may be a modifier of the association between ambient air pollution exposure and blood pressure.

However, the MEDLINE database shows very little evidence of epidemiologic evaluation of the effect of coexposure to ambient air pollution and obesity on blood pressure and hypertension in children, who are more susceptible to the health effects of environmental exposures than adults during the periods of development after birth. One possible reason for the lack of such an evaluation is due to the lack of study samples exposed to both air pollution and obesity. The Seven Northeastern Cities (SNEC) study, conducted in Liaoning Province in Northeastern China in 2012, however, provides an opportunity to examine the synergistic effects of air pollution exposure and obesity on blood pressure and hypertension in children. The SNEC study included children exposed to higher levels of air pollution than reported in the literature. Furthermore, with rapid economic development and lifestyle changes, childhood obesity has become epidemic in China in the past two decades.

Therefore, we hypothesized that obesity would modify the association between air pollution exposure and children’s blood pressure and hypertension in the SNEC study, with a stronger association of air pollution exposure with blood pressure in overweight or obese children than in children of normal weight.


Study Cities Selection and Subject Recruitment

The SNEC study is a cross-sectional study of health outcomes in children exposed to ambient air pollutants. There was a total population of more than 20 million people residing in 14 cities in Liaoning province in Northeastern China. To maximize the inter- and intra-city gradients of the pollutants of interest and minimize the correlation between district-specific ambient pollutants, in April 2012 seven cities—Shenyang, Dalian, Anshan, Fushun, Benxi, Liaoyang, and Dandong in Liaoning province—were selected as study sites, according to the level of air pollution measured in 2009–2011. The total number of urban districts from the seven cities was 24, including five from Shenyang, four from Dalian, four from Fushun, three from Anshan, three from Benxi, three from Dandong, and two from Liaoyang. In each of the 24 study districts, there was only one available municipal air monitoring station that generated air pollution data. One elementary school and one middle school within 1 km of air monitoring sites were randomly selected, and then one or two classrooms were randomly selected from each grade of the selected schools. In any classroom targeted for participation, all children who had lived in the district for at least 2 years before the start of study were included in the study. Individual air pollution exposure was estimated using the measurements from the municipal air monitoring station in each school district. In China, primary schools admit students restrictively basing the criteria on geographical boundaries, and the policy forbids selecting trans-regionally schools for children. Therefore the monitoring station, which was the only station in the selected child’s school district, was the closest station to the child’s home. Furthermore, the distance between each school and the nearest air pollution monitoring station that measured the pollutants was estimated by geographic information systems software. In addition, the time for each child to walk from his or her home to school was used as a proxy for the estimate of the distance from the child’s home address to the nearest monitoring station. The design and conduct of this investigation were in accordance with the World Medical Association Declaration of Helsinki-Ethical Principles for Medical Research Involving Human Subjects, and ethical approval was obtained from the Human Studies Committee of Sun Yat-Sen University. Before data collection, a written informed consent form was obtained from each participant and their parents.

Blood Pressure Measurements

Based on the procedures set by the American Academy of Pediatrics,12 the sitting blood pressure was measured three times, 2 minutes apart, using a standardized mercury-column sphygmomanometer, as described previously.5,13 Hypertension in children was defined as average systolic and diastolic blood pressures that were ≥95th percentile for gender, age, and height, according to the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents.12

Definition of Obesity and Overweight

Height and weight of all participants were measured using a standardized protocol from the World Health Organization (WHO),14 in which height is measured to the nearest 0.5 cm, with the participant’s back against a wall, no shoes, eyes looking straight forward, with a right-angle triangle resting on the scalp and against the wall. Weight was measured after the WHO protocol, with a lever balance to the nearest 100 g on participants without shoes and in minimal undergarments. BMI was then calculated using the gathered weight data (kg) and dividing it by height (m) squared (kg m−2). The BMI distribution was stratified by age and sex using the Centers for Disease Control and Prevention (CDC) BMI growth charts with a 1-month age interval.15 According to the CDC standards, overweight is defined as a “BMI greater than the age and sex-specific 85th percentile, and obesity, as BMI greater than the age and sex specific 95th percentile.”

Parental education was defined as the highest level of education completed by either parent. Passive smoking exposure was defined as living with someone who smokes cigarettes daily in the home. Breastfeeding exposure was defined as mainly breastfed for 3 months or more. Area of residence per person was calculated based on residence area and number of family members.

Ambient Air Pollution

In each of the selected study districts, there was one municipal air monitoring station located 1 km from the study participants’ homes. Measurements of particle with aerodynamic diameter ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) concentrations from 2009 to 2012 were obtained at the stations, using uniform methods and quality assurance. These stations were placed according to their distances from major roads, industrial sources, buildings, or residential sources of emissions from the combustion of coal, waste, or oil, assuring that the air pollution measurements obtained from the stations reflected the background air pollution levels. A detailed description of air pollution exposure measurements are shown in eAppendix 1 ( The measurements were taken strictly after the methodological standards set by the State Environmental Protection Administration of China,16 and were used to estimate long-term exposure for the participants.

Concentrations of each pollutant were assessed continuously and reported hourly: PM10 was assessed by beta-attenuation, SO2 was assessed by ultraviolet fluorescence, NO2 was assessed by chemiluminescence, and O3 was assessed by ultraviolet photometry.17 We calculated average daily concentrations of PM10, SO2, NO2, and O3 during the days when at least 75% of the hourly concentrations were available at each monitoring station, after excluding abnormal concentrations. Exposure parameters were 4-year averages (2009–2012) of the 24-hour concentrations of PM10, SO2, and NO2, and 8-hour O3 concentrations measured from 10:00 AM to 6:00 PM in each district.

Daily mean temperature of each city was collected on the dates of the collection of blood pressure measurements to adjust the exposure effect on hypertension and blood pressure.

Statistical Analysis

We assessed the association of ambient air pollutants with blood pressure using generalized additive models. To investigate the relation between hypertension and ambient air pollution, we conducted a two-level binary logistic regression model with children being the first-level units and districts being the second-level units, as described previously.18 In brief, at the child level, we modeled the logit of the prevalence of hypertension by BMI categories and other covariates. At the district level, the random coefficients were regressed on the district-specific pollutant level to explain the variations of the district-specific intercepts and coefficients. In the two-level binary logistic regression model, four ambient air pollutants—PM10, SO2, NO2, and O3—were considered as the key exposure variables. The key covariates considered were three BMI categories: normal weight, overweight, and obese-defined previously according to the CDC criterion, and 11 additional covariates (X in the equations below) to reduce confounding including age, sex, parental education, low birth weight, premature birth, breastfeeding, income, passive smoking exposure, home coal use, exercise time, area residence per person, family history of hypertension, distance from the monitor to school, distance from the children’s home to school, temperature, and district. All analyses were conducted using the GLIMMIX procedure using the SAS software (version 9.2; SAS Institute, Cary, NC).


There were a total of 10,428 children randomly selected from 24 districts of the seven cities, of whom 9,567 completed the survey and examination resulting in an overall response rate of 92%. We further excluded 213 children with less than 2 years of residence in their district. In the final sample of 9,354 children, the average age was 10.9 years (SD = 2.6 years; ranging from 5 to 17), and 4,771 (51%) were males. The prevalence of hypertension was 14%. The characteristics of the survey participants in this study, stratified by BMI, are shown in Table 1. In the study sample, 16% (1,460) of the children were overweight and 17% (1,571) were obese, with a higher overweight or obese rate in males (16% overweight and 24% obese) than in females (15% overweight and 10% obese). The prevalence of hypertension increased with BMI with 11% for children with a normal weight, and 17% and 23% in overweight and obese children (Zfor trend = 13.1; P < 0.01). Among all children in the study, the average area of residence per person was 22.7 m2 (SD = 10.2 m2); average time of exercise per week was 7.6 hours (SD = 7.7 hours); average distance from monitor to school was 549.3 m (SD = 214.8 m); average walking time from home to school was 15.3 minutes (SD = 9.6 minutes); and mean temperature during the investigation was 14.7°C (SD = 6.0°C).

Characteristics of the Children in the Seven Cities by BMI

Table 2 presents the average concentrations of the four pollutants, PM10, NO2, SO2, and O3, measured between 2009 and 2012, and compares them to the WHO guidelines and Chinese National Ambient Air Quality Standards. The PM10 levels exceeded the WHO standard in all districts, while 79% of all districts exceeded the PM10 limit levels dictated by the Chinese National Ambient Air Quality Standards. eTable 1 ( shows the correlation coefficients between the four pollutants.

Distribution of the 4-Year Mean Concentration of Air Pollutants Across 24 Districts of Seven Cities, China, from 2009 to 2012 (μg/m3)

The association between exposure to each pollutant and the prevalence of hypertension was consistently stronger among overweight or obese children than among children with a normal weight (Table 3), with point estimates ranging from 1.16 to 2.91 for obese children, 1.12 to 2.05 for overweight children, and 0.82 to 1.21 for children with a normal weight. BMI modified the associations of PM10, SO2, and O3 with hypertension (P < 0.01). When we stratified the association by gender, these findings remained in both gender groups.

Adjusted OR and 95% CI of Hypertension and Yearly Concentrations in Air Pollutants for Children in Three BMI Categoriesa

Table 4 presents the associations of long-term ambient air pollutant exposure with arterial blood pressure modified by BMI. Exposure to each ambient air pollutant, except for NO2, was associated with higher SBP and DBP levels and the strength of the association increased with BMI. For example, increase in SBP for PM10 in different groups of children (obese, overweight, and normal weight) was 2.15 mmHg (95% confidence interval [CI] = 1.07, 3.22 mmHg), 1.99 mmHg (95% CI = 1.07, 2.90 mmHg), and 1.10 mmHg (95% CI = 0.67, 1.54 mmHg), respectively. Increase in DBP for PM10 was 2.43 mmHg (95% CI = 1.54, 3.31 mmHg), 1.97 mmHg (95% CI = 1.15, 2.79 mmHg), and 1.22 mmHg (95% CI = 0.85, 1.59), respectively.

Estimated Absolute Increase in Arterial Blood Pressure (mmHg) with 95% CI per Interquartile Range Width of Long-term Exposure to the Air Pollutants in Three BMI Categoriesa

To assess potential effect modification by school age, we stratified the analysis by school age group. The associations of air pollutants with hypertension and blood pressure were much higher in elementary school-age children than those in middle-school-age children (eTable 2; However, the interaction between overweight/obesity and air pollutions was also observed among these two groups (eTable 3;

We calculated the average exposure in 5 days before blood pressure measurement as the short-term exposure and analyzed its effect on blood pressure and found the effect was positive (eTable 4; In addition, we assessed the effect of modification by obesity on the acute effect of air pollution on blood pressure and found that obesity enhanced the association of short-term air pollution exposure (5-day mean) with hypertension and blood pressure (eTable 5;

There was evidence of an association of home coal use and passive smoke exposure with hypertension and blood pressure (eTable 6; and such association also varied with BMI (eTable 7; In particular, the association with home coal use among the overweight and obese children was consistently stronger than among children with a normal weight.


This study showed that obesity modified the association of air pollution exposure with blood pressure and hypertension in children from Liaoning Province in northeast China. The observed associations in the study districts were stronger among obese and overweight children than among children with a normal weight, indicating that obesity was associated with increased susceptibility to adverse health effects of ambient air pollution.

It is difficult to compare the results of the present investigation with other studies because the literature is sparse with respect to the effect of interaction between obesity and long-term ambient air pollution exposure on blood pressure and hypertension in children. In the Medline database, we only found two relevant human studies using obesity as a modifier of the association between exposure to air pollution and blood pressure.7,11 The first one was part of the Healthy Environments Partnership study conducted on 348 biomarker adults at or above 25 years in 2002–2003 in Detroit, Michigan in the United States, assessed the acute effects of exposure to fine particulate matter (PM2.5) on blood pressure in adults.11 The results showed that after adjusting for the covariates, PM2.5 (at lags 2 and 3) was associated with an increased risk for elevated pulse pressure among adults who were obese with a BMI ≥ 30 kg/m2. For example, in obese adults, a 10 μg/m3 increase in daily PM2.5 was associated with a 4.2 mmHg increase in pulse pressure at lag 2 (P < 0.003) and with a 3.3 mmHg increase in pulse pressure among adults with a normal weight. Compared to the Healthy Environments Partnership study, this study is a first attempt to use a large population-level study design to explore the influence of obesity on blood pressure-related health effects of long-term air pollution in children. The second one was a study we conducted in 11 districts selected at random from three cities in Liaoning Province in Northeastern China in 2009.7 In that study, we examined the effect of interaction between obesity and air pollution on blood pressure and hypertension in 24,845 Chinese adults ages ≥18 years, and found the associations between ambient air pollutant’s yearly concentrations and blood pressure and hypertension were consistently larger in overweight/obese adults than in adults with a normal weight. However, these interaction effects between air pollution and obesity on hypertension were only apparent for O3, but not for other pollutants (e.g., PM10 and SO2).7 Compared with the two published studies in adults, children may be more susceptible than adults to the same environmental factors. This study not only explored in children the modification by obesity on the association between blood pressure and O3 but also PM10 and SO2. Our findings support the hypothesis that obesity amplifies the symptomatic response to long-term exposure to ambient air pollution on blood pressure measures and prevalence of hypertension.

These findings were also parallel to those in the studies on the interaction between obesity and air pollution on cardiovascular disease (CVD). Chen et al.19 examined the PM2.5-mediated acute effects on heart rate variability and heart rate using 10 24-hour and 13 48-hour ambulatory electrocardiogram recordings collected from 18 boilermakers (39.5 ± 9.1 years of age) exposed to high levels of metal particulates. The greater autonomic cardiac responses to metal particulates in obese workers than in those of normal weight supported the hypothesis that obesity would impart greater susceptibility to acute cardiovascular effects of fine particles. The Veterans Affairs Normative Aging Study,20 a recent population-based prospective cohort study on 580 men in the United States, examined the effects of ambient air pollutants on heart- rate-corrected QT interval, an electrocardiographic marker of ventricular repolarization, and whether these associations were modified by obesity. The results provided evidence of effect modification by obesity on the association among corrected QT interval, black carbon, and NO2 exposure (both as the cumulative and 4-hour lag effect), with stronger associations in obese participants than in those of normal weight. In the Women’s Health Initiative Observational Study, Miller et al.21 evaluated long-term exposures to air pollution and the incidence of CVD among 65,893 postmenopausal women in 36 US metropolitan areas from 1994 to 1998, with a median follow-up of 6 years. The results indicated that the association between PM2.5 concentrations and CVD events was larger for overweight/obese participants than for normal weight participants. The effects of air pollution on CVD incidence increased with BMI increasing (Pfor trend = 0.004). Because hypertension has been identified as a major risk factor for CVD and other vascular diseases,22,23 and usually precedes CVD, findings provided by this study could serve as useful input for human risk assessments and related disease analyses.

The mechanism underlying the synergistic effects of ambient air pollution and obesity on blood pressure and hypertension is not clear. One possible explanation is that systemic inflammation was a widely known effect of ambient air pollution that has been shown in many studies. Ambient air pollutant exposure had been associated with an influx of inflammatory cells into the lungs,24 enhanced production of pro-inflammatory cytokines by alveolar macrophages,25 elevated systemic blood viscosity,26 and increased production of inflammatory cells by bone marrow.27 Air pollution has also been associated with artery narrowing,28 arterial reactivity,29 atherosclerotic lesions,30,31 and C-reactive protein,26,32,33 an inflammatory marker that has been shown to be predictive of CVD including hypertension.34,35

An increasing number of studies have shown that obesity is associated with dysfunction of the adipose tissue characterized by enlarged hypertrophied adipocytes, increased infiltration by macrophages, and variations in secretion of adipokines and free fatty acids, and that these changes result in chronic vascular inflammation, oxidative stress, activation of the renin–angiotensin–aldosterone system and sympathetic response, and ultimately lead to hypertension.2 As obesity and air pollution are both associated with increased inflammation, and hypertension is a chronic inflammatory state aggravated by factors that promote inflammation at the level of vasculature and adipose tissue,34,35 these studies hypothesized that obese people would be more susceptible to the inflammatory effects of ambient air pollutants, leading to a higher prevalence of hypertension. This partially explains the interaction effect in our study. One recent study conducted in 44 senior citizens in St. Louis, Missouri, reported that obesity enhanced associations between air pollution and markers of systemic inflammation, including C-reactive protein, interleukin-6, and white blood cells.32 Some experimental studies have indicated that the synergistic interaction between air pollution and obesity on inflammation may occur by altering the balance between M1 and M2 adipose tissue macrophages in adipose tissue.36 Furthermore, the balance between M1 and M2 macrophages in end organs appears to be an important aspect of and contributes to the inflammation seen in atherosclerosis and obesity.37 Thus, inflammatory diseases such as hypertension that have been shown to be strongly associated with air pollution exposure may be caused not only by sustained pro-inflammatory effects but also by the failure of anti- inflammatory mechanisms.

In addition, temperature may confound the association between O3 exposure and prevalent hypertension and DBP. Hoffmann et al.38 observed that O3 and higher temperature were associated with a decrease in SBP in participants with type 2 diabetes mellitus. Weinhold39 pointed out that the opposing effects of air pollutants and heat exposures could plausibly exist in independent ways and might not cancel one another out.

Although this study provides new insight into the influence of obesity on associations between air pollution and blood pressure and hypertension in children, it has several limitations. First, our findings cannot establish a cause-and-effect relationship between long-term ambient air pollution and blood pressure and hypertension because of the nature of a cross-sectional study design that lacks temporal ordering of study variables. Selection and information biases are possible. However, we have attempted to reduce these biases as much as possible through strict quality control and assurance procedures. Second, there may be possible misclassification of the behavioral risk factors (passive smoking, and exercising) due to the limited nature of the response format (yes or no) of survey questions. Third, we used the 4-year average concentrations as the long-term exposure to PM10, SO2, NO2, and O3 because they likely reflected the background air pollution levels in the study city as described in the Methods section. Unfortunately, traffic-related air pollution exposure data is not available to us. Detailed spatial and temporal information is needed to develop a better long-term exposure assessment. Addressing spatial variations of traffic-related air pollution effects in our future studies would provide more insight into the interaction effect. Fourth, confounding from noise was not assessed in this study due to the lack of the related data. However, background noise had a minimal effect in our study because in China roads are located away from noise-sensitive areas, such as schools or hospitals, and placed near nonsensitive areas, such as businesses or industrial plants. Nonetheless we are committed to incorporating the confounders and assessing their effects in our future studies.

In conclusion, our results indicate that an increase in ambient air pollution was associated with increased blood pressure and hypertension among children, and that this association is more severe in overweight/obese children. Obesity may be substantially associated with the susceptibility to adverse health effects of airborne pollutants.


We are grateful to the participants in the Seven Northeastern Cities, who were very generous with their time and assistance. We would also like to thank the anonymous reviewers for their very helpful comments.


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