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Article

Prolonged Exposure to Air Pollution Increases Periodontal Disease Risk: A Nationwide, Population-Based, Cohort Study

by
Han-Jie Lin
1,†,
Stella Chin-Shaw Tsai
1,2,†,
Frank Cheau-Feng Lin
3,4,
Yi-Chao Hsu
5,
Shih-Wei Chen
1,2,
Ruey-Hwang Chou
6,7,8,9,
Cheng-Li Lin
10,
Chung Y. Hsu
11 and
Kuang-Hsi Chang
12,13,14,*
1
Department of Otolaryngology, Tungs’ Taichung MetroHarbor Hospital, Taichung 435, Taiwan
2
Rong Hsing Research Center for Translational Medicine, College of Life Sciences, National Chung Hsing University, Taichung 402, Taiwan
3
School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
4
Department of Thoracic Surgery, Chung Shan Medical University Hospital, Taichung 402, Taiwan
5
Institute of Biomedical Sciences, Mackey Medical College, New Taipei City 252, Taiwan
6
Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404, Taiwan
7
The Ph.D. Program of Biotechnology and Biomedical Industry, China Medical University, Taichung 404, Taiwan
8
Center for Molecular Medicine, China Medical University Hospital, Taichung 404, Taiwan
9
Department of Medical Laboratory and Biotechnology, Asia University, Taichung 413, Taiwan
10
Management Office for Health Data, China Medical University Hospital, Taichung 404, Taiwan
11
Graduate Institute of Clinical Medical Science, China Medical University, Taichung 404, Taiwan
12
Department of Medical Research, Tungs’ Taichung MetroHarbor Hospital, Taichung 435, Taiwan
13
Center for General Education, China Medical University, Taichung 404, Taiwan
14
General Education Center, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli 356, Taiwan
 
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*
Author to whom correspondence should be addressed.
†
First authors, Han-Jie Lin and Stella Chin-Shaw Tsai have contributed equally to this work.
Atmosphere 2021, 12(12), 1668; https://doi.org/10.3390/atmos12121668
Submission received: 17 September 2021 / Revised: 17 November 2021 / Accepted: 9 December 2021 / Published: 12 December 2021
(This article belongs to the Special Issue Outdoor Air Pollution and Human Health)
Versions Notes

Abstract

:
(1) Background: No association between air pollution and periodontitis has yet been shown. Thus, we merged two nationwide databases to evaluate the risk of periodontitis in Taiwanese residents with long-term exposure to air pollution. (2) Methods: We conducted a nationwide retrospective cohort study using the Longitudinal Generation Tracking Database and the Taiwan Air Quality-Monitoring Database. The daily average air pollutant concentrations were categorized into quartiles (Q1, Q2, Q3, and Q4). We carried out Cox proportional hazards models to compute the hazard ratios of periodontitis, with 95% confidence intervals, in Q2–Q4 of the daily average air pollutant concentrations, compared with Q1. (3) Results: the adjusted HR (95 CI%) for periodontitis in Q2–Q4 increased with increased exposure to SO2, CO, NO, NO2, NOX, PM2.5, and PM10 from 1.72 (1.70, 1.76) to 4.86 (4.78–4.94); from 1.89 (1.85–1.93) to 2.64 (2.59–2.70); from 1.04 (1.02–1.06) to 1.52 (1.49–1.55); from 1.61 (1.58–1.64) to 2.51 (2.47–2.56); from 1.48 (1.45–1.51) to 2.11 (2.07–2.15); from 2.02 (1.98–2.06) to 22.9 (22.4–23.4, and from 2.71 (2.66–2.77) to 17.2 (16.8–17.6), respectively, compared to Q1. (4) Conclusions: Residents in Taiwan with long-term exposure to higher levels of air pollutants had a greater risk of periodontitis.

1. Introduction

In recent decades, air pollution has become an important global issue, being highly correlated with human economic activity and climate change [1]. Many countries have seen rapid industrialization and population density, and there is growing evidence that substantial air pollutant exposure is associated with changes in the levels of inflammatory cytokines and biomarkers, including C-reactive protein (CRP); interleukins (ILs)-1β, 6, 8, 10; tumor necrosis factor (TNF)-α; vascular cell adhesion molecule-1 (VCAM-1); intercellular adhesion molecule-1 (ICAM-1); and reactive oxygen species (ROS) or reactive nitrogen species [2,3,4,5,6,7,8,9]. Inflammatory mediators such as IL-6 and TNF-αmay induce destruction of soft tissues near the teeth by stimulating the production of enzymes [10,11]. In addition, inflammatory cells are recruited, and adhesion to the vascular endothelium is enhanced [12]. Endothelial barrier dysfunction follows, allowing the facile translocation of inflammatory mediators [12,13,14]. Eventually, systemic inflammatory reactions are promoted, accompanied by multiorgan responses, such as suppressed vasodilatation, enhanced endothelial senescence, increased smooth muscle proliferation, and bone marrow activation [15,16,17,18]. Moreover, evidence has demonstrated that long-term exposure to ambient air pollution may be linked to adverse health conditions, including asthma, cardiovascular diseases, stroke, elevated cancer risk, neurological disorders, and increased morbidity and mortality [19,20,21,22,23,24,25,26,27].
Periodontal diseases, namely gingivitis and periodontitis, involve a protracted inflammatory process characterized by gingival swelling, redness, and irritability, as in gingivitis, or even by loss of supportive connective tissue or bone, as in periodontitis. These processes are related to chronic inflammatory conditions of oxidative stress [28,29,30]. The most recognized causes of periodontal diseases include dental biofilm plaque and peri-implant diseases [31,32,33]. Both of these conditions stimulate antimicrobial activity and ROS, which not only eradicate intrusive pathogens but also act as a double-edged sword, causing overwhelming oxidant load [34,35,36]. In our perspectives, evidence from various studies could be summarized into three pathogenic mechanisms of periodontal diseases: (1) promoted systemic and local inflammatory response [37]) iron and heme sequestration, resulting in dysregulation of intracellular homeostasis [38], (2) augmented inflammation in the presence of oral microbiota, especially Porphyromasgingivalis [39]. Local inflammatory responses, with systemic extension and upregulated ROS, lead to various pathological changes, resulting in the destruction of host tissues and damage to intracellular biomolecules and the cell membrane [37,40].
However, no association between air pollution and periodontitis has yet been shown. Thus, we merged two national nationwide databases to evaluate the risk of periodontitis in Taiwanese residents with long-term exposure to air pollution.

2. Materials and Methods

2.1. Data Source

To explore the risk of periodontitis associated with air pollution in Taiwan, we conducted a nationwide retrospective cohort study using the Longitudinal Generation Tracking Database (LGTD 2000) and the Taiwan Air Quality-Monitoring Database (TAQMD). The LGTD contains the data of two million individuals randomly selected from the National Health Insurance Research Database (NHIRD), which was established in 1995 and contains the comprehensive healthcare data of approximately 99% of Taiwanese residents, with information on outpatient visits, ambulatory care, and inpatient hospitalization, as well as diagnostic codes formatted according to the 9th and 10th revisions of the International Classification of Diseases, Clinical Modification (ICD-9-CM, ICD-10-CM). In 2016, Taiwan’s Ministry of Health and Welfare established the Health and Welfare Data Center (HWDC) to standardize the management of available healthcare data. The TAQMD has been maintained by the Taiwan Environmental Protection Agency (EPA) since 1998 and includes the daily concentrations of air pollutants from 74 ambient air quality-monitoring stations across Taiwan. We connected the residential areas of the insured population from the LGTD with the air pollutant information from the nearest TAQMD station. The study was approved by the Central Regional Research Ethics Committee of China Medical University, Taichung, Taiwan (CMUH109-109-REC2-031).

2.2. Study Participants

People residing in the vicinity of an air quality-monitoring station and covered by the NHI were selected as the study population. Their healthcare data from January 2005 to 31 December 2016 were then extracted. Each subject was monitored from the index date (2005/01/01) until a new diagnosis of periodontitis was made or until the subject was censored due to loss to follow-up, death, withdrawal from insurance, or the end of follow-up on 31 December 2017.The index date was defined as the date on which the subjects entered the LGTD. Individuals aged under 18 years were excluded, as were those with missing data on pollutant levels. Those who had ever been diagnosed with periodontitis before the baseline were also excluded.

2.3. Exposure Collection and Outcome Measurement

A total of 74 air pollution monitoring stations are located on Taiwan’s main island. The location of each monitoring station is determined by the population density. Participants’ residential addresses were not available from the TNHI program in compliance with the Personal Data Protection Act. Thus, the residential area of the study subjects was defined by the location of their most common clinic or hospital for cold diagnosis (ICD-9-CM 460). Each resident was assigned a pollutant-exposure level in accordance with the information received from the monitoring station located in the residential area. The air pollutants of interest were SO2, CO, NO, NOX, NO2, PM2.5, and PM10. The daily concentrations of air pollution data were measured automatically by the monitoring stations. The outcome event was the diagnosis of periodontitis (ICD-9-CM codes 5233, 5234; ICD-10-CM codes K0520, K0521, K0522, K0530, K0531, and K0532). The endpoint of follow-up was the date of withdrawal from the NHI program, development of periodontitis, or 31 December 2017, whichever occurred first. The daily average air pollutant concentrations were categorized into quartiles, with three cut-off points (25th, 50th, and 75th percentiles) as follows: SO2 concentration (Q1: <2.71 ppb, Q2: 2.71–3.26 ppb, Q3: 3.26–3.79 ppb, and Q4: >3.79 ppb); CO concentration (Q1: <0.38 ppm, Q2: 0.38–0.46 ppm, Q3: 0.46–0.56 ppm, and Q4: >0.56 ppm); NO concentration (Q1: <2.74 ppm, Q2: 2.74–4.24 ppm, Q3: 4.24–6.65 ppm, and Q4: >6.65 ppm); NO2 concentration (Q1: <13.6 ppm, Q2: 13.6–17.2 ppm, Q3: 17.2–20.8 ppm, and Q4: >20.8 ppm); NOX concentration (Q1: <16.3 ppm, Q2: 16.3–21.6 ppm, Q3: 21.6–27.3 ppm, and Q4: >27.3 ppm); PM2.5 concentrations (Q1: <17.5 μg/m3, Q2: 17.5–206 μg/m3, Q3: 3, 20.6–27.2 μg/m3, and Q4: >27.2 μg/m3); and PM10 concentrations (Q1: <36.5 μg/m3, Q2: 36.5–42.9 μg/m3, Q3: 42.9–52.6 μg/m3, and Q4: >52.6 μg/m3). The two-year average concentrations of air pollutants were calculated within two years before the PD diagnosis date or index date.

2.4. Confounding Factors

To control for covariates, the confounding factors we considered were age, sex, population density level, and comorbidities of alcohol abuse/dependence (ICD-9-CM code 303, 3050, 30300, 30301, 30302, 30303, 30390, 30391, 30392, 30393, 30500, 30501, 30502, 30503; ICD-10-CM code F10120, F10129, F10220, F10229, F1020, F1021, F1010), tobacco abuse/dependence (ICD-9-CM code 3051; ICD-10-CM code F17200, F17201, F17210, F17211, F17220, F17221, F17290, F17291), chronic obstructive pulmonary disease (ICD-9-CM code 490–492, 494, and 496; ICD-10-CM code J40, J41, J43, J44, J47), diabetes mellitus (DM, ICD-9-CM code250; ICD-10-CM codeE08, E09, E10, E11, E13),rheumatoid arthritis(RA, ICD-9-CM code 714; ICD-10-CM code J45), obesity (ICD-9-CM code 278; ICD-10-CM code E65, E66, E67, E68)and asthma (ICD-9-CM code 493; ICD-10-CM code J45). Population density was categorized into four levels from the highest to the lowest density.

2.5. Statistical Analysis

In descriptive statistics, the distributions of gender, age, comorbidity, and periodontitis were presented as percentages (%), whereas air pollutants were presented as mean (standard deviation). The chi-squared test was used to test the differences among the quartiles of the daily average concentrations of SO2, CO, NO, NO2, NOX, PM2.5, and PM10 at each population density level. The incidence of periodontitis per 1000 person-years was then calculated. We carried out Cox proportional hazards models to compute the hazard ratios (HRs) of periodontitis, with 95% confidence intervals (CIs), in Q2–Q4 of the two-year average air pollutant concentrations, compared with Q1. Multivariable models were adjusted for age, sex, population density level, monthly income, comorbidities of alcohol abuse/dependence, tobacco abuse/dependence, chronic obstructive pulmonary disease, asthma, diabetes, obesity, and rheumatoid arthritis.
Furthermore, we considered each pollutant level as a continuous measure in multi-variate analyses and computed the HRs of periodontitis, with 95% CIs in Appendix A.
In Appendix B, we have re-defined the PD patient via diagnosis of periodontitis (ICD-9-CM codes 5233, 5234; ICD-10-CM codes K0520, K0521, K0522, K0530, K0531, and K0532) and with two dental examinations within a year before PD diagnosis.
All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). A two-sided p-value < 0.05 was considered significant.

3. Results

3.1. Demographic Characteristics and Air Pollutants of Study Population

A total of 292,263 participants were enrolled in the study. The proportion of females was slightly higher than that of males (55.1% vs. 44.9%), and the mean age at enrollment was 41.1 ± 16.2 years. The proportion of participants who lived in areas with the highest population density was 59.9%. There were 4512 (1.54%) participants who showed alcohol abuse, 47,458 (16.2%) who showed tobacco abuse, and 43,818 (15.0%) with chronic obstructive pulmonary disease. The two-year average concentrations of SO2, CO, NO, NO2, NOx, PM2.5, and PM10 were 4.42 ± 1.68 ppb, 0.60 ± 0.23 ppm, 8.69 ± 8.77 ppm, 28.6 ± 14.0 ppm, 30.2 ± 7.88 µg/m3 and 54.3 ± 12.8 µg/m3, respectively. At the end of the study, 126,167 participants had experienced periodontitis during the study period. The mean follow-up time was 11.4 ± 2.80 years (Table 1).

3.2. Population Density among the Daily Average Concentration of Air Pollutants

As shown in Table 2, the quartiles of the two-yearaverage concentrations of SO2, CO, NO, NO2, NOX, PM2.5, and PM10 showed significant differences among the four levels of population density (p < 0.001). Participants residing in the highest population density were exposed to the highest concentrations of CO (29.2%), NO (30.0%), and NOX (28.9%).

3.3. Risk of Periodontitis Based on the Quartiles of Daily Average Air Pollutant Concentrations

The incidence rates and hazard ratios (95% CI) of periodontitis for SO2, CO, NO, NO2, NOX, PM2.5, and PM10 are presented in Table 3 and stratified into quartiles. From Q1 to Q4, the incidence rates of periodontitis for SO2, CO, NO, NO2, NOX, PM2.5, and PM10 increased from 27.9% to 67.2%, from 24.6% to 55.1%, from 27.8% to53.0%, from 25.1% to 58.6%, from 25.9% to 56.4%, from 20.9% to 62.6% and from 22.1% to 54.5% person-years, respectively. After controlling for age, sex, population density, and comorbidities, the adjusted HR (95 CI%) for periodontitis in Q2–Q4 increased with increased exposure to SO2, CO, NO, NO2, NOX, PM2.5, and PM10 from 1.28 (1.26, 1.30) to 3.39 (3.34–3.44); from 1.58 (1.55–1.61) to 2.77 (2.73–2.82); from 1.34 (1.32–1.36) to 2.30 (2.26–2.33); from 1.63 (1.60–1.65) to 3.02 (2.97–3.07); from 1.31 (1.28–1.33) to 4.25 (4.18–4.32, and from 1.69 (1.66–1.72) to 3.17 (3.12–3.22), respectively, compared to Q1.

4. Discussion

The present retrospective cohort study was the first to assess the association between long-term air pollutant exposure and periodontitis using a large panel database. The results showed that urban resident exposed to higher level of the investigated air pollutants (Table 2). These findings corroborate those from previous studies showing that air pollutant levels are significantly associated with population density, as higher levels of air pollution are observed in metropolitan areas than in rural areas [41,42]. The possible mechanisms connecting periodontitis and air pollution remain unclear. The air pollutants studied in the present work have been widely investigated and associated with various systemic effects, such as elevated systemic oxidative stress, enhanced blood coagulation, decreased plasma antioxidant capacity, autonomic imbalance, activation of the hypothalamic-pituitary-adrenal axis, and endothelial dysfunction [17,43,44,45,46,47,48,49,50].
One cross-sectional study on two panels of adult subjects, those with chronic periodontal infections and with healthy periodontal conditions, was conducted to evaluate the connections between particulate matter and high-sensitivity C-reactive protein (hs-CRP); the results suggested that adult patients with chronic periodontitis were more susceptible to PM-associated hs-CRP elevation [51]. Furthermore, the toxicology of air pollution exposure has been found to be closely related to cigarette smoking and environmental tobacco smoke (ETS). Humic-like substances (HULIS), a complex of polyacidic organic compounds formed by organic acids and aerosol particles, have been identified as a chemical component common to cigarette smoke and air pollution particles [52]. Several studies have reported that approximately 3% of ambient air particulate matter (PM), 7–10% of tobacco smoke condensate, and 5% of diesel exhaust is composed of HULIS [52,53]. In animal studies, introduction of HULIS into the lungs from cigarette smoke resulted in phagocytosis and accumulation of intracellular iron, leading to iron sequestration and subsequent deficiency of cellular metals [52]. Consequently, the response to functional metal deficiency includes oxidative stress, activation of cell signaling and transcription factors, release of pro-inflammatory mediators, and apoptosis [54,55]. These reactions further prompted the development of tissue inflammation and fibrosis [54,56].
Moreover, the interaction between ozone and air pollution particles has been proposed to further impact the effects of iron sequestration, disruption of cellular metal homeostasis, and tissue inflammation [57,58]. Apart from inflammatory reactions induced by air pollutants and cigarette smoke, pathogenic organisms also take part in the progression of periodontal disease. Porphyromonasgingivalis has been implicated as a major etiological component in the initiation and progression of periodontitis [59]. The ability of the pathogen to colonize and proliferate within the human periodontal pocket depends in part upon the acquisition of iron due to its inability to synthesize the protoporphyrin ring [39]. Characteristic secretions of surface-associated proteases and hemagglutinins have been demonstrated to be capable of degrading structural and defense mechanisms and harvesting heme, iron-containing proteins [39]. The virulence of P. gingivalis can be augmented in the presence of cigarette smoke and hydrogen sulfide, which are commonly seen aerosol particles [60,61]. Laboratory research and animal studies have revealed that purified gingipains and trypsin-like proteinase from P. gingivalis can promote MMP-8 and MMP-3 expression in rat mucosal epithelial cells and upregulate the collagen-degrading ability of some human gingival fibroblasts, causing an imbalance in the proliferative and catalytic activity of human gingival fibroblasts [40].
Eventually, tooth-supporting structures and alveolar bone are destroyed. At the cellular level, many studies have reported excessive release of matrix metalloproteinases, degradation of connective tissue and bone matrix, induction of RANKL, and increased levels of various cytokines (IL-8, IL-6, TNF-α, IL-1β, etc.) from peripheral blood polymorphonuclear neutrophils [37,62,63,64,65]. This pathognomonic reaction cascade has been found in several other disorders, such as diabetes mellitus, smoking, obesity, and rheumatoid arthritis [27,66,67,68,69]. We postulated that a similar inflammatory pathway underlies the connection between air pollution and periodontitis.
The present study has several advantages over previous studies. First, we used a nationwide database and recruited a relatively large sample size over an 11-year follow-up period, which yielded strong evidence regarding long-term outcomes in the observed Taiwanese population. Second, as 99% of the Taiwanese population is enrolled in the NHIRD, the bias associated with data collection, region, age, and institution was minimized. The use of the NHIRD also eliminated loss to follow-up and enabled the gathering of data from participants with varied demographic characteristics who were geographically dispersed [70]. Relatedly, the long follow-up period prevented any potential bias. Third, population density was incorporated to demonstrate the geographic connection between the severity of air pollution and periodontitis. However, the present study had some limitations. First, although this study merged two nationwide databases, the exposure levels of indoor air pollutants were not available [71]. Evidence has shown that buildings cannot block outdoor NO2 molecules efficiently. Thus, it is worthwhile to clarify the impact of indoor and outdoor air pollutants in future studies. Second, two large databases were combined: the NHIRD and TAQMD. The pollution levels in the residential areas of the NHIRD insurants were determined based on the location of their most common clinic or hospital for cold diagnosis (ICD-9-CM 460). Therefore, residents without a cold diagnosis during the study period were not enrolled in this study. Most likely they lived in areas with low levels of pollutants. This may have resulted in an underestimation of PD risk. Third, the NHIRD does not record detailed information on other potential confounders, such as socioeconomic status, family history, systemic comorbidities, smoking or alcohol consumption, and diet factors, which could be considered risk factors for periodontitis. Fourth, we conducted this retrospective nationwide cohort study using random sampling. Although this study had a long follow-up period, underdiagnosis due to PD development after the study period may have resulted in an underestimation of PD risk. Fifth, one of the limitations of LGTD is the lack of SES information. Tobacco abuse/dependence cannot completely reflect light smoking behavior and second-hand smoking. Thus, we considered COPD and asthma as the smoking status of the participants [72,73,74]. However, the covariates included are likely inadequate to control for socioeconomic position, which is a primary confounding factor in this analysis. Sixth, the NHIRD was established in early 1996 and was initially incomplete. Thus, only longitudinal data from January 2005 to December 2016 were selected and analyzed. Bias due to miscoding and misclassification of the ICD may have occurred during the transition phase from paper-based to electronic medical records. Additionally, the ICD-9 information used in this study was restricted to the ICD code only. The definitions of periodontitis and gingivitis have varied significantly between different specialties and timing. Since there were no objective image records, photos of the periodontal disease, or other laboratory data in the NHIRD, we relied on the professional judgment and accurate diagnosis of board-certified dentists. We did not determine the validity of the diagnosis in the present study. Furthermore, there are three sources for potential measurement error: (1) only 74 monitors in the whole study area without research enhanced monitors, and no information about the monitor locations; (2) no detailed residential addresses and moving history available; and (3) only raw measurements without temporal and spatial resolutions from advanced prediction models. Despite all these drawbacks, the data were examined carefully.

5. Conclusions

The present retrospective cohort study demonstrated an association between air pollution and periodontitis. In particular, residents in Taiwan with long-term exposure to higher levels of air pollutants had a greater risk of periodontitis. However, additional studies are required to investigate whether reduced exposure to air pollutants can lower the risk of periodontitis and to elucidate the underlying mechanism.

Author Contributions

Conceptualization, K.-H.C. and S.C.-S.T.; methodology, K.-H.C. and C.-L.L.; software, C.-L.L.; validation, H.-J.L., S.C.-S.T., F.C.-F.L., Y.-C.H., S.-W.C., C.Y.H., R.-H.C., C.-L.L. and K.-H.C.; formal analysis, K.-H.C. and C.-L.L.; investigation, K.-H.C. and C.-L.L.; resources, C.Y.H.; data curation, K.-H.C. and C.-L.L.; writing—original draft preparation, H.-J.L.; writing—review and editing, K.-H.C.; visualization, H.-J.L., S.C.-S.T., F.C.-F.L., Y.-C.H., S.-W.C., C.Y.H., R.-H.C., C.-L.L. and K.-H.C.; supervision, K.-H.C.; project administration, K.-H.C., C.Y.H. and S.C.-S.T.; funding acquisition, K.-H.C., C.Y.H. and S.C.-S.T. All authors have read and agreed to the published version of the manuscript.

Funding

This study is supported in part by Taiwan Ministry of Health and Welfare Clinical Trial Center (MOHW109-TDU-B-212-124004), China Medical University Hospital (DMR-111-105), and Tungs’ Taichung Metro Harbor hospital research grant (TTMHH-R1100012).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available from the NHIRD published by Taiwan National Health Insurance Bureau. Due to the ‘Personal Information Protection Act’, data cannot be made publicly available (http://nhird.nhri.org.tw/en/index.html).

Acknowledgments

We are grateful to Health Data Science Center, China Medical University Hospital for providing administrative, technical, and funding support. The funders had no role in the study design, data collection and analysis, the decision to publish, or preparation of the manuscript. No additional external funding was received for this study.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

In the Cox proportional hazard regression (pollutant levels as continuous variables), subjects who were exposed to higher concentrations of SO2 (adjusted hazard ratio [aHR] = 1.42, 95% CI = 1.41–1.42), CO (aHR = 2.73, 95% CI = 2.66–2.80), NO (aHR = 1.01, 95% CI = 1.013–1.014), NOx (aHR = 1.01, 95% CI = 1.013–1.014), NO2 (aHR = 1.05, 95% CI = 1.045–1.048), PM2.5 (aHR = 1.14, 95% CI = 1.13–1.14), and PM10 (aHR = 1.04, 95% CI = 1.038–1.04) developed a significantly higher risk of PD.
Table
Table A1. The risk of Periodontitis in patients exposed to various air pollutants daily average concentration in Cox proportional hazard regression.
Table A1. The risk of Periodontitis in patients exposed to various air pollutants daily average concentration in Cox proportional hazard regression.
PollutantscHR(95% CI)aHR †(95% CI)
SO21.42(1.41, 1.43) ***1.42(1.41, 1.42) ***
CO2.66(2.59, 2.73) ***2.73(2.66, 2.80) ***
NO1.013(1.012, 1.014) ***1.01(1.013, 1.014) ***
NOx1.013(1.013,1.014) ***1.01(1.013, 1.014) ***
NO21.045(1.044, 1.046) ***1.05(1.045, 1.048) ***
PM2.51.141(1.14, 1.142) ***1.14(1.13, 1.14) ***
PM101.038(1.038, 1.039) ***1.04(1.038, 1.04) ***
IR, incidence rate (per 1000 person-years); cHR, crude hazard ratio; aHR, adjusted hazard ratio; CI, confidence interval; Adjusted HR †, adjusted for age, sex, population density, monthly income and comorbidities of alcohol abuse/dependence, tobacco abuse/dependence, chronic obstructive pulmonary disease asthma, diabetes, obesity, and rheumatoid arthritis; *** p < 0.001.

Appendix B

The adjusted HR (95 CI%) for periodontitis in Q2–Q4 increased with increased exposure to SO2, CO, NO, NO2, NOX, PM2.5, and PM10 from 1.27 (1.24–1.30) to 3.33 (3.25–3.41); from 1.67 (1.63–1.72) to 2.97 (2.90–3.04); from 1.43 (1.39–1.46) to 2.48 (2.42–2.54); from 1.73 (1.68–1.77) to 2.96 (2.89–3.03); from 1.71 (1.67–1.75) to 3.27 (3.19–3.35); from 1.25 (1.22–1.29) to 3.98 (3.88–4.08, and from 1.65 (1.61–1.70) to3.00 (2.93–3.08), respectively, compared to Q1.
Table
Table A2. Comparisons of different periodontal disease incidences and associated hazard ratios among 4 levels of air pollutants.
Table A2. Comparisons of different periodontal disease incidences and associated hazard ratios among 4 levels of air pollutants.
PollutantLevelsEventIRcHR(95% CI)aHR †(95% CI)
SO2Q111,33512.8Reference groupReference group
Q212,82815.51.26(1.23,1.30)1.27(1.24, 1.30)
Q312,69913.51.06(1.03, 1.09)1.07(1.04, 1.09)
Q420,30030.23.32(3.24, 3.40)3.33(3.25, 3.41)
COQ1982810.6Reference groupReference group
Q214,18316.61.68(1.63, 1.72)1.67(1.63, 1.72)
Q314,17017.71.83(1.78, 1.88)1.84(1.79, 1.88)
Q418,95725.52.96(2.89, 3.03)2.97(2.90, 3.04)
NOQ110,99911.9Reference groupReference group
Q213,38416.11.42(1.39, 1.46)1.43(1.39, 1.46)
Q313,98617.21.54(1.50, 1.57)1.55(1.51, 1.58)
Q418,79324.72.46(2.41, 2.52)2.48(2.42, 2.54)
NO2Q1979410.7Reference groupReference group
Q215,18817.01.71(1.66, 1.75)1.73(1.68, 1.77)
Q314,04116.51.63(1.59, 1.67)1.45(1.41, 1.49)
Q418,13927.23.25(3.17, 3.33)2.96(2.89, 3.03)
NOXQ110,05011.1Reference groupReference group
Q214,39517.61.72(1.68, 1.77)1.71(1.67, 1.75)
Q313,39315.41.44(1.40, 1.48)1.64(1.60, 1.68)
Q419,32426.32.94(2.87, 3.02)3.27(3.19, 3.35)
PM2.5Q1895610.0Reference groupReference group
Q211,48612.01.25(1.22, 1.29)1.25(1.22, 1.29)
Q318,08122.52.90(2.83, 2.98)2.91(2.84, 2.98)
Q418,49327.63.97(3.87, 4.08)3.98(3.88, 4.08)
PM10Q1929410.4Reference groupReference group
Q214,34915.61.65(1.61, 1.69)1.65(1.61, 1.70)
Q314,57620.22.34(2.28, 2.40)2.34(2.28, 2.40)
Q418,94324.03.01(2.94, 3.09)3.00(2.93, 3.08)
IR, incidence rate (per 1000 person-years); cHR, crude hazard ratio; aHR, adjusted hazard ratio; CI, confidence interval; The two-year average air pollutant concentrations were categorized into 4 groups based on quartiles for each air pollutant; Adjusted HR †, adjusted for age, sex, population density, monthly income and comorbidities of alcohol abuse/dependence, tobacco abuse/dependence, chronic obstructive pulmonary disease asthma, diabetes, obesity, and rheumatoid arthritis.

References

  1. Davis, M.E.; Laden, F.; Hart, J.E.; Garshick, E.; Smith, T.J. Economic activity and trends in ambient air pollution. Environ. Health Perspect. 2010, 118, 614–619. [Google Scholar] [CrossRef] [Green Version]
  2. Panasevich, S.; Leander, K.; Rosenlund, M.; Ljungman, P.; Bellander, T.; de Faire, U.; Pershagen, G.; Nyberg, F. Associations of long- and short-term air pollution exposure with markers of inflammation and coagulation in a population sample. Occup. Environ. Med. 2009, 66, 747–753. [Google Scholar] [CrossRef]
  3. Zhang, Y.; Ji, X.; Ku, T.; Sang, N. Inflammatory response and endothelial dysfunction in the hearts of mice co-exposed to SO(2), NO(2), and PM(2.5). Environ. Toxicol. 2016, 31, 1996–2005. [Google Scholar] [CrossRef]
  4. Fashi, M.; Agha Alinejad, H.; Asilian Mahabadi, H. The Effect of Aerobic Exercise in Ambient Particulate Matter on Lung Tissue Inflammation and Lung Cancer. Iran. J. Cancer Prev. 2015, 8, e2333. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Block, M.L.; Calderon-Garciduenas, L. Air pollution: Mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 2009, 32, 506–516. [Google Scholar] [CrossRef] [Green Version]
  6. Kunzli, N.; Jerrett, M.; Garcia-Esteban, R.; Basagana, X.; Beckermann, B.; Gilliland, F.; Medina, M.; Peters, J.; Hodis, H.N.; Mack, W.J. Ambient air pollution and the progression of atherosclerosis in adults. PLoS ONE 2010, 5, e9096. [Google Scholar] [CrossRef]
  7. Zhang, R.; Dai, Y.; Zhang, X.; Niu, Y.; Meng, T.; Li, Y.; Duan, H.; Bin, P.; Ye, M.; Jia, X.; et al. Reduced pulmonary function and increased pro-inflammatory cytokines in nanoscale carbon black-exposed workers. Part. Fibre Toxicol. 2014, 11, 73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Wang, C.; Chen, R.; Zhao, Z.; Cai, J.; Lu, J.; Ha, S.; Xu, X.; Chen, X.; Kan, H. Particulate air pollution and circulating biomarkers among type 2 diabetic mellitus patients: The roles of particle size and time windows of exposure. Environ. Res. 2015, 140, 112–118. [Google Scholar] [CrossRef] [PubMed]
  9. Risom, L.; Møller, P.; Loft, S. Oxidative stress-induced DNA damage by particulate air pollution. Mutat. Res. 2005, 592, 119–137. [Google Scholar] [CrossRef] [PubMed]
  10. Deo, V.; Bhongade, M.L. Pathogenesis of periodontitis: Role of cytokines in host response. Dent. Today 2010, 29, 60–62. [Google Scholar]
  11. Yucel-Lindberg, T.; Bage, T. Inflammatory mediators in the pathogenesis of periodontitis. Expert Rev. Mol. Med. 2013, 15, e7. [Google Scholar] [CrossRef] [Green Version]
  12. Kampfrath, T.; Maiseyeu, A.; Ying, Z.; Shah, Z.; Deiuliis, J.A.; Xu, X.; Kherada, N.; Brook, R.D.; Reddy, K.M.; Padture, N.P.; et al. Chronic fine particulate matter exposure induces systemic vascular dysfunction via NADPH oxidase and TLR4 pathways. Circ. Res. 2011, 108, 716–726. [Google Scholar] [CrossRef] [Green Version]
  13. Rao, X.; Zhong, J.; Maiseyeu, A.; Gopalakrishnan, B.; Villamena, F.A.; Chen, L.C.; Harkema, J.R.; Sun, Q.; Rajagopalan, S. CD36-dependent 7-ketocholesterol accumulation in macrophages mediates progression of atherosclerosis in response to chronic air pollution exposure. Circ. Res. 2014, 115, 770–780. [Google Scholar] [CrossRef] [Green Version]
  14. Xu, X.; Yavar, Z.; Verdin, M.; Ying, Z.; Mihai, G.; Kampfrath, T.; Wang, A.; Zhong, M.; Lippmann, M.; Chen, L.C.; et al. Effect of early particulate air pollution exposure on obesity in mice: Role of p47phox. Arter. Thromb. Vasc. Biol. 2010, 30, 2518–2527. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Sharma, K.; Lee, H.H.; Gong, D.S.; Park, S.H.; Yi, E.; Schini-Kerth, V.; Oak, M.H. Fine air pollution particles induce endothelial senescence via redox-sensitive activation of local angiotensin system. Environ. Pollut. 2019, 252, 317–329. [Google Scholar] [CrossRef]
  16. Forstermann, U. Nitric oxide and oxidative stress in vascular disease. Pflügers Arch. Eur. J. Physiol. 2010, 459, 923–939. [Google Scholar] [CrossRef] [PubMed]
  17. Munzel, T.; Sorensen, M.; Gori, T.; Schmidt, F.P.; Rao, X.; Brook, F.R.; Chen, L.C.; Brook, R.D.; Rajagopalan, S. Environmental stressors and cardio-metabolic disease: Part II-mechanistic insights. Eur. Heart J. 2017, 38, 557–564. [Google Scholar] [CrossRef]
  18. Brook, R.D.; Rajagopalan, S.; Pope, C.A.; Brook, J.R.; Bhatnagar, A.; Diez-Roux, A.V.; Holguin, F.; Hong, Y.; Luepker, R.V.; Mittleman, M.A.; et al. Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the American Heart Association. Circulation 2010, 121, 2331–2378. [Google Scholar] [CrossRef] [Green Version]
  19. Tiotiu, A.I.; Novakova, P.; Nedeva, D.; Chong-Neto, H.J.; Novakova, S.; Steiropoulos, P.; Kowal, K. Impact of Air Pollution on Asthma Outcomes. Int. J. Environ. Res. Public Health 2020, 17, 6212. [Google Scholar] [CrossRef] [PubMed]
  20. Gehring, U.; Heinrich, J.; Kramer, U.; Grote, V.; Hochadel, M.; Sugiri, D.; Kraft, M.; Rauchfuss, K.; Eberwein, H.G.; Wichmann, H.E. Long-term exposure to ambient air pollution and cardiopulmonary mortality in women. Epidemiology 2006, 17, 545–551. [Google Scholar] [CrossRef] [PubMed]
  21. Atkinson, R.W.; Carey, I.M.; Kent, A.J.; van Staa, T.P.; Anderson, H.R.; Cook, D.G. Long-term exposure to outdoor air pollution and incidence of cardiovascular diseases. Epidemiology 2013, 24, 44–53. [Google Scholar] [CrossRef] [Green Version]
  22. Miller, K.A.; Siscovick, D.S.; Sheppard, L.; Shepherd, K.; Sullivan, J.H.; Anderson, G.L.; Kaufman, J.D. Long-term exposure to air pollution and incidence of cardiovascular events in women. N. Engl. J. Med. 2007, 356, 447–458. [Google Scholar] [CrossRef]
  23. Chang, K.H.; Hsu, P.Y.; Lin, C.J.; Lin, C.L.; Juo, S.H.; Liang, C.L. Traffic-related air pollutants increase the risk for age-related macular degeneration. J. Investig. Med. 2019, 67, 1076–1081. [Google Scholar] [CrossRef]
  24. Fan, H.C.; Chen, C.Y.; Hsu, Y.C.; Chou, R.H.; Teng, C.J.; Chiu, C.H.; Hsu, C.Y.; Muo, C.H.; Chang, M.Y.; Chang, K.H. Increased risk of incident nasopharyngeal carcinoma with exposure to air pollution. PLoS ONE 2018, 13, e0204568. [Google Scholar] [CrossRef]
  25. Wong, I.C.; Ng, Y.K.; Lui, V.W. Cancers of the lung, head and neck on the rise: Perspectives on the genotoxicity of air pollution. Chin. J. Cancer 2014, 33, 476–480. [Google Scholar] [CrossRef] [PubMed]
  26. Peters, R.; Ee, N.; Peters, J.; Booth, A.; Mudway, I.; Anstey, K.J. Air Pollution and Dementia: A Systematic Review. J. Alzheimers Dis. 2019, 70, S145–S163. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Chang, K.H.; Hsu, C.C.; Muo, C.H.; Hsu, C.Y.; Liu, H.C.; Kao, C.H.; Chen, C.Y.; Chang, M.Y.; Hsu, Y.C. Air pollution exposure increases the risk of rheumatoid arthritis: A longitudinal and nationwide study. Environ. Int. 2016, 94, 495–499. [Google Scholar] [CrossRef] [PubMed]
  28. Kinane, D.F. Causation and pathogenesis of periodontal disease. Periodontology 2000 2001, 25, 8–20. [Google Scholar] [CrossRef]
  29. Carcuac, O.; Berglundh, T. Composition of human peri-implantitis and periodontitis lesions. J. Dent. Res. 2014, 93, 1083–1088. [Google Scholar] [CrossRef] [Green Version]
  30. Linden, G.J.; Lyons, A.; Scannapieco, F.A. Periodontal systemic associations: Review of the evidence. J. Clin. Periodontol. 2013, 40, S8–S19. [Google Scholar] [CrossRef]
  31. Burt, B.; Research, S. Therapy Committee of the American Academy of P: Position paper: Epidemiology of periodontal diseases. J. Periodontol. 2005, 76, 1406–1419. [Google Scholar] [PubMed]
  32. Gilmore, N.; Sheiham, A. Overhanging dental restorations and periodontal disease. J. Periodontol. 1971, 42, 8–12. [Google Scholar] [CrossRef] [PubMed]
  33. Heitz-Mayfield, L.J.A.; Salvi, G.E. Peri-implant mucositis. J. Periodontol. 2018, 89, S257–S266. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Buczko, P.; Zalewska, A.; Szarmach, I. Saliva and oxidative stress in oral cavity and in some systemic disorders. J. Physiol. Pharmacol. 2015, 66, 3–9. [Google Scholar]
  35. Wang, G.P. Defining functional signatures of dysbiosis in periodontitis progression. Genome Med. 2015, 7, 40. [Google Scholar] [CrossRef] [Green Version]
  36. Almerich-Silla, J.M.; Montiel-Company, J.M.; Pastor, S.; Serrano, F.; Puig-Silla, M.; Dasí, F. Oxidative Stress Parameters in Saliva and Its Association with Periodontal Disease and Types of Bacteria. Dis. Markers 2015, 2015, 653537. [Google Scholar] [CrossRef] [Green Version]
  37. Johnstone, A.M.; Koh, A.; Goldberg, M.B.; Glogauer, M. A hyperactive neutrophil phenotype in patients with refractory periodontitis. J. Periodontol. 2007, 78, 1788–1794. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Ghio, A.J.; Soukup, J.M.; Madden, M.C. The toxicology of air pollution predicts its epidemiology. Inhal. Toxicol. 2018, 30, 327–334. [Google Scholar] [CrossRef]
  39. Olczak, T.; Simpson, W.; Liu, X.; Genco, C.A. Iron and heme utilization in Porphyromonas gingivalis. FEMS Microbiol. Rev. 2005, 29, 119–144. [Google Scholar] [CrossRef] [Green Version]
  40. Andrian, E.; Mostefaoui, Y.; Rouabhia, M.; Grenier, D. Regulation of matrix metalloproteinases and tissue inhibitors of matrix metalloproteinases by Porphyromonas gingivalis in an engineered human oral mucosa model. J. Cell Physiol. 2007, 211, 56–62. [Google Scholar] [CrossRef]
  41. Ko, Y.C. Air pollution and its health effects on residents in Taiwanese communities. Kaohsiung J. Med. Sci 1996, 12, 657–669. [Google Scholar]
  42. Strosnider, H.; Kennedy, C.; Monti, M.; Yip, F. Rural and Urban Differences in Air Quality, 2008–2012, and Community Drinking Water Quality, 2010–2015—United States. MMWR Surveill. Summ. 2017, 66, 1–10. [Google Scholar] [CrossRef]
  43. Franchini, M.; Mannucci, P.M. Thrombogenicity and cardiovascular effects of ambient air pollution. Blood 2011, 118, 2405–2412. [Google Scholar] [CrossRef]
  44. Kilinc, E.; Schulz, H.; Kuiper, G.J.; Spronk, H.M.; Ten Cate, H.; Upadhyay, S.; Ganguly, K.; Stoeger, T.; Semmler-Bhenke, M.; Takenaka, S.; et al. The procoagulant effects of fine particulate matter in vivo. Part. Fibre Toxicol. 2011, 8, 12. [Google Scholar] [CrossRef] [Green Version]
  45. Jiang, S.; Bo, L.; Gong, C.; Du, X.; Kan, H.; Xie, Y.; Song, W.; Zhao, J. Traffic-related air pollution is associated with cardio-metabolic biomarkers in general residents. Int. Arch. Occup. Environ. Health 2016, 89, 911–921. [Google Scholar] [CrossRef] [PubMed]
  46. Brook, R.D.; Bard, R.L.; Morishita, M.; Dvonch, J.T.; Wang, L.; Yang, H.Y.; Spino, C.; Mukherjee, B.; Kaplan, M.J.; Yalavarthi, S.; et al. Hemodynamic, autonomic, and vascular effects of exposure to coarse particulate matter air pollution from a rural location. Environ. Health Perspect. 2014, 122, 624–630. [Google Scholar] [CrossRef] [Green Version]
  47. Aragon, M.J.; Topper, L.; Tyler, C.R.; Sanchez, B.; Zychowski, K.; Young, T.; Herbert, G.; Hall, P.; Erdely, A.; Eye, T.; et al. Serum-borne bioactivity caused by pulmonary multiwalled carbon nanotubes induces neuroinflammation via blood-brain barrier impairment. Proc. Natl. Acad. Sci. USA 2017, 114, E1968–E1976. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Brook, R.D.; Sun, Z.; Brook, J.R.; Zhao, X.; Ruan, Y.; Yan, J.; Mukherjee, B.; Rao, X.; Duan, F.; Sun, L.; et al. Extreme Air Pollution Conditions Adversely Affect Blood Pressure and Insulin Resistance: The Air Pollution and Cardiometabolic Disease Study. Hypertension 2016, 67, 77–85. [Google Scholar] [CrossRef]
  49. Rao, X.; Montresor-Lopez, J.; Puett, R.; Rajagopalan, S.; Brook, R.D. Ambient air pollution: An emerging risk factor for diabetes mellitus. Curr. Diab. Rep. 2015, 15, 603. [Google Scholar] [CrossRef] [PubMed]
  50. Haberzettl, P.; Conklin, D.J.; Abplanalp, W.T.; Bhatnagar, A.; O’Toole, T.E. Inhalation of Fine Particulate Matter Impairs Endothelial Progenitor Cell Function Via Pulmonary Oxidative Stress. Arter. Thromb. Vasc. Biol. 2018, 38, 131–142. [Google Scholar] [CrossRef] [Green Version]
  51. Yang, T.H.; Masumi, S.; Weng, S.P.; Chen, H.W.; Chuang, H.C.; Chuang, K.J. Personal exposure to particulate matter and inflammation among patients with periodontal disease. Sci. Total Environ. 2015, 502, 585–589. [Google Scholar] [CrossRef] [PubMed]
  52. Ghio, A.J.; Stonehuerner, J.; Quigley, D.R. Humic-like substances in cigarette smoke condensate and lung tissue of smokers. Am. J. Physiol. 1994, 266, L382–L388. [Google Scholar] [CrossRef] [PubMed]
  53. Stedman, R.L.; Chamberlain, W.J.; Miller, R.L. High molecular weight pigment in cigarette smoke. Chem. Ind. 1966, 37, 1560–1562. [Google Scholar]
  54. Liu, Y.; Cui, Y.; Shi, M.; Zhang, Q.; Wang, Q.; Chen, X. Deferoxamine promotes MDA-MB-231 cell migration and invasion through increased ROS-dependent HIF-1α accumulation. Cell Physiol. Biochem. 2014, 33, 1036–1046. [Google Scholar] [CrossRef] [PubMed]
  55. Zhang, W.; Wu, Y.; Yan, Q.; Ma, F.; Shi, X.; Zhao, Y.; Peng, Y.; Wang, J.; Jiang, B. Deferoxamine enhances cell migration and invasion through promotion of HIF-1α expression and epithelial-mesenchymal transition in colorectal cancer. Oncol. Rep. 2014, 31, 111–116. [Google Scholar] [CrossRef]
  56. Ghio, A.J.; Soukup, J.M.; Dailey, L.A. Air pollution particles and iron homeostasis. Biochim. Biophys. Acta 2016, 1860, 2816–2825. [Google Scholar] [CrossRef] [PubMed]
  57. Sutherland, I.; Sheng, E.; Bradley, R.; Freakley, P. Effects of ozone oxidation on carbon black surfaces. J. Mater. Sci. 1996, 31, 5651–5655. [Google Scholar] [CrossRef]
  58. Ciobanu, M.; Lepadatu, A.-M.; Asaftei, S. Chemical and Electrochemical Studies of Carbon Black Surface by Treatment with Ozone and Nitrogen Oxide. Mater. Today Proc. 2016, 3, S252–S257. [Google Scholar] [CrossRef]
  59. Andrian, E.; Grenier, D.; Rouabhia, M. Porphyromonas gingivalis-epithelial cell interactions in periodontitis. J. Dent. Res. 2006, 85, 392–403. [Google Scholar] [CrossRef]
  60. Nakamura, S.; Shioya, K.; Hiraoka, B.Y.; Suzuki, N.; Hoshino, T.; Fujiwara, T.; Yoshinari, N.; Ansai, T.; Yoshida, A. Porphyromonas gingivalis hydrogen sulfide enhances methyl mercaptan-induced pathogenicity in mouse abscess formation. Microbiology 2018, 164, 529–539. [Google Scholar] [CrossRef]
  61. Zhang, W.; Song, F.; Windsor, L.J. Effects of tobacco and P. gingivalis on gingival fibroblasts. J. Dent. Res. 2010, 89, 527–531. [Google Scholar] [CrossRef]
  62. Graves, D. Cytokines that promote periodontal tissue destruction. J. Periodontol. 2008, 79, 1585–1591. [Google Scholar] [CrossRef] [Green Version]
  63. Lee, N.K.; Choi, Y.G.; Baik, J.Y.; Han, S.Y.; Jeong, D.W.; Bae, Y.S.; Kim, N.; Lee, S.Y. A crucial role for reactive oxygen species in RANKL-induced osteoclast differentiation. Blood 2005, 106, 852–859. [Google Scholar] [CrossRef] [Green Version]
  64. Hienz, S.A.; Paliwal, S.; Ivanovski, S. Mechanisms of Bone Resorption in Periodontitis. J. Immunol. Res. 2015, 2015, 615486. [Google Scholar] [CrossRef] [Green Version]
  65. Hatanaka, E.; Monteagudo, P.T.; Marrocos, M.S.; Campa, A. Neutrophils and monocytes as potentially important sources of proinflammatory cytokines in diabetes. Clin. Exp. Immunol. 2006, 146, 443–447. [Google Scholar] [CrossRef]
  66. Bullon, P.; Morillo, J.M.; Ramirez-Tortosa, M.C.; Quiles, J.L.; Newman, H.N.; Battino, M. Metabolic syndrome and periodontitis: Is oxidative stress a common link? J. Dent. Res. 2009, 88, 503–518. [Google Scholar] [CrossRef] [Green Version]
  67. de Pablo, P.; Chapple, I.L.; Buckley, C.D.; Dietrich, T. Periodontitis in systemic rheumatic diseases. Nat. Rev. Rheumatol. 2009, 5, 218–224. [Google Scholar] [CrossRef]
  68. Sfyroeras, G.S.; Roussas, N.; Saleptsis, V.G.; Argyriou, C.; Giannoukas, A.D. Association between periodontal disease and stroke. J. Vasc. Surg. 2012, 55, 1178–1184. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Bright, R.; Proudman, S.M.; Rosenstein, E.D.; Bartold, P.M. Is there a link between carbamylation and citrullination in periodontal disease and rheumatoid arthritis? Med. Hypotheses 2015, 84, 570–576. [Google Scholar] [CrossRef] [PubMed]
  70. Hsieh, C.Y.; Su, C.C.; Shao, S.C.; Sung, S.F.; Lin, S.J.; Kao Yang, Y.H.; Lai, E.C. Taiwan’s National Health Insurance Research Database: Past and future. Clin. Epidemiol. 2019, 11, 349–358. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Blondeau, P.; Iordache, V.; Poupard, O.; Genin, D.; Allard, F. Relationship between outdoor and indoor air quality in eight French schools. Indoor Air 2005, 15, 2–12. [Google Scholar] [CrossRef] [PubMed]
  72. Patel, B.D.; Loo, W.J.; Tasker, A.D.; Screaton, N.J.; Burrows, N.P.; Silverman, E.K.; Lomas, D.A. Smoking related COPD and facial wrinkling: Is there a common susceptibility? Thorax 2006, 61, 568–571. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Pauwels, R.A.; Rabe, K.F. Burden and clinical features of chronic obstructive pulmonary disease (COPD). Lancet 2004, 364, 613–620. [Google Scholar] [CrossRef]
  74. Harju, M.; Keski-Nisula, L.; Georgiadis, L.; Heinonen, S. Parental smoking and cessation during pregnancy and the risk of childhood asthma. BMC Public Health 2016, 16, 428. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table
Table 1. Characteristics of participants in this study.
Table 1. Characteristics of participants in this study.
N = 292,263 n%
GenderFemale160,98555.1
Male131,27844.9
Age, yearsmean, SD41.116.2
Population density †1 (highest)174,97759.9
295,73032.8
318,7216.41
4 (lowest)28350.97
Monthly income(NTD)
 <20,000 54,39718.6
 20,000–40,000 148,12150.7
 ≥40,000 89,74530.7
Comorbidity
 Alcohol abuse/dependence 45121.54
 Tobacco abuse/dependence 11,4743.93
 Chronic obstructive pulmonary disease 47,45816.2
 Asthma 43,81815.0
 Diabetes 52,88418.1
 Obesity 52621.80
 Rheumatoid arthritis 8580.29
Exposure of air pollutants
 SO2 level (two-year average, ppb) 4.421.68
 CO level (two-year average, ppm)mean, SD0.600.23
 NO level (two-year average, ppm)mean, SD8.698.77
 NO2 level (two-year average, ppm)mean, SD17.35.74
 NOX level (two-year average, ppm)mean, SD28.614.0
 PM2.5(two-year average, μg/m3)mean, SD30.27.88
 PM10(two-year average, μg/m3)mean, SD54.312.8
Outcome
 PeriodontitisYes126,16756.8
 Follow-up time, yearsmean, SD11.42.80
 Follow-up time, yearsMedian, IQR13.0(10.9–13.0)
† The population density was categorized into 4 levels, with level 1 as the highest level and level 4 as the lowest level; CO, carbon monoxide; NO, nitric oxide; NOX, nitrogen oxides; SD, standard deviation.
Table
Table 2. Baseline population density level among quartiles of daily average concentration of air pollutants in Taiwan children, 2005–2016.
Table 2. Baseline population density level among quartiles of daily average concentration of air pollutants in Taiwan children, 2005–2016.
Air Pollutant ConcentrationQ1 (Lowest)Q2Q3Q4 (Highest)p-Value *
N = 292,263n(%)n(%)n(%)n(%)
SO2<0.001
Population density level
139,99822.943,64524.949,25328.242,08124.1
229,28130.619,74520.620,92221.925,78226.9
3255413.6561130.0680836.4374820.0
4124443.949617.557420.352118.4
CO (missing = 288)<0.001
Population density level
138,27221.939,67122.745,92626.351,04829.2
232,18033.728,93730.317,16318.017,22718.0
3474225.3317116.9661835.4418622.4
4108238.252818.665123.057320.2
NO
Population density level
141,33123.638,24521.942,92624.552,47530.0
228,98530.328,56429.820,59221.517,58918.4
3467125.0329817.6662335.4412922.1
4103236.456820.064722.958820.7
NO2<0.001
Population density level
139,62122.641,99924.047,19327.046,16426.4
230,10231.429,49430.819,32820.216,80617.6
3467925.0475525.4577530.9351218.8
4110839.158320.662422.052018.3
NOX<0.001
Population density level
140,79523.337,62421.545,97126.350,58728.9
228,00829.329,46130.820,34221.317,91918.7
3468525.0329817.6682736.5391120.9
4104937.054919.466523.557220.2
PM2.5<0.001
Population density level
143,38224.849,19528.242,82424.539,21122.5
221,41422.421,11522.124,36025.528,61830.0
3496326.6459724.6447624.0464624.9
4109538.770825.053618.949217.4
PM10<0.001
Population density level
140,97423.450,69529.042,27024.241,03823.5
224,70725.819,12920.018,54219.433,35234.8
3471225.2553929.6410021.9437023.3
480928.592132.560221.250317.7
* Chi-square test; The population density level was categorized into 4 levels, with level 1 as the highest level and level 4 as the lowest level; The two-year average air pollutant concentrations were categorized into 4 groups based on quartiles for each air pollutant.
Table
Table 3. Comparisons of different periodontal disease incidences and associated hazard ratios among 4 levels of air pollutants.
Table 3. Comparisons of different periodontal disease incidences and associated hazard ratios among 4 levels of air pollutants.
PollutantLevelsEventIRcHR(95% CI)aHR †(95% CI)
SO2Q124,64527.9Reference groupReference group
Q228,00233.71.27(1.25, 1.29)1.28(1.26, 1.30)
Q328,34230.21.09(1.07, 1.11)1.11(1.09, 1.13)
Q445,17867.23.37(3.32, 3.42)3.39(3.34, 3.44)
COQ122,74024.6Reference groupReference group
Q230,90436.31.58(1.55, 1.60)1.58(1.55, 1.61)
Q331,48439.41.75(1.72, 1.78)1.78(1.75, 1.81)
Q440,97655.12.75(2.71, 2.80)2.77(2.73, 2.82)
NOQ125,58327.8Reference groupReference group
Q229,24335.31.34(1.31, 1.36)1.34(1.32, 1.36)
Q330,91538.11.46(1.43, 1.48)1.48(1.46, 1.51)
Q440,42653.02.27(2.23, 2.31)2.30(2.26, 2.33)
NO2Q122,85225.1Reference groupReference group
Q233,26737.21.60(1.57, 1.63)1.63(1.60, 1.65)
Q330,97236.31.54(1.51, 1.56)1.40(1.37, 1.42)
Q439,07658.62.98(2.93, 3.03)2.73(2.69, 2.78)
NOXQ123,39225.9Reference groupReference group
Q231,50038.51.62(1.59, 1.64)1.61(1.59, 1.64)
Q329,75434.31.37(1.35, 1.40)1.56(1.53, 1.59)
Q441,52156.42.70(2.66, 2.75)3.02(2.97, 3.07)
PM2.5Q118,74120.9Reference groupReference group
Q225,08826.31.30(1.28, 1.33)1.31(1.28, 1.33)
Q340,02549.73.05(3.00, 3.11)3.04(2.99, 3.09)
Q441,95562.64.28(4.21, 4.35)4.25(4.18, 4.32)
PM10Q119,75822.1Reference groupReference group
Q231,15533.81.68(1.65, 1.71)1.69(1.66, 1.72)
Q332,24344.72.42(2.38, 2.46)2.42(2.38, 2.47)
Q443,01154.53.20(3.14, 3.25)3.17(3.12, 3.22)
IR, incidence rate (person-years); cHR, crude hazard ratio; aHR, adjusted hazard ratio; CI, confidence interval; The annual average air pollutant concentrations were categorized into 4 groups based on quartiles for each air pollutant; Adjusted HR †, adjusted for age, sex, population density level, monthly income and comorbidities of alcohol abuse/dependence, tobacco abuse/dependence, chronic obstructive pulmonary disease, asthma, diabetes, obesity, and rheumatoid arthritis.
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Lin, H.-J.; Tsai, S.C.-S.; Lin, F.C.-F.; Hsu, Y.-C.; Chen, S.-W.; Chou, R.-H.; Lin, C.-L.; Hsu, C.Y.; Chang, K.-H. Prolonged Exposure to Air Pollution Increases Periodontal Disease Risk: A Nationwide, Population-Based, Cohort Study. Atmosphere 2021, 12, 1668. https://doi.org/10.3390/atmos12121668

AMA Style

Lin H-J, Tsai SC-S, Lin FC-F, Hsu Y-C, Chen S-W, Chou R-H, Lin C-L, Hsu CY, Chang K-H. Prolonged Exposure to Air Pollution Increases Periodontal Disease Risk: A Nationwide, Population-Based, Cohort Study. Atmosphere. 2021; 12(12):1668. https://doi.org/10.3390/atmos12121668

Chicago/Turabian Style

Lin, Han-Jie, Stella Chin-Shaw Tsai, Frank Cheau-Feng Lin, Yi-Chao Hsu, Shih-Wei Chen, Ruey-Hwang Chou, Cheng-Li Lin, Chung Y. Hsu, and Kuang-Hsi Chang. 2021. "Prolonged Exposure to Air Pollution Increases Periodontal Disease Risk: A Nationwide, Population-Based, Cohort Study" Atmosphere 12, no. 12: 1668. https://doi.org/10.3390/atmos12121668

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