Contributions of burning incense on indoor air pollution levels and on the health status of patients with chronic obstructive pulmonary disease

Study design and participant recruitment

In this cohort study comprising 18 participants, we examined responses to a lifestyle behavior questionnaire, namely, the Chronic Respiratory Questionnaire, and the results of a lung function test. In addition, changes in PM in the home were assessed at 7 time points (baseline, 10-, 20-, 30-, 60-minutes, 3 h, and 5 h). Outpatients with COPD were recruited from a regional hospital in the south-western region of Taiwan. Inclusion criteria comprised the following: age ≥40 years; a chest physician made the diagnosis according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD), which presents of a post-bronchodilator FEV1/FVC <0.70; moderate-to-severe COPD according to the GOLD grades (30 <FEV₁ predicted <80%) (Agusti & Vogelmeier, 2019); the habit of burning incense and having a shrine at home, and being able to understand and communicate in Mandarin or Taiwanese. Exclusion criteria comprised the following: heart diseases, cancer (any type), pulmonary tuberculosis, or asthma. This study was approved by the Institutional Review Board Ethics Committee of Chang Gung Memorial Hospital (102-2417B). After explaining the study aims and procedures to potential participants, informed consent was obtained from all participants agreeing to participate in the study. After written informed consent was obtained, data were collected via home visits involving face-to-face interviews using structured questionnaires, and environmental data were collected through observations and using specialized equipment.

Participants

To the best of our knowledge, no study has reported changes in particulate matter (i.e., PM_2.5 or PM₁₀) after burning incense among COPD patients. Therefore, we assumed the level of PM_2.5 increases from 200 µg/m³ before burning incense to 400 µg/m³ immediately after burning incense with a common standard deviation of 200 µg/m³; a minimum of 15 subjects were required to achieve an alpha level of 5% and a power level of 90%. Twenty participants were initially included in the study; however, 2 participants withdrew their consent, and were subsequently excluded, during the study period as their disease had exacerbated and they were admitted to hospital. There was no statistically significant difference between included (N = 18) and excluded (N = 2) participants in terms of variables such as age, body mass index (BMI), and length of COPD duration except COPD severity. Among 18 participants, no data were missing for any variable or time point.

Measurements and instruments

Data were collected for 30–45 min, using structured questionnaires to determine demographic and clinical characteristics, and assessed using a COPD Assessment Test (CAT) and a modified British Medical Research Council dyspnea scale (mMRC). We also collected environmental characteristics and air quality assessments including PM₁₀ and PM_2.5 concentration levels using an aerosol spectrometer (Model TSI8532).

Demographic and clinical characteristics

Demographics included age, sex, weight status, employment status, education levels, exercise habits, smoking status, disease severity, BMI, and a waist-hip ratio. Clinical characteristics were assessed in relation to the Charlson comorbidity index (CCI), the number of years since the COPD diagnosis (duration of disease), and forced expiratory volume in 1 s (FEV₁). The CCI is used as a measure of 1-year mortality risk and consists of 18 comorbidities (Charlson et al., 1987). The CCI scoring scales range from 0 (without any symptoms) to 6, with higher CCI scores indicating a higher disease burden level.

The forced expiratory volume in one second (FEV₁)

As COPD progresses, FEV₁ tends to decline gradually. A pulmonary function test, a non-invasive test, and measurements such as FEV₁ and forced vital capacity (FVC) are used to diagnose COPD and determine its severity based on American Thoracic Society (ATS), European Respiratory Society (ERS), and GOLD grades (Agusti & Vogelmeier, 2019; Celli et al., 2015; Jo et al., 2018). A change in pulmonary function is also useful to determine the influence of risk factors on COPD exacerbation (Vestbo & Lange, 2016; Scanlon et al., 2000).

The COPD Assessment Test (CAT)

The COPD Assessment Test (CAT) was designed to estimate the condition of COPD symptoms, including cough, phlegm (mucus), chest tightness, breathlessness while climbing a hill or stairs, limitation to activity at home, confidence, while leaving home, sleep quality, and energy. The score of each item is from 0 to 5 in the CAT, and the total score ranges from 0 to 40. A higher CAT score denoted poorer health status in terms of COPD (Agusti & Vogelmeier, 2019; Jo et al., 2018). In this study, the Chinese version of the CAT (CAT-Chinese version) was adopted. The Cronbach’s alpha of CAT-Chinese version was 0.81, which showed a good internal consistency, and revealed that higher CAT score indicated a greater severity of lung disease (Chai, Liu & Cai, 2011). Therefore, the CAT-Chinese version is a simple, reliable, and validated questionnaire to evaluate the symptoms of COPD patients.

The modified British Medical Research Council (mMRC) scale

The mMRC scale comprises a 5-point scale: 0 (breathlessness due to strenuous exercise), 1 (breathlessness when hurrying or walking up a hill), 2 (walking slower than people of the same age due to breathlessness), 3 (breathlessness after walking a few minutes or for 100 yards), and 4 (breathlessness when dressing). The mMRC scale is recommended for COPD assessment by the GOLD. Moreover, the mMRC scale is a predictor of future mortality risk (Agusti & Vogelmeier, 2019).

Environmental characteristics

We assessed participants’ home environment, including meteorological conditions (rain, and outdoor and indoor moisture), the smoking status of family members, the residential location, the age and type of house, the direction the house was facing and its proximity to a main road, and the frequency of having windows and doors open.

Air quality assessment

All study participants were in the habit of burning incense, and all participants had a shrine at home. Air sampling for PM₁₀ and PM_2.5 concentration levels due to incense burning was measured at the shrines, using an aerosol spectrometer (Model TSI8532). The PM₁₀ and PM_2.5 levels were assessed at 3 time points, each at 1-minute intervals; and the average value of the 3 measurements was used as the outcome for each specific assessment. Furthermore, PM₁₀ and PM_2.5 assessments were undertaken during seven time intervals as follows: a pre-test assessment prior to burning incense; at 10-, 20-, 30-, and 60-minute intervals during the burning of the incense; and at 3 h and 5 h after incense burning had stopped. CAT and mMRC scores were determined and lung function tests were performed after each time interval. The normal values of daily PM_2.5 & PM₁₀ levels as stated by the Taiwan Environment Protection Administration are 35 µg/m³ and 125 µg/m³, respectively (EPA, 2012).

Statistical analyses

The SPSS 25 package (IBM SPSS Inc., Chicago, IL) was used to analyze data. The characteristics of the study participants, house types, residential locations, and home environments (in relation to incense burning) are presented as numbers and percentages for categorical variables or as means and standard deviations for continuous variables. Some studies have reported their findings concerning PM indoor concentrations relative to external levels, different cooking methods (Isaxon et al., 2015), smoking, incense (Wallace et al., 2003), and candles (Beko et al., 2013). Moreover, house type and window opening can be to correlated to indoor PM concentrations (Shao et al., 2019; Andersen et al., 2011). A recent comprehensive literature review showed that the main origin of PM_2.5 and PM₁₀ at home was due to outdoor air (Morawska et al., 2017). Therefore, covariates such as house types, whether windows are open or not, family members who actively smoke, and outdoor PM were collected based on previous studies. The effect of burning incense on PM_2.5 and PM₁₀ was assessed using a generalized estimating equation (GEE) model with a robust standard error and an exchangeable working correlation matrix for the adjustment of time (Liang & Zeger, 1986). In the GEE analysis, the linking function was identity, and the distribution was normal. Since there were only 18 participants, covariate adjustment may not have been feasible, and therefore, the only explanatory variable in the GEE model was the time effect. In the GEE analysis, we compared baseline values to those taken after burning incense. To evaluate the robustness of the GEE model, we changed the linking function to log and the distribution to gamma.

Participant characteristics

Table 1 indicates the demographics of participants in our study. This study recruited 18 participants, who were mostly male (88.9%). The average age was 75.1 (± 8.6) years. The average BMI and waist-hip ratio were 24.2 (± 2.1) kg/m², and 95.9 (± 6.4) %, respectively. Additionally, the average duration of COPD and the mean predicted FEV₁ were 5.1 (± 4.3) years and 54.1 (± 14.2), respectively. Five participants (27.8%) reported exercising regularly. The average distance that participants accomplished in the 6-minute walking test was 135.2 (± 136.9) meters.

In terms of weight status, 7 (38.9%) participants were of normal weight and 11 (61.9%) were overweight/obese. With regard to education levels, 2 (11.1%) participants were uneducated, 13 (72.2%) had graduated from elementary school, and 3 (16.7%) had graduated from junior high school or above. Concerning smoking status, 3 (16.7%) participants were non-smokers, 14 (77.8%) were former smokers, and 1 (5.6%) participant was an active smoker. Based on the Taiwan Society of Pulmonary and Critical Care Medicine COPD guidelines (TSPCCM, 2017), the COPD severity concerning 14 participants (72.2%) was moderate, 3 (22.2%) participants had severe COPD, and 1 (5.6%) participant had very severe COPD.

Home environment (including house type and residential location)

Table 2 shows the characteristics of the home environment. Most participants resided in rural areas (83.3%) and opened their windows and doors during the day (77.8%). Most houses were located near low-traffic roads or in lanes where there was a lower risk of harmful PM from traffic emission.

Most days were sunny (77.8%). The average outdoor moisture level was 67.4% (± 10.4%), but the average indoor moisture level was higher, at 68.2% (± 10.3%), (Table 2).

Pollutant concentrations

Our study findings showed that PM₁₀ and PM_2.5 levels were the highest 30 min after incense burning (see Figs. 1 and 2) and that PM₁₀ and PM_2.5 levels were found to be the same as background concentration levels 1 h after incense burning.

The effect of burning incense on PM_2.5 and PM₁₀

Figure 1 illustrates the trend of PM parameters before and after burning incense. The result of the GEE showed that the PM_2.5 concentration levels significantly increased 10 min (B = 439.4, P < 0.01), 20 min (B = 423.2, P < 0.05), and 30 min (B = 439.4, P < 0.01) after burning incense, whereas the PM_2.5 levels 1 h, 3 h, and 5 h after burning incense returned to baseline levels. The results concerning PM₁₀ levels were similar to those of PM_2.5, with concentration levels significantly elevated 10 min (B = 609.6, P < 0.01), 20 min (B = 774.5, P < 0.05), and 30 min (B = 403.2, P < 0.01) after burning incense, and returning to baseline levels 1 h, 3 h, and 5 h after burning incense. In addition, the corrected quasi likelihood under the independence model criterion (QICC) value for PM_2.5 was 30569831 and 25604057 before and after incorporating the time effect, respectively. In contrast, the QICC value for PM₁₀ was 72044297 and 60407238 before and after incorporating the time effect, respectively. Finally, the conclusions were not altered when changing the linking function to log and the distribution to gamma in the GEE model (data not shown).

The effect of burning incense on predicted FEV ₁ and CAT scores

Figure 2 shows the trend of predicted FEV₁ and CAT total scores before and after burning incense. The GEE analyses indicated that the values of both predicted FEV₁ and CAT total scores did not change before and after burning incense. In addition, the QICC value for FEV1 was 31614 and 31690 before and after incorporating the time effect, respectively. In contrast, the QICC value for CAT was 2405 and 2374 before and after incorporating the time effect, respectively. At last, the conclusions were not altered when changing the linking function to log and the distribution to gamma in the GEE model (data not shown). Furthermore, there were no associations among PM₁₀, PM_2.5, and FEV1 (P > 0.05).