Abstract
Background:
Chronic obstructive pulmonary disease (COPD) is a serious lung condition that imposes a significant financial burden on individuals and society, straining the medical system. According to the World Health Organization, it was the third leading cause of death worldwide in 2020. In India, it ranks as the second leading cause of death, and in Tamil Nadu, it is the tenth. The Global Burden of Disease study in 2018 found that COPD accounted for 50% of all cases and 69% of disability. Outdoor air pollution plays a major role in India’s burden of chronic respiratory diseases. Early diagnosis and intervention can help to alleviate symptoms, prevent complications, and reduce morbidity and mortality, ultimately improving quality of life.
Objectives:
(1) To estimate the prevalence of COPD among the study population (2) To assess the risk factors associated with COPD among the study population.
Methodology:
A community-based cross-sectional study was conducted among adults along the roadside dwelling of a National Highway. Using a multi-stage random sampling technique 403 elderly was selected. Participants were interviewed by a pre-tested structured questionnaire followed by spirometry (pulmonary function test) evaluation. Data entry was performed in an Excel sheet and analyzed using SPSS. The odds ratio and Chi-square test were performed to determine the association between qualitative variables.
Results:
Among 403 study population 58% were male and 42% were female. The prevalence of COPD was found to be 22%, it was 11.1% among males and 10.9% among females. It is evident that individuals, who had exposure to risk factors such as cigarette smoking 78%, overcrowding 35.8%, lack of cross ventilation 10.9%, and living near a highway within 50 m of distance 36.2% are at more risk for developing COPD.
Conclusion:
Study revealed that people living in closer proximity with roadways increases the risk of COPD.
Keywords: COPD, ETS-environmental tobacco smoke exposure, indoor environment, outdoor environment, respiratory symptoms, roadside dwellers
INTRODUCTION
Chronic obstructive pulmonary disease (COPD) is a devastating lung condition that imposes a significant financial burden on individuals and society, straining the medical system. According to the World Health Organization (WHO), it was the third most common cause of death globally in 2020. The 2018 Global Burden of Disease study revealed that COPD contributed to 50% of all cases and 69% to disability.[1] More than 90% of COPD deaths occur in low- and middle-income countries. Sustainable development goals and India’s National Health Policy aim to reduce non-communicable diseases by one-third by 2030, including COPD.[2] In India, it is the second leading cause of death, and in Tamil Nadu, the fourth in 2016, according to a UNFPA report.[3] COPD is a leading cause of morbidity and mortality worldwide.[4,5] The Disability-Adjusted Life Years (DALY) estimates reveal that COPD leads to 1.68 years of healthy living lost due to disability per 100,000 populations, contributing about 1.8% of all Years Lost due to Disability (YLD). Outdoor and household air pollution combined contribute significantly to India’s burden of chronic respiratory diseases.[3] In India, the prevalence of COPD was reported to be 3.49% by a statewide questionnaire-based survey, with rates ranging from 1.1% in Mumbai to 10% in Thiruvananthapuram.[6] However, this burden may have been underestimated because spirometer tests were not used to diagnose COPD. The spirometer is essential for diagnosing COPD and is a simple, reliable, non-invasive, safe, and inexpensive investigation for evaluating airflow limitation. Reduction in FEV1 (forced expiratory volume in 1 second) is a hallmark of airway obstruction, and in COPD, there is usually a progressive decline in FEV1 every year compared to normal healthy adults.[7] A systematic review of the literature has shown that reduced FEV1 nearly doubles the risk for cardiovascular mortality, independent of age, sex, and cigarette smoking.[8,9,10] Passive smoking from male smokers inside the home is a predominant risk factor for COPD in non-smoker females.[11] The prevalence of respiratory symptoms like chronic cough, chronic sputum, breathlessness, and wheezing was significantly higher among smokers compared to non-smokers.[12] Outdoor air pollutants include heavy particulate matter, carbon dioxide, sulfur dioxide, nitrogen dioxide (released by the burning of coal and petroleum fossil fuels), and ozone. A community-based study observed that higher traffic density was significantly associated with lower FEV1.[13] There is a paucity of studies that measure outdoor air pollutant levels to objectively correlate them with adverse health effects.[14] Individuals living within 50 m of a highway are exposed to pollution created by vehicles on the road.[15] Hence, this study was conducted to determine the prevalence of COPD and its risk factors among persons living near roadsides.
METHODOLOGY
After receiving approval from the Institutional Ethical Committee (1133/IEC), a community-based cross-sectional study was conducted over a period of six-month from February to July 2022 along National Highway (NH-32) from Perungalathur to Singaperumal Kovil in Kattankulathur Block.
Study participants
The study included roadside dwellers whose households were within approximately 50 m (or 150 footsteps) of the National Highway (NH-32). Adults above 30 years old who had lived within this proximity for at least one year were eligible to participate. Exclusion criteria were individuals who were physically unable to undergo a spirometry test due to recent thoracic, abdominal, or eye surgery, myocardial infarction in the past 3 months, hospital admission for any cardiac condition in the past 3 months, undergoing antibacterial chemotherapy for tuberculosis or other chemotherapy treatments, pregnant or breastfeeding women, and those who did not give consent to participate in the study.
Sampling technique
The study used a multi-stage sampling technique. Town panchayats from Perungulathur to Singaperumal Kovil were listed, and Guduvanchery Town panchayat was selected using a lottery method. Within the selected panchayat, an important landmark (such as a school, temple, or church) was chosen for conducting spirometry procedures on the selected participants. Participants were then selected from either side of National Highway NH-32 until the estimated sample size was achieved, and they were investigated randomly.
Study variables
A semi-structured questionnaire was used to collect the data, it contains detailed information on socio-demographic characteristics, anthropometry measurements, respiratory symptoms, risk factors for COPD, details on the indoor and outdoor environment, behavioral aspects, environmental tobacco smoke exposure, and occupational exposure, a questionnaire has been validated through a pilot study.
Sample size estimation
The sample size was calculated using formula 4pq/d2 based on the prevalence rate of 30%[6] q = 70% d = 5% and adding 20% of the non-respondent rate, the total sample size was calculated as 403.
Data collection method
After obtaining consent, a brief introduction was given to the participants regarding the purpose of the study and its benefits. Participants were interviewed in the local language. Subjects had a spirometry evaluation after a clinical examination for respiratory problems. Since an individual’s height and weight primarily affect spirometry, it is necessary to compare each observed value to the reference values—also referred to as predicted values—for that specific age, height, and weight collected to interpret the results. By using the same anthropometric measurements on normal patients, predicted values can be determined.
Spirometry
The procedure for doing spirometry was explained in detail to each participant before starting the procedure. A pulmonary function test was performed using a portable data-logging spirometer. The test was formed by asking the patient to sit and providing a mouthpiece and asking them to seal around the mouth and make sure that the tongue did not occlude it. Then the subject was asked to inhale completely as much as possible and exhale maximally. Then the subject was encouraged verbally to continue exhale till the end of the maneuver to obtain optimal effort. Three times the maneuver was repeated. Spirometer that is designed to facilitate the total valuation of lung function such as forced vital capacity (FVC), vital capacity (VC), and maximal voluntary ventilation (MVV) tests. FVC, forced expiratory volume in 1 sec (FEV1), peak expiratory flow rate peak expiratory flow rate (PEFR), and mid expiratory volume (FEF 25_75%) values,
Interpretation of spirometry
Spirometry is influenced mainly by the height and weight of the individual, for interpretation, each observed value requires comparison with the reference values (also known as predicted values) for that particular age, height, and weight. Predicted values can be estimated from the normal subjects of the same anthropometric measurements.
Finally, the FEV1 Value was recorded, where FEV1 (forced expiratory volume) measures the rate at which air in the lungs is exhaled at 1 sec, and 80% of the air is exhaled in the first 1 sec of expiration.
COPD was diagnosed by the following criteria:
(1) Cough with expectoration on most days for 3 or more months of a year for at least 2 consecutive years. (2) FEV1 (Forced expiratory volume in 1 sec) lower than 80% predicted by the spirometer.
DIAGNOSIS: After questionnaire-based evaluation, each person underwent a clinical examination and a spirometry evaluation using the GOLD criteria (Global Initiative for Chronic Obstructive Lung Disease) to diagnose COPD.
Data analysis
Data was entered into an Excel sheet and analyzed using a statistical package for social sciences. Descriptive data were presented as simple proportions or percentages. The odds ratio was used to measure the strength of the association and a 95% confidence interval was calculated. The Chi-square test was used to lend statistical support to prove the association between categorical variables.
RESULTS
Among the participants, 403 adult males were (58%) and females (42%). Male participants were predominant in the study compared to females. Mean age of the participants was found to be 37 ± 1 (M ± S.D) years. The majority of the study population were belonging to the Hindu religion (77%). Most of them are married (90.1%). The majority of the study participants were literate (92%). The majority of the study participants (31.5%) include retired persons, drivers, carpenters, welders, Cooley, and unemployed [Table 1]. Figure 1 represents the prevalence of respiratory symptoms, among the study population (10.4%) are wheezing, feeling of chest tightness (10.9%), shortness of breath after exercise (11.7%), coughing in the morning (13.4%), sputum in the morning (11.2%) at least 3 consecutive months (6.9%) ever experienced shortness of breath (19.6%).
Table 1:
Socio-demographic characteristics
| Socio-demographic profile | Frequency (n) | Percentage (%) |
|---|---|---|
| Age | ||
| 30-40 years | 209 | 51.9 |
| 41-50 years | 96 | 23.8 |
| 51-60 years | 65 | 16.1 |
| >60 years | 33 | 8.2 |
| Sex | ||
| Male | 234 | 58 |
| Female | 169 | 42 |
| Religion | ||
| Hindu | 313 | 77 |
| Christian | 63 | 16 |
| Muslim | 27 | 7 |
| Marital status | ||
| Married | 362 | 90 |
| Unmarried | 37 | 9 |
| Widow | 3 | 0.7 |
| Widower | 1 | 0.2 |
| Educational status | ||
| Illiterate | 32 | 7.9 |
| Primary | 30 | 7.4 |
| Middle | 105 | 26.1 |
| Higher secondary | 90 | 22.3 |
| Graduate | 146 | 36.2 |
| Occupation | ||
| Professional | 63 | 15.7 |
| Industry | 90 | 22.3 |
| Business | 22 | 5.5 |
| Housewife | 100 | 24.8 |
| Others | 128 | 31.7 |
| Socio-Economic | ||
| Status | 25 | 6.2 |
| Upper (I) | 80 | 19.8 |
| Upper middle (II) | 120 | 29.8 |
| Lower middle (III) | 134 | 33.2 |
| Upper lower (IV) | 44 | 10.9 |
| Lower (V) |
Figure 1.
Proportion of respiratory symptoms
Table 2 shows COPD prevalence and risk factors. The prevalence of COPD among the study participants was 22%, among males the prevalence is 11.1%, and among females is 10.9%.
Table 2:
Association between risk factors and COPD
| Risk factors | COPD Present | COPD Absent | Crude OR, [95%CI], P | Adjusted OR, [95%CI], P |
|---|---|---|---|---|
| Age | ||||
| 31–40 | 49 (23.4%) | 160 (76.5%) | 1 | |
| 41–50 | 19 (19.7%) | 77 (80.2%) | 0.80, 0.44–1.46, <0.47 | - |
| 51–60 | 11 (16.9%) | 54 (83%) | 0.66, 0.32–1.37, <0.26 | - |
| >60 | 10 (30.3%) | 23 (69.6%) | 1.41, 0.63–3.18, <0.39 | - |
| Gender | ||||
| Male | 45 (19.2%) | 187 (79.9%) | 0.69, 0.43–1.11, <0.13 | - |
| Female | 44 (26.0%) | 127 (75.1%) | ||
| Educational Status | ||||
| Graduates | 21 (14.3%) | 125 (85.6%) | 1 | |
| School education | 57 (25.3%) | 168 (74.6%) | 3.64, 2.10–6.33, <0.0001* | 2.13, 0.66–6.73, <0.2 |
| Illiterate | 11 (34.3%) | 21 (65.6%) | 4.19, 1.77–9.89, <0.001* | 0.82, 0.19-3.34, <0.7 |
| Occupation | ||||
| Professional | 4 (6.3%) | 59 (93.6%) | 1 | - |
| Industry | 18 (20%) | 72 (80%) | 3.68, 1.18–11.49, <0.025* | 0.76, 0.13–4.56, <0.81 |
| Business | 5 (22.7%) | 17 (77.3%) | 4.33, 1.04–17.96, <0.043* | 0.91, 0.16–5.67, <0.21 |
| Housewife | 23 (23%) | 77 (77%) | 4.40, 1.44–13.43, <0.009* | 0.87, 0.12–6.13, <0.13 |
| Others | 39 (30.4%) | 89 (69.5%) | 6.46, 2.19–19.03, <0.007* | 1.32, 0.94–8.75, <0.08 |
| Smoking Status | ||||
| Non-smoker | 59 (16.2%) | 305 (83.8%) | 17.23, 7.77–38.17, <0.001* | 3.59, 1.19–10.76, <0.023* |
| Smoker | 30 (76.9%) | 9 (23.07%) | ||
| Environmental Tobacco Smoke Exposure | ||||
| ETS among family members | ||||
| Present | 30 (71.4%) | 12 (28.5%) | 12.76, 6.1–26.4, <0.001* | 7.15, 1.63–31.25, <0.009* |
| Absent | 59 (16.3%) | 302 (83.6%) | ||
| ETS among friends and colleagues | ||||
| Present | 22 (73.3%) | 8 (26.6%) | 12.6, 5.4–29.4, <0.001* | 6.87, 1.56–12.84, <0.13 |
| Absent | 67 (17.9%) | 306 (82.1%) | ||
| ETS among work site | 9 (30%) | |||
| Present | 21 (70%) | 10.4, 4.59–23.8, <0.001* | 4.67, 1.24–13.06, <0.06 | |
| Absent | 68 (18.2%) | 305 (81.8%) | ||
| Outdoor Environmental Exposure | ||||
| Doing leisure activities | 12 (22.6%) | 41 (77.4%) | 1 | 1.19, 0.43–3.26, <0.73 |
| Regular Travel | 47 (16.6%) | 235 (83.5%) | 0.68, 0.33–-1.39, <0.296 | |
| During Working | 30 (44.1%) | 38 (55.8%) | 2.69, 1.21–6.01, <0.015* | |
| Exposure to dust Particle | ||||
| Exposure to dust | ||||
| Present | 10 (40%) | 15 (60%) | 2.5, 1.09–5.83, <0.030* | 0.60, 0.16–2.19, <0.04 |
| Absent | 79 (20.8%) | 299 (79.1%) | ||
| Indoor Environmental Exposure | ||||
| Overcrowding | ||||
| Present | 58 (35.8%) | 104 (61.9%) | 5.58, 3.21–9.6, <0.001* | 1.21, 0.57–2.60, <0.61 |
| Absent | 21 (9.1%) | 210 (90.9%) | ||
| Cross ventilation | ||||
| Present | 30 (10.9%) | 243 (89.1%) | 6.5, 3.88–10.88, P<0.001* | 0.15, 0.71–3.40, <0.001* |
| Absent | 59 (45.4%) | 71 (54.6%) | ||
| Separate kitchen | ||||
| Present | 66 (19.4%) | 274 (80.5%) | 2.39, 1.33–4.25, <0.003* | 0.61, 0.25–1.48, <0.27 |
| Absent | 23 (36.5%) | 40 (63.5%) | ||
| Use of mosquito coils | ||||
| Present | 58 (27.8%) | 151 (72.2%) | 9.83, 5.20–17.58, <0.001* | 2.39, 1.17–4.88, <0.01* |
| Absent | 31 (15.9%) | 163 (84.1%) | ||
| Use of Incense | ||||
| Present | 81 (21.8%) | 291 (78.2%) | 0.80, 0.35–1.86, <0.603 | 1.55, 0.45–5.25, <0.48 |
| Absent | 8 (25.8%) | 23 (74.1%) | ||
| Distance from Highway | ||||
| <100 footsteps | 13 (%) | 23 (%) | 2.16,1.05–4.47, <0.03* | 2.15, 1.04–4.46, <0.04* |
| 101–150 footsteps | 76 (%) | 291 (%) |
P*- significance (<0.05) 1=Reference
Participants with a school education are 3.64 odds more likely to develop COPD compared to graduates. Additionally, illiterate participants are at even higher risk, with a 4.19 odds higher likelihood. Certain occupations, such as carpenter, driver, welder, Cooley (possibly a typo, perhaps you meant “coolie”), and retired persons, are associated with a 6.4 odds of higher risk of developing COPD compared to professionals (P < 0.007). Participants experiencing morning cough are at a significantly higher risk of developing COPD, with a 19.7 odds greater likelihood (P < 0.0001). Smokers face a significantly elevated risk of developing COPD compared to non-smokers, with a striking 17.23 odds increase in likelihood. Exposure to tobacco smoke within the family, termed passive smoking, also poses a substantial risk, showing a 12.76 odds higher likelihood (P < 0.001). Similarly, exposure to tobacco smoke from friends or colleagues presents a significantly heightened risk, with a 12.6 odds (P < 0.001). Individuals exposed to tobacco smoke in the workplace, also known as passive smoking, have a 10.4 odds of higher risk of developing COPD (P < 0.001). The odds of having COPD are 2.18 for individuals who reside in semi-pucca houses and 6.80 times higher in katcha houses (P < 0.0001). Overcrowded houses higher risk of COPD compared to non-overcrowded houses (OR; 3.21–9.6, P < 0.001). Lack of cross ventilation (OR; 3.21–9.6, P < 0.001), while houses without a separate kitchen are associated (OR; 1.33–4.25, P < 0.003), the use of mosquito coils in the house (OR; 5.20–17.58, P < 0.001) are at higher risk for COPD.
A higher risk of COPD is noted among dwellers those who reside very close proximity to the National Highway of less than 150 footsteps (OR; 1.05–4.47, P < 0.03) and workers who have exposure to vehicle pollution during working (drivers, shop keepers, coolie, and mason) (OR; 1.21–6.01, P < 0.01), those who have regular exposure to dust (OR; 1.09–5.83, P < 0.03).
Multiple logistic regression analysis for variables revealed a significant association with variables such as sex, respiratory symptoms breathlessness, smoking, environmental tobacco smoke (Family members), lack of cross ventilation, regular use of mosquito coil, distance <150 footsteps with P value with COPD at P < 0.05.
DISCUSSION
The present study determined the prevalence of COPD in persons 30 years of age and older out among the roadside dwellers of a National Highway and identified risk factors related to the disease. There can be conflicting prevalence estimates in the published literature due differences in use of methodologies like physician-diagnosed COPD, self-reported symptoms, respiratory symptoms, and measurement of airflow limitation and definitions. The spirometer is one of the most useful tools to assess COPD. It is also evident from previous studies that diagnosis of airflow limitation helps in preventing the progression of disease.[16] Hence spirometer was used in the present study, in the field application, there were practical challenges such as lengthy and time-consuming that required the utmost patient effort. In our study, 22% of participants had COPD, which is very similar to the results of a prior study conducted among individuals over 25 in a rural area of northern Italy, which revealed that the prevalence was 18.3%.[17] A study by Danielsson P et al.[18] in 2011 on people 40 years of age and older also found a nearly comparable prevalence of 16.2%. In comparison to the current study, some field investigations conducted in India have revealed an extremely low prevalence of COPD, ranging from 2% to 9%.[19] The variation in prevalence estimates between above-mentioned studies and the current study may be due to a variety of factors such as differences in the definition of a COPD case, variation in study instruments (such as the questionnaire), and use of different diagnostic techniques (such as spirometry). In contrast to the majority of Indian studies,[6,20] the current study used a spirometer in addition to the questionnaire. Utilizing both the questionnaire and measuring equipment for airflow limitation is useful for epidemiological investigations because it may reduce the false positive rates of patient identification associated with either tool individually.[21] The present study observed prevalence of COPD among males (11.1%) and females (10.9%) was more or less equally distributed, it is considerably higher than the prevalence of 9% in males and 5% in females reported by previous studies in India[14] which used diagnostic criteria (i.e.,) peak flow meter. A total of 11.1% of males and 10.9% of females. Passive smoking inside the house is found to be a major risk factor for COPD in non-smoker females.[11] About 78% of current smokers were found to have COPD, which was higher when compared to 46.6% reported by Vandevoorde J et al.[21] In the present study, inadequate ventilation was significantly associated with the development of COPD (P = 0.00). This finding is agreeable with the findings of the study in Chinese rural areas by Ran PX et al.[22] who reported an odds ratio of 1.97,95%CI = 1.06–2.03 for worse ventilation and a study by Priscilla Johnson et al.[23] This may be due to women spending most of their time indoors and having more cooking exposure, ETS exposure, inadequate ventilation, lack of a separate kitchen, and use of mosquito coil. The current study found that participants who had their residence in close proximity of a National Highway that is within 150 footsteps are at 2.162 times at higher risk of developing COPD. Our results are similar when comparing the study conducted by Andrea j. Venn, et al.[24] observed subjects who had their residence near the main road that is within 90 m are at higher risk of developing asthma, wheezing, and other respiratory problems.[22] Lower socio-economic status and higher prevalence of COPD were observed in the present study with a significant P value of 0.000, these findings are also in harmony with findings reported by Viegi G et al.,[25] Sasirekha B et al.[26] which stated, that factors like overcrowding and poorly ventilated housing could make the lower socio-economic class people more vulnerable to the disease and COPD along with economic burden impairs the quality of life of people.
Limitations
Bronchodilator reversibility was not assessed to distinguish COPD from other obstructive lung diseases, since it is difficult to assess in the field. However, the current study included a questionnaire to clinically rule out respiratory symptoms. Possible biases that can occur in this study are reporting, recall bias, and instrumental bias. Compared to undergoing a spirometry test directly, self-reported cases of COPD and asthma, as well as individuals lacking access to healthcare, present certain limitations. The study only looked at semi-urban areas.
CONCLUSION
The present study investigated the respiratory health of roadside dwellers in the selected area and revealed close proximity to roadways increases risk for COPD. Our findings strongly recommend that health policymakers should pay attention to create preventive measures to reduce the risk of COPD among residents who live in close proximity to the main road, and awareness campaigns for regular screening and treatment. Further long-term research encompassing a larger community of roadside dwellers is required.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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