Iranian Sub Cohort Chronic Obstructive Pulmonary Disease (IrSCCOPD): Need for Longitudinal Observational Studies COPD in Southwest of Iran

doi:10.21203/rs.3.rs-152306/v1

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Research Article

Iranian Sub Cohort Chronic Obstructive Pulmonary Disease (IrSCCOPD): Need for Longitudinal Observational Studies COPD in Southwest of Iran

https://doi.org/10.21203/rs.3.rs-152306/v1

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published 25 Mar, 2021

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Background: Chronic obstructive pulmonary disease (COPD) is a chronic and complex respiratory disorder that is associated with the airflow limitation and increased inflammatory response of the lungs to harmful particles and gases. The purpose of this original study was to describe the profile of Shahrekord PERSIAN Cohort Study regarding COPD in southwestern Iran.

Methods: This study of asthma and respiratory diseases is a subcohort of the larger cohort study, i.e., Shahrekord PERSIAN cohort, a population-based prospective study on people aged 35-70 years in southwestern Iran (n=10,075). The sample size of the subcohort was 8500 people. Annual follow-ups (person-year) of the cohort were designed to be conducted up to 2036. The instruments to collect data on various exposures were derived from the questionnaires previously developed in extensive multinational studies (occupational exposures, smoking, housing status, and fuel consumption, history of respiratory and chronic diseases, comorbidity, etc.). The Global Initiative for Chronic Obstructive Lung Disease (GOLD) and the lower limit of normal (NLL) spirometric criteria were used to confirm COPD diagnosis.

Results: The response rate was 93.85%. The mean age of the participants was 49.48 ± 9.32; 47.9% were male and 52.9% were female; about 20% were in rural areas and nearly 16% of the population was current smokers; the fuel used by most of the participants for heating the house and cooking was gas. The most common comorbidity among participants was dyslipidemia; 30% of people have three or more comorbidities. According to GOLD and LLN criteria, 3.6% and 8.4% of participants had COPD, respectively. 4.3% of the participants had a history of chronic lung disease. The mean FEV1/ FVC was 92.48 (SD, 7.47), the mean FEF 25-75 was 3.43 (SD, 1.28) L. 47.6% had a history of chronic phlegm; 2.7% of the participants had shortness of breath and wheezing

Conclusion: Epidemiological research is necessary to create an appropriate framework to fight COPD. This framework requires a better description of men and women at risk of developing COPD and describing people with early-stage illnesses.

Pulmonology

Profile

Chronic Obstructive

Pulmonary Disease

Longitudinal

Cohort study

Iran

Chronic obstructive pulmonary disease (COPD) is a complex respiratory disorder that is caused by airflow limitation and increased inflammatory response of the lungs to harmful particles and gases, which is usually progressive and irreversible [1]. According to the World Health Organization, COPD is not a single disease but is a so-called umbrella disease that covers a wide range of pulmonary diseases, including emphysema and bronchitis[2]. It affects 6-10% of the world's population [3] and is one of the most important causes of mortality and disability across the globe [4]. The burden of COPD has risen over time [5] and the current costs associated with this disease are remarkable and will increase in the future [6,7].

In a recently published meta-analysis study, the pooled prevalence of COPD was 15.70%. Among all WHO regions, the highest prevalence was in the Americas and the lowest was in the Southeast Asia / West Pacific region [8]. In Iran, the prevalence of COPD in estimating the burden of obstructive pulmonary disease was 8.3% [9]. The prevalence of COPD in Tehran, the capital of Iran, was 9.2% [10] and in Isfahan, )neighboring Chaharmahal and Bakhtiari province( was 5.7% [11]. In another study in Iran from 5 different geographical areas in Iran (north, south, east and center) the overall prevalence of COPD was 4.9%, which is the highest province of Kerman (13.9%) and then Tehran 4.4%, Ahvaz was 3.8%, Mazandaran was 3.7% and Mashhad was 2.8%, respectively [12].

Despite the significant impact of COPD on health and the economy, this chronic disease has not yet drawn enough attention from the public healthcare institutes and is not known among the general population. One possible reason for this great problem is the lack of epidemiological data on the prevalence and risk factors of COPD in developing countries, especially in Iran. According to previous studies, the diagnosis of COPD is underreported in Iran[10].

Evidence and epidemiological data on the status and progression of COPD in Iran are very limited and contradictory; the methods for examination of this disease in various studies are different and there is a paucity of evidence about the natural history of the disease. On the other hand, inconsistencies in information on the prevalence of COPD, chronic bronchitis and asthma in the Iranian population may affect the decision made by health care system officials, policymakers and insurance organizations, and may prevent them from taking satisfactory preventive and treatment measures in order to prevent potential serious effects and stupendous costs [13].

Therefore, this longitudinal study was conducted to investigate the need for longitudinal observational studies on COPD in Chaharmahal and Bakhtiari province, southwestern Iran. The province is geographically located at approximately 2,153 meters above sea level and is known as the roof of Iran. The effect of altitude on other medical conditions, such as pulmonary hypertension and heart failure, has previously been reported, but the potential mechanisms proposed for the effect of altitude on the prevalence of COPD are highly contradictory and controversial. In the PREPOCOL-PLATINO-BOLD-EPI-SCAN study, authors claimed that "known risk factors were less frequent at high altitude and high altitude had no significant influence in COPD prevalence" [14], while the results of PREPOCOL study in five Colombian cities and four geographically diverse in Peru showed that the prevalence of COPD increased with increasing altitude [15, 16].

In Iran, especially Chaharmahal and Bakhtiari province, no cohort study has yet been conducted to investigate the problems of lack of diagnosis of COPD and the need for intervention. Therefore, this work is a futuristic cohort study with a 20-year follow-up period in Chaharmahal and Bakhtiari, southwestern Iran, making it possible to do a cross-sectional and longitudinal analysis of data.

The study of asthma and respiratory diseases is a sub cohort of a larger cohort study, i.e., Shahrekord Cohort Study (SCS), which is a population-based prospective study on people aged 35-70 years in southwestern Iran. SCS was designed to serve as one of the centers of the Prospective Epidemiological Research Studies in IrAN (PERSIAN) Cohort and is being conducted in southwest of Iran [17]. The sample size of the subcohort was 8500 people. This study began in November 2015 in Shahrekord, and has been scheduled to continue until 2036, with a total follow-up of 200,000 person-years each year (Flowchart1). Details of the protocol and the objectives of this study have already been published [18].

2.1. Outcome definition.

The main outcome of this study is COPD and mortality from that. COPD is an airway inflammatory disease that is associated with continuous airflow limitation, which is usually progressive and irreversible. The most common symptoms of COPD are coughing, phlegm production and difficulty breathing that should be considered for the clinical diagnosis of the disease [19]. However, none of the symptoms is sufficient for make a diagnosis, and if there are several additional symptoms and tests to diagnose the disease, the likelihood of a diagnosis of COPD increases. According to ICD-10, COPD includes emphysema and chronic bronchitis. Chronic coughing is usually the first symptom that occurs. Chronic bronchitis is defined as a condition of cough and sputum for at least 3 months for two consecutive years during the past year. Diagnosis of emphysema is only possible by describing the changes in the anatomy of the lung tissue and cannot be considered a disease per se [1, 20]. The most common and easiest way to confirm the diagnosis of COPD is spirometry. Most studies have only used a questionnaire to diagnose COPD, but in this study, both instruments were used for the diagnosis of COPD (Table 1).

A pulmonary function test was conducted by using a spirometer (New Spirolab, MIR, Italy, 2015) according to the criteria of the American Thoracic Society/European Respiratory Society (ATS/ ERS). All tests were conducted in a quiet room in a sitting position on a comfortable chair. The spirometer was calibrated using a syringe by trained technicians daily before the study began. All participants were informed about all stages in the investigation and the pulmonary function test. All steps of the spirometry maneuver were performed practically by technicians so that the participant could see how to do proper inhaling and exhaling. The person was instructed to take a deep, full breath and then exhale strongly. Deep and complete inhalation is no less important than strong and complete exhalation. Inadequate and incomplete inhalation will lead to an insufficient volume of exhalation, resulting in a false decrease in forced vital capacity values and an increase in the likelihood of a restrictive pattern. Pulmonary function tests were conducted in triplicate for each individual with a single and acceptable method. By comparing the curves of the three pulmonary function tests, the maximal values of FEV1 (forced expiratory volume in one second) and FEV6 (forced expiratory volume in 6 second) forced vital capacity (FVC), maximum peak expiratory flow (PEF) in 25%, 50% and 75% of FVC (PEF25-75), and Maximum Ventilatory Volume (MVV) were obtained. Spirometry data were interpreted according to the ATS/ ERS recommendations by two respiratory medicine specialists. The pulmonary function test parameters values were presented as the percent of predicted values for the respective age, height, and weight [21].

The GOLD criteria (The Global Initiative for Chronic Obstructive Lung disease) uses a fixed ratio of forced expiratory volume in 1 s (FEV1) over forced vital capacity (FVC) <0.7 for the diagnosis of COPD [22]. Although, using this fixed ratio is easy and common, but the value varies greatly with age and decreases with age, thus leading to underestimation in adults under 45 years and overestimation in older people [23, 24]. For these reasons, ATS (the American Thoracic Society) and ERS (the European Respiratory Society) recommends setting the cut-off to 5% of normal to avoid potential Misclassification [25, 26]. Therefore, in this study, Spirometry data were expressed in predicted percentage according to the lower limit of normal (LLN), FEV1/FVC ratio < LLN, and also according to the GOLD criteria with a constant ratio FEV1/FVC < 0.70 and FEV1 < 80%. In addition, COPD severity was determined for all participants according to the GOLD criteria as follows: Stage 0 (at risk); stage 1 (mild): FEV1/FVC < 70% and FEV1 ≥ 80%; stage 2 (moderate): FEV1/FVC < 70% and 50% ≤ FEV1 < 80%; stage 3 (extreme): FEV1/FVC < 70% and 30% ≤ FEV1 < 50%; and stage 4 (extremely severe): FEV1 / FVC < 70% and FEV1 < 30% [1, 27].

Contraindications for the use of spirometry drugs included cardiac infarction, pulmonary embolism, diagnosed aneurysm, uncontrolled blood pressure over 140/200, previous surgery on the eyes, ears, brain, abdomen and chest, liver, heart or kidney failure, cancer, and endocrine disorders).

2.2. Definition of exposures.

A questionnaire was used to collect information about various exposures. After obtaining informed consent, complete information about various exposures was collected by experienced interviewers through face-to-face interviews. The main questionnaire used in this study was derived from valid questionnaires that had been used in multinational studies. Using this questionnaire, the main exposures of COPD disease are specifically studied. The questionnaire also addresses history and current occupational exposures, individual history and habits (smoking, alcohol, tobacco smoking and drinking), as well as sedentary time, the age at which smoking began and the stages of change of readiness to quit smoking in current smokers, fuel status for home heating and cooking, housing situation, history of contact with animals, exposure to agricultural toxins, pesticides and detergents.

All participants were asked questions about medical history including pulmonary diseases, the history of asthma in childhood, respiratory symptoms, respiratory infections, chronic illnesses, drug use, family history of respiratory and pulmonary diseases, and questions about whether Have you ever had a doctor or other health care professionals diagnose one of the following conditions:Chronic bronchitis, emphysema, pulmonary fibrosis and sleep apnea.

Comorbidities about which the subjects were asked questions due to their clinical significance in COPD, included cardiovascular disease (myocardial infarction, cardiac ischemia, and stroke), hypertension, type 2 diabetes, syndrome metabolic, dyslipidemia, anxiety, depression, Osteoporosis, fatty liver, Rheumatoid Arthritis, pulmonary fibrosis [21].

In terms of smoking, the participants were divided into three groups as follows: Non-smokers, i, e., the people who never or occasionally smoked (those who have not yet smoked or have smoked less than 100 cigarettes during their lifetime); current smokers, i.e., the people who smoke one or more cigarettes a day; and ex-smokers, i.e., the people who are not currently smokers but smoked regularly in the past). Current exposure to cigarette smoke or passive smoking, was also considered to be smoking-positive given the smoking of other family members or colleagues and exposure to parental cigarette smoke in childhood.

Other additional variables such as anthropometric measurements and laboratory variables, which have already been published in the SCS protocol, were also collected [18].

2.3. Generalizability of cohort (external cohort credibility).

Sub cohort COPD was designed for a sample of approximately 10,075 people aged 35-70 years (7034 people in urban areas and 3,041 rural areas) for a 20-year period in Chaharmahal and Bakhtiari province, southwest of Iran. It seems that since this cohort contains a balanced ratio of men and women and urban and rural populations, it is likely to represent the community.

The response rate was 93.85%. Based on the results, a total of 7978 people participated in the sub cohort COPD, 6388 (80.1%) were urban and 1590 (19.9%) were rural; the mean age of the population in the cross-sectional study was 49.48 (the standard deviation (SD), 9.32) yrs.; 47.9% were male and 52.9% were female; 94.3% were married; 48.6 % were of the Ethnicity Fars and 39.1% were of the Ethnicity Lor Bakhtiari; 14.3% of the participants were illiterate and 34.7% of participants were in the 35‐44 age category. 51.6% of the participants were housewives/unemployed/retired and 18.2% were employees (Table 2).

The mean body mass index of the participants was 27.70% (SD, 4.58); 44.9% of the population had overweight (25-30) and 27.4% had obesity (>30). Nearly 16% of the population was current smokers, with a higher proportion of men than that of women (33.3% VS 0.4%). The fuel used by most of the participants for heating the house and cooking was gas (65.2%) and also, the type of kitchen or cooking area for most participants was an open kitchen inside the house (74.9%). The most common comorbidity among participants was dyslipidemia (71.9%) and later hypertension (27.1 %). 31.7% of participants had at least one comorbid and 30% of people have 3 or more comorbidities (Table 3).

According to the GOLD criteria, 289 (3.6%) patients had COPD, and according to the LLN criteria, 673 (8.4%) had COPD. The mean FEV1 was 2.84 (SD, 0.79) L; the mean FEV6 was 2.08 (SD, 0.86) L; the mean FVC was 3.08 (SD, 0.86) L; the mean PEF was 5.07 (SD, 2.09) L; the mean FEV1/ FVC was 92.48 (SD, 7.47), the mean FEF 25-75 was 3.43 (SD, 1.28) L, the mean MVV was 99.67 (SD, 27.7) L/Min. 4.3% of the participants had a history of chronic lung disease (asthma, tuberculosis, emphysema, and bronchitis) and also 13% of the participants had a history of chronic cough and of those who had a chronic cough, 47.6% had a history of chronic phlegm; 2.7% of the participants had Shortness of breath and wheezing (Table 4).

Table 1- Prognostic and outcome measures flow chart

Measures Outcome and Exposure

Spirometry

pre- bronchodilator

Questionnaires (self-reported)

history and current occupational exposures, individual history and habits (smoking, alcohol, tobacco smoking and drinking), as well as sedentary time, the age at which smoking began and the stages of change of readiness to quit smoking in current smokers, fuel status for home heating and cooking, Housing status, history of contact with animals, exposure to agricultural toxins, pesticides and detergents
medical history including pulmonary diseases, the history of asthma in childhood, respiratory symptoms, respiratory infections, chronic illnesses, drug use, family history of respiratory and pulmonary diseases, and questions about whether Have you ever had a doctor or other health care professionals diagnose one of the following conditions: Chronic bronchitis, emphysema, pulmonary fibrosis and sleep apnea
Comorbidities including cardiovascular disease (myocardial infarction, cardiac ischemia, heart failure, myocardial infarction and stroke), hypertension, type 2 diabetes, syndrome metabolic, dyslipidemia, anxiety, depression, renal failure, fatty liver, musculoskeletal disorders, pulmonary blood pressure, Gastroesophageal reflux disease (GERD), pulmonary cancer, pulmonary fibrosis.

Physiology

blood pressure, heart rate, Electrocardiogram(EKG),

breathlessness on exertion

Anthropometry

height, weight, waist/hip/wrist circumference, Body components (fat, water, muscle), bio impedance

Blood samples

fasting blood sugar, serum triglyceride, total cholesterol, low and high density lipoprotein, cholesterol

COPD Assessment Test (CAT)

Only COPD and at-risk

Routine data

Link all variables to Shahrekord PERSIAN cohort

COPD, chronic obstructive pulmonary disease

Table 2-Baseline characteristics of the sub cohort

Variables	Total N = 7978	Urban N = 6388	Rural N = 1590
Age- Mean ± SD Years	49.48 ± 9.32	49.04 ± 9.20	51.25 ± 9.58
35‐44 Years	2772 (34.7 %)	2326 (36.4 %)	446 (28.1 %)
45‐54 Years	2708 (33.9 %)	2185 (34.2 %)	523 (32.9 %)
55‐64 Years	1914 (24 %)	1460 (22.9 %)	454 (28.6 %)
>=65	584 (7.3 %)	416 (6.5 %)	167 (10.5 %)
Sex
men	3824 (47.9 %)	3198 (50.1 %)	625 (39.3 %)
Female	4154 (52.1 %)	3189 (49.9 %)	965 (60.7 %)
Ethnicity
Fars	3874 (48.6 %)	3721 (58.3 %)	152 (9.6 %)
Lor Bakhtiari	3122 (39.1 %)	1775 (27.8 %)	1347 (84.7 %)
Turk Qashqai	649 (8.1 %)	619 (9.7 %)	30 (1.9 %)
Other	333 (4.2 %)	272 (4.3 %)	61 (3.8 %)
number of family members - Mean ± SD	4.00 ± 1.29	3.89 ± 1.14	4.45 ± 1.69
Number of family members– n (%)
1	84 (1.1 %)	59 (0.9 %)	25 (1.6 %)
2	782 (10 %)	617 (9.9 %)	165 (10.5 %)
3	1745 (22.3 %)	1477 (23.6 %)	267 (17 %)
4 or more	5205 (66.6 %)	4096 (65.5 %)	1109 (70.8 %)
Marital status
Single	137 (1.7 %)	112 (1.8 %)	25 (1.6 %)
Married	7520 (94.3%)	6074 (95.1 %)	1445 (90.9 %)
Widow and divorced	321 (4 %)	201 (3.1 %)	120 (7.5 %)
Education (N Years) - Mean ± SD	8.95 ±6.01	10.16 ±5.69	4.13 ±2.08
Illiterate	1142 (14.3 %)	593 (9.3 %)	549 (34.5 %)
<= 5 years	1689 (21.2 %)	1120 (17.5 %)	569 (35.8 %)
6‐8 years	891 (11.2 %)	702 (11 %)	189 (11.9 %)
9‐12 years	2059 (25.8 %)	1855 (29 %)	203 (12.8 %)
>12 years	2197 (27.5 %)	2117 (33.1 %)	80 (5 %)
Occupational status
Employee	1450 (18.2)	1389 (21.7 %)	60 (3.8 %)
Farmer/ Rancher / herder	293 (3.7)	122 (1.9 %)	171 (10.8 %)
Carpet weaver/ Tailor/ weaver	311 (3.9)	239 (3.7 %)	72 (4.5 %)
Heavy car driver/ Mechanic and oil change worker	507 (6.4 %)	448 (7 %)	59 (3.7 %)
building contractor/ Worker and builder	470 (5.9 %)	311 (4.9 %)	159 (10 %)
Housewife / unemployed / retired	4120 (51.6 %)	3142 (49.2 %)	978 (61.5 %)
Others	827 (10.4 %)	736 (11.5 %)	91 (5.7 %)

Table 3-Baseline behavioral and clinical characteristics of the sub cohort

Characteristics	Total N = 7978	Men N=3824	Women N=4154	Urban N = 6388	Rural N = 1590
Weight status	74.16 ± 13.27	78.15 ± 13.26	70.52 ± 12.20	75.49 ± 12.95	68.89 ± 13.27
Body mass index (BMI)- Mean (SD)	27.70 ± 4.58	26.62 ± 4.02	28.68 ± 4.83	27.87 ± 4.47	27.00 ± 4.93
Underweight (BMI<20) – n (%)	259 (3.3 %)	165 (4.4 %)	94 (2.3 %)	163 (2.6 %)	96 (6 %)
Healthy (20-25) – n (%)	1934 (24.4 %)	1100 (29.1 %)	834 (20.2 %)	1447 (22.9 %)	487 (30.7 %)
Overweight (25-30) – n (%)	3550 (44.9 %)	1813 (48 %)	1737 (42 %)	2948 (46.6 %)	601 (37.9 %)
Obesity (>30) – n (%)	2171 (27.4 %)	699 (18.5 %)	1472 (35.6 %)	1768 (27.9 %)	403 (25.4 %)
Smoking status
Current smoker n (%) yes	1288 (16.1 %)	1272 (33.3 %)	16 (0.4 %)	1078 (16.9 %)	210 (13.2 %)
Former smoker n (%) yes	612 (7.7 %)	596 (15.6 %)	16 (0.4 %)	511 (8 %)	101 (6.4 %)
Never smoker n (%) yes	6078 (76.2 %)	1956 (51.2 %)	4122 (99.2 %)	4798 (75.1 %)	1279 (80.4 %)
Fuels used
Gas	5198 (65.2 %)	2519 (65.9 %)	2679 (64.5 %)	4777 (74.8 %)	421 (26.5 %)
Oil/gasoline	1801 (22.6 %)	868 (22.7 %)	933 (22.5 %)	1183 (18.5 %)	618 (38.9 %)
Wood/firewood/ Animal dung	979 (12.3 %)	437 (11.4 %)	542 (13 %)	427 (6.7 %)	551 (34.7 %)
Cooking area (Kitchen Type)
closed kitchen inside the house	1905 (23.9 %)	826 (21.6 %)	1079 (26 %)	1371 (21.5 %)	534 (33.6 %)
open kitchen inside the house	5979 (74.9 %)	2951 (77.2 %)	3028 (72.9 %)	4951 (77.5 %)	1028 (64.7 %)
outside of the house	94 (1.2 %)	47 (1.2 %)	47 (1.1 %)	66 (1 %)	28 (1.8 %)
Kitchen ventilation status
Ventilated	4422 (55.4 %)	2277 (59.5 %)	2145 (51.6 %)	3899 (61 %)	522 (32.8 %)
Not ventilated	3556 (44.6 %)	1547 (40.5 %)	2009 (48.4 %)	2488 (39 %)	1068 (67.2 %)
Comorbidities diseases status
Cardiovascular disease	523 (6.6 %)	306 (8 %)	2.7 (5.2 %)	429 (6.7 %)	94 (5.9 %)
Chronic lung diseases (asthma, tuberculosis, emphysema and bronchitis)	346 (4.3 %)	155 (4.1 %)	191 (4.6 %)	302 (4.7 %)	44 (2.8 %)
Hypertension	2125 (27.1 %)	1032 (27.6 %)	1093 (26.7 %)	1753 (28 %)	372 (23.6 %)
Diabetes mellitus	955 (12 %)	424 (11.5 %)	531 (13.1 %)	815 (13.2 %)	140 (9.2 %)
Dyslipidemia	5610 (71.9 %)	2579 (69.3 %)	3031 (74.4 %)	4451 (70.9 %)	1159 (76 %)
Metabolic syndrome	2006 (25.2 %)	1660 (30.5 %)	846 (20.4 %)	1798 (28.3 %)	208 (13.1 %)
Anxiety and Depression	1346 (16.9 %)	353 (9.2 %)	993 (23.9 %)	1147 (18 %)	199 (12.5 %)
Musculoskeletal Disorders	3929 (56.5 %)	1562 (47.4 %)	2367 (64.7 %)	3316 (59.7 %)	613 (43.8 %)
Rheumatoid Arthritis	385 (4.8 %)	115 (3 %)	270 (6.5 %)	318 (5 %)	67 (4.2 %)
Osteoporosis	733 (9.2 %)	59 (1.5 %)	674 (16.2 %)	615 (9.6 %)	118 (7.4 %)
Fatty liver	1280 (16 %)	489 (12.8 %)	791 (19 %)	1134 (17.8 %)	146 (9.2 %)
Comorbidities – n (%)
None	1211 (15.2 %)	676 (17.7 %)	535 (12.9 %)	972 (15.2 %)	239 (15 %)
1	2529 (31.7 %)	1265 (33.1 %)	1264 (30.4 %)	1848 (28.9 %)	681 (42.8 %)
2	1848 (23.2 %)	849 (22.2 %)	999 (24 %)	1515 (23.7 %)	333 (20.9 %)
3 or more	2390 (30 %)	1034 (27 %)	1356 (32.6 %)	2053 (32.1 %)	337 (21.2 %)

Table 4- Baseline airway obstruction for sub cohort COPD in SCS, then split by patient sex group

	ALL N=7978	Men N=3824	Women N=4154	P Value	Urban N=6388	Rural N=1590	P Value
Airway obstruction – LLN	673 (8.4 %)	345 (9 %)	328 (7.9 %)	0.039	558 (8.7 %)	115 (7.2 %)	0.029
Airways obstruction – FR	289 (3.6 %)	159 (4.2 %)	130 (3.1 %)	0.008	243 (3.8 %)	46 (2.9 %)	0.045
Chronic lung disease (asthma, tuberculosis, emphysema and bronchitis) – n (%) yes	346 (4.3 %)	155 (4.1 %)	191 (4.6 %)	0.127	302 (4.7 %)	44 (2.8 %)	<0.0001
Symptoms
Chronic cough – n (%) yes	1038 (13 %)	383 (10 %)	655 (15.8 %)	<0.0001	937 (14.7 %)	101 (6.4 %)	<0.0001
Chronic cough with phlegm – n (%) yes	494 (47.6 %)	201 (52.5 %)	293 (44.7 %)	0.009	444 (47.4 %)	50 (49.5 %)	0.382
Shortness of breath and Wheezing – n (%) yes	217 (2. 7 %)	75 (2 %)	142 (3.4 %)	<0.0001	188 (2.9 %)	29 (1.8 %)	0.007
FEV1 (L.)- Mean ± SD	2.84 ± 0.79	2.93 ± 0.81	2.76 ± 0.76	<0.0001	2.92 ± 0.78	2.55 ± 0.74	<0.0001
FEV6 (L.)- Mean ± SD	2.08 ± 0.86	3.17 ± 0.87	2.99 ± 0.084	<0.0001	3.16 ± 0.85	2.74± 0.80	<0.0001
FVC (L)- Mean ± SD	3.08 ± 0.86	3.18 ± 0.88	3.00 ± 0.84	<0.0001	3.17 ± 0.85	2.74 ± 0.80	<0.0001
FEV1/FVC- Mean ± SD	92.48 ± 7.47	92.43 ± 7.63	92.52 ± 7.32	0.601	92.27 ± 7.45	93.33 ± 7.50	<0.0001
FEV1/FEV6- Mean ± SD	92.39 ± 7.48	92.60 ± 7.45	92.62 ± 7.32	0.678	92.42 ± 7.36	93.38 ± 7.41	<0.0001
PEF (L)- Mean ± SD	5.07 ± 2.09	5.28 ± 2.19	4.88 ± 1.96	<0.0001	5.24 ± 2.12	4.37 ± 1.79	<0.0001
FEF 25-75 (L)- Mean ± SD	3.63 ± 1.28	3.75 ± 1.33	3.52 ± 1.23	<0.0001	3.72 ± 1.29	3.25 ± 1.16	<0.0001
FEF 25 (L)- Mean ± SD	4.82 ± 1.97	5.01 ± 2.06	4.64 ± 1.86	<0.0001	4.98 ± 2.00	4.16 ± 1.71	<0.0001
FEF 50 (L)- Mean ± SD	3.89 ± 1.43	4.02 ± 1.48	3.78 ± 1.37	<0.0001	4.01 ± 1.44	3.44 ± 1.28	<0.0001
FEF 75 (L)- Mean ± SD	2.29 ± 0.84	2.36 ± 0.87	2.23 ± 0.80	<0.0001	2.33 ± 0.85	2.14 ± 0.78	<0.0001
MVV (L/Min)- Mean ± SD	99.67 ± 27.7	102.54 ± 28.3	97.02 ± 26.96	<0.0001	102.27 ± 27.55	89.37 ± 26.21	<0.0001

LLN, Low limit normal; FR, Fixed Ratio; FEV1, forced expiratory volume in 1 second; FEV6, forced expiratory volume in 6 second; FVC, forced vital capacity; PEF, peak expiratory flow; FEF 25-75, Forced expiratory flow in 25%, 50% and 75% of FVC; MVV, Maximum Ventilatory Volume.

Profile publication is one of the most important outcomes after the completion of enrollment in cohort studies. This is useful for researchers, helps develop research fields, and is helpful for health care system planners.

COPD is a preventable and curable disease [28]. Prevention of this disease should be taken into account as with other non-communicable chronic diseases, such as cardiovascular disease and cancer. Epidemiological studies are necessary to create an appropriate framework for fighting COPD. This framework requires a better description of men and women at risk of developing COPD and a description of people with early stage illness. This framework should also provide a better understanding of the risk factors that can be changed through interventions[29]. Sub cohort COPD is the first longitudinal prospective study for COPD with population sampling in Iran. This study seeks to provide a broad description of the characteristics of men and women with COPD and to identify other causes of airway obstruction that can lead to an outcome. This study provides a unique opportunity to advance and consult observations on the people with mild and unknown illnesses. The inclusion of healthy people and patients in the study provided a new opportunity to describe and follow a subgroup of the COPD patients who had not already been diagnosed, while many of them may at risk or have mild COPD that had not previously been diagnosed by a doctor or other health care professionals [30]. Most national estimates of COPD prevalence rates have been usually based on the data derived from the patients’ self-report questionnaires, and without an objective measurement of pulmonary function using a spirometer [10]. This study provides a good opportunity to assessment the incidence of COPD by mean of both GOLD and LLN criteria from spirometry data, so that its results can be compared with multivariate models of people who have not previously been diagnosed with COPD and who have COPD on the basis of known risk factors; in fact, this study examined the problems due to lack of COPD diagnosis and the need for intervention, and provides an opportunity to address the question Will undiagnosed COPD be clinically important? COPD is associated with a high incidence rate of one or more diseases. Comorbidities such as cardiovascular disease, musculoskeletal disorders, and metabolic syndrome are common in patients with COPD and significantly affect the quality of life of the patients, prognosis, and survival [31-34]. Increasing knowledge about the prevalence and effects of comorbidities in COPD is essential to adopt better intervention strategies and revise primary health care guidelines. COPD prognostic indicators currently focus primarily on prediction of mortality risk; creating a large COPD cohort for primary care and evaluating a wide range of outcomes enable us to review existing prognostic indicators and, if necessary, to develop new and appropriate prognostic indicators to predict other outcomes such as exacerbation and recurrence of disease, hospital admissions, and hospitalization due to exacerbation of respiratory diseases in primary care to be used in primary health care [30]. This study is a valuable work with respect to increasing the longitudinal information and identifying the prognostic factors for COPD and the contribution of each of these factors to the progression and development of the disease due to its similarity to other cohort studies conducted around the world in terms of methodology, data collection methods and many other distinctive features [29]. Sub cohort COPD is a good platform for standard research with access to a database (such as lifestyle information, records and occupational exposures, smoking status and exposure to cigarette smoke and exposure time, fuel status, medical records, illnesses, and outcomes). Reported by patients, housing status and lung function test information, etc.). Using linear regression models with FEV1 as a dependent variable, we can estimate the progression of COPD over time. The data of this cohort study provide an appropriate infrastructure for the development of mathematical and statistical models to predict COPD and the survival rate of patients, and also the grounds for the analysis of the effects of various exposures, smoking and age using regression models and mortality rate from COPD as a dependent variable. There is a need for research to identify the impact of occupational exposure in COPD, especially among non-smokers by large, prospective and longitudinal studies. Therefore, in addition to the impact of occupational exposure, the potential interaction between occupational exposure and smoking was also addressed in this study. This study also provides a basis for answering an important and challenging research question about disease improvement and management, as well as interdisciplinary collaboration ranging from epidemiology to basic clinical research.

We expect results from this and future research to help improve the health status and determine specific biological pathways or treatments for health care services planning and management decisions. Ultimately, this information will help policy-makers and public health decision makers develop policies to improve the diagnosis, management and control of COPD.

Ethics approval and consent to participate: This study was conducted with observance of the Declaration of Helsinki and the National Ethical Guidelines in Biomedical Research in Iran. As well, the study protocol was approved by the Ethics Committee of the SKUMS (IR.SKUMS.REC 1394.286 and IR. SKUMS.1396.110) at regional and national scales. All participants provided signed and fingerprinted informed written consent according to the Guidelines enforced by the Ethics Committee of the SKUMS. The participants can withdraw from the study whenever they wish. Data are stored in a codified confidential database.

Consent for publication: Not applicable.

Availability of data and material: The study that is ongoing. The general information is available from: http://cohort.skums.ac.ir. All researchers across Iran and the world can have free access to the findings of this study, and necessary processes are available at the Cohort website to reproduce the research project, participate in collaborative research projects, and use the data. After requested, under conditions of collaboration and endowment, Access to the data is available for interest researchers from corresponding author in AA ([email protected]).

Competing interests: The authors declare that they have no competing interests.

Funding: The SCS was funded by Iran's Ministry of Health and Medical Education (number 700/120), to develop cohort studies across Iran, and financially and nonfinancially supported by the SKUMS (number 2763 and 3366).

Acknowledgements: We hereby gratefully thank all people especially the participants, the field team, the staff of the Research and Technology Deputy of the SKUMS, the Research Councils of the Faculty of Public Health, Modeling in Health Research Center, Shahrekord and Ardal health centers of the SKUMS, the Treatment, Health, and Resource and Management Deputies of the SKUMS. In addition, we thank the central quality control team of the PERSIAN Cohort for providing the Central Protocol and the checklists of making arrangements and training the interviewers and monitoring their performance as well as assisting in implementing the pre-pilot phase especially Sareh Eghtesad, Farzin Rouzafazai, Ameneh Shayan-Raad, Zahra Mahmoudi, Romina Mohammadi, Esmaeil omidi, Reza Gojani, Kamal Solati, Arsalan Khaledifar, Morteza Hashemzadeh, Mahdi Sheikh, Hossein Poustchi and Reza Malekzadeh.

Author Contribution

A.A. in study design and principal investigator, F.Z.K. and A.A. participated in data gathering. F.Z.K., A.A., A.S.B., and H.R. wrote the first draft, and the statistical analysis was conducted by F.Z.K. and A.A. A.S.B. and H.R. contributed to the spirometry data collection and interpreting the results. All authors contributed to the data collection, interpreting the results and commenting on the initial manuscripts. all authors reviewed the manuscript.

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No competing interests reported.

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Iranian Sub Cohort Chronic Obstructive Pulmonary Disease (IrSCCOPD): Need for Longitudinal Observational Studies COPD in Southwest of Iran

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