The prevalence, burden and risk factors associated with chronic obstructive pulmonary disease in Commonwealth of Independent States (Ukraine, Kazakhstan and Azerbaijan): results of the CORE study

The CORE study is a multi-national, cross-sectional population-based epidemiological study conducted across major cities in Ukraine, Kazakhstan and Azerbaijan (Kiev, Almaty and Baku, respectively) from the first half of 2013 until the end of 2015. The study enrolled subjects who were ≥18 years old, had lived in the selected city for ≥10 years and provided written informed consent to participate in the study.

Subjects for whom spirometry could not be performed, and subjects who were not able to answer the study questionnaires (American Thoracic Society (ATS) Respiratory Symptoms Questionnaire, COPD Assessment Test (CAT™), Alcohol Intake, Tobacco Smoking Questions) or had any contraindication for spirometry or hypersensitivity to bronchodilator (Salbutamol) were excluded from the study. Contraindications for spirometry were established based on the judgment of the investigator and defined according to Cooper BG, 2011 [10] including absolute (myocardial infarction, ascending aortic aneurysm, pulmonary embolism, angina) or relative (thoracic/abdominal surgery; brain, eye, ear, nose or throat surgery; pneumothorax, haemoptysis, acute diarrhea, severe hypertension, confused/demented patients; patient discomfort, or infection control issue) contraindications.

Diagnosis of COPD was established based on the study questionnaire and/or spirometry conducted without bronchodilator (pre-dose) and with bronchodilator (post-dose: 15–20 min after administration of 200–400 mcg Salbutamol (GlaxoSmithKline). Consequently, FEV₁ (forced expiratory volume in one second) and FVC (forced vital capacity) were estimated during the spirometry using a standardized approach defined by Miller MR et al., 2005 [11]. Spirometry quality and results were regularly reviewed by members of the Study Executive Committee.

COPD was identified through three definitions:

If YES, please, indicate number of exacerbations during the last year.

As shown in Table 2, severity of COPD was investigated based on the GOLD guidelines (2011) [5] while using four categories for severity based on spirometry results only.

The data were collected from participants during household visits. Two-step cluster randomization (first step, administrative district; second step, street) was used for the sampling strategy. Districts and streets for household visits were selected by the Study Executive Committee. The interviewers visited households sequentially, starting with the first apartment of the first house in the selected street, and continuing in ascending order. At every household the interviewers assessed the eligibility of all inhabitants. Participants who provided their consent and were eligible to participate in the study provided their socio-demographic information and medical history, underwent weight/height measurement and spirometry with bronchodilator and completed the study questionnaires, as described previously [9].

Socio-demographic data were collected to describe the characteristics of the overall study population, including gender, age and ethnicity distribution, body mass index (BMI), smoking status and alcohol intake. COPD prevalence data were collected using the case definition described above and the impact of age, gender and severity were assessed. Additionally, the type and frequency of co-morbidities and any potential association between COPD and its related risk factors (i.e. smoking, BMI, alcohol intake, tuberculosis, dusty work, open fire cooking) were investigated.

The COPD Assessment Test (CAT™) and the modified Medical Research Council (mMRC) Dyspnoea Scale were used to assess additional characteristics of COPD in this study. All respondents answered the CAT™ and were assessed by the mMRC Dyspnoea Scale at the interview. The CAT™ is a validated short questionnaire for measurement of the impact of COPD on a patient’s health status [12]. It comprises eight items, each with a scoring range of 0–5. The total CAT™ score is derived based on the sum of responses given to the eight items with a range of 0–40. The mMRC Dyspnoea Scale was used as a simple grading system to assess the level of dyspnoea/shortness of breath in five categories from 0 to 4: 0 - Responder is not affected by shortness of breath, except when engaging in strenuous exercise; 1 - Responder has shortness of breath when walking briskly on flat ground or slightly uphill; 2 - Responder walks more slowly on flat surfaces than other people his/her age because of shortness of breath, or he/she has to stop to catch his/her breath when walking at his/her own pace on flat ground; 3 - Responder has to stop to catch his/her breath after walking around 100 m or after walking for a few minutes on flat ground; 4 - Responder’s shortness of breath prevents him/her from leaving home or he/she has shortness of breath when dressing or undressing.

The point prevalence of COPD, (overall and separate stages/categories), is defined as the number of COPD individuals divided by total number of subjects included in the study, and is expressed as a number per 1000 for each country. Prevalence was calculated in the subject population with valid data. 95% confidence intervals (CI) were calculated for each frequency using the Clopper-Pearson method [13]. Odds ratios (OR) and 95% CI were calculated to estimate the statistical significance (p˂0.05) of associations between risk factors and COPD. Statistical analysis was performed using IBM SPSS Statistics software (IBM Corp., USA) version 21.0 and R software version 3.1.2 (R Core Team, Austria).

A total of 2842 adult subjects were included in the CORE study (964 in Ukraine, 945 in Kazakhstan and 933 in Azerbaijan). The majority of study population were women across the three countries: 58.2% in Ukraine; 63.2% in Kazakhstan and 58.3% in Azerbaijan. The mean age was slightly above 40 years old in all participating countries. As expected, the majority of participants were Caucasian in Ukraine (99.7%) and Azerbaijan (100%), and almost two-thirds of participants in Kazakhstan were Asian (62.8%). The mean BMI was at the boundary of overweight in Ukraine, (25.0 (5.1) kg/m²), and in Kazakhstan, (25.7 (5.1) kg/m²), while it was slightly higher in Azerbaijan (26.4 (5.3) kg/m²). Approximately one-third of participants were either current or past smokers (33.7% in Ukraine, 40.2% in Kazakhstan, 26.0% in Azerbaijan). Heavy alcohol consumption was reported by 53.4% of respondents in Ukraine, 44.8% in Kazakhstan and 22.7% in Azerbaijan. See Table 3.

Subjects who fulfilled the definitions used in this study for COPD are shown in Table 4. Prevalence of previously diagnosed COPD was 10.4 (95% CI 5.0–19.1) per 1000 in Ukraine, 13.8 (95% CI 7.3–23.4) per 1000 in Kazakhstan, and 4.3 (95% CI 1.2–11.0) per 1000 in Azerbaijan. The estimated prevalence of COPD diagnosed by spirometry was higher among all participating countries compared to previously diagnosed COPD estimates: 31.9 (95% CI 21.7–45.3) per 1000 in Ukraine, 66.7 (95% CI 51.6–84.5) per 1000 in Kazakhstan, and 37.5 (95% CI 26.3–51.8) per 1000 in Azerbaijan. Almost all participating subjects were firstly diagnosed for COPD by spirometry. See Fig. 1.

A similar picture was obtained for the prevalence of COPD among respondents ≥40 years old (Fig. 2). The estimated prevalence of COPD diagnosed by spirometry was: 47.3 (95% CI 29.9–70.8) per 1000 in Ukraine, 114.1 (95% CI 87.3–145.6) per 1000 in Kazakhstan, and 60.1 (95% CI 40.3–85.7) per 1000 in Azerbaijan; compared to the prevalence of previously diagnosed COPD which was 14.7 (95% CI 5.9–30.1) per 1000 in Ukraine, 26.5 (95% CI 14.2–44.9) per 1000 in Kazakhstan, and 8.6 (95% CI 2.3–21.9) per 1000 in Azerbaijan.

GOLD stage classification (2011) [5] was used for COPD severity (airflow limitation) estimation. COPD patients identified in this study were distributed between stages I (FEV₁/FVC <  0.70, FEV₁ ≥ 80% normal) and II (FEV₁/FVC <  0.70, FEV₁ 50–79% normal). In all three participating countries, more patients were found in stage II (18.1 (95% CI 10.6–28.8) per 1000 in Ukraine; 48.7 (95% CI 35.9–64.4) per 1000 in Kazakhstan and 21.4 (95% CI 13.1–32.9) per 1000 in Azerbaijan) (Fig. 3).

A higher prevalence of previously diagnosed COPD was observed in the age group ≥65 years old compared to the younger age groups in Kazakhstan and Azerbaijan: 73.5 (95% CI 24.3–163.3) and 38.5 (95% CI 4.7–132.1) per 1000 respectively. However, in Ukraine, the highest prevalence was observed in the 40–64 years old age group: 14.8 (95% CI 5.4–31.9) per 1000 (Fig. 4). A higher prevalence of COPD diagnosed by spirometry was observed in the population aged ≥65 years old compared to younger age groups in Ukraine, Kazakhstan and Azerbaijan: 153.8 (95% CI 76.3–264.8), 264.7 (95% CI 165.0–385.7) and 192.3 (95% CI 96.3–325.4) per 1000 respectively.

In all three participating countries, COPD was more common in men. This applied to both previously diagnosed COPD and COPD confirmed based on spirometry. The prevalence of previously diagnosed COPD was 14.9 (95% CI 5.5–32.2) per 1000 in men vs 7.2 (95% CI 2.0–18.3) per 1000 in women in Ukraine; 17.2 (95% CI 6.4–37.2) per 1000 in men vs 11.7 (95% CI 4.7–24.0) per 1000 in women in Kazakhstan and 10.3 (95% CI 2.8–26.1) per 1000 in men vs 0.0 (95% CI 0.0–6.8) in women in Azerbaijan. The prevalence of COPD diagnosed by spirometry was 45.6 (95% CI 27.2–71.1) per 1000 in men vs 22.1 (95% CI 11.4–38.2) per 1000 in women in Ukraine; 120.7 (95% CI 88.4–159.6) per 1000 in men vs 35.2 (95% CI 21.9–53.3) per 1000 in women in Kazakhstan and 54.0 (95% CI 33.7–81.3) per 1000 in men vs 25.7 (95% CI 14.1–42.8) per 1000 in women in Azerbaijan (Figs. 5 and 6).

The ethnicity-specific prevalence of COPD was estimated only in Kazakhstan, because most Ukrainians and Azerbaijanians were Caucasians. Generally, in Kazakhstan, the prevalence of COPD in Caucasians was slightly higher than in Asians, both for previously diagnosed COPD (17.2 (95% CI 6.3–37.1) per 1000 in Caucasians vs 11.8 (95% CI 4.8–24.2) per 1000 in Asians), and for COPD diagnosed by spirometry (68.8 (95% CI 44.6–100.6) per 1000 in Caucasians vs 64.1 (95% CI 45.7–86.9) per 1000 in Asians).

The relationship between the presence of COPD and smoking status (current/past smoker), alcohol intake (severe alcohol intake), BMI (BMI ≥ 25 kg/m²), tuberculosis (ever diagnosed), dusty work, and open fire cooking was investigated and statistical significance was found between COPD and smoking in Kazakhstan (OR 3.756 (CI 2.156–6.543) p < 0.001) and Azerbaijan (OR 2.808 (CI 1.423–5.542) p = 0.002). Tuberculosis was a significant risk factor associated with COPD in Ukraine (OR 32.393 (CI 4.403–238.330) p < 0.001). Dusty work might increase the appearance of COPD in Kazakhstan (OR 2.306 (CI 1.328–4.002) p = 0.002)

The CAT™ and mMRC dyspnoea scale were assessed in respondents with COPD diagnosed by spirometry (COPD population) and those without COPD (non-COPD population). As seen in Table 5, the total CAT™ score and intensity of dyspnoea/shortness of breath by mMRC were significantly higher among respondents with COPD than in the non-COPD population in all countries. In all non-COPD respondents and COPD respondents in Kazakhstan, the median CAT™ score did not exceed 5 points, which corresponds to the upper limit of normal in healthy non-smokers, and in the COPD population of Ukraine and Azerbaijan the median CAT™ score corresponds to a low (< 10) impact of COPD on health status [12]. According to the mMRC dyspnoea scale, 70–80% respondents without COPD and only half of COPD respondents had no dyspnoea (grade 0).

While completing the study questionnaire the respondents were asked to report the presence of other chronic medical conditions except for respiratory diseases. Co-morbidities were reported by 44.2% of respondents in Ukraine, 23.5% respondents in Kazakhstan and 54.6% respondents in Azerbaijan. The respondents with COPD diagnosed by spirometry (COPD population) were compared to the rest of the respondents (non-COPD population) by the rate of co-morbidities. In all participating countries, the number of subjects that reported suffering from a chronic health condition was higher in the COPD population compared to the non-COPD population: 57% vs 43% in Ukraine, 51% vs 27% in Kazakhstan, and 74% vs 54% in Azerbaijan, respectively (Table 6).

A history of pneumonia was significantly more frequent in the COPD population than in the non-COPD population in all investigated countries (36.7% vs 19.4%, p = 0.024 in Ukraine, 31.7% vs 14.9%, p = 0.001 in Kazakhstan and 17.1% vs 5.9%, p = 0.019 in Azerbaijan). The same results were obtained for a previous cardiovascular disease (26.7% vs 6.0%, p < 0.001 in Ukraine, 22.2% vs 7.8%, p = 0.001 in Kazakhstan and 22.9% vs 3.5%, p˂0.001 in Azerbaijan in COPD and non-COPD populations respectively). Additionally, hypertension occurred significantly more often in the COPD population compared to the non-COPD population in Ukraine (40.0% vs 14.0%, p = 0.001) and Azerbaijan (34.3% vs 16.8%, p = 0.012). In Kazakhstan, hypertension was also more frequently observed in the COPD population (36.5%) compared to the non-COPD population (25.5%) but the difference was not shown to be significant (p = 0.074) (Table 6).

In all three participating countries, no serious adverse events (related to participation in the study) were recorded during the study period. Non-serious adverse events were not collected, as there was no investigational drug administration in this study.

The prevalence of previously diagnosed COPD shown in the present study is low compared to estimates provided by previous studies (42 in Brazil [25], 57 in Greece [15], 88 in The Netherlands [23] and 222 in Russia [26] per 1000). Sweden was the only country where the reported prevalence was comparable to the present study (18 per 1000) [21]. This can possibly be explained by peculiarities of the healthcare systems. In the CIS countries, a big issue is the lack of COPD knowledge and the attitude to this disease within the population (people do not take a “simple” cough or dyspnea seriously and therefore do not visit a doctor). Another major problem may be related to low access to primary care services; in all the countries that took part in this study primary care is underfinanced and underdeveloped. Under-reporting of COPD may reflect the lack of COPD knowledge not only among patients, but also among healthcare workers, especially general practitioners and internists, who are the primary contact between the healthcare system and the population. For example, in Kazakhstan as early as 10–15 years ago, COPD was considered an “exotic” disease; a COPD diagnosis would be given in specialized institutions, not by primary care physicians. Nowadays COPD is much more well known. However, some public health problems may still exist; for example, patients receive medications for COPD treatment free of cost which may force health authorities to regulate the number of COPD patients registered in primary and specialty care. The forth reason for COPD under-reporting may be related to low availability of spirometry and its low quality in primary care hospitals. From a public health perspective, another important issue is that all respiratory diseases are collected in one statistical pool; there is no separate registration of COPD, asthma, allergic rhinitis and other non-infectious respiratory diseases in the CIS countries.

The COPD prevalence estimates based on spirometry reported in this study were similar to the data published in previous studies (45 in Spain [16], 42 in USA [19] and 37 in United Arab Emirates [22] per 1000). Some other studies reported higher estimates (240 (The Netherlands) [23], 218 (Russia) [26], 197 (Uruguay) [20], 184 (Greece) [15], 162 (Uganda) [27], 162 (Sweden) [21], 142 (Portugal) [28], 134 (Korea) [17], 78 (Mexico) [20] and 71 (Vietnam) [18] per 1000). The variability in prevalence estimates could reflect true differences or be due to the different methodologies used in different studies. Study design aspects such as differences in the rigor of case ascertainment (for example, different diagnostic criteria) or the over-representation of a high-risk sub-population in the study (such as another age range of participants or percentage of smokers) or even differences in healthcare systems (the availability of medical care) could have led to variations in estimates. However, different nations or regions may have a truly increased or decreased burden of the disease as a result of true biological phenomena. It should be noted that in the Russian study (GARD) spirometry was performed only for participants with suspected COPD, so the prevalence may be overstated; in addition, a significantly higher prevalence of previously diagnosed COPD in the Russian study is probably due to different diagnostic criteria. One study estimated the prevalence of COPD firstly diagnosed by spirometry [15]. In line with our study, most cases of COPD diagnosed by spirometry were firstly diagnosed, and prevalence of firstly diagnosed COPD was higher than for the previously diagnosed COPD confirming the observation that COPD is often under-reported.

The majority of respondents with COPD diagnosed by spirometry in this study had mild/moderate COPD; there were no respondents with GOLD stages III or IV. The median CAT™ score did not exceed 10 points, which corresponds to a low impact of COPD on health status. Almost half of respondents with COPD did not have dyspnoea/shortness of breath by mMRC scale. At the same time, clear statistically significant differences for CAT™ and mMRC scale were obtained between COPD and non-COPD respondents that additionally confirm the validity of these instruments for evaluation of COPD in research studies and routine use.

As for co-morbid conditions, in Ukraine the participants more often reported unburdened anamnesis, than in Kazakhstan and especially in Azerbaijan. A high rate of arterial hypertension was observed, followed by other cardiovascular diseases, diabetes mellitus and blood lipid abnormalities. In other studies, cardiovascular diseases were also the most common co-morbidities [29] and were recorded more frequently than in this study.

As expected, the most significant correlation was found between COPD and cardiovascular diseases. The rate of hypertension was also higher among respondents with COPD compared to the non-COPD population (although this difference was only statistically significant in Ukraine and Azerbaijan). It is well established, that COPD is a precursor to cardiovascular disease development and/or its aggravation [30, 31]. The association between a history of pneumonia and COPD confirms available data. Pneumonia and COPD can aggravate each other. One study indicated that previous exacerbations of pneumonia are significantly associated with a higher rate of COPD exacerbation [32]. Another study confirmed that COPD increases mortality in patients with pneumonia [33].

This study has several strengths. It is a multi-national, cross-sectional, population-based study with a large sample size using consistent methodology across all countries, providing a standardized measure of prevalence in the CIS countries. In addition, the case definition of COPD used is based on both (i) self-reported diagnosis and (ii) diagnosis confirmed by spirometry. Furthermore, severity of COPD has been assessed based on the validated international GOLD guidelines. As it is the first time such an epidemiological study has been conducted in CIS countries, this study could facilitate increased recognition of COPD in CIS countries and allow preparation of educational interventions to optimize management of patients with COPD. Whereas many previously published studies on COPD concern patients only over 40 years of age, this study evaluates COPD prevalence in the overall adult population.

We acknowledge that the current study has several limitations. The method of district and street sampling may not ensure completely random selection of streets and participants. The relatively small number of COPD patients limits the analysis of risk factors associated with COPD and can limit the power for specific types of within-city analysis, such as detailed subgroup analyses. The subjectivity of the diagnostic criteria based on symptoms can lead to over or under diagnosis. Spirometry was the only objective diagnostic measure in the present study and its results were reviewed centrally, but difficulties encountered when conducting spirometry can affect the results of this procedure. Additionally, the physiological decrease in lung function in the elderly may influence the estimation of COPD prevalence stratified by age, taking into account that fixed ratio FEV₁/FVC was used as the diagnostic criteria for COPD in this study.

The city population may not be representative of each country in general, because risk factors and healthcare provision (including the availability of medical care) may vary widely across the country. In particular, the results may only reflect the situation in urban areas and not represent the whole country, since rural areas could have different levels of healthcare provision and accessibility to medical care and different living and working conditions for the people who live in these areas. Finally, some data are missing due to a lack of relevant information from participants, as a lot of study data were collected from respondents’ interview.