Prevalence and factors connected with chronic diseases in the elderly residents of Birjand: a community – based study in Birjand, South Khorasan Province, Iran

Abstract

Objectives

The rapid rise of non-communicable diseases (NCDs) across the elderly has attracted much attention in Iran due to the high rate of population aging in the country. The current survey intended to evaluate the prevalence of and factors associated with five NCDs in the elderly residents of Birjand, a metropolis of South Khorasan, Iran.

Methods

Following an observational design, 1820 elderly dwellers of Birjand aged ≥ 60 years residing in urban or rural areas were explored. Data on the target NCDS and socio-demographic features, health behavioral factors, and objective assessment of height and weight were collected using interviews.

Results

The prevalence of hypertension, diabetes mellitus, chronic obstructive pulmonary disease (COPD), stroke, and cancer was 55.2% (1004/1819), 25.5% (463/1819), 1.0% (18/1807), 4.4% (80/1810), and 1.8% (33/1816), respectively. There was no gender difference concerning the prevalence of COPD, whereas the prevalence of hypertension, diabetes mellitus, and cancer was higher in women than men. Stroke was conversely higher in males than females. The common correlations of the five main NCDs were locality of residence and low body mass index (BMI). Rural residents had higher odds of diabetes mellitus and hypertension and lower odds of stroke. Diabetes mellitus, hypertension, and stroke were associated with a low BMI. Gender, age, and occupation were found to be associated with some of the NCDs. Retired and housewives had more chance to have hypertension and diabetes mellitus than the unemployed elderly.

Conclusion

The findings demonstrated that hypertension, diabetes mellitus, and stroke are the three prevalent NCDs among elders in the area and warrant a specific focus on reducing the burden of diseases and aligning healthcare services to prepare the whole needs of this population.

Background

Elderly population growth is a global concern, as it has several consequences such as soared medical costs in elderly care. The portion of people aged ≥ 60 years is anticipated to double by 2050, compared to 2007, outreaching 2 billion elders worldwide [1]. As a middle-income country, Iran is likely to experience a crisis of elderly population, so that the elderly population is anticipated to increase by 21.7% by 2050 [2]. Such a speedy aging process may pose a major challenge in providing the financial and social support for taking care of elders in Iran. The aging population, along with a growth in life expectancy, may change the main mortality causes from infectious to long-term non-communicable conditions [3]. It has been reported that high blood pressure, dyslipidemia, arthritis, diabetes mellitus, cardiovascular disease (CVD), malignancy, and dementia are the main long-term diseases that burden old people in the most developed countries [3].

Regionally, in Iran, evidence confirms that chronic illnesses are the main health concern in the aged population. CVDs, cancers, chronic pulmonary diseases, and diabetes are major causes of death in Iran, accounting for 82.2% of all deaths [4]; however, in the literature review, the lack of a large-sized study on the outbreak of chronic diseases in old Iranian people was observed. According to the Global Burden of Disease study (2019) (GBD) [5], the main causes of death in old Iranian people were ischemic heart disease (IHD;29.9%) and stroke (18.1%). South Khorasan is the fifth oldest province of Iran. Despite the extreme effects of aging on health and economic, NCDs among the elderly population in the area remain understudied.

Understanding contributing components of chronic diseases is a key point in drafting strategies and interventions. Genetic elements may affect the lifetime of the Iranian elderly population as many have experienced healthy aging and others show age-related diseases in their last years of life [6]. More novel surveys have acknowledged that an unhealthy diet, body weight, and sedentary lifestyle can carry risks for long-term diseases [7, 8]. Further, other circumstances like smoking and alcohol consumption were also found out to be connected with NCDs in aged males [9]. Recognizing the demographic along with other adjustable risk factors that come up with NCDs discrepancy in old people is compulsory in outstretching interventions to diminish the outbreak of long-term illnesses.

The prevalence of NCDs and associated factors in the Birjand elderly population has not yet been determined. Hence, the current study aimed to firstly evaluate the prevalence and, secondly, correlates five chronic diseases, namely, diabetes mellitus, hypertension, stroke, chronic obstructive pulmonary disease (COPD), and cancer in the Birjand elderly population.

Methods

Study design and data gathering

This community-based cross-sectional study was carried out within the framework of the Birjand Community Health Assessment by referring to the first phase of the Birjand Longitudinal Aging Study (BLAS) [10]. The research was conducted in a one-year period from October 2018 to 2019 and involved a sample of 1820 elderly residents aged ≥ 60 years (863 men and 957 women). Participants were randomly selected from four regions in the city of Birjand using multi-stage cluster sampling. Subjects aged 60 years or older were included in the study. Among them, people who were not residents of Birjand (urban or rural areas) were excluded from the study. Initially, 73 postal codes from the four mentioned areas were randomly selected as captions. In the second step, 25 old men and women were assigned to each branch. In the third step, the whole permanent residents aged ≥ 60 years inhabiting in the selected sample areas were evaluated.

Data were collected through face-to-face interviews with the respondents. The self-reported of five chronic diseases queried in this study were hypertension, diabetes mellitus, COPD, stroke, and cancer. Then, patients' responses were verified through examination and review of their records by experts.

The questionnaire also contained items on socio-demographic attributes such as age (classified into 60–75 years, 75–85 years, and > 85 years), gender, occupation (unemployed, employed, retiree, self-employed, manual worker, and housewife), and residency (urban and rural). Health behavioral factors, i.e., smoking (never and current smoker), and objective assessment of height and weight, were also obtained.

The research purpose and methodology were subjected to scrutiny by the Ethics Committee of Birjand University of Medical Sciences (Ref: IR.BUMS.1399.292). In addition, written informed consent was obtained from all participants before entering the study and after a comprehensive introduction to the study protocol.

Measurements

Standing height was measured using a stadiometer, which is used for measuring human height, fixed to the wall and recorded to the nearest 0.1 cm. Bodyweight was measured to the nearest 0.1 kg using a digital electronic scale. Body Mass Index (BMI) was calculated as follows: BMI = kg/m2, where kg is a person's weight in kilograms and m2 is his/her height in meters squared. Along with self-report of being hypertensive or having diabetes mellitus, blood pressure was checked by experts for all participants in sitting position 2 times at 5-min intervals and Systolic BP ≥ 140 mmHg, diastolic ≥ 90 mmHg is considered high blood pressure according to the American Heart Association (AHA) Guidelines as mentioned in Birjand Longitudinal Aging Study Protocol (10). Fasting blood sugar, FBS ≥ 126 mg/dl, confirmed by a blood test, was considered diabetes mellitus, based on the American Diabetes Association (ADA) Guidelines as mentioned in Birjand Longitudinal Aging Study Protocol (10). COPD was considered in patients who had dyspnea, chronic cough, or sputum production, which was verified by spirometric evidence (FEV1/FVC < 0.70). Stroke determined based on patient's history and previous evidence of computed tomography (CT) of the brain. Cancer was verified through patients' laboratory and imaging records or previous evidence of biopsy. All measurements were performed at the clinic. Participants were invited to visit the clinic and were familiarized with staff through several journeys before the assessment. Afterward, they were asked to be fasted for 12 h the night before their last visit to the clinic.

Data analysis

Sample estimates of polled and measured chronic diseases (diabetes mellitus, hypertension, COPD, stroke, and cancer), stratified by behavioral factors and socio-demographic attributes, are reported, comprising values, their respective percentages of the whole study sample, and 95% confidence intervals (95% CIs). Binary logistic regression was used to determine the associations of reported chronic illnesses with the suspected risk factors. Odds ratios (ORs; for example, OR of hypertension: "hypertension: yes" vs." hypertension: no") and their respective 95% CIs were calculated. Data analysis was administered using SPSS version 22.

Results

The mean (mean ± SD) age of participants was 73.34 ± 7.80 years. The particular prevalence of hypertension, diabetes mellitus, COPD, stroke and cancer was 55.2% (1004/1819), 25.5% (463/1819), 1.0% (18/1807), 4.4% (80/1810) and 1.8% (33/1816), respectively (Table 1). Concerning demographic attributes, the prevalence of COPD did not vary between men and women, whereas the prevalence of hypertension, diabetes mellitus, and cancer were higher in women than men (hypertension 58.7% [female] vs. 51.3% [male]; diabetes mellitus 29.4% [female] vs. 21.1% [male]; cancer 2.4% [female] vs. 1.2% [male]) and stroke was conversely higher in males than females (4.9% [male] vs. 4.0% [female]). Participants aged 60–75 years had the lowest prevalence of the three chronic diseases (hypertension (50.9%), stroke (4.9%), and cancer (1.9%)), while those aged 85 years and older showed the highest prevalence of stroke (6.9%) and cancer (2.7%). Diabetes mellitus was inversely more prevalent in people aged 60–75 years (26.5%) than who were aged 85 years and older (13.6%). Prevalence of COPD slightly differed based on the age categorization (0.9% [60–75 years]; 1.2% [75–85 years]; 0.8% [> 85 years]). Elderly people living in urban areas had a considerably higher prevalence of hypertension, diabetes mellitus, and stroke than the rural ones (hypertension 59.6% [urban] vs. 39.8% [rural]; diabetes mellitus 28.5% [urban] vs. 14.7% [rural]; stroke 5.0% [urban] vs. 2.5% [rural]) but a non-significant prevalence of COPD and Cancer than their rural counterparts (COPD 1.1% [urban] vs. 0.5% [rural]; cancer 2.0% [urban] vs. 1.3% [rural]). Smokers had a non-significantly higher prevalence of diabetes mellitus, COPD and stroke than the non-smokers' participants (diabetes mellitus 26.2% [smokers] vs. 25.4% [non-smokers]; COPD 1.7% [smokers] vs. 1.0% [non-smokers]; stroke 5% [smokers] vs. 4.4% [non-smokers]) but a slightly lower prevalence of hypertension and cancer than non-smokers (hypertension 52.5% [smokers] vs. 55.4% [non-smokers]; cancer 0.8% [smokers] vs. 1.9% [non-smokers]). Participants with a BMI < 19 showed the highest prevalence of hypertension 58.9%, diabetes mellitus 29.8% and stroke 5.1%. The prevalence of COPD and cancer did not differ significantly based on the BMI changes. Finally, housewifely, retired and self- employed participants had the highest prevalence of hypertension (59.1%, 56.9% and 56.4%, respectively), higher than in employment, manual worker and unemployment, furthermore, elderly manual workers showed the lowest prevalence of diabetes mellitus (5.6%), hypertension (35.7%), stroke (2.8%) and cancer (0.7%) as compared to the other subgroups (Table 1).

Table 1.

Distribution of socio-demographic attributes and risk factors for five non-communicable diseases

variable	Hypertension (N = 1004)		Diabetes mellitus(N = 463)		COPD (N = 18)				Stroke(N = 80)		Cancer(N = 33)
	Sample N	Prevalence (95%CI)	Sample N	Prevalence (95%CI)	Sample N			Prevalence (95%CI)	Sample N	Prevalence (95%CI)	Sample N	Prevalence (95%CI)
Gender
Male	442	51.3(45.2–59.8)	182	21.1(16.5–28.9)	11		1.3(0.6–2.2)		42	4.9(3.3–6.2)	10	1.2(0.5–2.1)
Female	562	58.7(51.2–64.6)	281	29.4(21.3–36.5)	7		0.7(0.2–1.0)		38	4.0(2.7–5.2)	23	2.4(1.5–3.6)
Total	1004	55.5(48.7–60.1)	463	25.5(19.3–30.5)	18		1.0(0.5–1.1)		80	4.4(3.4–5.2)	33	1.8(1.2–2.5)
Age
60–75	644	50.9(42.6–57.6)	335	26.5(20.3–32.4)	10		0.9(0.4–1.6)		46	4.1(3.3–5.4)	19	1.9(1.4–2.9)
75–85	301	66.7(61.3–71.6)	114	25.3(19.6–30.9)	7		1.2(0.5–2.5)		25	4.4(2.9–6.5)	7	2.1(0.8–4.2)
> 85	59	57.3(51.3–62.5)	14	13.6(9.1–18.6)	1		0.8(0.2–4.3)		9	6.9(3.2–12.7)	2	2.7(0.3–3.9)
Residence
Urban	844	59.6(51.4–65.6)	404	28.5(21.6–33.6)	16	1.1(0.6–1.8)			70	5.0(3.7–5.9)	28	2.0(1.3–2.8)
Rural	160	39.8(32.6–46.6)	59	14.7(9.6–19.5)	2	0.5(0.1–1.8)			10	2.5(1.2–4.8)	5	1.3(0.4–2.9)
smoking
No	940	55.4(47.8–61.3)	430	25.4(19.6–31.6)	16		1.0(0.8–1.5)		74	4.4(3.3–5.2)	32	1.9(1.2–2.7)
Yes	64	52.5(47.3–59.1)	32	26.2(20.3–31.9)	2		1.7(0.2–3.8)		6	5.0(1.7–9.9)	1	0.8(0.2–4.4)
BMI
< 19	501	58.9(52.3–65.3)	254	29.8(22.3–34.5)	7	0.8(0.3–1.7)			43	5.1(3.5–6.4)	15	1.8(0.9–2.9)
19–21	335	57.4(50.9–64.1)	139	23.8(18.6–28.4)	8	1.4(0.5–2.6)			29	5.0(3.2–6.7)	12	2.1(1.0–3.5)
21–23	80	40.4(34.6–45.4)	25	12.6(8.6–19.2)	1	0.5(0.1–2.7)			3	1.5(0.7–4.3)	6	3.1(1.1–6.5)
> 23	87	48.3(41.2–55.3)	43	23.9(19.8–28.7)	2	1.1(0.1–3.9)			5	2.8(1.2–6.1)	0	0.0(0.0–2.0)
Occupation
Employed	4	44.4(38.7–54.6)	156	28.0(21.3–33.9)	9	1.6(0.6–5.0)			28	5.0(2.6–9.1)	14	2.5(1.4–4.2)
Retired	317	56.9(50.2–61.5)	3	33.3(28.6–40.0)	0	0.0(0.0–0.0)			0	0.0(0.0–0.0)	0	0.0(0.0–3.3)
Manual worker	51	35.7(29.8–43.6)	8	5.6(2.5–9.3)	0	0.0(0.0–0.0)			4	2.8(0.9–9.9)	1	0.7(0.1–3.8)
Self-employed	84	56.4(49.9–61.3)	29	19.5(13.8–26.1)	1	0.7(0.1–4.0)			8	5.3(1.8–10.8)	0	0.0(0.0–2.4)
House wife	505	59.1(52.3–65.3)	251	29.4(20.1–36.5)	6	0.7(0.1–4.1)			35	4.1(1.7–13.0)	17	2.0(1.2–3.2)
Unemployed	40	40.8(32.8–49.6)	13	13.3(8.9–20.1)	2	2.0(0.9–5.1)			4	4.1(1.9–12.4)	1	1.0(0.2–5.5)

According to the Binary logistic regression models, female gender was strongly associated with hypertension (OR _{female vs. male} = 1.35, 95%CI = 1.12–1.63) and diabetes mellitus (OR _{female vs. male} = 1.55, 95%CI = 1.26–1.92) (Table 2). Being 60–75 years old was highly associated with diabetes mellitus (OR_{60-75 years vs. 85 years diabetes mellitus} = 2.29, 95%CI = 1.29–4.08). There were associations of residence with diabetes mellitus, hypertension, and stroke; however, rural dwellers had higher odds of diabetes mellitus and hypertension and lower odds of stroke. The chance of stroke in rural residents was 50% lower than in urban residents.

Table2.

Binary logistic regression analysis of factors connected with five non-communicable diseases

Variable	Hypertension (N = 1004)		Diabetes mellitus(N = 463)		COPD (N = 18)		Stroke(N = 80)		Cancer(N = 33)
	OR	95%CI	OR	95%CI	OR	95%CI	OR	95%CI	OR	95%CI
Gender
Male	Reference		Reference		Reference		Reference		Reference
Female	1.35	1.12–1.63***	1.55	1.26–1.92***	0.57	0.22–1.48	0.81	0.51–1.26	2.10	0.99–4.45
Age
> 85	Reference		Reference		Reference		Reference		Reference
60–75	0.77	0.52–1.16	2.29	1.29–4.08***	1.13	0.14–8.88	0.57	0.28–1.21	0.70	0.16–3.08
75–85	1.50	0.97–2.32	2.15	1.18–3.93*	1.60	0.19–12.95	0.63	0.28–1.38	0.77	0.16–3.78
Residence
Urban	Reference		Reference		Reference		Reference		Reference
Rural	2.23	1.78–2.79***	2.32	1.72–3.13***	0.44	0.10–1.93	0.50	0.25–0.97*	1.58	0.61–4.13
smoking
No	Reference		Reference		Reference		Reference		Reference
Yes	0.89	0.61–1.28	1.04	0.69–1.59	1.75	0.40–7.70	1.14	0.48–2.67	0.43	0.06–3.16
BMI
< 19	Reference		Reference		Reference		Reference		Reference
19–21	0.94	0.76–1.16	0.74	0.58–0.93*	1.68	0.61–4.65	0.98	0.60–1.59	1.17	0.54–2.52
21–23	0.47	0.35–0.64***	0.34	0.22–0.53***	0.62	0.07–5.04	0.29	0.09–0.95*	1.76	0.67
> 23	0.65	0.47–0.90*	0.74	0.51–1.07	1.37	0.28–6.63	0.54	0.21–1.37	0.0	0.0–0.0
Occupation
Unemployed	Reference		Reference		Reference		Reference		Reference
Employed	1.16	0.29–4.58	3.26	0.72–14.71	0.79	0.16–3.73	1.23	0.42–3.60	2.50	0.32–19.24
Retired	1.91	1.24–2.96***	2.54	1.38–4.69***	0.000	0.000–00.0	0.000	0.000–00.0	0.000	0.000–00.0
Manual worker	0.80	0.47–1.36	0.39	0.15–0.97	0.000	0.000–00.0	0.68	0.17–2.78	0.69	0.04–11.33
Self-employed	1.87	1.12–3.14**	1.58	0.78–3.22	0.32	0.03–3.63	1.31	0.38–4.47	0.0	0.0–0.0
House wife	2.09	1.37–3.21***	2.72	1.49–4.96***	0.34	0.07–1.72	0.99	0.35–2.87	1.98	0.26–15.02

Odds ratio (ORs:Specific chronic disease vs. nonspecific chronic disease) and 95% confidence intervals (95%CIs) from binary logistic regression

_{*p<0.05 **p<0.01***p<0.001}

Hypertension, diabetes mellitus and stroke were associated with BMI (OR _{BMI 21–23 vs. BMI<19 hypertension} = 0.47, 95%CI = 0.35–0.64; OR _{BMI>23 vs.BMI<19hypertension} = 0.65, 95%CI = 0.47–0.90; OR _{BMI 19–21 vs. BMI<19 diabetes mellitus} = 0.74, 95%CI = 0.58–0.93; OR _{BMI 21–23 vs. BMI<19 diabetes mellitus} = 0.34, 95%CI = 0.22–0.53;OR_{BMI 21–23 vs. BMI<19 stroke} = 0.29, 95%CI = 0.09- 0.95). Hypertension and diabetes mellitus were positively associated with occupation. Retired and housewives had more chance to have hypertension and diabetes mellitus than the unemployed elderly (Table 2).

Discussion

The current study was conducted within the framework of the Birjand Community Health Assessment and provided evidence of the prevalence and correlates of five NCDs, including diabetes mellitus, hypertension, chronic obstructive pulmonary disease (COPD), stroke, and cancer in the older adult population in Birjand. In this study, half of the participants reported at least one NCD, which implies the severity of chronic diseases among the elderly people residing in Birjand. Hypertension was the most frequently reported chronic condition among the fifth. The prevalence of hypertension in our sample is higher than the findings from the survey carried out among the elderly of Birjand that indicated 34.5% of elders had hypertension in 2014 [11]. The result is thought-provoking as cardiovascular diseases are the leading cause of death in Iran, and hypertension is one of the most common preventable risk factors [12]. Despite the high prevalence of hypertension among the Iranian communities, recent studies showed most patients are unaware of their disease and do not adhere to a specific treatment protocol [13, 14]. Educational program on hypertension, along with periodic physical examination or more efficient monitoring system, needs to be enhanced among the elderly in Birjand.

In regards to diabetes mellitus, the second prevalent NCD, dissimilar to previously reported out of Iran [15], diabetes mellitus was more prevalent in older women than in older men; however, the results of a recent study conducted in Yazd, which has one of the highest recorded prevalence of DM in Iran, are in line with our results [16]. Currently, obesity is more pervasive in women than men in Iran [17]. This may explain the cause of the higher prevalence of DM among Iranian women.

Noteworthy, the prevalence of stroke in this study (4.4%) is considerably higher than the most recently reported in a survey performed in a province of China, a developing country like Iran, where the survey reported the prevalence of 1.9% [18]. Given the high prevalence of stroke, primary prevention should be the focus of attention, and a plan of action to tackle unhealthy behaviors that raise the risk of stroke should be developed.

The present study showed that the prevalence of almost four NCDs increases with age, as also found in other studies [18, 19]. As such, young adults and middle-aged ones should be aware of this alarming trend, adhering to a healthy lifestyle to achieve healthy aging. Diabetes mellitus was found to be more prevalent in people aged 60–75 years than in those aged 85 years and older. This result, however, may be due to loss of the body mass connecting with age or frailty syndrome, which adjusts the effect of insulin secretion deficiency in older people [20].

The study also revealed that rural residents were associated with a significantly high chance of DM and hypertension. The results are not consistent with the previous studies [18, 21] and can be clarified by the prompt engagements in unhealthy behaviors occurring as a consequence of reducing geographical disparities and the growing trend of rural areas, which would be alarming. Unlike previous studies [18, 22], none of the five chronic conditions were associated with smoking. A previous study showed that elders with more health problems are more presumably to be eager to cease smoking than those with lower health problems [23]. Complementary studies with a larger sample size of old people are needed to confirm such association in this age group. Body mass index (BMI) has been typically considered as a risk factor for chronic diseases [18, 19, 21]. In this study, elderly participants with a BMI < 19 had the highest prevalence of DM, hypertension, and stroke, and these three conditions were associated with a low BMI. Surprisingly, the results of a very recent study in China [24] showed that obesity status is significantly associated with successful aging in old people and one component of healthy aging from the fifth, according to the definition of Rowe and Kahn, [25] is the absence of chronic diseases. The results may be controversial, and the follow-up research may be helpful. Like previous studies [18, 26], elderly manual workers had the lowest prevalence of diabetes mellitus and hypertension. Still, the findings propose that a wellness scheme in society to develop active lifestyles should be patronized. Moreover, retired and housewives had more chance to have hypertension and DM than the unemployed elderly. The results of a recent study [27] conducted in the North of Iran revealed the highest prevalence of DM and hypertension among elderly housewives, which is in line with our results. This reflects the necessity of a serious program for this vulnerable population. Considering the growing population of the elderly, appropriate programs should be planned to reach the goal of having healthy elders in society.

National data of four main NCDs in Iran revealed that cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes make the most contribution to mortality among the Iranian population. Also, 43% of total deaths in Iran are due to cardiovascular diseases, and hypertension is one of the most common preventable risk factors. Cancers, chronic respiratory diseases, and diabetes are responsible for 16%, 4%, and 4% of total deaths, respectively [28]. Statistics of NCDs risk factors are provided by Iran STEPs (stepwise approach to surveillance) 2016 survey. A recent survey on HTN prevalence in the Iranian population using Iran STEPs 2016 study results found a high prevalence of this disease [29]. Another study based on the Iran STEPs 2016 survey revealed a high prevalence of pre-diabetes and diabetes conditions in Iran which is responsible for the high rate of mortality [30].

It is necessary to mention some limitations and biases of our study, including self-reporting errors of NCDs, participants, and interviewer bias. Underreporting of NCDs among the participants is a potential limitation; however, we verified the outbreak of chronic diseases among our respondents through their health records or examination. Following a cross-sectional design is the second limitation of the study, which probably has limited making causal relationships. Furthermore, considering the relation of multi-comorbidities as it is usual among the elderly, as well as the connection of these chronic diseases with education level, income, physical activity, and dietary intake, would be beneficial for future studies. Despite limitations, our study showed two novel findings in the area. First, the prevalence of NCDs is exceeding, and living in rural areas is associated with a significantly high chance of DM and hypertension, which would be alarming. Second, diabetes mellitus, hypertension, and stroke are associated with a low BMI in elderly residents.

Conclusions

In spite of the possible limitations, the study creates great insight into the prevalence of multiple NCDs and their associated factors in the elderly population of Birjand. Such evidence may be beneficial to recognize the health priorities for the elderly in Birjand. However, a long-term evaluation of the NCDs prevalence and its associated factors in the target population is recommended.

Abbreviations

GBD

Global Burden of Disease

IHD

Ischemic Heart Disease

COPD

Chronic Obstructive Pulmonary Disease

BLAS

Birjand Longitudinal Aging Study

BMI

Body Mass Index

BP

Blood Pressure

DM

Diabetes Mellitus

Authors' contributions

Conceptualization: MF, TK, and MM.

Investigation: HA and AJ.

Analysis: AA.

Writing—original draft: MF, and MN.

Writing – review & editing: MF, TK, and FSh.

All authors read and approved the final manuscript.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The research purpose and methodology were subjected to scrutiny by the Ethics Committee of Birjand University of Medical Sciences (Ref: IR.BUMS.1399.292). In addition, written informed consent was obtained from all participants before entering the study and after a comprehensive introduction to the study protocol.

Consent for publication

N/A

Competing interests

The authors declare that they have no competing interests.