INTRODUCTION
Globally, 31% of all deaths were attributed to cardiovascular disease (CVDs) in 2016, including 85% due to heart attack and stroke1. Among older adults (aged ≥50 years) the top-ranked causes of disability adjusted life years (DALYs) were ischemic heart disease and stroke in 20192. More than 75% die from CVDs in low-resources countries1.
In the Asian region: in China 3.3% of the men and 3.6% of the women reported CVD3 (age: 35–74 years), in India the prevalence of stroke was 2.0% (age: ≥50 years)4, in Iran 5.3% reported coronary heart disease (CHD) (age: 20–69 years)5, in urban areas in northern Iran 9.2% reported CHD (age: 35–70 years)6, in rural Malaysia 4.8% had CVD (age: ≥18 years)7, and in a community-based study in northwestern Pakistan 4.8% had a history of stroke8. We could not find national information on CVD in Afghanistan9,10. One in five persons died from CVDs in Afghanistan in 201611, and ischemic heart disease and stroke were among top 10 causes of premature mortality in Afghanistan12.
Social and demographic factors associated with CVD may include increasing age and sex5,13,14, lower socioeconomic status6,13-15, not married13, separated/divorced16, ethnicity17, and urban residence5. Behavioral variables associated with CVD may include, tobacco use14,15,18, exposed to indoor passive smoking19, physical inactivity15,20, low or insufficient vegetable and fruit intake20,21, psychological distress22, and opium use6. Biological factors associated with CVD may include, hypertension5-7,14-18,20, diabetes6,7,14-18,20, obesity6,7,14,15,18,20, lipoprotein cholesterol, and dementia17.
This investigation aimed to estimate the prevalence and associated factors of CVDs among the national adult population in Afghanistan in 2018.
METHODS
Sample and procedure
This analysis used data from a national cross-sectional household survey in Afghanistan in 201823. By using a multistage cluster approach, a nationally representative sample of individuals aged 18–69 years was generated24. The primary sampling units were 55 districts, followed by villages or blocks (secondary sampling units) and households (tertiary sampling units). One person from each household was randomly selected24. Ethical approval was obtained from the Ministry of Public Health Ethics Board in Afghanistan, and participants provided written informed consent.
Data collection followed the WHO STEPS methodology: step 1 included administration of a structured questionnaire on sociodemographic characteristics, medical history, medication use, and health risk behavior; step 2 consisted of blood pressure and anthropometric measurements; and step 3 included biochemical tests such as blood glucose and blood lipids24.
Measures
The outcome variable, having CVDs, was defined as an affirmative response to the question: ‘Have you ever had a heart attack or chest pain from heart disease (angina) or a stroke (cerebrovascular accident or incident)?23.
Sociodemographic information included age, sex, education level, number of adult household members (as a proxy for socioeconomic status)25, and residence (rural or urban).
Behavioral covariates included current tobacco use, daily servings of vegetables and fruit, sedentary behavior (≥8 hours/day)26, and physical activity (low, moderate or high) based on the Global Physical Activity Questionnaire27.
Biological variables included measured body mass index (BMI, kg/m2) classified as: <18.5 underweight, 18.5–24.4 normal weight, 25–29.9 overweight, and ≥30 obese28. Hypertension was defined as systolic blood pressure ≥140 mmHg and/or diastolic ≥90 mmHg or if the participant was on antihypertensive medication29.
Diabetes was defined as: fasting plasma glucose level ≥7.0 mmol/L (126 mg/dL); or using insulin or oral hypoglycemic drugs; or having a history of diagnosis of diabetes30. Raised total cholesterol was defined as fasting total cholesterol ≥5.0 mmol/L or currently on medication for raised cholesterol30.
Statistical analysis
Descriptive statistics were used to provide the distribution of sociodemographic and health information of the sample, for both sexes and gender stratified. Unadjusted and adjusted logistic regression was applied to estimate predictors (sociodemographic and health variables) of CVDs for both sexes and multivariable logistic regression for assessing predictions of CVDs among males and females, separately. Taylor linearization methods were applied in statistical procedures accounting for sample weight and multi-stage sampling. Only complete cases were included in the analysis, and significance was set at p<0.05. Statistical procedures were done using STATA software version 14.0 (Stata Corporation, College Station, TX, USA), and considering the complex study approach.
RESULTS
Descriptive characteristics
The sample consisted of 3956 adults (aged 18–69 years), with a median age of 35 years (interquartile range: 24–60), and 51.9% were male. The majority (61.1%) had no formal education, 47.4% were living with five or more adult household members, and 57.8% lived in urban areas. Two in five participants (40.3%) were physically inactive, 44.0% engaged in sedentary behavior, 26.2% currently consumed tobacco and 59.8% had low consumption of vegetables and fruit (≤1 servings/day). The mean BMI of respondents was 25.3 kg/m2, 29.2% had hypertension, 9.2% diabetes, and 18.0% raised total cholesterol. The overall proportion of CVDs was 8.8%; 6.0% among females and 11.4% among males (Table 1).
Table 1
The characteristics and prevalence rate of CVD in Afghanistan, STEPS survey 2018 (N=3956)
Associations with CVDs
In adjusted logistic regression analysis showed that age 45–69 years (AOR=2.06; 95% CI: 1.06–4.01), current tobacco use (AOR=1.40; 95% CI: 1.06–4.01) and raised total cholesterol (AOR=2.37; 95% CI: 1.19–4.73) were associated with CVD (Table 2). In addition, in gender stratified analysis, among men, higher number of adult household members (lower economic status) (AOR=3.52; 95% CI: 1.92–6.43) and inadequate fruit and vegetable intake (<3 servings/day) were associated with CVD, while among women, urban residence (AOR=0.32; 95% CI: 0.15–0.68) and more frequent (≥3 servings/day) fruit and vegetable consumption (AOR=0.18; 95% CI: 0.03–0.99) were negatively associated with CVD (Table 3).
Table 2
Associations with cardiovascular disease in both sexes in Afghanistan, STEPS survey 2018 (N=3626)
| Variable | OR (95% CI) | p | AOR (95% CI)a | p |
|---|---|---|---|---|
| Age (years) | ||||
| 18–29 (Ref.) | 1 | 1 | ||
| 30–44 | 1.43 (0.84–2.42) | 0.187 | 1.27 (0.74–2.16) | 0.385 |
| 45–69 | 2.52 (1.71–3.70) | <0.001 | 2.06 (1.06–4.01) | 0.034 |
| Sex | ||||
| Female (Ref.) | 1 | 1 | ||
| Male | 2.03 (0.89–4.65) | 0.093 | 1.69 (0.66–4.31) | 0.272 |
| Education level | ||||
| None (Ref.) | 1 | 1 | ||
| ≤Primary | 0.71 (0.34–1.49) | 0.369 | 0.56 (0.27–1.22) | 0.145 |
| ≥Secondary | 0.76 (0.43–1.34) | 0.344 | 0.62 (0.33–1.15) | 0.130 |
| Adult household members | ||||
| <5 (Ref.) | 1 | 1 | ||
| ≥5 | 1.30 (0.77–2.22) | 0.328 | 1.52 (0.85–2.71) | 0.156 |
| Residence | ||||
| Rural (Ref.) | 1 | 1 | ||
| Urban | 0.87 (0.42–1.80) | 0.699 | 1.00 (0.51–1.99) | 0.999 |
| Fruit/vegetable intake (daily servings) | ||||
| ≤1 (Ref.) | 1 | 1 | ||
| 2 | 1.50 (0.89–2.52) | 0.127 | 1.32 (0.82–2.10) | 0.248 |
| ≥3 | 0.82 (0.32–2.24) | 0.689 | 0.80 (0.31–2.01) | 0.626 |
| Physical activity | ||||
| Low (Ref.) | 1 | 1 | ||
| Moderate | 1.39 (0.61–3.17) | 0.436 | 1.21 (0.50–2.93) | 0.675 |
| High | 2.12 (1.13–3.97) | 0.020 | 2.03 (0.92–4.42) | 0.078 |
| Sedentary behavior (hours/day) | ||||
| <8 (Ref.) | 1 | 1 | ||
| ≥8 | 0.67 (0.34–1.31) | 0.239 | 0.67 (0.30–1.49) | 0.325 |
| Current tobacco use | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 2.12 (1.21–3.73) | 0.009 | 1.40 (1.06–4.01) | 0.034 |
| Hypertension | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 2.12 (1.07–4.18) | 0.030 | 1.71 (0.87–3.35) | 0.117 |
| Type 2 diabetes | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 1.81 (0.81–4.04) | 0.147 | 1.30 (0.59–2.83) | 0.514 |
| Raised cholesterol | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 2.22 (1.01–4.91) | 0.047 | 2.37 (1.19–4.73) | 0.014 |
| Body mass index (kg/m2) | 0.99 (0.95–1.04) | 0.746 | 0.97 (0.91–1.02) | 0.243 |
Table 3
Associations with cardiovascular disease among men and women in Afghanistan, STEPS survey 2018 (N=3626)
| Variable | Male | Female | ||
|---|---|---|---|---|
| AOR (95% CI) | p | AOR (95% CI)a | p | |
| Age (years) | ||||
| 18–29 (Ref.) | 1 | 1 | ||
| 30–44 | 0.87 (0.50–1.49) | 0.604 | 7.42 (1.93–28.38) | 0.004 |
| 45–69 | 1.52 (0.54–4.25) | 0.423 | 8.01 (2.76–23.24) | <0.001 |
| Education level | ||||
| None (Ref.) | 1 | 1 | ||
| ≤Primary | 0.44 (0.19–1.00) | 0.050 | 1.24 (0.39–3.92) | 0.713 |
| ≥Secondary | 0.52 (0.25–1.04) | 0.065 | 0.43 (0.05–3.50) | 0.432 |
| Adult household members | ||||
| <5 (Ref.) | 1 | 1 | ||
| ≥5 | 3.52 (1.92–6.43) | <0.001 | 0.58 (0.25–1.35) | 0.205 |
| Residence | ||||
| Rural (Ref.) | 1 | 1 | ||
| Urban | 1.69 (0.73–3.53) | 0.223 | 0.32 (0.15–0.68) | 0.003 |
| Fruit/vegetable intake (daily servings) | ||||
| ≤1 (Ref.) | 1 | 1 | ||
| 2 | 1.93 (1.24–2.99) | 0.003 | 0.42 (0.13–1.37) | 0.151 |
| ≥3 | 1.60 (0.77–3.36) | 0.209 | 0.18 (0.03–0.99) | 0.047 |
| Physical activity | ||||
| Low (Ref.) | 1 | 1 | ||
| Moderate | 1.05 (0.34–3.25) | 0.934 | 1.58 (0.45–5.61) | 0.476 |
| High | 2.18 (0.86–5.52) | 0.101 | 1.69 (0.65–4.38) | 0.283 |
| Sedentary behavior (hours/day) | ||||
| <8 (Ref.) | 1 | 1 | ||
| ≥8 | 0.90 (0.36–2.25) | 0.815 | 0.71 (0.39–1.26) | 2.40 |
| Current tobacco use | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 1.24 (0.50–3.10) | 0.637 | 0.98 (0.32–3.09) | 0.977 |
| Hypertension | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 1.76 (0.93–3.35) | 0.082 | 1.83 (0.65–5.15) | 0.250 |
| Type 2 diabetes | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 1.20 (0.41–3.69) | 0.737 | 1.80 (0.47–6.87) | 0.390 |
| Raised cholesterol | ||||
| No (Ref.) | 1 | 1 | ||
| Yes | 3.06 (1.58–5.62) | <0.001 | 1.89 (0.82–4.33) | 0.132 |
| Body mass index (kg/m2) | 1.01 (0.94–1.09) | 0.775 | 0.96 (0.89–1.02) | 0.101 |
DISCUSSION
In this population-based national study among adults in Afghanistan in 2018, the prevalence of CVD (8.8%) was higher than in China (3.5%)3, Malaysia (4.8%)7, Nepal (2.0%)21 and Thailand (1.6%)3. Public health interventions are urgently needed in Afghanistan to prevent and manage CVDs31,32.
In line with former results5,13,14, increasing age (45–69 years) increased the odds of CVD. Unlike some previous investigations5,13,14, this study did not find significant sex differences in the prevalence of CVD. Previous research5,6,13-15 found an association between lower socioeconomic status, and urban residence, with CVD, while this study did not show such associations, for both sexes. However, among men, lower economic status (more adult household members) was positively associated with CVD, and among women, urban residence was negatively associated with CVD.
In line with past research14,15,18, current tobacco use increased the odds of CVD. Of the stroke related risk factors, tobacco use represents the most urgent challenge for Afghanistan, since its use is high and common across gender and regions9. In a meta-analysis of studies, the importance of smoking as an independent risk factor for stroke was confirmed33. Consistent with previous findings20,21, we found among men and women that low or insufficient vegetable and fruit intake was associated with CVD. Contrary to expectation15,20, physical inactivity was in this study not significantly associated with CVD. It is possible that participants after having been diagnosed with CVD increased their physical activity.
Consistent with findings5-7,14-18,20, this survey showed an association between raised total cholesterol, and in univariate analysis hypertension, with CVD. High rates of total cholesterol were also found in the general population in Afghanistan suggesting high propensity for ischemic stroke in this population9. Unlike some studies6,7,14-18,20, this analysis did not find significant associations between higher BMI, and diabetes, and CVD.
Strengths and limitations
Some of the variables assessed in this study were by self-report, including the outcome variable CVDs. However, previous research comparing hospital diagnosed and self-reported CVD, found self-reported CVD to be valid34. Another limitation was the cross-sectional design of the study, which hinders making causative conclusions. The prevalence of CVD is this survey was probably underestimated, since only survivors of CVD were included31. Furthermore, more details of the CVD type, time of CVD diagnosis and other relevant variables, such as psychological distress, were not assessed and should be part of future research.
CONCLUSIONS
Almost one in ten Afghan adults had CVD. Several associated factors for CVDs, such as older age (45–65 years), current tobacco use, raised total cholesterol, and inadequate fruit and vegetable consumption, were identified, which can be targeted in public health interventions. Local health systems need to be strengthened and mass education programs initiated.
