The association between classic risk factors and CVD has been proven, but even for those risk factors with the same effect size, they can produce a completely different effect on the occurrence of disease due to the difference in the prevalence, so the calculation of PAF must be performed, using the population of the target community.
Comparison of the results of PAF studies in different societies might be difficult. In fact, different reports have used different demographic groups, in terms of gender, age and ethnicity. In addition, different set of risk factors for calculation of PAF might be entered to the model and also different computational methods are used with different definitions and cut- off points for risk factors. Therefore, such variations create major difference in the PAF values of the risk factors [13], which makes it difficult to compare the results of such studies.
In the present study, PAF of hypertension for CVDs has a higher value in women (42.8%) than in men (35.7%), and this difference has been reported from two population based cohort studies conducted in Iran (19.3% in women vs. 11.7% in men) and (17% in women vs. 9.4% in men) [26, 27]. Also, it is consistent with the results of study in Sweden from “the Malmö preventive project” (23% in women vs. 12% in men) [28]. However, PAF of hypertension for CVD has a lower ranking in report of study in Sweden compared to other risk factors [28]. In addition, in a study conducted in Germany using health and nutrition survey data [12], the highest PAF was related to hypertension. However, the ranking for other risk factors is different.
Our results indicated the prevalence of dyslipidemia was higher in men (53.2%) than in women (46.7%), which is in line with the findings of another population-based cohort study in Iran (22.5% in men vs. 33.2% in women) [26] and a report from Denmark (47% in men vs. 57% in women) [29]. In the present study, the PAF of dyslipidemia for developing CVD was higher in men (12.2%) than in women (9.7%), which is in contrast with the findings from elsewhere (36% in men vs. 46.5% in women in Latin America and 18% in men vs. 23% in women in Sweden) [28, 30]. It is similar to the study that was conducted in Argentina and the United States reported that the PAF of dyslipidemia in both groups (16.0% in men vs. 15.6% in women) gained the third ranking for CVD disease [31], which is consistent with the results of the current study in terms of ranking. However, in the present study dyslipidemia made higher contribution to the prevalence of cases with CVD among men compared to women. This difference might be due to different demographic characteristics of the study sample and different definition of dyslipidemia compared to the present study.
In the present study, the prevalence of diabetes was higher in men (11.4%) than in women(4.2%), which is in line with the results of the study in Denmark (4% in men vs. 2% in women) [29] and Spain (11.7% in men vs. 8.4% in women) [32], but in contrast with the findings of another study in Iran (14.4% in men vs. 15.9% in women) [26]. In addition, the results of this study showed that PAF of diabetes, for developing CVD is higher in women (3.9%) than men (3.8%), which is consistent with the results of studies conducted in industrialized countries, showing a greater impact of diabetes on the incidence of CVD in women population [33]. While PAF of diabetes was reported twice in women, compared to men (6% versus 3%) in Sweden [28], in Spain a significant difference was observed in women (16.2%) compared to men (1.7%) [32].
In our study, while, general obesity was not statistically significantly contributed to the prevalence of CVDs among men, almost (16.7%) of CVD in RaNCD was due to BMI ≥ 30. In addition, PAF of general obesity for CVD was more in women (10.7%) compare to men (5.7%). Due to different cut- off points and differences in computational methods, the results of this study were not consistent with the study in Denmark (7% in women vs. 10% in men) and Spanish population (36.5% in women vs. 42.5% in men) [29, 32]. On the other hand, central obesity (WHR) independent of general obesity (BMI), was the risk factor of occurrence of CVD [34]. In the present study, although none statistically significantly, PAF of central obesity, for developing CVD is more in women (10.1%), than in men (3.3%). The differences between men and women is consistent with the study of “Interheart Latin American” (63.1% in women vs. 35.8% in men) and other reports from Iran (9.9% in women vs. 5.9% in men) [26, 30].
Moreover, the prevalence of depression was higher in women (3.7%) than in men (2.4%). Not surprisingly, in the current study, the PAF of depression for developing CVD was higher in women (4.4%) than in men (3.1%), which is in agreement with the results of the study of “Interheart Latin American” (1.4% in women vs. 5.3% in men) [30]. This contradiction might be due to the differing demographic characteristics of the studied population and different definitions of depression.
The findings of this study showed that PAF of cigarette smoking in developing CVD in men (4.0%) is more than women (1.3%), which is consistent with the results of the study conducted in Argentina and the United States (10.1% in men vs. 7.2% in women) and Spain (33.9% in men vs. 8% in women) [31, 32]. It is also consistent with the results of the study of “Interheart Latin American” (42.5% in men vs. 25.7% in women) [30], but due to the higher prevalence of smoking in both sexes in Western countries, the findings of ours differ from those of other countries. In fact, the definition of smoking in our study might be different from others in which current smokers are those who have smoked at least 100 cigarettes during his/ her life. Such definition, although increases the prevalence of smoking, dilutes the effect size and therefore such points need to take into consideration for any interpretation of PAF related to smoking.
the results showed the prevalence of physical inactivity was higher in women (68.2%) than in men (51.3%), which is in line with the results of population-based cohort study in Iran (62.9% in women vs. 65.6% in men) [26] and of study in Denmark (19% in women vs. 20% in men) [29]. Further, the PAF of physical inactivity for developing CVD was higher in men (1.8%) than in women (1.3%), which is in agreement with the results of the “Interheart Latin American study” (28.1% in men vs. 27.9% in women) [30], and in contrast with the findings of study in Denmark (5% in men vs. 7% in women) [29]. In fact, PAF of physical inactivity (compared to other risk factors) in other studies is higher than the present study. This might be due to the use of different demographic groups, different computational methods, and ultimately different definitions and cut-off points for included variables.
The prevalence of alcohol consumption was lower in women (0.0%) than in men (10.8%), which is consistent with the similar study conducted in Sweden (10% in women vs. 32% in men) [28] but contradicting the findings of the study in Denmark (88% in women vs. 56% in men) [29]. In the present study, alcohol consumption in women (-0.1) has lower PAF, compared to men (1.9), which is consistent with the results of the study in Sweden (1% in women vs. 3% in men) and Denmark (-1% in women vs. 12% in men) [28, 29]. This difference can be due to low prevalence of alcohol use in the included population in RaNCD plus different definitions and cut-off points considered for this variable within all above mentioned studies. The results of this study were not in line with Interheart study in Latin American [30].
The findings of this study showed no significant statistical relationships between the CVD and substance abuse, occupation, place of residence, taking contraceptive pills, the use of hormone replacement therapy and menopause. None of the previous studies looked at these variables [26-33].
The PAF of socioeconomic status was low for CVD. It was higher in men (6.7%) than in women (3.8%), which is not consistent with the results of the study conducted in Denmark (10% in men vs. 15% in women) [29], this difference is probably due to the use of different demographic groups, different computational methods, and ultimately different definitions and cut-off points for included variables.
In the present study, high-risk age in men (15.0%), in comparison with women (6.3%) had a higher PAF, which was consistent with the results of two population based cohort studies conducted in Iran (36.1% in men vs. 16.6% in women and 42% in men vs. 22% in women) [26, 27] and a study from China (11.4%) [12].
The family history of CVD, in the presence of other variables, had a higher PAF in men (1.5%), compared to women (0.7%), which was not statistically significant in both genders. The results of this study are consistent with the results of the study from Sweden (9% in men vs. 3% in women) [28], but different from the results of two population based cohort studies conducted in Iran (3.9% in men vs. 7.6% in women and 2.5% in men vs. 6.8% in women) [26, 27]; This difference is partly due to inclusion of different population.
In interpreting the results of studies on PAF, it should be considered that the reduction in the incidence of disease attributed to each risk factor is a theoretical concept. Because in practice, one can never reduce the exposure to a risk factor to zero in the community, or no one can design an intervention that, while maintaining the exposure to other risk factors, affects only one particular risk factor [35]. As a result, PAF values are more appropriate to prioritize the impact of risk factors at the community level, rather than planning, to achieve practically, this level of reductions.
Study Strength and Limitations
For the purpose of this study we used the prevalent cases. Thus, due to lack of knowledge regarding exposure-outcome associations of individuals in such studies, the identification of temporality between exposure and outcome is difficult. Therefore we cannot discuss about causality. Despite these limitations, there are several strengths in current study that are including use of population-based Information; large sample size, and high quality data. In addition, the accuracy of PAF estimation is dependent on the correct detection of confounders of each risk factor, so the directed acyclic graph was used.