This study was conducted on 9300 participants with mean age of 48.06 ± 9.44 years that 4340 (46.7%) of them were male. Mean years of education was 4.8 ± 3.89. Of total, 8318(89.4%) were married and 4867(52.3%) had job, (Table 1).
Table 1
Socio demographic Characteristics of the opium and non-opium users in first phase of PERSIAN cohort study
variable | Opium user | Opium non-user | Total |
n | % | n | % | n | % |
Gender | | | | | | |
Male | 2152 | 49.6 | 2188 | 50.4 | 4340 | 46.7 |
Female | 87 | 1.89 | 4873 | 98.2 | 4960 | 53.3 |
Job status | | | | | | |
Employed | 1946 | 40 | 2921 | 60 | 4867 | 52.3 |
Unemployed | 291 | 6.6 | 4125 | 93.4 | 4416 | 47.5 |
Marital status | | | | | | |
Single | 53 | 14.8 | 304 | 85.2 | 357 | 3.8 |
Married | 2163 | 26 | 6155 | 74 | 8318 | 89.4 |
widow | 12 | 2.3 | 517 | 97.7 | 529 | 5.7 |
Divorced | 11 | 11.5 | 85 | 88.5 | 96 | 1 |
Socio-economic Status | | | | | | |
Low | 656 | 21.4 | 2411 | 78.6 | 3067 | 33 |
Middle | 722 | 24.2 | 2262 | 75.8 | 2984 | 32.1 |
High | 843 | 26.6 | 2322 | 73.4 | 3165 | 34 |
variable | Mean | SD | Mean | SD | Mean | SD |
Age (Year) | 47.13 | 8.58 | 48.36 | 9.68 | 48.06 | 9.44 |
Education (Years) | 5.78 | 3.80 | 4.48 | 3.87 | 4.80 | 3.89 |
BMI (Kg/M2) | 23.39 | 4.54 | 26.22 | 4.72 | 25.54 | 4.83 |
Physical activity (Met-hr/day) | 44.90 | 14.38 | 40.74 | 10.21 | 41.74 | 11.49 |
Fat intake (gr/day) | 89.78 | 42.35 | 72.69 | 34.91 | 78.8 | 37.55 |
2564 (27.6%) people were current smoker, 2239 (24.1%) were opium users and 196 (2.1%) consumed alcohol regularly.
In this population Mean of TG was 130.88 ± 82.72, Cholesterol was 186.38 ± 38.58, LDL was 109.1 ± 32.22, and HDL was 51.06 ± 15.98 mg/dl.
Univariate analysis show that age (r = 0.15, p < 0.001), years of education (r=-.0.11, P < 0.001), BMI (r = 0.2, p < 0.001), physical activity base on MET (r=-0.09, p < 0.001), fat intake (r=-0.05, P < 0.001) were significantly correlated with cholesterol level.
Female, unemployed, and widow participants had significantly higher level of cholesterol. Triglyceride level was not correlated with Age (r = 0.01, p = 0.07), years of education (r=-.0.01, P = 0.19) and fat intake (r=-0.009, p = 0.36) but, BMI (r = 0.21, p < 0.001) and physical activity base on MET (r=-0.05, p < 0.001) were significantly correlate with TG. Female, single and divorced, low socioeconomic level participants had significantly lower level of TG.
Lower level of HDL was seen in male, married, employed and high socio-economic status participants. Age (r = 0.08, p < 0.001), years of education (r=-0.13, p < 0.001) and BMI (r=-0.02, p = 0.01) were significantly correlated but physical activity (r=-0.01, p = 0.3) and fat intake (r = 0.005, p = 0.65) were not correlated with HDL level.
Age (r = 0.13, p < 0.001), years of education (r=-0.07, p < 0.001), BMI (r = 0.14, p < 0.001), physical activity (r=-0.08, p < 0.001) and fat intake (r=-0.05, p < 0.001) were significantly correlated with LDL level. Female, widow and unemployed persons had higher level of LDL, (Table 2).
Table 2
Correlation of lipid profile and socio-demographic characteristics of participants in first phase of PERSIAN cohort study
variable | Cholesterol mean ± SD | P value | TG mean ± SD | P value | LDL mean ± SD | P value | HDL mean ± SD | P value |
Gender | | | | | | | | |
Male | 179.82 ± 37.22 | < 0.001 | 136.17 ± 92.23 | < 0.001 | 105.26 ± 31.06 | < 0.001 | 47.28 ± 14.39 | < 0.001 |
Female | 192.3 ± 38.85 | 127.2 ± 74.65 | 112.47 ± 32.86 | 54.36 ± 16.56 |
Job | | | | | | | | |
Employed | 181.61 ± 37.9 | < 0.001 | 142.53 ± 87.03 | 0.16 | 106.56 ± 31.47 | < 0.001 | 48.49 ± 14.64 | < 0.001 |
Unemployed | 191.84 ± 38.68 | 130.14 ± 79.31 | 111.9 ± 32.84 | 53.87 ± 16.88 |
Marital status | | | | | | | | |
single | 183.65 ± 37.59 | < 0.001 | 114.68 ± 69.76 | < 0.001 | 105.23 ± 31.06 | < 0.001 | 55.48 ± 19.81 | < 0.001 |
Married | 184.6 ± 39.06 | 132.43 ± 83.92 | 107.38 ± 32.74 | 50.69 ± 15.76 |
divorced | 193.43 ± 41.23 | 110.34 ± 55.92 | 105.99 ± 29.76 | 53.5 ± 17.25 |
widow | 181.56 ± 35.88 | 136.89 ± 69.53 | 113.3 ± 35.56 | 52.63 ± 14.43 |
Socio-economic level | | | | | | | | |
Low | 186.06 ± 40.3 | 0.06 | 126.58 ± 76.28 | < 0.001 | 108.69 ± 33.75 | 0.26 | 51.99 ± 16.09 | < 0.001 |
Middle | 185.6 ± 39.58 | 133.78 ± 90.5 | 107.51 ± 33.35 | 51.3 ± 16.17 |
High | 183.63 ± 37.75 | 135.16 ± 80.13 | 106.76 ± 31.6 | 49.81 ± 15.36 |
Cigarette smoking | | | | | | | | |
Yes | 178.97 ± 38.74 | < 0.001 | 133.13 ± 84.83 | 0.2 | 104.78 ± 31.55 | < 0.001 | 47.5 ± 15.05 | < 0.001 |
No | 189.37 ± 38.16 | | 130.72 ± 82.86 | | 115.78 ± 32.33 | | 52.41 ± 16.12 |
Alcohol consuming | | | | | | | | |
Yes | 179.05 ± 40.4 | 0.006 | 146.21 ± 96.89 | 0.03 | 105.2 ± 35.18 | 0.11 | 43.95 ± 11.4 | < 0.001 |
No | 186.66 ± 38.56 | | 131.05 ± 83.07 | | 109.2 ± 32.16 | | 51.22 ± 16.03 |
Analysis show that cigarette smokers and alcohol users had significantly lower level of cholesterol compare with non-users. But alcohol consumers had significantly higher level of TG compare with non-users. LDL level was lower in cigarette smokers significantly. Cigarette smokers and alcohol users had lower level of HDL, (Table 2).
In a linear regression model, we added all variables which were correlate with lipid profile (Chol, TG, LDL, HDL) in univariate analysis with significant level of < 0.2. Adjusted p value was reported for correlation of Opium and lipid profile. Opium users had significantly lower level of total Cholesterol (β=-2.5), LDL (β=-2.03) and HDL (β=-1.0), Fig. 1.
Due to the importance of high lipid profile as risk factor for many diseases such as cardio vascular, we analyzed correlation of opium usage and abnormal level of lipid profile in present of other variable and confounders in logistics regression model, (Table 3).
Table 3
logistic regression model for lipid profile in first phase of PERSIAN cohort Study.
Variable | SE | OR | β | P value |
Cholesterol | 0.07 | 0.82 | -0.19 | 0.008 |
TG | 0.06 | 1.03 | 0.03 | 0.64 |
HDL | 0.22 | 0.83 | -0.18 | 0.41 |
LDL | 0.08 | 0.78 | -0.24 | 0.003 |