Relationship between opium consumption and lipid profile in drug addicts and non-addicts on Kharameh cohort study

Relationship between opium consumption and lipid profile in drug addicts and non-addicts on Kharameh cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Relationship between opium consumption and lipid profile in drug addicts and non-addicts on Kharameh cohort study Najibullah Baeradeh, Seyed Vahid Hosseini, Leila Moftakhar, Fatemeh Jafari, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2526717/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Drug abuse is known as one of the most important health, medical, and social problems. Furthermore, this study was performed to evaluate the relationship between opium and lipid profiles. Methods This cross-sectional study was conducted on 10,663 individuals, aged 40 to 70, living in Kharameh (south of Iran). Demographic information, lipid profile, and the history of use of opium, alcohol, and cigarettes in participants were investigated. To check the lipid profile, blood samples were taken from all participants. The prevalence of opium use was calculated. Linear regression was used to examine the relationship between opium use and the lipid profile of an individual. A significance level of 5% was considered for the tests, and STATA software was used for analysis. Result Among the 10,663 participants in the study with a mean age of 52.2 ± 8.22 years, about 55.7% were women. The prevalence of opium use among the participants in the study was estimated at 16%. Multiple linear regression results revealed no statistically significant relationship between opium use and lipid profile. Conclusion Contrary to the beliefs that there are about the effects of opium on reducing lipid profile levels, in our study, there was no correlation between LDL, triglycerides and opium consumption. Health sciences/Medical research Health sciences/Risk factors Opium use Lipid profile Persian cohort Prevalence Figures Figure 1 Figure 2 Introduction Drug abuse is known as one of the most important health, medical, and social problems of this century ( 1 , 2 ). Drug addiction is a serious threat to health in various communities, especially for young people ( 3 ). More than 62 million people worldwide use opiates for non-medical reasons, of which nearly 31 million use heroin and opium alone ( 4 ). The prevalence of drug use varies around the world and in different countries, cultures, and occupations ( 5 ). Opium has long been used in many south-central Asian countries, particularly Iran, Pakistan, Afghanistan, and India, as well as in some parts of South-East Asia ( 6 ). Iran is one of the countries with a high share of addicts in the world, so it is estimated that about 4 million Iranians use opium regularly or occasionally ( 7 , 8 ). According to studies, the prevalence of opium use in Iran varies in different regions, and suffering has been reported between 8.9% and 24.7% ( 9 – 11 ). There are common and unscientific beliefs that opium consumption lowers serum lipids as well as prevents chronic diseases such as diabetes and cardiovascular disease ( 12 , 13 ), but most studies have shown that opium use increases the risk of acute myocardial infarction, atherosclerosis, and cardiovascular mortality ( 14 ). Additionally, current evidence suggests that opium consumption is associated with an increased risk of laryngeal, lung ( 13 ), bladder ( 15 ), and upper gastrointestinal cancers ( 16 ). There is much disagreement about the effect of opium on lipid profiles. In one study, cholesterol and triglyceride levels were lower in opium users ( 17 ), whereas in Kahonji’s study, cholesterol, triglycerides, and LDL were higher in opium users compared to healthy individuals ( 18 ). We expect this study to provide more accurate information in this area so that scientific beliefs can be scientifically answered. Furthermore, this study was performed on a large scale, considering the role of confounding factors such as cigarettes, alcohol, and tobacco that can affect the relationship between opium and the lipid profile. Results The present study was conducted on 10,663 individuals aged 40 to 70, with a mean age of 52.2 ± 8.22 years. The majority of participants were female (55.74%) and married (89%). The prevalence of opium use in the individuals under study was 16% (CI: 15.3–16.7), and 25.35%, 5.1%, and 5.3% of the individuals under study used cigarettes, hookah, and alcohol, respectively (Table 1 ). Also, a statistically significant difference was seen in different levels of gender, occupation, education, SES, married status, BMI, smoking, alcohol, and hookah consumption between opium users and non-users (Table 1 ). Table 1 Distribution of demographic characteristics among opium users and non-users in the population of 40 to 70 years of Kharameh Variable Class Total Use opium(N%) Non-use opium(N%) P-value Gender Male 4719(44.26) 1733(36.72) 2986(63.28) 0.0001 Female 5944(55.74) 73(1.23) 5871(98.77) Occupation Unemployed 5147(48.27) 303(5.8) 4844(94.11) 0.0001 Employed 5516(51.73) 1503(27.25) 4013(72.75) Married status Single 216(2.03) 13(6.02) 203(93.98) 0.0001 Married 9492(89.02) 1761(18.5) 7731(81.45) Widow 896(8.04) 26(2.9) 870(97.1) Divorced 59(0.55) 6(10.1) 53(89.83) Socioeconomic status Low 2667(25.01) 402(15.07) 2265(84.93) 0.0001 Moderate 2977(27.92) 408(13.71) 2569(86.29) high 2539(23.81) 426(16.78) 2113(83.22) Very high 2480(23.26) 570(22.98) 1910(77.02) Education Illiterate 5587(52.4) 677(12.12) 4910(87.88) 0.0001 Primary school 2676(25.10) 551(20.59) 2125(79.41) Secondary school 1136(10.65) 324(28.5) 812(7148) Diploma 702(6.58) 185(26.35) 517(73.65) University 562(5.27) 69(12.28) 493(87.72) Use smoke No 7594(95.41) 366(4.59) 7594(95.41) 0.0001 Yes 2703(25.35) 1440(53.27) 1263(47.73) Use alcohol No 10095(94.67) 1337(13.24) 8758(86.76) 0.0001 Yes 568(5.33) 469(16.94) 99(17.43) Use hookah No 10115(94.86) 1468(14.54) 8647(85.49) 0.0001 Yes 548(5.14) 338(61.68) 210(38.32) BMI Under weight 413(3.88) 189(45.76) 224(54.24) 0.0001 Normal 3879(36.41) 909(23.43) 2970(76.57) Overweight 4447(41.74) 577(12.98) 3871(87.02) Obese 1916(17.98) 129(6.73) 1787(93.27) The mean levels of triglycerides, cholesterol, LDL, and HDL of the individuals were 130.3 ± 80.86, 186.75 ± 41.7, 104.99 ± 27.9, and 47.7 ± 12.8 mg/dL, respectively. Also, a statistically significant difference was seen in the mean levels of HDL (P < 0.001) and cholesterol (P = 0.04) between opium users and non-users (Table 2 ). Table 2 Distribution of the mean levels of lipids among opium users and non-users in the population of 40 to 70 years of Kharameh Variable Total Use opium (mean ± SD) Non-use opium (mean ± SD) P-value LDL 104.99 ± 27.9 104.13 ± 28.03 105.31 ± 27.96 0.15 HDL 47.7 ± 12.8 45.99 ± 12.15 48.07 ± 12.64 < 0.001 TG 130.3 ± 80.86 132.22 ± 87.07 129.99 ± 79.53 0.28 CHOL 186.75 ± 41.7 184.98 ± 41.84 187.11 ± 41.75 0.04 LDL : Low density lipid, HDL : High density lipid, TG : Triglyceride, CHOL : cholesterol About 15.06%, 20.3%, 12.81%, and 25.18% of opium users had abnormal levels of triglyceride, cholesterol, LDL, and HDL levels, respectively. Also, 13.34%, 13.94%, 3.72%, 5.38% had unhealthy levels of triglyceride, cholesterol, LDL, and HDL levels, respectively (Fig. 1). The results of the correlation analysis showed that age (r=-0.02, P = 0.029), BMI (r = 0.0119, P = 0.0001) and physical activity level (r=-0. 45, P = 0.0001) had a statistically significant correlation with triglyceride level. BMI (r=-0.06, P = 0.0001) and physical activity level (r=-0.02, P = 0.0024) had a statistically significant correlation with cholesterol levels but age did not show a significant correlation (P = 0.058) with cholesterol level. LDL level also showed a statistically significant correlation with BMI (r = 0.06, P = 0.0001) and physical activity level (r=-0.034, P = 0.003), but it did not show a significant correlation with age (P = 0.059). Age (r = 0.062, P = 0.0001), BMI (r = 0.0619, P = 0.0001), and physical activity level (r=-0.017, P = 0.0001) had a statistically significant correlation with HDL level. The results of linear regression analysis also showed that alcohol consumption (β = 12.2, P = 0.001), and individuals with normal BMI (β = 15.9, P = 0.0001), overweight (β = 29.4, P = 0.0001), and obesity (β = 36.5, P = 0.0001), and residents of the urban (β = 8.1, P = 0.0001) had a significant relationship with high triglyceride levels. Also, not having a job (β = -4.4, P = 0.015), age (β = -0.25, P = 0.008), the individuals with level of moderate of SES (β = -4.7, P = 0.03), the individuals with level of severe of physical activity (β = -8.7, P = 0.001) and smoking (β = -7.16, P = 0.001) had a statistically significant relationship with the lower level of triglycerides (Fig. 2 (A)). age (β = -0.14, P = 0.004), individuals with normal BMI (β = 6.27, P = 0.004), overweight (β = 9.5, P = 0.0001), and obesity (β = 10.5, P = 0.0001), individuals with level of education of diploma (β = -2.92, P = 0.003) and university (β = -2.98, P = 0.03), and alcohol consumption (β = 5.67, P = 0.004) showed a statistically significant relationship with cholesterol level (Fig. 2 (B)). individuals with normal BMI (β = 5.26, P = 0.0001), overweight (β = 7.44, P = 0.0001), and obesity (β = 7.94, P = 0.0001), and residents of the urban (β = 7.7, P = 0.0001) and age (β = -0.07, P = 0.025) had a statistically significant relationship with LDL (Fig. 2 (C). Also, individuals with normal BMI (β = 5.55, P = 0.0001), overweight (β = 7.88, P = 0.0001), and obesity (β = 8.3, P = 0.0001), and residents of the urban (β = 8.2, P = 0.0001), alcohol use (β = 2.82, P = 0.03), age (β = -0.08, P = 0.013), individuals with level of education of university (β = -2.39, P = 0.012), diploma (β = -2.1, P = 0.002) and secondary (β = -3.84, P = 0.0009) showed a statistically significant relationship with the level of HDL (Fig. 2 (D)). Discussion Opium abuse is common in West Asia and Iran due to the common beliefs among people about the effects of prevention and treatment of diseases. Also, conflicting results regarding the effects of opium consumption on lipid profiles have been reported. Therefore, in this cross-sectional study with a large sample size obtained from detailed cohort data, we examined the relationship between opium and lipid profile. The findings of our study showed that the prevalence of opium use is 16%, which is more than the study of Fallahzadeh et al. ( 19 ) and in line with the results of the cohort studies conducted in the north ( 10 ) and lower than south of Iran ( 20 ). In a study conducted in India, the prevalence of opium use in men was 5.76%, which was lower compared to our results ( 21 ). One of the reasons for the high prevalence of drug use in different parts of Iran and in this study can be attributed to its neighborhood with Afghanistan and the fact that Kharameh is on the way to transport opium into the country from the eastern and southern borders. Therefore, people have more access to this type of substance ( 9 ), and it may also be due to the belief that opium use has a preventive role in disease control ( 22 ). In our study, the prevalence of smoking (25.3%) was almost twice the average in Iran, so that in the meta-analysis study, Mooszadeh et al. estimated the prevalence to be 13.9% ( 23 ). In this study, the prevalence of smoking was higher than in the countries of Pakistan (19.4%), Oman (7%), Kuwait (17%), Saudi Arabia (11.6%), and America (20.6%), and was in line with the results of the study conducted in Italy (26.2%) ( 24 – 29 ). Alcohol consumption in the population under study is nearly one-third that of Iran. In the meta-analysis study conducted by Chegni et al., the prevalence of alcohol consumption in Iran was reported at 13% ( 30 ). In a study conducted in India, the prevalence of alcohol consumption in men was reported to be 35% ( 31 ), which is high compared to our study. The low prevalence of alcohol consumption in our study could be due to the following reasons: First, due to religious beliefs, Iranian society consumes less alcohol than some other countries; second, alcohol consumption is a crime in Iran, both because of the crime it is and because of the social stigma it carries. Previous studies have shown that cholesterol levels in opium users are lower than those of normal people. Fatemi et al. showed in their study that the cholesterol level of opium addicts with a BMI between 18 and 25 was 20 mg lower than that of healthy people ( 12 ). In our study, cholesterol was lower in opium users than in healthy people. In line with our study, in a meta-analysis study that was conducted on the lipid profile of diabetic patients, it has been shown that opium use reduces cholesterol levels ( 32 ). However, in the following studies, no significant results have been obtained regarding the relationship between opium and reducing cholesterol levels. In Hosseini et al.’s study, they showed weak evidence of the relationship ( 33 ), and in Rezvanfar et al.’s study, although cholesterol levels were lower in opium users, the results were not significant ( 34 ). In these studies, although the cholesterol levels were lower in the consumer group, the results were not significant, which may be due to the small sample size in these studies. The findings of our study showed that the consumption of opium has a negative effect on HDL levels and that it decreases with alcohol. In line with our study, in the study of Asadi Karam et al., they have shown that HDL levels in opium users are lower than healthy people ( 35 ). However, some studies have shown that opium consumption has no significant effect on HDL ( 32 – 34 ). The results of our study showed that opium is not related to LDL or triglycerides, which is in line with the results of other studies ( 12 , 36 , 37 ), but in some studies it has been shown that triglycerides are lower in opium users ( 33 , 34 ). On the other hand, Rahimi et al. reported weak evidence of the effect of opium on lowering LDL levels in their study ( 38 ). In general, low levels of some lipids in people who use opium may be due to malnutrition associated with a loss of appetite in these people. In studies, it has been shown that drug abuse significantly changes the diet and addicts have a poor nutritional status, and it has also been shown that the weight of addicts is lower than the average weight of the population in terms of gender and height ( 39 ). In our study, there was a significant difference in BMI between opium users and healthy people, which can be high for the mentioned reason. Some of the findings in our study, as well as other studies, may suggest anti-lipid effects of opium, but they should be interpreted with caution because many factors other than opium use can affect lipid profiles, which may be different between addicts and non-addicts, and it is difficult to control them in a cross-sectional study. The results of the multivariate analysis of our study showed that alcohol consumption and high BMI increase the level of triglycerides, while not having a job, old age, and university education decrease it. In other studies, the role of ethanol in increasing triglyceride levels has been mentioned, so that in a clinical trial study that was conducted on healthy people and people with hypertriglyceridemia, it was shown that people who drank moderate amounts of ethanol three times a day, saw their plasma triglyceride levels increase significantly ( 40 ), which is in line with the results of our study. It has been mentioned in other studies that alcohol increases triglyceride levels ( 20 , 41 ). Previous studies in line with this study have shown that triglycerides are significantly higher in obese people ( 20 , 42 ). In our study, age was shown as a protective factor for triglyceride levels, in contrast to other studies, which have shown that age plays a role as a risk factor and causes an increase in triglyceride levels ( 43 , 44 ). However, in a cohort study conducted for 15 years on people over 70 years old in Finland, no significant relationship between age and triglycerides was observed ( 45 ). One of the reasons for observing the inverse relationship between age and triglyceride levels in our study may be because with increasing age, the incidence of non-communicable diseases, especially cardiovascular ( 48 , 49 ), and hyperlipidemia ( 50 ), increases, which causes people to change their lifestyle or take triglyceride-lowering drugs. Therefore, the correlations obtained in cross-sectional studies should be interpreted with caution. The results of multivariate analysis also showed that age, body mass index, diploma and university levels of education, and alcohol consumption increase cholesterol levels. Studies have shown conflicting results regarding the relationship between age and cholesterol. Age raises cholesterol in some studies ( 21 ), but lowers it in others ( 51 – 53 ). In some studies, age increases cholesterol ( 20 ) and in others it decreases ( 46 – 48 ). In these studies, it has been shown that cholesterol increases in men up to the age of 65 and in women up to the age of 75 and then decreases ( 47 , 49 , 50 ). The difference observed among the studies may be due to the fact that the age range studied in each study is different from the other because, according to the studies, cholesterol in the elderly decreases with increasing age and increases in the middle-aged with increasing age, as mentioned above, and in our study, most of the people were middle-aged. Previous studies have also shown that alcohol consumption increases cholesterol levels ( 51 , 52 ), which is consistent with the findings of our study. Conclusion Contrary to the beliefs that there are about the effects of opium on reducing lipid profile levels, in our study, there was no correlation between LDL, triglycerides and opium consumption. The levels of HDL (good cholesterol that prevents heart attacks) were lower in addicted people than in healthy people. Although in this study the level of cholesterol was lower in addicts, in general, due to the known side effects of opium on non-communicable diseases, especially cancers, the use of opium is not recommended to reduce lipid profile. Methods The current study is a cross-sectional study that was conducted using the data of the Kharameh cohort study in southern Iran with the aim of determining the status of the lipid profile in opium users. In this study, 10,663 individuals aged 40 to 70 years have been examined. The Kharameh cohort study is a part of the large Prospective Epidemiological Research Studies in Iran (PERSIAN) that is being conducted in 18 regions of Iran. The inclusion criteria in this study include: age between 40 and 70 years, living in Kharameh city for at least 9 months, and having Iranian nationality. Exclusion criteria include mental disorders and mental retardation. Unwillingness to participate in the study and not attending the designated clinics for physical examinations is another exclusion criterion. In the Kharameh cohort study, all demographic information was collected by trained experts during face-to-face interviews. Also, clinical information was checked by trained doctors and recorded in electronic questionnaires. To collect the information of the participants, questionnaires related to the study of the PERSIAN cohort, which were previously validated, were used. To conduct the present study, information related to demographic characteristics such as age, sex, education level, socioeconomic status (SES), marital status, and body mass index (BMI) was used, as well as behavioral habits such as smoking, drinking, and using hookahs or opium. The SES was calculated using the variables related to an individual's property and the principal component analysis (PCA) method. To check the physical activity status of the individuals, the metabolic equivalent of task (MET) index was calculated. This index shows the ratio of the individual's physical activity metabolism rate to the individual's metabolism rate while sitting and resting ( 53 ). Therefore, a calorie is equal to one kilocalorie of energy consumed per kilogram of body weight at rest ( 54 ). History of smoking, opium, and alcohol usage was recorded. The participants were asked if they are active current smoker, or use opium derived products or alcohol frequently during a week. To check the levels of low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, and cholesterol of the individuals, their blood samples, which were collected at the beginning of the Kharameh cohort study, were used. For blood sampling, individuals were advised to refrain from strenuous physical activity for three days before and also to refrain from eating and drinking (except water), smoking, and alcohol consumption for 12 hours before. LDL, HDL, triglyceride, and cholesterol tests were done by the Mindray BS-380 machine, made in Japan, and using the Pars kit. Triglycerides above 150 mg/dL are considered high and abnormal triglycerides, and total cholesterol above 200 mg/dL is considered high cholesterol. Furthermore, LDL levels greater than 130 mg/dL are considered high, while HDL levels less than 40 for men and less than 50 for women are considered low HDL ( 20 , 55 ). Statistical analysis: Quantitative data were described with mean and standard deviation, and qualitative data with the frequency and percentage. A chi-square statistical test and Fisher's exact test were performed to evaluate the difference between the levels of qualitative variables, and a t-test was also performed to evaluate the difference between the lipid profile levels between opium users and non-users. After checking the normality of quantitative variables with the Kolmogorov-Smirnov statistical test, we used Pearson's correlation coefficient to check the correlation between the lipid profile of individuals with quantitative variables. We also used simple and multiple linear regression to identify the factors related to the increase or decrease in the lipid profile levels of individuals. All the variables with a p value less than 0.2 in simple linear regression were entered into multiple regressions. The significance level for all tests was considered less than 0.05, and all analyses were performed in STATA version 12 software. Declarations Ethics approval and consent to participate PERSIAN Cohort Study is being performed in 18 geographical regions of Iran. PERSIAN Cohort Study was approved by the ethics committees of the Ministry of Health and Medical Education Shiraz is one of the regions. This study is in agreement with the Helsinki declaration and Iranian national guidelines for ethics in research. (Reference number: IR.SUMS.REC.1400.612), and informed written consent was obtained from all participants. Consent for publication Written informed consent for publication was obtained from each participant. Competing interests The authors declare that there is no conflict of interest. Funding This research received no external funding. Authors’ contributions NB, and MGH did the research, wrote the manuscript, and contributed to data collection. 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The American journal of drug and alcohol abuse. 2008;34(4):383-8. Rahimi N, Gozashti MH, Najafipour H, Shokoohi M, Marefati H. Potential effect of opium consumption on controlling diabetes and some cardiovascular risk factors in diabetic patients. Addiction & health. 2014;6(1-2):1. Santolaria-Fernández FJ, Gómez-Sirvent J, González-Reimers CE, Batista-López J, Jorge-Hernández J, Rodríguez-Moreno F, et al. Nutritional assessment of drug addicts. Drug and Alcohol Dependence. 1995;38(1):11-8. GINSBERG H, Olefsky J, FARQUHAR JW, REAVEN GM. Moderate ethanol ingestion and plasma triglyceride levels: a study in normal and hypertriglyceridemic persons. Annals of Internal Medicine. 1974;80(2):143-9. Klop B, do Rego AT, Cabezas MC. Alcohol and plasma triglycerides. Current opinion in lipidology. 2013;24(4):321-6. Hodson L, Banerjee R, Rial B, Arlt W, Adiels M, Boren J, et al. Menopausal status and abdominal obesity are significant determinants of hepatic lipid metabolism in women. Journal of the American Heart Association. 2015;4(10):e002258. Greenfield MS, Kraemer F, Tobey T, Reaven G. Effect of age on plasma triglyceride concentrations in man. Metabolism. 1980;29(11):1095-9. Feng L, Nian S, Tong Z, Zhu Y, Li Y, Zhang C, et al. Age-related trends in lipid levels: a large-scale cross-sectional study of the general Chinese population. BMJ open. 2020;10(3):e034226. Upmeier E, Lavonius S, Heinonen P, Viitanen M, Isoaho H, Arve S, et al. Longitudinal changes in serum lipids in older people the Turku elderly study 1991–2006. Age and ageing. 2011;40(2):280-3. Ettinger WH, Wahl P, Kuller L, Bush T, Tracy R, Manolio T, et al. Lipoprotein lipids in older people. Results from the Cardiovascular Health Study. The CHS Collaborative Research Group. Circulation. 1992;86(3):858-69. Ferrara A, Barrett-Connor E, Shan J. Total, LDL, and HDL cholesterol decrease with age in older men and women: The Rancho Bernardo Study 1984–1994. Circulation. 1997;96(1):37-43. Weijenberg MP, Feskens E, Kromhout D. Age-related changes in total and high-density-lipoprotein cholesterol in elderly Dutch men. American journal of public health. 1996;86(6):798-803. Heiss G, Tamir I, Davis CE, Tyroler HA, Rifkand B, Schonfeld G, et al. Lipoprotein-cholesterol distributions in selected North American populations: the lipid research clinics program prevalence study. Circulation. 1980;61(2):302-15. MOULOPOULOS SD, ADAMOPOULOS PN, DIAMANTOPOULOS EI, NANAS SN, ANTHOPOULOS LN, ILIADI-ALEXANDRO M. CORONARY HEART DISEASE RISK FACTORS IN A RANDOM SAMPLE OF ATHENIAN ADULTS THE ATHENS STUDY. American journal of epidemiology. 1987;126(5):882-92. Brien SE, Ronksley PE, Turner BJ, Mukamal KJ, Ghali WA. Effect of alcohol consumption on biological markers associated with risk of coronary heart disease: systematic review and meta-analysis of interventional studies. Bmj. 2011;342. Nova E, San Mauro-Martín I, Díaz-Prieto LE, Marcos A. Wine and beer within a moderate alcohol intake is associated with higher levels of HDL-c and adiponectin. Nutrition Research. 2019;63:42-50. Esteghamati A, Khalilzadeh O, Rashidi A, Meysamie A, Haghazali M, Abbasi M, et al. Association between physical activity and metabolic syndrome in Iranian adults: national surveillance of risk factors of noncommunicable diseases (SuRFNCD-2007). Metabolism. 2009;58(9):1347-55. Wen CP, Wai JPM, Tsai MK, Yang YC, Cheng TYD, Lee M-C, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. The lancet. 2011;378(9798):1244-53. Baeradeh N, Ghoddusi Johari M, Moftakhar L, Rezaeianzadeh R, Hosseini SV, Rezaianzadeh AJBCD. The prevalence and predictors of cardiovascular diseases in Kharameh cohort study: a population-based study on 10,663 people in southern Iran. 2022;22(1):1-12. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2526717","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":181190206,"identity":"18f6e3e8-2999-483e-bfdf-9f5ef452abcc","order_by":0,"name":"Najibullah Baeradeh","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Najibullah","middleName":"","lastName":"Baeradeh","suffix":""},{"id":181190207,"identity":"74e180ea-a76a-469e-8350-b164aa79c489","order_by":1,"name":"Seyed Vahid Hosseini","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Vahid","lastName":"Hosseini","suffix":""},{"id":181190208,"identity":"d5ed1985-563a-404b-a91e-f5e7a3bc474d","order_by":2,"name":"Leila Moftakhar","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Leila","middleName":"","lastName":"Moftakhar","suffix":""},{"id":181190209,"identity":"083b88d4-5794-4ad5-a977-17d3c22caf6b","order_by":3,"name":"Fatemeh Jafari","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"","lastName":"Jafari","suffix":""},{"id":181190210,"identity":"aac7c937-fbf8-453e-8610-0bce88809e4c","order_by":4,"name":"Masoumeh Ghoddusi Johari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYHACNiBiZmBgZj5g8IGBIYEULWwJhTNI08LAY/CZhxgtug3s1x58KLNOnN/OY7jZts0uj5+9gfHDxxzcWswO8JQbzjiXnrjhMFuxcW5bcrFkzwFmyZnb8GpJk+ZtO5y4gZl5G1ALc+KGGwlszLzEaJnfzGD+27Ktnhgt7MfAWhoOsxgYM4KsI6jlMA+bJNAvxkC/JBj2nDueOLPnYDN+vxxvfyYBDDHZ+f2HDxj8KKtO7GdvPvjhIx4tDMw8BggOIxuYbMCjHgTYHyBx/hBQPApGwSgYBSMSAABuhVOwI6dddQAAAABJRU5ErkJggg==","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Masoumeh","middleName":"Ghoddusi","lastName":"Johari","suffix":""},{"id":181190211,"identity":"fa0f92ec-a9d1-4810-a129-185ec5f3eb07","order_by":5,"name":"Abbas Rezaianzadeh","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Abbas","middleName":"","lastName":"Rezaianzadeh","suffix":""}],"badges":[],"createdAt":"2023-01-29 16:29:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2526717/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2526717/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":34028170,"identity":"adda5e09-4c4d-45fa-a9f3-83431891edad","added_by":"auto","created_at":"2023-03-09 16:14:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":57074,"visible":true,"origin":"","legend":"\u003cp\u003e· Normal range: cholesterol \u0026lt;170, triglyceride \u0026lt;100, LDL \u0026lt;100, HDL \u0026gt;50\u003c/p\u003e\n\u003cp\u003e· healthy as normal borderline: cholesterol 170-200, triglyceride 100-150, LDL 100-130, HDL 40-50\u003c/p\u003e\n\u003cp\u003e· abnormal borderline:cholesterol 200-230, triglyceride 150-200, LDL 130-160, HDL 30-40\u003c/p\u003e\n\u003cp\u003e· unhealthy: \u0026gt;230, triglyceride \u0026gt;200, LDL \u0026gt;160, HDL \u0026lt;30\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of different lipid profile levels in opium users and non-users in the population of 40 to 70 years of Kharameh\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2526717/v1/5ae40b143660d6990f2fa51c.png"},{"id":34027497,"identity":"be06fa1e-204f-4549-b0f2-e80377131cf3","added_by":"auto","created_at":"2023-03-09 16:06:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":233784,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A): Predictors of TG level based on the results of multiple linear regression in the population of 40 to 70 years of Kharameh\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(B): Predictors of Chol level based on the results of multiple linear regression in the population of 40 to 70 years of Kharameh\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(C): Predictors of LDL level based on the results of multiple linear regression in the population of 40 to 70 years of Kharameh\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(D): Predictors of HDL level based on the results of multiple linear regression in the population of 40 to 70 years of Kharameh\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2526717/v1/c57b9dd6180bf1156cb08d04.png"},{"id":47569242,"identity":"c4e25ab7-9ef5-49c6-b7ed-0f31f5626095","added_by":"auto","created_at":"2023-12-04 17:07:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":654095,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2526717/v1/aee747df-1dfb-4504-93e3-8c91bcbd7084.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Relationship between opium consumption and lipid profile in drug addicts and non-addicts on Kharameh cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDrug abuse is known as one of the most important health, medical, and social problems of this century (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Drug addiction is a serious threat to health in various communities, especially for young people (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). More than 62\u0026nbsp;million people worldwide use opiates for non-medical reasons, of which nearly 31\u0026nbsp;million use heroin and opium alone (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The prevalence of drug use varies around the world and in different countries, cultures, and occupations (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Opium has long been used in many south-central Asian countries, particularly Iran, Pakistan, Afghanistan, and India, as well as in some parts of South-East Asia (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Iran is one of the countries with a high share of addicts in the world, so it is estimated that about 4\u0026nbsp;million Iranians use opium regularly or occasionally (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). According to studies, the prevalence of opium use in Iran varies in different regions, and suffering has been reported between 8.9% and 24.7% (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). There are common and unscientific beliefs that opium consumption lowers serum lipids as well as prevents chronic diseases such as diabetes and cardiovascular disease (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), but most studies have shown that opium use increases the risk of acute myocardial infarction, atherosclerosis, and cardiovascular mortality (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Additionally, current evidence suggests that opium consumption is associated with an increased risk of laryngeal, lung (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), bladder (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), and upper gastrointestinal cancers (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is much disagreement about the effect of opium on lipid profiles. In one study, cholesterol and triglyceride levels were lower in opium users (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), whereas in Kahonji\u0026rsquo;s study, cholesterol, triglycerides, and LDL were higher in opium users compared to healthy individuals (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). We expect this study to provide more accurate information in this area so that scientific beliefs can be scientifically answered. Furthermore, this study was performed on a large scale, considering the role of confounding factors such as cigarettes, alcohol, and tobacco that can affect the relationship between opium and the lipid profile.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe present study was conducted on 10,663 individuals aged 40 to 70, with a mean age of 52.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22 years. The majority of participants were female (55.74%) and married (89%). The prevalence of opium use in the individuals under study was 16% (CI: 15.3\u0026ndash;16.7), and 25.35%, 5.1%, and 5.3% of the individuals under study used cigarettes, hookah, and alcohol, respectively (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Also, a statistically significant difference was seen in different levels of gender, occupation, education, SES, married status, BMI, smoking, alcohol, and hookah consumption between opium users and non-users (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDistribution of demographic characteristics among opium users and non-users in the population of 40 to 70 years of Kharameh\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClass\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUse opium(N%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-use opium(N%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4719(44.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1733(36.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2986(63.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5944(55.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73(1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5871(98.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5147(48.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e303(5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4844(94.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5516(51.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1503(27.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4013(72.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eMarried status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e216(2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(6.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e203(93.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9492(89.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1761(18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7731(81.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e896(8.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e870(97.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59(0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53(89.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eSocioeconomic status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2667(25.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e402(15.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2265(84.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2977(27.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e408(13.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2569(86.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2539(23.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e426(16.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2113(83.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2480(23.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e570(22.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1910(77.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5587(52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e677(12.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4910(87.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2676(25.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e551(20.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2125(79.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1136(10.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e324(28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e812(7148)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e702(6.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e185(26.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e517(73.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e562(5.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e69(12.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e493(87.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUse smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7594(95.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e366(4.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7594(95.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2703(25.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1440(53.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1263(47.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUse alcohol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10095(94.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1337(13.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8758(86.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e568(5.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e469(16.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99(17.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUse hookah\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10115(94.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1468(14.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8647(85.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e548(5.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e338(61.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e210(38.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnder weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e413(3.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e189(45.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e224(54.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3879(36.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e909(23.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2970(76.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4447(41.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e577(12.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3871(87.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1916(17.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e129(6.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1787(93.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe mean levels of triglycerides, cholesterol, LDL, and HDL of the individuals were 130.3\u0026thinsp;\u0026plusmn;\u0026thinsp;80.86, 186.75\u0026thinsp;\u0026plusmn;\u0026thinsp;41.7, 104.99\u0026thinsp;\u0026plusmn;\u0026thinsp;27.9, and 47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8 mg/dL, respectively. Also, a statistically significant difference was seen in the mean levels of HDL (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and cholesterol (P\u0026thinsp;=\u0026thinsp;0.04) between opium users and non-users (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDistribution of the mean levels of lipids among opium users and non-users in the population of 40 to 70 years of Kharameh\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUse opium (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-use opium (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.99\u0026thinsp;\u0026plusmn;\u0026thinsp;27.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.13\u0026thinsp;\u0026plusmn;\u0026thinsp;28.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105.31\u0026thinsp;\u0026plusmn;\u0026thinsp;27.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45.99\u0026thinsp;\u0026plusmn;\u0026thinsp;12.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.07\u0026thinsp;\u0026plusmn;\u0026thinsp;12.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e130.3\u0026thinsp;\u0026plusmn;\u0026thinsp;80.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132.22\u0026thinsp;\u0026plusmn;\u0026thinsp;87.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e129.99\u0026thinsp;\u0026plusmn;\u0026thinsp;79.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHOL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e186.75\u0026thinsp;\u0026plusmn;\u0026thinsp;41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e184.98\u0026thinsp;\u0026plusmn;\u0026thinsp;41.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e187.11\u0026thinsp;\u0026plusmn;\u0026thinsp;41.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cstrong\u003eLDL\u003c/strong\u003e: Low density lipid, \u003cstrong\u003eHDL\u003c/strong\u003e: High density lipid, \u003cstrong\u003eTG\u003c/strong\u003e: Triglyceride, \u003cstrong\u003eCHOL\u003c/strong\u003e: cholesterol\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAbout 15.06%, 20.3%, 12.81%, and 25.18% of opium users had abnormal levels of triglyceride, cholesterol, LDL, and HDL levels, respectively. Also, 13.34%, 13.94%, 3.72%, 5.38% had unhealthy levels of triglyceride, cholesterol, LDL, and HDL levels, respectively (Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003cp\u003eThe results of the correlation analysis showed that age (r=-0.02, P\u0026thinsp;=\u0026thinsp;0.029), BMI (r\u0026thinsp;=\u0026thinsp;0.0119, P\u0026thinsp;=\u0026thinsp;0.0001) and physical activity level (r=-0. 45, P\u0026thinsp;=\u0026thinsp;0.0001) had a statistically significant correlation with triglyceride level. BMI (r=-0.06, P\u0026thinsp;=\u0026thinsp;0.0001) and physical activity level (r=-0.02, P\u0026thinsp;=\u0026thinsp;0.0024) had a statistically significant correlation with cholesterol levels but age did not show a significant correlation (P\u0026thinsp;=\u0026thinsp;0.058) with cholesterol level. LDL level also showed a statistically significant correlation with BMI (r\u0026thinsp;=\u0026thinsp;0.06, P\u0026thinsp;=\u0026thinsp;0.0001) and physical activity level (r=-0.034, P\u0026thinsp;=\u0026thinsp;0.003), but it did not show a significant correlation with age (P\u0026thinsp;=\u0026thinsp;0.059). Age (r\u0026thinsp;=\u0026thinsp;0.062, P\u0026thinsp;=\u0026thinsp;0.0001), BMI (r\u0026thinsp;=\u0026thinsp;0.0619, P\u0026thinsp;=\u0026thinsp;0.0001), and physical activity level (r=-0.017, P\u0026thinsp;=\u0026thinsp;0.0001) had a statistically significant correlation with HDL level.\u003c/p\u003e\n\u003cp\u003eThe results of linear regression analysis also showed that alcohol consumption (\u0026beta;\u0026thinsp;=\u0026thinsp;12.2, P\u0026thinsp;=\u0026thinsp;0.001), and individuals with normal BMI (\u0026beta;\u0026thinsp;=\u0026thinsp;15.9, P\u0026thinsp;=\u0026thinsp;0.0001), overweight (\u0026beta;\u0026thinsp;=\u0026thinsp;29.4, P\u0026thinsp;=\u0026thinsp;0.0001), and obesity (\u0026beta;\u0026thinsp;=\u0026thinsp;36.5, P\u0026thinsp;=\u0026thinsp;0.0001), and residents of the urban (\u0026beta;\u0026thinsp;=\u0026thinsp;8.1, P\u0026thinsp;=\u0026thinsp;0.0001) had a significant relationship with high triglyceride levels. Also, not having a job (\u0026beta; = -4.4, P\u0026thinsp;=\u0026thinsp;0.015), age (\u0026beta; = -0.25, P\u0026thinsp;=\u0026thinsp;0.008), the individuals with level of moderate of SES (\u0026beta; = -4.7, P\u0026thinsp;=\u0026thinsp;0.03), the individuals with level of severe of physical activity (\u0026beta; = -8.7, P\u0026thinsp;=\u0026thinsp;0.001) and smoking (\u0026beta; = -7.16, P\u0026thinsp;=\u0026thinsp;0.001) had a statistically significant relationship with the lower level of triglycerides (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e(A)).\u003c/p\u003e\n\u003cp\u003eage (\u0026beta; = -0.14, P\u0026thinsp;=\u0026thinsp;0.004), individuals with normal BMI (\u0026beta;\u0026thinsp;=\u0026thinsp;6.27, P\u0026thinsp;=\u0026thinsp;0.004), overweight (\u0026beta;\u0026thinsp;=\u0026thinsp;9.5, P\u0026thinsp;=\u0026thinsp;0.0001), and obesity (\u0026beta;\u0026thinsp;=\u0026thinsp;10.5, P\u0026thinsp;=\u0026thinsp;0.0001), individuals with level of education of diploma (\u0026beta; = -2.92, P\u0026thinsp;=\u0026thinsp;0.003) and university (\u0026beta; = -2.98, P\u0026thinsp;=\u0026thinsp;0.03), and alcohol consumption (\u0026beta;\u0026thinsp;=\u0026thinsp;5.67, P\u0026thinsp;=\u0026thinsp;0.004) showed a statistically significant relationship with cholesterol level (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e(B)).\u003c/p\u003e\n\u003cp\u003eindividuals with normal BMI (\u0026beta;\u0026thinsp;=\u0026thinsp;5.26, P\u0026thinsp;=\u0026thinsp;0.0001), overweight (\u0026beta;\u0026thinsp;=\u0026thinsp;7.44, P\u0026thinsp;=\u0026thinsp;0.0001), and obesity (\u0026beta;\u0026thinsp;=\u0026thinsp;7.94, P\u0026thinsp;=\u0026thinsp;0.0001), and residents of the urban (\u0026beta;\u0026thinsp;=\u0026thinsp;7.7, P\u0026thinsp;=\u0026thinsp;0.0001) and age (\u0026beta; = -0.07, P\u0026thinsp;=\u0026thinsp;0.025) had a statistically significant relationship with LDL (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e(C). Also, individuals with normal BMI (\u0026beta;\u0026thinsp;=\u0026thinsp;5.55, P\u0026thinsp;=\u0026thinsp;0.0001), overweight (\u0026beta;\u0026thinsp;=\u0026thinsp;7.88, P\u0026thinsp;=\u0026thinsp;0.0001), and obesity (\u0026beta;\u0026thinsp;=\u0026thinsp;8.3, P\u0026thinsp;=\u0026thinsp;0.0001), and residents of the urban (\u0026beta;\u0026thinsp;=\u0026thinsp;8.2, P\u0026thinsp;=\u0026thinsp;0.0001), alcohol use (\u0026beta;\u0026thinsp;=\u0026thinsp;2.82, P\u0026thinsp;=\u0026thinsp;0.03), age (\u0026beta; = -0.08, P\u0026thinsp;=\u0026thinsp;0.013), individuals with level of education of university (\u0026beta; = -2.39, P\u0026thinsp;=\u0026thinsp;0.012), diploma (\u0026beta; = -2.1, P\u0026thinsp;=\u0026thinsp;0.002) and secondary (\u0026beta; = -3.84, P\u0026thinsp;=\u0026thinsp;0.0009) showed a statistically significant relationship with the level of HDL (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e(D)).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOpium abuse is common in West Asia and Iran due to the common beliefs among people about the effects of prevention and treatment of diseases. Also, conflicting results regarding the effects of opium consumption on lipid profiles have been reported. Therefore, in this cross-sectional study with a large sample size obtained from detailed cohort data, we examined the relationship between opium and lipid profile.\u003c/p\u003e \u003cp\u003eThe findings of our study showed that the prevalence of opium use is 16%, which is more than the study of Fallahzadeh et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and in line with the results of the cohort studies conducted in the north (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) and lower than south of Iran (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a study conducted in India, the prevalence of opium use in men was 5.76%, which was lower compared to our results (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). One of the reasons for the high prevalence of drug use in different parts of Iran and in this study can be attributed to its neighborhood with Afghanistan and the fact that Kharameh is on the way to transport opium into the country from the eastern and southern borders. Therefore, people have more access to this type of substance (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), and it may also be due to the belief that opium use has a preventive role in disease control (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In our study, the prevalence of smoking (25.3%) was almost twice the average in Iran, so that in the meta-analysis study, Mooszadeh et al. estimated the prevalence to be 13.9% (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In this study, the prevalence of smoking was higher than in the countries of Pakistan (19.4%), Oman (7%), Kuwait (17%), Saudi Arabia (11.6%), and America (20.6%), and was in line with the results of the study conducted in Italy (26.2%) (\u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlcohol consumption in the population under study is nearly one-third that of Iran. In the meta-analysis study conducted by Chegni et al., the prevalence of alcohol consumption in Iran was reported at 13% (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). In a study conducted in India, the prevalence of alcohol consumption in men was reported to be 35% (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), which is high compared to our study. The low prevalence of alcohol consumption in our study could be due to the following reasons: First, due to religious beliefs, Iranian society consumes less alcohol than some other countries; second, alcohol consumption is a crime in Iran, both because of the crime it is and because of the social stigma it carries.\u003c/p\u003e \u003cp\u003ePrevious studies have shown that cholesterol levels in opium users are lower than those of normal people. Fatemi et al. showed in their study that the cholesterol level of opium addicts with a BMI between 18 and 25 was 20 mg lower than that of healthy people (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In our study, cholesterol was lower in opium users than in healthy people. In line with our study, in a meta-analysis study that was conducted on the lipid profile of diabetic patients, it has been shown that opium use reduces cholesterol levels (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, in the following studies, no significant results have been obtained regarding the relationship between opium and reducing cholesterol levels. In Hosseini et al.\u0026rsquo;s study, they showed weak evidence of the relationship (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), and in Rezvanfar et al.\u0026rsquo;s study, although cholesterol levels were lower in opium users, the results were not significant (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In these studies, although the cholesterol levels were lower in the consumer group, the results were not significant, which may be due to the small sample size in these studies.\u003c/p\u003e \u003cp\u003eThe findings of our study showed that the consumption of opium has a negative effect on HDL levels and that it decreases with alcohol. In line with our study, in the study of Asadi Karam et al., they have shown that HDL levels in opium users are lower than healthy people (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). However, some studies have shown that opium consumption has no significant effect on HDL (\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe results of our study showed that opium is not related to LDL or triglycerides, which is in line with the results of other studies (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), but in some studies it has been shown that triglycerides are lower in opium users (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). On the other hand, Rahimi et al. reported weak evidence of the effect of opium on lowering LDL levels in their study (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). In general, low levels of some lipids in people who use opium may be due to malnutrition associated with a loss of appetite in these people. In studies, it has been shown that drug abuse significantly changes the diet and addicts have a poor nutritional status, and it has also been shown that the weight of addicts is lower than the average weight of the population in terms of gender and height (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). In our study, there was a significant difference in BMI between opium users and healthy people, which can be high for the mentioned reason.\u003c/p\u003e \u003cp\u003eSome of the findings in our study, as well as other studies, may suggest anti-lipid effects of opium, but they should be interpreted with caution because many factors other than opium use can affect lipid profiles, which may be different between addicts and non-addicts, and it is difficult to control them in a cross-sectional study. The results of the multivariate analysis of our study showed that alcohol consumption and high BMI increase the level of triglycerides, while not having a job, old age, and university education decrease it. In other studies, the role of ethanol in increasing triglyceride levels has been mentioned, so that in a clinical trial study that was conducted on healthy people and people with hypertriglyceridemia, it was shown that people who drank moderate amounts of ethanol three times a day, saw their plasma triglyceride levels increase significantly (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), which is in line with the results of our study. It has been mentioned in other studies that alcohol increases triglyceride levels (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Previous studies in line with this study have shown that triglycerides are significantly higher in obese people (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). In our study, age was shown as a protective factor for triglyceride levels, in contrast to other studies, which have shown that age plays a role as a risk factor and causes an increase in triglyceride levels (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). However, in a cohort study conducted for 15 years on people over 70 years old in Finland, no significant relationship between age and triglycerides was observed (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). One of the reasons for observing the inverse relationship between age and triglyceride levels in our study may be because with increasing age, the incidence of non-communicable diseases, especially cardiovascular (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e), and hyperlipidemia (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e), increases, which causes people to change their lifestyle or take triglyceride-lowering drugs. Therefore, the correlations obtained in cross-sectional studies should be interpreted with caution.\u003c/p\u003e \u003cp\u003eThe results of multivariate analysis also showed that age, body mass index, diploma and university levels of education, and alcohol consumption increase cholesterol levels. Studies have shown conflicting results regarding the relationship between age and cholesterol. Age raises cholesterol in some studies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), but lowers it in others (\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). In some studies, age increases cholesterol (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and in others it decreases (\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). In these studies, it has been shown that cholesterol increases in men up to the age of 65 and in women up to the age of 75 and then decreases (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). The difference observed among the studies may be due to the fact that the age range studied in each study is different from the other because, according to the studies, cholesterol in the elderly decreases with increasing age and increases in the middle-aged with increasing age, as mentioned above, and in our study, most of the people were middle-aged. Previous studies have also shown that alcohol consumption increases cholesterol levels (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e), which is consistent with the findings of our study.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eContrary to the beliefs that there are about the effects of opium on reducing lipid profile levels, in our study, there was no correlation between LDL, triglycerides and opium consumption. The levels of HDL (good cholesterol that prevents heart attacks) were lower in addicted people than in healthy people. Although in this study the level of cholesterol was lower in addicts, in general, due to the known side effects of opium on non-communicable diseases, especially cancers, the use of opium is not recommended to reduce lipid profile.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe current study is a cross-sectional study that was conducted using the data of the Kharameh cohort study in southern Iran with the aim of determining the status of the lipid profile in opium users. In this study, 10,663 individuals aged 40 to 70 years have been examined. The Kharameh cohort study is a part of the large Prospective Epidemiological Research Studies in Iran (PERSIAN) that is being conducted in 18 regions of Iran. The inclusion criteria in this study include: age between 40 and 70 years, living in Kharameh city for at least 9 months, and having Iranian nationality. Exclusion criteria include mental disorders and mental retardation. Unwillingness to participate in the study and not attending the designated clinics for physical examinations is another exclusion criterion.\u003c/p\u003e \u003cp\u003eIn the Kharameh cohort study, all demographic information was collected by trained experts during face-to-face interviews. Also, clinical information was checked by trained doctors and recorded in electronic questionnaires. To collect the information of the participants, questionnaires related to the study of the PERSIAN cohort, which were previously validated, were used. To conduct the present study, information related to demographic characteristics such as age, sex, education level, socioeconomic status (SES), marital status, and body mass index (BMI) was used, as well as behavioral habits such as smoking, drinking, and using hookahs or opium. The SES was calculated using the variables related to an individual's property and the principal component analysis (PCA) method. To check the physical activity status of the individuals, the metabolic equivalent of task (MET) index was calculated. This index shows the ratio of the individual's physical activity metabolism rate to the individual's metabolism rate while sitting and resting (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Therefore, a calorie is equal to one kilocalorie of energy consumed per kilogram of body weight at rest (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). History of smoking, opium, and alcohol usage was recorded. The participants were asked if they are active current smoker, or use opium derived products or alcohol frequently during a week.\u003c/p\u003e \u003cp\u003eTo check the levels of low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, and cholesterol of the individuals, their blood samples, which were collected at the beginning of the Kharameh cohort study, were used. For blood sampling, individuals were advised to refrain from strenuous physical activity for three days before and also to refrain from eating and drinking (except water), smoking, and alcohol consumption for 12 hours before. LDL, HDL, triglyceride, and cholesterol tests were done by the Mindray BS-380 machine, made in Japan, and using the Pars kit. Triglycerides above 150 mg/dL are considered high and abnormal triglycerides, and total cholesterol above 200 mg/dL is considered high cholesterol. Furthermore, LDL levels greater than 130 mg/dL are considered high, while HDL levels less than 40 for men and less than 50 for women are considered low HDL (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eQuantitative data were described with mean and standard deviation, and qualitative data with the frequency and percentage. A chi-square statistical test and Fisher's exact test were performed to evaluate the difference between the levels of qualitative variables, and a t-test was also performed to evaluate the difference between the lipid profile levels between opium users and non-users. After checking the normality of quantitative variables with the Kolmogorov-Smirnov statistical test, we used Pearson's correlation coefficient to check the correlation between the lipid profile of individuals with quantitative variables. We also used simple and multiple linear regression to identify the factors related to the increase or decrease in the lipid profile levels of individuals. All the variables with a p value less than 0.2 in simple linear regression were entered into multiple regressions. The significance level for all tests was considered less than 0.05, and all analyses were performed in STATA version 12 software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePERSIAN Cohort Study is being performed in 18 geographical regions of Iran. PERSIAN Cohort Study was approved by the ethics committees of the Ministry of Health and Medical Education Shiraz is one of the regions. This study is in agreement with the Helsinki declaration and Iranian national guidelines for ethics in research. (Reference number: IR.SUMS.REC.1400.612), and informed written consent was obtained from all participants.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication was obtained from each participant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNB, and MGH did the research, wrote the manuscript, and contributed to data collection. AR and VH critically reviewed the manuscript and approved the final version. LM and FJ did the research, analyzed the data, and critically reviewed and edited the manuscript. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSinger M. Drugs and development: the global impact of drug use and trafficking on social and economic development. International Journal of Drug Policy. 2008;19(6):467-78.\u003c/li\u003e\n\u003cli\u003eDas P, Horton R. The global drug problem: change but not progression. The Lancet. 2019;394(10208):1488-90.\u003c/li\u003e\n\u003cli\u003eAttari MA, Asgary S, Shahrokhi S, Naderi GA, Shariatirad S. Cannabis and opium abuse patterns and their associated complications in a sample of young Iranians. 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Age-related trends in lipid levels: a large-scale cross-sectional study of the general Chinese population. BMJ open. 2020;10(3):e034226.\u003c/li\u003e\n\u003cli\u003eUpmeier E, Lavonius S, Heinonen P, Viitanen M, Isoaho H, Arve S, et al. Longitudinal changes in serum lipids in older people the Turku elderly study 1991–2006. Age and ageing. 2011;40(2):280-3.\u003c/li\u003e\n\u003cli\u003eEttinger WH, Wahl P, Kuller L, Bush T, Tracy R, Manolio T, et al. Lipoprotein lipids in older people. Results from the Cardiovascular Health Study. The CHS Collaborative Research Group. Circulation. 1992;86(3):858-69.\u003c/li\u003e\n\u003cli\u003eFerrara A, Barrett-Connor E, Shan J. Total, LDL, and HDL cholesterol decrease with age in older men and women: The Rancho Bernardo Study 1984–1994. Circulation. 1997;96(1):37-43.\u003c/li\u003e\n\u003cli\u003eWeijenberg MP, Feskens E, Kromhout D. Age-related changes in total and high-density-lipoprotein cholesterol in elderly Dutch men. American journal of public health. 1996;86(6):798-803.\u003c/li\u003e\n\u003cli\u003eHeiss G, Tamir I, Davis CE, Tyroler HA, Rifkand B, Schonfeld G, et al. Lipoprotein-cholesterol distributions in selected North American populations: the lipid research clinics program prevalence study. Circulation. 1980;61(2):302-15.\u003c/li\u003e\n\u003cli\u003eMOULOPOULOS SD, ADAMOPOULOS PN, DIAMANTOPOULOS EI, NANAS SN, ANTHOPOULOS LN, ILIADI-ALEXANDRO M. CORONARY HEART DISEASE RISK FACTORS IN A RANDOM SAMPLE OF ATHENIAN ADULTS THE ATHENS STUDY. American journal of epidemiology. 1987;126(5):882-92.\u003c/li\u003e\n\u003cli\u003eBrien SE, Ronksley PE, Turner BJ, Mukamal KJ, Ghali WA. Effect of alcohol consumption on biological markers associated with risk of coronary heart disease: systematic review and meta-analysis of interventional studies. Bmj. 2011;342.\u003c/li\u003e\n\u003cli\u003eNova E, San Mauro-Martín I, Díaz-Prieto LE, Marcos A. Wine and beer within a moderate alcohol intake is associated with higher levels of HDL-c and adiponectin. Nutrition Research. 2019;63:42-50.\u003c/li\u003e\n\u003cli\u003eEsteghamati A, Khalilzadeh O, Rashidi A, Meysamie A, Haghazali M, Abbasi M, et al. Association between physical activity and metabolic syndrome in Iranian adults: national surveillance of risk factors of noncommunicable diseases (SuRFNCD-2007). Metabolism. 2009;58(9):1347-55.\u003c/li\u003e\n\u003cli\u003eWen CP, Wai JPM, Tsai MK, Yang YC, Cheng TYD, Lee M-C, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. The lancet. 2011;378(9798):1244-53.\u003c/li\u003e\n\u003cli\u003eBaeradeh N, Ghoddusi Johari M, Moftakhar L, Rezaeianzadeh R, Hosseini SV, Rezaianzadeh AJBCD. The prevalence and predictors of cardiovascular diseases in Kharameh cohort study: a population-based study on 10,663 people in southern Iran. 2022;22(1):1-12.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Opium use, Lipid profile, Persian cohort, Prevalence","lastPublishedDoi":"10.21203/rs.3.rs-2526717/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2526717/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDrug abuse is known as one of the most important health, medical, and social problems. Furthermore, this study was performed to evaluate the relationship between opium and lipid profiles.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted on 10,663 individuals, aged 40 to 70, living in Kharameh (south of Iran). Demographic information, lipid profile, and the history of use of opium, alcohol, and cigarettes in participants were investigated. To check the lipid profile, blood samples were taken from all participants. The prevalence of opium use was calculated. Linear regression was used to examine the relationship between opium use and the lipid profile of an individual. A significance level of 5% was considered for the tests, and STATA software was used for analysis.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eAmong the 10,663 participants in the study with a mean age of 52.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22 years, about 55.7% were women. The prevalence of opium use among the participants in the study was estimated at 16%. Multiple linear regression results revealed no statistically significant relationship between opium use and lipid profile.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eContrary to the beliefs that there are about the effects of opium on reducing lipid profile levels, in our study, there was no correlation between LDL, triglycerides and opium consumption.\u003c/p\u003e","manuscriptTitle":"Relationship between opium consumption and lipid profile in drug addicts and non-addicts on Kharameh cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-09 16:06:34","doi":"10.21203/rs.3.rs-2526717/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3fa0dbea-dde5-46e7-8292-d941719aa34a","owner":[],"postedDate":"March 9th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":19700918,"name":"Health sciences/Medical research"},{"id":19700919,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2023-12-04T16:59:42+00:00","versionOfRecord":[],"versionCreatedAt":"2023-03-09 16:06:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2526717","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2526717","identity":"rs-2526717","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}