Personal, Familial and Environmental Determinants of Drug Abuse: A Causal-Comparative Study

Aims: Two purposes were followed in this study: 1) comparing case and control group in eight factors separately and 2) performing a multivariate analysis for identifying risk and protective factors in relation to drug abuse. Methods: A casual-comparative study was conducted to investigate the study goals. Fifty Cases in a convenient sampling of addicts referring to addiction withdrawal centers and fifty eligible controls (recruited in a randomly sampling) were identified. One-sample independent T-Test for a univariate and Logistic regression model for a multivariate was conducted. Results: Univariate analysis: addicted group compared with control group, in terms of aggression, easy access to drugs and depression had higher scores and of other factors (self-esteem, religious affiliation, socioeconomic status, family environment and responsibility) cases had lower scores (p<0.05). Multivariate analysis: Easy access to drugs and depression identified as risk factors (OR>1) and high self-esteem, family socioeconomic status and responsibility as protective (OR<1). Conclusions: Addiction is a multivariate phenomenon and before any intervention, we have to consider personal, familial and environmental factors and separate subjects by them. We can’t give all of addicts the same prescription and follow a drug therapy approach to treat them. Any addict has a unique profile that should be taken into consideration.


Introduction
Nowadays, drug addiction is one of the serious social problems in many parts of the world which has a high priority for health managers and decision makers. Drug addiction, not only have negative consequences for individuals, but also threat welfare, political stability, economic and social structure of countries (Dostiyan, Bahmani, Azami, & Ali Akbar, 2013). The trafficking (e.g. annual flow of 430-450 tons of heroin into the global heroin market: NUODC, 2014) and abuse of illicit drugs inflict tremendous harm upon individuals, families, and communities throughout the world (Shannon, 2010). Despite a nearly one century efforts to prevent and control of this costly social problem, the number of addicted people is increasing (Rahmdel, 2003). According to the United Nation Organization, there were 220 million of drug addicts in the world by 2005 (Geramian, Akhavan, Gharaat, Tehrani, & Farajzadegan, 2012). National and international reports show that Iran has the highest rates of substance addiction in the world as this population is growing continuously (KeyvanAra et al., 2008;Kheje & Dadgar, 2013;Mohammadi & Shyany, 2008;Mokri, 2002; United Nations Office on Drugs and Crime [UNODC], 2013). Evidence shows that there are about 2 million drug addicts and 6 million recreational addicts in Iran (KeyvanAra, Kiyanpour, & Jianpour, 2008). Based on another report, 1300,000 addicts (9% women and 91% men) have been identified in Iran that mean age of 45% of them is less than 29 and 30% are between 30-39 years old. In this population, Opium with its derivatives and Glass are the most common consumed drugs, respectively (Iran Drug Control Headquarters [IDCH], 2014).
factors that determine behavior of people can vary from person to person and also may change over time.
To our knowledge, there are many models for understanding and treating addicted persons prior to 1600 AD (e.g. moral, criminal and preternatural); 1600 to 1900 AD (e.g. epidemic and illness); and models appearing since 1900 AD (e.g. personality disorders, learning, Comorbidity, genetic, recovery, biomedical, bio psychosocial and so on) (Miller, 2013). According to this evidence, there is no single explanation of addiction, but it is clear that a number of factors must be taken into account in explaining addiction. These factors lie within three major domains: biological, psychological and social factors (McMurran, 2005).

Method
A casual-comparative study was conducted among 100 participants in Shahrekord city (in the west of Iran) during 2013-2014. Fifty Cases were selected by using convenient sampling among addicts who attended to addiction withdrawal centers and had a history of addiction. Also, simple random sampling was used for selection of fifty eligible controls. The two groups were matched by age and residence.
Data collection tools In order to compare the case and control groups, investigator-constructed questionnaire was used. It was constructed based on eight scales, including religious belongings, F-SES, family environment, easy access to drugs responsibility, Coopersmith self-esteem, Ahvaz aggression, and Beck Depression. This questionnaire has 59 item with eigh domains, including self-esteem (10 item), aggression (10 item), religious belongings (10 item), family socioeconomic status (7 item), family environment (7 item), easy access to drugs (4 item), depression (7 item) and responsibility (6 item). All of the items were answered on a five point Likert scale ranging from strongly agree to strongly disagree. Exploratory factor analysis (EFA) was used to determine construct reliability of the questionnaire. Prior to performing EFA, suitability of data for factor analysis was assessed. The Kaiser-Meyer-Oklin values are presented in Table1, exceeding the recommended value of 0.6 and the Barlett's Tests of Sphericity (Pallant, 2010) reached statistical significance, supporting the factor ability of the correlation matrix. Principal components analysis revealed the presence of one component with suggested items in each scale. Explained percent of the variance ofeach component is presented in Table1. In order of hardship in access to addicted subjects for researchers, data for reliability of structured tools were only gathered through a sample (n= 60) of general population. To verify the accuracy of respondents answering to the questions, correlations between factors were also calculated ( Table 2).

Data Analysis
In bivariate analysis, After the assumptions of homogeneity of variances and normality for all variables were met, Chi square for the comparison of proportions and independent-sample T-Test for comparing differences between www.ccsenet.org/gjhs Global Journal of Health Science Vol. 7, No. 4;2015 groups) were used.. The adjusted association of all proposed factors on the youth's tendency to drug abuse and addiction were examined by multiple logistic regression model. The following independent variables were entered into the model: self-esteem, aggression, religious affiliation, family socioeconomic status, family environment¸ easy access to drugs, responsibility and depression. Level of confidence interval was 95%. Statistical Package for the Social Sciences (SPSS) was used to the data analysis.

Results
Mean age of the participants in the case group was 27 (SD= 3.16) years with a range of 18 to 33 years and in the control group was 27.4 (SD=3.95) years with a range of 16 to 32 years. The mean of addicted history was 8 (SD=4.09) years with a range of 2 to 5 years As Table 3 shows, there was a significant difference in education levels of two groups. Numbers of subjects from urban and rural areas was nearly equal. In the case group, 36% of the participants did not respond to the drug used question. In the bivariate analysis, the case and control groups' status in the eight factors were examined separately. An independent-sample T-Test was conducted to compare the scores of eight factors for the case and control groups. As Table 4 shows, there weresignificant differences between the two groups in the all factors. The magnitude of the differences in the mean of each factor is reported (eta squared).
. The model as a whole explained the variance in person status between 51.2% (Cox and Snell R square) to 70.8% (Nagelkerke R squared) of, and correctly classified 87% of cases (sensitivity and specificity of the model was 82% and 89.6% respectively). As shown in Table 5, the independent variables which made a unique statistically significant contribution to the model were Self-esteem, family socioeconomic status, easy access to drugs, responsibility and depression.
The strongest predictor was easy access to drugs variable, OR=1.36 (95% CI, 1.12-1.64). This indicated that participants in the case group were 1.36 times more likely to report an access to drugs than those who were in the control group, after adjusting for other factors in the model. The odds ratio of 1.34 for depression, indicating that for every additional score of depression, participants in the case group were 1.34 times more likely to have had depression than the control group, adjusting for other factors in the model. Self-esteem (OR=0.777), family socioeconomic status (OR=0.711) and responsibility (OR=0.671) indicates that the control group had more scores than the case group. Remained variables (aggression, religious affiliation and family environment) had no significant effects in the model (see Table 5).

Discussion
The present study was designed to determine the effect of eight factors on young adults' tendency to drug abuse and addiction. Firstly, the case and control groups were compared by the eight factors separately and then a multivariate analysis was used to identify the risk and protective factors.
The results of bivariate analysis showed that the case group had a higher scores than the control group in terms of some factors as aggression, easy access to drugs and depression. Also, in terms of other factors, including self-esteem, religious affiliation, socioeconomic status, family environment and responsibility the cases had www.ccsenet.org/gjhs Global Journal of Health Science Vol. 7, No. 4;2015 lower scores. These findings are consistet with most conducted research (Bagheri et al., 2010;Baghiani Moghadam et al., 2008;Baumeister et al., 2003;Benjet et al., 2007;Bry, McKeon, & Pandina, 1982;Dew et al., 2008;Farhadinasab et al., 2008;Gryczynski & Ward, 2011;Jessor, 1987;Newcomb, Maddahian, & Bentler, 1986;Van Hasselt et al., 1993;Wills, 1994;Zargar et al., 2008). Eta squared coefficients showed that the weight of each factor was different as the case and control groups had the greatest and least difference in self-esteem and religious affiliation, respectively (see Table 2). Therfore, a combined model of all factors was designed to identify the risk and protective factors that predispose the persons to become addicted or not. According to the eight factors which entered into the logistic regression model, easy access to drugs and depression identified as the risk factors. These results are consistent with findings of other research (Baghiani Moghadam et al., 2008;mohhamadi et al., 2011;Van Hasselt et al., 1993). High self-esteem, family socioeconomic status and responsibility identified as the protective factors. In contrast to these findings, Gerrard et al., and Sharp & Getzidentified high self-esteem as a risk factor, whereas findings of Bagheri et al. and Benjet et al. confirmed high socioeconomic status as a protective. In the literature, it was not any findings on responsibility.
Also, as the results showed the family environment, religious affiliation and aggression had no significant effect on attitudes to addiction. This finding can be explained as follows: Firstly, an addiction phenomenon among Iranian families is a taboo that they generally have a negative view toward it. Secondly, religious affiliation among the studied target population, especially in Shahrekord city, is high and they are committed to such beliefs. Finally, other variables in the model, including family environment and religious affiliation that had a negative correlation with aggression acted as a buffer and neutralize the effect of aggression.
Studies support the notion that self-aggression is linked with depression. Becker & Lesiak (Becker & Lesiak, 1977) found that severity of depression correlated with covert hostility, including guilt, resentment, irritability and suspicion, but not with overt hostility. Wolfersdorf and Kiefer (1998) showed that inpatients with depression compared with healthy controls had increased levels of inhibited aggression and covert hostility, but did not express the aggression. Goldman and Haaga (Goldman & Haaga, 1995) in a self-report of outpatients with depression found that they hadincreased anger, suppressed anger and fear of expressing anger compared with controls without depression. Brody and colleagues (Brody, Haaga, Kirk, & Solomon, 1999) found more suppressed anger and increased fear of expressing anger in individuals recovered from depression than in healthy controls that could damage their relationships. All of these studies suggested that anger is a prominent feature of depression. As noted above, both expressed and suppressed anger can be a source of conflict and become self-directed.

Conclusion
Totally, the results of present study showed that personal, familial and environmental factors have to be considered before any intervention and subjects be separated by them. Any addict has a unique profile that should be taken into consideration. All of them can not take the same prescription and follow a drug therapy for treatment.
The findings should be considered in the light of several limitations. Firstly, this study only examined the voluntary addicts who attended to addiction withdrawal centers, not all addicts around Shahrekord city. Secondly, our statistical analyses were based on self-report data not diagnostic tests. Thirdly, because of limited sample size (n=100), any generalization should be done cautiously. It is required that results to repeat in different and broader contexts.