The use of the substance in women outside religious, cultural or medicinal contexts has been seen in India for centuries. The use of substance outside these contexts has not been recognised until recently in India. Even the large national-level study of substance use in India did not include females in their study. Instances of women using substances have emerged in literature in India from around the 1980s. Recently, there are several studies done on female substance use at the national level; regional studies and the hospital-level data on the use of substances by women have also become available. The available studies have some methodological limitations, but the broad findings, which have emerged, have been described below.

The National Family Household Survey-3, which screened a representative sample of 124,385 for use of alcohol and tobacco throughout India, showed that 2 % women aged 15–49 years use alcohol and 11 % of them use tobacco. Among those who use alcohol, 15 % drink alcohol daily and 84 % once a week, or less than once a week. Among those who smoke, 1 % use smoking forms of tobacco and 8 % use smokeless forms. Around one-fourth of smokers report they smoke 10 or more cigarettes or bidis. Tobacco use was more prevalent than alcohol use in almost every state. All forms of substance use were more prevalent in rural, than in urban areas. Substance use decreased with increased level of education and income (NFHS-3). There was a change in the trend in the form of increased use of tobacco in National Family Health Survey-3, compared to National Family Health Survey-2, but the use of alcohol remained same. The National-level House to House Survey of 6,266 women in 25 states in India revealed that predominant substances used were alcohol (91.7 %), opioids (87.9 %) and tobacco (85.6 %) (Murthy et al. 2009). Another national-level survey of 1,865 women users by 110 NGOs showed that women who used substances were in their 20s or 30s, and married. The common substances used were alcohol, tobacco, opioids, sedatives and cannabis. Among users, 25 % had lifetime history and 24 % had been injecting in the previous month. The reasons for initiation of the substance use were due to childhood difficulty, peer influence, partner influence and stress (Murthy 2008).

A survey of 4,648 users in 14 cities found that 8 % of the users were women. These users were single, educated, employed and started using before 20 years of age. The common substances were opioid, alcohol, cannabis and minor tranquilisers. The reasons for initiation of the substance were influence of friends, spouse or partner, and stress and ‘tension’. Among them, 40 % were IDUs and were involved in unsafe practices, unprotected sex and drug peddling (Kumar 2002). The Gender, Alcohol and Culture: An International Study (GENACIS) assessed alcohol and other substance use across 5 districts of Karnataka among 1,464 females. Most females were middle aged, poorly educated (<6 years), married and earning less. Around one-third of the women users had hazardous drinking, more than a third had husbands who used alcohol and a tenth drank exclusively. Only about 6 % of female drank less than once in the last 12 months (Benegal et al. 2005). A study of 7,445 adult men and 6,919 adult women from South India found that the average consumption on typical drinking occasions, in both men and women, was five standard drinks (12 g of ethanol per drink) (Benegal et al. 2003). Another study in South India found that one-fifth of the people who frequented pubs on weekends were girls aged between 13 and 19 years in Bangalore city (Kumar and Sharma 2008).

There are very few national-level studies, particularly about substance use in children. Though majority of the studies on children have been done on inhalant use, literature is also available for other substance use. Majority of the data have been obtained from the regional studies from the metropolitan cities and from the hospital-based studies. The regional studies are mostly on substance use in street children.

The National Household Survey on Drug Abuse surveyed 40,697 males of whom 8,587 were children (aged 12–18 years). Of these, 3.8 % were using alcohol, 0.6 % were cannabis, and 0.2 % were using opiates (Ray et al. 2004).

In a study of 300 street child labourers in slums of Surat, it was observed that 135 (45 %) used substances. The substances used were smoking tobacco, followed by chewing tobacco, snuff, cannabis and opioids (Bansal and Banerjee 1993). A study of inhalant use in street children in Bangalore showed that tobacco was the predominant substance, followed by inhalants, alcohol, cannabis and opioids (Benegal et al. 1999). Nearly a decade later, in another study of street children from Bangalore, it was observed that inhalants are the commonest substance of abuse, followed by tobacco, alcohol, heroin, cannabis and pharmaceutical preparations. Substance use in street children helps them cope with the rigours of living in the streets (Benegal et al. 2008). A study in the Andamans demonstrated that onset of regular use of alcohol in late childhood and early adolescence is associated with the highest rates of consumption in adult life, compared to later onset of drinking (Benegal et al. 2008). Another study among street children found that among 163 street boys, 132 (80.98 %) were substance abusers. The common substances used were nicotine by 104 (63.8 %), inhalants by 78 (48 %), alcohol by 60 (37 %), sedatives and stimulants by 42 (26 %) and cannabis and opioids by 31 (19 %). A significant portion of the street children had been sexually abused 52 (31.9 %), and 87 (53.3 %) had been physically abused (Gaidhane et al. 2008).

A clinic-based study on elderly population has demonstrated a slow but increasing trend of registered elderly patients suffering from substance dependence. There is a preponderance of alcohol dependence, which is followed by opioid dependence (Grover et al. 2008).

A study of the substance use in the 250 auto-rickshaw pullers in New Delhi shows that majority of them used tobacco (79.2 %), followed by alcohol (54.4 %), cannabis (8.0) and opioid (0.8 %). The substance used helped them to remain awake at night while working (Gupta et al. 1986a, b). A study in industrial population about psychiatric prevalence has shown that harmful substance use or substance dependence (42.83 %) is the most common psychiatric condition (Dutta et al. 2007). Another study among industrial workers from Goa estimated a prevalence of 211/1,000 with hazardous drinking using the Alcohol Use Disorder Identification Test (AUDIT) (Silva et al. 2003).

Substance use among medical students has also been examined in several studies (Kumar and Basu 2000; Seshadri 2008). As early as 1977, a drug abuse survey in Lucknow among medical students revealed that 25.1 % abused a drug at least once in a month. Commonly abused drugs included minor tranquilisers, alcohol, amphetamines, bhang (cannabis) and non-barbiturate sedatives. In a study of internees on the basis of a youth survey developed by the WHO in 1982, 22.7 % of males ‘indulged in alcohol abuse’ at least once in a month and 9.3 % abused cannabis, followed by tranquilisers. Common reasons cited were social reasons, enjoyment, curiosity and relief from psychological stress. Most reported that it was easy to obtain drugs such as marijuana and amphetamines (Ponnudurai et al. 1984). Another study in New Delhi of 2,135 medical students showed that current alcohol, tobacco (chewable or smoked) and illicit substance use reported by 7.1, 6.1 and 6.7 % of the respondents, respectively. Use of illicit substances was strongly associated with use of tobacco, alcohol and non-prescription drugs (Rai et al. 2008). A monograph on substance use in the prison population revealed that among the inmates, nearly 80 % had diagnosable psychiatric disorders, and a substantial proportion of them were dependent on substances.

The majority of Indian studies on the special populations have tried to establish the extent of substance use in these populations. Not much work has been done on the treatment-related aspects of substance use in special populations, except among street children using substances.

Hospital admission rates due to the adverse effects of alcohol consumption are disproportionately high. Several studies indicate that nearly 20–30 % of admissions or consultations are due to alcohol-related problems (direct or indirect) in different healthcare settings but are under-recognised by primary-care physicians (Sri et al. 1997; Benegal et al. 2001). Alcohol misuse has been implicated in over 20 % of traumatic brain injuries (Gururaj 2002; Sabheshan and Natarajan 1987) and 60 % of all injuries reporting to emergency rooms (Benegal et al. 2002). It has a disproportionately high association with deliberate self-harm (Gururaj and Isaac 2001), high-risk sexual behaviour (Chandra et al. 2003), HIV infection, tuberculosis (Rajeswari et al. 2002), oesophageal cancer (Chitra et al. 2008), liver disease (Sarin et al. 1988) and duodenal ulcer (Jain et al. 1999). Association between alcohol dependence and seizures is well recognised. Seizure prevalence of 8–16 % among patients with alcohol dependence has been reported (Matto et al. 2009b). Importantly, a confident diagnosis of withdrawal seizure could be made only in minority of instances (Murthy et al. 2007; Mattoo et al. 2009a, b). A recent estimate from surveillance of major non-communicable diseases in India placed the burden due to alcohol use as most important among all non-communicable disorders (Anand 2000). Hence, huge healthcare expenditure is being incurred due to alcohol use. Using their findings in the Bangalore study, researchers from NIMHANS calculated that the direct and indirect costs are attributable to alcohol addiction to be more than three times the profits of alcohol taxation and several times more than the annual health budget of Karnataka. Extrapolating their findings to the whole of India, they estimated that the total alcohol revenue for the period of 2003–2004 was 216 billion rupees, which fell 28 billion rupees short of the total cost of managing the effects of alcohol addiction (Benegal et al. 2000; Gururaj et al. 2006). Alcohol abuse also causes social dysfunction. In a study from India focusing on the distress of the family members of patients with alcoholism, it was found that relatives of all patients reported behaviours such as excessive spending and disturbance of peace at home to be distressful (Chand and Chaturvedi 2010).

The other side of the coin, the alcohol industry, promotes and nurtures a concept called ‘responsible drinking’. The concept, though lucrative for the global trade and excise, should be critically viewed from a health perspective. In a review, it was concluded that currently, there is not enough evidence to promote drinking of alcoholic beverages, even at so-called responsible levels, from a public health and policy perspective (Banerjee et al. 2006).

Research on ‘dual diagnosis’ can be well classified into two broad categories based on the locus of the study. Research has been done primarily either in the psychiatry or in the de-addiction clinics, looking for the presence of either of these groups of disorders. Trivedi et al. screened 1,000 consecutive patients presenting to a psychiatric hospital and found that about 8 % of them abused alcohol. The figure indicates that almost half of the all substance abusers were using alcohol. Alcohol was observed to be more commonly used by patients with bipolar and neurotic disorders, rather than patients suffering from schizophrenia (Trivedi and Sethi 1978). Among the second group of studies, Basu and Gupta (2000) noted that the prevalence of drug use among people with mental illness was twice that found in the general population. The prevalence was 16 % in bipolar disorder, 14 % in schizophrenia, 5 % in organic psychosis and 2 % in non-psychotic disorders. Kishore et al. assessed the lifetime prevalence of comorbidity in 43 patients with substance dependence and the chronology of such comorbidity from the de-addiction centre of a tertiary hospital at Lucknow. The substance most commonly used was alcohol. A study was conducted in the Regional Institute of Medical Sciences (RIMS), Manipur, also replicated the findings of higher psychiatric comorbidity among patients with alcohol dependence, compared to controls (Singh et al. 2005). A relatively older clinic-based study from North India, which compared the prevalence of both axis I and axis II psychiatric disorders in patients with alcohol and opioid dependence, found no difference between these patients. The overall prevalence figure for alcohol and opioid dependence was about 60 % (Vohra et al. 2003). In a recent retrospective chart-based review of consecutive patients from the same centre, 13 % patients were found to have any psychiatric disorders. Mood disorders were the commonest comorbidity in both of these studies. A study on ‘dual diagnosis’ schizophrenia found that patients ascribed hedonistic pursuit as the principal reason for substance use, but reduction in symptoms and distress were also cited as reasons. A trend was discovered for alcohol to be used more for self-medication purposes, compared to opioids and cannabis (Goswami et al. 2003). Another clinic-based study has shown that there is a high frequency of psychiatric comorbidity, predominantly affective disorders, in patients with alcoholic liver disease (ALD) when compared with alcohol dependence alone (Kakunjee 2012). The same group of researchers also found out a substantial and equal occurrence of personality disorders in both ALD and non-ALD groups (Kakunji et al. 2012). Another study, which attempted to assess the prevalence of sexual dysfunction in a clinical sample with alcohol dependence, demonstrated that 72 % had one or more sexual dysfunctions, the most common being premature ejaculation, low sexual desire and erectile dysfunction. The amount of alcohol consumed appeared to be the most significant predictor of developing sexual dysfunction (Arackal and Benegal 2007). Externalising disorders in childhood and adolescence have been found to predate alcohol dependence. Childhood attention-deficit hyperkinetic disorder, which is a member of this group of disorders, was found to be significantly associated with the early-onset subtype of alcohol dependence (Sringeri et al. 2008). In a study from Chandigarh, with a larger sample and better methodology, the same finding was replicated and extended to other childhood disruptive disorders (conduct disorder and oppositional defiant disorder) and adult attention-deficit hyperkinetic disorder (Ghosh 2013). Substance abuse not only predisposes subjects to psychiatric disorders, but also complicates the course of the same. This fact has been substantiated in both patients with alcohol and opioid dependence, where an increase in substance abuse preceded schizophrenic exacerbation in one-third of the patients with ‘dual-diagnosis’ disorders (Goswami et al. 2003).

Not only psychiatric disorders, but also alcohol dependence is also associated with certain personality traits. In a study to evaluate their personality traits, patients with alcohol dependence obtained significantly higher scores on a variety of traits (Chaudhury et al. 2006). Experience and expression of anger and subsequent lower quality of life were found more commonly among patients with alcohol dependence (Sharma et al. 2011). Individuals with alcohol dependence had significantly lower self-esteem compared with control subjects, and significantly, more of the patients were identified as alexithymic. The same study has also commented on the limited value of MAST and CAGE in the diagnosis of alcohol dependence (Ray and Chandrasekhar 1982). Cross-system diagnostic concordance is contradicted by results from two different studies (Basu et al. 2000a, b; Ray and Neeliyara 1989). Typology of alcohol dependence, which has been studied extensively elsewhere, has not attracted much research attention in India. In a study, multivariate cluster analytic approach to classify alcohol dependence was found to be superior as compared to the univariate one, both in terms of concurrent validity and in terms of predictive validity (Basu et al. 2004a, b). Another study was aimed at finding out clinical, personality and behavioural correlates of age at onset of alcohol dependence. Results showed that early-onset patients with alcohol dependence were higher sensation seekers, higher on the Psychopathic Deviate Scale of the multidimensional personality questionnaire (MPQ) and tended to display aggression, violence and general disinhibition when drinking. On the contrary, late-onset patients with alcohol dependence (age at onset of alcohol dependence more than 25 years) were anxiety prone and guilt ridden and had less alcohol-related problems (Varma et al. 1994). Individuals with chronic alcohol abuse show impairments in several cognitive functions. A study of frontal lobe functions and their association with alcohol consumption variables found that chronic alcohol dependence affects visual scanning, set-shifting and response inhibition abilities. Patients with a fewer number of days of alcohol intake during the past 1 year performed relatively better (SriGowri et al. 2008).

Consumption of alcohol has been attributed to different reasons by consumers. Attitude and knowledge about the substance and addiction can be influenced by the cultural background of the individual. In an effort to develop an instrument to assess the attitude towards drinking, four factors have emerged to the forth, namely ‘acceptance’, ‘avoidance’, ‘rejection’ and ‘social dimension’ (Basu et al. 1998). A recent study examining the reasons for alcohol intake and the belief about addiction in people with different ethnic backgrounds has found that societal acceptance and pressure, as well as emotional problems, appear to be the major aetiology, leading to higher prevalence of substance dependence in the tribal community (Sreeraj et al. 2012). Another study on information technology professionals has implicated higher rates of professional stress and risk for developing depression in the development of harmful alcohol use (Darshan et al. 2013). Three phases have been defined and characterised in the downhill progression of alcohol dependence (Mattoo and Basu 1997). The early phase is characterised by the absence of any problems; the middle phase, beginning with daily drinking and ending with the use of a bottle of spirits a day, is characterised mainly by social problems; the late phase begins with the onset of morning drinking and is characterised by the onset of physical problems. In a recent effort, the chronology of criteria of dependence in alcohol dependence syndrome was examined (Mattoo and Basu 1997). In order-wise chronology, either craving or tolerance was present as the first criterion and the presence of craving, tolerance or loss of control was observed as the first criterion in more than half of the subjects. Relapse of alcoholism is a rule rather than exception in dependent patients. Lack of cognitive vigilance was observed to be the most common precipitant of relapse. Family and patients’ perceptions about the precipitants of relapse were found to be concordant (Malhotra et al. 1999).

Alcohol abuse disorders result from the interaction between an individual’s genetic and environmental susceptibility and repeated intake of alcohol over time. It is not possible to become dependent on alcohol without repeatedly consuming alcohol, but only a small percentage of all drinkers develop alcohol dependence. Although the prevalence of alcohol dependence in the Asian population is low, a sizable number of people in India suffer from alcohol use disorders. Genetic polymorphisms, particularly those of the alcohol-metabolising enzymes alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), have been largely implicated in the development of alcohol dependence. Though India represents about one-sixth of the world’s population, there are limited data on genes or polymorphisms that confer susceptibility to alcohol dependence in this population. In a study, aldehyde dehydrogenase (ALDH) levels in patients with alcohol dependence and their first degree non-dependent relatives and controls were compared (Murthy et al. 1996). Findings indicated that low erythrocyte ALDH may be considered as a biochemical trait marker associated with alcoholism. Another study from the northern part of India highlighted the uniquely high frequency of the ALDH2*2/*2 genotype (among subjects with alcohol dependence) being a risk-conferring factor for alcohol dependence. Recently, males with alcohol dependence belonging to six ethnic populations, from four linguistic groups of India, were studied for a single nucleotide polymorphism (SNP) of ALDH2 gene. The small number of haplotypes coding for low-level enzyme activity in this region suggests the strong linkage disequilibrium across the region and confirms the global long-range linkage disequilibrium around the ALDH2 locus (Vaswani et al. 2009). In addition to ALDH polymorphism, it is well established that the central dopaminergic reward pathway is likely involved in alcohol intake and the progression of alcohol dependence. Dopamine transporter (DAT1) mediates the active re-uptake of dopamine from the synapse and is a principal regulator of dopaminergic neurotransmission. A study from the southern part of our country demonstrated a population-specific DAT1 polymorphism determining the vulnerability to alcohol dependence (Bhaskar et al. 2012). Another study provided preliminary insight into genetic risk of alcohol dependence in Indian men (Prasad et al. 2010). It demonstrated two polymorphisms in the DRD2 gene, which may have clinical implications among Indian men with alcohol dependence.

In addition to the molecular genetic studies, neurobiological and neurophysiological investigations have been undertaken in India. These studies have looked into the high-risk population for alcohol dependence, consisting of either person with family history of alcohol dependence or person having externalising disorders. A study aimed to evaluate corpus callosum morphometry in subjects at high risk for alcoholism found that smaller callosal areas had a negative association with externalising behaviours and might represent yet another marker of susceptibility to alcoholism in high-risk subject (Benegal et al. 2006; Venkatasubramaniam et al. 2007). On similar lines, an electrophysiological study on high-risk subjects showed lower P300 amplitudes over frontal brain areas (Benegal et al. 1995; Murlidharan 2008). Differences were greater in the young, tending to converge with increasing age. There was a strong association between this reduced brain activation and an excess of externalising behaviours in high-risk individuals. Another study in this area concluded that P300 amplitudes varied inversely with the presumed continuum (children with high family loading of alcohol dependence, early-onset alcohol dependence and late-onset alcohol dependence) of risk in those at high risk for developing alcoholism (Silva et al. 2007).

Among studies on interventions related to withdrawal and relapse prevention, drug trials outnumber studies on psychosocial interventions. In substance abuse treatment, it is always essential to determine the treatment setting prior to the initiation of actual treatment. Unfortunately, there is no published literature from India on the relative efficacy or indication of inpatient or outpatient treatment. The only retrospective review of inpatient treatment to determine the long-term outcome of both alcohol dependence and opioid dependence revealed that those who were following up at the time of evaluation had significantly longer duration to relapse. Hence, putting emphasis on the follow-up could result in a better long-term outcome (Singh et al. 2008). To ensure an optimal follow-up of patients, it is quite essential to have a multidisciplinary approach.

Lorazepam and chlordiazepoxide are both popular treatments for alcohol-withdrawal syndrome all over the world and so also in India. In a double-blind randomised control trial that was done to compare their efficacy, lorazepam and chlordiazepoxide showed similar efficacy in reducing symptoms of alcohol withdrawal as assessed using the revised Clinical Institute Withdrawal Assessment (CIWA) for Alcohol Scale (Kumar et al. 2009). No difficulties in drug discontinuation or differences in impairing adverse events were observed with either drug. Then again, another study has highlighted the problem with mega doses of lorazepam (Chand and Murthy 2003). Another study demonstrated an increase in the low activity of aldehyde dehydrogenase (ALDH) following administration of either diazepam or chlordiazepoxide in alcohol withdrawal, explaining their efficacy (Murthy 1992).

In India, disulfiram is still the most commonly used agent for relapse prevention, as it is cheap and easily available. Disulfiram in alcohol use disorders in the Indian context is a useful treatment, particularly when compliance with the drug regimen is overseen by family members (Grover and Basu 2004; Grover et al. 2007a, b). An open-label randomised control trial compared the efficacy of disulfiram (DSF) and topiramate (TPM) for preventing alcoholic relapse in routine clinical practice in India (Sousa 2008). Though DSF proved to be more efficacious in terms of time spent in abstinence, TPM-treated patients did show less craving than DSF-treated patients. Another study with similar methodology comparing the efficacy of disulfiram and naltrexone (NTX) demonstrated superior efficacy of DSF in terms of time to relapse (Sousa and Sousa 2004). The third study concluded that DSF is superior to acamprosate (ACP) for preventing relapse in men with alcohol dependence with good family support (Sousa 2005). Comparison of efficacy with DSF and NTX in adolescent population has demonstrated superiority of the former in terms of reducing relapse rate (Sousa 2008). These findings were also replicated in the elderly population (Sousa and Jagtap 2009). All these studies were from same centre and were done by the same research team. Moreover, they had recruited patients with good family support and also provided psychosocial interventions. Hence, the findings of these studies should be interpreted within these limitations. Further comparisons between these drugs in different treatment settings and populations are, thus, warranted. In a retrospective chart review, patients with alcohol dependence who received treatment from an addiction centre were studied to compare those on ACP or NTX versus those on no prophylactic drugs with regard to their demographic and clinical background and short-term outcome after treatment (Basu et al. 2005). Results showed a superiority of ACP over NTX, or no drugs, both in the short term and during follow-up. Despite the popular notion of DSF’s potential dangerousness, it has rarely been implicated in serious adverse events. A study was conducted to evaluate the short-term safety of DSF in patients with alcohol dependence with chronic smoking (Galgali et al. 2002). Finding suggested that disulfiram does not significantly alter forced expiratory volume in the first minute (FEV1) values and airway reactivity during the treatment period, thus, could be used safely. Though there is no systemic study on the adverse reactions of these prophylactic medications, there is one case report of possible DSF-induced delirium after 6 weeks of initiation of the medication (Basu 2010).

There are only a handful of studies on psychosocial interventions for alcohol dependence. A five-year follow-up study of 150 patients treated for alcohol dependence using a primarily Alcoholics Anonymous approach reported a modest improvement in outcome, both in short term and in long term (Kuruvilla and Jacob 2007). In a recent study conducted in South India, it was found that individuals randomly assigned to dyadic relapse prevention (i.e. involvement of both patient and family members in the intervention) consistently performed better than those assigned to treatment as usual (Nattala et al. 2010). Intervention was more effective for relapse prevention in terms of reduction in quantity of alcohol, drinking days and number of days with dysfunction in family, occupational and financial dimensions. Another study demonstrated the effectiveness of training community volunteers in imparting knowledge and skills to identify and motivate persons with alcohol and drug dependence to seek treatment (Manickam 1997). Keeping patients with alcohol dependence in the treatment net is one of the most difficult yet a crucial task. Tracing techniques such as home visits were found to be effective in increasing follow-up rates in patients with alcohol dependence (Mahadevappa et al. 1987). Along the same lines, follow-up support and continued care appeared to significantly improve longer-term recovery in this group of patients (Murthy et al. 2009).

Study on the predictors of outcome following alcohol de-addiction treatment has mentioned younger age, higher psychosocial problem index, family history of alcoholism and delayed follow-up after relapse among the few negative predictors (Kar et al. 2003).

Injecting drug use (IDU) has been strongly associated with HIV. In India too, among all risk groups, prevalence of HIV is highest among IDUs. High prevalence of hepatitis C has also been described among Indian IDU populations. In a review, hepatitis C virus infection is found to co-occur in 30–50 % of IDUs in general and 60–90 % in some high-risk pockets. Hence, the figure indicates an appreciable magnitude of problem that may turn into an epidemic. This review also points towards glaring lacunae of studies on risk behaviours associated with acquiring hepatitis C virus infection in IDUs (Basu 2010). Taking cue from the same, the author has tried to address this issue in a recent study. It was found that seroprevalence of anti-HCV antibody is high in IVDUs compared to non-IVDUs and is primarily related to injecting risk behaviour (Basu et al. 2012, 2013). In a study of consecutive patients, 12.5 % was found to have seizures and most of these were associated with substance use (Mattoo et al. 2009a). Dextropropoxyphene (DPP), a weak opioid, is often abused as a psychoactive substance in India. A retrospective chart review from PGIMER, Chandigarh, has demonstrated that DPP-induced epileptic seizures are common (one in five) and much more frequent than seizures in patients using other opioids. Those with seizures had significantly greater duration of DPP use and higher rates of medical comorbidity compared to patients without seizure (Basu et al. 2009a). Metabolic syndrome (MS) is an emerging condition in present psychiatric literature. A study from India, conducted in Chandigarh, has demonstrated that almost one in three of opioid-dependent patients has metabolic syndrome, and the figure is more than the prevalence of MS in alcohol dependence in the same study. Moreover, the prevalence of MS in both disorders is in turn greater than the general population prevalence (Mattoo et al. 2011).

Studies on comorbidity or ‘dual diagnosis’: No research till date has exclusively looked into prevalence of psychiatric disorders among patients with opioid dependence. Rather opioid dependence has been studied as a subset of the entire spectrum of substance dependence. In Trivedi et al.’s previously mentioned study, opium was the least sought-after substance among patients with psychiatric illnesses. But, in another study from a de-addiction clinic of Lucknow, opioids were found to be the second most common substances of abuse in patients with dual diagnosis (Kishore et al. 1994). Possibly, the locus of research can explain the discrepancy.

Though subtypes of alcohol dependence have been studied extensively, there are only a few studies on subtyping or profiling of opioid dependence. A study from Chandigarh has shown that the early-onset group was characterised by a significantly younger current age, more urban and unemployed subjects, a higher severity of opioid use, higher sensation seeking and higher global psychopathology in terms of MPQ. These results indicate that the age-at-onset typology in opioid dependence is a feasible way of classifying patients with opioid dependence, and this subtyping has some similarities to age-at-onset typology in alcoholism (De et al. 2003). A recent study from the same centre has sparked renewed the interest in the area of opioid typology. This has compared early- and late-onset opioid patients with opioid dependence on five explanatory domains including clinical (severity), genetic (family history), psychological (sensation seeking and impulsivity), neuropsychological (attention concentration and executive functions) and neurophysiological (P300 evoked response potential). Taking a cue from the classic categorical versus dimensional debate in clinical psychiatry, this research has emphasised that age of onset of opioid dependence is meaningful when the diagnosis of dependence is used as dimension rather than a category (Basu et al. 2014b).

Initiation of substance abuse is undoubtedly affected by psychosocial factors. In one study, peer influence was found to have a significant role in initiation of heroin use (Chowdhury and Sen 1992). Sometimes medical prescriptions can initiate opioid use. In a case series of tramadol dependence, prescription of the same medication as an analgesic was found to precede its regular use (Sarkar et al. 2012). Likewise, psychological traits have also been implicated. High sensation seeking combined with alienation, leading to an inability to meet the demands through a socially sanctioned channels, has been hypothesised to foster opioid dependence (Basu et al. 1995). Relapse is a common and distressing aspect of substance dependence mediated by several biological and psychosocial factors (Mattoo et al. 1997, 2009a). A study examined the association between demographic variables, clinical parameters and certain psychosocial factors and relapse among patients with either alcohol or opioid dependence. Patients who had relapsed were significantly more likely to have a positive family history, to have a higher number of previous relapses, to be using maladaptive coping strategies and to have been exposed to a higher total number of ‘high-risk’ situations and undesirable life events. Conversely, those who had remained abstinent tended to use significantly more number of coping strategies, principally adaptive ones, and scored significantly higher on all measures of self-efficacy. Another study has highlighted on the role of craving in relapse of heroin dependence (Dhawan et al. 2002). Craving was found to be inversely proportional to the duration of abstinence and was not influenced by socio-cultural factors. In a clinic-based study on patients with buprenorphine addiction, a chronic but slowly improving course was ascertained. Substance substitution was found to complicate the overall course and outcome (Basu et al. 2000a, b).

The opioid receptor mu1 (OPRM1) mediates the action of morphine. A study demonstrated the role of OPRM1 receptor polymorphism in the development of opioid addiction (Deb et al. 2010). The same group of researchers also found out the contribution of c-AMP receptor-binding element (CREB) polymorphism to opioid dependence (Kumar et al. 2011). Investigating endophenotypes is an emerging concept, especially for opioid dependence (Singh and Basu 2009). A study has demonstrated maximum abnormality in P300 latency and amplitude, and executive function, in patients with opioid dependence, followed by their healthy relatives, with least abnormalities in the control group (Singh et al. 2009).

The treatment of opioid dependence syndrome constitutes of treatment for intoxication, withdrawal and relapse prevention. No studies on the treatment of opioid intoxication have been undertaken in India. Buprenorphine has been found to be an effective agent for management of opioid withdrawal symptoms. When compared to clonidine, buprenorphine was found to be efficacious both in terms of less subjective symptoms and in terms of no change in the ‘liking’ for opioids (Ray et al. 2011). Another study has been conducted to correlate the effect of clonidine in opioid withdrawal with the opiate receptor activity. Clonidine seems to mitigate kappa receptor effects earlier than the mu receptor effects and does not have much effect on delta receptor effects (Chaturvedi 1994).

For long-term management of opioid dependence, one approach is opioid substitution or agonist therapy. Methadone, which has been extensively studied in the West, has been launched only recently in India and is being implemented as a pilot project at five sites in India. The initial clinical experience is encouraging; however, the adequate dose for Indian patients is yet to be determined. Early observations indicate that most Indian patients would require doses ranging between 40 and 80 mg/day. But, there are quite a few studies on the efficacy of another agonist, buprenorphine. A study has demonstrated the low abuse liability of buprenorphine in higher doses (Singhal et al. 2007). De et al. (2001) in a double-blind randomised controlled trial compared different doses of sublingual buprenorphine (2 and 4 mg/day) in an inpatient setting for long-term pharmacotherapy among opiate-dependent subjects. The results indicated that both 2 and 4 mg doses of buprenorphine were effective in pharmacotherapy of opioid dependence without significant difference. Mohan and Ray (1997) did a quasi-experimental study of community-based treatment with buprenorphine for heroin dependence in an urban slum of Delhi. It was seen that 70 % subjects improved with no use or very little use of heroin. Dhawan and Sunder (2008), in a brief overview of buprenorphine substitution in India, have concluded that buprenorphine substitution programmes have been successful in decreasing the harm associated with drug use, as well as decreasing the drug use per se and improving the quality of life. In another study carried out by the All India Institute of Medical Sciences (AIIMS) in Nagaland, 54 patients with opioid dependence on buprenorphine maintenance were followed up for 6 months. There was significant improvement in ‘Drug and family domain’ of the Addiction Severity Index (ASI), and the subjective well-being scale. Similarly, the treatment centre of TT Ranganathan Clinical Research Foundation, Chennai, found improvement in patients maintained on buprenorphine in their drug use pattern, life functioning, general health, high-risk behaviour, crime rate and arrests. In a multisite study on buprenorphine, Dhawan et al. (2010) reported that the mean dose required was 6 mg/day. Results showed significant abstinence and reduction in addiction severity with buprenorphine at this dose. A recent study found out that buprenorphine and naloxone combination had a higher adherence rate, compared to buprenorphine when used for opioid substitution therapy (Balhara and Jain 2012). In another study, buprenorphine maintenance was found to be helpful not only in terms of diminished use, but also in improving the quality of life (QoL) of patients with opioid dependence (Dhawan and Chopra 2013). Slow-release oral morphine (SROM), a natural derivative of opium and a mu receptor agonist, is relatively cheap with a long duration of action. In India too, SROM has been tried for patients with opioid dependence as a maintenance agent at the Nation Drug De-addiction and Treatment Center (NDDTC), AIIMS, New Delhi. It has been found to be a safe drug with minimal side effects and can be administered in once-daily dosage. Patients showed definite improvement, with a decrease in heroin consumption, improved functioning and a decrease in illegal activities (Rao et al. 2005, 2012). Though opioid substitution therapy has been researched reasonably well, opioid antagonist treatment has been studied rarely. In an open-label study, opioid antagonist naltrexone was found to be efficacious with an overall abstinence rate up to 50 %. It also proved to be acceptable to the patients (Malhotra et al. 2003).