Metabolic syndrome among substance dependent men: A study from north India.

BACKGROUND: Substance abuse, alcohol in particular, is associated with increased risk of diabetes and metabolic syndrome (MS). The relationship between the substance abuse and MS is complex and the literature is sparse.
OBJECTIVES: The present research was aimed to study the prevalence and predictors of MS among outpatients with substance dependence.
MATERIALS AND METHODS: Patients with substance dependence were recruited from a deaddiction center in North India, who attended outpatient clinic from 1(st) January, 2010-31(st) December, 2010. MS was assessed using International Diabetes Federation (IDF) criteria.
RESULTS: Out of 250 subjects, 34 (13.6%) of the subjects met the IDF criteria for MS and highest being in alcohol group (21.6%). The commonest abnormality was increased triglycerides (TG; 54%) and increased waist circumference (36.8%). Age, body weight, body mass index, and obesity were significant predictor of MS.
CONCLUSION: MS was highest in subjects with alcohol dependence with the commonest abnormality of TG and blood pressure. Hence, routine screening is advisable in this population to address emerging MS.

Substance abuse is associated with increased mortality,[1] one of the prominent causes being metabolic diseases.[2] Alcohol and tobacco use, in particular, have been associated with increased risk of diabetes,[3] cardiovascular mortality,[4] and the development of metabolic syndrome (MS);[34] which in turn is an important risk factor for cardiovascular diseases and all cause mortality.[5] MS is a cluster of abnormalities that include insulin resistance, hypertension, dyslipidemia, and abdominal obesity. Insulin resistance and a proinflammatory state have been hypothesized to result in the development of MS.[67]

Subjects with substance use have increased risk of MS because of the nutritional deficiencies, increasing cell damage, augmenting excitotoxicity, reducing energy production, lowering the antioxidant potential of the cells, etc.[8] Though their relationship remains complex as low to moderate alcohol use has been found to lower the risk for MS,[491011121314] while heavy alcohol use has been found to increase the risk for MS.[34111516] Some studies have reported increased MS even with low alcohol use.[1718]

The prevalence of MS in substance dependent population have been reported in the range of 5-31%.[101214161819202122] Higher body mass index is also reported to contribute MS.[23] Research from India on MS and substance abuse is limited to only one study from North India.[24] The present research was aimed to study the prevalence and predictors of MS among inpatients with substance dependence.

MATERIALS AND METHODS

The study was conducted at the Drug Deaddiction and Treatment Center (DDTC), Department of Psychiatry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh - a multispecialty tertiary-care teaching hospital providing services to a major area of North India. The study had the approval of the institutional research ethics committee. Patients with any substance dependence were recruited from outpatient setting at their first contact at DDTC from 1st January, 2010-31st December, 2010. A cross-sectional design was employed and written informed consent was obtained from the patients taken up for the study. Diagnoses were made by consultant psychiatrist as per International Classification of Diseases - Classification of Mental and Behavioral Disorders - Clinical Descriptions and Diagnostic Guidelines tenth revision (ICD-10).[25] All of our patients were males as because of lack of separate facilities in this center, we admitted female substance users in psychiatric inpatient unit under the same department. After enrolment into the study, a semistructured proforma was used to assess demographic and substance use details.

Metabolic and anthropometric assessments

Body weight was measured in kilogram (kg) and height in centimeters (cm) by a calibrated scale. Waist circumference, in centimeters (cm), was measured midway between the inferior costal margin and the superior border of the iliac crest, at the end of normal expiration in standing position. At least two readings at 5 min intervals were recorded for blood pressure (BP) using standard mercury manometer in supine position. If blood pressure was found to be high (≥140/90) then a third reading was taken after 30 min; the lowest of these readings was taken. Fasting venous blood sample was collected under aseptic condition to measure the blood glucose (FBS), triglycerides (TG), and high density lipoprotein (HDL) levels.

MS was diagnosed using International Diabetes Federation (IDF) criteria.[26] According to IDF criteria a person is considered to have MS if he has high waist circumference (≥80 cm for females and ≥90 cm for males of Asian origin) along with two of the following criteria: Systolic blood pressure ≥130 mmHg and/or diastolic blood pressure ≥85 mmHg (or on treatment for hypertension), TG levels ≥150 mg/dl (or on specific treatment for this abnormality), HDL cholesterol <40 mg/dl for male and <50 mg/dl for females (or on specific treatment for this abnormality), FBS ≥100 mg/dl (or on treatment for diabetes mellitus).[26]

Ethical issues

All patients and healthy controls with metabolic abnormalities were informed and educated about the need for proper diet and regular exercise, and referred for specialist care whenever required.

Statistical analysis

Analysis was done using the Statistical Package for Social Sciences (SPSS) version 14.0 for Windows (Chicago, Illinois, USA). Frequencies with percentages were calculated for categorical variables and mean and standard deviation (SD) were calculated for continuous variables. Chi-square test and t-test and one-way analysis of variance (ANOVA) were used for comparisons. Binary logistic regression was performed to examine the influence of independent variables on MS.

RESULTS

Demographic profile

A total of 250 subjects, all men, were included in the study. By the substance of dependence the groups were made: Alcohol (N = 97), opioid (N = 52), alcohol + opioid (N = 49), and other substance, with or without alcohol or opioid (others) (N = 52). Among the groups; 68, 73.1, 87.8, and 80.8 subjects respectively were currently using tobacco in dependent or nondependent pattern.

A typical study subject was aged 34.5 ± 1.04 years, married (68.8%), working (66.8%), from urban area (60%), Hindu (54.4%), educated up to matriculation (49.6%), and from nuclear family (47.2%). Compared to others, alcohol group was more often married, currently employed (P < 0.001) and older (P < 0.01), alcohol and others groups were more often Hindu (P < 0.001), and others group was more often from urban areas (P < 0.05). Majority of the subjects were from urban background in all the groups except in the alcohol + opioid group, who were from rural background [Table 1].

Table 1

Sociodemographic profile

Metabolic profile

Mean duration of dependence was 7.16 years. MS criteria were met in 13.6% of the subjects and highest in alcohol group (21.6%) and the lowest in others group subjects (7.7%). Among the metabolic abnormalities, the commonest were increased TG (54%) and waist circumference (36.8%), and the least common were increased FBS level (6.4%) and low HDL (7.6%). Groups differed for hypertension by systolic or diastolic criteria (P < 0.001), high systolic and diastolic blood pressures (P < 0.01), duration of dependence and number of subjects with increased waist circumference (P < 0.01), and the prevalence of MS (P < 0.05). The groups were similar for the number of subjects with low HDL levels, high TG levels or high FBS. Nearly two-third of the subjects (62.8%) in entire sample was fulfilling one or two MS components [Table 2].

Table 2

Clinical profile of total sample and substance dependent groups

Comorbid psychiatric diagnosis present in 9.6% cases (N = 24), included depression (N = 6), and psychotic illness and bipolar affective disorder (BPAD; N = 5 each). Comorbid physical diagnosis were present in 14% (N = 35), included seizure disorder (N = 12) and diabetes mellitus and alcoholic liver disease (N = 5 each), while 13 subjects have other physical diagnosis.

Compared to those without MS, the subjects with MS were more often currently working (82.4 vs 55.1%; P < 0.01), married (85.3 vs 66.2%; P < 0.05), and older (38.2 vs 33.9 years; P < 0.05); and had higher body weight (79 vs 72 kg; P < 0.005), body mass index (27.7 vs 21.6; P < 0.01), and obesity (BMI ≥ 25) (76.5 vs 18.5%; P < 0.01).

Predictors of metabolic syndrome

Simple binary logistic regression analysis with enter method was used to study the relationship among independent variables which were more frequently present in subjects with MS in entire sample and individual groups. As shown in Table 3, significant predictors of MS were greater age, higher body weight, higher body mass index and obesity (body mass index ≥ 25) in entire group. Of all predictors, odds ratio was highest (OR = 14.3) for obesity. In individual groups, significant MS predictors were body weight, BMI and obesity in alcohol group; BMI and obesity in opioid and others groups.

Table 3

Predictors of MS in total sample (N=250)

DISCUSSION

Our typical study subject was a married, working, male in forth decade from urban area with 7.16 years of substance dependence. The demographic profile of our sample was similar to that of our clinic population.[2427] Study consisted of all male subjects as more than 99% of the subjects that present to us for treatment are males.[27]

The prevalence rate of MS at 13.6% in the present study was within the range of 5-31% reported for subjects taking alcohol by the Western studies.[101214161819202122] In our study, the prevalence of MS was found to be highest in the alcohol dependent group and it was also in the range of MS reported earlier.[101214161819202122] Compared to the previous study from our center which was conducted in inpatient setting,[24] our study is from outpatient setting with bigger sample size (250 vs 100); MS rate is similar in alcohol group (21.6 vs 24.6%), but lower in opioid group (9.6 vs 29.3%). Our finding is also consistent with the reported increase in TG and decrease in HDL with heroin use by a study from the West.[28]

The most common abnormality in the present study being increased TG (54%) was similar to previous studies.[1429] The significant difference among various groups for the number of subjects with increased waist circumference, hypertension, and prevalence of MS; signifies that the substance dependent population is a heterogeneous one and needs to be studied separately.

The subjects with MS being older and more likely to be married and employed in the present study, was a finding similar to that from other studies from our center in subjects with substance dependence.[24] Our subjects with MS was older and had more weight, higher BMI, and obesity; compared to subjects without MS and similar variables remained significant predictors of MS. Other studies[233031] also reported age and body mass index as significant predictors of MS. These facts point to the need for physical examination and measurement of weight, waist circumference, and body mass index to be an essential part of the assessment of patients seeking deaddiction, especially for those aged >30 years.

This study had certain limitations. Being a hospital based sample, it was not a true representation of the community. A male only sample puts a restriction on the generalization of the findings. The lack of a matched control group further limits the conclusions on causal links.

To conclude, MS is prevalent amongst substance dependent subjects. Besides presence of MS, a significant proportion of patients had one or two metabolic abnormality. This suggests that clinicians should not just focus on patients who have MS, but also look at this high risk population, which can convert to MS positive cases. Hence, any patient who fulfills a single criterion of MS should be considered at risk for development of MS and the preventive strategies should be in place. Older age, higher body weight, and higher body mass index are certain risk factors for development of MS. However, these findings need further validation with larger samples, prospective, and longitudinal designs.