Apoyo social a drogodependientes en programa de mantenimiento con metadona en una prisión

Goal: To learn more about the social support available to patients participating in a prison methadone maintenance program (PMM). Methodology: Descriptive, with controls. Setting: A penitentiary in Albolote (Granada) Population Sample: The total prison population was 1,579; 364 patients were included in the PMM; 35 were female and 329 were male. 60 patients, 7 women and 53 men, were used as cases. 30 non-drug dependent prisoners, 3 women and 27 men, were the control group. They had no antecedents of problems with drug addiction. Interventions: Interviews with cases and controls to learn about their addictive antecedents, family structure, socio-economic level, and a hetero-applied MOS questionnaire was completed. Percentages of each social support variable were obtained and compared using the chi-squared technique. Results: The overall support received is low in 38 cases (74.5%) and in 9 controls (30%): p = 0.0001. OR 0.1466, confidence interval at 95% (0.0538-0.3989). Support received is normal in 13 cases (25%) and 21 controls (70%): p = 0.0007. OR 0.69, confidence interval at 95% (0.44-0.93). All of the variables were statistically significant for non-drug addicts, except for emotional support, which was the same for both groups. Conclusion: The perception of inmates participating in the methadone maintenance program was that they received less social support than the non-drug dependent inmates.

Real-time molecular epidemiology of tuberculosis by direct genotyping of smear-positive clinical specimens.

We applied MIRU-VNTR (mycobacterial interspersed repetitive-unit-variable-number tandem-repeat typing) to directly analyze the bacilli present in 61 stain-positive specimens from tuberculosis patients. A complete MIRU type (24 loci) was obtained for all but one (no amplification in one locus) of the specimens (98.4%), and the allelic values fully correlated with those obtained from the corresponding cultures. Our study is the first to demonstrate that real-time genotyping of Mycobacterium tuberculosis can be achieved, fully transforming the way in which molecular epidemiology techniques can be integrated into control programs.

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.