5-Methyltetrahydrofolate-homocysteine methyltransferase gene polymorphism (MTR) and risk of head and neck cancer

The functional effect of the A>G transition at position 2756 on the MTR gene (5-methyltetrahydrofolate-homocysteine methyltransferase), involved in folate metabolism, may be a risk factor for head and neck squamous cell carcinoma (HNSCC). The frequency of MTR A2756G (rs1805087) polymorphism was compared between HNSCC patients and individuals without history of neoplasias. The association of this polymorphism with clinical histopathological parameters was evaluated. A total of 705 individuals were included in the study. The polymerase chain reaction-restriction fragment length polymorphism technique was used to genotype the polymorphism. For statistical analysis, the chi-square test (univariate analysis) was used for comparisons between groups and multiple logistic regression (multivariate analysis) was used for interactions between the polymorphism and risk factors and clinical histopathological parameters. Using univariate analysis, the results did not show significant differences in allelic or genotypic distributions. Multivariable analysis showed that tobacco and alcohol consumption (P < 0.05), AG genotype (P = 0.019) and G allele (P = 0.028) may be predictors of the disease and a higher frequency of the G polymorphic allele was detected in men with HNSCC compared to male controls (P = 0.008). The analysis of polymorphism regarding clinical histopathological parameters did not show any association with the primary site, aggressiveness, lymph node involvement or extension of the tumor. In conclusion, our data provide evidence that supports an association between the polymorphism and the risk of HNSCC.

Impact of a 2-year intervention program on cardiometabolic profile according to the number of goals achieved

We investigated the impact of lifestyle goal achievement on cardiovascular risk factors after a 2-year behavioral intervention program applied to 394 adults (113 with diabetes, mean age 60.2 ± 11.4 years, 56% women) and targeting four goals: ≥5% weight loss; ≥150 min/week physical activities; <10% saturated fat intake/day; ≥400 g fruit and vegetable intake/day. Baseline characteristics and changes in variables after intervention among the four categories of number of goals achieved (none, 1, 2, and ≥3) were compared by independent ANOVA or the Kruskal-Wallis test. Individuals without diabetes achieving a higher number of goals were more likely to be older (3 or 4 goals: 61.8 ± 12.6 years vs none: 53.3 ± 10.3 years, P < 0.05) and to have a lower mean BMI (3 or 4 goals: 21.7 ± 2.6 kg/m² vs none: 29.0 ± 4.8 kg/m², P < 0.05), diastolic blood pressure (3 or 4 goals: 77.3 ± 2.1 mmHg vs none: 85.4 ± 9.6 mmHg, P < 0.05), triglyceride (3 or 4 goals: 116.1 ± 95.1 mg/dL vs none: 144.8 ± 65.5 mg/dL, P < 0.05) and insulin levels (3 or 4 goals: 3.6 ± 2.4 μU/L vs none: 5.7 ± 4.0 μU/L, P < 0.05) than those achieving fewer goals. The absolute changes in cardiovascular risk factors tended to be more pronounced with increasing number of goals achieved in individuals without diabetes. The intervention had a beneficial impact on the cardiometabolic profile of individuals with normal or altered glucose metabolism. The number of goals achieved in this lifestyle intervention was associated with the magnitude of improvement of cardiovascular risk factors in individuals without diabetes. Participants with a better cardiometabolic profile seemed to be more likely to have a healthy lifestyle.

Percent body fat is a better predictor of cardiovascular risk factors than body mass index

The objective of the present study was to evaluate the predictive values of percent body fat (PBF) and body mass index (BMI) for cardiovascular risk factors, especially when PBF and BMI are conflicting. BMI was calculated by the standard formula and PBF was determined by bioelectrical impedance analysis. A total of 3859 ambulatory adult Han Chinese subjects (2173 males and 1686 females, age range: 18-85 years) without a history of cardiovascular diseases were recruited from February to September 2009. Based on BMI and PBF, they were classified into group 1 (normal BMI and PBF, N = 1961), group 2 (normal BMI, but abnormal PBF, N = 381), group 3 (abnormal BMI, but normal PBF, N = 681), and group 4 (abnormal BMI and PBF, N = 836). When age, gender, lifestyle, and family history of obesity were adjusted, PBF, but not BMI, was correlated with blood glucose and lipid levels. The odds ratio (OR) and 95% confidence interval (CI) for cardiovascular risk factors in groups 2 and 4 were 1.88 (1.45-2.45) and 2.06 (1.26-3.35) times those in group 1, respectively, but remained unchanged in group 3 (OR = 1.32, 95%CI = 0.92-1.89). Logistic regression models also demonstrated that PBF, rather than BMI, was independently associated with cardiovascular risk factors. In conclusion, PBF, and not BMI, is independently associated with cardiovascular risk factors, indicating that PBF is a better predictor.