METHODS: We conducted a nested case-control study in a cohort of 519 978 men and women aged 25 to 70 years followed from 1992 to 2003. A total of 713 incident colon cancer cases were matched, using risk-set sampling, to 713 controls on age, sex, study centre, fasting status and hormonal therapy use. The amount of total physical activity during the past year was expressed in metabolic equivalent of task [MET]-h/week. Anthropometric measurements and blood samples were collected at study baseline.
RESULTS: High physical activity was associated with a lower risk of colon cancer: relative risk ≥91 MET-h/week vs <91 MET-h/week = 0.75 [95% confidence interval (CI): 0.57 to 0.96]. In mediation analyses, this association was accounted for by waist circumference: proportion explained effect (PEE) = 17%; CI: 4% to 52%; and the biomarkers soluble leptin receptor (sOB-R): PEE = 15%; 95% CI: 1% to 50% and 5-hydroxyvitamin D (25[OH]D): PEE = 30%; 95% CI: 12% to 88%. In combination, these factors explained 45% (95% CI: 20% to 125%) of the association. Beyond waist circumference, sOB-R and 25[OH]D additionally explained 10% (95% CI: 1%; 56%) and 23% (95% CI: 6%; 111%) of the association, respectively.
CONCLUSIONS: Promoting physical activity, particularly outdoors, and maintaining metabolic health and adequate vitamin D levels could represent a promising strategy for colon cancer prevention.
METHODS AND STUDY DESIGN: A randomized controlled study was conducted on obese women with high breast adiposity (<0.1 Sm-1), aged 40-60 years in Klang Valley, Malaysia. Subjects were assigned to intervention (n=16) and control group (n=15). Intervention group received a home based health education package with close monitoring weekly, personal diet consultation and physical training in group. Assessment was ascertained at three time points; baseline, weeks 8 and 16. Outcome measures were the energy intake, physical activity, body composition, blood tests, blood biomarkers and electrical impedance tomography (EIT) quantitative values. Analyses were done using 2-way repeated measures ANOVA.
RESULTS AND CONCLUSIONS: All subjects completed the program without any drop-out. The HSI group had 100% compliance towards the intervention program; their energy intake was reduced for approximately 35% and their activity score was increased for approximately 11%. A significant interaction effect was found in body weight, body mass index (BMI), total cholesterol/HDL, vitamin C intake and matrix metallopeptidase 9 (MMP-9) (p<0.05). Interestingly, their EIT extremum values were also significantly increased indicating a reduction of breast adiposity. The intervention program was successful in improving body composition, physical activities, MMP9 and breast adipose tissue composition.
Methods: : We utilized data among 1020 infants from a mother-offspring cohort, who were Singapore citizens or permanent residents of Chinese, Malay or Indian ethnicity with homogeneous parental ethnic backgrounds, and did not receive chemotherapy, psychotropic drugs or have diabetes mellitus. Ethnicity was self-reported at recruitment and later confirmed using genotype analysis. Subject-specific BMI curves were fitted to infant BMI data using natural cubic splines with random coefficients to account for repeated measures in each child. We estimated characteristics of the child's BMI peak [age and magnitude at peak, average pre-peak velocity (aPPV)]. Systolic (SBP) and diastolic blood pressure (DBP), BMI, sum of skinfolds (SSF) and fat-mass index (FMI) were measured during a follow-up visit at age 48 months. Weighted multivariable linear regression was used to assess the predictors (maternal BMI, gestational weight gain, ethnicity, infant sex, gestational age, birthweight-for-gestational age and breastfeeding duration) of infant BMI peak and its associations with outcomes at 48 months. Comparisons between ethnicities were tested using Bonferroni post-hoc correction.
Results: : Of 1020 infants, 80.5% were followed up at the 48-month visit. Mean (SD) BMI, SSF and FMI at 48 months were 15.6 (1.8) kg/m 2 , 16.5 (5.3) mm and 3.8 (1.3) kg/m 2 , respectively. Mean (SD) age at peak BMI was 6.0 (1.6) months, with a magnitude of 17.2 (1.4) kg/m 2 and pre-peak velocity of 0.7 (0.3) kg/m 2 /month. Compared with Chinese infants, the peak occurred later in Malay {B [95% confidence interval (CI): 0.64 mo (0.36, 0.92)]} and Indian infants [1.11 mo (0.76, 1.46)] and was lower in magnitude in Indian infants [-0.45 kg/m 2 (-0.69, -0.20)]. Adjusting for maternal education, BMI, gestational weight gain, ethnicity, infant sex, gestational age, birthweight-for-gestational-age and breastfeeding duration, higher peak and aPPV were associated with greater BMI, SSF and FMI at 48 months. Age at peak was positively associated with BMI at 48 months [0.15 units (0.09, 0.22)], whereas peak magnitude was associated with SBP [0.17 units (0.05, 0.30)] and DBP at 48 months [0.10 units (0.01, 0.22)]. Older age and higher magnitude at peak were associated with increased risk of overweight at 48 months [Relative Risk (95% CI): 1.35 (1.12-1.62) for age; 1.89 (1.60-2.24) for magnitude]. The associations of BMI peak with BMI and SSF at 48 months were stronger in Malay and Indian children than in Chinese children.
Conclusions: : Ethnic-specific differences in BMI peak characteristics, and associations of BMI peak with early childhood cardio-metabolic markers, suggest an important impact of early BMI development on later metabolic outcomes in Asian populations.
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.