METHODS: Predialysis CKD patients were included in this cross-sectional study. Patient demographics, medical/medication histories, and laboratory parameters (serum 25-hydroxyvitamin D (25(OH)D), creatinine, phosphate (P), calcium, albumin, and intact-PTH (i-PTH)) were collected and compared among patients with various CKD stages. The association between 25(OH)D and these parameters was determined by multiple linear regression.
RESULTS: A total of 196 patients with mean ± SD eGFR of 26.4 ± 11.2 mL/min/1.73 m2 was included. Vitamin D deficiency (25(OH)D concentration < 15 ng/mL) and insufficiency (25(OH)D concentration 16 - 30 ng/mL) was found in 29.1% and 57.7% of the patients, respectively. Mean ± SD serum 25(OH)D was 20.8 ± 9.3 ng/mL. Female patients had lower vitamin D concentrations than males (16.9 ng/mL vs. 23.9 ng/mL; p < 0.001). Vitamin D levels were also higher in Chinese (22.3 ng/mL) than Malay (17.3 ng/mL) and Indian (13.1 ng/mL) patients (p < 0.05). Nonadjusted analyses showed higher i-PTH concentration in vitamin D deficient patients (p < 0.05).
CONCLUSION: Despite being a sun-rich country all year round, the majority (86.8%) of predialysis CKD patients in Singapore have suboptimal vitamin D status. Lower vitamin D concentrations were found in females and in those with darker skin tone. Vitamin D deficient patients also tended to have higher i-PTH levels.
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.
OBJECTIVE: This study evaluated the associations of plasma carotenoid, retinol, tocopherol, and vitamin C concentrations and risk of breast cancer.
DESIGN: In a nested case-control study within the European Prospective Investigation into Cancer and Nutrition cohort, 1502 female incident breast cancer cases were included, with an oversampling of premenopausal (n = 582) and estrogen receptor-negative (ER-) cases (n = 462). Controls (n = 1502) were individually matched to cases by using incidence density sampling. Prediagnostic samples were analyzed for α-carotene, β-carotene, lycopene, lutein, zeaxanthin, β-cryptoxanthin, retinol, α-tocopherol, γ-tocopherol, and vitamin C. Breast cancer risk was computed according to hormone receptor status and age at diagnosis (proxy for menopausal status) by using conditional logistic regression and was further stratified by smoking status, alcohol consumption, and body mass index (BMI). All statistical tests were 2-sided.
RESULTS: In quintile 5 compared with quintile 1, α-carotene (OR: 0.61; 95% CI: 0.39, 0.98) and β-carotene (OR: 0.41; 95% CI: 0.26, 0.65) were inversely associated with risk of ER- breast tumors. The other analytes were not statistically associated with ER- breast cancer. For estrogen receptor-positive (ER+) tumors, no statistically significant associations were found. The test for heterogeneity between ER- and ER+ tumors was statistically significant only for β-carotene (P-heterogeneity = 0.03). A higher risk of breast cancer was found for retinol in relation to ER-/progesterone receptor-negative tumors (OR: 2.37; 95% CI: 1.20, 4.67; P-heterogeneity with ER+/progesterone receptor positive = 0.06). We observed no statistically significant interaction between smoking, alcohol, or BMI and all investigated plasma analytes (based on tertile distribution).
CONCLUSION: Our results indicate that higher concentrations of plasma β-carotene and α-carotene are associated with lower breast cancer risk of ER- tumors.