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: Given this information, this study systematically explores what risk factors may be associated with ADRD in Indigenous populations.
METHODS: A search of all published literature was conducted in October 2016, March 2018, and July 2019 using Medline, Embase, and PsychINFO. Subject headings explored were inclusive of all terms related to Indigenous persons, dementia, and risk. All relevant words, phrases, and combinations were used. To be included in this systematic review, articles had to display an association of a risk factor and ADRD. Only studies that reported a quantifiable measure of risk, involved human subjects, and were published in English were included.
RESULTS: Of 237 articles originally identified through database searches, 45 were duplicates and 179 did not meet a priori inclusion criteria, resulting in 13 studies eligible for inclusion in this systematic review.
CONCLUSION: The large number of potentially modifiable risk factors reported relative to non-modifiable risk factors illustrates the importance of socioeconomic context in the pathogenesis of ADRD in Indigenous populations. The tendency to prioritize genetic over social explanations when encountering disproportionately high disease rates in Indigenous populations can distract from modifiable proximal, intermediate, and distal determinants of health.
METHODS: A case-control study was conducted involving 600 people with type 2 diabetes (300 chronic kidney disease cases, 300 controls) who participated in The Malaysian Cohort project. Retrospective subanalysis was performed on the chronic kidney disease cases to assess chronic kidney disease progression from the recruitment phase. We genotyped 32 single nucleotide polymorphisms using mass spectrometry. The probability of chronic kidney disease and predicted rate of newly detected chronic kidney disease progression were estimated from the significant gene-environment interaction analyses.
RESULTS: Four single nucleotide polymorphisms (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and five environmental factors (age, sex, smoking, waist circumference and HDL) were significantly associated with chronic kidney disease. Gene-environment interaction analyses revealed significant probabilities of chronic kidney disease for sex (PPARGC1A rs8192678), smoking (eNOS rs2070744, PPARGC1A rs8192678 and KCNQ1 rs2237895), waist circumference (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and HDL (eNOS rs2070744 and PPARGC1A rs8192678). Subanalysis indicated that the rate of newly detected chronic kidney disease progression was 133 cases per 1000 person-years (95% CI: 115, 153), with a mean follow-up period of 4.78 (SD 0.73) years. There was a significant predicted rate of newly detected chronic kidney disease progression in gene-environment interactions between KCNQ1 rs2283228 and two environmental factors (sex and BMI).
CONCLUSIONS: Our findings suggest that the gene-environment interactions of eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228 with specific environmental factors could modify the probability for chronic kidney disease.
METHODS: This was a cross-sectional study of 22,210 adult men and women who underwent a comprehensive health screening examination between 2011 and 2013 (median age 40 years). Sugar-sweetened carbonated beverage consumption was assessed using a validated food frequency questionnaire, and CAC was measured by cardiac computed tomography. Multivariable-adjusted CAC score ratios and 95% CIs were estimated from robust Tobit regression models for the natural logarithm (CAC score +1).
RESULTS: The prevalence of detectable CAC (CAC score >0) was 11.7% (n = 2,604). After adjustment for age; sex; center; year of screening examination; education level; physical activity; smoking; alcohol intake; family history of cardiovascular disease; history of hypertension; history of hypercholesterolemia; and intake of total energy, fruits, vegetables, and red and processed meats, only the highest category of sugar-sweetened carbonated beverage consumption was associated with an increased CAC score compared with the lowest consumption category. The multivariable-adjusted CAC ratio comparing participants who consumed ≥5 sugar-sweetened carbonated beverages per week with nondrinkers was 1.70 (95% CI, 1.03-2.81). This association did not differ by clinical subgroup, including participants at low cardiovascular risk.
CONCLUSION: Our findings suggest that high levels of sugar-sweetened carbonated beverage consumption are associated with a higher prevalence and degree of CAC in asymptomatic adults without a history of cardiovascular disease, cancer, or diabetes.