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.

METHODS AND FINDINGS: Utilising the Asian Sudden Cardiac Death in Heart Failure (ASIAN-HF) registry (11 Asian regions including Taiwan, Hong Kong, China, India, Malaysia, Thailand, Singapore, Indonesia, Philippines, Japan, and Korea; 46 centres with enrolment between 1 October 2012 and 6 October 2016), we prospectively examined 5,964 patients with symptomatic HF (mean age 61.3 ± 13.3 years, 26% women, mean BMI 25.3 ± 5.3 kg/m2, 16% with HF with preserved ejection fraction [HFpEF; ejection fraction ≥ 50%]), among whom 2,051 also had waist-to-height ratio (WHtR) measurements (mean age 60.8 ± 12.9 years, 24% women, mean BMI 25.0 ± 5.2 kg/m2, 7% HFpEF). Patients were categorised by BMI quartiles or WHtR quartiles or 4 combined groups of BMI (low, <24.5 kg/m2 [lean], or high, ≥24.5 kg/m2 [obese]) and WHtR (low, <0.55 [thin], or high, ≥0.55 [fat]). Cox proportional hazards models were used to examine a 1-year composite outcome (HF hospitalisation or mortality). Across BMI quartiles, higher BMI was associated with lower risk of the composite outcome (ptrend < 0.001). Contrastingly, higher WHtR was associated with higher risk of the composite outcome. Individuals in the lean-fat group, with low BMI and high WHtR (13.9%), were more likely to be women (35.4%) and to be from low-income countries (47.7%) (predominantly in South/Southeast Asia), and had higher prevalence of diabetes (46%), worse quality of life scores (63.3 ± 24.2), and a higher rate of the composite outcome (51/232; 22%), compared to the other groups (p < 0.05 for all). Following multivariable adjustment, the lean-fat group had higher adjusted risk of the composite outcome (hazard ratio 1.93, 95% CI 1.17-3.18, p = 0.01), compared to the obese-thin group, with high BMI and low WHtR. Results were consistent across both HF subtypes (HFpEF and HF with reduced ejection fraction [HFrEF]; pinteraction = 0.355). Selection bias and residual confounding are potential limitations of such multinational observational registries.

CONCLUSIONS: In this cohort of Asian patients with HF, the 'obesity paradox' is observed only when defined using BMI, with WHtR showing the opposite association with the composite outcome. Lean-fat patients, with high WHtR and low BMI, have the worst outcomes. A direct correlation between high WHtR and the composite outcome is apparent in both HFpEF and HFrEF.

METHODS: Online literature search databases including Scopus, Web of Science, PubMed/Medline, Embase and Google Scholar were searched to discover relevant articles available up to 17 March 2020. We used mean changes and SD of the outcomes to assess treatment response from baseline and mean difference, and 95 % CI were calculated to combined data and assessment effect sizes in astaxanthin and control groups.

RESULTS: 14 eligible articles were included in the final quantitative analysis. Current study revealed that astaxanthin consumption was not associated with FBS, HbA1c, TC, LDL-C, TG, BMI, BW, DBP, and SBP. We did observe an overall increase in HDL-C (WMD: 1.473 mg/dl, 95 % CI: 0.319-2.627, p = 0.012). As for the levels of CRP, only when astaxanthin was administered (i) for relatively long periods (≥ 12 weeks) (WMD: -0.528 mg/l, 95 % CI: -0.990 to -0.066), and (ii) at high dose (> 12 mg/day) (WMD: -0.389 mg/dl, 95 % CI: -0.596 to -0.183), the levels of CRP would decrease.