Processed meat consumption and associated factors in Chile: A cross-sectional study nested in the MAUCO cohort.

Processed meat consumption is increasing in Latin America. While in developed countries processed meat consumption has been associated with cardiovascular diseases and cancer, our region lacks data associated to its consumption and health impact. We characterized processed meat intake and associated factors in a population-based cohort of a Chilean agricultural county, MAUCO. We analyzed baseline dietary data of 7,841 participants, 4,358 women and 3,483 men (38-77 years), who answered an adapted Mediterranean index food frequency questionnaire. Eight percent of the participants presented high processed meat consumption (≥5 times per week). We explored associations of processed meat consumption with participant characteristics using multinomial logistic regression models. Main factors associated with higher consumption were being men, younger and currently employed, and having a high intake (>4 times per week) of red meat (Odds ratio, 2.71, 95% CI 2.10-3.48), butter/cream (1.96, 1.60-2.41), whole-fat dairy products (1.32, 1.04-1.67) and a high intake (≥1 time per day) of sugary snacks/sweets (2.49, 2.04-3.03) and sugary drinks (1.97, 1.63-2.38). Processed meat consumption associated to chronic diseases, particularly cardiovascular disease (Prevalence ratio, 2.28, 95% CI 1.58-3.29). Obesity mediated this association in a proportion of 5.0%, whereas for diabetes the proportion was 13.9%. In this population, processed meat was associated with other unhealthy dietary and lifestyle factors, as well as with chronic diseases, particularly cardiovascular disease.

The Association between Fasting Glucose and Sugar Sweetened Beverages Intake Is Greater in Latin Americans with a High Polygenic Risk Score for Type 2 Diabetes Mellitus.

Chile is one of the largest consumers of sugar-sweetened beverages (SSB) world-wide. However, it is unknown whether the effects from this highly industrialized food will mimic those reported in industrialized countries or whether they will be modified by local lifestyle or population genetics. Our goal is to evaluate the interaction effect between SSB intake and T2D susceptibility on fasting glucose. We calculated a weighted genetic risk score (GRSw) based on 16 T2D risk SNPs in 2828 non-diabetic participants of the MAUCO cohort. SSB intake was categorized in four levels using a food frequency questionnaire. Log-fasting glucose was regressed on SSB and GRSw tertiles while accounting for socio-demography, lifestyle, obesity, and Amerindian ancestry. Fasting glucose increased systematically per unit of GRSw (ß = 0.02 ± 0.006, p = 0.00002) and by SSB intake (ß[cat4] = 0.04 ± 0.01, p = 0.0001), showing a significant interaction, where the strongest effect was observed in the highest GRSw-tertile and in the highest SSB consumption category (ß = 0.05 ± 0.02, p = 0.02). SNP-wise, SSB interacted with additive effects of rs7903146 (TCF7L2) (ß = 0.05 ± 0.01, p = 0.002) and with the G/G genotype of rs10830963 (MTNRB1B) (ß = 0.19 ± 0.05, p = 0.001). Conclusions: The association between SSB intake and fasting glucose in the Chilean population without diabetes is modified by T2D genetic susceptibility.