Objective To investigate factors associated with the prevalence and incidence of gallstone disease (GSD) in women and men of the MAUCO population-based prospective cohort. Design 8948 MAUCO participants (aged 38–74 years) underwent abdominal ultrasound at baseline (2015–2019); 4385 received follow-up ultrasound at years 2 or 4. Factors associated with prevalent GSD were assessed using Poisson multiple regression and with incident GSD using Cox regression models. Results GSD prevalence was 40.4% in women (13.1% gallstones, 27.3% cholecystectomies) and 17.1% in men (8.9% gallstones, 8.2% cholecystectomies). In men, GSD prevalence rate ratio (PRR) by age in >64 years was 3.85 (95% CI 3.00 to 4.94), doubling that of women’s PRR 1.78 (95% CI 1.57 to 2.01). In women, waist circumference and diabetes were stronger GSD factors; a higher number of children and worse metabolic and socioeconomic conditions were also highlighted. GSD men had higher cardiovascular disease and a family history of GSD and gallbladder cancer. 198 GSD cases developed during follow-up, with incidence increasing by 2% (95% CI 1.005% to 1.03%) per each centimetre above the ideal waist circumference, statistically significant only in women. In men, age was the strongest factor for incidence, followed by a family history of GSD and low high-density lipoprotein increased incidence risk. Conclusions GSD burden was high in this population; a third of women had their gallbladder removed, which may pose them at risk of other health problems. Abdominal obesity was the only preventable GSD risk factor, highlighting the need for effective public health policies promoting obesity reduction.

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 (β = 0.02 ± 0.006, p = 0.00002) and by SSB intake (β[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 (β = 0.05 ± 0.02, p = 0.02). SNP-wise, SSB interacted with additive effects of rs7903146 (TCF7L2) (β = 0.05 ± 0.01, p = 0.002) and with the G/G genotype of rs10830963 (MTNRB1B) (β = 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.

Pregnant women are normally screenedfor Gestational diabetes (GDM) at week 24 of pregnancy. Howeversome women develop the disease later on their pregnancies. No study has analyzed women developing GDM later in pregnancy. Objective: To analyze data on a cohort study and compare women diagnosed with GDM in second and third trimester of pregnancy with women without GDM. Results: GDM women diagnosed during their first two trimesters of pregnancy were older (p = 0.0008) and had higher body mass Índex (BMI) (p = 0.0007) than non GDM women. However, the only risk factor in women diagnosed in their third trimester of pregnancy was having first degree relatives with type 2 DM and this was independent of age and BMI (OR of2.7, 95% CI 1.2 - 6.0). Conclusions: Women who develop GDM in their second trimester of pregnancy have known risk factors for diabetes mellitus such as age and higher BMI, however, the only recognised risk factor between non GDM women and women developing GDM late in pregnancy is family history of type 2 DM. Two populations ofGDM may exist andfuture studies should focus on analysing short and long term complications ofthese women to support the need to diagnosed and treat them all.

ABO and Rhesus blood systems are associated with type 2 Diabetes Mellitus (DM2). Gestational Diabetes (GDM) is a model to study DM. To study the association between GDM and ABO and Rhesus groups. A retrospective cohort study was performed in 1,078 women who gave birth to a singleton in Talca Regional Hospital, Chile, during 2008. We analyzed personal, obstetric, medical data and ABO and Rh blood groups. GDM was diagnosed in 6.6% of women. Age and body mass index were significantly associated with GDM. There were no differences in Rh blood groups (p = 0.604), while ABO groups were different between GDM and controls. B antigen was present in 3% of GDM women and in 10.8% of controls (p = 0.037), with an odds ratio of 0.25 after adjusting for other associated risk factors (p = 0.06). ABO group is suggested as a possible protector marker for GDM.

This study aims to assess the performance of Steatotic Liver Disease (SLD) criteria in identifying liver steatosis compared to the NAFLD and MAFLD definitions in an agricultural population in Chile. We performed a cross-sectional analysis on the MAUCO cohort, composed of 9,013 individuals aged 38 to 74. Health conditions, socio-demographics, anthropometrics, hepatic ultrasonography, blood pressure, and biological samples were obtained. Participants were classified as NAFLD, MAFLD, or any of the five SLD categories: Metabolic dysfunction-associated steatosis liver disease (MASLD), Metabolic and Alcohol-Associated Liver Disease (MetALD), Alcohol-Associated Liver Disease (ALD), Specific aetiologies, and Cryptogenic. The Framingham cardiovascular risk score and BARD liver fibrosis score were used to assess clinical relevance. Liver steatosis was present in 4,082 participants (45%); SLD criteria captured an additional 176 individuals not classified under NAFLD and 103 not included under MAFLD definition. The main SLD subgroups were MASLD (95%), MetALD (1.9%) and ALD (1.3%). Individuals classified in the MetALD and ALD subgroups exhibited more severe liver steatosis and a higher cardiovascular risk. Notably, participants categorized under specific etiologies and cryptogenic subgroups were younger and had a higher risk for liver fibrosis. The study reveals that SLD offers a more inclusive classification to identify high-risk individuals in the Chilean population, capturing cases that could be missed by NAFLD or MAFLD definitions by using the same resources.

Background: Gestational diabetes mellitus (GDM) is a high incidence disease. Easily measured predictor factors could help to implement preventive policies and early detection tests. Aim: To measure recognizable risk factors for GDM such as skinfolds and analyze the association between these factors and the development of GDM in a cohort of pregnant women. Material and Methods: Evaluation of 76 mothers that developed gestational diabetes, aged 32.2 ± 0.6 years and 324 control mothers that did not develop the disease, aged 30.1 ± 0.3 years. Weight, height, arm circumference, tricipital, bicipital, subscapular, suprailiac, knee, costal and mid-thigh skinfolds were measured in the pre-diseased stage. History of diabetes, fasting glucose and insulin levels were also evaluated. Results: Age, body mass index (BMI), fasting blood glucose, the homeostasis model assessment of insulin resistance (HOMA), bi-cipital, tricipital, costal, subscapular, suprailiac, and knee skinfolds were associated with GDM development. Age, fasting blood glucose and subscapular skinfolds were independent predictors in the logistic regression model. The odds ratio for a subs-capular skinfold over percentile 90 was 1.7 (95% confdence intervals: 1.07-3.04). Conclusions: Age and fasting blood glucose are independent risk factors for GDM. Subscapular skinfold is also an independent risk factor and could be used to detect high risk pregnant women and implement preventive policies.