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Objective: Evidence from low- and middle-income countries regarding the effect of smoking in people with diabetes is lacking. Here, we report the association of smoking with mortality in a large cohort of Mexican adults with diabetes., Methods: Participants with diabetes mellitus (self-reported diagnosis, use of antidiabetic medications or HbA1c ≥ 6.5%) aged 35-74 years when recruited into the Mexico City Prospective Study were included. Cox regression confounder-adjusted mortality rate ratios (RRs) associated with baseline smoking status were estimated., Results: Among 15,975 women and 8225 men aged 35-74 years with diabetes but no other comorbidities at recruitment, 2498 (16%) women and 2875 (35%) men reported former smoking and 2753 (17%) women, and 3796 (46%) men reported current smoking. During a median of 17 years of follow-up there were 5087 deaths at ages 35-74 years. Compared with never smoking, all-cause mortality RR was 1.08 (95%CI 1.01-1.17) for former smoking, 1.11 (95%CI 1.03-1.20) for current smoking, 1.09 (95%CI 0.99-1.20) for non-daily smoking, 1.06 (95%CI 0.96-1.16) for smoking < 10 cigarettes/day (median during follow-up 4 cigarettes/day), and 1.28 (95% CI 1.14-1.43) for smoking ≥ 10 cigarettes/day (median during follow-up 15 cigarettes/day). Mortality risk among daily smokers was greatest for COPD, lung cancer, cardiovascular diseases, and acute diabetic complications., Conclusion: In this cohort of Mexican adults with diabetes, low-intensity daily smoking was associated with increased mortality, despite observing smoking patterns which are different from other populations, and over 5% of total deaths were associated with smoking., (© 2024. The Author(s).)

Objective: Older adults have heterogeneous aging rates. Here, we explored the impact of biological age (BA) and accelerated aging on frailty in community-dwelling older adults., Methods: We assessed 735 community-dwelling older adults from the Coyocan Cohort. BA was measured using AnthropoAge, accelerated aging with AnthropoAgeAccel, and frailty using both Fried's phenotype and the frailty index. We explored the association of BA and accelerated aging (AnthropoAgeAccel ≥0) with frailty at baseline and characterized the impact of both on body composition and physical function. We also explored accelerated aging as a risk factor for frailty progression after 3-years of follow-up., Results: Older adults with accelerated aging have higher frailty prevalence and indices, lower handgrip strength and gait speed. AnthropoAgeAccel was associated with higher frailty indices (β=0.0053, 95%CI 0.0027-0.0079), and increased odds of frailty at baseline (OR 1.16, 95%CI 1.09-1.25). We observed a sexual dimorphism in body composition and physical function linked to accelerated aging in non-frail participants; however, this dimorphism was absent in pre-frail/frail participants. Accelerated aging at baseline was associated with higher risk of frailty progression over time (OR 1.74, 95%CI 1.11-2.75)., Conclusions: Despite being intertwined, biological accelerated aging is largely independent of frailty in community-dwelling older adults., Competing Interests: CONFLICT OF INTERESTS: The authors declare that they have no conflict of interests.

Background and Aims: Remnant cholesterol (RC) and insulin resistance (IR) have been independently associated with cardiovascular risk. Here, we evaluated the role of IR and RC on cardiovascular disease (CVD) mortality., Methods: We conducted an analysis of 16,113 individuals ≥20 years without diabetes from the National Health and Nutrition Examination Survey (NHANES-III/IV). RC levels were calculated using total cholesterol, non-HDL-c, and LDL-c; IR was defined as HOMA2-IR≥2.5 and CVD mortality as a composite of cardiovascular and cerebrovascular mortality. Multiple linear regression was used to assess the relationship between HOMA2-IR and RC and Cox regression models to assess their joint role in CVD mortality. Causally ordered mediation models were used to explore the mediating role of IR in RC-associated CVD mortality., Results: We identified an association between higher HOMA2-IR and higher RC levels. The effect of IR on CVD mortality was predominant (HR 1.32, 95%CI 1.18-1.48) and decreased at older ages (HR 0.934, 95%CI 0.918-0.959) compared to RC (HR 0.983, 95%CI 0.952-1.014). Higher risk of CVD mortality was observed in individuals with IR but normal RC (HR 1.37, 95%CI 1.25-1.50) and subjects with IR and high RC (HR 1.24, 95%CI 1.13-1.37), but not in subjects without IR but high RC. In mediation models, HOMA2-IR accounted for 78.2% (95%CI 28.11-98.89) of the effect of RC levels on CVD mortality., Conclusions: Our findings suggest that RC potentiates the risk of CVD mortality through its effect on whole-body insulin sensitivity, particularly among younger individuals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To validate AnthropoAge, a new metric of biological age (BA), for prediction of all-cause mortality and age-related outcomes and characterize population-specific aging patterns using multinational longitudinal cohorts., Methods: We analyzed harmonized multinational data from the Gateway to Global Aging, including studies from the US, England, Mexico, Costa Rica, and China. We used body mass index and waist-to-height ratio to estimate AnthropoAge and AnthropoAgeAccel in participants aged 50-90 years old as proxies of BA and age acceleration, respectively. We compared the predictive capacity for all-cause mortality of AnthropoAge and chronological age (CA) using Cox models, described aging trends in all countries and explored the utility of longitudinal assessments of AnthropoAgeAccel to predict new-onset functional decline and age-related diseases using generalized estimating equations (GEE)., Findings: Using data from 55,628 participants, we found AnthropoAge (c-statistic 0.772) outperformed CA (0.76) for prediction of mortality independently of comorbidities, sex, race/ethnicity, education, and lifestyle; this result was replicated in most countries individually except for Mexico. Individuals with accelerated aging had a ~39% higher risk of death, and AnthropoAge also identified trends of faster biological aging per year. In longitudinal analyses, higher AnthropoAgeAccel values were independently predictive of self-reported health deterioration and new-onset deficits in basic/instrumental activities of daily living (ADL/IADL), diabetes, hypertension, cancer, chronic lung disease, myocardial infarction, and stroke., Conclusions: AnthropoAge is a robust and reproducible BA metric associated with age-related outcomes. Its implementation could facilitate modeling trends of biological aging acceleration in different populations, although recalibration may enhance its utility in underrepresented populations such as individuals from Latin America., Competing Interests: CONFLICT OF INTEREST/FINANCIAL DISCLOSURE: Nothing to disclose. CONFLICT OF INTERESTS: The authors declare that they have no conflict of interests.

Background: Differences in the prevalence of four diabetes subgroups have been reported in Mexico compared to other populations, but factors that may contribute to these differences are poorly understood. Here, we estimate the prevalence of diabetes subgroups in Mexico and evaluate their correlates with indicators of social disadvantage using data from national representative surveys., Methods: We analyzed serial, cross-sectional Mexican National Health and Nutrition Surveys spanning 2016, 2018, 2020, 2021, and 2022, including 23,354 adults (>20 years). Diabetes subgroups (obesity-related [MOD], severe insulin-deficient [SIDD], severe insulin-resistant [SIRD], and age-related [MARD]) were classified using self-normalizing neural networks based on a previously validated algorithm. We used the density-independent social lag index (DISLI) as a proxy of state-level social disadvantage., Findings: We identified 4204 adults (median age: 57, IQR: 47-66, women: 64%) living with diabetes, yielding a pooled prevalence of 16.04% [95% CI: 14.92-17.17]. When stratified by diabetes subgroup, prevalence was 6.62% (5.69-7.55) for SIDD, 5.25% (4.52-5.97) for MOD, 2.39% (1.95-2.83) for MARD, and 1.27% (1.00-1.54) for SIRD. SIDD and MOD clustered in Southern Mexico, whereas MARD and SIRD clustered in Northern Mexico and Mexico City. Each standard deviation increase in DISLI was associated with higher odds of SIDD (OR: 1.12, 95% CI: 1.06-1.12) and lower odds of MOD (OR: 0.93, 0.88-0.99). Speaking an indigenous language was associated with higher odds of SIDD (OR: 1.35, 1.16-1.57) and lower odds of MARD (OR 0.58, 0.45-0.74)., Interpretation: Diabetes prevalence in Mexico is rising in the context of regional and sociodemographic inequalities across distinct diabetes subgroups. SIDD is a subgroup of concern that may be associated with inadequate diabetes management, mainly in marginalized states., Funding: This research was supported by Instituto Nacional de Geriatría in Mexico., Competing Interests: The authors declare that they have no competing interests., (© 2024 The Author(s).)

Background: Post-acute sequelae after SARS-CoV-2 infection (PASC) remains a concerning long-term complication of COVID-19. Here, we aimed to characterize the epidemiology of PASC in Mexico during 2022 and identify potential associations of covariates with PASC prevalence using nationally representative data., Methods: We analyzed data from the 2022 Mexican National Health and Nutrition Survey (ENSANUT) from 24,434 participants, representing 85,521,661 adults ≥20 years. PASC was defined using both the National Institute for Health and Care Excellence (NICE) definition and a PASC score ≥12. Estimates of PASC prevalence were stratified by age, sex, rural vs. urban setting, social lag quartiles, number of reinfections, vaccination status and periods of predominance of SARS-CoV-2 circulating variants. Determinants of PASC were assessed using log-binomial regression models adjusted by survey weights., Findings: Persistent symptoms after SARS-CoV-2 infection were reported by 12.44% (95% CI 11.89-12.99) of adults ≥20 years in Mexico in 2022. The most common persistent symptoms were fatigue, musculoskeletal pain, headache, cough, loss of smell or taste, fever, post-exertional malaise, brain fog, anxiety, and chest pain. PASC was present in 21.21% (95% CI 19.74-22.68) of subjects with previously diagnosed COVID-19. Over 28.6% of patients with PASC reported symptoms persistence ≥6 months and 14.05% reported incapacitating symptoms. Higher PASC prevalence was associated with SARS-CoV-2 reinfections, depressive symptoms and living in states with high social lag. PASC prevalence, particularly its more severe forms, decreased with COVID-19 vaccination and for infections during periods of Omicron variant predominance., Interpretation: PASC remains a significant public health burden in Mexico as the COVID-19 pandemic transitions into endemic. Promoting SARS-CoV-2 reinfection prevention and booster vaccination may be useful in reducing PASC burden., Funding: This research was supported by Instituto Nacional de Geriatría in Mexico., Competing Interests: Nothing to disclose., (© 2024 The Author(s).)

Background: Characterizing prediabetes phenotypes may be useful in guiding diabetes prevention efforts; however, heterogeneous criteria to define prediabetes have led to inconsistent prevalence estimates, particularly in low- and middle-income countries. Here, we estimated trends in prediabetes prevalence in Mexico across different prediabetes definitions and their association with prevalent cardiometabolic conditions., Methods: We conducted a serial cross-sectional analysis of National Health and Nutrition Surveys in Mexico (2016-2022), totalling 22 081 Mexican adults. After excluding individuals with diagnosed or undiagnosed diabetes, we defined prediabetes using ADA (impaired fasting glucose [IFG] 100-125 mg/dL and/or HbA1c 5.7-6.4%), WHO (IFG 110-125 mg/dL), and IEC criteria (HbA1c 6.0-6.4%). Prevalence trends of prediabetes over time were evaluated using weighted Poisson regression and its association with prevalent cardiometabolic conditions with weighted logistic regression., Findings: The prevalence of prediabetes (either IFG or high HbA1c [ADA]) in Mexico was 20.9% in 2022. Despite an overall downward trend in prediabetes (RR 0.973, 95% CI 0.957-0.988), this was primarily driven by decreases in prediabetes by ADA-IFG (RR 0.898, 95% CI 0.880-0.917) and WHO-IFG criteria (RR 0.919, 95% CI 0.886-0.953), while prediabetes by ADA-HbA1c (RR 1.055, 95% CI 1.033-1.077) and IEC-HbA1C criteria (RR 1.085, 95% CI 1.045-1.126) increased over time. Prediabetes prevalence increased over time in adults >40 years, with central obesity, self-identified as indigenous or living in urban areas. For all definitions, prediabetes was associated with an increased risk of cardiometabolic conditions., Interpretation: Prediabetes rates in Mexico from 2016 to 2022 varied based on defining criteria but consistently increased for HbA1c-based definitions and high-risk subgroups., Funding: This research was supported by Instituto Nacional de Geriatría in Mexico. JAS was supported by NIH/NIDDK Grant# K23DK135798., Competing Interests: The authors declare that they have no competing interests., (© 2023 The Author(s).)

Competing Interests: Nothing to disclose.

Background: With the widespread transmission of the Omicron SARS-CoV-2 variant, reinfections have become increasingly common. Here, we explored the role of immunity, primary infection severity, and variant predominance in the risk of reinfection and severe COVID-19 during Omicron predominance in Mexico., Methods: We analyzed reinfections in Mexico in individuals with a primary infection separated by at least 90 days from reinfection using a national surveillance registry of SARS-CoV-2 cases from March 3rd, 2020, to August 13th, 2022. Immunity-generating events included primary infection, partial or complete vaccination, and booster vaccines. Reinfections were matched by age and sex with controls with primary SARS-CoV-2 infection and negative RT-PCR or antigen test at least 90 days after primary infection to explore reinfection and severe disease risk factors. We also compared the protective efficacy of heterologous and homologous vaccine boosters against reinfection., Results: We detected 231,202 SARS-CoV-2 reinfections in Mexico, most occurring in unvaccinated individuals (41.55%). Over 207,623 reinfections occurred during periods of Omicron (89.8%), BA.1 (36.74%), and BA.5 (33.67%) subvariant predominance and a case-fatality rate of 0.22%. Vaccination protected against reinfection, without significant influence of the order of immunity-generating events and provided >90% protection against severe reinfections. Heterologous booster schedules were associated with ~11% and ~ 54% lower risk for reinfection and reinfection-associated severe COVID-19, respectively, modified by time-elapsed since the last immunity-generating event, when compared against complete primary schedules., Conclusion: SARS-CoV-2 reinfections increased during Omicron predominance. Hybrid immunity provides protection against reinfection and associated severe COVID-19, with potential benefit from heterologous booster schedules., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Montes-González, Zaragoza-Jiménez, Antonio-Villa, Fermín-Martínez, Ramírez-García, Vargas-Vázquez, Gutiérrez-Vargas, García-Rodríguez, López-Gatell, Valdés-Ferrer and Bello-Chavolla.)

Objectives: Vaccination has been effective in ameliorating the impact of COVID-19. Here, we report vaccine effectiveness (VE) of the nationally available COVID-19 vaccines in Mexico., Methods: Retrospective analysis of a COVID-19 surveillance system to assess the VE of the BNT162b2, messenger RNA (mRNA)-12732, Gam-COVID-Vac, Ad5-nCoV, Ad26.COV2.S, ChAdOx1, and CoronaVac vaccines against SARS-CoV-2 infection, COVID-19 hospitalization, and death in Mexico. The VE was estimated using time-varying Cox proportional hazard models in vaccinated and unvaccinated adults, adjusted for age, sex, and comorbidities. VE was also estimated for adults with diabetes, aged ≥60 years, and comparing the predominance of SARS-CoV-2 variants B.1.1.519 and B.1.617.2., Results: We assessed 793,487 vaccinated and 4,792,338 unvaccinated adults between December 24, 2020 and September 27, 2021. The VE against SARS-CoV-2 infection was the highest for fully vaccinated individuals with mRNA-12732 (91.5%, 95% confidence interval [CI] 90.3-92.4) and Ad26.COV2.S (82.2%, 95% CI 81.4-82.9); for COVID-19 hospitalization, BNT162b2 (84.3%, 95% CI 83.6-84.9) and Gam-COVID-Vac (81.4% 95% CI 79.5-83.1), and for mortality, BNT162b2 (89.8%, 95% CI 89.2-90.2) and mRNA-12732 (93.5%, 95% CI 86.0-97.0). The VE decreased for all vaccines in adults aged ≥60 years, people with diabetes, and periods of Delta variant predominance., Conclusion: All the vaccines implemented in Mexico were effective against SARS-CoV-2 infection, COVID-19 hospitalization, and death. Mass vaccination with multiple vaccines is useful to maximize vaccination coverage., Competing Interests: Declaration of competing interest SECL, GCS, CAZJ, GGR, RCA, and HLG works at the Mexican Ministry of Health and oversee the monitoring SARS-CoV-2 epidemiological surveillance and designing COVID-19 vaccination policies in Mexico. Data analysis and interpretation were primarily conducted by members of the team independent of these duties., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Aging is believed to occur across multiple domains, one of which is body composition; however, attempts to integrate it into biological age (BA) have been limited. Here, we consider the sex-dependent role of anthropometry for the prediction of 10-year all-cause mortality using data from 18,794 NHANES participants to generate and validate a new BA metric. Our data-driven approach pointed to sex-specific contributors for BA estimation: WHtR, arm and thigh circumferences for men; weight, WHtR, thigh circumference, subscapular and triceps skinfolds for women. We used these measurements to generate AnthropoAge, which predicted all-cause mortality (AUROC 0.876, 95%CI 0.864-0.887) and cause-specific mortality independently of ethnicity, sex, and comorbidities; AnthropoAge was a better predictor than PhenoAge for cerebrovascular, Alzheimer, and COPD mortality. A metric of age acceleration was also derived and used to assess sexual dimorphisms linked to accelerated aging, where women had an increase in overall body mass plus an important subcutaneous to visceral fat redistribution, and men displayed a marked decrease in fat and muscle mass. Finally, we showed that consideration of multiple BA metrics may identify unique aging trajectories with increased mortality (HR for multidomain acceleration 2.43, 95%CI 2.25-2.62) and comorbidity profiles. A simplified version of AnthropoAge (S-AnthropoAge) was generated using only BMI and WHtR, all results were preserved using this metric. In conclusion, AnthropoAge is a useful proxy of BA that captures cause-specific mortality and sex dimorphisms in body composition, and it could be used for future multidomain assessments of aging to better characterize the heterogeneity of this phenomenon., (© 2022 The Authors. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.)

Background: In 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent of non-COVID deaths on excess mortality, its regional distribution and the association between socio-demographic inequalities have not been characterized., Methods: We conducted a retrospective municipal and individual-level study using 1 069 174 death certificates to analyse COVID-19 and non-COVID-19 deaths classified by ICD-10 codes. Excess mortality was estimated as the increase in cause-specific mortality in 2020 compared with the average of 2015-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. Correlates of individual and municipal non-COVID-19 mortality were assessed using mixed effects logistic regression and negative binomial regression models, respectively., Results: We identified a 51% higher mortality rate (276.11 deaths per 100 000 inhabitants) compared with the 2015-2019 average period, largely attributable to COVID-19. Non-COVID-19 causes comprised one-fifth of excess deaths, with acute myocardial infarction and type 2 diabetes as the two leading non-COVID-19 causes of excess mortality. COVID-19 deaths occurred primarily in-hospital, whereas excess non-COVID-19 deaths occurred in out-of-hospital settings. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization and social marginalization. At the individual level, lower educational attainment, blue-collar employment and lack of medical care assistance prior to death were associated with non-COVID-19 deaths., Conclusion: Non-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual- and municipal-level socio-demographic inequalities., (© The Author(s) 2022; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Objective: To estimate diabetes-related mortality in Mexico in 2020 compared with 2017-2019 after the onset of the coronavirus disease 2019 (COVID-19) pandemic., Research Design and Methods: This retrospective, state-level study used national death registries of Mexican adults aged ≥20 years for the 2017-2020 period. Diabetes-related death was defined using ICD-10 codes listing diabetes as the primary cause of death, excluding certificates with COVID-19 as the primary cause of death. Spatial and negative binomial regression models were used to characterize the geographic distribution and sociodemographic and epidemiologic correlates of diabetes-related excess mortality, estimated as increases in diabetes-related mortality in 2020 compared with average 2017-2019 rates., Results: We identified 148,437 diabetes-related deaths in 2020 (177 per 100,000 inhabitants) vs. an average of 101,496 deaths in 2017-2019 (125 per 100,000 inhabitants). In-hospital diabetes-related deaths decreased by 17.8% in 2020 versus 2017-2019, whereas out-of-hospital deaths increased by 89.4%. Most deaths were attributable to type 2 diabetes (130 per 100,000 inhabitants). Compared with 2018-2019 data, hyperglycemic hyperosmolar state and diabetic ketoacidosis were the two contributing causes with the highest increase in mortality (128% and 116% increase, respectively). Diabetes-related excess mortality clustered in southern Mexico and was highest in states with higher social lag, rates of COVID-19 hospitalization, and prevalence of HbA1c ≥7.5%., Conclusions: Diabetes-related deaths increased among Mexican adults by 41.6% in 2020 after the onset of the COVID-19 pandemic, occurred disproportionately outside the hospital, and were largely attributable to type 2 diabetes and hyperglycemic emergencies. Disruptions in diabetes care and strained hospital capacity may have contributed to diabetes-related excess mortality in Mexico during 2020., (© 2022 by the American Diabetes Association.)

Arterial stiffness may be associated with glucose metabolism parameters, such as HbA1c, mainly via insulin resistance. We aimed to investigate the association between arterial stiffness and HbA1c and explore the mediator effect of insulin resistance. In this cross-sectional study, arterial stiffness (pulse-wave velocity; PWV), HbA1c, and insulin resistance (METS-IR) were determined in Hispanic adults. In addition to sex and age, various biochemical measurements (glucose, lipid profile, etc.) and adipose tissue (fat mass and visceral fat mass) were considered as potential confounding variables. A multivariate regression analysis shows that HbA1c is associated with PWV, even after adjusting for several confounding variables. Importantly, the results show that insulin resistance mediated 17.9% of the effect of HbA1c over PWV. In conclusion, HbA1c may be a potential resource for predicting arterial stiffness due to the influence of insulin resistance in Hispanic subjects.

Objective: To externally validate various prognostic models and scoring rules for predicting short term mortality in patients admitted to hospital for covid-19., Design: Two stage individual participant data meta-analysis., Setting: Secondary and tertiary care., Participants: 46 914 patients across 18 countries, admitted to a hospital with polymerase chain reaction confirmed covid-19 from November 2019 to April 2021., Data Sources: Multiple (clustered) cohorts in Brazil, Belgium, China, Czech Republic, Egypt, France, Iran, Israel, Italy, Mexico, Netherlands, Portugal, Russia, Saudi Arabia, Spain, Sweden, United Kingdom, and United States previously identified by a living systematic review of covid-19 prediction models published in The BMJ , and through PROSPERO, reference checking, and expert knowledge., Model Selection and Eligibility Criteria: Prognostic models identified by the living systematic review and through contacting experts. A priori models were excluded that had a high risk of bias in the participant domain of PROBAST (prediction model study risk of bias assessment tool) or for which the applicability was deemed poor., Methods: Eight prognostic models with diverse predictors were identified and validated. A two stage individual participant data meta-analysis was performed of the estimated model concordance (C) statistic, calibration slope, calibration-in-the-large, and observed to expected ratio (O:E) across the included clusters., Main Outcome Measures: 30 day mortality or in-hospital mortality., Results: Datasets included 27 clusters from 18 different countries and contained data on 46 914patients. The pooled estimates ranged from 0.67 to 0.80 (C statistic), 0.22 to 1.22 (calibration slope), and 0.18 to 2.59 (O:E ratio) and were prone to substantial between study heterogeneity. The 4C Mortality Score by Knight et al (pooled C statistic 0.80, 95% confidence interval 0.75 to 0.84, 95% prediction interval 0.72 to 0.86) and clinical model by Wang et al (0.77, 0.73 to 0.80, 0.63 to 0.87) had the highest discriminative ability. On average, 29% fewer deaths were observed than predicted by the 4C Mortality Score (pooled O:E 0.71, 95% confidence interval 0.45 to 1.11, 95% prediction interval 0.21 to 2.39), 35% fewer than predicted by the Wang clinical model (0.65, 0.52 to 0.82, 0.23 to 1.89), and 4% fewer than predicted by Xie et al's model (0.96, 0.59 to 1.55, 0.21 to 4.28)., Conclusion: The prognostic value of the included models varied greatly between the data sources. Although the Knight 4C Mortality Score and Wang clinical model appeared most promising, recalibration (intercept and slope updates) is needed before implementation in routine care., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: funding from the European Union’s Horizon 2020 research and innovation programme. ML and FWA have received grants from the Dutch Heart Foundation and ZonMw; FWA has received grants from Novartis Global, Sanofi Genzyme Europe, EuroQol Research Foundation, Novo Nordisk Nederland, Servier Nederland, and Daiichi Sankyo Nederland, and MM has received grants from Czech Ministry of Education, Youth and Sports for the submitted work; RKG has received grants from National Institute for Health and Care Research; FS has received an AWS DDI grant and grants from University of Sheffield and DBCLS; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; TD works with International Societiy for Pharmacoepidemiology Comparative Effectiveness Research Special Interest Group (ISPE CER SIG) on methodological topics related to covid-19 (non-financial); no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Serum uric acid (SUA) has been associated with cardiometabolic conditions such as insulin resistance (IR) and visceral adipose tissue (VAT) accumulation. Here, we aimed to clarify a unifying mechanism linking elevated SUA to IR and VAT., Methods: We conducted analyses in 226 subjects from the UIEM cohort with both euglycemic hyperinsulinemic clamp (EHC) and dual X-ray absorptiometry (DXA) measurements for IR and VAT accumulation and explored the role of SUA and adiponectin by developing a network of causal mediation analyses to assess their impact on IR and VAT. These models were then translated to two population-based cohorts comprising 6337 subjects from NHANES 2003-2004 and 2011-2012 cycles in the US and ENSANUT Medio Camino 2016 in Mexico, using HOMA2IR and adipoIR as indicators of peripheral and adipose tissue IR, and METS-VF as a surrogate for VAT accumulation., Results: SUA has a mediating role inside a bidirectional relationship between IR and visceral obesity, which was similar using either gold standard measurements or surrogate measures for IR and VAT. Furthermore, adiponectin acts as a linking mediator between elevated SUA and both peripheral IR and VAT accumulation. The proportion of the mechanism for IR-mediated (in either peripheral or adipose tissue) VAT accumulation was greater, compared to VAT-mediated IR accumulation (10.53% [9.23%-12.00%] to 5.44% [3.78%-7.00%]). Normal-range SUA levels can be used to rule-out underlying cardio-metabolic abnormalities in both men and women., Conclusions: Elevated SUA acts as a mediator inside the bidirectional relationship between IR and VAT accumulation and these observations could be applicable at a phenotype scale., (© 2022 John Wiley & Sons Ltd.)

Background: The impact of the coronavirus disease 2019 (COVID-19) pandemic in Mexico City has been sharp, as several social inequalities at all levels coexist. Here we conducted an in-depth evaluation of the impact of individual and municipal-level social inequalities on the COVID-19 pandemic in Mexico City., Methods: We analyzed suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, from the Mexico City Epidemiological Surveillance System from 24 February 2020 to 31 March 2021. COVID-19 outcomes included rates of hospitalization, severe COVID-19, invasive mechanical ventilation, and mortality. We evaluated socioeconomic occupation as an individual risk, and social lag, which captures municipal-level social vulnerability, and urban population density as proxies of structural risk factors. Impact of reductions in vehicular mobility on COVID-19 rates and the influence of risk factors were also assessed. Finally, we assessed discrepancies in COVID-19 and non-COVID-19 excess mortality using death certificates from the general civil registry., Results: We detected vulnerable groups who belonged to economically unfavored sectors and experienced increased risk of COVID-19 outcomes. Cases living in marginalized municipalities with high population density experienced greater risk for COVID-19 outcomes. Additionally, policies to reduce vehicular mobility had differential impacts modified by social lag and urban population density. Finally, we report an under-registry of COVID-19 deaths along with an excess mortality closely related to marginalized and densely populated communities in an ambulatory setting. This could be attributable to a negative impact of modified hospital admission criteria during the pandemic., Conclusions: Socioeconomic occupation and municipality-wide factors played a significant role in shaping the course of the COVID-19 pandemic in Mexico City., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Context: Data-driven diabetes subgroups were proposed as an alternative to address diabetes heterogeneity. However, changes in trends for these subgroups have not been reported., Objective: Here, we analyzed trends of diabetes subgroups, stratified by sex, race, education level, age categories, and time since diabetes diagnosis in the United States., Methods: We used data from consecutive NHANES cycles spanning the 1988-2018 period. Diabetes subgroups (mild obesity-related [MOD], severe insulin-deficient [SIDD], severe insulin-resistant [SIRD], and mild age-related diabetes [MARD]) were classified using validated self-normalizing neural networks. Severe autoimmune diabetes (SAID) was assessed for NHANES-III. Prevalence was estimated using examination sample weights considering bicyclic changes (BCs) to evaluate trends and changes over time., Results: Diabetes prevalence in the United States increased from 7.5% (95% CI 7.1-7.9) in 1988-1989 to 13.9% (95% CI 13.4-14.4) in 2016-2018 (BC 1.09%, 95% CI 0.98-1.31, P < .001). Non-Hispanic Black people had the highest prevalence. Overall, MOD, MARD, and SIDD had an increase during the studied period. Particularly, non-Hispanic Black people had sharp increases in MARD and SIDD, Mexican Americans in SIDD, and non-Hispanic White people in MARD. Males, subjects with secondary/high school, and adults aged 40-64 years had the highest increase in MOD prevalence. Trends in diabetes subgroups sustained after stratifying time since diabetes diagnosis., Conclusion: Prevalence of diabetes and its subgroups in the United States has increased from 1988 to 2018. These trends were different across sex, ethnicities, education, and age categories, indicating significant heterogeneity in diabetes within the US obesity burden, population aging, socioeconomic disparities, and lifestyle aspects could be implicated in the increasing trends of diabetes in the United States., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: SARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico., Methods: We analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n = 6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n = 216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality., Results: Rapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6-38.7), high specificity 95.5% (95%CI 95.1-95.8) and acceptable positive 86.1% (95%CI 85.0-86.6) and negative predictive values 67.2% (95%CI 66.2-69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41-1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and ≥7 days from symptom onset (HR 1.53 95% CI 1.48-1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course., Conclusions: Rapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results., Competing Interests: The authors have declared that no competing interests exist.

Background: Chronological age (CA) is a predictor of adverse coronavirus disease 2019 (COVID-19) outcomes; however, CA alone does not capture individual responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components., Method: In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (intensive care unit admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components., Results: We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel >0 had higher risk of death and critical illness compared to those with lower values (log-rank p < .001). Using unsupervised clustering, we identified 4 adaptive responses to SARS-CoV-2 infection: (i) inflammaging associated with CA, (ii) metabolic dysfunction associated with cardiometabolic comorbidities, (iii) unfavorable hematological response, and (iv) response associated with favorable outcomes., Conclusions: Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Healthcare workers (HCWs) could be at increased occupational risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections due to increased exposure. Information regarding the burden of coronavirus disease 2019 (COVID-19) epidemic in HCWs living in Mexico is scarce. Here, we aimed to explore the epidemiology, symptoms, and risk factors associated with adverse outcomes in HCWs in Mexico City., Methods: We explored data collected by the National Epidemiological Surveillance System in Mexico City, in HCWs who underwent real-time reverse transcription polymerase chain reaction (RT-PCR) test. We explored COVID-19 outcomes in HCWs and the performance of symptoms to detect SARS-CoV-2 infection., Results: As of 20 September 2020, 57 758 HCWs were tested for SARS-CoV-2 and 17 531 were confirmed (30.35%); 6610 were nurses (37.70%), 4910 physicians (28.0%), 267 dentists (1.52%), and 5744 laboratory personnel and other HCWs (32.76%). Overall, 2378 HCWs required hospitalization (4.12%), 2648 developed severe COVID-19 (4.58%), and 336 required mechanical-ventilatory support (.58%). Lethality was recorded in 472 (.82%) cases. We identified 635 asymptomatic SARS-CoV-2 infections (3.62%). Compared with general population, HCWs had higher incidence, testing, asymptomatic cases, and mortality rates. No individual symptom offers adequate performance to detect SARS-CoV2. Older HCWs with chronic noncommunicable diseases and severe respiratory symptoms were associated with higher risk for adverse outcome; physicians were at higher risk compared with nurses and other HCWs., Conclusions: We report a high prevalence of SARS-CoV-2 infection in HCWs in Mexico City. Symptoms as a screening method are not efficient to discern those HCWs with a positive PCR-RT test. Particular attention should focus on HCWs with risk factors to prevent adverse outcomes., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

We profiled cases with nonrespiratory symptoms (NRS) and asymptomatic severe acute respiratory syndrome coronavirus 2 infections assessed within Mexico City's Epidemiological Surveillance System. Initially asymptomatic or NRS cases have decreased risk of adverse outcomes compared with cases with respiratory symptoms. Comorbidity and age influence symptom development in initially asymptomatic cases., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: COVID-19 has had a disproportionate impact on older adults. Mexico's population is younger, yet COVID-19's impact on older adults is comparable to countries with older population structures. Here, we aim to identify health and structural determinants that increase susceptibility to COVID-19 in older Mexican adults beyond chronological aging., Methods: We analyzed confirmed COVID-19 cases in older adults using data from the General Directorate of Epidemiology of Mexican Ministry of Health. We modeled risk factors for increased COVID-19 severity and mortality, using mixed models to incorporate multilevel data concerning healthcare access and marginalization. We also evaluated structural factors and comorbidity profiles compared to chronological age for COVID-19 mortality risk prediction., Results: We analyzed 20 804 confirmed SARS-CoV-2 cases in adults aged 60 and older. Male sex, smoking, diabetes, and obesity were associated with pneumonia, hospitalization, and intensive care unit (ICU) admission in older adults, CKD and COPD were associated with hospitalization. High social lag indexes and access to private care were predictors of COVID-19 severity and mortality. Age was not a predictor of COVID-19 severity in individuals without comorbidities and combination of structural factors and comorbidities were better predictors of COVID-19 lethality and severity compared to chronological age alone. COVID-19 baseline lethality hazards were heterogeneously distributed across Mexican municipalities, particularly when comparing urban and rural areas., Conclusions: Structural factors and comorbidity explain excess risk for COVID-19 severity and mortality over chronological age in older Mexican adults. Clinical decision-making related to COVID-19 should focus away from chronological aging onto more a comprehensive geriatric care approach., (© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background and Aims: Both insulin resistance (IR) and visceral adipose tissue (VAT) are related cardiometabolic risk factors; nevertheless, their joint effect on endothelial functionality is controversial. This study aims to evaluate the joint effect of IR and VAT on endothelial functionality using the pulse-waveform analysis and explore the mediating role of VAT on the effect of IR on arterial pressure, arterial stiffness and incident arterial hypertension., Methods and Results: We measured VAT (n = 586) using two methods (dual-energy X-ray absorptiometry and a clinical surrogate), arterial stiffness (with pulse-waveform velocity), and IR (using three methods: HOMA2-IR (n = 586), a frequently sampled intravenous glucose tolerance test (n = 131) and euglycemic hyperinsulinemic clamping (n = 97)) to confirm the mediator effect of IR on VAT. The incidence of arterial hypertension attributable to the mediating effect of IR related to VAT was evaluated using a prospective cohort (n = 6850). Adjusted linear regression models, causal mediation analysis, and Cox-proportional hazard risk regression models were performed to test our objective. IR and VAT led to increased arterial stiffness and increased blood pressure; the combination of both further worsened vascular parameters. Nearly, 57% (Δ E→MY 95% CI: 31.7-100.0) of the effect of IR on altered pulse-wave velocity (PWV) analysis was mediated through VAT. Moreover, VAT acts as a mediator of the effect of IR on increased mean arterial pressure (Δ E→MY 35.7%, 95% CI: 23.8-59) and increased hypertension risk (Δ E→MY 69.1%, 95% CI: 46.1-78.8)., Conclusion: VAT acts as a mediator of IR in promoting arterial stiffness and arterial hypertension. Both phenomena should be targeted to ameliorate the cardiometabolic risk., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interests., (Copyright © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Background: The SARS-CoV-2 outbreak poses a challenge to health care systems due to its high complication rates in patients with cardiometabolic diseases. Here, we identify risk factors and propose a clinical score to predict COVID-19 lethality, including specific factors for diabetes and obesity, and its role in improving risk prediction., Methods: We obtained data of confirmed and negative COVID-19 cases and their demographic and health characteristics from the General Directorate of Epidemiology of the Mexican Ministry of Health. We investigated specific risk factors associated to COVID-19 positivity and mortality and explored the impact of diabetes and obesity on modifying COVID-19-related lethality. Finally, we built a clinical score to predict COVID-19 lethality., Results: Among the 177 133 subjects at the time of writing this report (May 18, 2020), we observed 51 633 subjects with SARS-CoV-2 and 5,332 deaths. Risk factors for lethality in COVID-19 include early-onset diabetes, obesity, chronic obstructive pulmonary disease, advanced age, hypertension, immunosuppression, and chronic kidney disease (CKD); we observed that obesity mediates 49.5% of the effect of diabetes on COVID-19 lethality. Early-onset diabetes conferred an increased risk of hospitalization and obesity conferred an increased risk for intensive care unit admission and intubation. Our predictive score for COVID-19 lethality included age ≥ 65 years, diabetes, early-onset diabetes, obesity, age < 40 years, CKD, hypertension, and immunosuppression and significantly discriminates lethal from non-lethal COVID-19 cases (C-statistic = 0.823)., Conclusions: Here, we propose a mechanistic approach to evaluate the risk for complications and lethality attributable to COVID-19, considering the effect of obesity and diabetes in Mexico. Our score offers a clinical tool for quick determination of high-risk susceptibility patients in a first-contact scenario., (© Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: Previous reports in European populations demonstrated the existence of five data-driven adult-onset diabetes subgroups. Here, we use self-normalizing neural networks (SNNN) to improve reproducibility of these data-driven diabetes subgroups in Mexican cohorts to extend its application to more diverse settings., Research Design and Methods: We trained SNNN and compared it with k-means clustering to classify diabetes subgroups in a multiethnic and representative population-based National Health and Nutrition Examination Survey (NHANES) datasets with all available measures (training sample: NHANES-III, n=1132; validation sample: NHANES 1999-2006, n=626). SNNN models were then applied to four Mexican cohorts (SIGMA-UIEM, n=1521; Metabolic Syndrome cohort, n=6144; ENSANUT 2016, n=614 and CAIPaDi, n=1608) to characterize diabetes subgroups in Mexicans according to treatment response, risk for chronic complications and risk factors for the incidence of each subgroup., Results: SNNN yielded four reproducible clinical profiles (obesity related, insulin deficient, insulin resistant, age related) in NHANES and Mexican cohorts even without C-peptide measurements. We observed in a population-based survey a high prevalence of the insulin-deficient form (41.25%, 95% CI 41.02% to 41.48%), followed by obesity-related (33.60%, 95% CI 33.40% to 33.79%), age-related (14.72%, 95% CI 14.63% to 14.82%) and severe insulin-resistant groups. A significant association was found between the SLC16A11 diabetes risk variant and the obesity-related subgroup (OR 1.42, 95% CI 1.10 to 1.83, p=0.008). Among incident cases, we observed a greater incidence of mild obesity-related diabetes (n=149, 45.0%). In a diabetes outpatient clinic cohort, we observed increased 1-year risk (HR 1.59, 95% CI 1.01 to 2.51) and 2-year risk (HR 1.94, 95% CI 1.13 to 3.31) for incident retinopathy in the insulin-deficient group and decreased 2-year diabetic retinopathy risk for the obesity-related subgroup (HR 0.49, 95% CI 0.27 to 0.89)., Conclusions: Diabetes subgroup phenotypes are reproducible using SNNN; our algorithm is available as web-based tool. Application of these models allowed for better characterization of diabetes subgroups and risk factors in Mexicans that could have clinical applications., Competing Interests: Competing interests: JPB-L, AV-V and NEA-V are enrolled at the PECEM program of the Faculty of Medicine at UNAM. JPB-L and AV-V are supported by CONACyT., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)