Artificial intelligence (AI) has the potential to improve primary diabetes care in low-income and middle-income countries (LMICs), where the rising burden of disease contrasts sharply with limited health-care resources. Emerging evidence shows the promise of AI for screening, risk prediction, monitoring, and personalised management of diabetes and its complications. However, substantial barriers remain, including infrastructure deficits, data fragmentation, equity and inclusivity challenges, limited prospective validation, and concerns about the acceptability, sustainability, and regulatory oversight of AI. The effective integration of AI into primary diabetes care will depend on coordinated investment in foundational infrastructure that includes large-scale development and rigorous validation of novel AI models for use by primary care physicians and patients across diverse populations. AI initiatives are also needed to support interdisciplinary and international collaborations spanning clinical, technical, and policy domains to ensure successful implementation. By aligning technological innovation with health care needs, AI could evolve from a proof-of-concept tool to a practical enabler of equitable, scalable, and cost-effective diabetes care in LMICs. In this Personal View, we outline the major opportunities and challenges of applying AI to primary diabetes care in LMICs, and propose directions for future development and implementation.

This protocol describes a standardized and reproducible accelerometer data collection and processing workflow implemented in the ELSA-Brasil cohort using ActiLife software. The protocol enables consistent derivation of physical activity, sedentary behavior, and sleep metrics from hip-worn accelerometers in large epidemiological studies.Protocol summary:• Defines standardized procedures for accelerometer configuration, deployment, and data acquisition under 24-hour free-living conditions;• Specifies predefined ActiLife processing parameters including wear-time validation, sleep detection, and activity intensity classification;• Generates harmonized accelerometry-derived variables supporting replicable epidemiological analyses and cross-cohort comparability;This protocol provides a parameter-explicit framework for accelerometer data processing using ActiLife software and may serve as a reference standard for cohort studies using similar accelerometry approaches.

Background Diabetes is a major global public health challenge, with rapidly rising incidence, particularly in low- and middle-income countries. Physical activity is a well-established protective factor against type 2 diabetes (T2DM); however, the population-level impact of realistic modest increases in physical activity remains unclear.Objectives To estimate the burden of T2DM attributable to physical inactivity in Brazil and project the impact of modest increases in physical activity.Research design and methods We calculated the population attributable fractions (PAFs) and economic costs of diabetes due to physical inactivity in Brazil. We estimated the incidence of T2DM from 2026 to 2050 using data from the National Health Survey (2013 and 2019) and the Global Burden of Disease Study. The relative risk of incident diabetes across the physical activity continuum was extracted from a previous meta-analysis. We modelled scenarios simulating gradual increases in leisure-time physical activity (LTPA) and resistance exercise (RE) and projected economic impacts through 2050.Results From 2026 to 2050, 11.7% (95% uncertainty interval, UI 9.5% to 14.1%) of incident T2DM cases in Brazil (~3.7 million) might be attributable to physical inactivity, with higher PAFs among adults with lower education (PAF: 13.7%; 95% UI 11.1% to 16.4%) and in Mixed Race (12%; 95% UI 9.6% to 14.3%) and Black (11.9%; 95% UI 9.5% to 14.2%) populations. In a nonlinear dose-response association, increasing LTPA by 10, 20 or 30 min/day among inactive individuals could prevent 7.0% (2.20 million), 12.9% (4.05 million) and 16.0% (5.02 million) of incident cases, respectively, by 2050. For RE, the same daily increases could prevent 12.0% (3.80 million), 18.7% (5.87 million) and 22.5% (7.07 million) of cases. These increments could significantly reduce healthcare costs, starting at R$1.9 billion for the 10 min LTPA scenario, with the greatest impact observed from RE.Conclusions Promoting small increases in physical activity could yield substantial health and economic benefits. Equitable public health strategies are essential to address disparities and halt the growing burden of diabetes in Brazil.

OBJECTIVE:To describe the Brazilian Diabetes Risk Score (BrDMrisc), an online calculator for estimating the risk of developing diabetes in 10 years, comparing it to other commonly used screening approaches to identify high-risk of future diabetes. METHODS:BrDMrisc is derived from 7.4-year follow-up data from ELSA-Brasil, a contemporary Brazilian cohort. Risk functions to predict future diabetes were based on socioeconomic, lifestyle, clinical, and laboratory variables, many of which are incorporated as continuous variables on a training sample including half of the analyzed cohort. We used ELSA-Brasil participant baseline data and incident diabetes cases detected during follow-up on the other half to compare the predictive capacity of BrDMrisc against traditional pre-diabetes screening strategies. RESULTS:BrDMrisc's 27 risk functions offer versatility to the online app, enabling estimates based on differing combinations of clinical and laboratory findings, which present more favorable diagnostic properties than other recommended approaches. For example, the BrDMrisc function based on clinical data plus fasting glucose, when compared with detection using solely the presence of impaired fasting glucose (≥ 100 mg/dL), identified a more manageable fraction (20.0% versus 40.6%) of the population as high risk, with those identified as presenting a two-fold risk of developing diabetes (28.5% versus 17.1%). CONCLUSIONS:BrDMrisc diabetes risk calculator, based on data from a contemporary Brazilian cohort, is readily available online, versatile, and presents generally more favorable diagnostic properties than other commonly used screening strategies.

INTRODUCTION:Metabolic dysfunction-associated steatotic liver disease (MASLD) has been linked to adverse brain outcomes. We aim to evaluate whether MASLD is associated with cognitive impairment/decline. METHODS:We analyzed data from the Estudo Longitudinal da Saúde do Adulto (ELSA-Brasil study). Global cognitive performance was assessed at baseline and follow-up. Associations between MASLD and cognition were tested using Poisson regression and linear mixed-effects models (LMMs). RESULTS:MASLD was present in 13.6% (n = 918/6754) of participants at baseline. MASLD was not associated with incident cognitive impairment (Relative Risk: 1.01; 95% confidence interval [CI]: 0.83-1.23; p = 0.91). In LMMs, in a fully adjusted model, MASLD was not associated with cognitive decline (estimate: 0.039; 95% CI: -0.109 to 0.031; p = 0.2721) but was associated with the memory domain at the baseline. DISCUSSION:MASLD is not independently associated with cognitive impairment or cognitive decline in middle-aged adults. HIGHLIGHTS:Metabolic dysfunction-associated steatotic liver disease (MASLD) is not independently associated with cognition in the longitudinal analysis. Hepatic steatosis is not independently associated with cognition. The effect on cognition is dependent on vascular and metabolic risk factors.

Risk of bias assessment is a crucial step in evidence synthesis. The traditionally adopted tool, however, is complex, resource-intensive, and unreliable. While prior investigations have focused on whether Large Language Models (LLMs) could perform assessments with RoB 2, this study is the first to evaluate the reliability of ROBUST-RCT, a novel risk-of-bias tool, as applied by humans and LLMs. Reviewers working independently used ROBUST-RCT to assess different aspects of a sample of RCTs and then reached a consensus through discussion. A chain-of-thought prompt instructed four LLMs on how to apply ROBUST-RCT. The primary analysis used Gwet’s AC2 to assess inter-rater reliability based on all the final ratings (i.e., the ratings in the second step of the tool) for all the core items of the ROBUST-RCT. A sample of 56 assessments, derived from 9 studies, was compared for each LLM against human consensus. In the primary analysis, Gwet’s AC2 inter-rater reliability varied across the LLMs. DeepSeek-R1, the lowest performer, yielded an AC2 of 0.46 ( 95% CI: 0.24 to 0.69). On the other side, Gemini 2.5 Pro Preview – the model with higher consistency with human consensus – yielded an AC2 of 0.69 (95% CI: 0.54 to 0.84). With 95% confidence, three of the four tested LLMs achieved ‘moderate’ or higher reliability based on benchmarking. LLMs could be helpful in the risk-of-bias assessment of systematic reviews using the ROBUST-RCT tool.

BACKGROUND:Leisure-time physical activity offers protection against the risk of death. However, most studies have considered only one measure of lifetime exposure, and there is a lack of cohort studies in low- and middle-income countries. We aimed to evaluate the prospective effect of leisure-time physical activity and its changes in the mortality risk among adults from Brazil. METHODS:We analyzed leisure-time physical activity data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Changes from the first wave (2008-2010) to the second wave (2012-2014) were assessed by the International Physical Activity Questionnaire. Mortality data were updated on January 1, 2024. Cox regression estimated hazard ratios (HR). RESULTS:Overall, 13,589 individuals had valid data for physical activity in both waves. The mean age at baseline was 52.2 (9.1), varying from 34 to 75 years old. There were 553 deaths, with a crude mortality rate of 3.3 per 1000. The mean follow-up time for the risk of dying was 12 years. The risk of death was lower for individuals who had: (1) high levels of moderate to vigorous physical activity at wave 1 and maintained or increased at wave 2 (HR = 0.59; 95% CI, 0.37-0.92), (2) incident vigorous physical activity at wave 2 (HR = 0.47; 95% CI, 0.32-0.70), and (3) maintained or increased their walking level (HR = 0.75; 95% CI, 0.57-0.99) as compared with those inactive at both waves. CONCLUSIONS:We found a greater protective effect of vigorous physical activity on mortality risk. However, maintaining leisure-time walking was also associated with a lower mortality risk. Performing physical activity above the recommended threshold could provide more benefits.

OBJECTIVE:To describe Brazilian national and regional trends in type 2 diabetes mellitus (T2DM) prevalence, incidence, burden, and exposure to T2DM risk factors. MATERIALS AND METHODS:We sourced the Global Burden of Diseases Study (GBD) 2021 to obtain estimates and trends of T2DM deaths, incidence, prevalence, Years of Life Lost (YLLs), Years Lived with Disability (YLDs), and Disability Adjusted Life Year (DALYs) in Brazil and its regions. We present crude and age-standardized metrics, as well as the exposure to T2DM risk factors between 1990 and 2021. RESULTS:The national age-standardized prevalence of T2DM increased by 37.4% (95% UI 32.7 to 42.6) and the incidence by 32.3% (95% UI 27.6 to 37.7) from 1990 to 2021. Age-standardized deaths by T2DM decreased by 18.0% (95% UI -21.4 to -15.3), and the accompanying YLLs by 22.8% (95% UI -25.8 to -20.2). YLDs increased by 35.4% (95% UI 29.1 to 41.3), while DALYs' rates reduced by 3.1% (95% UI -8.2 to 1.7) since 1990. The Northeast region showed higher age-standardized prevalence, incidence, YLLs, and YLDs in 2021, while the North region had the most pronounced increases. T2DM prevalence increased consistently, alongside rises in exposure to sugar-sweetened beverage consumption and high BMI. While smoking exposure declined in all regions, low physical activity and diets high in red and processed meat increased over time. CONCLUSION:T2DM burden in Brazil is growing due to the increasing exposure to T2DM risk factors. Greater emphasis on prevention and public policies focusing on reducing risk factors and inequalities can reduce T2DM burden in Brazil.

Objective:To estimate the associations between gestational weight gain and maternal immediate perinatal and postpartum outcomes by pooling data from low and middle income countries. Design:Individual participant data meta-analyses. Data sources:PubMed, Embase, Web of Science, and Cochrane Library, based on three searches (Search 1: all prospective studies published from January 2000 to May 2021; Search 2: randomized controlled trials of balanced energy and protein supplementation published until June 2021; Search 3: randomized controlled trials of anti-infectious agents published until August 2021). Eligibility criteria for selecting studies:Prospective studies (randomised controlled trials or observational cohort studies) with measured maternal weight during pregnancy and data available on maternal height, based in populations from low and middle income countries with no underlying conditions. Results:The analyses included 156 300 women from 61 studies and 23 countries, with most participants based in South Asia (n=78 454, 50.2%) and sub-Saharan Africa (n=36 327, 23.2%). Compared with women with adequate (90-125%) gestational weight gain, women with excessive (>125%) gestational weight gain had a higher risk of caesarean delivery (risk ratio 1.10, 95% confidence interval 1.06 to 1.13, τ2=0.000) and emergency caesarean delivery (risk ratio 1.22, 1.03 to 1.43, τ2=0.000). Women with moderately (70% to <90%) or severely inadequate (<70%) versus adequate gestational weight gain had lower risks for caesarean delivery (risk ratio in women with moderately inadequate gestational weight gain 0.88, 95% confidence interval 0.84 to 0.92, τ2=0.004; risk ratio in women with severely inadequate gestational weight gain 0.82, 0.77 to 0.88, τ2=0.010) and emergency caesarean delivery (risk ratio in moderately inadequate gestational weight gain 0.82, 0.71 to 0.95, τ2=0.004; risk ratio in severely inadequate gestational weight gain 0.73, 0.56 to 0.96, τ2=0.103). Excessive versus adequate gestational weight gain was associated with higher postpartum weight retained at any time point (mean difference 2.00 kg, 95% confidence interval 1.49 to 2.50, τ2=1.317), whereas moderately and severely inadequate gestational weight gain were associated with lower retained weight compared with adequate gestational weight gain. Similar trends were found for postpartum body mass index. Severely inadequate gestational weight gain was associated with lower systolic and diastolic blood pressure at any time point post partum than adequate gestational weight gain. No associations were observed for other outcomes including postpartum depressive symptoms or breastfeeding. Evidence indicating an interaction between gestational weight gain and body mass index before pregnancy was found when examining the risk of caesarean delivery and postpartum weight retention, body mass index, and systolic blood pressure as outcomes. Conclusions:These findings support the association between suboptimal gestational weight gain and adverse maternal outcomes in the immediate perinatal and postpartum periods. Further research examining the consequences of suboptimal gestational weight gain in low and middle income countries would be valuable to inform potential strategies to improve long term maternal health. Review registration:PROSPERO CRD42023432836.

As Cochrane’s RoB-2 has been widely adopted in systematic reviews, its traffic-light-style plot has become the standard for risk-of-bias visualization. A new risk-of-bias tool, however, introduced a two-step framework for assessing risk of bias: the ROBUST-RCT tool. Through its framework, the reviewers first evaluate what occurred in the trial (step 1) and then assess the potential impact of these events on the outcome (step 2). This paper introduces a novel visualization tool specifically designed for ROBUST-RCT, namely the “eclipse plot”, which displays both the factual evaluation and the judgment. Therefore, it aims to empower readers of systematic reviews not only to passively accept the authors' judgments but also to form their own judgments about the study’s design and conduct. Finally, consistent with the tool’s aim of simplicity, beyond the R package (“eclipseplot”), an easy-to-use web tool is also available to ensure accessibility for non-coders.

Our objective was to describe weight, fat mass, skeletal mass and waist gains across the adult lifespan. We analysed data from 11 611 participants in the Brazilian Longitudinal Study of Adult Health, aged 35-74 years at baseline and followed from 2008 to 2024. Anthropometric measurements were performed at all visits, and bioimpedance at follow-up visits. Weight at age 20 was self-reported. Age-related changes in weight, fat and muscle mass and waist circumference were estimated using generalised estimating equations with restricted cubic splines. Participants' weight increased a mean of 15 kg from age 20-60, when weight peaked. Most of this increase (50%) occurred before age 35. While obesity manifested mainly in later life, maximum annual weight gains were seen up to age 40-45. Gains then tapered, and weight stabilised across ages 55-65, and then decreased at older ages. While fat and muscle mass followed trajectories similar to that of weight, waist circumference increased steadily up to age 75. Approximately half of the difference in adult weight occurred before age 35. Population-based and clinical interventions to limit weight gain in young adulthood, if effective, could have a major impact on the incidence and long-term burden of obesity.

AIMS:We aimed to develop a multistage schema to stratify diabetes risk using continuous plasma glucose (PG) values (fasting and 1 h) in combination with clinical variables. METHODS:In 962 Brazilian adults, we initially estimated the probability of developing diabetes with the Finnish Diabetes Risk Score (FINDRISC). We then stratified participants with a FINDRISC score of 9 or higher into three progressive high-risk stages based on their probability of developing diabetes. We evaluated the schemás ability to predict the incidence of diabetes using robust Poisson regression with a time offset, employing bootstrap resampling for internal validation. RESULTS:Over 5.31 (0.44) years of follow-up, we observed a steep and graded increase in the risk of diabetes across stages. Initiating screening with FINDRISC reduced OGTT testing by 35.1%. The staging schema categorized 39.1% (36.1-42.2) of the sample in three high-risk stages, with relative risk for incident diabetes ranging from 2.7 (1.0-7.4) to 14.9 (7.3-30.3). Adding 2 h PG and HbA1c to scores produced little change. CONCLUSIONS:A staging schema based on scores derived from continuous FPG and 1 h PG values along with clinical variables, applied after a FINDRISC screening, offers a nuanced and practical approach to identifying individuals for diabetes prevention.

BACKGROUND AND OBJECTIVE:The recently introduced ROBUST-RCT tool aims to balance ease of application and methodological rigor in risk-of-bias assessment for systematic reviews. The tool is structured in two steps: first, evaluating what happened; second, judging the risk of bias related to the assessed aspect of the study. Its straightforward design aims to avoid overly complex workflows. Thus, its usability testing included junior reviewers to ensure accessibility and ease of use. No data regarding its inter-rater reliability are currently available. This study aims to assess the inter-rater reliability of the ratings between junior researchers using the ROBUST-RCT. METHODS:In this inter-rater reliability study, four junior researchers screened and rated a random sample of 115 articles from a systematic search on PubMed. An additional phase beyond the prospectively defined research phases was introduced to exclude articles in which the two raters assessed different outcomes, resulting in a sample of 85 articles. As prespecified in the protocol, the primary statistical analysis employed Gwet's AC2 at each step for each core item ("step-level") and at aggregated step 2 ratings ("judgment set") to provide an overview of the final judgment in the tool. Exploratory analyses include Fleiss' Kappa and a block-level approach. RESULTS:In the primary analysis, the aggregated data with the step 2 ratings ("judgment set") yielded a Gwet's AC2 agreement coefficient of 0.59 (95% CI: 0.53, 0.65); its inter-rater reliability was classified in Gwet's benchmarking as "moderate or higher." The AC2 agreement coefficient for specific steps was, in some instances, higher in the first step of the tool than in the second. Results on the step level ranged from 0.43 (95% CI: 0.24, 0.62, classified as "fair or higher") in the core item 3 step 2 to 0.86 (95% CI: 0.79, 0.92, classified as "almost perfect") in the core item 1 step 1. CONCLUSION:The results support the perspective that the ROBUST-RCT is a reliable and straightforward tool for assessing the risk of bias in systematic reviews. Taken together with previous findings, the higher agreement on some items in the first step may support the view that authors of future systematic reviews should transparently report both steps, enabling readers to build their own reasoning from ratings in step 1. PLAIN LANGUAGE SUMMARY:Risk of bias tools are the instruments used in the synthesis of medical scientific literature to assess whether specific characteristics of clinical trials could affect their results. The ROBUST-RCT is one of these tools and was recently introduced with characteristics that may enable junior researchers to conduct those assessments. This study evaluates the tool's inter-rater reliability, the extent to which users agree in their assessments. A result of 0.00 would mean no better agreement than random data, while 1.00 would suggest perfect agreement-an ideal not often met. In this study, the junior researchers had an inter-rater reliability of 0.59 for the most relevant step of the tool, which is interpreted as at least moderate agreement. Therefore, it supports that the risk of bias could be assessed by junior scientists using the ROBUST-RCT tool.

Objectives:Hair cortisol has been increasingly used as an important biomarker of chronic stress, as it reflects prolonged systemic exposure to cortisol over time. Such exposure has been associated with alterations in body composition; however, the associations with sarcopenia and sarcopenic obesity have still received little attention in the scientific literature on aging. The study aimed to assess the association between hair cortisol, dynapenia, sarcopenia, and sarcopenic obesity in a multicenter and multiethnic Brazilian cohort. Methods:The criterion used to classify sarcopenia was specific to the study population, and the categories used were dynapenia (reduced muscle strength), sarcopenia (reduced muscle strength and mass), and sarcopenic obesity (≥ 38% body fat plus sarcopenia). Hair cortisol levels (pg/mg) were divided into three categories: Low (< 40), normal (40 to 128), and high (> 128). Simple and multiple logistic regression analyses were used to verify the association between hair cortisol, reduced muscle strength, sarcopenia, and sarcopenic obesity. The final model was adjusted for sex, BMI, hypertension, diabetes, smoking, physical activity, and race/ethnicity, and odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. Results:A total of 947 participants were included (aged 54 to 82 years, mean age 67.1 years, 63.7% women). Participants with high hair cortisol levels showed lower odds of reduced muscle strength (OR: 0.796; 95% CI: 0.504-1.255), suggesting an inverse association; this was not statistically significant. However, no significant association was seen between chronic stress and sarcopenia (OR: 1.106; 95% CI: 0.555-2.206) or sarcopenic obesity (OR: 0.607; 95% CI: 0.162-2.279). Conclusions:In a sample of Brazilian adults, hair cortisol level, a measurement technique not affected by physiological fluctuations, was not associated with reduced muscle strength, sarcopenia, or sarcopenic obesity.

BACKGROUND:Sedentary behavior (SB) has been associated with adverse cognitive outcomes. Mentally active sedentary behavior and PA may mitigate the negative impact of SB on brain health. We aimed to investigate the association between context-specific SB, PA, and cognitive decline in middle-aged and older adults over a 4-year follow-up. METHOD:We analyzed data from the Estudo Longitudinal de Saude do Adulto (ELSA-Brasil) study. Participants were enrolled between 2012 and 2014, with a follow-up visit between 2017 and 2019. We used the International Physical Activity Questionnaire - long form to assess leisure PA. We evaluated screen time at work or study and at leisure to categorize SB as mentally active or passive. We evaluated global and domain-specific (memory, verbal fluency, and executive function) cognitive function at baseline and follow-up. Incident cognitive impairment was defined using age and education-specific cutoffs. RESULT:Participants (N = 5,795) had a mean age of 62.4 (SD: 5.8) years and were primarily female (57%). During a mean follow-up of 4.4 (SD: 0.5) years, greater leisure screen time was associated with a higher risk of cognitive impairment, while more screen time for work or study was linked to a lower risk. Screen time for work was associated with a slower decline in global cognition (β=0.03; 95%CI: 0.01, 0.04), memory (β=0.05; 95%CI: 0.00, 0.10), language (β=0.07; 95%CI: 0.02, 0.11), and executive function (β=0.17; 95%CI: 0.11, 0.22). Leisure screen time was associated with more rapid memory decline (β=-0.07; 95%CI: -0.11, -0.02). Medium (4-6 hours/day: RR: 0.99; 95%CI: 0.72-1.36) and high (≥7 hours/day; RR: 1.25; 95%CI: 0.93, 1.67) leisure screen time was not associated with higher risk of cognitive impairment in those with high PA levels (Figure 1). In individuals with high screen time for work (≥7 hours/day), low PA was not linked to a higher risk of cognitive impairment compared to those with high PA (RR≥1.29; p <0.05 for all categories) (Figure 2). There was no interaction between SB and PA (p ≥0.903). CONCLUSION:The association between SB and cognitive decline is context dependent. PA appears to mitigate the negative association between mentally passive SB and cognitive decline.

BACKGROUND:Studies investigating the association of physical activity (PA) with cognitive decline usually do not characterize the parameters of PA, especially the domains in life in which PA occurs such as at leisure and commuting. We evaluated the associations of various parameters of PA (volume, frequency, intensity, and context) with cognitive decline in middle-aged and older adults over an 8-year follow-up. METHOD:We analyzed data from the Estudo Longitudinal de Saude do Adulto (ELSA-Brasil) study. Participants were enrolled between 2008-2010, with a follow-up visit between 2017 and 2019. We used the International Physical Activity Questionnaire - long form to assess PA volume (minutes/week), intensity (light [LPA], moderate [MPA], and vigorous [VPA]), and frequency (1-2, 3-4, 5-6, 7 days/week) in leisure time and commuting contexts at baseline. We evaluated global and domain-specific (memory, verbal fluency, and executive) cognitive function at baseline and follow-up. Incident cognitive impairment was defined as a global cognitive function score at follow-up lower than -1.5 SD from the baseline mean. We used robust Poisson regression models to examine the risk of cognitive impairment according to distinct PA paraments. Models were adjusted for sociodemographic, behavioural, and clinical variables. We modelled PA volume as restricted cubic splines due to non-linear association with the risk of cognitive impairment. RESULT:Participants (N = 10,187; 57% women) had a mean age of 50.6 (SD: 8.6) years. During a mean follow-up of 8.1 (SD: 0.6) years, leisure VPA was associated with a reduced risk of cognitive impairment (150 min/week: RR: 0.76; 95%CI: 0.58, 0.98) (Figure 1). Conversely, active commuting (walking or cycling) was associated with an increased risk of cognitive impairment (150 min/week: RR: 1.57; 95%CI: 1.23, 2.00). Leisure MPA was linked to a lower incidence of cognitive impairment (highest significant volume: 67 min/week: RR: 0.83; 95%CI: 0.69, 0.99) while LPA was not linked (p ≥0.06) during leisure. PA frequency was not associated with incident cognitive impairment. CONCLUSION:The association between PA and the incidence of cognitive impairment depends on PA parameters such as volume, domain, and intensity, especially the latter two. Interventions to promote PA should facilitate opportunities for leisure time PA, especially at higher intensities.

Background/Objectives: While clinical guidelines recommend screening and treatment for gestational diabetes mellitus (GDM) between 24 and 28 weeks, the benefits of earlier diagnosis are emerging. The objective of this study was to evaluate whether the early diagnosis of GDM is associated with reduced excessive gestational weight gain (GWG). Methods: Cohort study that analyzed 4694 pregnant women diagnosed with GDM attending high-risk prenatal care services within the Brazilian Unified Health System in six Brazilian capitals. GWG was classified according to Brazilian-specific pregnancy recommendations. ANCOVA tests were used to compare mean differences in total GWG across the timing of diagnosis. The timing of GDM diagnosis and excessive GWG was further evaluated using linear and logistic regression analysis. Results: Among the 4694 women with GDM (mean age 31.7 ± 6.3 years; mean pre-pregnancy BMI 30.4 ± 6.5 kg/m2, with 47.6% classified with obesity), those diagnosed in the first trimester (n = 1315) gained 2.29 kg less (95% CI: −2.87 to −1.71 kg) total GWG compared to the third trimester, adjusting for risk factors including pregestational weight. First-trimester GDM diagnosis was associated with 22% lower odds of experiencing excessive GWG (Odds Ratio [OR] = 0.78; 95% CI: 0.72–0.86), compared to the third trimester. Diagnoses before 20 weeks and before 24 weeks had 18% (OR = 0.82; 95% CI: 0.77–0.88) and 19% (OR = 0.81; 95% CI: 0.76–0.87) lower odds of excessive GWG. Conclusions: Early diagnosis of GDM, particularly during the first trimester, is associated with reduced GWG. Integrating earlier GDM screening into routine prenatal care could mitigate excessive GWG.

BACKGROUND:Ultra-processed foods (UPFs) are associated with metabolic disorders, mental health and stress-related behaviors. Chronic stress, marked by sustained cortisol elevation, may influence UPF intake. Hair cortisol is a reliable biomarker of long-term stress and enables a deeper understanding of this bidirectional association. OBJECTIVE:This study aimed to investigate the association between hair cortisol, a biomarker of chronic stress, and UPF consumption in the ELSA-Brasil cohort. METHODS:A cross-sectional analysis was performed on 2525 participants from the ELSA-Brasil cohort. Hair cortisol levels were categorized as low, normal, and high, and UPF consumption was expressed as the percentage of the total energy intake divided into tertiles. Multinomial logistic regression was performed to examine the association between cortisol levels and UPF consumption after adjusting for sociodemographic and behavioral factors. RESULTS:Individuals with high hair cortisol levels were 61 % more likely to be in the second tertile of UPF consumption (13.78-21.60 % of total energy intake) compared with the lowest tertile, even after adjustment for confounders. No significant association was observed between high cortisol levels and the highest UPF consumption in any tertile. These findings suggest a non-linear association, in which moderate UPF consumption may provoke a stronger physiological stress response than excessive intake. CONCLUSION:Moderate UPF consumption is significantly associated with elevated hair cortisol levels, emphasizing the importance of dietary and behavioral interventions to mitigate chronic stress. Reducing UPF intake, promoting increased consumption of unprocessed or minimally processed foods, and stress management strategies can be essential in addressing stress-related health outcomes.

Resumo Fundamento A atividade física (AF) desempenha um papel fundamental na prevenção do Diabetes Mellitus tipo 2 (DM-2). No entanto, os achados sobre a influência da intensidade da AF no DM-2 ao longo do tempo ainda são inconsistentes. Objetivo Examinar a associação dose-resposta entre trajetórias de intensidade da AF no lazer e DM-2. Métodos O estudo incluiu dados basais do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil) (2008-2010) e ao longo de 11 anos de acompanhamento de 5.777 mulheres e 4.590 homens, com idades entre 35 e 75 anos. As trajetórias de intensidade da AF no lazer foram avaliadas por meio do Questionário Internacional de Atividade Física (IPAQ), enquanto o DM-2 foi identificado por autorrelato, uso de medicação ou critérios laboratoriais. Foi utilizada regressão logística ordinal para estimar razões de chances (OR) e intervalos de confiança de 95% (IC95%). Resultados Uma menor proporção de participantes com DM-2 (14,4% dos homens e 5% das mulheres) e uma maior proporção sem diabetes (22,1% dos homens e 40,8% das mulheres) foram observadas entre aqueles com trajetória de alta intensidade. Comparado às trajetórias de intensidade moderada, a alta intensidade conferiu proteção contra DM-2: OR 0,63 (IC95% = 0,40-0,98) para homens, e OR 0,33 (IC95% = 0,14-0,79) para mulheres, e as trajetórias de baixa intensidade conferiu maior chance de pré-diabetes entre os homens [OR = 1,36 (IC95% = 1,09-1,69)]. Conclusão A AF de maior intensidade ao longo do tempo esteve associada a uma menor proporção de casos de DM-2 em homens e mulheres. Assim, programas visando a prevenção e o controle do DM-2 devem enfatizar a importância da manutenção de atividades de alta intensidade ao longo do tempo.