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Análise da associação entre as políticas e programas pró-AM e três principais indicadores de AM em países de alta, média e baixa renda

Fri, 24 Apr 2026 00:00:00 GMT

Title: Análise da associação entre as políticas e programas pró-AM e três principais indicadores de AM em países de alta, média e baixa renda Abstract: Introduction: The World Breastfeeding Trends Initiative (WBTi) was developed as a standardized tool to assist countries in identifying strengths and limitations in breastfeeding promotion policies and programs. The use of the WBTi across different countries, focusing on the impact of breastfeeding policies and programs on indicators over time, reinforces the importance of relating these policies to breastfeeding outcomes, since evidence regarding this association remains limited. Therefore, the objectives of this thesis were: to verify the association between gross domestic product based on purchasing power parity (GDP PPP) and WBTi scores; to assess the association between WBTi scores and the indicators exclusive breastfeeding (EBF), breastfeeding within the first hour of life (BF1h), and continued breastfeeding (continued BF) in high-, middle-, and low-income countries; and to investigate the association between WBTi scores and the outcomes EBF and mixed breastfeeding (mixed BF) during the 2000s and 2020s in low- and middle-income countries. Methods: All data regarding breastfeeding policies and programs were obtained from the WBTi tool, whereas GDP PPP and countries’ economic classifications were obtained from the World Bank. The first and second objectives were operationalized through ecological studies. Initially, WBTi scores and GDP PPP data from 98 countries were obtained. Means and standard deviations (SD) were estimated for total scores and for each WBTi indicator. ANOVA and Tukey’s tests were used to compare mean WBTi scores according to countries’ GDP PPP. The association between GDP PPP and total and individual WBTi scores was analyzed using linear regression. Subsequently, data on EBF, BF1h, and continued BF from 63 countries were obtained from household surveys and other national nutrition surveys involving children under two years of age. Data on breastfeeding policies and programs were obtained from the WBTi and countries’ economic classifications from the World Bank. Associations between WBTi scores and breastfeeding indicators were analyzed using beta regression. Finally, the third objective was operationalized through a cross-sectional study using EBF and mixed BF data from DHS (Demographic and Health Surveys) and MICS (Multiple Indicator Cluster Surveys) surveys involving children under six months of age. Data on breastfeeding policies and programs were obtained from the WBTi. Time 1 (T1) corresponded to the 2000s and Time 2 (T2) to the 2020s. Multilevel logistic regression evaluated associations between WBTi scores and the outcomes EBF and mixed BF. Results: Analysis of 98 high-, middle-, and low-income countries identified the highest mean WBTi scores for health care systems and nutrition support (indicator 5) (6.4±2.0) and information support (indicator 7) (6.4±2.5). Mean total scores and scores for indicators 3 (Code implementation), 7 (information support), 9 (infant feeding during emergencies), and 10 (monitoring and evaluation) were higher in low- and middle-income countries, whereas indicator 4 (maternity protection) presented higher mean scores in high-income countries (p<0.05). A negative association was observed between GDP PPP and the total WBTi score (β=-2.67; 95%CI:-5.06;-0.29), indicator 3 (Code implementation) (β=-0.50; 95%CI:-0.91;-0.08), indicator 7 (information support) (β=-0.67; 95%CI:-1.07;-0.27), indicator 8 (infant feeding and HIV) (β=-0.59; 95%CI:-1.07;-0.11), and indicator 9 (infant feeding during emergencies) (β=-0.91; 95%CI:-1.34;-0.48). A positive association was observed between GDP PPP and indicator 4 (maternity protection) (β=0.63; 95%CI:0.24;1.02). In the second article, upper-middle-income countries presented lower mean EBF prevalence (37.9±2.9). Upper-middle-income (40.9±3.9) and high-income countries (26.3±9.9) showed lower mean continued BF prevalence. Countries with higher scores for indicator 8 (infant feeding and HIV) presented higher EBF prevalence (β=7.7; 95%CI=1.6;13.7). Countries with higher scores for indicator 2 (BFHI) (β=4.2; 95%CI=3.2;11.6) and indicator 3 (Code implementation) presented higher prevalence of continued BF. In the third article, at T1, maternal age (OR=0.68; 95%CI:0.58–0.79), total WBTi score (OR=0.99; 95%CI:0.98–0.99), indicator 1 (policy and funding) (OR=0.87; 95%CI:0.85–0.89), and indicator 5 (health care systems and nutrition support) (OR=0.81; 95%CI:0.78–0.84) were negatively associated with EBF, whereas BF1h (OR=1.24; 95%CI:1.14–1.34), indicator 2 (BFHI) (OR=1.12; 95%CI:1.09–1.16), and indicator 4 (maternity protection) (OR=1.06; 95%CI:1.02–1.10) were positively associated with EBF. At T2, female sex (OR=1.08; 95%CI:1.01–1.16), BF1h (OR=1.16; 95%CI:1.08–1.24), and indicator 1 (policy and funding) (OR=1.04; 95%CI:1.02–1.07) were positively associated with EBF, whereas maternal age (OR=0.80; 95%CI:0.70–0.92), indicator 2 (BFHI) (OR=0.91; 95%CI:0.89–0.94), and indicator 4 (maternity protection) (OR=0.89; 95%CI:0.86–0.91) were negatively associated. For mixed BF, at T1, maternal age (OR=1.68; 95%CI:1.37–2.06), indicator 1 (policy and funding) (OR=1.21; 95%CI:1.18–1.25), and indicator 5 (health care systems and nutrition support) (OR=1.32; 95%CI:1.26–1.39) were positively associated, whereas BF1h (OR=0.73; 95%CI:0.66–0.81), indicator 2 (BFHI) (OR=0.86; 95%CI:0.83–0.87), indicator 4 (maternity protection) (OR=0.86; 95%CI:0.82–0.91), and the total WBTi score (OR=1.02; 95%CI:1.02–1.03) were negatively associated with mixed BF. At T2, maternal age (OR=1.32; 95%CI:1.10–1.58), cesarean section (OR=1.38; 95%CI:1.22–1.57), and indicator 9 (infant feeding during emergencies) (OR=1.05; 95%CI:1.03–1.08) were positively associated with mixed BF, whereas BF1h (OR=0.71; 95%CI:0.64–0.78), indicator 3 (Code implementation) (OR=0.87; 95%CI:0.83–0.92), and indicator 5 (health care systems and nutrition support) (OR=0.95; 95%CI:0.92–0.99) were negatively associated. Conclusion: Countries with lower GDP PPP presented higher WBTi scores, except for the maternity protection indicator, which showed higher scores in countries with higher GDP PPP. Countries with higher WBTi scores presented higher breastfeeding prevalence. Wealthier countries showed lower EBF and continued BF rates compared to poorer countries. Countries with higher scores for BFHI implementation (indicator 2), implementation of the International Code of Marketing of Breastmilk Substitutes (indicator 3), and development of infant feeding and HIV policies (indicator 8) presented higher prevalence of EBF and continued BF. BF1h was identified as a protective factor for EBF and as a reducing factor for mixed BF, regardless of the analyzed period. Older maternal age and cesarean section appeared to act as barriers to EBF. Infant feeding during emergencies may favor the adoption of mixed BF, whereas strengthening regulatory measures related to Code implementation may contribute to reducing mixed BF. The positive association between total WBTi score and mixed BF suggests that advances in breastfeeding promotion and support may contribute to maintaining breastfeeding, even if not exclusively.

Identificação de metabólitos séricos e salivares por meio de análise metabolômica e técnicas de aprendizado de máquina para o diagnóstico do câncer colorretal

Fri, 08 May 2026 00:00:00 GMT

Title: Identificação de metabólitos séricos e salivares por meio de análise metabolômica e técnicas de aprendizado de máquina para o diagnóstico do câncer colorretal Abstract: Introduction: Colorectal cancer (CRC) is the third most prevalent neoplasm worldwide, as well as the second leading cause of cancer death, and is frequently associated with late diagnosis due to low adherence to gold-standard screening and diagnostic methods such as colonoscopy, which is considered invasive. Therefore, the search for serum and salivary metabolites that can aid in the development of screening tools and contribute to a diagnosis better accepted by patients is necessary. Objective: To analyze the abundance of serum and salivary metabolites using Liquid Chromatography coupled to Mass Spectrometry (LC-MS) and machine learning (ML) techniques for CRC diagnosis. Materials and methods: In the first manuscript, a cross-sectional study was conducted with 52 CRC patients and 47 healthy control individuals matched for sex and age, in which serum samples were analyzed. In the second manuscript, a cross-sectional study was conducted with 55 CRC patients and 46 individuals in the control group, matched for sex and age, in which saliva samples were analyzed. In both studies, samples were analyzed using LC-MS. A heat map analysis with hierarchical clustering and a volcano plot were used to show the differentially abundant metabolites between the groups. Significance criteria (p ≤ 0.05; expression variation ≥ 2.0) were applied. Subsequently, ML algorithm approaches were applied. Diagnostic accuracy was evaluated through sensitivity, specificity, and respective ROC curves. Results: In the first manuscript, differentially abundant metabolites were identified between serum samples from the groups, with increased levels of sn-glycero-3-phosphocholine, 18:1(13Z)(17Me), glyceryl 5-hydroxydecanoate, and piperidine in CRC patients, while D-tryptophan showed greater abundance in the control group. Among the ML models evaluated, Random Forest showed the best diagnostic performance, with a sensitivity of 92.31%, specificity of 91.49%, and an area under the ROC curve of 0.973. In the second manuscript, an increase in metabolites related to vitamin E, polyamines, glycerides, phospholipids, and sphingolipids was observed in cancer patients, while glycerophospholipids, eicosanoids, and 17-Hydroxy-5alpha,17alpha-pregn-1-en-3-one showed greater abundance in the control group. The Naïve Bayes model demonstrated excellent discriminatory power, with a sensitivity of 97.83%, specificity of 96.36%, and an area under the curve of 0.996. Conclusion: The results indicate that metabolomics, combined with ML, represents a promising technique for non-invasive CRC screening, with the potential to optimize diagnosis, improve patient acceptance and, consequently, clinical prognosis, provided it is validated in future studies.

Integração de abordagens ômicas na investigação de alterações metabólicas associadas à hepatite D

Thu, 30 Apr 2026 00:00:00 GMT

Title: Integração de abordagens ômicas na investigação de alterações metabólicas associadas à hepatite D Abstract: Background and aims: Hepatitis D virus (HDV) is a single-stranded circular RNA satellite virus with hepatocyte-specific tropism that occurs in the presence of hepatitis B virus (HBV), being functionally dependent on it to complete its infectious cycle. Transmission occurs predominantly via the parenteral route and may present as simultaneous coinfection or as superinfection in individuals chronically infected with HBV, the latter being associated with more severe clinical outcomes, including early cirrhosis and an increased risk of hepatocellular carcinoma. Given the central role of the liver in metabolic regulation, HDV infection is expected to induce alterations in systemic metabolism. However, to date, comprehensive characterization of these alterations, particularly through omics-based approaches, remains limited. In this context, this study aimed to investigate serum metabolomic and lipidomic signatures capable of distinguishing HDV infection from HBV monoinfection, as well as to explore their discriminative potential. Materials and methods: This exploratory study employed untargeted metabolomic and lipidomic approaches based on high-resolution liquid chromatography–mass spectrometry (LC–MS) and gas chromatography–mass spectrometry (GC–MS), respectively. Residual anonymized serum samples from individuals with confirmed HDV infection and HBV-monoinfected controls from the Brazilian Amazon were provided by the Central Laboratory of Public Health of Acre and analyzed. Exploratory analyses were performed, including principal component analysis (PCA), as well as volcano plots and heatmaps to identify differentially abundant features. Predictive modeling using supervised machine learning algorithms was applied to evaluate discriminative performance. Results: Metabolomic analysis identified six metabolites significantly altered in HDV infection, predominantly related to lipid and phospholipid metabolism. Linoleic acid, heptadecanoic acid, 3-hydroxyicosanoic acid, pregnanolone, and choline showed higher abundance, whereas LysoPC(18:0/0:0) showed lower abundance in HDV-positive serum samples. Machine learning models demonstrated good discriminative performance, with Gradient Boosting achieving an area under the curve (AUC) of 0.943, with sensitivity and specificity of 86%. In contrast, lipidomic analysis revealed four lipid species with significantly lower abundance in HDV-positive samples, particularly cholesterol-derived compounds. Random Forest showed the best performance in this dataset, with an AUC of 0.854, sensitivity of 84.8%, and specificity of 100%. In both approaches, model interpretability, assessed using Shapley additive explanations (SHAP) and permutation-based feature importance, identified the same metabolites and lipids as the main contributors to model performance. Conclusions: HDV infection is associated with distinct metabolomic and lipidomic alterations in the context of HBV infection, suggesting a disruption of metabolic homeostasis, possibly associated with the severity of liver injury. These findings provide preliminary evidence supporting the use of metabolomic and lipidomic signatures, integrated with artificial intelligence analyses, for biomarker investigation, with potential applications in improving diagnosis and in characterizing alterations associated with hepatitis D. Further studies with larger and longitudinal cohorts are required to validate these findings.

Padrões crononutricionais e suas associações com desfechos metabólicos: resultados do National Health and Nutrition Examination Survey 2003–2018

Fri, 17 Apr 2026 00:00:00 GMT

Title: Padrões crononutricionais e suas associações com desfechos metabólicos: resultados do National Health and Nutrition Examination Survey 2003–2018 Abstract: Introduction: Fasting duration has been widely investigated in relation to metabolism, weight loss, and chronic diseases. However, population-based studies describing its distribution and variation across sociodemographic subgroups remain limited. In addition, the timing and regularity of food intake influence circadian rhythms and metabolism and have been associated with various health outcomes such as obesity and metabolic syndrome. Long-term population based evidence integrating fasting patterns and eating timing remains scarce. Objectives: : To describe fasting patterns over a 16-year period among adults and elderly according to sociodemographic characteristics (manuscript 1). The second objective was to evaluate the association between chrononutrition patterns, defined by the timing of the first and last eating episodes, and metabolic outcomes in adults and elderly (manuscript 2). Materials and Methods: A total of 32,053 (manuscript 1) and 7,895 participants (manuscript 2) from eight cycles of the National Health and Nutrition Examination Survey (NHANES) (2003-2018) were analyzed. Information on fasting duration and eating timing was obtained from two 24-hour dietary recalls. The first eating episode was defined as the first intake of energy-containing foods or beverages recorded after 05:00, and the last eating episode corresponded to the final caloric intake of the day. Fasting patterns were defined as the interval between the last and first eating episodes, including fasting duration, fasting midpoint, and night fasting duration (18:00 6:00). Additional chrononutrition variables included eating duration, eating midpoint, timing of the first and last eating episodes, number of eating occasions, and total energy intake (manuscript 1). For manuscript 2, a chrononutrition pattern was defined based on the population median timing of the first and last eating episodes, categorized into earlier and later intake patterns. Associations were assessed using linear, logistic, and multinomial regression models adjusted for potential confounders in both manuscripts. In manuscript 2, Poisson regression was used to examine the association between chrononutrition patterns and metabolic outcomes, including fasting glucose, triglycerides, HDL cholesterol, obesity, abdominal obesity, and metabolic syndrome. Results: Fasting patterns differed across sociodemographic subgroups (p < 0.001), with later patterns more common among younger adults and individuals with lower educational attainment and income, and earlier patterns among elderly individuals. Differences in fasting duration and night fasting duration (18:00-6:00) were also observed across subgroups (p < 0.001), and findings from stratified analyses were consistent with those from the overall sample. Over the 16-year period, modest changes in fasting patterns were observed, including slight increases in night fasting duration (18:00–6:00) (p = 0.026), earlier timing of the last eating episode (p = 0.048), fewer eating occasions (p = 0.028), and lower total energy intake (p = 0.003) (manuscript 1). In manuscript 2, later eating patterns were associated with a higher prevalence of elevated triglycerides (PR: 1.23; 95% CI: 1.05-1.46) and elevated fasting glucose (PR: 1.13; 95% CI: 1.03-1.24; PR: 1.16; 95% CI: 1.05-1.28), compared with earlier eating patterns. Conclusion: Later fasting patterns were more common among younger adults and individuals with lower educational attainment and income, whereas earlier patterns were more frequent among elderly. Over time, only modest changes were observed in fasting patterns and other chrononutrition variables (manuscript 1). Additionally, later eating patterns were associated with worse metabolic outcomes (manuscript 2). These findings contribute to the understanding of fasting patterns across population subgroups and highlight the role of eating timing as a relevant factor in the understanding and potential prevention of metabolic disorders at the population level.