1,721,106 research outputs found
Predictors of water intake among Mexican children and adolescents
No full textPatterns of water consumption among children and adolescents are not widely analyzed. The aim of the study is to assess predictors (including dietary habits, anthropometric and physical activity frequency) of water consumption in Mexican children and adolescents. The NutriRun is an International study started in 2011. Subjects' anthropometrics, health status and behaviours were assessed during the race Carrera Kinder Generación en Movimiento, which has taken place in Mexico City every April between 2011 and 2013. The analysis of factors associated with water consumption showed that, age (p-value 0.025), male gender (p-vale 0.011), to be overweight/obese (p-value 0.013) and beverages consumption (p-value 0.014) were significant predictors of water intake. Particularly, age, male gender and weight status were found to be in a positive relationship with water intake, while a higher level of beverages consumption was a predictor of lower levels of water intake. These findings might be taken into account in the development of public health policies targeting on increasing water consumption (which has been demonstrated to have beneficial effects on health) among kids and their families
Does Love Really Make Mothers Blind? A Large Transcontinental Study on Mothers' Awareness About Their Children's Weight
Full text linkObjective: The aim of this study was to assess maternal misperception rates (perception as normal or underweight of a child with overweight or obesity) and their role in affecting the chance of implementing actions to change children’s weight.
Methods: Obesogeneicity of Gadgets Marketed with Snacks (OBEY-AD) is an international study investigating factors promoting childhood overweight and obesity in 10 countries, in which 2,720 child-mother dyads have been enrolled. Mothers’ perception of their children’s weight was assessed using a projective test. Children’s weight status was measured according to the anthropometric standards established by the World Health Organization.
Results: Mothers classified 89% of children with overweight and 52% of children with obesity as normal weight. The odds ratio of mothers’ misperception was significantly higher for higher parental BMI, higher children’s International Brand Awareness Inventory score, and high family socioeconomic status. Children with overweight and/or obesity who were perceived as normal weight by their mothers were less likely to be referred to specific health care services.
Conclusions: Most children with overweight and/or obesity were perceived as normal weight by their mothers. Such lack of concern regarding a severe disease might interfere with the effectiveness of prevention programs. Considering the contextual factors that frame the etiological causes of a disease may
help in finding effective and enduring solutions to target childhood obesity
Association between simple anthropometric measures in children of different ethnicities: Results from the OBEY-AD study
No full textBody mass index (BMI) is considered a good predictor of overall adiposity, with significant sensitivities in identifying overweight children. Recently, it has been suggested that other anthropometric measures may also be employed as adequate surrogates for imaging techniques and BMI. However, it is well known that differences exist in body fat distribution among different ethnicities. The present study aims at assessing the relationship between anthropometric measures in children from different geographical regions. The OBEY-AD is an international study enrolling 2720 children (3-11 years of age), balanced by gender. Children underwent anthropometric assessment.The association between these anthropometric measures was estimated using linear mixed models. South-American children had a higher BMI and waist and hip circumference compared to European and Indian ones. Conversely, Indian children were found to be taller and to have a higher waisthip ratio than those of European and South-American kids, suggesting a different body composition of Indian children compared to those of the other ethnic groups. Overall, this data provides further evidence on the differences in anthropometric measures between the Indian, South American and European child populations
Modelling Inflammatory Bowel Diseases trajectories combining dynamic, multifactorial, Artificial Intelligence-based approaches
Full text linkPredictors of water intake among Mexican children and adolescents
No full textPatterns of water consumption among children and adolescents are not widely analyzed. The aim of the study is to assess predictors (including dietary habits, anthropometric and physical activity frequency) of water consumption in Mexican children and adolescents. The NutriRun is an International study started in 2011. Subjects' anthropometrics, health status and behaviours were assessed during the race Carrera Kinder Generación en Movimiento, which has taken place in Mexico City every April between 2011 and 2013. The analysis of factors associated with water consumption showed that, age (p-value 0.025), male gender (p-vale 0.011), to be overweight/obese (p-value 0.013) and beverages consumption (p-value 0.014) were significant predictors of water intake. Particularly, age, male gender and weight status were found to be in a positive relationship with water intake, while a higher level of beverages consumption was a predictor of lower levels of water intake. These findings might be taken into account in the development of public health policies targeting on increasing water consumption (which has been demonstrated to have beneficial effects on health) among kids and their families
Comparison of Borrowing Methods for Incorporating Historical Data in Single-Arm Phase II Clinical Trials
No full textBackground: Over the last few years, many efforts have been made to leverage historical information in clinical trials. Incorporating historical data into current trials allows for a more efficient design, smaller studies, or shorter duration and may potentially increase the relative amount of information on efficacy and safety. Despite these advantages, it is crucial to select external data sources appropriately to avoid introducing potential bias into the new study. This is where borrowing methods become useful. We illustrate and compare the latest methods of borrowing historical data in a single-arm phase II clinical trial setting, examining their impact on statistical power and type I error. Methods: We implemented static and dynamic versions of the power prior method, incorporating overlapping coefficient and loss functions and meta-analytic predictive priors. These methods were compared with standard and pooling approaches, in which none or all historical data are used. Results: Dynamic borrowing methods achieve lower type I error inflation than pooling. The power prior approach, integrated with overlapping coefficient, allowed for measuring the similarity of the subjects considering their baseline characteristics, thus the likelihood of the data contains information about both confounders and outcome. Using a discounting function to estimate the power parameter guarantees the similarity of historical information and current trial data. Conclusion: We provided a comprehensive overview of borrowing methods, encompassing frequentist and Bayesian approaches as well as static and dynamic technique, to guide researchers in selecting the most appropriate strategy
Unmasking pandemic patterns: decoding the COVID-19’s impact on mortality in Italy with Generalized Gamma overdispersion model
No full textBackground: Italy has been significantly impacted by the COVID-19 pandemic, particularly in its early stages, resulting in healthcare strain, societal restrictions, and disruption. Understanding the long-term effects, notably excess mortality beyond the initial peaks, remains important. Prior studies have focused on the early phase, leaving out subsequent and updated mortality trends. Method: This study analyzes Italian mortality rates from 2015 to 2023, employing Generalized Additive Models for Location, Scale, and Shape (GAMLSS), the Generalized Gamma Overdispersion model. Data analysis considered factors such as gender, age groups (under 65 and 65 or older), and geographical differences (Northern versus Central-Southern Italy) as key characteristics of the mortality trend. Results: The study identified several phases of the pandemic, characterized by a significant early 2020 mortality peak and subsequent smaller peaks. Mortality rates were higher in Northern Italy, with males and the elderly being the most affected. Overall, mortality rates increased during the pandemic, particularly among these groups, and then returned to normal levels in 2023. An increase in the overdispersion parameter, estimated via the GAMLSS model, is evident in the post-pandemic phase and persists until 2023. Conclusion: The findings highlight the complex nature of COVID-19's impact on mortality in Italy. They reveal the temporal phases, regional disparities, and demographic vulnerabilities that contribute to the overall mortality picture. The overdispersion component indicates more significant variability and unpredictability of mortality patterns until 2023. This highlights the intricate interplay of factors, including healthcare capacity, viral mutations, and the effectiveness of public health responses. This study emphasizes the need for targeted interventions and protective measures in the most affected groups
Association between simple anthropometric measures in children of different ethnicities: Results from the OBEY-AD study
No full textBody mass index (BMI) is considered a good predictor of overall adiposity, with significant sensitivities in identifying overweight children. Recently, it has been suggested that other anthropometric measures may also be employed as adequate surrogates for imaging techniques and BMI. However, it is well known that differences exist in body fat distribution among different ethnicities. The present study aims at assessing the relationship between anthropometric measures in children from different geographical regions. The OBEY-AD is an international study enrolling 2720 children (3-11 years of age), balanced by gender. Children underwent anthropometric assessment.The association between these anthropometric measures was estimated using linear mixed models. South-American children had a higher BMI and waist and hip circumference compared to European and Indian ones. Conversely, Indian children were found to be taller and to have a higher waisthip ratio than those of European and South-American kids, suggesting a different body composition of Indian children compared to those of the other ethnic groups. Overall, this data provides further evidence on the differences in anthropometric measures between the Indian, South American and European child populations
Bayesian Sequential Pragmatic Cluster Randomized Clinical Trial Design for PrEventive Effect of MEditerranean Diet in Children: PEMED Trial Research Protocol
No full textBackground: Childhood nutrition plays an important role in the promotion of long-term health. Introducing solid foods in alignment with the Mediterranean Diet during weaning fosters a preference for healthy foods early in life. However, access to nutritious diets remains a challenge in underserved communities. Scampia, a socioeconomically disadvantaged district in Naples, Italy, exemplifies a community where barriers to healthy eating persist. This research reports a trial protocol that plans for a study to evaluate the impact of the Mediterranean Diet on child health and to establish preventive strategies for chronic diseases. Methods: The PEMED (PrEventive effect of MEditerranean Diet in Children) trial is a Bayesian Sequential Pragmatic Cluster Randomized Clinical Trial. Family Pediatricians (FPs) are randomized to deliver either Mediterranean Diet-based dietary guidance starting at weaning or standard dietary practices using typical baby foods. Children will be followed up for six years, with regular assessments of growth, microbiome composition, and adherence to the Mediterranean Diet, using validated tools. Interim analyses will be conducted at three-year intervals to evaluate the efficacy and monitor adverse events. Saliva and stool samples will be collected for genetic and microbiome analyses, and adherence will be monitored through quarterly dietary recalls and biomarkers. Results: This trial will consider Italy’s established FP network for implementing innovative dietary intervention in a real-world setting. Conclusions: This study will address nutritional disparities in the underserved Scampia community and provide a scalable model for early dietary interventions. The results will shed light on the role of the Mediterranean Diet in improving childhood health and informing public health strategies globally
Evaluating therapeutic effect on WOMAC subscales in osteoarthritis RCTs: When model choice matters
No full textAbstract
Rationale, Aims, and Objectives: The study aimed at developing a method for modelling
the Western Ontario and McMaster Universities index (WOMAC), accounting for correlation
between its subscales and for heterogeneity of treatment effect (HTE), using data from 2 twin
trials on knee osteoarthritis.
Method: Two randomized, double‐blind, placebo‐controlled clinical trials (twin trials). Studies
aimed at investigating the effectiveness of a pharmacological treatment on clinical outcomes of
knee osteoarthritis, measured using WOMAC index. To take into account that the WOMAC
subscales are correlated and skewed, we proposed and compared multivariate gamma and
Gaussian approaches with latent variable capturing correlation between outcomes. Besides the
latent term, the interaction between the latent term and treatment, accounting for HTE, was
further estimated.
Results: Modelling the subscales by using a gamma approach accounting for skewness of data,
we found out different results compared with Gaussian models. The main difference regarded the
latent variable interacting with treatment (accounting for unobserved heterogeneity), which is
not significant for the Gaussian approach (P value = .102) and significant in the gamma model
(P value < .002). Thus, indicating that unobserved covariates affect treatment's performance.
Additionally, plotting the observed and the estimated values of WOMAC index of the Gaussian
and gamma models, we showed that, compared with the Gaussian, the gamma one best fits the
data, especially among poor responders.
Conclusion: Multivariate gamma approach accounting for correlation between outcomes and
for HTE has been demonstrated to be more suitable to model WOMAC subscales and to provide
more information on effect of therap
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