Adherence to Mediterranean Diet and Maternal Lifestyle during Pregnancy: Island–Mainland Differentiation in the CRIBS Birth Cohort

Auguštin, Dubravka Havaš; Šarac, Jelena; Lovrić, Mario; Živković, Jelena; Malev, Olga; Fuchs, Nives; Novokmet, Natalija; Turkalj, Mirjana; Missoni, Saša

doi:10.3390/nu12082179

Cited by 18 publications

(28 citation statements)

References 38 publications

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“…The group of heavy meat eaters was not explained by any sociodemographic characteristic. This suggests that this behavior is widely spread in the studied countries, which is supported by evidence indicating that adherence to the plant-rich Mediterranean diet is low [ 32 ] and that consumption of fruits and vegetables is below recommendations in EU countries [ 33 ].…”

Section: Discussionmentioning

confidence: 65%

How Do Consumers Perceive Cultured Meat in Croatia, Greece, and Spain?

et al. 2021

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The meat production industry is one of the leading contributors of greenhouse gas emissions. Cultured meat presents itself as a potential eco- and animal-friendly meat substitute which has the potential to eradicate animal cruelty and reduce both the environmental footprint and the risk of zoonotic illnesses, while delivering a nutrient-dense product. The purpose of this study was to investigate how consumers perceive cultured meat and if the frequency of meat consumption is related to their intention of trying or purchasing cultured meat. Data were collected online in 2020 from Croatia, Greece, and Spain. Among the 2007 respondents, three segments were identified according to meat consumption and variety, plus an a priori identified group of “non-meat eaters”. Sixty percent perceived cultured meat as kind to animals, 57% as unnatural, 45% as healthy and environmentally-friendly, 21% as disgusting, and only 16% as tasty. Although 47% of the respondents had not heard of cultured meat before, 47% would taste it and 41% would purchase it for the same price as conventional meat. This indicates that consumers from Croatia, Greece and Spain might be likely to purchase cultured meat if sold at an affordable price.

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Section: Discussionmentioning

confidence: 65%

How Do Consumers Perceive Cultured Meat in Croatia, Greece, and Spain?

et al. 2021

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“…Other studies have shown that pregnant women have high adherence to the Mediterranean Diet. However, higher adherence was observed in women of higher socioeconomic status [ 32 ]. In contrast, with previous results showing lactating women with high adherence scores to the Mediterranean Diet [ 33 ], our results showed that lactating women obtained the lowest AP-Q score.…”

Section: Discussionmentioning

confidence: 99%

Assessment of Adherence to the Healthy Food Pyramid in Pregnant and Lactating Women

et al. 2021

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There are numerous dietary recommendations during pregnancy. However, there are limited recommendations during the lactation period, a nutritionally vulnerable period for women. The Mediterranean Diet and adherence to the Healthy Food Pyramid (HFP) is considered as the standard for healthy eating. In this study, we investigated the differences in adherence to the HFP in pregnant, lactating, and non-pregnant/non-lactating (NPNL) women concerning sociodemographic factors. A sociodemographic and nutritional and lifestyle questionnaire (AP-Q) were used to assess adherence to the HFP, including lifestyle. The AP-Q score ranges from 0 to 10 meaning the higher the score, the greater the adherence to the HFP. Lactating women had the lowest AP-Q score (6.13 [5.31; 6.82]) compared to the pregnant (6.39 [5.56; 7.05]) and NPNL women (6.27 [5.43; 6.88]), while pregnant women had the highest scores. Maternal age was positively correlated with AP-Q score in pregnant (rho = 0.22; p-Value < 0.001) and lactating women (rho = 0.18; p-Value < 0.001), but not in NPNL women. Educational level and monthly income had a positive influence on the degree of adherence to the HFP. In conclusion, breastfeeding mothers of young age and low socioeconomic and educational level would be the target population to carry out nutritional interventions that improve their adherence to the HFP. The knowledge gained from this study can help to design recommendation guidelines and nutritional educational interventions for a given population.

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“…For model explanation we used permutation importance (PI) which we used in our prior work 30 . It follows the rationale that a random permutation of a predictor variable values as well as the difference in the classification metrics before and after permuting a predictor variable are used as an importance measure 31 .…”

Section: Machine Learningmentioning

confidence: 99%

Predicting treatment outcomes using explainable machine learning in children with asthma

Lovrić

Banić

Lacic

et al. 2020

Preprint

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Background Asthma in children is a heterogeneous disease manifested by various phenotypes and endotypes. The level of disease control as well as the effectiveness of anti-inflammatory treatment is variable and inadequate in a significant portion of patients. Objectives By applying machine learning algorithms, we aimed to predict treatment success in a pediatric asthma cohort and to identify key variables for understanding underlying mechanisms. Methods We predicted treatment outcomes in children with mild to severe asthma (N=365), according to changes in asthma control, lung function (FEV1, MEF50) and FENO values after 6 months of controller medication use, using RandomForest and AdaBoost classifiers. Results The highest prediction power is achieved for control-and, to lower extend, for FENO-related treatment outcomes. The most predictive variables for asthma control are related to asthma severity and total IgE, which was also predictive for FENO-based outcomes. MEF50-related treatment outcomes were better predicted than FEV1-based response and one of the best predictive variables for this response was hsCRP. Conclusions Our results suggest that asthma control-and FENO-based outcomes can be more accurately predicted using machine learning than FEV1 and MEF50. This supports the symptom control-based asthma management approach and its complementary FENO-guided tool in children. T2-high asthma seemed to respond best to anti-inflammatory treatment. The prediction of MEF50-based treatment outcomes emphasizes the role of the distal airways in childhood asthma. The results of this study in predicting treatment success will help to enable treatment optimization and to implement the concept of precision medicine in pediatric asthma treatment.

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Adherence to Mediterranean Diet and Maternal Lifestyle during Pregnancy: Island–Mainland Differentiation in the CRIBS Birth Cohort

Cited by 18 publications

References 38 publications

How Do Consumers Perceive Cultured Meat in Croatia, Greece, and Spain?

How Do Consumers Perceive Cultured Meat in Croatia, Greece, and Spain?

Assessment of Adherence to the Healthy Food Pyramid in Pregnant and Lactating Women

Predicting treatment outcomes using explainable machine learning in children with asthma

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