Publishing Nutrition Research: A Review of Multivariate Techniques—Part 3: Data Reduction Methods

Sociodemographic and Lifestyle Characteristics Associated with Maternal Dietary Patterns in Mexico

There is scarce evidence on sociodemographic and lifestyle characteristics that may explain adherence to different dietary patterns (DPs) during pregnancy. Our aims were to identify dietary patterns in a sample of pregnant Mexican women and to describe their association with selected sociodemographic and lifestyle characteristics. This is a secondary cross-sectional analysis of 252 mothers of children that participated as controls in a hospital-based case-control study of childhood leukemia. We obtained parents' information about selected sociodemographic characteristics, as well as alcohol and tobacco consumption. We also obtained dietary information during pregnancy. We identified DPs using cluster and factor analyses and we estimated their association with characteristics of interest. We identified two DPs using cluster analysis, which we called "Prudent" and "Non healthy", as well as three DPs through factor analysis, namely "Prudent", "Processed foods and fish", and "Chicken and vegetables". Characteristics associated with greater adherence to "Prudent" patterns were maternal education, older paternal age, not smoking, and being a government employee and/or uncovered population. Likewise, the "Processed foods and fish" pattern was associated with greater maternal and paternal education, as well as those with less household overcrowding. We did not identify sociodemographic variables related to the "Chicken and Vegetables" pattern. Our results may be useful to identify target populations that may benefit from interventions aimed to improve individual dietary decisions during pregnancy.

Exploring tradeoffs among diet quality and environmental impacts in self-selected diets: a population-based study

PURPOSE

Proposed sustainable diets often deviate dramatically from currently consumed diets, excluding or drastically reducing entire food groups. Moreover, their environmental sustainability tends to be measured only in terms of greenhouse gases emissions. The aim of this study was to overcome these limitations and identify a cluster of already adopted, relatively healthy diets with substantially lower environmental impacts than the average diet. We also aimed to estimate the reduction in multiple environmental impacts that could be achieved by shifting to this diet cluster and highlight possible tradeoffs among environmental impacts.

METHODS

The diet clusters were identified by applying energy-adjusted multiple factor analysis and hierarchical clustering to the dietary data of the National FinHealth 2017 Study (n = 5125) harmonized with life cycle assessment data on food products from Agribalyse 3.0 and Agri-Footprint using nutrient intakes and global warming potential, land use, and eutrophication of marine and freshwater systems as the active variables.

RESULTS

We identified five diet clusters, none of which had the highest overall diet quality and lowest impact for all four environmental indicators. One cluster, including twenty percent of the individuals in the sample was identified as a "best compromise" diet with the highest diet quality and the second lowest environmental impacts of all clusters, except for freshwater eutrophication. The cluster did not exclude any food groups, but included more fruits, vegetables, and fish and less of all other animal-source foods than average. Shifting to this cluster diet could raise diet quality while achieving significant reductions in most but not all environmental impacts.

CONCLUSION

There are tradeoffs among the environmental impacts of diets. Thus, future dietary analyses should consider multiple sustainability indicators simultaneously. Cluster analysis is a useful tool to help design tailored, socio-culturally acceptable dietary transition paths towards high diet quality and lower environmental impact.

Are Major a Posteriori Dietary Patterns Reproducible in the Italian Population? A Systematic Review and Quantitative Assessment

Although a posteriori dietary patterns (DPs) naturally reflect actual dietary behavior in a population, their specificity limits generalizability. Among other issues, the absence of a standardized approach to analysis have further hindered discovery of genuinely reproducible DPs across studies from the same/similar populations. A systematic review on a posteriori DPs from principal component analysis or exploratory factor analysis (EFA) across study populations from Italy provides the basis to explore assessment and drivers of DP reproducibility in a case study of epidemiological interest. First to our knowledge, we carried out a qualitative (i.e., similarity plots built on text descriptions) and quantitative (i.e., congruence coefficients, CCs) assessment of DP reproducibility. The 52 selected articles were published in 2001-2022 and represented dietary habits in 1965-2022 from 70% of the Italian regions; children/adolescents, pregnancy/breastfeeding women, and elderly were considered in 15 articles. The included studies mainly derived EFA-based DPs on food groups from food frequency questionnaires and were of "good quality" according to standard scales. Based on text descriptions, the 186 identified DPs were collapsed into 113 (69 food-based and 44 nutrient-based) apparently different DPs (39.3% reduction), later summarized along with the 3 "Mixed-Salad/Vegetable-based Patterns," "Pasta-and-Meat-oriented/Starchy Patterns," and "Dairy Products" and "Sweets/Animal-based Patterns" groups, by matching similar food-based and nutrient-based groups of collapsed DPs. Based on CCs (215 CCs, 68 DPs, 18 articles using the same input lists), all pairs of DPs showing the same/similar names were at least "fairly similar" and ∼81% were "equivalent." The 30 "equivalent" DPs ended up into 6 genuinely different DPs (80% reduction) that targeted fruits and (raw) vegetables, pasta and meat combined, and cheese and deli meats. Such reduction reflects the same study design, list of input variables, and DP identification method followed across articles from the same groups. This review was registered at PROSPERO as CRD42022341037.

Comparison of habitual and meal-specific dietary patterns identified by latent class analysis and confirmatory factor analysis in adults: A cross-sectional study

OBJECTIVE

The aim of this study was to compare characteristics of habitual and meal-specific dietary patterns identified by latent class analysis (LCA) and confirmatory factor analysis (CFA).

METHODS

Participants included 778 adults selected for the present cross-sectional study from local health care centers in Tehran, Iran. Three 24-h dietary recalls evaluated dietary intake. LCA was used to group study participants into exclusive subgroups of individuals with similar patterns of dietary intake. CFA was applied to identify patterns of habitual and meal-specific dietary intake. Analysis of variance was used to compare the average scores of habitual and meal-specific CFA-derived dietary patterns across classes identified by LCA.

RESULTS

Using habitual dietary intake, CFA grouped correlated food items into three major factors: fruits and vegetables, mixed, and Western dietary patterns. LCA grouped study participants with similar patterns of habitual intake into four subgroups of individuals: fruits and vegetables, mixed, Western, and low consumer classes. LCA-fruits and vegetables, LCA-Western, and LCA-mixed classes had, respectively, higher mean scores of CFA-fruits and vegetables, CFA-Western, and CFA-mixed dietary patterns compared with other classes (P < 0.001). Similar findings were observed for meal-specific dietary intake, where classes identified by LCA had the highest mean scores of their corresponding dietary pattern identified by CFA.

CONCLUSION

Habitual and meal-specific classes identified by LCA were well characterized by the dietary patterns derived by CFA, suggesting that LCA may be an appropriate statistical approach to classify study participants with similar patterns of intake into exclusive subgroups of individuals.

Cross-sectional and prospective associations between behavioural patterns and adiposity in school-aged children

OBJECTIVE

Behavioural patterns are important in understanding the synergistic effect of multiple health behaviours on childhood adiposity. Most previous evidence assessing associations between patterns and adiposity were cross-sectional and investigated two or three behaviour domains within patterns. This study aimed to identify behavioural patterns comprising four behaviour domains and investigate associations with adiposity risk in children.

DESIGN

Parent-report and accelerometry data were used to capture daily dietary, physical activity, sedentary behaviour and sleep data. Variables were standardised and included in the latent profile analysis to derive behavioural patterns. Trained researchers measured children's height, weight and waist circumference using standardised protocols. Associations of patterns and adiposity measures were tested using multiple linear regression.

SETTING

Melbourne, Australia.

PARTICIPANTS

A total of 337 children followed up at 6-8 years (T2) and 9-11 years (T3).

RESULTS

Three patterns derived at 6-8 years were broadly identified to be healthy, unhealthy and mixed patterns. Patterns at 9-11 years were dissimilar except for the unhealthy pattern. Individual behaviours characterising the patterns varied over time. No significant cross-sectional or prospective associations were observed with adiposity at both time points; however, children displaying the unhealthy pattern had higher adiposity measures than other patterns.

CONCLUSION

Three non-identical patterns were identified at 6-8 and 9-11 years. The individual behaviours that characterised patterns (dominant behaviours) at both ages are possible drivers of the patterns obtained and could explain the lack of associations with adiposity. Identifying individual behaviour pattern drivers and strategic intervention are key to maintain and prevent the decline of healthy patterns.

Impact of parental lifestyle patterns in the preconception and pregnancy periods on childhood obesity

Introduction

High prevalence of overweight and obesity already observed in preschool children suggests the involvement of early-life risk factors. Preconception period and pregnancy are crucial windows for the implementation of child obesity prevention interventions with parental lifestyle factors as relevant targets. So far, most studies have evaluated their role separately, with only a few having investigated their potential synergistic effect on childhood obesity. Our objective was to investigate parental lifestyle patterns in the preconception and pregnancy periods and their association with the risk of child overweight after 5 years.

Materials and methods

We harmonized and interpreted results from four European mother-offspring cohorts participating in the EndObesity Consortium [EDEN, France; Elfe, France; Lifeways, Ireland; and Generation R, Netherlands] with data available for 1,900, 18,000, 1,100, and 9,500 families, respectively. Lifestyle factors were collected using questionnaires and included parental smoking, body mass index (BMI), gestational weight gain, diet, physical activity, and sedentary behavior. We applied principal component analyses to identify parental lifestyle patterns in preconception and pregnancy. Their association with risk of overweight (including obesity; OW-OB) and BMI z-scores between 5 and 12 years were assessed using cohort-specific multivariable logistic and linear and regression models (adjusted for potential confounders including parental age, education level, employment status, geographic origin, parity, and household income).

Results

Among the various lifestyle patterns derived in all cohorts, the two explaining the most variance were characterized by (1) "high parental smoking, low maternal diet quality (and high maternal sedentary behavior in some cohorts)" and, (2) "high parental BMI and low gestational weight gain." Patterns characterized by high parental BMI, smoking, low diet quality or high sedentary lifestyle before or during pregnancy were associated with higher risk of OW-OB in children, and BMI z-score at any age, with consistent strengths of associations in the main cohorts, except for lifeways.

Conclusion

This project provides insight into how combined parental lifestyle factors in the preconception and pregnancy periods are associated with the future risk of child obesity. These findings are valuable to inform family-based and multi-behavioural child obesity prevention strategies in early life.

Relationship Between Human Milk Feeding Patterns and Growth in the First Year of Life in Infants with Congenital Heart Defects

The purpose of this study was to determine the relationship between patterning of human milk feeding and growth of infants with congenital heart defects in the first year of life. Inclusion criteria for this prospective cohort study included infants 0-21 days, who had undergone or had planned neonatal corrective or palliative surgery prior to hospital discharge, and whose mothers planned to feed human milk. Data on anthropometric measures (weight, length, head circumference) and infant milk type (human milk, formula, other) were collected at nine time points (0.5, 1, 2, 3, 4, 6, 8, 10, 12 months). Anthropometric data were converted to weight-for-age, length-for-age, head circumference-for-age, and weight-for-length Z-scores using World Health Organization growth reference data. Cluster analysis identified three milk type feeding patterns in the first year: Infants fed human milk only with no formula supplementation, infants fed human milk who then transitioned to a mix of human milk and formula, and infants who fed human milk and transitioned to formula only. General linear models assessed the effect of milk type feeding patterns on growth parameters over time. No effect of milk type pattern × time was found on longitudinal changes in weight-for-age (p for interaction = 0.228), length-for-age (p for interaction = 0.173), weight-for-length (p for interaction = 0.507), or head circumference-for-age (p for interaction = 0.311) Z-scores. In this cohort study, human milk alone or combined with infant formula supported age-appropriate growth in infants with congenital heart defects in the first year.

Lower adherence to a prudent dietary pattern is associated with earlier age at menarche in adolescents from the Growth and Obesity Chilean Cohort Study

Introduction

Early menarche is associated with obesity, and metabolic and mental health risks, among other diseases. Thus, it is relevant to identify modifiable risk factors of early menarche. Some nutrients and foods have been linked to pubertal timing, but how menarche relates to overall dietary patterns is unclear.

Methods

The aim of this study was to analyze the association between dietary patterns and age at menarche in a prospective cohort of Chilean girls from low and middle-income families. We conducted a survival analysis of 215 girls (median = 12.7 years, IQR = 12.2-13.2) from the Growth and Obesity Cohort Study (GOCS) who had been followed prospectively since 4 years of age (2006). Age at menarche and anthropometric measurements were recorded every 6 months since 7 years of age while diet (24-hour dietary recall) was collected for 11 years. Dietary patterns were obtained from exploratory factor analysis. Accelerated Failure Time models adjusted for potential confounding variables were used to study the association between dietary patterns and age at menarche.

Results

Girls' median age at menarche was 12.7 years. Three dietary patterns were identified: "Breakfast/Light Dinner," "Prudent" and "Snacking" which explained 19.5% of the diet variation. Girls in the lowest tertile of the "Prudent" pattern had menarche 3 months earlier than girls in the highest tertile (β: 0.022; 95% CI: 0.003; 0.041). "Breakfast/Light Dinner" and "Snacking" patterns were not associated with age at menarche.

Conclusion

Our results suggest that healthier dietary patterns during puberty might be associated with menarche timing. Nevertheless, further studies are required to confirm this result and to clarify the association between diet and puberty.

Dietary patterns and breast cancer risk, prognosis, and quality of life: A systematic review

Background

Statistics indicate that the morbidity of breast cancer is increasing globally, and its (overall figures) incidence has now surpassed that of lung cancer for the first time. The relation between a whole dietary pattern, rather than of a single food or nutrient, and breast cancer (BC) should be examined for findings to capture the complexities of diet and the potential for synergism between dietary components. Hence, the effects of dietary patterns on breast cancer have recently attracted increasing attention.

Objective

To systematically review the effects of dietary patterns on breast cancer risk, prognosis, and quality of life in survivors.

Methods

This systematic review was conducted following PRISMA guidelines and was registered in PROSPERO. Data from Ovid, China Biomedical Literature Database, Wanfang Data Knowledge Service Platform, CNKI, PubMed, Weipu, The Cochrane Library, Duxiu Data, ProQuest, Embase, Web of Science, and Scopus Database were retrieved and evaluated.

Results

A total of 47 studies that investigated the association between eating patterns and breast cancer were identified. Ten studies evaluated the effect of the model on treatment outcome and prognosis of breast cancer and two cross-sectional studies examined the influence of dietary patterns on quality of life. The resulting favorable dietary patterns were shown to regulate metabolic biomarkers, antioxidants, anti-inflammatory agents, and protective genes, and inhibit cell proliferation and invasion.

Conclusion

Numerous studies have examined the effects of healthy eating, plant-based, anti-inflammation, low-fat, and other favorable dietary patterns in relation to breast cancer. However, few studies reported significant associations and the studies had limitations, suggesting that the current findings should be interpreted with caution.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, CRD4202 2350171.

Characteristics associated with dietary patterns in Brazilian children under two years of age

OBJECTIVE

To analyze the dietary patterns of Brazilian children under two years of age and assess their association with sociodemographic characteristics and health service use.

METHODS

This is a cross-sectional study with data from the 2013 National Health Survey (PNS). Patterns were found for two age groups by principal component analysis and their correlation with characteristics of interest was tested by linear regression models.

RESULTS

We found two dietary patterns for our groups. The first consisted of the consumption of fresh or minimally processed foods and the second, of ultra-processed foods. The greater adherence of children between six and 11 months to the first pattern was associated with higher per capita family income and urban residences in the most developed regions of Brazil. At 12 months or more, adherence related to white race/color, higher per capita family incomes, residence in more developed regions, and visits to private childcare. Adherence to the second pattern among children under one year of age was inversely associated with Yellow or Indigenous race/color, residence in the Brazilian Northeast, and childcare in specialized public or private services. At 12 months or more, greater adherence was directly associated with Black or Brown children who resided in more developed regions, and inversely associated with those living in the Brazilian Northeast.

CONCLUSION

We found two opposite dietary patterns in Brazilian children under two years of age and that several social determinants modify their chance of adhering to these patterns.

Are Dietary Patterns Related to Cognitive Performance in 7-Year-Old Children? Evidence from a Birth Cohort in Friuli Venezia Giulia, Italy

Research from different sources supports a link between nutrition and neurodevelopment, but evidence is still sparse regarding the relationship between a posteriori dietary patterns (DPs) and cognitive performance in school-aged children. Within the Northern Adriatic Cohort II, Friuli Venezia Giulia, Italy, 379 7-year-old children were cross-sectionally evaluated. Dietary patterns were identified through a principal component factor analysis based on 37 nutrients from children’s 3-day dietary records. The Wechsler Intelligence Scale of Children (WISC-IV) test provided measures of cognitive performance, including the full-scale intelligence quotient (FSIQ) and single index scores. Each DP was related to FSIQ or single index scores through multiple robust linear regression models. We identified five DPs named “Dairy Products”, “Plant-based Foods”, “Fats”, “Meat and Potatoes”, and “Seafood” (63% of variance explained). After adjustment, no significant relationship was observed with the FSIQ score; positive associations were found between the “Seafood” DP and Verbal Comprehension Index or Perceptual Reasoning Index. The “Meat and Potatoes” and “Dairy Products” DPs were inversely associated with the Verbal Comprehension Index and Processing Speed Index scores, respectively. In the absence of a relation with the overall FSIQ score, single DPs might influence specific cognitive functions, including verbal and reasoning abilities, as targeted by single indexes, in the expected direction.

Fusion Evaluation of College Cultivation by Adaptive Multivariate Neural Network Model

The quality of graduates is the key factor in evaluating the cultivation effect of colleges and universities. Quantification of whether the graduates qualify for their working post in companies and industries provides conduction for further college cultivation reform enhancement. In this work, we proposed an adaptive multivariate neural network architecture for fusion evaluation of college student cultivation. Specifically, we designed a questionnaire to collect data on the current working status of 1231 graduates and recorded 32 in-school training items categorized into four different modules. For quantitative evaluation, 10 indices of career-require competence were set to describe the graduates' job abilities. The fused contribution of the in-school training items to the career-required competence was predicted by the multivariate network model with the linking weights adaptively trained. A comprehensive contribution matrix was generated by discrete PCA multivariate transforming to provide a digital reference for the network training. A 7-level scoring system was designed for quantifying the contribution matrix. For model optimization, the network structure was tuned by testing a different number of hidden nodes. The model was trained and optimized to reveal the direct correlation between college cultivation and job-required abilities. Experimental results indicated that the methodology we proposed is feasible to evaluate the cultivation mode in colleges and universities, theoretically and technically providing positive directions for colleges and universities to make their cultivation reforming, as to enhance the quality of their graduates.

Consumer Attitudes as Part of Lifestyle in the COVID-19 Emergency

The pandemic brought significant changes to the functioning of society. This article examines the opinion of consumers in south-eastern Poland on lifestyle elements such as shopping preferences, physical activity, holiday preferences and others, against the background of the COVID-19 situation. The aim of this study was to identify the relationship between selected components included in the lifestyle of society in the context of the COVID-19 emergency situation. The research was conducted from 9 November 2020 to 17 January 2021. In order to identify the respondents’ attitudes and their perception of the issues discussed in this study, a questionnaire was created containing a number of theses formulations assessed by the respondents in terms of compliance with their beliefs. The evaluation was carried out using a seven-point bipolar Likert scale with a neutral value. The study was not probabilistic, therefore the inference applies only to the studied group. A total of 737 questionnaires meeting the research assumptions were collected. The form was used to identify ecological attitudes, shopping behavior, food preferences, physical activity and tourist preferences in the COVID-19 situation in which the research was conducted. Also identified were holiday destinations in 2019 and 2020, preferred diet type, and socio-demographic background: sex, age, place of residence and approximate per capita income. The research revealed that the purchasing behavior of the respondents was a predictor of their physical activity and tourist preferences. Studies have also shown that the food preferences of the respondents are an important part of their balanced lifestyle and depend on the sex of the person. The respondents preferred an active lifestyle as a form of pro-health activity when living in the situation of COVID-19. During the COVID-19 pandemic, respondents’ interest in domestic tourism also increased.

Differing associations with childhood outcomes using behavioural patterns derived from three data reduction techniques

BACKGROUND

Behavioural patterns help to understand the influence of multiple health behaviours on childhood outcomes. Behavioural patterns derived using different data reduction techniques can be non-identical and may differentially associate with childhood outcomes. This study aimed to compare associations of behavioural patterns derived from three methods with three childhood outcomes.

METHODS

Data were from the Healthy Active Preschool and Primary Years study when children were 6-8 years old (n = 432). Cluster analysis (CA), latent profile analysis (LPA) and principal component analysis (PCA) were used to derive behavioural patterns from children's diet, physical activity, sedentary behaviour and sleep data. Behavioural data were obtained through parent report and accelerometry. Children's height, weight and waist circumference were measured by trained study staff. Health-related quality of life data were obtained using the Pediatric Quality of Life Inventory and academic performance scores were from a national test. Associations between derived patterns from each method and each of the outcomes were tested using linear regression (adjusted for child age and sex and parent education).

RESULTS

Three patterns were each derived using CA and LPA, and four patterns were derived using PCA. Each method identified a healthy, an unhealthy and a mixed (comprising healthy and unhealthy behaviours together) pattern. Differences in associations were observed between pattern groups from CA and LPA and pattern scores from PCA with the three outcomes.

CONCLUSIONS

Discrepancies in associations across pattern derivation methods suggests that the choice of method can influence subsequent associations with outcomes. This has implications for comparison across studies that have employed different methods.

Dietary patterns of 5-year-old children and their correlates: findings from a multi-ethnic Asian cohort

There is limited data on the dietary patterns of 5-year-old children in Asia. The study examined childhood dietary patterns and their maternal and child correlates in a multi-ethnic Asian cohort. Based on caregiver-reported 1-month quantitative FFQ of 777 children from the Growing Up in Singapore Towards healthy Outcomes cohort, cluster analysis identified two mutually exclusive clusters. Children in the 'Unhealthy' cluster (43·9 %) consumed more fries, processed meat, biscuits and ice cream, and less fish, fruits and vegetables compared with those in the 'Healthy' cluster (56·1 %). Children with mothers of lower educational attainment had twice the odds of being assigned to the 'Unhealthy' cluster (adjusted OR (95 % CI) = 2·19 (95 % CI 1·49-3·24)). Children of Malay and Indian ethnicities had higher odds of being assigned to the 'Unhealthy' cluster (adjusted OR = 25·46 (95 % CI 15·40, 42·10) and 4·03 (95 % CI 2·68-6·06), respectively), relative to Chinese ethnicity. In conclusion, this study identified two dietary patterns in children, labelled as the 'Unhealthy' and 'Healthy' clusters. Mothers' educational attainment and ethnicity were two correlates that were associated with the children's assignments to the clusters. These findings can assist in informing health promotion programmes targeted at Asian children.

Association Between Dietary Patterns and Plasma Lipid Biomarker and Female Breast Cancer Risk: Comparison of Latent Class Analysis (LCA) and Factor Analysis (FA)

Background: Diet research focuses on the characteristics of "dietary patterns" regardless of the statistical methods used to derive them. However, the solutions to these methods are both conceptually and statistically different. Methods: We compared factor analysis (FA) and latent class analysis (LCA) methods to identify the dietary patterns of participants in the Chinese Wuxi Exposure and Breast Cancer Study, a population-based case-control study that included 818 patients and 935 healthy controls. We examined the association between dietary patterns and plasma lipid markers and the breast cancer risk. Results: Factor analysis grouped correlated food items into five factors, while LCA classified the subjects into four mutually exclusive classes. For FA, we found that the Prudent-factor was associated with a lower risk of breast cancer [4th vs. 1st quartile: odds ratio (OR) for 0.70, 95% CI = 0.52, 0.95], whereas the Picky-factor was associated with a higher risk (4th vs. 1st quartile: OR for 1.35, 95% CI = 1.00, 1.81). For LCA, using the Prudent-class as the reference, the Picky-class has a positive association with the risk of breast cancer (OR for 1.42, 95% CI = 1.06, 1.90). The multivariate-adjusted model containing all of the factors was better than that containing all of the classes in predicting HDL cholesterol (p = 0.04), triacylglycerols (p = 0.03), blood glucose (p = 0.04), apolipoprotein A1 (p = 0.02), and high-sensitivity C-reactive protein (p = 0.02), but was weaker than that in predicting the breast cancer risk (p = 0.03). Conclusion: Factor analysis is useful for understanding which foods are consumed in combination and for studying the associations with biomarkers, while LCA is useful for classifying individuals into mutually exclusive subgroups and compares the disease risk between the groups.

Late Evening Eating Patterns among US Adults Vary in Their Associations With, and Impact on, Energy Intake and Diet Quality: Evidence from What We Eat in America, National Health and Nutrition Examination Survey 2013-2016

BACKGROUND

Evening eating has been associated with higher energy intake and lower nutrient density. However, these qualities may not characterize all late evening (LE) eating patterns.

OBJECTIVE

We sought to characterize US adults' LE eating patterns on a given day and identify differences, if any, in pattern-specific associations with, and impact on, daily energy intake and total diet quality.

DESIGN

LE eating patterns, energy intakes, and Healthy Eating Index (HEI) scores were identified using Day-1 dietary recall data from the cross-sectional National Health and Nutrition Examination Survey 2013-2016.

PARTICIPANTS/SETTING

The sample included adults aged ≥ 20 years (n = 9,861). LE reporters were respondents who consumed foods/beverages between 20:00 and 23:59 on the intake day.

MAIN OUTCOME MEASURES

Energy intake and HEI-2015 scores by LE status/pattern and the impact of LE consumption on these measures.

STATISTICAL ANALYSES

Cluster analysis assigned individuals to LE eating patterns based on the LE energy contribution of food/beverage groups. Regression models estimated energy intake and HEI-2015 scores; estimates were compared between LE reporters and nonreporters. Similarly, LE's contribution to total energy and the difference in total HEI inclusive vs exclusive of LE consumption were estimated and compared among patterns.

RESULTS

Among US adults, 64.4% were LE reporters. Eleven LE patterns were identified; the six most prevalent patterns (representing 89% of LE reporters) were further analyzed. Daily energy intake in all prevalent patterns except the fruit pattern exceeded that of nonreporters by ≥ 268 kcal (unadjusted; P < 0.001), varying by pattern. Conversely, total HEI score did not differ from that of nonreporters (51.0) in any pattern except the fruit pattern, where it was higher (57.4, unadjusted; P < 0.001). Generally, LE consumption's impact on energy was high and its impact on HEI scores was low.

CONCLUSIONS

Late evening food/beverage consumption is common among US adults, and LE patterns are not monolithic in their associations with, and impact on, total energy intake and dietary quality.

Pointers and Pitfalls in Interpreting Nutrition and Dietetics Research: The Importance of Statistical and Clinical Significance

This monograph focuses on understanding statistical and clinical significance and is one of a research and statistics series published by the statistical team of the Journal of the Academy of Nutrition and Dietetics. The content covers the research questions, the definition of clinical significance, hypothesis testing, p-values, effect sizes, sample sizes, confidence intervals, power analyses, minimal clinically important differences, and validity. This monograph concludes with a summary of the importance of clinical and statistical results, for nutrition professionals to consider when assessing statistical and clinical significance. The assessment will help readers make subjective clinical judgements in the application of research findings based on their experience.

Dietary networks identified by Gaussian graphical model and general and abdominal obesity in adults

BACKGROUND

Gaussian graphical model (GGM) has been introduced as a new approach to identify patterns of dietary intake. We aimed to investigate the link between dietary networks derived through GGM and obesity in Iranian adults.

METHOD

A cross-sectional study was conducted on 850 men and women (age range: 20-59 years) who attended the local health centers in Tehran. Dietary intake was evaluated by using a validated food frequency questionnaire. GGM was applied to identify dietary networks. The odds ratios (ORs) and 95% confidence intervals (CIs) of general and abdominal adiposity across tertiles of dietary network scores were estimated using logistic regression analysis controlling for age, sex, physical activity, smoking status, marital status, education, energy intake and menopausal status.

RESULTS

GGM identified three dietary networks, where 30 foods were grouped into six communities. The identified networks were healthy, unhealthy and saturated fats networks, wherein cooked vegetables, processed meat and butter were, respectively, central to the networks. Being in the top tertile of saturated fats network score was associated with a higher likelihood of central obesity by waist-to-hip ratio (OR: 1.56, 95%CI: 1.08, 2.25; P for trend: 0.01). There was also a marginally significant positive association between higher unhealthy network score and odds of central obesity by waist circumference (OR: 1.37, 95%CI: 0.94, 2.37; P for trend: 0.09). Healthy network was not associated with central adiposity. There was no association between dietary network scores and general obesity.

CONCLUSIONS

Unhealthy and saturated fat dietary networks were associated with abdominal adiposity in adults. GGM-derived dietary networks represent dietary patterns and can be used to investigate diet-disease associations.

Association between dietary patterns and risk of breast cancer in Chinese female population: a latent class analysis

OBJECTIVE

To determine if specific dietary patterns are associated with breast cancer (BC) risk in Chinese women.

DESIGN

Latent class analysis (LCA) was performed to identify generic dietary patterns based on daily food-frequency data.

SETTING

The Chinese Wuxi Exposure and Breast Cancer Study (2013-2014).

PARTICIPANTS

A population-based case-control study (695 cases, 804 controls).

RESULTS

Four dietary patterns were identified, Prudent, Chinese traditional, Western and Picky; the proportion in the controls and cases was 0·30/0·32/0·16/0·23 and 0·29/0·26/0·11/0·33, respectively. Women in Picky class were characterised by higher extreme probabilities of non-consumption of specific foods, the highest probabilities of consumption of pickled foods and the lowest probabilities of consumption of cereals, soya foods and nuts. Compared with Prudent class, Picky class was associated with a higher risk (OR = 1·42, 95 % CI 1·06, 1·90), while the relevant association was only in post- (OR = 1·44, 95 % CI 1·01, 2·05) but not in premenopausal women. The Western class characterised by high-protein, high-fat and high-sugar foods, and the Chinese traditional class characterised by typical consumption of soya foods and white meat over red meat, both of them showed no difference in BC risk compared with Prudent class did.

CONCLUSIONS

LCA captures the heterogeneity of individuals embedded in the population and could be a useful approach in the study of dietary pattern and disease. Our results indicated that the Picky class might have a positive association with the risk of BC.

Association between body weight misperception and dietary patterns in Brazilian adolescents: Cross-sectional study using ERICA data

The association between body image and eating behaviors or weight control strategies has been demonstrated in the scientific literature, but there is a lack of evidence on the association between weight misperception and food consumption indicators in adolescents. This study aimed to evaluate the association between weight misperception and dietary patterns (DPs) in the Brazilian Study of Cardiovascular Risks in Adolescents (ERICA). It was a national school-based cross-sectional study conducted among students aged 12-17 years. Data were collected in the form of anthropometric measurements, responses in self-answered questionnaires, and 24-h dietary recall. The following variables were assessed: weight underestimation and overestimation (independent variables), which were defined as the presence of a disagreement between nutritional status and self-perceived weight; dietary patterns (dependent variables), defined by a posteriori method using principal component factor analysis; and individual and demographic variables (covariates). Data analysis was performed using the Poisson regression models method, stratified by sex. A total of 52,038 adolescents with normal weights were evaluated. The weight misperception prevalence was 34.0% (95% confidence interval [CI]: 33.0, 35.0). Three DPs were identified: "Traditional Brazilian," "Processed meat sandwiches and coffee," and "Ultra-processed and sweet foods." In girls, weight underestimation was directly associated with the "Traditional Brazilian" (1.24; 95% CI: 1.08, 1.43) and "Ultra-processed and sweet foods" DPs (1.29; 95% CI: 1.09, 1.54), and overestimation was inversely associated with all the DPs. In boys, a direct association between underestimation and the "Ultra-processed and sweet foods" DP (1.29; 95% CI: 1.10, 1.51) was found. Overestimation was inversely associated with the "Traditional Brazilian" DP (0.79; 95% CI: 0.63, 0.99). The inverse association between overestimation and the "Traditional Brazilian" DP, and the direct association between underestimation and the "Ultra-processed and sweet foods" DP indicated that weight misperception was related to unhealthy eating habits in Brazilian adolescents.

Maternal Dietary Quality and Dietary Inflammation Associations with Offspring Growth, Placental Development, and DNA Methylation

The ‘Developmental Origins of Health and Diseases’ hypothesis posits that prenatal maternal diet influences offspring growth and later life health outcomes. Dietary assessment has focused on selected nutrients. However, this approach does not consider the complex interactions between foods and nutrients. To provide a more comprehensive approach to public health, dietary indices have been developed to assess dietary quality, dietary inflammation and risk factors for non-communicable diseases. Thus far, their use in the context of placental development is limited and associations with offspring outcomes have been inconsistent. Although epidemiological studies have focused on the role of maternal diet on foetal programming, the underlying mechanisms are still poorly understood. Some evidence suggests these associations may be driven by placental and epigenetic changes. In this narrative review, we examine the current literature regarding relationships between key validated diet quality scores (Dietary Inflammatory Index [DII], Mediterranean diet [MD], Healthy Eating Index [HEI], Alternative Healthy Eating Index [AHEI], Dietary Approaches to Stop Hypertension [DASH], Glycaemic Index [GI] and Glycaemic Load [GL]) in pregnancy and birth and long-term offspring outcomes. We summarise findings, discuss potential underlying placental and epigenetic mechanisms, in particular DNA methylation, and highlight the need for further research and public health strategies that incorporate diet quality and epigenetics.

A comparison of children's diet and movement behaviour patterns derived from three unsupervised multivariate methods

Background

Behavioural patterns are typically derived using unsupervised multivariate methods such as principal component analysis (PCA), latent profile analysis (LPA) and cluster analysis (CA). Comparability and congruence between the patterns derived from these methods has not been previously investigated, thus it’s unclear whether patterns from studies using different methods are directly comparable. This study aimed to compare behavioural patterns derived across diet, physical activity, sedentary behaviour and sleep domains, using PCA, LPA and CA in a single dataset.

Methods

Parent-report and accelerometry data from the second wave (2011/12; child age 6-8y, n = 432) of the HAPPY cohort study (Melbourne, Australia) were used to derive behavioural patterns using PCA, LPA and CA. Standardized variables assessing diet (intake of fruit, vegetable, sweet, and savoury discretionary items), physical activity (moderate- to vigorous-intensity physical activity [MVPA] from accelerometry, organised sport duration and outdoor playtime from parent report), sedentary behaviour (sedentary time from accelerometry, screen time, videogames and quiet playtime from parent report) and sleep (daily sleep duration) were included in the analyses. For each method, commonly used criteria for pattern retention were applied.

Results

PCA produced four patterns whereas LPA and CA each generated three patterns. Despite the number and characterisation of the behavioural patterns derived being non-identical, each method identified a healthy, unhealthy and a mixed pattern. Three common underlying themes emerged across the methods for each type of pattern: (i) High fruit and vegetable intake and high outdoor play (“healthy”); (ii) poor diet (either low fruit and vegetable intake or high discretionary food intake) and high sedentary behaviour (“unhealthy”); and (iii) high MVPA, poor diet (as defined above) and low sedentary time (“mixed”).

Conclusion

Within this sample, despite differences in the number of patterns derived by each method, a good degree of concordance across pattern characteristics was seen between the methods. Differences between patterns could be attributable to the underpinning statistical technique of each method. Therefore, acknowledging the differences between the methods and ensuring thorough documentation of the pattern derivation analyses is essential to inform comparison of patterns derived through a range of approaches across studies.

Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach

The human diet consists of a complex mixture of components. To realistically assess dietary impacts on health, new statistical tools that can better address nonlinear, collinear, and interactive relationships are necessary. Using data from 1,928 healthy participants in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort (1985-2006), we explored the association between 12 dietary factors and 10-year predicted risk of atherosclerotic cardiovascular disease (ASCVD) using an innovative approach, Bayesian kernel machine regression (BKMR). Employing BKMR, we found that among women, unprocessed red meat was most strongly related to the outcome: An interquartile range increase in unprocessed red meat consumption was associated with a 0.07-unit (95% credible interval: 0.01, 0.13) increase in ASCVD risk when intakes of other dietary components were fixed at their median values (similar results were obtained when other components were fixed at their 25th and 75th percentile values). Among men, fruits had the strongest association: An interquartile range increase in fruit consumption was associated with -0.09-unit (95% credible interval (CrI): -0.16, -0.02), -0.10-unit (95% CrI: -0.16, -0.03), and -0.11-unit (95% CrI: -0.18, -0.04) lower ASCVD risk when other dietary components were fixed at their 25th, 50th (median), and 75th percentile values, respectively. Using BKMR to explore the complex structure of the total diet, we found distinct sex-specific diet-ASCVD relationships and synergistic interaction between whole grain and fruit consumption.

Risk and protective behaviors for chronic non-communicable diseases among Brazilian adults

OBJECTIVES

This study aimed to analyze behavioral patterns of protective and risk factors for chronic non-communicable diseases (NCDs) among adults and to explore the association between these patterns and sociodemographic characteristics using data from the National Health Survey 2013.

STUDY DESIGN

This was a cross-sectional study.

METHODS

This is a population-based study, nationwide, of individuals aged ≥18 years (n = 60,202). The sampling process used was grouping with three selection stages: census sector, households, and individuals. The factor analysis by principal component was used to identify behavioral patterns of protective and risk factors for NCDs. Linear regression was used to explore the association between patterns and sociodemographic characteristics.

RESULTS

Two behavioral patterns were identified: a 'protective pattern' featured by consumption of vegetable, fruits/natural fruit juice, and low-fat milk and recommended physical activity practice during leisure time; and a 'risk pattern' characterized by consumption of high-fat meat and soft drinks, alcohol abuse, and smoking habit. Adherence to the protective pattern was associated with older White women who had higher levels of education, were economically active, and lived in the urban areas of the country. Younger, economically active men living in the urban areas were associated with the risk patterns.

CONCLUSIONS

Two behavioral patterns for NCDs have been identified and are distributed non-randomly in the adult Brazilian population. These findings are expected to contribute to better targeting health promotion and prevention of NCDs.

Dietary patterns and risk of nasopharyngeal carcinoma: a population-based case-control study in southern China

BACKGROUND

Dietary factors, such as consumption of preserved foods, fresh vegetables, and fruits, have been linked to the risk of nasopharyngeal carcinoma (NPC). However, little is known about associations between dietary patterns and the risk of NPC in NPC-endemic areas.

OBJECTIVES

We aimed to evaluate whether dietary patterns are associated with NPC risk.

METHODS

We studied 2554 newly diagnosed NPC patients aged 20-74 y living in 3 endemic regions of southern China, and 2648 population-based controls frequency-matched to case patients by age, sex, and region, between 2010 and 2014. Dietary components were derived from food frequency data in adulthood and adolescence using principal component analysis. Four dietary components were identified and highly similar in adulthood and adolescence. We used multivariable unconditional logistic regression to calculate ORs with 95% CIs for the association between dietary patterns and NPC risk.

RESULTS

Compared with the lowest quartile, individuals in the highest quartile of the "plant-based factor" in adulthood had a 52% (OR: 0.48; 95% CI: 0.38, 0.59) decreased risk of NPC, and those in the highest quartile of the "animal-based factor" had a >2-fold (OR: 2.26; 95% CI: 1.85, 2.77) increased risk, with a monotonic dose-response trend (P-trend < 0.0001). Similar but weaker associations were found in adolescence. High intakes of the "preserved-food factor" were associated with increased NPC risk in both periods, although stronger associations were found in adolescence. Results from joint analysis and sensitivity analyses indicated that dietary factors in adulthood might be more stable and robust predictors of NPC risk than those in adolescence.

CONCLUSIONS

Our results deliver compelling evidence that plant- and animal-based dietary factors are associated with NPC risk, and provide more insights on the associations of diets and cancer risk that may assist healthy diet recommendations.

A review of statistical methods for dietary pattern analysis

Background

Dietary pattern analysis is a promising approach to understanding the complex relationship between diet and health. While many statistical methods exist, the literature predominantly focuses on classical methods such as dietary quality scores, principal component analysis, factor analysis, clustering analysis, and reduced rank regression. There are some emerging methods that have rarely or never been reviewed or discussed adequately.

Methods

This paper presents a landscape review of the existing statistical methods used to derive dietary patterns, especially the finite mixture model, treelet transform, data mining, least absolute shrinkage and selection operator and compositional data analysis, in terms of their underlying concepts, advantages and disadvantages, and available software and packages for implementation.

Results

While all statistical methods for dietary pattern analysis have unique features and serve distinct purposes, emerging methods warrant more attention. However, future research is needed to evaluate these emerging methods’ performance in terms of reproducibility, validity, and ability to predict different outcomes.

Conclusion

Selection of the most appropriate method mainly depends on the research questions. As an evolving subject, there is always scope for deriving dietary patterns through new analytic methodologies.

Metabolomic Biomarkers of Healthy Dietary Patterns and Cardiovascular Outcomes

PURPOSE OF REVIEW

Healthy dietary patterns are recommended for prevention of CVD. Recently, metabolomics has been used to identify biomarkers of healthy dietary patterns and elucidate mechanisms underlying diet-disease associations. This review provides an overview of approaches to define healthy dietary patterns, discusses important issues related to using metabolomics to describe healthy dietary patterns, and summarizes studies identifying blood metabolites associated with hypothesis-driven healthy dietary patterns and cardiovascular risk factors and incident CVD.

RECENT FINDINGS

We identified 17 studies which reported on blood metabolomic signatures of 5 healthy dietary patterns (Healthy Eating Index, Alternative Healthy Eating Index, the Dietary Approaches to Stop Hypertension diet, Mediterranean diet, vegetarian diet). Four of these studies evaluated associations between diet-related metabolites and cardiovascular outcomes. Many metabolites replicated across different healthy dietary patterns, which suggest that they may represent biomarkers of generally healthy diets. Unsaturated lipids positively associated with healthy dietary patterns were inversely associated with incident CVD, suggesting that they may be a pathway through which diet is associated with a lower risk of CVD. Although many metabolites replicated across cross-sectional studies, few metabolites identified as candidate biomarkers of healthy diets in feeding studies replicated in observational studies. Additionally, limited evidence exists on the ability of diet-related metabolites to predict cardiovascular outcomes. Replication of candidate biomarkers of dietary patterns in different study designs and more studies evaluating the associations between diet-related metabolites and cardiovascular outcomes are needed.

Factor Analysis Reduces Complex Measures of Nutrition Environments in US Elementary and Middle Schools into Cohesive Dimensions in the Healthy Communities Study

BACKGROUND

Although it has been recommended that schools be the hub of efforts to improve child nutrition, research describing school nutrition environments in US public schools and their associations with child health is limited.

OBJECTIVE

This study aimed to evaluate the applicability of factor analysis methods to characterize school nutrition environments by identifying underlying factors, or dimensions, in the observed data and to examine the relation between school nutrition environment dimensions and child anthropometric and dietary outcomes.

METHODS

This study examined a cross-sectional sample of 4635 US children aged 4-15 y from 386 US elementary and middle schools from the Healthy Communities Study (2013-2015). Data collected from schools were used to create 34 variables that assessed the school nutrition environment. To identify dimensions of school nutrition environments, exploratory factor analysis was conducted with orthogonal rotation, and factor scores were derived using methods to account for sporadic missing data. Mixed-effects regression models adjusted for child- and community-level variables and clustered by community and school examined the associations of school nutrition environment dimensions with child anthropometric and dietary outcomes.

RESULTS

Six dimensions of school nutrition environments were derived: nutrition education, food options, wellness policies, dining environment, unhealthy food restriction, and nutrition programs. The unhealthy food restriction dimension was negatively associated with added sugar intake (β = -1.13, P < 0.0001), and the wellness policies dimension was positively associated with waist circumference (β = 0.57, P = 0.01).

CONCLUSIONS

This study demonstrates how factor analysis can reduce multiple measures of complex school nutrition environments into conceptually cohesive dimensions for purposes of assessing the relation of these dimensions to student health-related outcomes. Findings were mixed and indicate that the restriction of unhealthy foods in school is associated with lower added sugar intake. Additional, longitudinal studies are needed to substantiate the utility of this method for identifying promising school nutrition environments.

Healthy Dietary Pattern is Related to Blood Lipids in Patients with Type 1 Diabetes Mellitus: A Cross-sectional Study from a Developing Country

Background:

The association between dietary patterns and cardiovascular disease (CVD) risk factors has been investigated in very limited studies in patients with type 1 diabetes mellitus (T1DM). The aim of this study was to determine the relationship between the major dietary patterns and CVD risk factors in these patients.

Methods:

A cross-sectional study was performed on 169 females of 18--35 years who were diagnosed with T1DM attending Iranian Diabetes Association in Tehran. Anthropometric measures, blood glucose, and lipid levels of all participants were measured. Dietary data was collected using a food frequency questionnaire. Dietary patterns were determined by factor analysis. Using the analysis of covariance (ANCOVA), mean value of the biochemical factors across the tertiles of dietary patterns was compared.

Results:

Three major dietary patterns were identified: the grain, legume and nut (GLN), the fruits and vegetables (FV), and the high calorie foods, salty snacks, sweet and dessert (HSD). After adjustment for age, body mass index and energy intake, subjects who were in the highest tertile of FV pattern had significantly lower levels of LDL-c (P = 0.01), triglyceride (TG) (P = 0.02), and total cholesterol (P = 0.01). GLN and HSD patterns had no significant relationship with blood glucose and lipids.

Conclusions:

This study demonstrates that a dietary pattern rich in vegetables and fruits may be inversely associated with dyslipidemia in patients with T1DM. The results can be used for developing interventions that aim to promote healthy eating for the prevention of CVD in these patients.

Validation of a life-logging wearable camera method and the 24-h diet recall method for assessing maternal and child dietary diversity

Accurate and timely data are essential for identifying populations at risk for undernutrition due to poor-quality diets, for implementing appropriate interventions and for evaluating change. Life-logging wearable cameras (LLWC) have been used to prospectively capture food/beverage consumed by adults in high-income countries. This study aimed to evaluate the concurrent criterion validity, for assessing maternal and child dietary diversity scores (DDS), of a LLWC-based image-assisted recall (IAR) and 24-h recall (24HR). Direct observation was the criterion method. Food/beverage consumption of rural Eastern Ugandan mothers and their 12-23-month-old child (n 211) was assessed, for the same day for each method, and the IAR and 24HR DDS were compared with the weighed food record DDS using the Bland-Altman limits of agreement (LOA) method of analysis and Cohen's κ. The relative bias was low for the 24HR (-0·1801 for mothers; -0·1358 for children) and the IAR (0·1227 for mothers; 0·1104 for children), but the LOA were wide (-1·6615 to 1·3012 and -1·6883 to 1·4167 for mothers and children via 24HR, respectively; -2·1322 to 1·8868 and -1·7130 to 1·4921 for mothers and children via IAR, respectively). Cohen's κ, for DDS via 24HR and IAR, was 0·68 and 0·59, respectively, for mothers, and 0·60 and 0·59, respectively, for children. Both the 24HR and IAR provide an accurate estimate of median dietary diversity, for mothers and their young child, but non-differential measurement error would attenuate associations between DDS and outcomes, thereby under-estimating the true associations between DDS - where estimated via 24HR or IAR - and outcomes measured.

A systematic review of lifestyle patterns and their association with adiposity in children aged 5-12 years

Diet, physical activity, sedentary behaviour and sleep are typically examined independently with childhood adiposity; however, their combined influence remains uncertain. This review aims to systematically summarize evidence on the clustering of these behaviours through lifestyle patterns and evaluate associations with adiposity in children aged 5-12 years. Search strategies were run in six databases. Twenty-eight papers met the inclusion criteria, six of which included all four behaviours. A range of lifestyle patterns were identified (healthy, unhealthy and mixed). Mixed patterns were most frequently reported. Unhealthy patterns comprising low physical activity and high sedentary behaviour were also frequently observed. Mixed patterns comprising healthy diets, low physical activity and high sedentary behaviour were more commonly seen in girls, whereas boys were more physically active, similarly sedentary and had unhealthier diets. Children from lower socio-economic backgrounds tended to more frequently display unhealthy patterns. Unhealthy lifestyle patterns were more often associated with adiposity risk than healthy and mixed patterns. With few studies including all four behaviours, it is difficult to establish a clear picture of their interplay and associations with adiposity. Nonetheless, reliance on lifestyle patterns is likely more beneficial than individual behaviours in targeting adiposity and improving understanding of how these behaviours influence health.

Dietary Patterns of Adolescents from the Chilean Growth and Obesity Cohort Study Indicate Poor Dietary Quality

Diet during adolescence can have lasting effects on nutritional status, health, and development. We hypothesized that dietary patterns with low-quality nutrition are associated with overweightness. We collected data for 882 Chilean adolescents from the Growth and Obesity Cohort Study (mean age: 12 years). Dietary intake was assessed through 24-h recalls and weight status data were obtained during clinical visits. Dietary patterns were obtained through exploratory factor analysis. Multiple logistic regression models were used to examine cross-sectional associations between dietary patterns and overweight (BMI z-score ≥ 1SD). Four dietary patterns were identified: "Breakfast/Light dinner", "Natural foods", "Western", and "Snacking". "Breakfast/Light dinner", "Western", and "Snacking" patterns provided higher energy and excess nutrients (sodium, saturated fat, and added sugar). Moreover, adolescents with higher adherence to "Western" or " Snacking" patterns (third tertile) had higher odds of being classified as overweight (OR = 1.67; 95%CI: 1.103-2.522 and OR = 1.86; 95%CI: 1.235-2.792, respectively) than those with lower adherence (first tertile). "Natural foods" pattern was also associated with overweightness (OR = 1.83; 95%CI: 1.219-2.754). These dietary patterns were associated with overconsumption of nutrients of public health concern. Three of the four main dietary patterns were associated with overweightness. These results highlight the need of prioritizing adolescents on obesity prevention strategies.

Trend in dietary patterns among adults from Brazilian state capitals

OBJECTIVE

To describe and analyze the trend in dietary patterns followed by the adult population aged 18 to 44 years living in Brazilian state capitals between 2007 and 2012.

METHODS

We identified dietary patterns using the principal component analysis (PCA). The analysis retained components with eigenvalues >1.0 and highlighted factor loadings (FLs) >|0.2|. After the identification of four patterns, they received standardized scores with zero mean. The mean scores were presented for each pattern according to gender, age group, schooling, and year of data collection. We estimated the temporal variation of the mean scores of the patterns by linear regression.

RESULTS

We identified four dietary patterns in the population: prudent, transition, western, and traditional. We found an increasing trend in the mean score of the patterns: prudent, western, and traditional and a reduced mean score in the transition pattern. Individuals with better education showed greater adherence to the prudent pattern. Less-educated individuals presented higher adherence to the western and traditional patterns.

CONCLUSION

Public policies targeting the population with lower schooling and men are necessary due to their greater adherence to unhealthy dietary patterns.

Association between Dietary Intake of One-Carbon Metabolism Nutrients in the Year before Pregnancy and Birth Anthropometry

Few studies have evaluated the role of methylation-pathway nutrients involved in fetal growth (B vitamins, choline, betaine, and methionine). These one-carbon metabolism (OCM) nutrients are essential for DNA methylation in the periconception period. We aimed to characterize dietary patterns of 1638 women from the EDEN mother-child cohort in the year before pregnancy according to the contribution of OCM nutrients and to study the association of such patterns with anthropometric measurements at birth. Dietary intake before pregnancy was assessed by using a semi-quantitative food frequency questionnaire. We used the reduced-rank regression (RRR) method to identify dietary patterns using OCM nutrients as intermediate variables. We ran linear regressions models to study the association between dietary patterns scores and birth weight, length, head circumference, gestational age, and sex-specific z-scores, adjusting for maternal characteristics and vitamin supplementation before and during pregnancy. Three patterns, “varied and balanced”, “vegetarian tendency”, and “bread and starchy food” were identified, explaining 58% of the variability in OCM nutrient intake. Higher scores on the “varied and balanced” pattern tended to be associated with higher birth length and weight. In mainly well-nourished young French women, we did not find evidence that variability in OCM nutrient intake has major effects on fetal growth.

Dietary Patterns and Cognitive Health in Older Adults: A Systematic Review

While the role of diet and nutrition in cognitive health and prevention of dementia in older adults has attracted much attention, the efficacy of different dietary patterns remains uncertain. Previous reviews have mainly focused on the Mediterranean diet, but either omitted other dietary patterns, lacked more recent studies, were based on cross-sectional studies, or combined older and younger populations. We followed PRISMA guidelines, and examined the efficacy of current research from randomized controlled trials and cohort studies on the effects of different dietary patterns. We reviewed the Mediterranean diet, Dietary Approach to Stop Hypertension (DASH) diet, the Mediterranean-DASH diet Intervention for Neurodegenerative Delay (MIND) diet, Anti-inflammatory diet, Healthy diet recommended by guidelines via dietary index, or Prudent healthy diets generated via statistical approaches, and their impact on cognitive health among older adults. Of 38 studies, the Mediterranean diet was the most investigated with evidence supporting protection against cognitive decline among older adults. Evidence from other dietary patterns such as the MIND, DASH, Anti-inflammatory, and Prudent healthy diets was more limited but showed promising results, especially for those at risk of cardiovascular disease. Overall, this review found positive effects of dietary patterns including the Mediterranean, DASH, MIND, and Anti-inflammatory diets on cognitive health outcomes in older adults. These dietary patterns are plant-based, rich in poly- and mono-unsaturated fatty acids with lower consumption of processed foods. Better understanding of the underlying mechanisms and effectiveness is needed to develop comprehensive and practical dietary recommendations against age-related cognitive decline among older adult.

Patterns of PCBs and OCPs exposure in a sample of Lebanese adults: The role of diet and physical activity

BACKGROUND

Exposure to persistent organic pollutants (POPs) in the general population is 90% from food intake. Dietary patterns provide a global estimation of exposure to POPs, taking into account multiple food sources of environmental contaminants.

OBJECTIVES

To evaluate the association of dietary, socio-demographic, anthropometric, and lifestyle-related variables with clusters of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs), in a sample of students and employees of Saint Joseph University of Beirut.

METHODS

A total of 302 participants were randomly recruited. Questionnaires covering dietary, socio-demographic, and lifestyle-related characteristics were administered. Anthropometric measurements were obtained. Serum concentrations of six indicator PCBs (PCB 28, 52, 101, 138, 153 and 180) and four OCPs, hexachlorobenzene (HCB), β-hexachlorocyclohexanes (β-HCH), p,p'-dichlorodiphenyltrichloroethane (DDT) and its metabolite p,p'-dichlorodiphenyldichloroethylene (DDE) were measured, and cluster analysis was applied. We evaluated the association of dietary intake with PCBs/OCPs exposure using two different approaches: food consumption categories and dietary patterns retrieved from principal component analysis (PCA).

RESULTS

Three clusters of PCBs/OCPs were obtained: middle-level, high-level, and low-level. Practicing physical activity was associated with a three times higher risk of having high-level PCBs/OCPs, after adjustment for confounding variables (ORa = 2.97; CI = 1.23-7.19; p < 0.05). The highest tertile of fish and shellfish consumption increased by three-folds the odds of having high-level PCBs/OCPs (ORa = 3.41; CI = 1.07-10.84; p < 0.05). PCA revealed six dietary patterns. A "cereals, fats and oils, and eggs" dietary pattern was associated with 50% increase in the risk of having high-level PCBs/OCPs (ORa = 1.48; CI = 1.03-2.13; p < 0.05).

CONCLUSION

The present results offer a valuable contribution to the understanding of the factors increasing exposure to POPs, namely fish consumption and the "cereals, fats and oils, and eggs" dietary pattern. We also demonstrated that physical activity was positively associated with a higher risk of exposure to PCBs and OCPs, knowing that data on this matter are scarce.

Sketching the Power of Machine Learning to Decrypt a Neural Systems Model of Behavior

Uncovering brain-behavior mechanisms is the ultimate goal of neuroscience. A formidable amount of discoveries has been made in the past 50 years, but the very essence of brain-behavior mechanisms still escapes us. The recent exploitation of machine learning (ML) tools in neuroscience opens new avenues for illuminating these mechanisms. A key advantage of ML is to enable the treatment of large data, combing highly complex processes. This essay provides a glimpse of how ML tools could test a heuristic neural systems model of motivated behavior, the triadic neural systems model, which was designed to understand behavioral transitions in adolescence. This essay previews analytic strategies, using fictitious examples, to demonstrate the potential power of ML to decrypt the neural networks of motivated behavior, generically and across development. Of note, our intent is not to provide a tutorial for these analyses nor a pipeline. The ultimate objective is to relate, as simply as possible, how complex neuroscience constructs can benefit from ML methods for validation and further discovery. By extension, the present work provides a guide that can serve to query the mechanisms underlying the contributions of prefrontal circuits to emotion regulation. The target audience concerns mainly clinical neuroscientists. As a caveat, this broad approach leaves gaps, for which references to comprehensive publications are provided.

Parental Perceived Travel Time to and Reported Use of Food Retailers in Association with School Children's Dietary Patterns

Considering the association between the neighborhood food environment and individual eating behaviors, this study aimed to assess the association between parents' reported use of food facilities by their children, and parental perceived travel time to food facilities, with their children's dietary patterns. Parents reported the use of supermarkets, full-service and fast-food restaurants, and perceived travel time to these food retailers. To assess school children's food consumption, a previous day dietary recall was applied. Factor analysis was conducted to identify dietary patterns. To test the association between reported use and perceived travel time to food retailers and school children's dietary patterns, we performed multilevel linear regression analyses. Parents' reported use of supermarkets was associated with children's higher score in the "Morning/Evening Meal" pattern. The use of full-service and fast-food restaurants was associated with children's higher score in the "Fast Food" pattern. Higher parental perceived travel time to full-service and fast-food restaurants was associated with children's lower score in the "Fast Food" pattern. Although the use of full-service and fast-food restaurants was associated with a less healthy dietary pattern, the perception of living further away from these food retailers may pose a barrier for the use of these facilities.

Padrões alimentares de adolescentes brasileiros por regiões geográficas: análise do Estudo de Riscos Cardiovasculares em Adolescentes (ERICA)

O estudo teve como objetivo identificar os padrões alimentares de adolescentes brasileiros para cada uma das cinco regiões do país, e verificar se há diferença na adesão dos padrões alimentares de acordo com idade, sexo e tipo de escola. Foram analisados dados de 71.298 adolescentes de 12 a 17 anos que participaram do Estudo de Riscos Cardiovasculares em Adolescentes (ERICA), pesquisa transversal, nacional, multicêntrica e de base escolar. Os dados de consumo alimentar foram obtidos por meio de recordatório alimentar de 24hs, e para a identificação dos padrões alimentares foi aplicada análise fatorial. A associação entre as características dos adolescentes e os padrões alimentares foi verificada por meio de análises de regressão linear, estratificadas por idade e ajustadas por estado nutricional, ingestão energética total e atividade física. Nas cinco regiões foram identificados três padrões alimentares com características similares: padrão tradicional, padrão pão e café e padrão não saudável. A Região Norte apresentou um quarto padrão alimentar caracterizado por alimentos típicos da região: padrão tradicional Norte. Em todas as regiões, os adolescentes do sexo masculino registraram maior adesão ao padrão tradicional e menor adesão ao padrão não saudável. entre os estudantes de escolas privadas foi observada maior adesão ao padrão não saudável e menor adesão ao padrão tradicional. Os resultados sugerem que, entre os adolescentes avaliados, ser do sexo masculino foi associado ao maior consumo de alimentos tradicionalmente brasileiros como o arroz e feijão, já o maior nível socioeconômico esteve associado ao consumo de alimentos não saudáveis como bebidas açucaradas e lanches.

Development and Validation of a Tool to Measure Dietitians' Self-Efficacy with Using Mobile Health Apps in Dietetic Practice

OBJECTIVE

To develop and validate a tool for assessing dietitians' self-efficacy with using mobile health (mHealth) apps in dietetic practice.

DESIGN AND PARTICIPANTS

A tool for measuring mHealth app self-efficacy among dietitians was constructed based on a literature review, consultation with experts, and Bandura's self-efficacy scales development guide. Senior dietetic students and new graduate dietitians in Australia (n = 100) tested the tool.

OUTCOME MEASURES AND ANALYSIS

Validation of the tool was conducted using factor analysis. Reliability testing was undertaken to examine internal consistency and repeatability.

RESULTS

Construct validity was demonstrated through extraction of 4 factors with significant loadings accounting for 68% of variance: efficiency and effectiveness of nutrition care, training and support, integration into dietetic work systems, and familiarity with apps. Internal consistency reliability overall was 0.90; 3 of 4 constructs had Cronbach α > .70. Weighted kappas for test-retest reliability indicated moderate to substantial agreement (0.43-0.76).

CONCLUSIONS AND IMPLICATIONS

This tool will be useful to researchers and dietetic associations interested in measuring dietitians' levels of mHealth app self-efficacy, developing interventions to enhance self-efficacy, and/or evaluating changes in self-efficacy after professional training. Testing of the tool in a more diverse sample of dietitians and among other health professional groups could enhance the applicability of the tool.

Consumption of processed food dietary patterns in four African populations

OBJECTIVE

To identify predominant dietary patterns in four African populations and examine their association with obesity.

DESIGN

Cross-sectional study.Setting/SubjectsWe used data from the Africa/Harvard School of Public Health Partnership for Cohort Research and Training (PaCT) pilot study established to investigate the feasibility of a multi-country longitudinal study of non-communicable chronic disease in sub-Saharan Africa. We applied principal component analysis to dietary intake data collected from an FFQ developed for PaCT to ascertain dietary patterns in Tanzania, South Africa, and peri-urban and rural Uganda. The sample consisted of 444 women and 294 men.

RESULTS

We identified two dietary patterns: the Mixed Diet pattern characterized by high intakes of unprocessed foods such as vegetables and fresh fish, but also cold cuts and refined grains; and the Processed Diet pattern characterized by high intakes of salad dressing, cold cuts and sweets. Women in the highest tertile of the Processed Diet pattern score were 3·00 times more likely to be overweight (95 % CI 1·66, 5·45; prevalence=74 %) and 4·24 times more likely to be obese (95 % CI 2·23, 8·05; prevalence=44 %) than women in this pattern's lowest tertile (both P<0·0001; prevalence=47 and 14 %, respectively). We found similarly strong associations in men. There was no association between the Mixed Diet pattern and overweight or obesity.

CONCLUSIONS

We identified two major dietary patterns in several African populations, a Mixed Diet pattern and a Processed Diet pattern. The Processed Diet pattern was associated with obesity.

The traditional lunch pattern is inversely correlated with body mass index in a population-based study in Brazil

Background

The association of obesity and dietary patterns has been well documented in scientific literature; however, information on the impact of meal patterns on obesity is scarce. The objective of this study was to investigate the association of adherence to lunch patterns and body mass index (BMI) in a representative sample of individuals aged 20 years or older in Sao Paulo.

Methods

Data for 933 participants were retrieved from the Health Survey of São Paulo (ISA-Capital 2008), a cross-sectional population-based survey. The usual dietary intake of individuals with at least one 24-h recall was estimated by the Multiple Source Method. The definition of lunch was self-reported by the participant. Five lunch patterns were derived from twenty-two food groups by exploratory factor analysis: Traditional, Western, Sweetened juice, Salad, and Meats. To estimate the effect of lunch patterns on BMI, we used a generalized linear model with link identity and inverse Gaussian distribution. Analyses were adjusted by age, gender, household income per capita, physical activity levels, smoking status, alcohol consumption, total energy intake, and misreporting status.

Results

The greater adherence to the traditional pattern at the lunch meal was associated with lower BMI, only in insufficiently active individuals (ß = −0.78; 95% CI -1.57; −0.02).

Conclusions

The traditional Brazilian lunch pattern might protect the insufficiently active individuals against obesity.

Using reduced rank regression methods to identify dietary patterns associated with obesity: a cross-country study among European and Australian adolescents

This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12-17 years) and Australia (2007 National Children's Nutrition and Physical Activity Survey, including 1498 adolescents, 12-16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled 'energy dense, high fat, low fibre') explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet-obesity associations, to prevent reverse causality.

Maternal iron status during pregnancy compared with neonatal iron status better predicts placental iron transporter expression in humans

The placenta richly expresses nonheme and heme Fe transport proteins. To address the impact of maternal and neonatal Fe status and hepcidin on the regulation of these proteins, mRNA expression and protein abundance of nonheme and heme Fe transport proteins were evaluated in placental tissue from 154 adolescents. Regression analyses found maternal Fe status was significantly associated with multiple placental nonheme and heme transporters, whereas neonatal Fe status was related to only 3 heme transporters. Across statistical analyses, maternal Fe status was consistently associated with the placental nonheme Fe importer transferrin receptor 1 (TfR1). Protein abundance of TfR1 was related to midgestation maternal serum ferritin (SF) (β = -0.32; P = 0.005) and serum TfR (β = 0.25; P = 0.024). Protein abundance of the heme importer, proton-coupled folate transporter, was related to neonatal SF (β = 0.30; P = 0.016) and serum TfR (β = -0.46; P < 0.0001). Neonatal SF was also related to mRNA expression of the heme exporter feline leukemia virus subgroup C receptor 1 (β = -0.30; P = 0.004). In summary, maternal Fe insufficiency during pregnancy predicts increased expression of the placental nonheme Fe transporter TfR1. Associations between placental heme Fe transporters and neonatal Fe status require further study.-Best, C. M., Pressman, E. K., Cao, C., Cooper, E., Guillet, R., Yost, O. L., Galati, J., Kent, T. R., O'Brien, K. O. Maternal iron status during pregnancy compared with neonatal iron status better predicts placental iron transporter expression in humans.