Principal Component Analysis and Factor Analysis: differences and similarities in Nutritional Epidemiology application

Dietary patterns and biochemical markers related to diabetes mellitus: an association analysis based on data from the Study of Cardiovascular Risk in Adolescents (ERICA)

OBJECTIVE

The aim of this study was to investigate the association between dietary patterns and biochemical markers related to diabetes mellitus (DM): glucose, insulin, glycated hemoglobin (HbA1c), and homeostasis model assessment of insulin resistance index from 35 454 Brazilian adolescents 12 to 17 y of age.

METHODS

Dietary patterns were derived using factor analysis by the principal components method. The data originated from the school-based study ERICA (Study of Cardiovascular Risk in Adolescents) carried out between 2013 and 2014. Linear regression models analyzed the associations.

RESULTS

Three dietary patterns were found: traditional Brazilian, bread and coffee, and Western. An inverse association was found in young girls between the traditional Brazilian pattern and fasting glucose (β = -0.76; P = 0.005) and HbA1c in the second and third tertiles (β = -0.04; P = 0.002; β = -0 .06; P < 0.001), and the Western pattern with HbA1c (β = -0.02; P = 0.035). In boys, a positive association was found between the second tertile of the dietary pattern and insulin (β = 0.48; P = 0.009) and homeostasis model assessment of insulin resistance index (β = 0.11; P = 0.012).

CONCLUSIONS

This study showed that the traditional Brazilian pattern was inversely associated with blood glucose and HbA1c values in girls. Furthermore, the data suggest that there is an important difference between boys and girls in the association of dietary patterns and the markers used.

The Validity and Feasibility of Utilizing the Photo-Assisted Dietary Intake Assessment among College Students and Elderly Individuals in China

Dietary assessments hold significant importance within the field of public health. However, the current methods employed for dietary assessments face certain limitations and challenges that necessitate improvement. The aim of our study was to develop a reliable and practical dietary assessment tool known as photo-assisted dietary intake assessment (PAD). In order to evaluate its validity, we conducted an analysis on a sample of 71 college students' dinners at a buffet in a canteen. We compared estimates of food weights obtained through the 24-h recall (24 HR) or PAD method with those obtained through the weighing method; we also evaluated the feasibility of PAD for recording dinner intakes among a sample of college students (n = 76) and elderly individuals (n = 121). In addition, we successfully identified the dietary factors that have a significant impact on the bias observed in weight estimation. The findings of the study indicated that the PAD method exhibited a higher level of consistency with the weighing method compared to the 24 HR method. The discrepancy in D% values between cereals (14.28% vs. 40.59%, P < 0.05), vegetables (17.67% vs. 44.44%, P < 0.05), and meats (14.29% vs. 33.33%, P < 0.05) was clearly apparent. Moreover, a significant proportion of the food mass value acquired through the PAD method fell within the limits of agreement (LOAs), in closer proximity to the central horizontal line. Furthermore, vegetables, cereals, eggs, and meats, for which the primary importance lies in accuracy, exhibited a considerably higher bias with the 24 HR method compared to the PAD method (P < 0.05), implying that the PAD method has the potential to mitigate the quality bias associated with these food items in the 24 HR method. Additionally, the PAD method was well received and easily implemented by the college students and elderly individuals. In conclusion, the PAD method demonstrates a considerable level of accuracy and feasibility as a dietary assessment method that can be effectively employed across diverse populations.

Social Network, Food Patterns, Physical Activity and Associations with Overweight and Obesity in Adolescents from a School in Rural Brazil

The objective of this study was to evaluate the social network, food patterns, physical activity, and their associations with overweight/obesity in adolescents from a school in rural Brazil. Students from a rural school in Northeast Brazil (n = 90) completed questionnaires on sociodemographic characteristics, food consumption, physical activity, and a name generator. Social networks were constructed using students' social proximity ties. Principal component analysis was performed to determine food patterns, and logistic models were used to investigate variables associated with overweight/obesity. Most participants were girls (62.9%), and the proportion of overweight/obesity was 30% among adolescents. Students cited 2070 people from their networks (family, friends at school, friends outside of school, and others). Among them, the family had the highest degree of influence (61%) in the network and had the most shared meals with adolescents (47%). Adolescents' perception of their family members' body size as obese, compared to normal or underweight, was prevalent (51%). Adolescents with unhealthy food patterns were 72% more likely to be categorized as overweight/obese, and eigenvector centrality was also associated with overweight/obesity (OR = 5.88, 95% CI = 1.08-32.03). Adolescents presented a social network with strong family influence, in which a high percentage of overweight/obesity was observed. Adolescents with high eigenvector centrality were more likely to be in the overweight/obesity category. Additionally, overweight/obesity was associated with unhealthy food patterns in the family network.

Body Composition, Physical Function, and Dietary Patterns in People from 20 to Over 80 Years Old

OBJECTIVES

Diet may influence biochemical pathways involved in age-related changes in body composition and physical function. This study aimed to describe dietary patterns and their relationships with body composition, physical performance, and grip strength according to age and sex.

DESIGN

Cross-sectional study.

SETTING

Data were collected in the Clinical Research Center (CRC) of the Gérontopôle of the Centre Hospitalier Universitaire (CHU) of Toulouse or at participants' homes when unable to attend the research facilities.

PARTICIPANTS

470 (63% female) people with a median age of 56 (38 - 70) years.

MEASUREMENTS

The "Mediterranean-like" (i.e., plant-based foods, dairy), "Animal products" (i.e., meat, processed meat, butter, refined starch), and "Sugar and fast food" (i.e., ultra-processed and sugary foods) dietary patterns were extracted by principal component analysis. Total and trunk fat mass indexes (kg/m²), and total and appendicular lean mass indexes (kg/m²) were assessed by DXA. The physical tests comprised gait speed (m/sec), chair rise (sec), the Short Physical Performance Battery test (/12 points), and handgrip strength (kg). The associations were explored through multivariate linear regressions by sex and age groups: ≥20 to <50, ≥50 to <65, and ≥65 years.

RESULTS

Men and women had higher adherence to the "Sugar and fast food" diet in the youngest group. Middle-aged and older women adhered more to a "Mediterranean-like" diet. Men kept a "Sugar and fast food" diet when middle-aged and changed to the "Animal products" diet when ≥65 years. Higher adherence to the "Mediterranean-like" diet was associated with lower BMI, body fat, and lean mass in middle-aged men. Higher adherence to the "Animal products" diet was associated with higher lean mass in middle-aged women, more trunk fat in young men, lower strength in middle-aged men, and higher strength in older men. Higher adherence to the "Sugar and fast food" diet was associated with higher body fat in middle-aged men but lower body fat in older men.

CONCLUSION

Diets composed of sugary foods, fast foods, and processed meat were associated with higher fat mass and lower strength. Men were more prone to have less healthy food intake in all age groups.

Regional well-being inequalities arising from healthcare expenditure public policies in Spain

Well-being inequalities arising from different healthcare expenditure public policies is currently a hot topic at a national scale, but especially so at a sub-national level because the inequalities in question are among citizens of the same country. Spain is an optimal study area to carry out research on this topic because it is considered to have one of the best health systems in the world, it is one of the top-ranking countries in terms of life expectancy rates (the indicators we use for well-being), and it has a decentralized public health system with significantly different regional healthcare expenditure public policies. Given that the factors involved in the complex direct, indirect, and second-order relationships between well-being and health spending are latent in nature, and that there are more hypotheses than certainties regarding these relationships, we propose a partial least squares structural equation modeling specification to test the research hypotheses and to estimate the corresponding impacts. These constructs are proxied by a set of 26 indicators, for which annual values at a regional scale were used for the period 2005-2018. From the estimation of this model, it can be concluded that mortality, expenditure and resources are the factors that have the greatest impact on well-being. In addition, a cluster analysis of the indicators for the constructs included in this research reveals the existence of three clearly differentiated groups of autonomous communities: the northern part of the country plus Extremadura (characterized by the lowest well-being and the highest mortality rates), Madrid (with the best results in well-being and mortality, the lowest public health expenditure per inhabitant and percentage of pharmaceutical spending, and the highest percentage in specialty care services and medical staff spending), and the rest of the country (south-eastern regions, with similar well-being values to those of the first group but with less health expenditure). Finally, a principal component analysis reveals that "healthiness" and "basic spending" are the optimal factors for mapping well-being and health spending in Spain.

A Data Science Approach for the Identification of Molecular Signatures of Aggressive Cancers

The main hallmarks of cancer include sustaining proliferative signaling and resisting cell death. We analyzed the genes of the WNT pathway and seven cross-linked pathways that may explain the differences in aggressiveness among cancer types. We divided six cancer types (liver, lung, stomach, kidney, prostate, and thyroid) into classes of high (H) and low (L) aggressiveness considering the TCGA data, and their correlations between Shannon entropy and 5-year overall survival (OS). Then, we used principal component analysis (PCA), a random forest classifier (RFC), and protein-protein interactions (PPI) to find the genes that correlated with aggressiveness. Using PCA, we found GRB2, CTNNB1, SKP1, CSNK2A1, PRKDC, HDAC1, YWHAZ, YWHAB, and PSMD2. Except for PSMD2, the RFC analysis showed a different list, which was CAD, PSMD14, APH1A, PSMD2, SHC1, TMEFF2, PSMD11, H2AFZ, PSMB5, and NOTCH1. Both methods use different algorithmic approaches and have different purposes, which explains the discrepancy between the two gene lists. The key genes of aggressiveness found by PCA were those that maximized the separation of H and L classes according to its third component, which represented 19% of the total variance. By contrast, RFC classified whether the RNA-seq of a tumor sample was of the H or L type. Interestingly, PPIs showed that the genes of PCA and RFC lists were connected neighbors in the PPI signaling network of WNT and cross-linked pathways.

Prospects and Pitfalls of Machine Learning in Nutritional Epidemiology

Nutritional epidemiology employs observational data to discover associations between diet and disease risk. However, existing analytic methods of dietary data are often sub-optimal, with limited incorporation and analysis of the correlations between the studied variables and nonlinear behaviours in the data. Machine learning (ML) is an area of artificial intelligence that has the potential to improve modelling of nonlinear associations and confounding which are found in nutritional data. These opportunities notwithstanding, the applications of ML in nutritional epidemiology must be approached cautiously to safeguard the scientific quality of the results and provide accurate interpretations. Given the complex scenario around ML, judicious application of such tools is necessary to offer nutritional epidemiology a novel analytical resource for dietary measurement and assessment and a tool to model the complexity of dietary intake and its relation to health. This work describes the applications of ML in nutritional epidemiology and provides guidelines to avoid common pitfalls encountered in applying predictive statistical models to nutritional data. Furthermore, it helps unfamiliar readers better assess the significance of their results and provides new possible future directions in the field of ML in nutritional epidemiology.

Longitudinal association between the timing of adiposity peak and rebound and overweight at seven years of age

Background

The timing of adiposity peak (AP) or adiposity rebound (AR) is a determinant of overweight or obesity in adolescence and adulthood. However, limited studies have reported the association in young school-age children. We aimed to evaluate this association and explore the role of health behaviours in it.

Methods

Routinely collected, sequential, anthropometric data from the 1st to 80th months of age were used to estimate AP and AR timings in 2330 children born in Shanghai between 2010 and 2013. Multivariate regression analyses were applied to identify the associations between the AP or AR timings and the risk of developing overweight or obesity in first-grade school children. The roles of health behaviours, including dietary patterns, physical activity level, sleep and snacking habits, and screen time, were also evaluated.

Results

Children with a late AP or an early AR were at higher risk of overweight but not obesity or central obesity in their first grade. A high physical activity level was associated with a lower risk of having overweight in children with a late AP, and limited screen time was associated with a decreased risk of having overweight or obesity in children with an early AR. The absence of a late-night snacking habit in children with a non-early AR indicated a decreased risk of having overweight. However, this association was not observed among children with an early AR.

Conclusion

The timings of AP and AR are tied to overweight in middle childhood. Prevention strategies are suggested to move forward to control late AP and early AR.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03190-9.

Dietary Patterns in the Argentinian Population and Their Association With Sociodemographic Characteristics: Results From the ELANS Study (2014–2015)

Aim

To describe dietary patterns in the Argentinian population and their association with sociodemographic characteristics.

Methods

Cross-sectional analysis of Argentina's food consumption and sociodemographic data of 1,266 men and women between 15 and 65 years from the Latin American Study of Nutrition and Health carried out between March 2014 and December 2015. Dietary patterns were identified by using factor analysis and median factor scores were calculated for gender, age, region, body mass index (BMI), socioeconomic, education, and physical activity categories.

Results

Five dietary patterns were identified. Western, Local Western, and Rural were generally characterized by high consumptions of animal fats, sugar-sweetened beverages, meats or processed meats, pizza and empanadas, sweets, pastries, and low consumption of fruits and vegetables. Traditional pattern was mainly characterized by consumption of oils, starchy vegetables, and red meat and Sweet Prudent by milk and yogurt, vegetables, fruit, artificially sweetened beverages, sweets, and cookies. Higher adherence to the Sweet Prudent pattern was observed in women, in people who meet physical activity guidelines and higher socioeconomic and educational levels. Higher adherence to traditional pattern was only observed for men. Higher adherence to the rest of the patterns was observed mostly by men, young, leaner, lower socioeconomic, and educational levels, not meeting physical activity guidelines, from the metropolitan area of Buenos Aires or northern regions.

Conclusion

Food consumption in Argentina is expressed in a diversity of dietary patterns. Men, younger, and sedentary individuals, with lower socioeconomic and educational level, from the metropolitan area of Buenos Aires and northern regions, seem to have higher adherence to least healthy dietary patterns.

Manipulating the Self-Assembly of Multicomponent Low Molecular Weight Gelators (LMWGs) through Molecular Design

Multicomponent low molecular weight gelators (LMWGs) may self-assemble by co-assembly (CA), social self-sorting (SSS), or narcissistic self-sorting (NSS). Understanding the nuances of the self-assembly processes is important to predict the behavior of multicomponent organogels. Here, we investigate the effect of molecular structure on self-assembly in a series of amino-acid based bicomponent LMWGs that differ in headgroup and alkyl chain length. Packing preference of the organogels was determined using differential scanning calorimetry, nuclear magnetic resonance spectroscopy and small angle X-ray scattering. From 66 bicomponent samples we found 50 CA, 14 SSS and 2 NSS. Furthermore, we performed statistical analysis to investigate the role of hydrophobicity and chain length on the overall pathway of self-assembly for these systems. We found the hydrophobicity of the headgroup strongly affected the assembly preference of the organogel, but alkyl chain length only played a small role.

Bioaccumulation and human health risks of potentially toxic elements in fish species from the southeastern Carajás Mineral Province, Brazil

Anthropogenic activities may have increased the concentrations of potentially toxic elements (PTEs) in fish from the southeastern Carajás Mineral Province in Brazil, which has not yet been studied. The objectives were to determine the quality parameters of surface water and bottom sediments, and to assess the bioaccumulation and risks of Al, Fe, Ba, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, Ti, V and Zn in fish species from the southeastern Carajás Mineral Province. Water, sediments and fish species (Colossoma macropomum, Curimata cyprinoides, Geophagus sp., Leporinus trifasciatus, and Serrasalmus eigenmanni) were collected in 14 areas in the municipalities of Parauapebas, Marabá and Canaã dos Carajás, contemplating the Gelado Stream and the Parauapebas, Tapirapé and Itacaiúnas Rivers. Water samples were subjected to physicochemical analysis using a multiparameter meter. Concentrations of PTEs in all samples were quantified by inductively coupled plasma-optical emission spectrometry. Enrichment factor (EF) and geoaccumulation index (Igeo) were calculated to study the sediment enrichment and contamination. Ecological and human health risk assessments were performed to determine the risks to the environment and population's health. EF and Igeo revealed that the sediments from the Parauapebas River and Gelado Stream are respectively enriched by Ba, Co, Cu, Cr, Mn, Pb, and Ba, Co, Cr, Ni, Pb and V. The concentrations of Fe (1.67 mg L^-1) and Mn (0.11 mg L^-1) in water and the concentrations of Cr (>0.1 mg kg^-1) and Pb (>2 mg kg^-1) in fish were above the Brazilian legislation thresholds. The ecological risk assessment revealed considerable risk from Ni and moderate risk from multiple PTEs in sediments from the Gelado Stream. Human health risks were detected for Pb in all fish species and for Mo in L.trifasciatus. These results indicate that techniques for monitoring and controlling contamination must be implemented by the environmental agencies.

An Exploratory Analysis of the Internal Structure of Test Through a Multimethods Exploratory Approach of the ASQ:SE in Brazil

Background  A wide range of exploratory methods is available in psychometrics as means of gathering insight on existing data and on the process of establishing the number and nature of an internal structure factor of a test. Exploratory factor analysis (EFA) and principal component analysis (PCA) remain well-established techniques despite their different theoretical perspectives. Network analysis (NA) has recently gained popularity together with such algorithms as the Next Eigenvalue Sufficiency Test. These analyses link statistics and psychology, but their results tend to vary, leading to an open methodological debate on statistical assumptions of psychometric analyses and the extent to which results that are generated with these analyses align with the theoretical basis that underlies an instrument. The current study uses a previously published data set from the Ages & Stages Questionnaires: Social-Emotional to explore, show, and discuss several exploratory analyses of its internal structure. To a lesser degree, this study furthers the ongoing debate on the interface between theoretical and methodological perspectives in psychometrics.

Methods  From a sample of 22,331 sixty-month-old children, 500 participants were randomly selected. Pearson and polychoric correlation matrices were compared and used as inputs in the psychometric analyses. The number of factors was determined via well-known rules of thumb, including the parallel analysis and the Hull method. Multidimensional solutions were rotated via oblique methods. R and Factor software were used, the codes for which are publicly available at https://luisfca.shinyapps.io/psychometrics_asq_se/ .

Results  Solutions from one to eight dimensions were suggested. Polychoric correlation overcame Pearson correlation, but nonconvergence issues were detected. The Hull method achieved a unidimensional structure. PCA and EFA achieved similar results. Conversely, six clusters were suggested via NA.

Conclusion  The statistical outcomes for determining the factor structure of an assessment diverged, varying from one to eight domains, which allowed for different interpretations of the results. Methodological implications are further discussed.

Sweet Taste Preference: Relationships with Other Tastes, Liking for Sugary Foods and Exploratory Genome-Wide Association Analysis in Subjects with Metabolic Syndrome

Taste perception and its association with nutrition and related diseases (type 2 diabetes, obesity, metabolic syndrome, cardiovascular, etc.) are emerging fields of biomedicine. There is currently great interest in investigating the environmental and genetic factors that influence sweet taste and sugary food preferences for personalized nutrition. Our aims were: (1) to carry out an integrated analysis of the influence of sweet taste preference (both in isolation and in the context of other tastes) on the preference for sugary foods and its modulation by type 2 diabetes status; (2) as well as to explore new genetic factors associated with sweet taste preference. We studied 425 elderly white European subjects with metabolic syndrome and analyzed taste preference, taste perception, sugary-foods liking, biochemical and genetic markers. We found that type 2 diabetic subjects (38%) have a small, but statistically higher preference for sweet taste (p = 0.021) than non-diabetic subjects. No statistically significant differences (p > 0.05) in preferences for the other tastes (bitter, salty, sour or umami) were detected. For taste perception, type 2 diabetic subjects have a slightly lower perception of all tastes (p = 0.026 for the combined “total taste score”), bitter taste being statistically lower (p = 0.023). We also carried out a principal component analysis (PCA), to identify latent variables related to preferences for the five tastes. We identified two factors with eigenvalues >1. Factor 2 was the one with the highest correlation with sweet taste preference. Sweet taste preference was strongly associated with a liking for sugary foods. In the exploratory SNP-based genome-wide association study (GWAS), we identified some SNPs associated with sweet taste preference, both at the suggestive and at the genome-wide level, especially a lead SNP in the PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2) gene, whose minor allele was associated with a lower sweet taste preference. The PTPRN2 gene was also a top-ranked gene obtained in the gene-based exploratory GWAS analysis. In conclusion, sweet taste preference was strongly associated with sugary food liking in this population. Our exploratory GWAS identified an interesting candidate gene related with sweet taste preference, but more studies in other populations are required for personalized nutrition.

Association between Dietary Patterns and Chronic Obstructive Pulmonary Disease in Korean Adults: The Korean Genome and Epidemiology Study

In addition to smoking, dietary habits may contribute to the development of chronic obstructive pulmonary disease (COPD). This study aimed to examine the association between dietary patterns and lung function in a Korean community cohort. A total of 5436 participants were included from the Ansan–Ansung cohort study. To identify the dietary patterns, we performed principal component factor analysis using the results of a semi-quantitative food frequency questionnaire. The forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio were measured by spirometry. Multiple logistic regression models were used to evaluate the association between dietary patterns and lung function after adjusting for confounders. We identified four major dietary patterns; ‘prudent’, ‘coffee, fat, and sweet’, ‘westernized’, and ‘white rice’. After adjusting for potential confounders, the ‘coffee, fat, and sweet’ dietary pattern was negatively associated with lung function, particularly the FEV1/FVC ratio. Participants with high scores for the ‘coffee, fat and sweet’ pattern had a higher risk of COPD among men but not women. Therefore, these results indicate that the ‘coffee, fat and sweet’ dietary pattern is inversely related to lung function in Korean adults. Our results indicate that dietary habits may be modifiable risk factors for COPD.

Breakfast Dietary Pattern Is Inversely Associated with Overweight/Obesity in European Adolescents: The HELENA Study

Obesity in children and adolescents is a public health problem and diet can play a major role in this condition. We aimed to identify sex-specific dietary patterns (DP) and to evaluate the association with overweight/obesity in European adolescents. We conducted a cross-sectional analysis with 2327 adolescents aged between 12.5 to 17.5 years from a multicenter study across Europe. The body mass index was categorized in “normal weight” and “overweight/obesity”. Two non-consecutive 24-h dietary recalls were collected with a computerized self-reported software. Principal component factor analysis was used to identify DP. Mixed-effect logistic regression models were used to evaluate the association between the sex-specific DP and overweight/obesity outcome. As a result, we found three DP in boys (snacking and bread, Mediterranean diet, and breakfast) and four DP in girls (convenience, plant-based and eggs, Western, and breakfast). The association between DP and overweight/obesity highlights that those adolescents with higher adherence to the breakfast DP had lower odds for overweight/obesity, even after the inclusion of covariables in the adjustments. In European adolescents, the breakfast DP positively characterized by breakfast cereals, fruit, milk, and dairy and negatively characterized by sugar-sweetened beverages in boys and negatively characterized by cereals (pasta, rice, and others) in girls, was inversely associated with overweight/obesity.

Ethnic Differences Between Hispanics and Non-Hispanic Whites in Neuropsychiatric Symptoms Predict Conversion to Mild Cognitive Impairment

The aim of the study is to ascertain the neuropsychiatric symptoms (NPS) subtypes significantly influencing progression to mild cognitive impairment (MCI) by ethnicity. In this retrospective cohort study, we included 386 cognitively normal individuals participating in the longitudinal Texas Alzheimer's Research and Care Consortium between February 2007 and August 2014. The primary outcome was time to incident MCI. Data driven NPS subtypes at baseline were identified and the effects of these subtypes on the outcome were obtained for Hispanic and non-Hispanic ethnic cohorts and summarized with a hazard ratio (HR). Three NPS subtypes were identified and internally validated: psychomotor apathy factor (including agitation, irritability, apathy), affective mood factor (including depression, anxiety), and physical behavior factor (including nighttime behavior, eating/appetite disturbances). In adjusted analysis, a psychomotor apathy score of NPS was the best predictor for MCI (HR = 2.19, p = 0.037) among non-Hispanics whereas physical behavior score was the most predictive of MCI (HR = 2.55, p = 0.029) among Hispanics. A high score of affective mood factor also tended to increase the risk of MCI (HR = 2.09, p = 0.06) in Hispanics. Progression from normal cognition to MCI was differentially predicted by NPS subtypes in Hispanics and non-Hispanic whites. These data may inform the allocation of efforts for monitoring individuals at-risk of MCI.

The impacts of the built environment on the incidence rate of COVID-19: A case study of King County, Washington

With COVID-19 prevalent worldwide, current studies have focused on the factors influencing the epidemic. In particular, the built environment deserves immediate attention to produce place-specific strategies to prevent the further spread of coronavirus. This research assessed the impact of the built environment on the incidence rate in King County, US and explored methods of researching infectious diseases in urban areas. Using principal component analysis and the Pearson correlation coefficient to process the data, we built multiple linear regression and geographically weighted regression models at the ZIP code scale. Results indicated that although socioeconomic indicators were the primary factors influencing COVID-19, the built environment affected COVID-19 cases from different aspects. Built environment density was positively associated with incidence rates. Specifically, increased open space was conducive to reducing incidence rates. Within each community, overcrowded households led to an increase in incidence rates. This study confirmed previous research into the importance of socioeconomic variables and extended the discussion on spatial and temporal variation in the impacts of urban density on the spread of COVID, effectively guiding sustainable urban development.

Green Growth in the OECD Countries: A Multivariate Analytical Approach

Green growth is about merging environmental and social protection with economic growth. The OECD countries follow the progress toward greening though a set of indicators. The aim of the study is to analyze the condition and development of the OECD countries using a set of green growth indicators. The univariate and multivariate statistical approach was used to identify the main features of green growth development in two time spans. The achieved success of the OECD countries toward the green growth was measured from period 1 (years 2000–2009) to period 2 (years 2010–2019). For stimulant indicators, an increase was achieved, while for the destimulant variables, a decrease was reached between the analyzed periods. CO2 productivity increased by more than 31%, material productivity by 25%, and the energy productivity by nearly 21%. From the ecological point of view, a positive sign was achieved by an intensive increase of the percentage of municipal waste treatment by recycling or composting. The real GDP increased between periods in each of the OECD countries, except in Greece. The destimulant indicators decreased over time. The mortality declined by about 20% from exposure to ambient PM2.5 and thus the welfare costs of premature death from exposure to PM2.5 also declined. The decline of the mean population exposure to PM2.5 by 12.5% on average for the OECD countries is a positive signal for environmental protection and public health of the OECD population. Some uncertainty exists as the municipal waste generated per capita decreased only slightly by 2%.

Data-Driven Prediction of Fatigue in Parkinson's Disease Patients

Introduction: Numerous non-motor symptoms are associated with Parkinson's disease (PD) including fatigue. The challenge in the clinic is to detect relevant non-motor symptoms while keeping patient-burden of questionnaires low and to take potential subgroups such as sex differences into account. The Fatigue Severity Scale (FSS) effectively detects clinically significant fatigue in PD patients. Machine learning techniques can determine which FSS items best predict clinically significant fatigue yet the choice of technique is crucial as it determines the stability of results. Methods: 182 records of PD patients were analyzed with two machine learning algorithms: random forest (RF) and Boruta. RF and Boruta calculated feature importance scores, which measured how much impact an FSS item had in predicting clinically significant fatigue. Items with the highest feature importance scores were the best predictors. Principal components analysis (PCA) grouped highly related FSS items together. Results: RF, Boruta and PCA demonstrated that items 8 ("Fatigue is among my three most disabling symptoms") and 9 ("Fatigue interferes with my work, family or social life") were the most important predictors. Item 5 ("Fatigue causes frequent problems for me") was an important predictor for females, and item 6 ("My fatigue prevents sustained physical functioning") was important for males. Feature importance scores' standard deviations were large for RF (14-66%) but small for Boruta (0-5%). Conclusion: The clinically most informative questions may be how disabling fatigue is compared to other symptoms and interference with work, family and friends. There may be some sex-related differences with frequency of fatigue-related complaints in females and endurance-related complaints in males yielding significant information. Boruta but not RF yielded stable results and might be a better tool to determine the most relevant components of abbreviated questionnaires. Further research in this area would be beneficial in order to replicate these findings with other machine learning algorithms, and using a more representative sample of PD patients.

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.

Identifying Nutrient Patterns in South African Foods to Support National Nutrition Guidelines and Policies

Food composition databases (FCDBs) provide the nutritional content of foods and are essential for developing nutrition guidance and effective intervention programs to improve nutrition of a population. In public and nutritional health research studies, FCDBs are used in the estimation of nutrient intake profiles at the population levels. However, such studies investigating nutrient co-occurrence and profile patterns within the African context are very rare. This study aimed to identify nutrient co-occurrence patterns within the South African FCDB (SAFCDB). A principal component analysis (PCA) was applied to 28 nutrients and 971 foods in the South African FCDB to determine compositionally similar food items. A second principal component analysis was applied to the food items for validation. Eight nutrient patterns (NPs) explaining 73.4% of the nutrient variation among foods were identified: (1) high magnesium and manganese; (2) high copper and vitamin B₁₂; (3) high animal protein, niacin, and vitamin B₆; (4) high fatty acids and vitamin E; (5) high calcium, phosphorous and sodium; (6) low moisture and high available carbohydrate; (7) high cholesterol and vitamin D; and (8) low zinc and high vitamin C. Similar food patterns (FPs) were identified from a PCA on food items, yielding subgroups such as dark-green, leafy vegetables and, orange-coloured fruit and vegetables. One food pattern was associated with high sodium levels and contained bread, processed meat and seafood, canned vegetables, and sauces. The data-driven nutrient and food patterns found in this study were consistent with and support the South African food-based dietary guidelines and the national salt regulations.

Food intake patterns and high blood pressure levels among Brazilians: a cross-sectional study, 2013

OBJECTIVE

To analyze association between patterns of food intake markers and high blood pressure levels among Brazilians.

METHODS

This was a cross-sectional study using National Health Survey data. Its outcome was high blood pressure levels, measured during interviews between August and November 2013. Food intake marker patterns were identified. These were the exposure variables. Prevalence ratios (PR) and 95% confidence intervals (95%CI) were calculated using multivariate Poisson regression.

RESULTS

High blood pressure prevalence was 16.0% (95%CI - 15.3;16.7) in the sample of 37,216 participants. It was higher in those with a diet that included meat and alcoholic beverages (PR=1.21 - 95%CI 1.08;1.35). The pattern with greater presence of greens and vegetables did not show statistically significant association with high blood pressure levels (PR=0.94 - 95%CI 0.84;1.06).

CONCLUSION

The pattern marked by meat and alcoholic beverages was associated with high blood pressure levels.

Consumption of dairy products and CVD risk: results from the French prospective cohort NutriNet-Santé

In France, dairy products contribute to dietary saturated fat intake, of which reduced consumption is often recommended for CVD prevention. Epidemiological evidence on the association between dairy consumption and CVD risk remains unclear, suggesting either null or inverse associations. This study aimed to investigate the associations between dairy consumption (overall and specific foods) and CVD risk in a large cohort of French adults. This prospective analysis included participants aged ≥18 years from the NutriNet-Santé cohort (2009-2019). Daily dietary intakes were collected using 24-h dietary records. Total dairy, milk, cheese, yogurts, fermented and reduced-fat dairy intakes were investigated. CVD cases (n 1952) included cerebrovascular disease (n 878 cases) and CHD (n 1219 cases). Multivariable Cox models were performed to investigate associations. This analysis included 104 805 French adults (mean age at baseline 42·8 (sd 14·6) years, mean follow-up 5·5 (sd 3·0) years, i.e. 579 155 person-years). There were no significant associations between dairy intakes and total CVD or CHD risks. However, the consumption of at least 160 g/d of fermented dairy (e.g. cheese and yogurts) was associated with a reduced risk of cerebrovascular diseases compared with intakes below 57 g/d (hazard ratio = 0·81 (95 % CI 0·66, 0·98), Ptrend = 0·01). Despite being a major dietary source of saturated fats, dairy consumption was not associated with CVD or CHD risks in this study. However, fermented dairy was associated with a lower cerebrovascular disease risk. Robust randomised controlled trials are needed to further assess the impact of consuming different dairy foods on CVD risk and potential underlying mechanisms.

A Concrete Study on Social-Media Connection of Global Literacy Abilities in MOOCs under the Dual Impacts of Lower Birth-Rate and COVID-19

In order to break through the dual impacts of lower birth rates and COVID-19, a majority of higher education institutions have commenced in providing a series of diversified Massive Open Online Courses (MOOCs) to effectively reduce these huge dual impacts. This research employed the Social Learning Theory (SLT) of educational doctrine for theoretical uses and the Factor Analysis (FA) approach of quantitative analysis and Trigonometrical Entropy Method (TEM) method of qualitative analysis for statistically purposes. These concepts were employed to explore the most critical social-media connection of global literacy abilities in MOOC. After a succession of assessed measurements, there are two most valuable findings. First, higher education institutions have to simultaneously and efficiently institute the Course Complete Rate of Course Assessment (CCR-CA), User Completely Unrestricted Operation of Course Operation (UCUO-CO) and Course Professionalization Technology Function of Course Function (CPTF-CF) into the course’s design. Specifically, higher education institutions need to establish MOOCs features in Course Evaluation Technology Function (CETF), Course Professionalization Technology Function (CPTF) and Aggregation Technology Function (ATF) of MOOCs features into the current MOOCs. This is done in order to effectively promote the Individual Social Feature (ISF) of “social-media connection of global literacy abilities” for overcoming these serious dual impacts. In addition, higher education institutions have to also construct the social-media connection of global literacy abilities evaluation model for appraising Individual Social Feature (ISF) of each MOOCs participant. Second finding, higher education institutions should develop Convenience of Course Operation (C-CP), Feedback Technology Function of Basic Function (FTF-BF) and Connectionization of Course Operation (C-CO) of higher education strategies of developed sustainability into the course’s structure. Further, they should also build Connectionization (CZ) of MOOCs features into the current MOOCs in order to efficiently foster Application Programming Interface (API) of social-media connection of global literacy abilities for conquering these serious dual impacts as well.

The Evaluation and Use of a Food Frequency Questionnaire Among the Population in Trivandrum, South Kerala, India

Dietary record tools such as food frequency questionnaire (FFQ) and food diaries (FD) are the most commonly used choices for assessing dietary intakes in most large-scale epidemiological studies. The authors developed a self-administered 360-item food frequency questionnaire (FFQ) to assess dietary intakes amongst a population-based cohort in South Kerala. In the validation study (n = 460), the data were collected using FFQs that were administered on three different occasions which were then compared to 7-day food records. The intake of foods and nutrients was higher as determined by the FFQ than that assessed using food records. Spearman correlations for macro-nutrients ranged from 0.72 for protein to 0.61 for carbohydrates and for micronutrients, from 0.71 for vitamin B6 to 0.34 for magnesium. The correlation was improved with energy-adjusted nutrient intakes. On average, the exact agreement for the macronutrients ranged from 48.2% to 57.1%, and that for micronutrients ranged from 66.7% to 41.9%, with the median percentage of 49.58%. The authors conclude that the FFQ has an acceptable reproducibility, however, there was a systematic trend towards higher estimates with the FFQ for most nutrients compared to the FD records.

The association between dietary patterns before and in early pregnancy and the risk of gestational diabetes mellitus (GDM): Data from the Malaysian SECOST cohort

Generally, dietary patterns (DP)s have been linked to the risk of diabetes mellitus, however, only few studies examined the associations between DPs in early pregnancy and the risk of gestational diabetes mellitus (GDM). This study aims to determine the association between DPs before and during pregnancy and risk of GDM in Malaysian pregnant women. DPs were derived using principal component analysis of consumed 126 food and beverage items assessed using a validated semi-quantitative food frequency questionnaire collecting data retrospectively for pre-pregnancy, but prospectively for the first and second trimester. Three different DPs were identified at each time point and labelled as DP 1–3 (pre-pregnancy), DP 4–6 (first trimester), and DP 7–9 (second trimester). About 10.6% (n = 48) of pregnant women were diagnosed with GDM in our cohort. Women with high adherence (HA) to DP 2 (adjusted OR: 0.45, 95% CI: 0.20–0.91) and DP 5 (adjusted OR: 0.28, 95% CI: 0.11–0.68) showed a significantly reduced risk of GDM compared to women with low adherence (LA). Other DPs were not significantly associated with GDM risk. Compared to women with GDM, non-GDM women showed HA scores for all DPs throughout pregnancy. Overall, a relative low percentage of women with GDM was found in this cohort. The risk was lower in women with HA to a relatively unhealthy dietary pattern, i.e. DP 2 and DP 5. The lower body mass index (BMI) status and energy intake of women showing a HA to DP 2 in the first trimester may underlie the observed association with a lower GDM risk. Additionally, genetic variance might explain the less susceptibility to GDM despite HA to unhealthy DPs among non-GDM women.