Depression is highly prevalent in haemodialysis patients, and diet might play an important role. Therefore, we conducted this cross-sectional study to determine the association between dietary fatty acids (FA) consumption and the prevalence of depression in maintenance haemodialysis (MHD) patients. Dietary intake was assessed using a validated FFQ between December 2021 and January 2022. The daily intake of dietary FA was categorised into three groups, and the lowest tertile was used as the reference category. Depression was assessed using the Patient Health Questionnaire-9. Logistic regression and restricted cubic spline (RCS) models were applied to assess the relationship between dietary FA intake and the prevalence of depression. As a result, after adjustment for potential confounders, a higher intake of total FA [odds ratio (OR)T3 vs. T1 = 1·59, 95 % confidence interval (CI) = 1·04, 2·46] and saturated fatty acids (SFA) (ORT3 vs. T1 = 1·83, 95 % CI = 1·19, 2·84) was associated with a higher prevalence of depressive symptoms. Significant positive linear trends were also observed (P < 0·05) except for SFA intake. Similarly, the prevalence of depression in MHD patients increased by 20% (OR = 1.20, 95% CI = 1.01–1.43) for each standard deviation increment in SFA intake. RCS analysis indicated an inverse U-shaped correlation between SFA and depression (Pnonlinear > 0·05). Additionally, the sensitivity analysis produced similar results. Furthermore, no statistically significant association was observed in the subgroup analysis with significant interaction. In conclusion, higher total dietary FA and SFA were positively associated with depressive symptoms among MHD patients. These findings inform future research exploring potential mechanism underlying the association between dietary FA and depressive symptoms in MHD patients.

The Mediterranean Region registers an increasing prevalence of obesity. The region lacks a diet screener to assess obesogenic nutrients. This study aimed to evaluate the reproducibility and validity of the Modified Mediterranean Prime Screen (MMPS) in estimating obesogenic nutrients’ intake among women of reproductive age, as compared with a culturally validated Food Frequency Questionnaire (FFQ), in Lebanon. We developed the MMPS consisting of thirty-two food/beverage items specific to the Lebanese Mediterranean culture. The MMPS and FFQ were administered in two visits (2 weeks–6 months apart), face to face and via telephone during the coronavirus disease 2019 pandemic. The reproducibility and validity of the MMPS were assessed using intraclass correlation coefficients (ICC) and Pearson’s correlations, respectively. The study included 143 women, aged 31·5 (sd 4·6) years, BMI 24·2 (sd 4·0) kg/m2, 87 % with university education and 91 % food secure. The reproducibility of the MMPS was moderate for energy and all assessed nutrients except for SFA (ICC = 0·428). The agreement of the MMPS with the reference FFQ was adequate for energy and obesogenic nutrients. Yet, the Pearson correlations for energy-adjusted nutrient intake were low for trans-fatty acids (0·294) and PUFA (0·377). The MMPS can be a time-efficient tool for dietary assessment of energy and many obesogenic nutrients. Future studies should validate the MMPS across the lifespan and re-evaluate it after updating the fatty acid profiles in the culturally specific food composition tables.

Obesity and COVID-19 are global pandemics listed by World Health Organization, which need urgent attention. Obesity involves low grade chronic inflammation, which is characterised by sustained pro-inflammatory innate immune responses mediated through activation of the NLR family pyrin domain-containing 3 (NLRP3) inflammasome/IL-1 axis, and is a strong risk factor for Diabetes and Heart diseases(1). Dietary fats provide energy, satiety, source of fat-soluble vitamins and essential fatty acids – Omega 3 (n-3) and Omega 6 (n-6) fatty acids, but must be consumed in right amounts and ratios. Essential fatty acids (EFA) deficiency and n-6/n-3 imbalance is linked with chronic illnesses such as, heart attacks, cancer, insulin resistance, stroke, obesity, and diabetes(2). Excess dietary fat intake and imbalance of fatty acids, contribute to obesity, inflammation, comorbidities and faster disease progression. A cross-sectional survey aimed to understand the fatty food frequency of overweight and obese middle age adults from Mumbai, India during the COVID-19 outbreak. Using purposive sampling, 100 adults (30-60 years), a questionnaire (demographics, anthropometrics and fat food frequency questionnaire) was administered. Data was analysed using SPSS 26.0. As per BMI standards, 60.2% participants were overweight, 12.6% were obese and 27.1% had normal BMI. For visible fat consumption, sunflower oil (47.6%), ghee (38.8%), rice bran oil (34%) groundnut oil (11.7%) and invisible fats – milk (100%). Other dairy products, nuts and oilseeds were consumed weekly. twice a week, majority (92.3%) consumed packaged high fat foods as compared to eating deep-fried items (58.9%). We concluded that excess dietary fat intake is high risk factor for obesity and related comorbidities diabetes, and hypertension. High BMI increases the risk for non-communicable diseases (NCDs) such as obesity, cardiovascular disease (CVD), insulin resistance and type 2 diabetes. People with co-morbidities are high risk groups for COVID-19 infection susceptibility. Hence, managing weight could be a cost-effective preventive strategy to help in delaying the onset and progression of NCDs, thereby lowering the susceptibility to COVID-19. Our findings have important implications in working towards adopting healthy fats and reducing mortality and reducing the global burden of pandemic. High dietary fat intake is a modifiable risk factor for overweight and obesity. Comorbidities increased risk for COVID-19 infection, disease severity and mortality. Hence, there is a need to understand the dietary fat consumption patterns in obesity and COVID-19. Dietary carbohydrate, sugar and fat quality in relation to obesity and pandemic such as, COVID-19 could be explored in future studies.

Dietary carotenoids are associated with lower risk of CHD. Assessment of dietary carotenoid intake using questionnaires can be susceptible to measurement error. Consequently, there is a need to validate data collected from FFQs which measure carotenoid intake. This study aimed to assess the performance of the Cardio-Med Survey Tool (CMST)-FFQ-version 2 (v2) as a measure of dietary carotenoid intake over 12-months against plasma carotenoids biomarkers and 7-Day Food Records (7DFR) in an Australian cardiology cohort. Dietary carotenoid intakes (β- and α-carotene, lycopene, β-cryptoxanthin and lutein/zeaxanthin) were assessed using the 105-item CMST-FFQ-v2 and compared to intakes measured by 7DFR and plasma carotenoid concentrations. Correlation coefficients were calculated between each dietary method, and validity coefficients (VCs) were calculated between each dietary method and theoretical true intake using the ‘methods of triads’. Thirty-nine participants aged 37–77 years with CHD participated in the cross-sectional study. The correlation between FFQ and plasma carotenoids were largest and significant for β-carotene (0.39, p=0.01), total carotenoids (0.37, p=0.02) and β-cryptoxanthin (0.33, p=0.04), with weakest correlations observed for α-carotene (0.21, p=0.21) and lycopene (0.21, p=0.21). The FFQ VCs were moderate (0.3–0.6) or larger for all measured carotenoids. The strongest were observed for total carotenoids (0.61) and β-carotene (0.59), while the weakest were observed for α-carotene (0.33) and lycopene (0.37). In conclusion, the CMST-FFQ-v2 measured dietary carotenoids intakes with moderate confidence for most carotenoids, however, there was less confidence in ability to measure α-carotene and lycopene intake, thus further research is warranted using a larger sample.

In studies that contain repeated measures of variables, longitudinal analysis accounting for time-varying covariates is one of the options. We aimed to explore longitudinal association between diet quality (DQ) and non-communicable diseases (NCDs). Participants from the 1973–1978 cohort of the Australian Longitudinal Study on Women’s Health (ALSWH) were included, if they; responded to survey 3 (S3, 2003, aged 25–30 years) and at least one survey between survey 4 (S4, 2006) and survey 8 (S8, 2018), were free of NCDs at or before S3, and provided dietary data at S3 or S5. Outcomes were coronary heart disease (CHD), hypertension (HT), asthma, cancer (except skin cancer), diabetes mellitus (DM), depression and/or anxiety, and multimorbidity (MM). Longitudinal modelling using generalised estimation equation (GEE) approach with time-invariant (S4), time-varying (S4–S8) and lagged (S3–S7) covariates were performed. The mean (± standard deviation) of Alternative Healthy Eating Index-2010 (AHEI-2010) of participants (n = 8022) was 51·6 ± 11·0 (range: 19–91). Compared to women with the lowest DQ (AHEI-2010 quintile 1), those in quintile 5 had reduced odds of NCDs in time-invariant model (asthma: OR (95 % CI): 0·77 (0·62–0·96), time-varying model (HT: 0·71 (0·50–0·99); asthma: 0·62 (0·51–0·76); and MM: 0·75 (0·58–0·97) and lagged model (HT: 0·67 (0·49–0·91); and asthma: 0·70 (0·57–0·85). Temporal associations between diet and some NCDs were more prominent in lagged GEE analyses. Evidence of diet as NCD prevention in women aged 25–45 years is evolving, and more studies that consider different longitudinal analyses are needed.

Vitamin D deficiency is common in Irish adults, though there is limited research on its determinants, knowledge of vitamin D or indications for testing. We aimed to explore the determinants of vitamin D status in adults and examine knowledge and reasons for testing. The study population comprised adults who had serum 25-hydroxyvitamin D tested by general practitioners request at a Dublin Hospital in 2020. Questionnaires detailing dietary intake, sun exposure, ethnicity, biophysical factors and vitamin D knowledge were sent to a sample stratified by age, sex and vitamin D status. In total, there were 383 participants, mean age 56·0 (sd 16·6) years. Wintertime deficiency disproportionally affected non-white v. white (60 % v. 24 %, P < 0·001). The greatest predictors of deficiency were low vitamin D intake (< 10 μg/d) (P < 0·001) and non-white ethnicity (P = 0·006), followed by sun avoidance (P = 0·022). It was also more prevalent in those with lower body exposure when outdoors. The majority (86 %) identified vitamin D as important for bone health. However, 40 % were tested for non-clinical indications and half were not aware of the recommended daily allowance (RDA). Low vitamin D intake was the most important determinant of deficiency, but ethnicity and sun exposure habits were also significant predictors. The majority had no clear indication for testing and were not aware of the RDA. Public health policies to improve knowledge and vitamin D intake, especially for those of non-white ethnicity and with reduced sun exposure, should be considered.

All dietary assessment methods inevitably introduce measurement errors, which should ideally be considered during data analysis and interpretation. Methodological studies should be conducted to address how well a given assessment method captures dietary intake and to highlight the extent and direction of the measurement error. Within a subgroup of the Hordaland Health Study (HUSK3), we examined the relative validity of a web-based food frequency questionnaire (WebFFQ) by comparing its estimates of mean daily intake of nutrients and foods with estimated mean daily intakes from repeated administrations of 24-hour dietary recall interviews (24-HDRs). Men and women born between 1950 and 1951 were recruited from HUSK3. The participants (n = 67) completed a WebFFQ and three non-consecutive 24-HDRs over the course of a year. Relative validity was assessed using Spearman's rank correlation, crosstab analysis and Bland–Altman plots. Linear regression models were used to compute the calibration coefficients. The estimated correlation coefficients were acceptable or strong for all nutrients and foods except iodine (rs = 0⋅19). The highest correlation coefficient was found for juice (rs = 0⋅71), whereas the lowest correlation coefficient was found for iodine (rs = 0⋅19). Cross-classification by quartiles categorised more than 72 % of the participants into the same or adjacent quartiles using the two methods. Few data points fell outside the limits of agreement in the Bland–Altman plots. Calibration coefficients ranged from 0⋅10 (wholegrain) to 0⋅81 (alcohol). Our findings suggest that the WebFFQ has reasonable ranking abilities for all the included nutrients and foods, except for iodine.

The World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) published evidence-based recommendations for cancer prevention focusing on body weight, physical activity, and diet. Our aim is to evaluate whether adherence to the WCRF/AICR recommendations could reduce endometrial cancer risk. We used data from a multicentric, Italian hospital-based case–control study (1992–2006) including 454 endometrial cancer cases and 908 age-matched controls. Adherence to the WCRF/AICR recommendations was measured using a score (range: 0–7) based on seven components: body mass index (BMI), physical activity and five dietary items; higher scores indicated higher adherence. Odds ratios (OR) were estimated by multiple (adjusted) conditional logistic regression models including terms for major confounders and energy intake. Adherence to the WCRF/AICR recommendations was inversely related to endometrial cancer risk (OR = 0·42, 95 % confidence interval (CI) 0·30, 0·61 for the highest compared with the lowest score quartile), with a significant trend of decreasing risk with increasing adherence. An inverse association was also observed for a score including only dietary recommendations (OR = 0·67, 95 % CI 0·46, 0·96 for the highest compared with the lowest score tertile). In stratified analyses, the association was stronger among women with a normal weight, those who were older, and consequently those in post-menopause, and those with ≥ 2 children. In conclusion, high adherence to the WCRF/AICR recommendations has a favourable role in endometrial cancer risk, which is not fully explained by body weight.

The role of dietary factors in osteoporotic fractures (OFs) in women is not fully elucidated. We investigated the associations between incidence of OF and dietary calcium, magnesium and soy isoflavone intake in a longitudinal study of 48 584 postmenopausal women. Multivariable Cox regression was applied to derive hazard ratios (HRs) and 95 % confidence intervals (CIs) to evaluate associations between dietary intake, based on the averages of two assessments that took place with a median interval of 2⋅4 years, and fracture risk. The average age of study participants is 61⋅4 years (range 43⋅3–76⋅7 years) at study entry. During a median follow-up of 10⋅1 years, 4⋅3 % participants experienced OF. Compared with daily calcium intake ≤400 mg/d, higher calcium intake (>400 mg/d) was significantly associated with about a 40–50 % reduction of OF risk among women with a calcium/magnesium (Ca/Mg) intake ratio ≥1⋅7. Among women with prior fracture history, high soy isoflavone intake was associated with reduced OF risk; the HR was 0⋅72 (95 % CI 0⋅55, 0⋅93) for the highest (>42⋅0 mg/d) v. lowest (<18⋅7 mg/d) quartile intake. This inverse association was more evident among recently menopausal women (<10 years). No significant association between magnesium intake and OF risk was observed. Our findings provide novel information suggesting that the association of OF risk with dietary calcium intake was modified by Ca/Mg ratio, and soy isoflavone intake was modified by history of fractures and time since menopause. Our findings, if confirmed, can help to guide further dietary intervention strategies for OF prevention.

This study aimed to verify the association between the community food environment and dietary patterns in a population of different socio-economic levels. This cross-sectional study was conducted with a sample of 400 adults and elderly aged between 20 and 70 years residing in the central area of Porto Alegre, Rio Grande do Sul. Four dietary patterns were explored: healthy, traditional Brazilian, refined carbohydrates and sugars, and fast food. The community food environment included the identification of all food stores by areas where individuals lived and auditing based on the Nutrition Environment Measures Survey in Stores (NEMS-S) score. Poisson regression was used to estimate the prevalence ratios (PR) and their respective 95 % CI. After the adjustment for individual sociodemographic characteristics, residents of the area with the best community food environment (highest NEMS-S score) had 12 % and 18 % lower probabilities of high consumption (upper tertile) of the traditional (PR = 0·88; 95 % CI (0·78, 0·98)) and refined carbohydrate and sugar (PR = 0·82; 95 % CI (0·73, 0·92)) dietary patterns, respectively, compared with those living in the area with the worst community food environment (lowest NEMS-S score). Healthy and fast-food dietary patterns showed no association with the community food environment. In conclusion, the community food environment is a factor associated with the consumption of certain dietary patterns, independent of individual sociodemographic characteristics. Thus, aspects of the community food environment become important in food and nutrition actions and policies aimed at health promotion.

Food insecurity is an important public health concern; however, research into this phenomenon within the Netherlands is limited. Food insecurity is not solely related to individual factors, but can also be influenced by various factors in the social and physical environment. Therefore, this study aimed to identify determinants of food insecurity within the personal, social and physical environment, based on the social ecological model (SEM), and to identify their relative importance for experiencing food insecurity. The study population consisted of 307 participants living in disadvantaged neighbourhoods of the Dutch city The Hague, of which approximately one-quarter were food insecure. Participant characteristics showing bivariate associations P < 0⋅20 were placed in a predetermined level of the SEM, after which a multivariate logistic regression was performed for each level and the Nagelkerke pseudo R2 was presented. Determinants of food insecurity were BMI, gross monthly income, highest educational attainment, smoking status, diet quality, employment status, marital status and religion (P < 0⋅05). The results showed that 29⋅7 % of the total variance in food insecurity status was explained by all included determinants together. The personal, social and physical environment explained 20⋅6, 14⋅0 and 2⋅4 % of the total variance, respectively. Our findings suggest that determinants within the personal environment are most important for explaining differences in experienced food insecurity. The present study contributes to furthering the knowledge about the relative importance of the personal, social and physical environment, indicating that determinants within the personal environment may be most promising for developing targeted interventions to reduce food insecurity.

Constipation can greatly impact the quality of life (QoL), which can be relieved by dietary fibres; however, preserving a higher fibre intake remains a challenge. We investigated the effects of a personalised dietary advice (PDA) on fibre intake and mild constipation complaints. A total number of twenty-five adults with mild constipation complaints were included in a 4-week observation period followed by a 4-week personalised intervention. The PDA provided high-fibre alternatives via a web tool. In weeks 1, 4 and 8, dietary intake, constipation complaints and QoL were assessed. Furthermore, participants collected a faecal sample at weeks 1, 4 and 8 to determine microbiota diversity and composition, and short-chain fatty acids (SCFA). Participants completed questions daily for 8 weeks regarding abdominal complaints, stool frequency and stool consistency. Fibre intake in week 8 was significantly higher compared to week 1 (Δ = 5·7 ± 6·7 g, P < 0·001) and week 4 (Δ = 5·2 ± 6·4 g, P < 0·001). Constipation severity and QoL significantly improved at week 8 compared to the observation period (P < 0·001). A higher fibre intake significantly reduced constipation severity (β = −0·031 (−0·05; −0·01), P = 0·001) and the QoL (β = −0·022 (−0·04; −0·01), P = 0·009). Stool consistency (P = 0·040) and abdominal pain (P = 0·030) improved significantly during the intervention period (P = 0·040), but stool frequency did not. Average microbial alpha diversity and composition and SCFA concentrations did not change over time, but indicated individual-specific dynamics. Several SCFAs were associated with constipation complaints. To conclude, a PDA effectively increased fibre intake and subsequently reduced constipation complaints, indicating that guided dietary adjustments are important and feasible in the treatment of mild constipation complaints.

There is a lack of region-adapted tools to evaluate diet as a risk factor for cardiovascular disease (CVD) in adolescents. The study aim was to evaluate the reproducibility and validity of a paper-based and region-adapted food frequency questionnaire (FFQ) designed to assess CVD-related food and nutrient intakes of adolescents from Northwest México. The study design was cross-sectional. The FFQ was developed in a two-step process: prototype designing and a pilot test, with re-tested in a 3-month period, along with two administrations of 24 h-recall (24 hR). Pearson's and intra-class correlation coefficients (PCC and ICC) were assessed. Bland–Altman plots, limits of agreement and quintile classifications were carried out. Participants (n 221) were 53·8 % male, 18·5 ± 0·4 years old. Reproducibility had a median PCC = 0·66 for processed meats, ranging from 0·40 (saturated fat) to 0·74 (fish & shellfish), P = 0·001. ICC ranged from 0·53 (saturated fat) to 0·80 (sodium; and nuts, seeds and legumes), P = 0·001. Validity comparing FFQ1 v. 24 hR mean, PCCs ranged from 0·12 (P = 0·06) to 0·95 (P = 0·001), and ICC from 0·20 (P = 0·048) to 0·88 (P = 0·001); comparing FFQ2 v. 24 hR mean, PCCs ranged from 0·07 (P = 0·25) to 0·46 (P = 0·001), and ICC from 0·15 (P = 0·106) to 0·58 (P = 0·001). The FFQ overestimated the intake of all food groups and nutrients (P < 0·05), while Cohen's κ showed coefficients lower than 0·20. The proposed FFQ represents a moderately validated tool to estimate CVD-related food and nutrient intakes as a risk factor, which can be used in combination with multiple administrations of 24 hRs, as a critical mean in future interventions intended to reduce cardiometabolic risk in adolescents.

In recent decades, different data-driven approaches have emerged to identify dietary patterns (DP) and little is discussed about how these methods are able to capture diet complexity within the same population. This study aimed to apply three statistical methods to identify the DP of the Longitudinal Study of Adult Health (ELSA-Brasil) population and evaluate the similarities and differences between them. Dietary data were assessed at baseline in the ELSA-Brasil study using a FFQ. DP were identified by applying three statistical methods: (1) factor analysis (FA), (2) treelet transform (TT) and (3) reduced rank regression (RRR). The characteristics of individuals classified in the last tertile of each DP were compared. Cross-classification and Pearson’s correlation coefficients were assessed to evaluate the agreement between individuals’ adherence to DP of the three methods. A similar convenience DP was identified for all three methods. FA and TT also identified a similar prudent DP and a DP highly loaded for the food groups rice and beans. Individuals classified in the third tertile of similar DP of each method presented similar socio-demographic and nutrient intake characteristics. Regarding the cross-classification, prudent DP from FA and TT presented a higher level of agreement (75 %), while convenience DP from TT and RRR presented the lowest agreement (44·8 %). The different statistical methods were able to capture the populations’ DP in a similar way while highlighting the particularities of each method.

Dietary pattern analysis is typically based on dimension reduction and summarises the diet with a small number of scores. We assess ‘joint and individual variance explained’ (JIVE) as a method for extracting dietary patterns from longitudinal data that highlights elements of the diet that are associated over time. The Auckland Birthweight Collaborative Study, in which participants completed an FFQ at ages 3·5 (n 549), 7 (n 591) and 11 (n 617), is used as an example. Data from each time point are projected onto the directions of shared variability produced by JIVE to yield dietary patterns and scores. We assess the ability of the scores to predict future BMI and blood pressure measurements of the participants and make a comparison with principal component analysis (PCA) performed separately at each time point. The diet could be summarised with three JIVE patterns. The patterns were interpretable, with the same interpretation across age groups: a vegetable and whole grain pattern, a sweets and meats pattern and a cereal v. sweet drinks pattern. The first two PCA-derived patterns were similar across age groups and similar to the first two JIVE patterns. The interpretation of the third PCA pattern changed across age groups. Scores produced by the two techniques were similarly effective in predicting future BMI and blood pressure. We conclude that when data from the same participants at multiple ages are available, JIVE provides an advantage over PCA by extracting patterns with a common interpretation across age groups.

We developed a culturally-specific Food Frequency Questionnaire (FFQ) to the Ethiopian context and evaluate its validity in comparison to two 24-h dietary recalls (24-HRs) of food and nutrient intake. To evaluate the validity of a culturally-specific FFQ against two 24-HRs, we used a paired t-test, Wilcoxon-signed-rank test, Correlation coefficients, cross-classification, κ and Bland-Altman analysis. The FFQ was obtained 15 d after the second 24-HR was completed. A total of 105 adults, of which 43 (41 %) were men and 62 (59 %) women, aged 20–65 years participated in this present study. Mean energy and macronutrient intake obtained from the FFQ were significantly higher than those obtained from the mean of two 24-HRs. For energy and nutrient intakes, the crude correlation ranged from 0⋅05 (total fat) to 0⋅49 (vitamin B1). The de-attenuated correlation ranged from to 0⋅10 (total fat) to 0⋅80 (vitamin A). For the majority of food groups, no significant difference was observed in the median intake of food and nutrients. Crude correlation for food groups ranged from 0⋅12 (egg) to 0⋅78 (legumes). The de-attenuated correlation ranged from 0⋅24 (egg) to 1⋅00 (meat/poultry/fish and dairy). The FFQ is valid to assess and rank individuals in terms of intake of most food groups according to high and low intake categories.

Recent genome-wide association studies (GWAS) on the dietary habits of the Japanese population have shown that an effect rs671 allele was inversely associated with fish consumption, whereas it was directly associated with coffee consumption. Although meat is a major source of protein and fat in the diet, whether genetic factors that influence meat-eating habits in healthy populations are unknown. This study aimed to conduct a GWAS to find genetic variations that affect meat consumption in a Japanese population. We analysed GWAS data using 14 076 participants from the Japan Multi-Institutional Collaborative Cohort (J-MICC) study. We used a semi-quantitative food frequency questionnaire to estimate food intake that was validated previously. Association of the imputed variants with total meat consumption per 1000 kcal energy was performed by linear regression analysis with adjustments for age, sex, and principal component analysis components 1–10. We found that no genetic variant, including rs671, was associated with meat consumption. The previously reported single nucleotide polymorphisms that were associated with meat consumption in samples of European ancestry could not be replicated in our J-MICC data. In conclusion, significant genetic factors that affect meat consumption were not observed in a Japanese population.

Eggs contain important compounds related to enhanced cognition, but it is not clear if egg consumption, as a whole, has a direct impact on memory decline in older adults. This study aimed to determine whether egg intake levels predict the rate of memory decline in healthy older adults after sociodemographic and dietary controls. We conducted a secondary analysis of data from 470 participants, age 50 and over, from the Biospsychosocial Religion and Health Study. Participants completed a food frequency questionnaire, which was used to calculate egg intake and divide participants into Low (<23 g/week, about half an egg), Intermediate (24–63 g/week, half to 1½ eggs) and High (≥63 g/week, about two or more eggs) tertiles. Participants were administered the California Verbal Learning Test – 2nd Edition (CVLT-II) Short Form in 2006–2007, and 294 of them were again tested in 2010–2011. Using linear mixed model analysis, no significant cross-sectional differences were observed in CVLT-II performance between egg intake levels after controlling for age, sex, race, education, body mass index, cardiovascular risk, depression and intake of meat, fish, dairy and fruits/vegetables. Longitudinally, the Intermediate egg group exhibited significantly slower rates of decline on the CVLT-II compared to the Low egg group. The High egg group also exhibited slower rates of decline, but not statistically significant. Thus, limited consumption of eggs (about 1 egg/week) was associated with slower memory decline in late life compared to consuming little to no eggs, but a dose-response effect was not clearly evident. This study may help explain discrepancies in previous research that did not control for other dietary intakes and risk factors.

This manuscript details the strategy employed for categorising food items based on their processing levels into the four NOVA groups. Semi-quantitative food frequency questionnaires (FFQs) from the Nurses’ Health Studies (NHS) I and II, the Health Professionals Follow-up Study (HPFS) and the Growing Up Today Studies (GUTS) I and II cohorts were used. The four-stage approach included: (i) the creation of a complete food list from the FFQs; (ii) assignment of food items to a NOVA group by three researchers; (iii) checking for consensus in categorisation and shortlisting discordant food items; (iv) discussions with experts and use of additional resources (research dieticians, cohort-specific documents, online grocery store scans) to guide the final categorisation of the short-listed items. At stage 1, 205 and 315 food items were compiled from the NHS and HPFS, and the GUTS FFQs, respectively. Over 70 % of food items from all cohorts were assigned to a NOVA group after stage 2. The remainder were shortlisted for further discussion (stage 3). After two rounds of reviews at stage 4, 95⋅6 % of food items (NHS + HPFS) and 90⋅7 % items (GUTS) were categorised. The remaining products were assigned to a non-ultra-processed food group (primary categorisation) and flagged for sensitivity analyses at which point they would be categorised as ultra-processed. Of all items in the food lists, 36⋅1 % in the NHS and HPFS cohorts and 43⋅5 % in the GUTS cohorts were identified as ultra-processed. Future work is needed to validate this approach. Documentation and discussions of alternative approaches for categorisation are encouraged.