Different dietary indexes are proposed to investigate adherence to the Mediterranean diet (MD). However, they are based on different methodologies, and limited research has compared them to each other, particularly in non-Mediterranean populations. We aimed to compare five indexes intended to measure adherence to the MD. The sample was composed of adults and older adults (n 1187) from 2015 ISA-Nutrition, a cross-sectional population-based study in São Paulo, SP, Brazil. Dietary data obtained through two 24-h dietary recalls (24HDR) from which the Mediterranean diet scale (MDS), Mediterranean diet Score (MedDietscore), Mediterranean dietary pattern (MDP), Mediterranean Adequacy Index (MAI) and Mediterranean-Style Dietary Pattern Score (MSDPS) were calculated. The correlations and agreements between them were analysed by Spearman's correlation and linearly weighted Cohen's Kappa coefficients, respectively. Confirmatory factor analyses (CFAs) were applied to investigate their convergent validity. The highest correlations were found between MDP and MAI (r = 0⋅76; 95% CI 0⋅74–0⋅79) and between MDP and MDS (r = 0⋅72; 95% CI 0⋅69–0⋅75). The greatest agreements observed were moderate, between MDP v. MAI (κ = 0⋅57, P < 0⋅001) and MDP v. MDS (κ = 0⋅48, P < 0⋅001). The goodness-of-fit of CFA for MedDietscore (RMSEA = 0⋅033, 90% CI 0⋅02–0⋅042; SRMR = 0⋅042) and MSDPS (RMSEA = 0⋅028, 90% CI 0⋅019–0⋅037; SRMR = 0⋅031) had acceptable values for absolute fit indices. Vegetables, olive oil, MUFA:SFA ratio and cereals with legumes were more relevant to characterise the MD (factor loadings ≥0⋅50). The MDS, MAI and MDP classified the population similarly, but the MedDietscore showed better performances in evaluating adherence to the MD. These results provided guidance for the most appropriate Mediterranean dietary index to be applied in non-Mediterranean populations.

The aim of the present study was to investigate the relationship of four TNF-α SNP with inflammatory biomarkers and plasma fatty acids (FA), and the interaction among them in a population-based, cross-sectional study in São Paulo, Brazil. A total of 281 subjects, aged >19 and <60 years, participated in a cross-sectional, population-based study performed in Brazil. The following SNP spanning the TNF-α gene were genotyped: -238G/A (rs361525), -308G/A (rs1800629), -857C/T (rs1799724) and -1031T/C (rs1799964). In all, eleven plasma inflammatory biomarkers and plasma FA profile were determined. To analyse the interaction between TNF-α SNP and plasma FA, a cluster analysis was performed to stratify individuals based on eleven inflammatory biomarkers into two groups used as outcome: inflammatory (INF) and non-inflammatory clusters. The -238A allele carriers had higher TNF-α (P=0·033), IL-6 (P=0·013), IL-1β (P=0·037), IL-12 (0·048) and IL-10 (P=0·010) than the GG genotype. The -308A allele carriers also had lower levels of plasma palmitoleic acid (P=0·009), oleic acid (P=0·039), total MUFA (P=0·014), stearoyl-CoA desaturase (SCD) activity index-16 (P=0·007), SCD-18 (P=0·020) and higher levels of PUFA (P=0·046) and DHA (P=0·044). Significant interactions modifying the risk of belonging to the INF cluster were observed with inflammatory cluster as outcome between -857C/T and plasma α-linolenic acid (P=0·026), and also between -308G/A and plasma stearic acid (P=0·044) and total SFA (P=0·040). Our study contributes to knowledge on TNF-α SNP and their association with inflammatory biomarker levels, plasma FA and the interaction among them, of particular interest for the Brazilian population.

This cross-sectional, population-based study aimed to estimate the prevalence of dietary mineral inadequacies among residents in urban areas of Sao Paulo, to identify foods contributing to mineral intake and to verify possible associations between socio-demographic and lifestyle factors and mineral intake. Data were obtained from the 2008 Health Survey of Sao Paulo (n 1511; mean age 43·6 (sd 23·2), range 14–97 years). Dietary intake of minerals was measured using two 24-h dietary recalls. Socio-demographic and lifestyle data were collected. The prevalence of inadequate intake was estimated according to Dietary Reference Intakes methods. Associations between mineral intake and baseline factors were determined using multiple linear regression. Na, Ca and Mg showed the highest dietary inadequacies. Some age/sex groups had lower intakes of P, Zn, Cu and Se. Rice, beans and bread were the main foods contributing towards mineral intake. Female sex was negatively associated with K, Na, P, Mg, Zn and Mn intakes. All age groups were positively associated with the intakes of K, P, Mg and Mn. Family income above one minimum wage was positively associated with Se intake. Living in a household whose head completed ≥10 years of education was positively associated with Ca and negatively associated with Na intake. Former smoker status was negatively associated with Ca intake. Current smoker status was inversely associated with K, Ca, P and Cu intakes. Sufficient physical activity was positively associated with K, Ca and Mg intakes. Overall, the intakes of all major minerals were inadequate and were influenced by socio-demographic and lifestyle factors.

There are statistical methods that remove the within-person random error and estimate the usual intake when there is a second 24-h recall (24HR) for at least a subsample of the study population. We aimed to compare the distribution of usual food intake estimated by statistical models with the distribution of observed usual intake. A total of 302 individuals from Rio de Janeiro (Brazil) answered twenty, non-consecutive 24HR; the average length of follow-up was 3 months. The usual food intake was considered as the average of the 20 collection days of food intake. Using data sets with a pair of 2 collection days, usual percentiles of intake of the selected foods using two methods were estimated (National Cancer Institute (NCI) method and Multiple Source Method (MSM)). These estimates were compared with the percentiles of the observed usual intake. Selected foods comprised a range of parameter distributions: skewness, percentage of zero intakes and within- and between-person intakes. Both methods performed well but failed in some situations. In most cases, NCI and MSM produced similar percentiles between each other and values very close to the true intake, and they better represented the usual intake compared with 2-d mean. The smallest precision was observed in the upper tail of the distribution. In spite of the underestimation and overestimation of percentiles of intake, from a public health standpoint, these biases appear not to be of major concern.