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The association between ultra-processed food (UPF) and risk of cardiometabolic disorders is an ongoing concern. Different food processing-based classification systems have originated discrepancies in the conclusions among studies. To test whether the association between UPF consumption and cardiometabolic markers changes with the classification system, we used baseline data from 5636 participants (48.5% female and 51.5% male, mean age 65.1 ± 4.9) of the PREDIMED-Plus (“PREvention with MEDiterranean DIet”) trial. Subjects presented with overweight or obesity and met at least three metabolic syndrome (MetS) criteria. Food consumption was classified using a 143-item food frequency questionnaire according to four food processing-based classifications: NOVA, International Agency for Research on Cancer (IARC), International Food Information Council (IFIC) and University of North Carolina (UNC). Mean changes in nutritional and cardiometabolic markers were assessed according to quintiles of UPF consumption for each system. The association between UPF consumption and cardiometabolic markers was assessed using linear regression analysis. The concordance of the different classifications was assessed with intra-class correlation coefficients (ICC3, overall = 0.51). The highest UPF consumption was obtained with the IARC classification (45.9%) and the lowest with NOVA (7.9%). Subjects with high UPF consumption showed a poor dietary profile. We detected a direct association between UPF consumption and BMI (p = 0.001) when using the NOVA system, and with systolic (p = 0.018) and diastolic (p = 0.042) blood pressure when using the UNC system. Food classification methodologies markedly influenced the association between UPF consumption and cardiometabolic risk markers.

a lower intake of vitamins B6, C, E and folates was associated with a higher risk of frailty. Not meeting RDAs for vitamins was also strongly associated.

Self-reported sleep duration is not associated with hypertension in older adults.

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OBJECTIVE: To identify the factors associated with geographic variations in Body Mass Index (BMI) and obesity in Spain. DESIGN: Cross-sectional, ecological analysis using data on illiteracy rate (per 1000 population), energy intake (kcala apersona ad), sedentary population (%), smoking population (%), alcohol consumption (gapersonad), and percentage of population aged 65 y or over, for Spain's 50 provinces. SUBJECTS: Non-institutionalized population aged 16 y or over. MEASUREMENTS: Median BMI and percentage of population with obesity, de®ned as BMI b 30 kgam 2 . RESULTS: There was a clear geographical pattern, with some areas in the south and north-west of the country registering the highest BMI and prevalence of obesity and a north ± south pattern on illiteracy per 1000 population. Multivariate regression analysis showed that illiteracy, sedentary lifestyle and energy intake explain 35% and 14% of the variation in BMI and obesity, respectively. Illiteracy proved to be the variable most associated with both BMI (regression coef®cient (b b 0.01; P 0.005) and obesity (b b 0.05; P 0.013). Sedentary lifestyle showed a statistically signi®cant relationship with BMI (b b 0.01; P 0.03), but not with obesity (b b 0.03; P 0.581). Energy intake exhibited a relationship with BMI (b b`0.01 P 0.03) that lost statistical signi®cance when adjusted for age. CONCLUSION: Geographical variations in BMI in Spain are partly explained by illiteracy, sedentary lifestyle and, to a lesser extent, energy intake, whereas regional variations in obesity are related only to the educational level of the population.

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