Handgrip strength (HGS) is a well-established indicator of muscle strength and can help to identify risk of sarcopenic obesity in children. This study explores the relationship between adiposity and muscular strength in healthy Chilean adolescents. Adolescents (n = 491) aged 10-17 were selected from five schools in Santiago, Chile. HGS was determined by dynamometry. Anthropometry (weight, height, waist and mid arm circumference), physical activity and socioeconomic status were also measured. Relative HGS (RHGS) was calculated by dividing maximum HGS of the dominant hand by body-mass index (BMI) and low RHGS was categorized as <25 th percentile by sex. Logistic regression was used to determine the relationship between two markers of adiposity (abdominal obesity category by waist circumference and nutritional status measured by BMI category) and low RHGS, adjusting for possible confounding variables. Participants were on average 13.6y (2.4), 32.8% were overweight or obese and 37.5% were at risk of or had abdominal obesity. RHGS was 1.25 kg/kg/m 2 overall, with a significant difference by sex (1.51 for boys versus 1.14 for girls). In adjusted analyses, boys and girls with risk of abdominal obesity, had 3.3 (1.6-6.6) and 4.1 (1.8-9.3) increased odds of low RHGS, respectively, compared to boys and girls with normal waist circumference. Those with abdominal obesity compared to normal WC, had 8.5 (3.4-21.4) and 6.5 (2.0-21.3) increased odds of low RHGS for boys and girls, respectively. We observed similar associations for BMI category. In our sample of healthy adolescents, higher adiposity related to greater odds of low muscle strength measured by dynamometry. Considering the demographic shift from a young to an aging population in many countries, along with the increasing prevalence of obesity beginning in childhood, understanding how adiposity relates to low muscle strength is of growing importance.

IntroductionIncreasing consumption of ultra-processed foods (UPF), defined by the NOVA classification, has been associated with obesity and other health outcomes. However, some authors have criticized the UPF definition because it is somewhat subjective. Most studies identify UPF using food descriptions; nevertheless, NOVA developers described a list of ingredients, including substances not commonly used for cooking and “cosmetic additives” that could be used to identify UPF. Assessing the impact of the use of different UPF definitions is particularly relevant with respect to children’s diet, because several dietary policies target this age group. Thus, our study compared the frequency of UPF among foods and beverages and their share in the diet of Chilean preschoolers using three different methods of identifying UPF.MethodsWe used cross-sectional 24-h dietary recall data from 962 preschoolers enrolled in the Food and Environment Chilean Cohort (FECHIC) in 2016. All foods and beverages consumed were classified according to NOVA, considering their description (classic method), the presence of ingredients markers of UPF (ingredient marker method), and the presence of markers plus all cosmetic additives (food additive method). We also estimated the caloric share and quintiles of UPF consumption using the three methods. We used kappa coefficients, consistency-of-agreement intra-class correlation (CA-ICC), absolute agreement intra-class correlation (AA-ICC), and weighted kappa coefficients for assessing agreement between methods.ResultsThe proportion of UPF products were 65% in the “classic,” 67% in the “ingredient marker,” and 73% in the “food additive” method, and kappa coefficients between methods varied from 0.79 to 0. 91. The caloric share of UPF was 47, 52, and 58% with “classic,” “ingredient marker,” and “food additive” methods, respectively. Consistency-of-agreement was higher than the absolute agreement between the methods (CA-ICC = 0.81; AA-ICC = 0.74). For quintiles of UPF consumption, we found weighted kappa of 0.65 as measure of agreement between “classic” and “ingredient marker,” and 0.51 between “classic” and “food additive” methods.ConclusionSearching for all possible markers of UPF in the list of ingredients increased the proportion of food products identified as UPF compared to the classic method. These differences affected the estimated caloric share of UPF in Chilean preschoolers’ diets.

Breakfast is one of the most important meals of the day. A good quality breakfast must include dairy products, cereals, and fruits. The aim of this study is to determine breakfast dietary patterns and their nutritional quality among Chilean university students. A cross-sectional non-probabilistic study was conducted in 200 university students between 18 and 27 years in Santiago, Chile. To identify dietary patterns and breakfast quality, a breakfast food survey was conducted. Patterns were identified by factor analysis. Most of the subjects (53%) ate breakfast daily, with a higher prevalence among females (60.2% vs. 43.7%, p < 0.05); 68% did not consume fruits and 17.5% had good breakfast quality, with no differences by sex. Four breakfast dietary patterns were identified: “dairy & cereals”, “healthy”, “traditional salty” and “traditional sweet” that together explained 35.6% of the total variance. There was no sex difference in predominant dietary patterns. The “dairy & cereals” and “traditional sweet” patterns were associated with regularly eating breakfast (β: −0.47, p = 0.001; β: −0.32, p = 0.020) and the “healthy” pattern with BMI ≥25 kg/m2 (β: 0.35, p = 0.024). In conclusion, breakfast quality was inadequate due to low fruit consumption and energy intake. The four identified patterns included cereals, bread, dairy, fats and sugars. Results may be usual in the planning of future interventions aimed at improving breakfast consumption and quality in university students.

Handgrip strength (HGS) is a well-established indicator of muscle strength and a reasonable clinical predictor of metabolic health and diseases. This study explores the association between relative muscular strength and abdominal obesity (AO) in healthy Chilean adults. A convenience sample was recruited (n = 976) between 2018 and 2020. The HGS was determined by dynamometry. The anthropometry (weight, height, waist, and mid-arm circumference) and physical activity were also measured. The relative HGS (RHGS) was calculated by dividing the maximum HGS of the dominant hand by the body mass index. The AO was defined as a waist circumference (WC) &gt;88 cm for women, and &gt;102 cm for men. From the sample, 52.6% were women, 56.4% had excessive weight, and 42.7% had AO. The absolute and RHGS were greater in men compared to women (p &lt; 0.001) and were decreased with age in both sexes. We observed a moderate negative correlation between WC and RHGS (rho = −0.54, and rho = −0.53, for men and women, respectively). The RHGS was lower in individuals with AO, independent of age and sex (p &lt; 0.05). For each cm increase in WC, the odds of low RHGS (&lt;25th percentile) increased by 12 and 9% for men and women, respectively. The AO is related to higher odds for low RHGS (OR: 1.72; 95% CI: 1.23–2.41). In our sample of healthy adults, a higher AO was associated with a lower muscle strength measured by dynamometry.