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2022 ◽  
Vol 109 ◽  
pp. 103383
Pierre Ganault ◽  
Sandra Barantal ◽  
Sylvain Coq ◽  
Stephan Hättenschwiler ◽  
Shéhérazade Lucas ◽  

2024 ◽  
Vol 55 (11) ◽  
pp. 973-979 ◽  
P Deurenberg ◽  
A Andreoli ◽  
P Borg ◽  
K Kukkonen-Harjula ◽  
A de Lorenzo ◽  

2022 ◽  
Vol 270 ◽  
pp. 348-358
Adrienne N. Christopher ◽  
Martin P Morris ◽  
Viren Patel ◽  
Robyn B. Broach ◽  
John P. Fischer

2022 ◽  
Vol 9 ◽  
Saeed Mastour Alshahrani ◽  
Abdullah F. Alghannam ◽  
Nada Taha ◽  
Shurouq Saeed Alqahtani ◽  
Abrar Al-Mutairi ◽  

The COVID-19 pandemic has had a major impact on various health conditions. The objective of this study was to assess the impact of the COVID-19 pandemic on body weight and body mass index (BMI) in Saudi Arabia. We used electronic health records obtained from a healthcare system representing five hospitals in three different regions in the Kingdom to examine the change in weight utilizing a longitudinal design. The study included all adults who had visited outpatient clinics in two different time points, pre-2020 (years 2018 and 2019 prior to COVID-19) and post-2020 (the year 2021). Weight and BMI changes in percentages were described. Also, bivariate chi-square test, paired t-test, and multivariable multinomial logistic regression model were used for the analyses. A total of 165,279 individuals were included in the study. On average, a significant weight gain of 0.33 kg (95% CI: 0.29–0.36) was observed in our study. Approximately 10% of the population had shifted to either overweight or obese BMI classes during the study period, as 4.8% of those with normal BMI pre-2020 had shifted to overweight or obese classes at post-2020, and 5.1% of those who were overweight had shifted to obese class. Also, 23.1% of the population had gained 5% or more of their pre-2020 weight, while 17% had lost 5% or more. Young individuals were over three times more likely to gain 5% or more than older individuals (OR: 3.34; 95% CI: 3.12–3.56). Females had 24% higher odds to gain 5% or more of their pre-2020 weight than males (OR: 1.24; 95% CI: 1.21–1.27). Diabetics were 27% more likely to lose 5% or more than non-diabetics (OR: 1.27; 95% CI: 1.23–1.31). Our findings provide insights into the impact of COVID-19 on weight and population health. Further investment in interventions for weight management is warranted during similar circumstances such as lockdowns due to infection waves or new variants. Future studies are also needed to explore the modifications that have occurred during the pandemic in the weight-related lifestyle factors such as dietary choices and physical activity levels.

Jérémy Raffin ◽  
Davide Angioni ◽  
Kelly V Giudici ◽  
Philippe Valet ◽  
Geetika Aggarwal ◽  

Abstract Physical activity (PA) has been shown to moderate the negative effects of obesity on pro-inflammatory cytokines but its relationship with the adipokine progranulin (PGRN) remains poorly investigated. This study aimed to examine the cross-sectional main and interactive associations of body mass index (BMI) and PA level with circulating PGRN in older adults. Five-hundred and twelve subjects aged 70 years and over involved in the Multidomain Alzheimer Prevention Trial (MAPT) Study who underwent plasma PGRN measurements (ng/ml) were included. Self –reported PA levels were assessed using questionnaires. People were classified into three BMI categories: normal weight, overweight or obesity. Further categorization using PA tertiles was used to define highly active, moderately active and low active individuals. Multiple linear regressions were performed in order to test the associations of BMI, PA level, and their interaction with PGRN levels. Multiple linear regressions adjusted by age, sex, diabetes mellitus status, total cholesterol, creatinine level and MAPT group demonstrated significant interactive associations of BMI status and continuous PA such that in people without obesity, higher PA levels were associated with lower PGRN concentrations, while an opposite pattern was found in individuals with obesity. In addition, continuous BMI was positively associated with circulating PGRN in highly active individuals but not in their less active peers. This cross-sectional study demonstrated reverse patterns in older adults with obesity compared to those without obesity regarding the relationships between PA and PGRN levels. Longitudinal and experimental investigations are required to understand the mechanisms that underlie the present findings.

Jelena Ivanović ◽  
Filip Kukić ◽  
Gianpiero Greco ◽  
Nenad Koropanovski ◽  
Saša Jakovljević ◽  

This study investigated the hierarchical structure of physical characteristics in elite young (i.e., U17-U19) basketball players according to playing positions. In addition, their predictive value of physical characteristics was determined for the evaluation of players’ physical preparedness. Sixty elite male basketball players performed 13 standardized specific field tests in order to assess the explosive power of lower limbs, speed, and change-of-direction speed. They were divided into three groups according to playing positions (guard [n = 28], forward [n = 22], center [n = 10]). The basic characteristics of the tested sample were: age = 17.36 ± 1.04 years, body height = 192.80 ± 4.49 cm, body mass = 79.83 ± 6.94 kg, and basketball experience = 9.38 ± 2.10 years for guards; age = 18.00 ± 1.00 years, body height = 201.48 ± 3.14 cm, body mass = 90.93 ± 9.85 kg, and basketball experience = 9.93 ± 2.28 years for forwards; and age = 17.60 ± 1.43 years; body height = 207.20 ± 3.29 cm, body mass = 104.00 ± 9.64 kg, and basketball experience = 9.20 ± 1.62 years for centers. For all playing positions factor analysis extracted three factors, which cumulatively explained 76.87, 88.12 and 87.63% of variance, respectively. The assessed performance measures were defined as significant (p < 0.001), with regression models of physical performance index (PPINDEX). PPINDEX of guards = −6.860 + (0.932 × t-test) − (1.656 × Acceleration 15 m) − (0.020 × Countermovement jump); PPINDEX of forwards = −3.436 − (0.046 × Countermovement jump with arm swing) − (1.295 × Acceleration 15 m) + (0.582 × Control of dribbling); PPINDEX of centers = −4.126 + (0.604 × Control of dribbling) − (1.315 × Acceleration 15 m) − (0.037 × Sargent jump). A model for the evaluation of physical performance of young basketball players has been defined. In addition, this model could be used as a reference model for selection procedures, as well as to monitor the efficacy of applied training programmes within the short, medium and long-term periodization.

María Teresa Martínez-Romero ◽  
Antonio Cejudo ◽  
Pilar Sainz de Baranda

Puberty is a vulnerable period for musculoskeletal disorders due to the existence of a wide inter-individual variation in growth and development. The main objective of the present study was to describe the prevalence of back pain (BP) in the past year and month in school-aged children according to sex, age, maturity status, body mass index (BMI) and pain characteristics. This study involved 513 students aged between 9 and 16 years. Anthropometric measures were recorded to calculate the maturity stage of the students using a regression equation comprising measures for age, body mass, body height, sitting height and leg length. An ad hoc questionnaire composed of eight questions was used to describe BP prevalence in school-aged children. The results showed that the prevalence of BP in school-aged children was observed in 35.1% over the last year (45% boys and 55% girls), and 17.3% (40.4% boys and 59.6% girls, with an association found between female sex and BP) in the last month. The prevalence of back pain in the past year and month was higher the older the students were, or the more pubertal development they had experienced. The prevalence of BP in the last year was also higher in those with overweight or obesity. After adjustment for sex, there was an association between BP and older age and higher BMI in boys and an association between BP and higher pubertal development in girls. In summary, the present study showed that the prevalence of BP was related to the maturity stage and weight of the participants, with different prevalence patterns found according to sex.

Metabolites ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 81
Bryant H. Keirns ◽  
Christina M. Sciarrillo ◽  
Samantha M. Hart ◽  
Sam R. Emerson

Post-meal triglycerides are an independent cardiovascular disease (CVD) risk factor, but the ideal high-fat meal formulation has yet to be standardized and is one challenge prohibiting widespread clinical adoption of postprandial triglyceride assessment. Two general approaches often used are giving individuals a high-fat meal scaled to body weight or a standardized high-fat meal containing a set fat bolus. A recent expert panel statement has endorsed the latter, specifying 75 g of fat as an appropriate fat dosage. Despite this recommendation, no study to date has tested whether there is a difference in postprandial triglycerides or if risk classification is affected based on these different approaches. We recruited 16 generally healthy individuals with roughly equal distribution among body mass index (BMI)class (n = 5–6/per BMI category) and sex (n = 2–3 M/F) within each BMI class. Each participant underwent two abbreviated fat tolerance tests separated by ~1 week: one with a scaled to body weight high-fat meal (9 kcal/kg; 70% fat) and a standardized meal containing 75 g of fat (70% fat). Fasting, 4 h, and absolute change in triglycerides across the entire sample and within each BMI category were similar regardless of high-fat meal. Only one participant with obesity had discordant postprandial responses between the fat tolerance tests (i.e., different CVD risk classification). These findings suggest that, within a certain range of fat intake, generally healthy individuals will have a similar postprandial triglyceride response. Considering the greater convenience of utilizing standardized high-fat meals, our data suggest that a standardized high-fat meal may be acceptable for large-scale studies and clinical implementation.

2022 ◽  
Vol 8 (4) ◽  
pp. 260-264
S Ravichandran ◽  
Mahrukh Mehraj ◽  
Fathima Feroz ◽  
R M Madhumitha Sri

Malnutrition is a condition that results from eating a diet that does not supply a healthy amount of one or more nutrients. It is a condition characterized by lack of one or more essential nutrients from the diet or a surplus of some nutrients which affect the body negatively. Malnutrition consists of two types: undernutrition and overnutrition. Undernutrition involves the deficiency of macronutrients like protein or calories and micronutrients like iron, iodine and many more. Protein energy malnutrition is caused by the inadequate intake of protein and calories. It is further classified in three types, kwashiorkor, marasmus and marasmic kwashiorkor. Malnutrition mainly affects an individual’s immune system, lean body mass, cardio-respiratory functions, muscle functions. Malnutrition can be caused due to many factors including unavailability of food, poverty, higher food prices and many more. Strategies like biofortification and supplementation are used for the treatment of malnutrition.

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