Search

Muscle and bone have been considered a functional unit that grows together early in life, deteriorates with aging, and can cause osteosarcopenia. Due to its importance in public health, detecting risk factors in early life is desirable. This study examined whether birth weight (BW) was associated with muscle–bone unit using dual energy X-ray absorptiometry (DXA) parameters in young women from the Nutritionists’ Health Study (NutriHS), a cohort study of undergraduates and Nutrition graduates. This cross-sectional analysis included 170 young healthy women who answered early life events-questionnaire, and had anthropometric, muscle tests and DXA-determined body composition and bone densitometry (iDXA-Lunar®). A blood sample was obtained for a subsample of 148 participants. Appendicular skeletal muscle mass index (ASMI) was calculated. BW was categorized in quartiles (BWq) and variables of interest compared by ANOVA. Associations of BWq with calf circumference (CC), handgrip, muscle performance tests, ASMI, bone mineral density and content (BMD and BMC), and plasma glucose, lipids, insulin, and 25-hydroxyvitamin D were performed using multiple linear regression and directed acyclic graph-recommended adjustments. Mean values of age, body mass index, and BW were 23.0 years (20.0–28.0), 22.9 ± 2.9 kg/m2, and 3199 ± 424 g, respectively. Comparing variables across BWq, significant differences in CC, handgrip, ASMI, and total body BMC were detected. Regression models adjusted for confounders showed associations of BWq with CC (β = 0.72, p = 0.005), handgrip (β = 1.53, p = 0.001), ASMI (β = 0.16, p = 0.022), total body BMC (β = 64.8, p = 0.005), total femur BMC (β = 0.70, p = 0.041), total body BMD (β = 0.02, p = 0.043), and lumbar spine BMD (β = 0.03, p = 0.028). We conclude that BW is associated with muscle–bone unit using DXA-parameters in Brazilian young healthy women from the NutriHS, suggesting a role for intrauterine environment for musculoskeletal health.

Objective:To investigate the association between maternal pre-pregnancy BMI and offspring body composition in adulthood.Design:Retrospective cohort. Undergraduates of nutrition or nutritionists were recruited at the baseline of the Nutritionists’ Health Study between 2014 and 2017. Maternal pre-pregnancy BMI and current life aspects were self-reported through online questionnaires. Three body compartments were dual-energy x-ray absorptiometry-determined. The following variables were obtained: body fat (%), fat mass index (FMI) (kg/m2), android-to-gynoid fat ratio, visceral adipose tissue (VAT) (cm3), appendicular skeletal muscle mass index (ASMI) (kg/m2), total bone and femur mineral content (g) and density (g/cm2). Linear regression adjusted according to directed acyclic graphs recommendation was performed.Setting:São Paulo, Brazil.Participants:Healthy non-pregnant women (aged 20–45 years) (n 150).Results:Median age and BMI were 22 years (IQR = 20, 29) and 22·3 kg/m2 (IQR = 20·4, 25·3), respectively. Pre-pregnancy BMI ≥ 25 kg/m2 was reported by 14·7 % of mothers. In fully adjusted models, maternal pre-pregnancy BMI was associated with their daughters’ body fat % (β = 0·31; 95 % CI 0·0004, 0·63), FMI (β = 0·17; 95 % CI 0·03, 0·30), android-to-gynoid ratio (β = 0·01; 95 % CI 0·004, 0·02) and VAT (β = 0·09; 95 % CI 0·02, 0·16), but not with total bone density (β = 0·001; 95 % CI –0·003, 0·006) and content (β = 7·13; 95 % CI –4·19, 18·46). Direct association with ASMI was also detected, but lost statistical significance when participants whose mothers were underweight were excluded.Conclusions:Maternal pre-pregnancy BMI was directly associated with offspring general and visceral adiposity but seems not to be associated with bone mass. Results reinforce importance of avoiding excess of maternal adiposity, as an attempt to break the vicious cycle of obesity transmission.

Little is known about the long-term effect of breastfeeding on dietary habits. We examined the association between breastfeeding duration and adherence to current dietary patterns of young women. This was a cross-sectional analysis of 587 healthy women aged ≤45 years, undergraduates or nutrition graduates. Maternal characteristics and breastfeeding duration [2. The four dietary patterns identified (Processed, Prudent, Brazilian and Lacto-vegetarian) explained 27% of diet variance. Women breastfed for Prudent pattern (odds ratio (OR) = 0.53, p = 0.04). Breastfeeding was not associated with the other patterns. Maternal pre-pregnancy BMI was directly associated with moderate-to-high adherence to the Processed pattern (OR = 2.01, p = 0.03) and inversely to the Prudent pattern (OR = 0.52, p = 0.02). Higher adherence to the Brazilian pattern was associated with proxies of low socioeconomic status and the Lacto-vegetarian pattern with the opposite. Confirmation in prospective studies of the association found in this study between breastfeeding with the Prudent pattern in adult offspring could suggest that early feeding practices influence long-term dietary habits, which could then affect the risk of nutrition-related diseases.

BACKGROUND/OBJECTIVES We investigated if breastfeeding duration and current dietary patterns (DP) were associated with glucose and lipid metabolism biomarkers in women from the Nutritionist's Health Study. SUBJECTS/METHODS This is a cross-sectional analysis of 200 healthy undergraduates and nutrition graduates aged ≤45 years. Total [

Due to immunomodulatory properties, vitamin D status has been implicated in several diseases beyond the skeletal disorders. There is evidence that its deficiency deteriorates the gut barrier favoring translocation of endotoxins into the circulation and systemic inflammation. Few studies investigated whether the relationship between vitamin D status and metabolic disorders would be mediated by the gut microbiota composition.We examined the association between vitamin D intake and circulating levels of 25(OH)D with gut microbiota composition, inflammatory markers and biochemical profile in healthy individuals.In this cross-sectional analysis, 150 young healthy adults were stratified into tertiles of intake and concentrations of vitamin D and their clinical and inflammatory profiles were compared. The DESeq2 was used for comparisons of microbiota composition and the log2 fold changes (log2FC) represented the comparison against the reference level. The association between 25(OH)D and fecal microbiota (16S rRNA sequencing, V4 region) was tested by multiple linear regression.Vitamin D intake was associated with its concentration (r=0.220, p=0.008). There were no significant differences in clinical and inflammatory variables across tertiles of intake. However, lipopolysaccharides increased with the reduction of 25(OH)D (p-trend0.05). Prevotella was more abundant (log2FC 1.67, p0.01), while Haemophilus and Veillonella were less abundant (log2FC -2.92 and -1.46, p0.01, respectively) in the subset with the highest vitamin D intake (reference) than that observed in the other subset (first plus second tertiles). PCR (r=-0.170, p=0.039), E-selectin (r=-0.220, p=0.007) and abundances of Coprococcus (r=-0.215, p=0.008) and Bifdobacterium (r=-0.269, p=0.001) were inversely correlated with 25(OH)D. After adjusting for age, sex, season and BMI, 25(OH)D maintained inversely associated with Coprococcus (β=-9.414, p=0.045) and Bifdobacterium (β=-1.881, p=0.051), but significance disappeared following the addition of inflammatory markers in the regression models.The role of vitamin D in the maintenance of immune homeostasis seems to occur in part by interacting with the gut microbiota. The attenuation of association of bacterial genera by inflammatory markers suggests that inflammation participate in part in the relationship between the gut microbiota and vitamin D concentration. Studies with appropriate design are necessary to address hypothesis raised in the current study.

Introduction Non-communicable chronic diseases (NCCDs) represent a burden for public health. Alongside the established cardiometabolic risk factors such as high blood pressure and disorders of glucose and lipid metabolism, living habits and nutritional status at different stages of life are seen as contributors to this scenario. Gut microbiota composition and subclinical inflammation have been pointed out as underlying mechanisms of NCCDs. Studies involving health professionals have brought relevant contributions to the knowledge about risk factors. Technological advances facilitate data collection and analysis for big samples. A web-based survey addressed to collect data from a cohort study, which is able to identify NCCDs risk factors, is highly desirable. The objective of the Brazilian Nutritionists’ Health Study (NutriHS) is to gather online information on early life events, daily habits, emergent cardiometabolic risk factors and health outcomes of a specific subset of the Brazilian population. Methods and analysis NutriHS, developed at the School of Public Health—University of Sao Paulo, Brazil, is a research initiative that enrols undergraduates of nutrition courses from Brazilian universities and graduated volunteers. A web-based self-administered system was designed to collect health-related data. After fulfilling online questionnaires (socioeconomic, early life events and lifestyle data), participants are invited to a clinical visit for physical examination and laboratory procedures (blood sampling, faeces collection and body composition). At a 3-year interval, they will be invited to repeat similar procedures. Ethics and dissemination The NutriHS research protocol was approved by the Institutional Ethics Committee and is providing promising data which contribute to the understanding of pathophysiological links between early life events, body composition, gut microbiota, and inflammatory and metabolic risk profile. The combination of a friendly tool with the innovative purposes of NutriHS offers a remarkable resource for testing hypotheses about mechanisms of nutrition-related diseases and further planning of preventive programmes in public health.

Objectives Associations of leisure-time physical activity (LTPA), commuting and total physical activity with inflammatory markers, insulin resistance and metabolic profile in individuals at high cardiometabolic risk were investigated. Design This was a cross-sectional study. Methods A total of 193 prediabetic adults were compared according to physical activity levels measured by the international physical activity questionnaire; p for trend and logistic regression was employed. Results The most active subset showed lower BMI and abdominal circumference, reaching significance only for LTPA (p for trend = 0.02). Lipid profile improved with increased physical activity levels. Interleukin-6 decreased with increased total physical activity and LTPA (p for trend = 0.02 and 0.03, respectively), while adiponectin increased in more active subsets for LTPA (p for trend = 0.03). Elevation in adjusted OR for hypercholesterolemia was significant for lower LTPA durations (p for trend = 0.04). High apolipoprotein B/apolipoprotein A ratio was inversely associated with LTPA, commuting and total physical activity. Increase in adjusted OR for insulin resistance was found from the highest to the lowest category of LTPA (p for trend = 0.04) but significance disappeared after adjustments for BMI and energy intake. No association of increased C-reactive protein with physical activity domains was observed. Conclusions In general, the associations of LTPA, but not commuting or total physical activity, with markers of cardiometabolic risk reinforces the importance of initiatives to increase this domain in programs for the prevention of lifestyle-related diseases.

The e-NutriHS is a web-based system developed to gather online information on health of a cohort of college students and graduates in nutrition. It consists of six validated and internationally recognized questionnaires regarding demographic and socioeconomic data, dietary habits, physical activity level, alcohol and tobacco use, anti-fat attitudes and personal and family histories. Our software and respective database is hosted in the School of Public Health server and is based on free programming languages. An e-NutriHS prototype was created preceding online deployment. An improved version of the website was released based on 20 volunteers' opinions. A total of 503 users were registered. Considering that web-based systems produce reliable data, are easy to use, less costly and are less time-consuming, we conclude that our experience deserves to be shared, particularly with middle income economy countries.

Objective This study aimed to compare the effects of two lifestyle intervention programs for type 2 diabetes mellitus (T2DM) prevention – traditional or interdisciplinary psychoeducation-based intervention – in daily habits and cardiometabolic risk factors and investigate the role of the psychoeducational approach for the retention of individuals in the program. Subjects and methods Between 2008 and 2010, in a public health service, 183 pre-diabetic individuals were allocated to two 18-month interventions involving diet and physical activity. Physical activity, diet, quality of life (QOL) and depression and biochemical measurements were obtained. Linear mixed-effect models were used to assess the effect of the interventions. A student t test was used to compare dropouts versus non-dropouts. Results Improvements in energy intake and physical activity were greater in the interdisciplinary than the traditional intervention. A decrease in fat mass and blood pressure was more pronounced with interdisciplinary intervention. Dropouts from the traditional intervention only had higher BMI and lower fiber intake and QOL than non-dropouts. Conclusion The interdisciplinary psychoeducation-based intervention revealed useful for reducing cardiometabolic risk and retaining individuals with worse health profiles. This approach represents a feasible strategy for motivating high-risk individuals to adopt a long-term healthy lifestyle.

We investigated whether diet quality was associated with leisure-time physical activity (LTPA) and television viewing and the associations of these variables with traditional cardiovascular risk factors and novel biomarkers in individuals at cardiometabolic risk.A total of 193 prediabetic adults (63.7% women, mean age 54.1 years), screened for a diabetes prevention program in Brazil, participated in this cross-sectional study. Clinical data and blood samples were collected for several determinations. Twenty-four-hour recalls were used to calculate the Healthy Eating Index (HEI) adapted to Brazilian dietary habits and the International Physical Activity Questionnaire to assess physical activity level. Analysis of covariance with adjustments for age and body mass index (BMI) was employed to test associations across categories of LTPA and television viewing.Stratifying according to LTPA categories, the most active subset (≥150 minutes/week) showed better HEI scores after adjustments (64.6 ± 11.0, 65.1 ± 10.3, and 68.6 ± 10.8, p = 0.02) and significant higher values of dark green and orange vegetables but not of whole grains (p = 0.06). Active individuals had lower BMI, waist circumference, inflammatory markers, and better insulin sensitivity (p0.05). Individuals at the highest category of television viewing had higher age-adjusted BMI (32.0 ± 6.2, 30.7 ± 6.0, and 28.8 ± 4.7 hours/week; p = 0.01) than the others. Time watching television was inversely associated with homeostasis model assessment (HOMA-IR) and C-reactive protein (CRP; p0.01) after adjustments but not with lipids and HEI score. Comparisons of individuals with healthy habits (better diet and higher physical activity [PA]), with those with unhealthy habits revealing better anthropometric and cardiometabolic profiles in the former group.Diet quality assessed by the HEI adapted for Brazilian eating habits attained significance in differentiating more active from inactive at-risk individuals during leisure time. Time watching television, as a surrogate of sedentary behavior, is not useful to detect unhealthy diet quality. LTPA is indicative of better cardiometabolic profile reflected by lipid and inflammatory markers and index of insulin resistance.