scholarly journals Maternal smoking during pregnancy and offspring body composition in adulthood: Results from two birth cohort studies

BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e023852 ◽  
Author(s):  
Elma Izze da Silva Magalhães ◽  
Natália Peixoto Lima ◽  
Ana Maria Baptista Menezes ◽  
Helen Gonçalves ◽  
Fernando C Wehrmeister ◽  
...  
Keyword(s):  
Body Composition ◽  
Waist Circumference ◽  
Fat Mass ◽  
Maternal Smoking ◽  
Height Ratio ◽  
Fat Mass Index ◽  
Smoking During Pregnancy ◽  
Gynoid Fat ◽  
Maternal Smoking During Pregnancy ◽  
Waist To Height Ratio

ObjectiveTo evaluate the association of maternal smoking during pregnancy with offspring body composition in adulthood and explore the causality of this association.DesignBirth cohort.SettingPopulation-based study in Pelotas, Brazil.ParticipantsAll newborn infants in the city’s hospitals were enrolled in 1982 and 1993. At a mean age of 30.2 and 22.6 years, the 1982 and 1993 cohorts, respectively, followed the subjects and 7222 subjects were evaluated.Primary outcome measuresBody mass index (BMI), fat mass index, android to gynoid fat ratio, waist circumference, waist to height ratio, lean mass index and height.ResultsPrevalence of maternal smoking during pregnancy was 35.1% and 32.6%, in 1982 and 1993 cohorts, respectively. Offspring of smoking mothers showed higher mean BMI (β: 0.84; 95% CI: 0.55 to 1.12 kg/m2), fat mass index (β: 0.44; 95% CI: 0.23 to 0.64 kg/m2), android to gynoid fat ratio (β: 0.016; 95% CI: 0.010 to 0.023), waist circumference (β: 1.74; 95% CI: 1.15 to 2.33 cm), waist to height ratio (β: 0.013; 95% CI: 0.010 to 0.017) and lean mass index (β: 0.33; 95% CI: 0.24 to 0.42 kg/m2), whereas height was lower (β: −0.95; −1.26 to −0.65). Weight gain in the first 2 years captured most of the association of maternal smoking with BMI (96.2%), waist circumference (86.1%) and fat mass index (71.7%).ConclusionsMaternal smoking in pregnancy was associated with offspring body composition measures in adulthood.

scholarly journals Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3–7 years

2014 ◽  
Vol 33 (2) ◽  
pp. 311-315 ◽  
Author(s):  
Anna Sijtsma ◽  
Gianni Bocca ◽  
Carianne L'Abée ◽  
Eryn T. Liem ◽  
Pieter J.J. Sauer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Waist Circumference ◽  
Fat Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Height Ratio ◽  
Waist To Height Ratio

scholarly journals Maternal smoking during pregnancy and subcutaneous fat mass in early childhood. The Generation R Study

2011 ◽  
Vol 26 (4) ◽  
pp. 295-304 ◽  
Author(s):  
Büşra Durmuş ◽  
Lamise Ay ◽  
Anita C. S. Hokken-Koelega ◽  
Hein Raat ◽  
Albert Hofman ◽  
...  
Keyword(s):  
Early Childhood ◽  
Fat Mass ◽  
Maternal Smoking ◽  
Subcutaneous Fat ◽  
Smoking During Pregnancy ◽  
Maternal Smoking During Pregnancy

scholarly journals Longitudinal changes in body composition and waist circumference by self-reported levels of physical activity in leisure among adolescents: the Tromsø study, Fit Futures

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Nils Abel Aars ◽  
Bjarne K. Jacobsen ◽  
Bente Morseth ◽  
Nina Emaus ◽  
Sameline Grimsgaard
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Waist Circumference ◽  
Fat Mass ◽  
Lean Mass ◽  
Leisure Time ◽  
Leisure Time Physical Activity ◽  
First Year ◽  
Fat Mass Index

Abstract Background It is not clear how physical activity affects body composition in adolescents. Physical activity levels are often reduced during this period, and the relative proportion of body fat mass and lean mass undergo natural changes in growing adolescents. We aimed to examine whether self-reported physical activity in leisure time at baseline or change in activity during follow-up affect changes in four measures of body composition; body mass index (kg/m2), waist circumference, fat mass index (fat mass in kg/m2) and lean mass index (lean mass in kg/m2). Methods We used data from the Tromsø Study Fit Futures, which invited all first year students in upper secondary high school in two municipalities in northern Norway in 2010–2011. They were reexamined in 2012–2013. Longitudinal data was available for 292 boys and 354 girls. We used multiple linear regression analyses to assess whether self-reported level of physical activity in leisure time at baseline predicted changes in body composition, and analysis of covariance to assess the effects of change in level of activity during follow-up on change in body composition. All analyses were performed sex-specific, and a p-value of < 0.05 was considered statistically significant. Results There were no associations between self-reported leisure time physical activity in the first year of upper secondary high school and changes in any of the considered measure of body composition after 2 years of follow up, with the exception of waist circumference in boys (p = 0.05). In boys, change in fat mass index differed significantly between groups of activity change (p < 0.01), with boys adopting activity or remaining physically active having less increase in fat mass index than the consistently inactive. In girls, change in lean mass index differed significantly between groups of activity change (p = 0.04), with girls adopting physical activity having the highest increase. Conclusions Self-reported leisure time physical activity does not predict changes in body composition in adolescents after 2 years of follow up. Change in the level of physical activity is associated with change in fat mass index in boys and lean mass index in girls.

scholarly journals Body composition: population epidemiology and concordance in Australian children aged 11–12 years and their parents

BMJ Open ◽  
2019 ◽  
Vol 9 (Suppl 3) ◽  
pp. 95-105 ◽  
Author(s):  
Susan A Clifford ◽  
Alanna N Gillespie ◽  
Timothy Olds ◽  
Anneke C Grobler ◽  
Melissa Wake
Keyword(s):  
Body Composition ◽  
Waist Circumference ◽  
Body Fat ◽  
Correlation Coefficients ◽  
Home Visits ◽  
Overweight And Obesity ◽  
Height Ratio ◽  
Partial Correlations ◽  
Waist To Height Ratio ◽  
Parent Child

ObjectivesOverweight and obesity remain at historically high levels, cluster within families and are established risk factors for multiple diseases. We describe the epidemiology and cross-generational concordance of body composition among Australian children aged 11–12 years and their parents.DesignThe population-based cross-sectional Child Health CheckPoint study, nested within the Longitudinal Study of Australian Children (LSAC).SettingAssessment centres in seven major Australian cities and eight regional cities, or home visits; February 2015–March 2016.ParticipantsOf all participating CheckPoint families (n=1874), body composition data were available for 1872 children (49% girls) and 1852 parents (mean age 43.7 years; 88% mothers), including 1830 biological parent-child pairs.MeasuresHeight, weight, body mass index (BMI), waist circumference and waist-to-height ratio for all participants; body fat and fat-free mass by four-limb bioimpedence analysis (BIA) at assessment centres, or body fat percentage by two-limb BIA at home visits. Analysis: parent-child concordance was assessed using (i) Pearson’s correlation coefficients, and (ii) partial correlation coefficients adjusted for age, sex and socioeconomic disadvantage. Survey weights and methods accounted for LSAC’s complex sample design.Results20.7% of children were overweight and 6.2% obese, as were 33.5% and 31.6% of parents. Boys and girls showed similar distributions for all body composition measures but, despite similar BMI and waist-to-height ratio, mothers had higher proportions of total and truncal fat than fathers. Parent-child partial correlations were greatest for height (0.37, 95% CI 0.33 to 0.42). Other anthropometric and fat/lean measures showed strikingly similar partial correlations, ranging from 0.25 (95% CI 0.20 to 0.29) for waist circumference to 0.30 (95% CI 0.25 to 0.34) for fat-free percentage. Whole-sample and sex-specific percentile values are provided for all measures.ConclusionsExcess adiposity remains prevalent in Australian children and parents. Moderate cross-generational concordance across all measures of leanness and adiposity is already evident by late childhood.

Effects of maternal smoking during pregnancy on body composition in offspring

2011 ◽  
Vol 53 (6) ◽  
pp. 851-857 ◽  
Author(s):  
Toshihiro Ino ◽  
Tomoyuki Shibuya ◽  
Kota Saito ◽  
Tetsuya Ohtani
Keyword(s):  
Body Composition ◽  
Maternal Smoking ◽  
Smoking During Pregnancy ◽  
Maternal Smoking During Pregnancy

scholarly journals Determinants of Metabolic Syndrome among Malaysian Government Employees

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Chee Huei Phing ◽  
Hazizi Abu Saad ◽  
Barakatun Nisak Mohd Yusof ◽  
Mohd Nasir Mohd Taib
Keyword(s):  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Fat Mass ◽  
Government Agencies ◽  
Body Fat Percentage ◽  
Government Employees ◽  
Fat Percentage ◽  
Height Ratio ◽  
Waist To Hip Ratio ◽  
Waist To Height Ratio

Introduction: The metabolic syndrome comprises a collection of cardiovascular disease risks, which has been demonstrated to predict type 2 diabetes mellitus and cardiovascular disease. Metabolic syndrome is a crucial health concern in Malaysia, with a prevalence of about 42.5% in the general population based on the ‘Harmonized’ definition. The aim of this study was to ascertain the association between socioeconomic status among Malaysian government employees with metabolic syndrome, compared with those without metabolic syndrome. Furthermore, this study also aimed to ascertain the associated obesity indicators for metabolic syndrome among employees—explicitly body mass index, waist circumference, waist-to-hip ratio, body fat percentage, fat mass index, and waist-to-height ratio. Methods: This cross-sectional study was undertaken at government agencies in Putrajaya, Malaysia, via multi-stage random sampling. A total of 675 government employees were randomly sampled from a list of 3,173 government employees working in five government agencies under five geographical areas. Data on socioeconomic status, anthropometric, biochemical, and clinical assessments were collected. Results: Employees who were males had higher metabolic syndrome prevalence compared to their counterparts (p=0.019). In addition, employees aged between 20 to younger than 30 years had lowest metabolic syndrome prevalence (p=0.002). The risk of having metabolic syndrome was almost 10 times more likely in men with a waist-to-hip ratio of ≥0.90 compared to men with a waist-to-hip ratio of <0.90 (p<0.001). Women with a waist-to-hip ratio of ≥0.85 were approximately 33 times more likely to have metabolic syndrome as compared to women with waist-tohip ratios of <0.85 (p<0.001). Men with a waist circumference of ≥90 cm were approximately twice as likely to have metabolic syndrome, compared to men with waist circumferences of <90 cm (p=0.030). The risk of having metabolic syndrome was almost three times more likely in women with a waist circumference of ≥80 cm compared to women with waist circumferences of <80 cm (p<0.001). Furthermore, the risk of having metabolic syndrome was almost five times more likely in women with fat mass indexes in Quartile 4 (≥7.93), compared to women with fat mass indexes in Quartile 1 (<5.25) [p<0.001]. On the other hand, men with waist-to-height ratios of <0.445 were 75% less likely to have metabolic syndrome as compared to men with waist-to-height ratios of ≥0.625 (p=0.020). Women with waist-to-height ratios of 0.445 to <0.525 were 95% less likely to have metabolic syndrome as compared to women with waist-to-height ratios of ≥0.625 (p<0.001). In addition, women with waist-to-height ratios of 0.525 to <0.625 were 77% less likely to have metabolic syndrome as compared to women with waist-to-height ratios of ≥0.625 (p<0.001). Conclusion: Gender and age were associated with metabolic syndrome prevalence. Waist-to-hip ratio, waist circumference, and waist-to-height ratio seems to be the better obesity indicators to predict the presence of metabolic syndrome than body mass index and body fat percentage in both men and women.

scholarly journals Comparison of body composition parameters in the study of the association between body composition and pulmonary function

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Caren Ishikawa ◽  
Marco Antonio Barbieri ◽  
Heloisa Bettiol ◽  
Gabriel Bazo ◽  
Alexandre A. Ferraro ◽  
...  
Keyword(s):  
Body Composition ◽  
Waist Circumference ◽  
Pulmonary Function ◽  
Fat Mass ◽  
Mass Measurement ◽  
Height Ratio ◽  
Cross Sectional ◽  
Bod Pod ◽  
Waist Height Ratio ◽  
Composition Measurements

Abstract Background The excess adiposity, even in the absence of diseases, is responsible for a decline in pulmonary function, which is considered a predictor of mortality and a risk factor for diseases in several epidemiological studies. However, studies on the association between obesity and pulmonary function have found only few associations or inconclusive results. The aim of the study is to evaluate the association between body composition and spirometric parameters, comparing simple obesity measures such as body mass index (BMI) and waist circumference with more precise body composition measurements such as dual-energy X-ray absorptiometry (DXA) and air-displacement plethysmography (BOD POD). Methods This is an observational, cross-sectional study that used data from the 1978/79 Ribeirão Preto birth cohort (São Paulo, Brazil). The study included 1746 participants from the 5th follow-up of the cohort. Linear regressions were calculated to evaluate the association between BMI, waist circumference, waist–height ratio (WHtR), BOD POD- and DXA-measured fat mass percentage, and spirometric parameters FEV1, and FVC. Results For every 1-kg/m2 BMI increase, FVC decreased by 13 ml in males and by 6 ml in females and FEV1 decreased by 11 ml and 5 ml, respectively. Regarding body composition measurements, for a 1% increase in fat mass assessed by BOD POD, FVC decreased by 16 ml in males and by 8 ml in females and FEV1 decreased by 13 ml and 7 ml, respectively. Hence, negative associations between body measurements and FEV1 and FVC were observed in both genders, especially when using the fat mass measurement and were more expressive in men. Conclusion The anthropometric and body composition parameters were negatively associated with the spirometric variables FVC and FEV1. We have also observed that simple measures such as waist-height ratio were sufficient to detect the association of body composition with pulmonary function reduction.

Sign in / Sign up

Export Citation Format

Share Document