Aim: To assess if there is an association between sitting time and obesity among adult Peruvian population, using three different anthropometric measurements. Methods: A secondary analysis using data from a population-based study, the National Household Survey (ENAHO, in Spanish), was conducted enrolling adults aged ≥18 years from the 25 regions of Peru using a multistage random sampling technique. The outcome of interest was obesity, determined by body mass index (BMI > 30 kg/m2), waist circumference (WC > 80 and >90 cm in women and men, respectively) and waist to height ratio (WHR > 0.5); while the exposure was sitting time, measured using the last domain of the International Physical Activity Questionnaire and then categorised in <4 hours/day, 4 to <8 hours/day and 8+ hours/day. Associations were estimated using Poisson regression models, reporting prevalence ratios (PRs) and their respective 95% CI. Results: Data from 8587 subjects were analysed; mean age was 38.4 (SD: 13.5) and 53.6% were females. The prevalence of obesity was 16.3% (95% CI: 15.2–17.5%) by BMI, 58.5% (95% CI: 56.9–60.0%) by WC, and 78.0% (95% CI: 76.5–79.3%) by WHR. In the multivariable model, subjects reporting a sitting time of 8+ hours/day were more likely to be obese than those reporting <4 hours/day according to BMI (PR: 1.38; 95% CI: 1.15–1.65), WC (PR: 1.20; 95% CI: 1.12–1.28) and WHR (PR: 1.05; 95% CI: 1.01–1.10). Conclusions: Subjects with greater sitting time were more likely to be obese, and this association was evident with three different anthropometric indicators. Findings suggest the need of generating public health actions to reduce sedentary behaviour. / Revisión por pares / Revisión por pares

abstract: Most studies that explored the health benefits of interrupting sitting time focused on using different modalities (i.e., comparing walking vs standing breaks)33,36,59. However, experimental studies that directly compare patterns of interrupting sitting time through standing only are needed to advance the field. This study aimed to (i) determine if there is a difference in glucose response between continuous sitting (CS) and two intermittent standing regimes (high frequency, low duration breaks (HFLD) and low frequency, high duration breaks (LFHD)) and (ii) to determine if there is a difference in glucose response between the two strategies (HFLD vs. LFHD). Ten sedentary employees (mean±SD age 46.8±10.6 years; 70% female) with impaired fasting glucose (mean glucose= 109.0±9.8 mg/dL) participated. Eligible participants were invited to three 7.5 hour laboratory visits where they were randomized to perform each study conditions: (i) CS, (ii) HFLD and (iii) LFHD. Standardized meals (breakfast and lunch) were given with each meal providing 33% of the participant’s total daily caloric needs following a typical American diet (50-60% carbohydrates, 25-30% fat, and 10-20% protein). Participants wore an activPAL device to measure compliance with the sit-stand condition and a continuous glucose monitor to measure post-prandial glucose response. Post-prandial mean glucose, incremental area under the curve and mean amplitude glycemic excursion between conditions were evaluated using linear mixed models. Participants demonstrated high compliance with the study condition. The results indicated that the mean glucose of the HFLD condition were significantly lower (p< .01) than the CS condition with mean difference of -7.70 (-11.98, -3.42) mg/dL·3.5h and -5.76 (-9.50, -2.03) mg/dL·7h for lunch and total time, respectively. Furthermore, the mean post-prandial glucose during lunch and total time were significantly lower in the HFLD condition compared to the LFHD condition with mean difference of -9.94 (-14.13, -5.74) mg/dL·3.5h and -6.23 (-9.93, -2.52) mg/dL·7h, respectively. No differences were found between the CS and LFHD conditions. This study provides evidence favoring the use of frequent interruptions in sitting time to improve glycemic control of prediabetic individuals. In contrast, less frequent, although longer bouts of standing resulted in similar post-prandial glucose profile to that of the continuous sitting condition despite total standing time being equal to the LFHD condition. / Dissertation/Thesis / Doctoral Dissertation Physical Activity, Nutrition and Wellness 2019

This cross-sectional investigation of 6,931 U.S. adults examined the relationship between sitting time and insulin resistance. A primary objective was to evaluate how this relationship was mediated by the following variables: age, sex, race, year of assessment, cigarette smoking, physical activity, body mass index (BMI), and waist circumference. Self-reported sitting time, measured in minutes per day, was the exposure variable. Insulin resistance, indexed by the homeostatic model assessment of insulin resistance (HOMA-IR), was the outcome variable. Data were used from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Results showed a strong, positive association between sitting time and insulin resistance after adjusting for age, sex, race, and year of assessment (F = 13.3, p < 0.0001). Further controlling for cigarette smoking and physical activity did not alter the significance of the relationship. Adding BMI to the demographic covariates weakened the relationship but did not nullify it; however, the association was no longer significant after adjusting for differences in waist circumference (F = 1.39, p = 0.2563). Overall, waist circumference was a powerful mediating variable between sitting time and insulin resistance.

Tyrimo problema: Šiuolaikinis mokslas fizinį pajėgumą pripažįsta kaip vieną iš svarbiausių sveikatos rodiklių, kuris turi didelę įtaką prognozuojant sergamumą lėtinėmis ligomis ir jų sukeltą mirtingumą (Lohman et al., 2008). Fizinis pajėgumas gerinamas fizinio aktyvumo pagalba, mažinant fizinį pasyvumą, bei sėdimo laiko trukmę (Adaškevičienė, 1993; Domarkienė ir kt., 2003; Tamošiūnas ir kt., 2003; Lee & Moudon, 2004; Grabauskas ir kt., 2005; Borodulin, 2006; Jankauskienė, 2008; Kallings, 2008; Stessman et al., 2009; Haskell et al., 2009; Renaud et al., 2010; Glazer et al., 2013; Guiney & Machado, 2013). Kol kas moksliniais tyrimais nepagrįsta nuo ko labiau priklauso fizinio pajėgumo rodikliai nuo kasdienio fizinio aktyvumo ar laiko skirto sėdimai veiklai. Tyrimo tikslas – nustatyti 15-18 metų moksleivių fizinio pajėgumo priklausomybė nuo laiko skirto sėdimai veiklai ir fizinio aktyvumo. Tyrimo uždaviniai: 1. Nustatyti ir palyginti 15-18 metų moksleivių laiką skirtą sėdimai veiklai gyvenamosios vietos ir lyties aspektais. 2. Nustatyti ir palyginti 15-18 metų moksleivių fizinį aktyvumą gyvenamosios vietos ir lyties aspektais. 3. Nustatyti ir palyginti 15-18 metų moksleivių fizinį pajėgumą gyvenamosios vietos, lyties, fizinio aktyvumo ir laiko skirto sėdimai veiklai aspektais. 4. Nustatyti 15-18 metų moksleivių fizinio pajėgumo priklausomybę nuo laiko skirto sėdimai veiklai ir fizinio aktyvumo. Hipotezės: 1. Mieste gyvenančių, bei vyriškos lyties 15-18 metų moksleivių... [toliau žr. visą tekstą] / Problem of research: Modern science considers a physical fitness as one of the most important health indicators, which has a great impact on prediction of incidence of chronic diseases and mortality caused by them (Lohman et al., 2008). A physical fitness is improved by physical activity, by reducing a physical inactivity and duration of sitting time (Adaškevičienė, 1993; Domarkienė et al., 2003; Tamošiūnas et al., 2003; Lee & Moudon, 2004; Grabauskas et al., 2005; Borodulin, 2006; Jankauskienė, 2008; Kallings, 2008; Stessman et al., 2009; Haskell et al., 2009; Renaud et al., 2010; Glazer et al., 2013; Guiney & Machado, 2013). Scientific research has not grounded yet what has a higher impact on physical fitness indicators: daily physical activity or sitting time. Aim of research – to determine the influence of sitting time and physical activity on physical fitness of 15-18 year-old pupils. Tasks of research: 1. To determine and compare the duration of sitting time of 15-18 year-old pupils in respect of place of residence and gender. 2. To determine and compare a physical activity of 15-18 year-old pupils in respect of place of residence and gender. 3. To determine and compare a physical fitness of 15-18 year-old pupils in respect of place of residence, gender, physical activity and sitting time. 4. To determine of 15-18 year-old pupils the influence of physical fitness on sitting time and physical activity. Hypotheses: 1. The duration of sitting time of male 15-18 age-old... [to full text]

The aim of the diploma thesis is to decide on the basis of pilot questionnaire results whether the business plan of the author is viable and long-term financially sustainable.

Submitted by PPG Pediatria e Sa?de da Crian?a (pediatria-pg@pucrs.br) on 2018-05-21T13:54:31Z No. of bitstreams: 1 Tese_Eduardo_Mundstock Versao Final.pdf: 1978473 bytes, checksum: 4be8f1b605788a6e254263a3c448a60f (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2018-06-06T18:34:35Z (GMT) No. of bitstreams: 1 Tese_Eduardo_Mundstock Versao Final.pdf: 1978473 bytes, checksum: 4be8f1b605788a6e254263a3c448a60f (MD5) / Made available in DSpace on 2018-06-06T18:36:11Z (GMT). No. of bitstreams: 1 Tese_Eduardo_Mundstock Versao Final.pdf: 1978473 bytes, checksum: 4be8f1b605788a6e254263a3c448a60f (MD5) Previous issue date: 2018-03-15 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / Introduction: The phase angle is considered an important prognostic marker because it reflects cellular health. Inadequate physical activity and sitting time are associated with a significant number of chronic noncommunicable diseases. Recent studies suggest that these two factors may be associated with phase angle values. Objective: to verify the association of phase angle with physical activity Methodology: the thesis will present two articles: a systematic review with metaanalysis and a cross-section article. Meta-analysis: We searched the following databases: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, SciELO, LILACS, SPORTDiscus, Scopus and Web of Science. Two reviewers independently assessed eligibility criteria and bias risks. The results were synthesized using random effects models. The association between physical activity and phase angle was evaluated considering the design of the study. Cross-sectional study: individuals over 11 years of age, of both sexes, who met bioimpedance assessment criteria and without diagnosis of chronic disease, were invited to participate in the study. The phase angle evaluation was performed using Ottoboni's Biospace equipment, model InBodyS10. Physical activity level and sitting time were assessed using the International Physical Activity Questionnaire (IPAQ). The association between the phase angle and the predictor variables was evaluated using a univariate and multivariate generalized linear model (GLM). All variables with a value of p <0.20 were included in the multivariate model. In the final model, only the variables with p <0.05 were included. Results: Systematic Review: Nine studies, totaling 575 participants, were included in the meta-analysis. The results of cross-sectional studies indicate that the active subjects presented a mean value of higher phase angle when compared to controls (DM = 0.70, 95% CI 0.48 to 0.92, P <0.001), with low heterogeneity (I2 = 0%, P = 0.619). In the crosssectional analysis, the differences between health status and type of physical activity evaluation were not significant (P = 0.332, P <0.253). In longitudinal studies (clinical trial and follow-up), mean values of final phase angle increased significantly compared to baseline (DM = 0.30, 95% CI 0.11 to 0.49, P <0.001), with low heterogeneity (I2 = 13%, P = 0.331). The differences were not significant in relation to the state of health and the type of longitudinal study (clinical trials or follow-up studies) (P = 0.900; 0.989). Evidence of publication bias was not observed, and the overall risk of bias was moderate to high. Cross-sectional article: 1228 subjects were included. The multivariate generalized linear model showed that both physical activity (? = 0.164, 95% CI 0.071 to 0.256, P = 0.001) and sitting time (? = 0.152, 95% CI 0.063 to 0, 242, P = 0.001) were determinant for the phase angle. As well as sex, body mass index and age, also remained associated with phase angle (? = -0.890, 95%CI -0.975 to -0.806, P <0.001; ? = 0.037, 95%CI 0.029 to 0,045, p <0.001 e; ? = -0.006, 95%CI -0.008 to -0.003 P<0.001, respectively). Conclusion: The results of the systematic review and the cross-sectional article suggest an association of phase angle with physical activity and sitting time. Among the main factors that may explain the positive effect of physical activity on the phase angle are the increase in cell membrane integrity and the change in intracellular content, these factors reflecting the cellular health and, consequently, the health of the individual. / Introdu??o: O ?ngulo de fase est? sendo considerado um importante marcador progn?stico, pois reflete a sa?de celular. A atividade f?sica inadequada e o tempo sentado est?o associados a um n?mero importante de doen?as cr?nicas n?o transmiss?veis. Estudos recentes sugerem que esses dois fatores podem estar associados com os valores do ?ngulo de fase. Objetivo: verificar a associa??o do ?ngulo de fase com a atividade f?sica. Metodologia: a tese ir? apresentar dois artigos: uma revis?o sistem?tica com metan?lise e um artigo transversal. Metan?lise: foram realizadas buscas nas seguintes bases de dados: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, SciELO, LILACS, SPORTDiscus, Scopus e Web of Science. Dois revisores avaliaram independentemente os crit?rios de elegibilidade e o risco de vi?s. Os resultados foram sintetizados mediante modelos de efeitos aleat?rios. A associa??o entre atividade f?sica e ?ngulo de fase foi avaliada considerando o desenho do estudo. Artigo transversal: os indiv?duos com mais de 11 anos de idade, de ambos os sexos, que atendiam aos crit?rios de avalia??o da bioimped?ncia e sem diagn?stico de doen?a cr?nica, foram convidados a participar do estudo. A avalia??o do ?ngulo de fase foi realizada usando o equipamento Biospace, modelo InBodyS10, da Ottoboni. O n?vel de atividade f?sica e o tempo sentado foram avaliados com o question?rio internacional de atividade f?sica (IPAQ). A associa??o entre o ?ngulo de fase e as vari?veis preditoras foram avaliadas utilizando um modelo linear generalizado univari?vel e multivari?vel (MLG). Todas as vari?veis com um valor de p <0,20 foram inclu?das no modelo multivari?vel. No modelo final, apenas as vari?veis com p <0,05 foram inclu?das. Resultados: Revis?o Sistem?tica: Nove estudos, totalizando 575 participantes, foram inclu?dos na metan?lise. Os resultados dos estudos transversais indicam que os sujeitos ativos apresentaram um valor m?dio de ?ngulo de fase superior quando comparado aos controles (DM = 0,70; IC 95%: 0,48 a 0,92, P <0,001), com baixa heterogeneidade (I2 = 0%; P = 0,619). Na an?lise transversal, as diferen?as entre o estado de sa?de e o tipo de avalia??o da atividade f?sica n?o foram significativas (P = 0,332; P <0,253). Nos estudos longitudinais (ensaio cl?nico e acompanhamento), os valores m?dios do ?ngulo de fase finais aumentaram significativamente comparando com os valores iniciais (DM = 0,30; IC 95%: 0,11 a 0,49, P <0,001), com heterogeneidade baixa (I2 = 13%, P = 0,3314). As diferen?as n?o foram significativas, em rela??o ao estado de sa?de e ao tipo de estudo longitudinal (ensaios cl?nicos ou estudos de seguimento) (P = 0,900; 0,989). N?o encontramos evid?ncia de vi?s de publica??o e o risco geral de vieses foi de moderado a alto. Artigo transversal: foram inclu?dos 1228 indiv?duos. O modelo linear generalizado multivari?vel mostrou que tanto a atividade f?sica (? = 0,164, IC95% 0,071 a 0,256, P= 0,001) como o tempo sentado (? = 0,152, IC95% 0,063 a 0,242, P= 0,001) foram determinantes para o ?ngulo de fase. Assim como o sexo, o ?ndice de massa corporal e a idade tamb?m permaneceram associados com o ?ngulo de fase (? = -0,890, IC95% -0,975 a -0,806, P <0,001; ? = 0,037, IC95% 0,029 a 0,045, p <0,001 e; ? = -0,006, IC95% - 0,008 a -0,003 P<0,001, respectivamente). Conclus?o: Os resultados da revis?o sistem?tica e do artigo transversal sugerem uma associa??o do ?ngulo de fase com a atividade f?sica e com o tempo sentado. Entre os principais fatores que podem explicar o efeito positivo da atividade f?sica sobre o ?ngulo de fase est?o o aumento da integridade da membrana celular e a mudan?a no conte?do intracelular, fatores estes que refletem a sa?de celular e, consequentemente, a sa?de do indiv?duo.