Submitted by PPG Medicina e Ci?ncias da Sa?de (medicina-pg@pucrs.br) on 2018-01-26T13:27:51Z No. of bitstreams: 1 RAFAELA_SIVIERO_CARON_LIENERT_TES.pdf: 9419976 bytes, checksum: f123a0ee4d12fb6dd455c726f40ece4f (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2018-01-31T13:24:29Z (GMT) No. of bitstreams: 1 RAFAELA_SIVIERO_CARON_LIENERT_TES.pdf: 9419976 bytes, checksum: f123a0ee4d12fb6dd455c726f40ece4f (MD5) / Made available in DSpace on 2018-01-31T13:29:24Z (GMT). No. of bitstreams: 1 RAFAELA_SIVIERO_CARON_LIENERT_TES.pdf: 9419976 bytes, checksum: f123a0ee4d12fb6dd455c726f40ece4f (MD5) Previous issue date: 2017-11-21 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / Background: During 24 hours of peritoneal dialysis (PD), it is estimated that 100 to 300g of the glucose are absorbed, which can generate metabolic changes and nutritional disorders. Objective: To study pathophysiological and clinical aspects related to nutritional status of PD patients. Materials and Methods: Observational study of PD patients evaluating body composition by bioimpedance (Body Composition Monitor; Fresenius Medical Care), examining peritoneal membrane characteristics, measuring biochemical parameters and using inductively coupled plasma mass spectrometer to measure serum concentrations of copper (63Cu), zinc (66Zn), selenium (78Se), chromium (52Cr) and nickel (58Ni). Results for each paper: Article 1: After 1y on PD, 50.6% had dry weight (DW) gain, 41.2% showed lean tissue mass (LTM) loss, and 65.9% presented fat mass (FM) gain and significant differences in DW, body mass index (BMI), adipose tissue mass (ATM), FM and fat tissue index (FTI) were disclosed. Patients with lower dialysate-to-plasma creatinine ratio showed FM gain. We observed a higher percentage of nonfast transporters in DW gain when comparing with no gain. Artigo 2: No differences were disclosed regarding body composition changes between PD modalities (CAPD and APD). Article 3: At baseline 29.9% of the patients were classified as having undernutrition (Lean Tissue Index (LTI) percentile <10th), 55.5% as obese (FTI percentile >90th), 7.9% as having fat tissue undernutrition (FTI percentile <10th) and 23.8% had LTI undernutrition and obesity in combination. The cumulative survival rates were 92%, 83%, 69%, 67% and 60% (12, 24, 36, 48 and 60 months, respectively). Kaplan-Meier survival and Cox regressions analysis showed that only PhA bellow 5? had an impact on mortality during the follow-up, even after adjusting for age, gender and diabetes. Artigo 4: Values below references were disclosed for Zn (5.8 ? 1.1 ?mol/L) in 100%; Cu (15.7 ? 5.0 ?mol/L) in 20.7%; Se (0.59 ? 0.22 ?mol/L) in 75.9%. Values above references were disclosed for Cr (0.29 ? 0.08 ?mol/L) in 86.3% and Ni (0.21 (0.17 ? 0.26) ?mol/L) in 96.6%. We observed significant positive corretations between Cu and DW (r=0.407, P=0.028), BMI (r=0.460, P=0.012) and FTI (r=0.370, P0.048). Zn was positivily correlated to albumin (r=0.527, P=0.003) and negatively correlated with OH (r=-0.394, P=0.034) and extracellular water (%ECW) (r=-0.466, P=0.014). Se had a positive correlation with serum albumin (r=0.515, P=0.005) and total cholesterol (r=0.443, P=0.021), but a negative correlation with %ECW (r=-0.404, P=0.041) and extracellular water/intracellular water (r=0.398, P0.036). Ni was negatively correlated to dry weight (r=-0.377, P0.044). Cu/Zn ratio was only correlated to BMI (r=0.376, P=0.044). Conclusions: Body composition changes over PD treatment and it does not seems to be related to the exposure of glucose or to the PD modality, however, it seems to be related to patients with slower peritoneal transports at the beginning of the treatment. Detailed analysis of body composition can generate more accurate data of nutritional status. The use of the phase angle as a marker of nutritional status is suggested and further studies are needed to better understand the association of serum microelements and body composition in this population. / Introdu??o: Durante 24 horas de Di?lise Peritoneal (DP), estima-se que cerca de 100 a 300g da glicose s?o absorvidas, o que pode gerar altera??es metab?licas e no estado nutricional. Objetivos: Estudar aspectos fisiopatol?gicos e cl?nicos relacionados ao estado nutricional de pacientes em DP. Materiais e m?todos: Estudo observacional de pacientes em DP com an?lise da composi??o corporal atrav?s da bioimped?ncia espectrosc?pica (Body Composition Monitor, Fresenius Medical Care), avalia??o da caracter?stica de transporte peritoneal, exames bioqu?micos e concentra??o s?rica de cobre (63Cu), zinco (66Zn), sel?nio (78Se), cromo (52Cr) e n?quel (58Ni) atrav?s de espectometria de massa com plasma indutivamente acoplado. Resultados por artigo: Artigo 1: Ap?s 1 ano de DP, 50,6% ganharam peso, 41,2% perderam massa magra, 65,9% aumentaram massa gorda, sendo encontrado aumento significativo para peso, ?ndice de massa corporal (IMC), tecido adiposo e ?ndice de massa gorda. Os pacientes que ganharam peso predominantemente apresentavam baixo transporte peritoneal. Artigo 2: A modifica??o da composi??o corporal encontrada n?o foi diferente entre modalidades de DP, ambulatorial cont?nua (CAPD) e automatizada (APD). Artigo 3: No in?cio da DP, os pacientes foram classificados em: 29,9% desnutridos (massa magra percentil <10), 55,5% obesos (massa gorda percentil >90) e 7,9% como desnutridos por massa gorda (massa gorda percentil <10) e 23,8% desnutri??o e obesidade em combina??o. A sobrevida cumulativa foi de 92%, 83%, 69%, 67% e 60% (12, 24, 36, 48 e 60 meses, respectivamente). O ?ngulo de fase (abaixo de 5?) possui impacto na mortalidade, inclusive ap?s ajuste para idade, sexo e diabetes. Artigo 4: Valores abaixo da refer?ncia foram observados para Zn (5,8 ? 1,1 ?mol/L) em 100%; Cu (15,7 ? 5,0 ?mol/L) em 20,7%; Se (0,59 ? 0,22 ?mol/L) em 75,9%. Valores acima do recomendado foram encontrados para Cr (0,29 ? 0,08 ?mol/L) em 86,3% e Ni (0,21 (0.17 ? 0.26) ?mol/L em 96,6%. Foi observada correla??o positiva entre Cu e peso seco (r=0,407, P=0,028), IMC (r=0,460, P=0,012) e ?ndice de massa gorda (r=0,370, P0,048). Zn apresentou correla??o positiva com albumina (r=0,527, P=0,003) e negativa com hiperhidrata??o (r=-0,394, P=0,034) e percentual de ?gua extracelular (r=-0,466, P=0,014). Se apresentou correla??o positiva com albumina (r=0,515, P=0,005) e colesterol total (r=0,443, P=0,021), mas negativa com percentual de ?gua extracelular (r=-0,404, P=0,041) e ?gua extracelular/?gua intracelular (r=0,398, P0,036). Ni correlacionou-se negativamente com peso seco (r=-0,377, P0,044). Cu/Zn apresentou correla??o com IMC (r=0,376, P=0,044). Conclus?es: A composi??o corporal de pacientes em DP se modifica ao longo do tratamento, o que n?o parece estar relacionado a exposi??o a glicose ou ? modalidade de DP, por?m, as altera??es parecem estar relacionadas ? pacientes que apresentam transportes peritoneais mais lentos no in?cio da terapia. A an?lise da composi??o corporal de forma detalhada pode gerar dados mais precisos de avalia??o nutricional. Sugere-se o uso do ?ngulo de fase como um marcador de estado nutricional e mais estudos s?o necess?rios para o melhor entendimento da associa??o de microelementos s?ricos e composi??o corporal nesta popula??o.

Submitted by PPG Gerontologia Biom?dica (geronbio@pucrs.br) on 2018-08-08T14:17:43Z No. of bitstreams: 1 SAFIAN_CLAUDIA_ALINE_DIS.pdf: 2337155 bytes, checksum: 87ead8f6373020e0552079ac1ee57eef (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-08-09T12:39:31Z (GMT) No. of bitstreams: 1 SAFIAN_CLAUDIA_ALINE_DIS.pdf: 2337155 bytes, checksum: 87ead8f6373020e0552079ac1ee57eef (MD5) / Made available in DSpace on 2018-08-09T13:06:32Z (GMT). No. of bitstreams: 1 SAFIAN_CLAUDIA_ALINE_DIS.pdf: 2337155 bytes, checksum: 87ead8f6373020e0552079ac1ee57eef (MD5) Previous issue date: 2018-03-07 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / Introduction: Brazil has undergone considerable changes in the age distribution of its population, with the elderly being responsible for almost 26 million inhabitants. Allied to this reality, is a series of nutritional disorders in this population segment. An important factor related to quality of life and healthy aging is good nutrition throughout life. Objective: To observe the possible relationship between the nutritional status and the body composition of the longevity. Methodology: This is a descriptive, cross-sectional and analytical study, with elderly individuals aged 90 years or older. The instruments used were the Mini Nutritional Assessment to evaluate nutritional status, Anthropometry to evaluate weight, height and BMI, and bioimpedance to evaluate body composition. Results: The sample consisted of 72 elderly individuals, with a mean age of 93.7 years, most female(72%), white (82%) and widowed (64%). Of the total longevity, 19.4% were classified with nutritional risk based on the Mini Nutritional Assessment. All anthropometric parameters presented lower averages among participants with nutritional risk. Regarding the bioimpedance parameters, in general the risk-free individuals presented higher averages of weight, maximum ideal weight, minimum ideal weight, BMI, lean mass, fat mass, percentage of fat mass and minimum percentage of fat mass. Conclusions: It was observed that most of the longevity were classified without nutritional risk based on MAN. The importance of not only nutritional assessment and diet quality in the multiprofessional care of the longevity, but also the presence of a nutritionist was clear, since the measurement of the nutritional risk in the third age requires the joint analysis of the several existing methods for the nutritional evaluation, in order to obtain global diagnosis and accurate analysis of the nutritional status of the longevity. / Introdu??o:O Brasil vem passando por mudan?as consider?veis na distribui??o et?ria da sua popula??o, sendo os idosos respons?veis por quase 26 milh?es de habitantes. Aliada a essa realidade, encontra-se uma s?rie de desordens nutricionais nesse segmento populacional. Um importante fator relacionado ? qualidade de vida e ao envelhecimento sadio ? a boa nutri??o durante toda a vida. Objetivo:Observar a poss?velrela??o entre o estado nutricional e a composi??o corporal de longevos. Metodologia: Trata-se de um estudo descritivo, transversal e anal?tico, com idosos longevos de idade igual ou superior a 90 anos. Os instrumentos utilizados foram a Mini Avalia??o Nutricional (MAN) para avaliar o estado nutricional, Antropometria para avaliar o peso, altura e IMC, e a Bioimped?ncia para avaliar a composi??o corporal.Resultados:A amostra foi composta por 72 idosos longevos, com m?dia de idade de 93,7 anos, a maioria (72%) era mulher, cor branca (82%) e estado civil vi?vo (64%). Do total de longevos, 19,4% foram classificados com risco nutricional com base na Mini Avalia??o Nutricional. Todos os par?metros antropom?tricos apresentaram m?dias menores entre os participantes com risco nutricional. Em rela??o aos par?metros de bioimped?ncia, em geral os indiv?duos sem risco apresentaram maiores m?dias de peso, peso ideal m?ximo, peso ideal m?nimo, IMC, massa magra, massa gorda.Conclus?es:Observou-se que a maioria dos longevos foram classificados sem risco nutricional baseado no MAN. Ficou clara a import?ncia n?o somente da avalia??o nutricional e da qualidade da dieta na aten??o multiprofissional do longevo, mas tamb?m a presen?a de um nutricionista, poisa mensura??o do risco nutricional na terceira idade requer a an?lise conjunta dos diversos m?todos existentes para a avalia??o nutricional, a fim de obter diagn?stico global e an?lise acurada do estado nutricional do longevo.

Submitted by PPG Pediatria e Sa?de da Crian?a (pediatria-pg@pucrs.br) on 2018-09-11T11:29:41Z No. of bitstreams: 1 Tese VFC 09-07-18 Lisi Vers?o Final.pdf: 2404794 bytes, checksum: cc151e819fe2b2d350e28543f9ab9cbf (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-09-12T13:08:07Z (GMT) No. of bitstreams: 1 Tese VFC 09-07-18 Lisi Vers?o Final.pdf: 2404794 bytes, checksum: cc151e819fe2b2d350e28543f9ab9cbf (MD5) / Made available in DSpace on 2018-09-12T13:12:17Z (GMT). No. of bitstreams: 1 Tese VFC 09-07-18 Lisi Vers?o Final.pdf: 2404794 bytes, checksum: cc151e819fe2b2d350e28543f9ab9cbf (MD5) Previous issue date: 2018-06-14 / Introduction: The analysis of body composition is fundamental, since it is associated with the general health of individuals. Objective: To evaluate the association between socioeconomic and clinical variables with body composition in children and adolescents. Methods: Were included for convenience, participants between 5 and 19 years. Socioeconomic and clinical variables were assessed by a standardized questionnaire and corporal bioimpedance by Biospace, model InBodyS10, from Ottoboni. The variables studied were compared in relation to sex by t-test for independent and chi-square samples. The outcome variables (body mass index, skeletal mass, fat free mass and fat percentage )and predictor variables (age, sex, race, place of residence, father's schooling, physical activity, birth weight and breastfeeding )were analyzed using the quantile regression model (percentile 5, 50 and 95). The testes were bidirectional and were compared in comparison with p <0.05. Results: Among the 529 participants included, 284 (53.6%) were female and mean age was 11.41 ? 3.9 years. The body mass index was the only one to be dissociated from the majority of the sexes (p = 0.753). The decrease in weight was associated with lower skeletal muscle mass (Difference = -8.51, 95% CI -11.12 to -5.90, p <0.001), lower fat-free mass (Difference = -13.80, 95% CI (P <0.001) and lower body mass index (Difference = -2.88, 95% CI - 4.42 to - 1.33, p <0.001) when adjusted for birth weight and breastfeeding. The lowest percentage of fat was associated with an inexpensive relative (Difference = -5.01, 95% CI -9.45 to -0.56, p = 0.027) only in the crude analyzes. Conclusion: Muscle mass,fat free mass, skeletal muscle mass and body mass index are associated with family income. / Introdu??o: A an?lise da composi??o corporal ? fundamental, pois est? fortemente associada com sa?de geral dos indiv?duos. Objetivo: Avaliar as associa??es entre fatores socioecon?micos e cl?nicos na composi??o corporal em crian?as e adolescentes. M?todos: Foram inclu?das por conveni?ncia, participantes com idades entre 5 e 19 anos. Crit?rios socioecon?micos e cl?nicos foram analisados por um question?rio padronizado e a composi??o corporal por bioimped?ncia el?trica (Biospace, modelo InBodyS10, da Ottoboni). As vari?veis estudadas foram comparadas em rela??o ao sexo por meio do teste t para amostras independentes e Qui-quadrado. As rela??es das vari?veis de desfecho (?ndice de massa corporal, massa livre de gordura, massa muscular esquel?tica e percentual de gordura) e as vari?veis preditoras (renda familiar, idade, sexo, ra?a, local de moradia, escolaridade do pai, atividade f?sica, peso ao nascimento e amamenta??o) foram analisadas mediante o modelo de regress?o quant?lica (percentil 5, 50 e 95). Os testes foram bidirecionais e as diferen?as foram consideradas significativas com p<0,05. Resultados: Entre os 529 participantes inclu?dos, 284 (53,6%) eram do sexo feminino e m?dia de idade foi de 11,41? 3,9 anos. O ?ndice de massa corporal foi o ?nico desfecho que n?o mostrou diferen?a significativa entre os sexos (p=0,753). A menor renda familiar foi associada com a menor massa muscular esquel?tica (Diferen?a= -8,51; IC95% -11,12 a -5,90, p<0,001), menor massa livre de gordura (Diferen?a= -13,80; IC95% -18,70 a -8,89, p<0,001) e menor ?ndice de massa corporal (Diferen?a= -2,88; IC95% - 4,42 a - 1,33, p<0,001) quando ajustado para peso ao nascimento e amamenta??o. O menor percentual de gordura associou-se a menor renda familiar (Diferen?a= -5,01; CI95% -9,45 a - 0,56, p=0,027) apenas nas an?lises brutas. Conclus?o: A renda familiar est? associada com a menor massa livre de gordura, massa muscular esquel?tica e ?ndice de massa corporal.

Made available in DSpace on 2014-12-17T14:10:24Z (GMT). No. of bitstreams: 1 SheilaMQML_DISSERT.pdf: 1368501 bytes, checksum: 2c822b3639e0a0b07601b48174a835c9 (MD5) Previous issue date: 2011-03-29 / In this work we analyze the skin bioimpedance statistical distribution. We focus on the study of two distinct samples: the statistics of impedance of several points in the skin of a single individual and the statistics over a population (many individuals) but in a single skin point. The impedance data was obtained from the literature (Pearson, 2007). Using the Shapiro-Wilk test and the assymmetry test we conclude that the impedance of a population is better described by an assymetric and non-normal distribution. On the other side, the data concerning the individual impedance seems to follow a normal distribution. We have performed a goodnes of fitting test and the better distribution to fit the data of a population is the log-normal distribution. It is interesting to note that our result for skin impedance is in simtony with body impedance from the literature of electrical engeneering. Our results have an impact over the statistical planning and modelling of skin impedance experiments. Special attention we should drive to the treatment of outliers in this kind of dataset. The results of this work are important in the general discussion of low impedance of points of acupuncture and also in the problem of skin biopotentials used in equipments like the Electrodermal Screen Tests. / Neste trabalho analisamos a distribui??o estat?stica de bioimped?ncia de pele. Focamos o estudo sobre duas amostragens: a estat?stica da imped?ncia de v?rios pontos na pele em um ?nico indiv?duo e a estat?stica de um lugar espec?fico da pele em uma popula??o. Os dados de imped?ncia de pele foram obtidos da literatura (Pearson, 2007). A combina??o dos resultados do teste de Shapiro-Wilk e do Teste de Assimetria confirmam que os dados em uma popula??o s?o melhores modelados por uma distribui??o n?o normal e assim?trica. Outrossim, os dados referentes ? distribui??o de imped?ncia para um indiv?duo parecem seguir a uma distribui??o normal. Realizamos testes de ajustes de curva e a melhor distribui??o encontrada para ajustar o conjunto dos dados de imped?ncia de pele para uma popula??o foi a log-normal. ? interessante notar que este resultado est? em sintonia com medidas de imped?ncia corporal de humanos relatados na literatura de engenharia el?trica. Nossos resultados t?m um impacto no planejamento estat?stico e na modelagem de experimentos da imped?ncia da pele, especialmente no tratamento de outliers neste conjunto de dados. Este resultado ? importante n?o somente para a quest?o cl?ssica da suposta baixa imped?ncia dos pontos de acupuntura, mas, al?m disso, para o problema geral de medidas de biopotenciais sobre a pele usada em equipamentos do tipo Electrodermal Screen Tests.

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.