Thesis (doctoral)--Katholieke Universiteit te Nijmegen.

Thesis (doctoral)--Katholieke Universiteit te Nijmegen.

Thesis (M.S..)--Cornell University, May, 2008. / Vita. Includes bibliographical references (leaves 77-92).

<p>Uvod: Osteoporoza je sistemsko oboljenje skeleta koje se karakteri&scaron;e smanjenjem mase kosti i promenama u ko&scaron;tanoj strukturi, &scaron;to sve ima za posledicu povećanu sklonost ko&scaron;tanog tkiva ka prelomima. Prema preporuci Svetske zdravstvene organizacije, dijagnoza osteoporoze postavlja se ukoliko je T-score -2,5 SD i ispod te vrednosti, a normalan nalaz ako je vrednost T-score -1,0 SD i iznad te vrednosti. Danas se smatra da je zlatni standard u dijagnostici osteoporoze primena dvostruke X apsorpcione denzitometrije lumbalne kičme i kuka putem koje se dobiju vrednosti ko&scaron;tane mase Bone mineral density i T-score. Međutim, poznato je da postoje faktori rizika koji utiču na redukciju mase kosti na taj način &scaron;to smanjuju maksimum mase kosti koji se stiče do 35. godine života i / ili ubrzavaju inače normalan proces postepenog i blagog smanjenja mase kosti koji počinje posle 35. godine života i na taj način povećavaju rizik za frakture. Takođe, poznato je da neki od faktora rizika i njihova udruženost može dovesti do povećanog rizika za frakture i nezavisno od ko&scaron;tane mase i T-score. Ciljevi istraživanja : 1. Utvrditi ko&scaron;tanu masu u postmenopauznih žena primenom dvostruke X apsorpcione denzitometrije. 2. Analizirati distribuciju faktora rizika u pacijentkinja sa T-score ispod -2.5 SD u poređenju sa pacijentkinjama sa T-score iznad -1.0 SD. 3. Utvrditi odnos između statističkog prostora koji čine pojedinačni i udruženi faktori rizika (sa karakteristikama svakih od njih) i mase kosti određene denzitometrijski. Materijal i metode rada: Istraživanje je koncipirano delom kao prospektivna, a delom kao retrospektivna studija koja je sprovedena kod pacijentkinja u postmenopauznom periodu života, životne dobi od 50 do 80 godina. Nakon urađene dvostruke X apsorpcione denzitometrije lumbalne kičme i kuka ispitivane pacijentkinje su same popunjavale upitnik uz pomoć medicinske sestre ili lekara. Nakon dobijenih podataka pacijentkinje su podeljene u dve grupe: sa osteoporozom i bez osteoporoze. U grupi sa osteoporozom je bilo 270 pacijentkinja, a u grupi bez osteoporoze 250 pacijentkinja. Potom je sprovedena statistička obrada podataka. Nakon sveobuhvatne analize dobijenih rezultata istraživanja izvedeni su sledeći zaključci: 1.Ustanovljeno je da 60% postmenopauznih žena prosečne životne dobi od 67.0 &plusmn; 7.0 godina ima osteoporozu odnosno vrednost T-score &le; -2.5 SD. 2. Postoji statistička značajna povezanost između ko&scaron;tane mase i sledećih faktora rizika: pozitivna porodična anamneza na osteoporozu i frakture, telesna težina, telesna visina, ranije frakture, česti padovi i smanjenje u visini vi&scaron;e od 3 cm. 3. Analizom faktora rizika se dobijaju karakteristike osoba sa osteoporozom: pozitivna porodična anamneza na osteoporozu i frakture, manja telesna težina i telesna visina, smanjenje u visini vi&scaron;e od 3 cm, česti padovi i ranije frakture. 4. Hipertireoidizam i hiperparatireoidizam, reumatoidni artritis, primena kortikosteroidne terapije su faktori rizika koji su vi&scaron;e zastupljeni kod ispitivanih pacijentkinja sa osteoporozom. 5. Pu&scaron;enje, rana menopauza, alergija na mleko bez adekvatne supstitucije sa kalcijumom i nedovoljan boravak na suncu bez adekvatne supstitucije sa vitaminom D su faktori rizika koji su vi&scaron;e zastupljeni kod ispitivanih pacijentkinja sa osteoporozom. 6. Najveći doprinos celini daje pozitivna porodična anamneza na osteoporozu i frakture (20.99%), zatim slede telesna težina, telesna visina, Index telesne mase (19.03%), ranije frakture, česti padovi, smanjenje u visini vi&scaron;e od 3 cm (18.41%), pu&scaron;enje i nedovoljna fizička aktivnost (12.75%), alergija na mleko i nedovoljan boravak na suncu (12.14%), rana menopauza (8.72%), hipertireoidizam, hiperparatireoidizam, reumatoidni artritis (7.93%). 7. Analizom tri grupe obeležja koja daju najveći doprinos celini ustanovljeno je da pozitivna porodična anamneza na frakture (37.7%) i telesna težina (31.3%) predstavljaju major faktore rizika za osteoporozu. 8. Matematičkom obradom dolazi se do formule pomoću koje bi sa verovatnoćom od 64.0 % mogla predvideti osteoporoza, a sa verovatnoćom 73.2 % odsustvo osteoporoze, čime se između ostalog u na&scaron;em istraživanju donekle relativizuje neophodnost određivanja ko&scaron;tane mase u proceni rizika za prelome i u proceni potrebe za uvođenje antiosteoporotične terapije. Formula je +.214 O +.562 F +.202 R +.223 P +.335 S +.493 T +.057 V +.020 9. Potrebno je testirati dobijenu formulu na ispitivanim pacijentkinjama i nastaviti istraživanje na većem uzorku na faktore rizika koji nisu pokazali statističku značajnost.</p> / <p>Introduction: Osteoporosis is a systematic disease of skeleton characterized by the reduction of bone mass and changes in bone structure which result in the increased aptitude of bone tissue to fractures. According to the suggestion of the World Health Organization, the diagnosis for osteoporosis is set if the T-score is -2.5 SD and below it and the normal report if the value of T-score is -1.0 SD and above it. Nowadays, it is considered that the golden standard in osteoporosis diagnostic is the use of double X absorption densitometry of lumbal spine and hipe which provides the values of bone mass Bone mineral density as well as T-score. However, it has been known that there are risk factors whish influence the reduction of bone mass by reducing maximum bone mass gained by the age of 35 and/or by quckening, the normal process of gradual and mild reduction of bone mass starting after 35 and in that way increase the risk toward fractures. It mas also been known that some of the risk factors and their correlation may cause the increasement of the risk factor toward fractures not having the connection with the bone mass and T-score. Researchment aims: 1. Determine bone mass in postmenopausal women using double X absorption densitometry. 2. Analyse distribution of risk factors in patients whith the T-score below -2.5 SD comparing to the patients with T-score above -1.0SD. 3. Determine the relation between statistical space made by individual and associated risk factors (with the characteristics of each of them) and the bone mass specified by densitometry. Material and methods of working: Researchment is outlined partly as prospective and partly as retrospective study which was carried out in patients in postmenopausal life period, aged 50-80. After applying double X absorption densitometry of lumbal spine and hip the examined patients did the questionnaire by themselves whith the help of nurses and doctors. After obtaining the data, patients were divided into two groups: with and without osteoporosis. There were 270 patients in the group with osteoporosis and 250 of them without it. Thereafter, the statistic data processing was carried out. After the overall analysis of obtained results of researchment, following conclusions were conducted: 1. It has been determined that 60 % of postmenopausal women of average age 67.0&plusmn;7.0 have osteoporosis, in other words, their T-score is &le; -2.5 SD. 2. There is statistically important relationship between the bone mass and following risk factors: positive family anamnesis to osteoporosis and fractures, body weight, height, previos fractures, frequent falls and reduction of height for more than 3 cm. 3. Analysing the risk factors, characteristics of persons with osteoporosis have been obtained: positive family anamnesis to osteoporosis and fractures, smaller body weight and height, the reduction in height for more than 3 cm, frequent falls and previous fractures. 4. Hyperthyroidism and hyperparathyroidism, rheumatoid arthritis and the usage of corticosteroid therapy are the risk factors more incident in the examined patients with osteoporosis. 5. Smoking, early menopause, allergy to milk with no adequate substitution of calcium and insufficient exposition to sun rays with no adequate substitution of vitamine D are the risk factors more incident in patients with osteoporosis. 6. The largest contribution to the total makes positive family anamnesis to osteoporosis and fractures (20.99%), followed by body weight, height, Body mass index (19.03%), previos fractures, frequent falls and reduction in height for more than 3 cm (18.41%), smoking and insufficient physical activity (12.75%), allergy to milk and insufficient exposition to the sun (12.14%), early menopause (8.72%), hyperthyroidism and hyperparathyroidism, rheumatoid arthritis (7.93%). 7. By the analysis of all three goups of features giving the largest cintribution to the total, it has been determined that positive family anamnesis to fractures (37.7%), and body weight (31.3%), present the major risk factors for osteoporosis. 8. By mathematical processing we obtain the formula which can with the probability of 64.0% predict osteoporosis, and with the probability of 73.2% the absence of osteoporosis, which can, among other things in our research to some extent, require relative necessity for introduction of antiosteoporotic therapy. The formula is +.214 O +.562 F +.202 R +.223 P +.335 S +.493 T +.057 V +.020. 9. It is necessary to test the formula obtained in examined patients and continue the reseachment, on larger sample, of risk factors which have not shown statistic importance.</p>

Gasto Energético de Repouso (GER) varia ao longo do tempo e apresenta efeitos práticos nas comparações interpessoais. O método tradicional para estimar GER não leva em conta as diferentes atividades metabólicas de órgãos, tecido ósseo (TO), tecido adiposo (TA), tecido músculo esquelético (TME) e cérebro. Assim, o objetivo deste estudo foi determinar o GER de adultos jovens brasileiros de forma multicompartimentada (DXA) referenciada por calorimetria indireta (CI). Uma amostra de 155 jovens universitários de ambos os sexos (18 a 30 anos) foi submetida a medidas antropométricas, estimativa de GER por CI e varredura de corpo total por DXA (nível molecular). Após a transformação dos componentes (DXA) para o nível órgão tecidular, foi determinado o GER de cada componente. A concordância (Bland-Altman) entre GER medido (CI) e predito (DXA) foi realizada para validação do modelo testado. Como a validação falhou um novo modelo foi desenvolvido (Regressão Linear - ENTER) e validado (PRESS) tendo como variável dependente as cinco variáveis geradas após a relativização do GER dado pela CI para o modelo testado mais a variável sexo. As análises foram realizadas com o pacote estatístico SPSS v. 20.0 (Chicago, IL); MedCalc® 2015 (v. 15.2); e Minitab® (v. 17.3.1), com nível de significância em ? = 0,05. Os resultados evidenciaram maiores valores de massa isenta de tecido adiposo (MITA), área craniana e tecido residual (TR) para os homens e menores valores de massa gorda (MG) e tecido adiposo (TA) do que as mulheres. Maiores gastos (p<0,001) foram encontrados nos homens para todos os componentes em relação às mulheres, exceto no gasto do TA (p<0,001). Nas comparações entre medido e predito diferenças (p<0,001) foram encontradas para a amostra total, homens e mulheres. Dessa forma, equações específicas para cada componente foram propostas e validadas pela soma dos quadrados dos resíduos, nos coeficientes (R2PRESS = 0,95; 0,73; 0,80; 0,16; 0,84) e na confiabilidade de erro reduzido (SPRESS = 14,2; 1,8; 46,3; 48,1; 87,2) para o gasto do TA, TO, TME, cérebro e TR. Em conclusão, essa abordagem traz implicações importantes para a avaliação e interpretação do metabolismo energético multicompartimental, considerando as diferenças interpessoais na produção de calor. É uma estratégia aplicável no contexto da saúde ou esporte, para prescrição de exercícios ou manipulação de dietas, pois retrata a magnitude de GER de cada componente corporal / Resting Energy Expenditure (REE) varies over time and has practical consequences for interpersonal comparisons. The traditional method to estimate REE does not take into account the metabolic activities of organs, bone tissue (BT), adipose tissue (AT), muscle tissue (MT) and brain. Therefore, the aim of this study was to determine the REE of Brazilian young adults from a multicompartmental way (DXA) referenced by indirect calorimetry (IC). A sample of 155 university students of both sexes (18-30 years) was submitted to anthropometric measurements, to estimate REE by IC and total body scan (DXA) of the molecular level. After transformation of DXA components to the organ-tissue level, the REE was determined for each component. The agreement (Bland-Altman) between measured REE (CI) and predicted (DXA) was carried out to validate the tested model. How validation failed, a new model was developed (Linear Regression - ENTER) and validated (PRESS) having as dependent variable the five variables generated after the relativization of the GER given by the IC for the model tested plus the sex variable. The analyzes were performed with the statistical package SPSS v. 20.0 (Chicago, IL); MedCalc® 2015 (v.15.2); and Minitab® (see 17.3.1), with significance level at ? = 0.05. The results showed higher values of adipose tissue free mass (ATFM), head area and residual tissue (RT) for men and lower values of fat mass (MG) and adipose tissue (AT) in relation to women. Higher expenditure (p <0.001) were found in men for all components compared to women, except for AT (p <0.001). In the comparisons between measured and predicted differences (p <0.001) were found for the total sample, men and women. In this way, specific equations for each component were proposed and validated by the sum of the squares of the residues, in the coefficients (R2PRESS = 0.95, 0.73, 0.80, 0.16, 0.84) and the reduced error reliability (SPRESS = 14.2, 1.8, 46.3, 48.1, 87.2) for the expenditure of AT, BT, MT, brain and RT. In conclusion, this approach has important implications for the evaluation and interpretation of multicompartmental energy metabolism considering the interpersonal differences in the production of heat. It is a strategy applicable in the context of health or sports, for prescription of exercises or manipulation of diets, as it portrays the magnitude of GER of each body component

Gasto Energético de Repouso (GER) varia ao longo do tempo e apresenta efeitos práticos nas comparações interpessoais. O método tradicional para estimar GER não leva em conta as diferentes atividades metabólicas de órgãos, tecido ósseo (TO), tecido adiposo (TA), tecido músculo esquelético (TME) e cérebro. Assim, o objetivo deste estudo foi determinar o GER de adultos jovens brasileiros de forma multicompartimentada (DXA) referenciada por calorimetria indireta (CI). Uma amostra de 155 jovens universitários de ambos os sexos (18 a 30 anos) foi submetida a medidas antropométricas, estimativa de GER por CI e varredura de corpo total por DXA (nível molecular). Após a transformação dos componentes (DXA) para o nível órgão tecidular, foi determinado o GER de cada componente. A concordância (Bland-Altman) entre GER medido (CI) e predito (DXA) foi realizada para validação do modelo testado. Como a validação falhou um novo modelo foi desenvolvido (Regressão Linear - ENTER) e validado (PRESS) tendo como variável dependente as cinco variáveis geradas após a relativização do GER dado pela CI para o modelo testado mais a variável sexo. As análises foram realizadas com o pacote estatístico SPSS v. 20.0 (Chicago, IL); MedCalc® 2015 (v. 15.2); e Minitab® (v. 17.3.1), com nível de significância em ? = 0,05. Os resultados evidenciaram maiores valores de massa isenta de tecido adiposo (MITA), área craniana e tecido residual (TR) para os homens e menores valores de massa gorda (MG) e tecido adiposo (TA) do que as mulheres. Maiores gastos (p<0,001) foram encontrados nos homens para todos os componentes em relação às mulheres, exceto no gasto do TA (p<0,001). Nas comparações entre medido e predito diferenças (p<0,001) foram encontradas para a amostra total, homens e mulheres. Dessa forma, equações específicas para cada componente foram propostas e validadas pela soma dos quadrados dos resíduos, nos coeficientes (R2PRESS = 0,95; 0,73; 0,80; 0,16; 0,84) e na confiabilidade de erro reduzido (SPRESS = 14,2; 1,8; 46,3; 48,1; 87,2) para o gasto do TA, TO, TME, cérebro e TR. Em conclusão, essa abordagem traz implicações importantes para a avaliação e interpretação do metabolismo energético multicompartimental, considerando as diferenças interpessoais na produção de calor. É uma estratégia aplicável no contexto da saúde ou esporte, para prescrição de exercícios ou manipulação de dietas, pois retrata a magnitude de GER de cada componente corporal / Resting Energy Expenditure (REE) varies over time and has practical consequences for interpersonal comparisons. The traditional method to estimate REE does not take into account the metabolic activities of organs, bone tissue (BT), adipose tissue (AT), muscle tissue (MT) and brain. Therefore, the aim of this study was to determine the REE of Brazilian young adults from a multicompartmental way (DXA) referenced by indirect calorimetry (IC). A sample of 155 university students of both sexes (18-30 years) was submitted to anthropometric measurements, to estimate REE by IC and total body scan (DXA) of the molecular level. After transformation of DXA components to the organ-tissue level, the REE was determined for each component. The agreement (Bland-Altman) between measured REE (CI) and predicted (DXA) was carried out to validate the tested model. How validation failed, a new model was developed (Linear Regression - ENTER) and validated (PRESS) having as dependent variable the five variables generated after the relativization of the GER given by the IC for the model tested plus the sex variable. The analyzes were performed with the statistical package SPSS v. 20.0 (Chicago, IL); MedCalc® 2015 (v.15.2); and Minitab® (see 17.3.1), with significance level at ? = 0.05. The results showed higher values of adipose tissue free mass (ATFM), head area and residual tissue (RT) for men and lower values of fat mass (MG) and adipose tissue (AT) in relation to women. Higher expenditure (p <0.001) were found in men for all components compared to women, except for AT (p <0.001). In the comparisons between measured and predicted differences (p <0.001) were found for the total sample, men and women. In this way, specific equations for each component were proposed and validated by the sum of the squares of the residues, in the coefficients (R2PRESS = 0.95, 0.73, 0.80, 0.16, 0.84) and the reduced error reliability (SPRESS = 14.2, 1.8, 46.3, 48.1, 87.2) for the expenditure of AT, BT, MT, brain and RT. In conclusion, this approach has important implications for the evaluation and interpretation of multicompartmental energy metabolism considering the interpersonal differences in the production of heat. It is a strategy applicable in the context of health or sports, for prescription of exercises or manipulation of diets, as it portrays the magnitude of GER of each body component