A subnutrição é uma das comorbidades mais freqüentes que atinge os pacientes oncológicos. Entender as conseqüências do câncer nas alterações do metabolismo energético é necessário para o estabelecimento de estratégias que previnam o desenvolvimento e tratem a má-nutrição. A carnitina desempenha papel fundamental no metabolismo energético lipídico. Sendo que o objetivo deste estudo foi avaliar os níveis plasmáticos nos pacientes com câncer no pré cirúrgico e relacionar com os resultados da história alimentar, antropometria, impedância bioelétrica, calorimetria indireta, aminoacidemia e valores urinários de carnitina e nitrogênio. Trata-se de um trabalho prospectivo no qual foram escolhidos aleatoriamente 4 grupos, sendo um de pacientes portadores de câncer esofágico ou gástrico (n=24), e os outros 3 considerados controles. O primeiro grupo controle foi o obesos (n=16), o segundo de voluntários saudáveis (n=12), enterectomizados (n=6) Os valores médios de carnitinemia , em todos os grupos, variou entre 60 e 80 µM no plasma e urinária entre 78 e 124 µM, sem diferenças estatísticas entre os grupos. Quando avaliados os níveis de carnitina plasmático, 80% (p<0.05) dos pacientes com câncer apresentaram deficiência associados à excreção urinária inferior a 5 mol/kg/dia, consumo insuficiente de proteínas e baixa reserva adiposa. No entanto os níveis de metionina e lisina, bem como o gasto energético de repouso não apresentaram diferença com os controles. A deficiência de carnitina nestes pacientes pode comprometer o metabolismo energético além de estar associado à ocorrência de fadiga e piora da qualidade de vida. / The malnutrition is one most common comorbidity among hospitalized patients. Understanding cancer consequences in energetic metabolim changes is necessary in order to avoid malnutrition or to treat it. Carnitine has a important role in lipid metabolism. The aim of this study was to evaluate the levels of serum carnitine in patients with stomach and esophagus cancer and correlated with dietary intake, body composition, resting energy expenditure, carnitine and amino acid serum levels and urinary excretion of carnitine. Twenty-four cancer patients were assessed. Cancer patients were compared with obese (n=16), healthful (n=12) and short bowel disease (n=6). The mean values of serum carnitine and urinary carnitine among all groups were 60-80 µM and 74-124 µM respectively. Serum carnitine levels between cancer patients and other groups were significantly different. 80% of cancer patients had low serum levels, which was associated with urinary below 5 µmol/Kg/day, decreased protein and low adipose tissue. However, the methionine and lysine levels, as well as the resting energy expenditure had no difference when compared with the healthy volunteers. Carnitine deficiency in cancer patients can affect energetic metabolism and contribute to the progression of cachexia.

A subnutrição é uma das comorbidades mais freqüentes que atinge os pacientes oncológicos. Entender as conseqüências do câncer nas alterações do metabolismo energético é necessário para o estabelecimento de estratégias que previnam o desenvolvimento e tratem a má-nutrição. A carnitina desempenha papel fundamental no metabolismo energético lipídico. Sendo que o objetivo deste estudo foi avaliar os níveis plasmáticos nos pacientes com câncer no pré cirúrgico e relacionar com os resultados da história alimentar, antropometria, impedância bioelétrica, calorimetria indireta, aminoacidemia e valores urinários de carnitina e nitrogênio. Trata-se de um trabalho prospectivo no qual foram escolhidos aleatoriamente 4 grupos, sendo um de pacientes portadores de câncer esofágico ou gástrico (n=24), e os outros 3 considerados controles. O primeiro grupo controle foi o obesos (n=16), o segundo de voluntários saudáveis (n=12), enterectomizados (n=6) Os valores médios de carnitinemia , em todos os grupos, variou entre 60 e 80 µM no plasma e urinária entre 78 e 124 µM, sem diferenças estatísticas entre os grupos. Quando avaliados os níveis de carnitina plasmático, 80% (p<0.05) dos pacientes com câncer apresentaram deficiência associados à excreção urinária inferior a 5 mol/kg/dia, consumo insuficiente de proteínas e baixa reserva adiposa. No entanto os níveis de metionina e lisina, bem como o gasto energético de repouso não apresentaram diferença com os controles. A deficiência de carnitina nestes pacientes pode comprometer o metabolismo energético além de estar associado à ocorrência de fadiga e piora da qualidade de vida. / The malnutrition is one most common comorbidity among hospitalized patients. Understanding cancer consequences in energetic metabolim changes is necessary in order to avoid malnutrition or to treat it. Carnitine has a important role in lipid metabolism. The aim of this study was to evaluate the levels of serum carnitine in patients with stomach and esophagus cancer and correlated with dietary intake, body composition, resting energy expenditure, carnitine and amino acid serum levels and urinary excretion of carnitine. Twenty-four cancer patients were assessed. Cancer patients were compared with obese (n=16), healthful (n=12) and short bowel disease (n=6). The mean values of serum carnitine and urinary carnitine among all groups were 60-80 µM and 74-124 µM respectively. Serum carnitine levels between cancer patients and other groups were significantly different. 80% of cancer patients had low serum levels, which was associated with urinary below 5 µmol/Kg/day, decreased protein and low adipose tissue. However, the methionine and lysine levels, as well as the resting energy expenditure had no difference when compared with the healthy volunteers. Carnitine deficiency in cancer patients can affect energetic metabolism and contribute to the progression of cachexia.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 4 uppsatser.

Although case studies in avoidant/restrictive food intake disorder (ARFID) indicate severe nutritional deficiencies in those with a highly limited amount or variety of food intake, systematic analyses on food intake in treatment-seeking children and adolescents with ARFID are lacking. Within this study, n = 20 patients with an interview-based diagnosis of ARFID (0–17 years) were included and compared to n = 20 healthy controls individually matched for age and sex. Children or parents completed three-day food diaries and a food list. Macronutrient, vitamin, and mineral supply was determined based on the percentage of their recommended intake. The results showed a significantly lower total energy and protein intake in ARFID versus controls, with trends for lower fat and carbohydrate intake. ARFID subtypes of limited amount versus variety of food intake significantly differed in macro-, but not micronutrient intake. Those with ARFID met only 20–30% of the recommended intake for most vitamins and minerals, with significantly lower intake relative to controls for vitamin B1, B2, C, K, zinc, iron, and potassium. Variety of food intake was significantly reduced in ARFID versus controls in all food groups except carbohydrates. This study demonstrated that ARFID goes along with reduced everyday life macro- and micronutrient intake, which may increase the risk for developmental and health problems. Future studies additionally assessing serum nutrient levels in a larger sample may further explore differences in food intake across diverse ARFID presentations.

Glycemic intake influences the rise in blood glucose concentration following consumption of a carbohydrate containing meal, known as the postprandial glycemic response. The glycemic response is a result of both the type and amount of carbohydrate foods consumed and is commonly measured as the glycemic index (GI) or glycemic load (GL), where the GI is a ranking in comparison to glucose and the GL is an absolute value encompassing both the GI and amount of carbohydrate consumed. Evidence from controlled trials in rat models suggests that glycemic intake has a role in development of insulin resistance, however trials and observational studies of humans have produced conflicting results. As insulin resistance is a precursor to type 2 diabetes mellitus, lifestyle factors that could prevent development of this condition have important public health implications. Previous observational studies have used food frequency questionnaires to assess usual diet, which could have resulted in a lack of precision in assessment of individual serve sizes, and have been limited to daily measures of glycemic intake. Daily measures do not take fluctuations in glycemic intake on a per meal basis into account, which may be a more relevant measure for investigation in relation to disease outcomes. This PhD research was conducted in a group of Brisbane women aged 42 to 81 years participating in the multidisciplinary Brisbane Longitudinal Assessment of Ageing in Women (LAW study). Older women may be at particular risk of insulin resistance due to age, hormonal changes, and increases in abdominal obesity associated with menopause, and the LAW study provided an ideal opportunity to study the relationship between diet and insulin resistance. Using the diet history tool, we aimed to assess the glycemic intake of the population and hypothesised that daily GI and daily GL would be significantly positively associated with increased odds of insulin resistant status. We also hypothesised that a new glycemic measure representing peaks in GL at different meals would be a stronger predictor of insulin resistant status than daily measures, and that a specially designed questionnaire would be an accurate and repeatable dietary tool for assessment of glycemic intake. To address these hypotheses, we conducted a series of studies. To assess glycemic intake, information on usual diet was obtained by detailed diet history interview and analysed using Foodworks and the Australian Food and Nutrient (AUSNUT) database, combined with a customised GI database. Mean ± SD intakes were 55.6 ± 4.4% for daily GI and 115 ± 25 for daily GL (n=470), with intake higher amoung younger participants. Bread was the largest contributor to intakes of daily GI and GL (17.1% and 20.8%, respectively), followed by fruit (15.5% and 14.2%, respectively). To determine whether daily GI and GL were significantly associated with insulin resistance, the homeostasis model assessment of insulin resistance (HOMA) was used to assess insulin resistant status. Daily GL was significantly higher in subjects who were insulin resistant compared to those who were not (134 ± 33 versus 114 ± 24 respectively, P<0.001) (n=329); the odds of subjects in the highest tertile of GL intake being insulin resistant were 12.7 times higher when compared with the lowest tertile of GL (95% CI 1.6-100.1, P=0.02). Daily GI was not significantly different in subjects who were insulin resistant compared to those who were not (56.0 ± 3.3% versus 55.7 ± 4.5%, P=0.69). To evaluate whether a new glycemic measure representing fluctuations in daily glycemic intake would be a stronger predictor of insulin resistant status than other glycemic intake measures, the GL peak score was developed to express in a single value the magnitude of GL peaks during an average day. Although a significant relationship was seen between insulin resistant status and GL peak score (Nagelkerke’s R2=0.568, P=0.039), other glycemic intake measures of daily GL (R2=0.671, P<0.001) and daily GL per megajoule (R2=0.674, P<0.001) were stronger predictors of insulin resistant status. To develop an accurate and repeatable self-administered tool for assessment of glycemic intake, two sub-samples of women (n=44 for the validation study and n=52 for the reproducibility study) completed a semi-quantitative questionnaire that contained 23 food groupings selected to include the top 100 carbohydrate foods consumed by the study population. While there were significant correlations between the glycemic intake questionnaire and the diet history for GL (r=0.54, P<0.01), carbohydrate (r=0.57, P<0.01) and GI (r=0.40, P<0.01), Bland-Altman plots showed an unacceptable difference between individual intakes in 34% of subjects for daily GL and carbohydrate, and 41% for daily GI. Reproducibility results showed significant correlations for daily GL (r=0.73, P<0.001), carbohydrate (r=0.76, P<0.001) and daily GI (r=0.64, P<0.001), but an unacceptable difference between individual intakes in 25% of subjects for daily GL and carbohydrate, and 27% for daily GI. In summary, our findings show that a significant association was observed between daily glycemic load and insulin resistant status in a group of older women, using a diet history interview to obtain precise estimation of individual carbohydrate intake. Both the type and quantity of carbohydrate are important to consider when investigating relationships between diet and insulin resistance, although our results suggest the association is more closely related to overall daily glycemic intake than individual meal intake variations. A dietary tool that permits precise estimation of carbohydrate intake is essential when evaluating possible associations between glycemic intake and individual risk of chronic diseases such as insulin resistance. Our results also suggest that studies using questionnaires to estimate glycemic intake should state degree of agreement as well as correlation coefficients when evaluating validity, as imprecise estimates of carbohydrate at an individual level may have contributed to the conflicting findings reported in previous studies.

Diss. (sammanfattning) Linköping : Univ., 2005. / Härtill 4 uppsatser.