13 resultados para Longitudinal Growth Modelling

em DigitalCommons@The Texas Medical Center


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The growth patterns of weight from birth through the first twelve months of life among rural Taiwanese infants were investigated with the following objectives: (i) compare each of the parameters of the Count model estimated for infants who were nutritionally at risk with those for a reference population from the United States; and (ii) within the Taiwanese infants, account for the variance in the growth patterns in the first and second six months of life on the basis of selected ecological factors.^ The significance between group differences were observed in the patterns of the weight growth in both linear growth and in the timing and the direction of velocity changes. A significant decline in growth velocity was observed among Taiwanese infants at about the fourth month of life. The decline is in keeping with a recent proposal made by J. C. Waterlow regarding the timing of change in growth velocity among nutritionally at risk populations in developing countries. The growth course of a nutritionally at risk infant during the first three months is apparently protected by the nurturance of the mother and innate biological properties of the infant.^ A highly significant portion of the growth variance in the second six months of life was accounted for by exogenous factors and biological factors related to the infant. Conversely, none of the growth variance in the first six months of life was accounted for by predictor variables. The most potent determinant of growth in the second six months of life was seasonality which represents a multiple environmental event.^ The model parameters estimated from the Count model represent different aspect of physical growth; yet the correlation coefficients between parameters b and c are high (r > .80). Clearly, the biological interpretation of the model parameters requires analysis of the whole function in the specific context of a given age period. ^

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Longitudinal principal components analyses on a combination of four subcutaneous skinfolds (biceps, triceps, subscapular and suprailiac) were performed using data from the London Longitudinal Growth Study. The main objectives were to discover at what age during growth sex differences in body fat distribution occur and to see if there is continuity in body fatness and body fat distribution from childhood into the adult status (18 years). The analyses were done for four age sectors (3mon-3yrs, 3yrs-8yrs, 8yrs-18yrs and 3yrs-18yrs). Longitudinal principal component one (LPC1) for each age interval in both sexes represents the population mean fat curve. Component two (LPC2) is a velocity of fatness component. Component three (LPC3) in the 3mon-3yrs age sector represents infant fat wave in both sexes. In the next two age sectors component three in males represents peaks and shifts in fat growth (change in velocity), while in females it represents body fat distribution. Component four (LPC4) in the same two age sectors is a reversal in the sexes of the patterns seen for component three, i.e., in males it is body fat distribution and in females velocity shifts. Components five and above represent more complicated patterns of change (multiple increases and decreases across the age interval). In both sexes there is strong tracking in fatness from middle childhood to adolescence. In males only there is also a low to moderate tracking of infant fat with middle to late childhood fat. These data are strongly supported in the literature. Several factors are known to predict adult fatness among the most important being previous levels of fatness (at earlier ages) and the age at rebound. In addition we found that the velocity of fat change in middle childhood was highly predictive of later fatness (r $\approx -$0.7), even more so than age at rebound (r $\approx -$0.5). In contrast to fatness (LPC1), body fat distribution (LPC3-LPC4) did not track well even though significant components of body fat distribution occur at each age. Tracking of body fat distribution was higher in females than males. Sex differences in body fat distribution are non existent. Some sex differences are evident with the peripheral-to-central ratios after age 14 years. ^

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The objectives of this study were to investigate the relationship between fasting serum insulin levels and Acanthosis Nigricans (AN) (a dermatological condition characterized by hyperpigmentation and thickening of the skin in specific body areas such as the neck and knuckles) and obesity among 6 to 9 year old children. Children were selected at random from a pediatric clinic located on the U.S.-Mexico border. Because none of the children participants had a weight for height at or above the 97th percentile of the CDC growth charts, obesity was defined as weight for height at or above the 95th percentile and at risk of overweight between the 85 th and 95th percentiles of the CDC growth charts. Anthropometrics, blood samples for fasting serum insulin and blood glucose, and a picture of the neck were obtained at baseline (n = 85) and 6 months later (n = 49). None of the children partipating had high fasting serum insulin levels and only 2 children had AN degree 2 (moderately severe). At baseline children with a weight for height at or above the 95th, percentile had 15 units less of insulin than children who weighed less. However, 6 months later this was not confirmed, thus the baseline result is considered to be an anomaly. Eventhough statistical significance was not reached, results showed that children without AN had 5 percentiles lower weight for height than children with AN. The most important recommendation from this study is the need to monitor longitudinal growth in children to characterize the individual child's growth pattern. AN seems to be related to longitudinal growth changes. ^

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Left ventricular mass (LVM) is a strong predictor of cardiovascular disease (CVD) in adults. However, normal growth of LVM in healthy children is not well understood, and previous results on independent effects of body size and body fatness on LVM have been inconsistent. The purpose of this study was (1) to establish the normal growth curve of LVM from age 8 to age 18, and evaluate the determinants of change in LVM with age, and (2) to assess the independent effects of body size and body fatness on LVM.^ In Project HeartBeat!, 678 healthy children aged 8, 11 and 14 years at baseline were enrolled and examined at 4-monthly intervals for up to 4 years. A synthetic cohort with continuous observations from age 8 to 18 years was constructed. A total of 4608 LVM measurements was made from M-mode echocardiography. The multilevel linear model was used for analysis.^ Sex-specific trajectories of normal growth of LVM from age 8 to 18 was displayed. On average, LVM was 15 g higher in males than females. Average LVM increased linearly in males from 78 g at age 8 to 145 g at age 18. For females, the trajectory was curvilinear, nearly constant after age 14. No significant racial differences were found. After adjustment for the effects of body size and body fatness, average LVM decreased slightly from age 8 to 18, and sex differences in changes of LVM remained constant.^ The impact of body size on LVM was examined by adding to a basic LVM-sex-age model one of 9 body size indicators. The impact of body fatness was tested by further introducing into each of the 9 LVM models (with one or another of the body size indicators) one of 4 body fatness indicators, yielding 36 models with different body size and body fatness combinations. The results indicated that effects of body size on LVM can be distinguished between fat-free body mass and fat body mass, both being independent, positive predictors. The former is the stronger determinant. When a non-fat-free body size indicator is used as predictor, the estimated residual effect of body fatness on LVM becomes negative. ^

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Approximately 12,000 new cases of spinal cord injury (SCI) are added each year to the estimated 259,000 Americans living with SCI. The majority of these patients return to society, their lives forever changed by permanent loss of sensory and motor function. While there are no FDA approved drugs for the treatment of SCI or a universally accepted standard therapy, the current though controversial treatment includes the delivery of high dosages of the corticosteroid methyliprednisolone sodium succinate, surgical interventions to stabilize the spinal column, and physical rehabilitation. It is therefore critically important to fully understand the pathology of injury and determine novel courses and rationally-based therapies for SCI. ^ Vascular endothelial growth factor (VEGF) is an attractive target for treating central nervous system (CNS) injury and disease because it has been shown to influence angiogenesis and neuroprotection. Preliminary studies have indicated that increased vasculature may be associated with functional recovery; therefore exogenous delivery of a pro-angiogenic growth factor such as VEGF may improve neurobehavioral outcome. In addition, VEGF may provide protection from secondary injury and result in increased survival and axonal sprouting. ^ In these studies, SCI rats received acute intraspinal injections of VEGF, the antibody to VEGF, or vehicle control. The effect of these various agents was investigated using longitudinalmulti-modal magnetic resonance imaging (MRI), neuro- and sensory behavioral assays, and end point immunohistochemistry. We found that rats that received VEGF after SCI had increased tissue sparing and improved white matter integrity at the earlier time points as shown by advanced magnetic resonance imaging (MRI) techniques. However, these favorable effects of VEGF were not maintained, suggesting that additional treatments with VEGF at multiple time points may be more beneficial, Histological examinations revealed that VEGF treatment may result in increased oligodendrogenesis and therefore may eventually lead to remyelination and improved functional outcome. ^ On the neurobehavioral studies, treatments with VEGF and Anti-VEGF did not significantly affect performance on tests of open-field locomotion, grid walk, inclined plane, or rearing. However, VEGF treatment resulted in significantly increased incidence of chronic neuropathic pain. This phenomenon could possibly be attributed to the fact that VEGF treatment may promote axonal sprouting and also results in tissue sparing, thereby providing a substrate for the growth of new axons. New connections made by these sprouting axons may involve components of pathways involved in the transmission of pain and therefore result in increased pain in those animals. ^

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Second-generation antipsychotics (SGAs) are increasingly prescribed to treat psychiatric symptoms in pediatric patients infected with HIV. We examined the relationship between prescribed SGAs and physical growth in a cohort of youth with perinatally acquired HIV-1 infection. Pediatric AIDS Clinical Trials Group (PACTG), Protocol 219C (P219C), a multicenter, longitudinal observational study of children and adolescents perinatally exposed to HIV, was conducted from September 2000 until May 2007. The analysis included P219C participants who were perinatally HIV-infected, 3-18 years old, prescribed first SGA for at least 1 month, and had available baseline data prior to starting first SGA. Each participant prescribed an SGA was matched (based on gender, age, Tanner stage, baseline body mass index [BMI] z score) with 1-3 controls without antipsychotic prescriptions. The main outcomes were short-term (approximately 6 months) and long-term (approximately 2 years) changes in BMI z scores from baseline. There were 236 participants in the short-term and 198 in the long-term analysis. In linear regression models, youth with SGA prescriptions had increased BMI z scores relative to youth without antipsychotic prescriptions, for all SGAs (short-term increase = 0.192, p = 0.003; long-term increase = 0.350, p < 0.001), and for risperidone alone (short-term = 0.239, p = 0.002; long-term = 0.360, p = 0.001). Participants receiving both protease inhibitors (PIs) and SGAs showed especially large increases. These findings suggest that growth should be carefully monitored in youth with perinatally acquired HIV who are prescribed SGAs. Future research should investigate the interaction between PIs and SGAs in children and adolescents with perinatally acquired HIV infection.

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OBJECTIVE: To examine the relationships between physical growth and medications prescribed for symptoms of attention-deficit hyperactivity disorder in children with HIV. METHODS: Analysis of data from children with perinatally acquired HIV (N = 2251; age 3-19 years), with and without prescriptions for stimulant and nonstimulant medications used to treat attention-deficit hyperactivity disorder, in a long-term observational study. Height and weight measurements were transformed to z scores and compared across medication groups. Changes in z scores during a 2-year interval were compared using multiple linear regression models adjusting for selected covariates. RESULTS: Participants with (n = 215) and without (n = 2036) prescriptions were shorter than expected based on US age and gender norms (p < .001). Children without prescriptions weighed less at baseline than children in the general population (p < .001) but gained height and weight at a faster rate (p < .001). Children prescribed stimulants were similar to population norms in baseline weight; their height and weight growth velocities were comparable with the general population and children without prescriptions (for weight, p = .511 and .100, respectively). Children prescribed nonstimulants had the lowest baseline height but were similar to population norms in baseline weight. Their height and weight growth velocities were comparable with the general population but significantly slower than children without prescriptions (p = .01 and .02, respectively). CONCLUSION: The use of stimulants to treat symptoms of attention-deficit hyperactivity disorder does not significantly exacerbate the potential for growth delay in children with HIV and may afford opportunities for interventions that promote physical growth. Prospective studies are needed to confirm these findings.

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Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

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The global social and economic burden of HIV/AIDS is great, with over forty million people reported to be living with HIV/AIDS at the end of 2005; two million of these are children from birth to 15 years of age. Antiretroviral therapy has been shown to improve growth and survival of HIV-infected individuals. The purpose of this study is to describe a cohort of HIV-infected pediatric patients and assess the association between clinical factors, with growth and mortality outcomes. ^ This was a historical cohort study. Medical records of infants and children receiving HIV care at Mulago Pediatric Infectious Disease Clinic (PIDC) in Uganda between July 2003 and March 2006 were analyzed. Height and weight measurements were age and sex standardized to Centers for Disease Control and prevention (CDC) 2000 reference. Descriptive and logistic regression analyses were performed to identify covariates associated with risk of stunting or being underweight, and mortality. Longitudinal regression analysis with a mixed model using autoregressive covariance structure was used to compare change in height and weight before and after initiation of highly active antiretroviral therapy (HAART). ^ The study population was comprised of 1059 patients 0-20 years of age, the majority of whom were aged thirteen years and below (74.6%). Mean height-for-age before initiation of HAART was in the 10th percentile, mean weight-for-age was in the 8th percentile, and the mean weight-for-height was in the 23rd percentile. Initiation of HAART resulted in improvement in both the mean standardized weight-for-age Z score and weight-for-age percentiles (p <0.001). Baseline age, and weight-for-age Z score were associated with stunting (p <0.001). A negative weight-for-age Z score was associated with stunting (OR 4.60, CI 3.04-5.49). Risk of death decreased from 84% in the >2-8 years age category to 21% in the >13 years age category respectively, compared to the 0-2 years of age (p <0.05). ^ This pediatric population gained weight significantly more rapidly than height after starting HAART. A low weight-for-age Z score was associated with poor survival in children. These findings suggest that age, weight, and height measurements be monitored closely at Mulago PIDC. ^

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Triglyceride levels are a component of plasma lipids that are thought to be an important risk factor for coronary heart disease and are influenced by genetic and environmental factors, such as single nucleotide polymorphisms (SNPs), alcohol intake, and smoking. This study used longitudinal data from the Bogalusa Heart Study, a biracial community-based survey of cardiovascular disease risk factors. A sample of 1191 individuals, 4 to 38 years of age, was measured multiple times from 1973 to 2000. The study sample consisted of 730 white and 461 African American participants. Individual growth models were developed in order to assess gene-environment interactions affecting plasma triglycerides over time. After testing for inclusion of significant covariates and interactions, final models, each accounting for the effects of a different SNP, were assessed for fit and normality. After adjustment for all other covariates and interactions, LIPC -514C/T was found to interact with age3, age2, and age and a non-significant interaction of CETP -971G/A genotype with smoking status was found (p = 0.0812). Ever-smokers had higher triglyceride levels than never smokers, but persons heterozygous at this locus, about half of both races, had higher triglyceride levels after smoking cessation compared to current smokers. Since tobacco products increase free fatty acids circulating in the bloodstream, smoking cessation programs have the potential to ultimately reduce triglyceride levels for many persons. However, due to the effect of smoking cessation on the triglyceride levels of CETP -971G/A heterozygotes, the need for smoking prevention programs is also demonstrated. Both smoking cessation and prevention programs would have a great public health impact on minimizing triglyceride levels and ultimately reducing heart disease. ^

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Cross-sectional designs, longitudinal designs in which a single cohort is followed over time, and mixed-longitudinal designs in which several cohorts are followed for a shorter period are compared by their precision, potential for bias due to age, time and cohort effects, and feasibility. Mixed longitudinal studies have two advantages over longitudinal studies: isolation of time and age effects and shorter completion time. Though the advantages of mixed-longitudinal studies are clear, choosing an optimal design is difficult, especially given the number of possible combinations of the number of cohorts and number of overlapping intervals between cohorts. The purpose of this paper is to determine the optimal design for detecting differences in group growth rates.^ The type of mixed-longitudinal study appropriate for modeling both individual and group growth rates is called a "multiple-longitudinal" design. A multiple-longitudinal study typically requires uniform or simultaneous entry of subjects, who are each observed till the end of the study.^ While recommendations for designing pure-longitudinal studies have been made by Schlesselman (1973b), Lefant (1990) and Helms (1991), design recommendations for multiple-longitudinal studies have never been published. It is shown that by using power analyses to determine the minimum number of occasions per cohort and minimum number of overlapping occasions between cohorts, in conjunction with a cost model, an optimal multiple-longitudinal design can be determined. An example of systolic blood pressure values for cohorts of males and cohorts of females, ages 8 to 18 years, is given. ^

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Multiple dietary deficiencies and high rates of infectious illness are major health problems leading to malnutrition and limitation of growth of children in developing countries. Longitudinal studies which provide information on illness incidence and growth velocity are needed in order to untangle the complex interrelationship between nutrition, illness and growth. From 1967 to 1973, researchers led by Dr. Bacon Chow of the Johns Hopkins University School of Hygiene undertook a quasi-experimental prospective study in Suilin Township, Taiwan to determine the effects of a nutritional supplement to the diets of pregnant and lactating women on the growth, development and resistance to disease of their offspring. This dissertation presents results from the analysis of infant morbidity and postnatal growth.^ Maternal nutritional supplementation has no apparent effect on the postnatal growth or morbidity of infants. Significant sex differences exist in growth response to illness and in illness susceptibility. Male infants have more diarrhea and upper respiratory illness. Respiratory illness is positively associated with growth rate in weight in the first semester of life. Diarrhea is significantly negatively associated with growth in length in the second semester. Small-for-date infants are more susceptible to illness in general and have a different pattern of growth response than large-for-date infants.^ Principal components analysis of illness data is shown to be an effective technique for making more precise use of ambiguous morbidity data. Multiple regression with component scores is an accurate method for estimating variance in growth rate predicted by indepenent illness variables. A model is advanced in which initial postnatal growth rate determines subsequent susceptibility to nutritional stress and infection. Initial growth rate is a function of prenatal nutrition, but is not significantly affected by maternal supplementation during gestation or lactation. Critical evaluation is made of nutritional supplementation programs which do not afford disease control.^

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Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^