LONGITUDINAL GROWTH PARAMETERS AND THEIR ECOLOGICAL DETERMINANTS (SEASONALITY)

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. ^

Anal warts and their predictors among HIV-infected women

Human papillomavirus (HPV) is a necessary cause of cervical cancer and is also strongly associated with anal cancer. While different factors such as CD4+ cell count, HIV RNA viral load, smoking status, and cytological screening results have been identified as risk factors for the infection of HPV high-risk types and associated cancers, much less is known about the association between those risk factors and the infection of HPV low-risk types and anogential warts. In this dissertation, a public dataset (release P09) obtained from the Women's Interagency HIV Study (WIHS) was used to examine the effects of those risk factors on the size of the largest anal warts in HIV-infected women in the United States. Linear mixed modeling was used to address this research question. ^ The prevalence of anal warts at baseline for WIHS participants was higher than other populations. Incidence of anal warts in HIV-infected women was significantly higher than that of HIV-uninfected women [4.15 cases per 100 person-years (95% CI: 3.83–4.77) vs. 1.30 cases per 100 person-years (95% CI: 1.00–1.58), respectively]. There appeared to be an inverse association between the size of the largest anal wart and CD4+ cell count at baseline visit, however it was not statistically significant. There was no association between size of the largest anal wart and CD4+ cell count or HIV RNA viral load over time among HIV-infected women. There was also no association between the size of the largest anal wart and current smoking over time in HIV-infected women, even though smokers had larger warts at baseline than non-smokers. Finally, even though a woman with Pap smear results of ASCUS/LGSIL was found to have an anal wart larger than a woman with normal cervical Pap smear results the relationship between the size of the largest anal wart with cervical Pap smear results over time remains unclear. ^ Although the associations between these risk factors and the size of the largest anal wart over time in HIV-infected women could not be firmly established, this dissertation poses several questions concerning anal wart development for further exploration: (1) the role of immune function (i.e., CD4+ cell count), (2) the role of smoking status and the interaction between smoking status with other risk factors (e.g., CD4+ cell count or HIV RNA viral load), (3) the molecular mechanism of smoking on anal warts over time, (4) the potential for development of a screening program using anal Pap smear in HIV-infected women, and (5) how cost-effective and efficacious would an anal Pap smear screening program be in this high-risk population. ^

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

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.^

Changes in blood lipids and their associations with changes in measures of height, weight and body mass index from age 8 to 18 years: Project Heartbeat!

A variety of studies indicate that the process of athrosclerosis begins in childhood. There was limited information on the association of the changes in anthropometric variables to blood lipids in school age children and adolescents. Previous longitudinal studies of children typically with insufficient frequency of observation could not provide sound inference on the dynamics of change in blood lipids. The aims of this analysis are (1) to document the sex- and ethnic-specific trajectory and velocity curves of blood lipids (TC, LDL-C, HDL-C and TG); (2) to evaluate the relationship of changes in anthropometric variables, such as height, weight and BMI, to blood lipids from age 8 to 18 years. ^ Project HeartBeat! is a longitudinal study designed to examine the patterns of serial change in major cardiovascular risk factors. Cohort of three different age levels, 8, 11 and 14 years at baseline, with a total of 678 participants were enrolled. Each member of these cohorts was examined three times per year for up to four years. ^ Sex- and ethnic-specific trajectory and velocity curves of blood lipids; demonstrated the complex and polyphasic changes in TC, LDL-C, HDL-C and TG longitudinally. The trajectory curves of TC, LDL-C and HDL-C with age showed curvilinear patterns of change. The velocity change in TC, HDL-C and LDL-C showed U-shaped curves for non-Blacks, and nearly linear lines in velocity of TG for both Blacks and non-Blacks. ^ The relationship of changes in anthropometric variables to blood lipids was evaulated by adding height, weight, or BMI and associated interaction terms separately to the basic age-sex models. Height or height gain had a significant negative association with changes in TC, LDL-C and HDL-C. Weight or BMI gain showed positive associations with TC, LDL-C and TC, and a negative relationship with HDL-C. ^ Dynamic changes of blood lipids in school age children and adolescents observed from this analysis suggested that using fixed screening criteria under the current NCEP guidelines for all ages 2–19 may not be appropriate for this age group. The association of increasing BMI or weight to an adverse blood lipid profile found in this analysis also indicated that weight or BMI monitoring could be a future intervention to be implemented in the pediatric population. ^

Physical activity, body composition, exogenous estrogen use and their association with insulin-like growth factors

Obesity and physical inactivity are modifiable risk factors that are associated with several health issues; they are major factors in up to 30% of major cancers. Elevated levels of circulating insulin-like growth factor-I (IGF-I) have been associated with high body composition measurements and high cancer risk; exogenous estrogen use is associated with low circulating IGF-I levels and high cancer risk. The relationship between physical activity and circulating IGF levels is complex and findings of previous studies of their relationship remain inconsistent; however, these studies included vague definitions of physical activity. In this study, we used cross-sectional data from the Women's Health Initiative to determine the relationship between specific measures of physical activity (e.g., intensity, duration, and frequency) and circulating IGF-I levels, accounting for exogenous estrogen use and body composition. These data were collected from women enrolled at Women's Health Initiative clinical centers at Baylor College of Medicine and Wake Forest University School of Medicine. Multivariate linear regression analysis showed that circulating IGF-I and IGF-binding protein (BP) 3 levels were positively associated with frequency, duration, and intensity of physical activity. Circulating IGF-I levels and the molar IGF-I:IGF-BP3 ratio were significantly associated with frequency of walking, whereas circulating IGF-BP3 levels were significantly associated with strenuous physical activity, suggesting that different aspects of physical activity and their effects on fitness affect members of the IGF family differently. The results from our study support the recommendation of a regular exercise routine, particularly that of strenuous intensity, for postmenopausal women as a means to prevention of cancer.^

Micronutrient intakes and their associations with markers of inflammation, subclinical atherosclerosis, cardiovascular disease, type II diabetes and metabolic syndrome

We investigated cross-sectional associations between intakes of zinc, magnesium, heme- and non heme iron, beta-carotene, vitamin C and vitamin E and inflammation and subclinical atherosclerosis in the Multi-Ethnic Study of Atherosclerosis (MESA). We also investigated prospective associations between those micronutrients and incident MetS, T2D and CVD. Participants between 45-84 years of age at baseline were followed between 2000 and 2007. Dietary intake was assessed at baseline using a 120-item food frequency questionnaire. Multivariable linear regression and Cox proportional hazard regression models were used to evaluate associations of interest. Dietary intakes of non-heme iron and Mg were inversely associated with tHcy concentrations (geometric means across quintiles: 9.11, 8.86, 8.74, 8.71, and 8.50 µmol/L for non-heme iron, and 9.20, 9.00, 8.65, 8.76, and 8.33 µmol/L for Mg; ptrends <0.001). Mg intake was inversely associated with high CC-IMT; odds ratio (95% CI) for extreme quintiles 0.76 (0.58, 1.01), ptrend: 0.002. Dietary Zn and heme-iron were positively associated with CRP (geometric means: 1.73, 1.75, 1.78, 1.88, and 1.96 mg/L for Zn and 1.72, 1.76, 1.83, 1.86, and 1.94 mg/L for heme-iron). In the prospective analysis, dietary vitamin E intake was inversely associated with incident MetS and with incident CVD (HR [CI] for extreme quintiles - MetS: 0.78 [0.62-0.97] ptrend=0.01; CVD: 0.69 [0.46-1.03]; ptrend =0.04). Intake of heme-iron from red meat and Zn from red meat, but not from other sources, were each positively associated with risk of CVD (HR [CI] - heme-iron from red meat: 1.65 [1.10-2.47] ptrend = 0.01; Zn from red meat: 1.51 [1.02 - 2.24] ptrend =0.01) and MetS (HR [CI] - heme-iron from red meat: 1.25 [0.99-1.56] ptrend =0.03; Zn from red meat: 1.29 [1.03-1.61]; ptrend = 0.04). All associations evaluated were similar across different strata of gender, race-ethnicity and alcohol intake. Most of the micronutrients investigated were not associated with the outcomes of interest in this multi-ethnic cohort. These observations do not provide consistent support for the hypothesized association of individual nutrients with inflammatory markers, MetS, T2D, or CVD. However, nutrients consumed in red meat, or consumption of red meat as a whole, may increase risk of MetS and CVD.^

Longitudinal dyadic data analysis of stroke survivors and their spousal caregivers

Approximately 795,000 new and recurrent strokes occur each year. Because of the resulting functional impairment, stroke survivors are often discharged into the care of a family caregiver, most often their spouse. This dissertation explored the effect that mutuality, a measure of the perceived positive aspects of the caregiving relationship, had on the stress and depression of 159 stroke survivors and their spousal caregivers over the first 12 months post discharge from inpatient rehabilitation. Specifically, cross-lagged regression was utilized to investigate the dyadic, longitudinal relationship between caregiver and stroke survivor mutuality and caregiver and stroke survivor stress over time. Longitudinal meditational analysis was employed to examine the mediating effect of mutuality on the dyads’ perception of family function and caregiver and stroke survivor depression over time.^ Caregivers’ mutuality was found to be associated with their own stress over time but not the stress of the stroke survivor. Caregivers who had higher mutuality scores over the 12 months of the study had lower perceived stress. Additionally, a partner effect of stress for the stroke survivor but not the caregiver was found, indicating that stroke survivors’ stress over time was associated with caregivers’ stress but caregivers’ stress over time was not significantly associated with the stress of the stroke survivor.^ This dissertation did not find mutuality to mediate the relationship between caregivers’ and stroke survivors’ perception of family function at baseline and their own or their partners’ depression at 12 months as hypothesized. However, caregivers who perceived healthier family functioning at baseline and stroke survivors who had higher perceived mutuality at 12 months had lower depression at one year post discharge from inpatient rehabilitation. Additionally, caregiver mutuality at 6 months, but not at baseline or 12 months, was found to be inversely related to caregiver depression at 12 months.^ These findings highlight the interpersonal nature of stress in the context of caregiving, especially among spousal relationships. Thus, health professionals should encourage caregivers and stroke survivors to focus on the positive aspects of the caregiving relationship in order to mitigate stress and depression. ^