Changes in the PQRST intervals and heart rate variability associated with rewarming in two newborns undergoing hypothermia therapy.

BACKGROUND: Little is known about the effects of hypothermia therapy and subsequent rewarming on the PQRST intervals and heart rate variability (HRV) in term newborns with hypoxic-ischemic encephalopathy (HIE). OBJECTIVES: This study describes the changes in the PQRST intervals and HRV during rewarming to normal core body temperature of 2 newborns with HIE after hypothermia therapy. METHODS: Within 6 h after birth, 2 newborns with HIE were cooled to a core body temperature of 33.5 degrees C for 72 h using a cooling blanket, followed by gradual rewarming (0.5 degrees C per hour) until the body temperature reached 36.5 degrees C. Custom instrumentation recorded the electrocardiogram from the leads used for clinical monitoring of vital signs. Generalized linear mixed models were calculated to estimate temperature-related changes in PQRST intervals and HRV. Results: For every 1 degrees C increase in body temperature, the heart rate increased by 9.2 bpm (95% CI 6.8-11.6), the QTc interval decreased by 21.6 ms (95% CI 17.3-25.9), and low and high frequency HRV decreased by 0.480 dB (95% CI 0.052-0.907) and 0.938 dB (95% CI 0.460-1.416), respectively. CONCLUSIONS: Hypothermia-induced changes in the electrocardiogram should be monitored carefully in future studies.

Improving adherence in African American women with uncontrolled primary hypertension

Background and Objectives: African American (AA) women are disproportionately affected with hypertension (HTN). The aim of this randomized controlled trial was to evaluate the effectiveness of a 6-week culturally-tailored educational intervention for AA women with primary HTN who lived in rural Northeast Texas. ^ Methods: Sixty AA women, 29 to 86 years (M 57.98 ±12.37) with primary HTN were recruited from four rural locations and randomized to intervention (n =30) and wait-list control groups ( n =30) to determine the effectiveness of the intervention on knowledge, attitudes, beliefs, social support, adherence to a hypertension regimen, and blood pressure (BP) control. Survey and BP measurements were collected at baseline, 3 weeks, 6 weeks (post intervention) and 6 months post intervention. Culturally-tailored educational classes were provided for 90 minutes once a week for 6 weeks in two local churches and a community center. The wait-list control group received usual care and were offered education at the conclusion of the data collection six months post-intervention. Linear mixed models were used to test for differences between the groups. ^ Results: A significant overall main effect (Time) was found for systolic blood pressure, F(3, 174) =11.104, p=.000, and diastolic blood pressure. F(3, 174) =4.781, p=.003 for both groups. Age was a significant covariate for diastolic blood pressure. F(1, 56) =6.798 p=.012. Participants 57 years or older (n=30) had lower diastolic BPS than participants younger than 57 (n=30). No significant differences were found between groups on knowledge, adherence, or attitudes. Participants with lower incomes had significantly less knowledge about HBP Prevention (r=.036, p=.006). ^ Conclusion: AA women who participated in a 6 week intervention program demonstrated a significant decrease in BP over a 6 month period regardless of whether they were in the intervention or control group. These rural AA women had a relatively good knowledge of HTN and reported an average level of compliance, compared to other populations. Satisfaction with the program was high and there was no attrition, suggesting that AA women will participate in research studies that are culturally tailored to them, held in familiar community locations, and conducted by a trusted person with whom they can identify. Future studies using a different program with larger sample sizes are warranted to try to decrease the high level of HTN-related complications in AA women. ^

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Health outcomes, quality improvement and cost-effectiveness of the Community Diabetes Education (CoDE) program: Results of a randomized controlled trial

The objectives of this dissertation were to evaluate health outcomes, quality improvement measures, and the long-term cost-effectiveness and impact on diabetes-related microvascular and macrovascular complications of a community health worker-led culturally tailored diabetes education and management intervention provided to uninsured Mexican Americans in an urban faith-based clinic. A prospective, randomized controlled repeated measures design was employed to compare the intervention effects between: (1) an intervention group (n=90) that participated in the Community Diabetes Education (CoDE) program along with usual medical care; and (2) a wait-listed comparison group (n=90) that received only usual medical care. Changes in hemoglobin A1c (HbA1c) and secondary outcomes (lipid status, blood pressure and body mass index) were assessed using linear mixed-models and an intention-to-treat approach. The CoDE group experienced greater reduction in HbA1c (-1.6%, p<.001) than the control group (-.9%, p<.001) over the 12 month study period. After adjusting for group-by-time interaction, antidiabetic medication use at baseline, changes made to the antidiabetic regime over the study period, duration of diabetes and baseline HbA1c, a statistically significant intervention effect on HbA1c (-.7%, p=.02) was observed for CoDE participants. Process and outcome quality measures were evaluated using multiple mixed-effects logistic regression models. Assessment of quality indicators revealed that the CoDE intervention group was significantly more likely to have received a dilated retinal examination than the control group, and 53% achieved a HbA1c below 7% compared with 38% of control group subjects. Long-term cost-effectiveness and impact on diabetes-related health outcomes were estimated through simulation modeling using the rigorously validated Archimedes Model. Over a 20 year time horizon, CoDE participants were forecasted to have less proliferative diabetic retinopathy, fewer foot ulcers, and reduced numbers of foot amputations than control group subjects who received usual medical care. An incremental cost-effectiveness ratio of $355 per quality-adjusted life-year gained was estimated for CoDE intervention participants over the same time period. The results from the three areas of program evaluation: impact on short-term health outcomes, quantification of improvement in quality of diabetes care, and projection of long-term cost-effectiveness and impact on diabetes-related health outcomes provide evidence that a community health worker can be a valuable resource to reduce diabetes disparities for uninsured Mexican Americans. This evidence supports formal integration of community health workers as members of the diabetes care team.^

Heart rate variability in response to pain stimulus in VLBW infants followed longitudinally during NICU stay.

The objective of this longitudinal study, conducted in a neonatal intensive care unit, was to characterize the response to pain of high-risk very low birth weight infants (<1,500 g) from 23 to 38 weeks post-menstrual age (PMA) by measuring heart rate variability (HRV). Heart period data were recorded before, during, and after a heel lanced or wrist venipunctured blood draw for routine clinical evaluation. Pain response to the blood draw procedure and age-related changes of HRV in low-frequency and high-frequency bands were modeled with linear mixed-effects models. HRV in both bands decreased during pain, followed by a recovery to near-baseline levels. Venipuncture and mechanical ventilation were factors that attenuated the HRV response to pain. HRV at the baseline increased with post-menstrual age but the growth rate of high-frequency power was reduced in mechanically ventilated infants. There was some evidence that low-frequency HRV response to pain improved with advancing PMA.

Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Statistical and methodological challenges for disaster preparedness and medical needs assessment in Rio Grande Valley of Texas

In recent years, disaster preparedness through assessment of medical and special needs persons (MSNP) has taken a center place in public eye in effect of frequent natural disasters such as hurricanes, storm surge or tsunami due to climate change and increased human activity on our planet. Statistical methods complex survey design and analysis have equally gained significance as a consequence. However, there exist many challenges still, to infer such assessments over the target population for policy level advocacy and implementation. ^ Objective. This study discusses the use of some of the statistical methods for disaster preparedness and medical needs assessment to facilitate local and state governments for its policy level decision making and logistic support to avoid any loss of life and property in future calamities. ^ Methods. In order to obtain precise and unbiased estimates for Medical Special Needs Persons (MSNP) and disaster preparedness for evacuation in Rio Grande Valley (RGV) of Texas, a stratified and cluster-randomized multi-stage sampling design was implemented. US School of Public Health, Brownsville surveyed 3088 households in three counties namely Cameron, Hidalgo, and Willacy. Multiple statistical methods were implemented and estimates were obtained taking into count probability of selection and clustering effects. Statistical methods for data analysis discussed were Multivariate Linear Regression (MLR), Survey Linear Regression (Svy-Reg), Generalized Estimation Equation (GEE) and Multilevel Mixed Models (MLM) all with and without sampling weights. ^ Results. Estimated population for RGV was 1,146,796. There were 51.5% female, 90% Hispanic, 73% married, 56% unemployed and 37% with their personal transport. 40% people attained education up to elementary school, another 42% reaching high school and only 18% went to college. Median household income is less than $15,000/year. MSNP estimated to be 44,196 (3.98%) [95% CI: 39,029; 51,123]. All statistical models are in concordance with MSNP estimates ranging from 44,000 to 48,000. MSNP estimates for statistical methods are: MLR (47,707; 95% CI: 42,462; 52,999), MLR with weights (45,882; 95% CI: 39,792; 51,972), Bootstrap Regression (47,730; 95% CI: 41,629; 53,785), GEE (47,649; 95% CI: 41,629; 53,670), GEE with weights (45,076; 95% CI: 39,029; 51,123), Svy-Reg (44,196; 95% CI: 40,004; 48,390) and MLM (46,513; 95% CI: 39,869; 53,157). ^ Conclusion. RGV is a flood zone, most susceptible to hurricanes and other natural disasters. People in the region are mostly Hispanic, under-educated with least income levels in the U.S. In case of any disaster people in large are incapacitated with only 37% have their personal transport to take care of MSNP. Local and state government’s intervention in terms of planning, preparation and support for evacuation is necessary in any such disaster to avoid loss of precious human life. ^ Key words: Complex Surveys, statistical methods, multilevel models, cluster randomized, sampling weights, raking, survey regression, generalized estimation equations (GEE), random effects, Intracluster correlation coefficient (ICC).^

Statistical issues on studies of mixed longitudinal design

Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^

The use of second-generation antipsychotics and the changes in physical growth in children and adolescents with perinatally acquired HIV.

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.

Impact of medications prescribed for treatment of attention-deficit hyperactivity disorder on physical growth in children and adolescents with HIV.

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.

Changes in serum lipids with change and fluctuation in body mass index and body fat distribution in Mexican Americans with type 2 diabetes

This dissertation was written in the format of three journal articles. Paper 1 examined the influence of change and fluctuation in body mass index (BMI) over an eleven-year period, on changes in serum lipid levels (total, HDL, and LDL cholesterol, triglyceride) in a population of Mexican Americans with type 2 diabetes. Linear regression models containing initial lipid value, BMI and age, BMI change (slope of BMI), and BMI fluctuation (root mean square error) were used to investigate associations of these variables with change in lipids over time. Increasing BMI over time was associated with gains in total and LDL cholesterol and triglyceride levels in women. Fluctuation of BMI was not associated with detrimental lipid profiles. These effects were independent of age and were not statistically significant in men. In Mexican-American women with type 2 diabetes, weight reduction is likely to result in more favorable levels of total and LDL cholesterol and triglyceride, without concern for possible detrimental effects of weight fluctuation. Weight reduction may not be as effective in men, but does not appear to be harmful either. ^ Paper 2 examined the associations of upper and total body fat with total cholesterol, HDL and LDL cholesterol, and triglyceride levels in the same population. Multilevel analysis was used to predict serum lipid levels from total body fat (BMI and triceps skinfold) and upper body fat (subscapular skinfold), while controlling for the effects of sex, age and self-correlations across time. Body fat was not strikingly associated with trends in serum lipid levels. However, upper body fat was strongly associated with triglyceride levels. This suggests that loss of upper body fat may be more important than weight loss in management of the hypertriglyceridemia commonly seen in type 2 diabetes. ^ Paper 3 was a review of the literature reporting associations between weight fluctuation and lipid levels. Few studies have reported associations between weight fluctuation and total, LDL, and HDL cholesterol and triglyceride levels. The body of evidence to date suggests that weight fluctuation does not strongly influence levels of total, LDL and HDL cholesterol and triglyceride. ^

Evaluation of therapist and client language in Motivational Interviewing (MI) sessions: A secondary analysis of data from the Southern Methodist Alcohol Research Trial (SMART) study

In the United States, “binge” drinking among college students is an emerging public health concern due to the significant physical and psychological effects on young adults. The focus is on identifying interventions that can help decrease high-risk drinking behavior among this group of drinkers. One such intervention is Motivational interviewing (MI), a client-centered therapy that aims at resolving client ambivalence by developing discrepancy and engaging the client in change talk. Of late, there is a growing interest in determining the active ingredients that influence the alliance between the therapist and the client. This study is a secondary analysis of the data obtained from the Southern Methodist Alcohol Research Trial (SMART) project, a dismantling trial of MI and feedback among heavy drinking college students. The present project examines the relationship between therapist and client language in MI sessions on a sample of “binge” drinking college students. Of the 126 SMART tapes, 30 tapes (‘MI with feedback’ group = 15, ‘MI only’ group = 15) were randomly selected for this study. MISC 2.1, a mutually exclusive and exhaustive coding system, was used to code the audio/videotaped MI sessions. Therapist and client language were analyzed for communication characteristics. Overall, therapists adopted a MI consistent style and clients were found to engage in change talk. Counselor acceptance, empathy, spirit, and complex reflections were all significantly related to client change talk (p-values ranged from 0.001 to 0.047). Additionally, therapist ‘advice without permission’ and MI Inconsistent therapist behaviors were strongly correlated with client sustain talk (p-values ranged from 0.006 to 0.048). Simple linear regression models showed a significant correlation between MI consistent (MICO) therapist language (independent variable) and change talk (dependent variable) and MI inconsistent (MIIN) therapist language (independent variable) and sustain talk (dependent variable). The study has several limitations such as small sample size, self-selection bias, poor inter-rater reliability for the global scales and the lack of a temporal measure of therapist and client language. Future studies might consider a larger sample size to obtain more statistical power. In addition the correlation between therapist language, client language and drinking outcome needs to be explored.^

The impact of a child's unexpected hospitalization upon Taiwanese parents' situational anxiety

Background. The parents of a sick child likely experience situational anxiety due to their young child being unexpectedly hospitalized. The emotional upheaval may be great enough that their anxiety inhibits them in providing positive support to their hospitalized child. Because anxiety affects psychological distress as well as behavioral distress, identifying parental distress helps parents improving their coping mechanisms. ^ Purpose. The study compared situational anxiety levels between Taiwanese fathers and mothers and focused on differences between parental anxiety levels at the beginning of the child's unplanned hospitalization and at time of discharge. The study also identified factors related to the parents' distress and use of coping mechanisms. ^ Methods. A descriptive, comparative research design was used to determine the difference between the anxiety levels of 62 Taiwanese father-mother dyads during the situational crisis of their child's unexpected hospitalization. The Mandarin version (M) of Visual Analog Scale (VAS-M), State-Trait Anxiety Inventory (STAI-M), and the Index of Parent Participation/Hospitalized Child (IPP/HC-M) were used to differentiate maternal and paternal anxiety levels and identify factors related to the parents' distress. Questionnaires were completed by parents within 24-36 hours of the child's hospital admission and within 24 hours prior to discharge. A paired t-test, two sample t-test, and linear mixed regression model were used to test and support the study hypothesis. ^ Results. The findings reveal that the mothers' anxiety levels did not significantly differ from the fathers' anxiety level when their child had a sudden admission to the hospital. In particular, parental state anxiety levels did not decrease during the child's hospital stay and subsequent discharge. Moreover, anxiety levels did not differ between parents regardless of whether the child's disease was acute or chronic. The most effective factor related to parental situational anxiety was parental perception of the severity of the child's illness. ^ Conclusions. Parental anxiety was found to be significantly related to changes in their perception of the severity of their child's illness. However, the study was not able to illustrate how parental involvement in the child's hospital care was related to parental perception of the severity of their child's illness. Future studies, using a qualitative approach to gamer more information as to what variables influence parental anxiety during a situational crisis, may provide a richer database from which to modify key variables as well as the instruments used to improve the quality of the data obtained. ^

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

Health significance of chlorination byproducts in drinking water: The Houston experience: A continuation study

Background. Houston, Texas, once obtained all its drinking water from underground sources. However, in 1853, the city began supplementing its water from the surface source Lake Houston. This created differences in the exposure to disinfection byproducts (DBPs) in different parts of Houston. Trihalomethanes (THMs) are the most common DBP and are useful indicators of DBPs in treated drinking water. This study examines the relationship between THMs in chlorinated drinking water and the incidence of bladder cancer in Houston. ^ Methods. Individual bladder cancer deaths, from 1975 to 2004, were assigned to four surface water exposure areas in Houston utilizing census tracts—area A used groundwater the longest, area B used treated lake water the longest, area C used treated lake water the second longest, and area D used a combination of groundwater and treated lake water. Within each surface water exposure area mortality rates were calculated in 5 year intervals by four race-gender categories. Linear regression models were fitted to the bladder cancer mortality rates over the entire period of available data (1990–2004). ^ Results. A decrease in bladder cancer mortality was observed amongst white males in area B (p = 0.030), white females in area A (p = 0.008), non-white males in area D (p = 0.003), and non-white females in areas A and B (p = 0.002 & 0.001). Bladder cancer mortality differed by race-gender and time (p ≤ 0.001 & p ≤ 0.001), but not by surface water exposure area (p = 0.876). ^ Conclusion. The relationship between bladder cancer mortality and the four surface water exposure areas (signifying THM exposure) was insignificant. This result could be attributable to Houston controlling for THMs starting in the early 1980’s by using chloramine as a secondary disinfectant in the drinking water purification process.^