Thesis (D.P.H.)--University of Michigan, 1994.

Thesis (D.P.H.)--University of Michigan, 1994.

Evidence available shows that the ethics review process in Malaysia suffers from a range of problems (Kaur, 2011). These problems may be the result of a lack of training given for REC members and relatedly, it may stem from a lack of understanding of the role of RECs. Since Malaysia is striving to promote the country as a research hub for international collaboration, it is important that the ethics review system that is in place is well set up to ensure only ethical research are being approved. The aim of this thesis is to develop three important key elements of a framework that can be used to provide practical guidance for RECs and their governance in Malaysia. These three important elements of the ethics review process are: - the role of RECs, the criteria of REC membership and the acceptability of variation in decisions made between different RECs. These analysis is then applied to the Malaysian context. My initial recommendation is for RECs to adopt the Daniels and Sabin (1997) accountability for reasonableness model to assist with the decision-making process. The adoption of the model helps to clarify the role of RECs and can be used as a basis to develop the criteria for REC membership as well as to provide a better understanding of the acceptability of variation in decisions between different RECs.

No description available.

Efficient allocation of scarce resources to health programs involves measuring the economic benefits of life saving and/or improvement in health status. While several attempts have been made to quantify individual preferences for life, only a few, if any, have attempted to measure individual preferences for quality of life. In this thesis, we develop a methodology based on the estimation of individual preference functions to arrive at monetary measures of the value of marginal improvements in health status. / The first chapter reviews conventional methodologies for estimating the value of human life, and points out many theoretical and empirical propositions related to our own concerns. The second chapter analyzes various procedures used to quantify variations in health status. We distinguish non-monetary procedures, which combine recent psychometric techniques and research on health level scaling to obtain estimates of the relative desirability of a state of health, and monetary procedures which, we conclude, still need to be developed. / The third chapter presents a new methodology based on the direct estimation of bivariate welfare function of income and level of health. The theoretical basis of our approach and the data source are described in this chapter. Various functional forms were tried but we have finally retained the log-normal specification to derive estimates of the monetary value of a marginal change in the state of health for different subgroups of individuals. / We conclude with critical discussion of our results. Some improvements over the approach used are suggested in the fifth chapter.

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning; and, (M.S.)--Massachusetts Institute of Technology, Alfred P. Sloan School of Management, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES, DEWEY, AND ROTCH. / Bibliography: leaves 95-97. / by Lisa Joy Endlich. / M.C.P.

Thesis ( MPH.) --University of Limpopo, 2014 / The purpose of this study was to investigate the knowledge and practices among households at Ga-Mokgwathi Village regarding the disposal of mercury coated bulbs. Cross-sectional design with quantitative approach was used in this study. The study objectives were to determine the knowledge about the disposal methods of mercury coated bulbs and also to determine the practices of handling broken mercury coated bulbs among the villagers of Ga-Mokgwathi. Data collection was done using self-administered questionnaires. Cluster random sampling was used in the study where a total number of 338 households were randomly selected to participate in the study. The results indicated that 36.7 % of the households at Ga-Mokgwathi Village had knowledge of safe disposal methods of mercury coated bulbs, 7.7% were not sure and 55.6% did not have such knowledge. Furthermore, the results indicated that 51.5% of the households had improper practices regarding the handling of broken mercury coated bulbs, 6.2% were not sure and 42.3% had proper practices regarding the handling of broken mercury coated bulb. The results of the study concluded that the majority of people were lacking knowledge of proper disposal methods and the handling of mercury coated bulbs. These results necessitate education of people about the disposal methods and handling of mercury coated bulbs.

No description available.

Fine particulate matter (PM2.5) is the leading public health risk factor of global disease burden, which has caused 4.2 million deaths in 2015. This thesis aims to improve the scientific understanding on the sources and health impacts of PM2.5 in Hong Kong. Various chemical and biological analytical techniques were applied to characterize the chemical and toxicological properties of PM2.5 samples collected in Hong Kong during 2011-2012. Positive matrix factorization (PMF), together with the quantified chemical markers and water-soluble PM2.5-induced reactive oxygen species (ROS) activity as the input matrix, was performed to apportion the source-specific contributions to ambient organic carbon (OC) and the oxidative potential of water-soluble PM2.5. Zebrafish was applied as in-vivo model to evaluate the PM2.5-induced differential expression genes (DEGs). An L2-normaliztion integrated PMF was developed and applied to quantitatively assess the ability of PM2.5 to induced DEGs in relation to various sources and chemical compositions of PM2.5. The main findings are summarized below: (1) Thirty nine primary organic aerosol (POA) and secondary organic aerosol (SOA) markers of various anthropogenic (i.e. biomass burning (BB)) and biogenic sources (i.e. isoprene, monoterpenes and β-caryophyllene) were identified and quantified. High levels of OC and SOA markers were observed on regional pollution days than long regional transport (LRT) pollution and local emissions days. A kinetic model (Kintecus) was applied to explore the major formation channels of isoprene SOA, and it was found that isoprene SOA was mainly formed through the ring-opening reaction of isoprene epoxydiols (IEPOX) in Hong Kong. (2) PMF analysis, together with the chemical markers measured in Chapter 1 &2, was performed to evaluate the sources of OA in Hong Kong. Sea salt, marine vessels, vehicle emissions, BB/SOA, SOA, and secondary sulfate (SS) were apportioned as the major sources of ambient OC in Hong Kong. Secondary formation, including SOA, BB aging and SS sources, was found to be the major contributor to OC (~51%) throughout the whole year. BB was the major anthropogenic contributor to OC on regional days (28.8%); while marine vessel was the dominated primary source of OC on local days (33.2%). SOC concentrations were estimated using a tracer-based method (SOCTBM) and PMF (SOCPMF). Both SOCTBM and SOCPMF showed highest concentrations on regional days (SOCTBM: 0.74 µg m-3; SOCPMF: 3.27 µg m-3). Among all SOA precursors, monoterpenes had the most abundant contribution (40.9%) to SOCTMB during the whole year. Moreover, sulfate has significant impacts on SS-related SOC and SOA from monoterpenes and naphthalene. Particle acidity (HP+) showed correlation with SOC from BB aging. These results provide us a quantitative understanding on the SOA origins in the region, which lays a foundation for the source apportionment of PM2.5-induced toxicity in the following chapters. (3)Cell-free dithiothreitol (DTT) and ·OH generation assays were applied to measure the ROS activity induced by water-soluble PM2.5 collected in Hong Kong during 2011-2012. Different levels of ROS activity were observed for different chemical fractions of PM2.5 and PM2.5 from various sources. Six factors, i.e. SS, BB, SOA, vehicle emissions, marine vessels and metal factors were apportioned by PMF as the major sources of water-soluble PM2.5 induced ROS potential. Metal factors was found to be the major contributor to both DTT activity (39.1%) and ·OH generation ability (84.5%) throughout the year, especially on LRT (DTT: 54.8%; ·OH generation: 91.1%) and regional days (DTT: 53.9%; ·OH generation: 87.7%). On local days, contribution of marine vessels to DTT oxidation become more significant (48.7%), however its contribution to ·OH generation is negligible. Metal factors is by far the most significant contributor to ·OH generation, even on local days (73.1%). It is interesting to note that all six PMF-resolved sources are associated with DTT oxidation, however only three sources (i.e. metal factor, vehicle emissions and SOA) showed contributions to ·OH generation. Moreover, among these six sources, marine vessels exhibited the highest intrinsic DTT ability; while metal factor was the most effective source in ·OH generation. (4) Zebrafish embryo (AB strain) was applied as the in-vivo model to assess PM2.5 toxicity in Hong Kong through genome-wide gene transcriptional analysis. The results showed that embryonic exposure to PM2.5 could induce remarkable changes in gene expression patterns in zebrafish. DEGs between PM2.5 extract treated and untreated zebrafish embryo samples were identified, and they were found mainly associated with responses to xenobiotic stimulus, and muscle and heart development and functions. The correlation analysis between co-expressed gene modules and chemical species of PM2.5 implied the different chemical compositions and sources of PM2.5 have significant influences on the PM2.5-induced biological responses. (5) An L2-normalizaiton integrated PMF was developed to analyze the high throughput biological and chemical data simultaneously, which quantitatively evaluated the ability of PM2.5 to induce DEGs in relation to sources and compositions. In this chapter, nine sources associated with PM2.5-induced DEGs were well apportioned, i.e. fresh sea salt, aged sea salt, SS, SOA, BB, coal combustion, vehicle emissions, marine vessels and metal factors. Among these sources, metal factors (annual mean: 26.5%, range: 17.6-39.3%) and vehicle emissions (annual mean: 16.3%, range: 0.0-25.3%) are the two leading contributors to PM2.5-induced DEGs levels. PM2.5 from combustion related sources (e.g. vehicle emissions, metal factors, BB) and sea salt exhibited stronger ability to induce DEGs than those from secondary sources. Although secondary formation (including SOA and SS) has a significant contribution to ambient PM2.5 (12 μg m-3, 40%), its capacity of DEGs induction is quite low. Moreover, several biological functions and pathways influenced by PM2.5 from various sources have also been well evaluated. In this study, large scales of biological and chemical data were analyzed for the first time by a L2-normalizaiton integrated PMF to apportion the PM2.5-induced DEGs, and this thesis work firstly reported the major sources of water-soluble PM2.5-induced ROS in Hong Kong. Results from this study provide a scientific basis for the prediction of PM2.5-associated adverse health outcomes and can help the policy makers to formulate cost-effective and targeted PM2.5 mitigation strategies to protect public health.;Fine particulate matter (PM2.5) is the leading public health risk factor of global disease burden, which has caused 4.2 million deaths in 2015. This thesis aims to improve the scientific understanding on the sources and health impacts of PM2.5 in Hong Kong. Various chemical and biological analytical techniques were applied to characterize the chemical and toxicological properties of PM2.5 samples collected in Hong Kong during 2011-2012. Positive matrix factorization (PMF), together with the quantified chemical markers and water-soluble PM2.5-induced reactive oxygen species (ROS) activity as the input matrix, was performed to apportion the source-specific contributions to ambient organic carbon (OC) and the oxidative potential of water-soluble PM2.5. Zebrafish was applied as in-vivo model to evaluate the PM2.5-induced differential expression genes (DEGs). An L2-normaliztion integrated PMF was developed and applied to quantitatively assess the ability of PM2.5 to induced DEGs in relation to various sources and chemical compositions of PM2.5. The main findings are summarized below: (1) Thirty nine primary organic aerosol (POA) and secondary organic aerosol (SOA) markers of various anthropogenic (i.e. biomass burning (BB)) and biogenic sources (i.e. isoprene, monoterpenes and β-caryophyllene) were identified and quantified. High levels of OC and SOA markers were observed on regional pollution days than long regional transport (LRT) pollution and local emissions days. A kinetic model (Kintecus) was applied to explore the major formation channels of isoprene SOA, and it was found that isoprene SOA was mainly formed through the ring-opening reaction of isoprene epoxydiols (IEPOX) in Hong Kong.

Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is to assume there are latent clusters of individuals in the population which each generate their own distinct distribution of observations (multivariate or univariate) which are then mixed up together in the full population. Hence, the name mixture comes from the fact that what we observe is a mixture of distributions. The goal of this model-based clustering technique is to identify what the mixture of distributions is so that, given a particular response pattern, individuals can be clustered accordingly. Commonly, finite mixture models, as well as the special case of latent class analysis, are used on data that inherently involve repeated measures. The purpose of this dissertation is to extend the finite mixture model to allow for the number of repeated measures to be incorporated and contribute to the clustering of individuals rather than measures. The dimension of the repeated measures or simply the count of responses is assumed to follow a truncated Poisson distribution and this information can be incorporated into what we call a dimension informative finite mixture model (DIMM). The outline of this dissertation is as follows. Paper 1 is entitled, "Dimension Informative Mixture Modeling (DIMM) for questionnaire data with an informative number of repeated measures." This paper describes the type of data structures considered and introduces the dimension informative mixture model (DIMM). A simulation study is performed to examine how well the DIMM fits the known specified truth. In the first scenario, we specify a mixture of three univariate normal distributions with different means and similar variances with different and similar counts of repeated measurements. We found that the DIMM predicts the true underlying class membership better than the traditional finite mixture model using a predicted value metric score. In the second scenario, we specify a mixture of two univariate normal distributions with the same means and variances with different and similar counts of repeated measurements. We found that that the count-informative finite mixture model predicts the truth much better than the non-informative finite mixture model. Paper 2 is entitled, "Patterns of Physical Activity in the Northern Manhattan Study (NOMAS) Using Multivariate Finite Mixture Modeling (MFMM)." This is a study that applies a multivariate finite mixture modeling approach to examining and elucidating underlying latent clusters of different physical activity profiles based on four dimensions: total frequency of activities, average duration per activity, total energy expenditure and the total count of the number of different activities conducted. We found a five cluster solution to describe the complex patterns of physical activity levels, as measured by fifteen different physical activity items, among a US based elderly cohort. Adding in a class of individuals who were not doing any physical activity, the labels of these six clusters are: no exercise, very inactive, somewhat inactive, slightly under guidelines, meet guidelines and above guidelines. This methodology improves upon previous work which utilized only the total metabolic equivalent (a proxy of energy expenditure) to classify individuals into inactive, active and highly active. Paper 3 is entitled, "Complex Drug Use Patterns and Associated HIV Transmission Risk Behaviors in an Internet Sample of US Men Who Have Sex With Men." This is a study that applies the count-informative information into a latent class analysis on nineteen binary drug items of drugs consumed within the past year before a sexual encounter. In addition to the individual drugs used, the mixture model incorporated a count of the total number of drugs used. We found a six class solution: low drug use, some recreational drug use, nitrite inhalants (poppers) with prescription erectile dysfunction (ED) drug use, poppers with prescription/non-prescription ED drug use and high polydrug use. Compared to participants in the low drug use class, participants in the highest drug use class were 5.5 times more likely to report unprotected anal intercourse (UAI) in their last sexual encounter and approximately 4 times more likely to report a new sexually transmitted infection (STI) in the past year. Younger men were also less likely to report UAI than older men but more likely to report an STI.