This study is based on an a priori hypothesis for a particular SNP in the SIRT5 gene (rs9382222; C¨T) for which we have evidence that the common C-allele is associated with an older biological age of the brain. Digit Symbol Substitution Test (DSST), 20 meters timed-walk (Gait Test) and Epidemiological Studies Depression Scale (CES-D) are functional markers of brain health and applicable tests to measure cognitive function, motor function and depressed mood. HYPOTHESIS: At baseline, subjects carrying the common C/C risk genotype at the SIRT5 SNP will display poorer function on cognitive function tests (lower DSST score) and motor function tests (longer time to walk 20 meters), and have increased self-reported symptoms of a depressed mood (higher CES-D score), as compared to all other subjects. METHODS: The linear model type, one-way analysis of covariance (ANCOVA), was fitted using SAS GLM procedure to test for between-group differences in functional outcomes. Concordance in SNP effects were investigated for the three interrelated functional markers in subjects carrying the specific genotype (C/C, C/T, T/T). RESULTS: We detected a borderline significant association between DSST and SNP in the black population (p=0.051, mean diff.=-0.05, SD=0.95) with C/C subjects displaying lower DSST scores vs. C/T (almost 2 units lower than heterozygotes). There is a trend for an association between CES-D and SNP in the white population (p=0.08, mean diff.=-1.85, SD=0.03) with the C/C risk group reporting higher depression-like symptoms vs. C/T. Gait Test were no statistical significant associated to the SNP. CONCLUSIONS: The C/C previously linked with older biological brain age was associated with (1) lower DSST scores in the black population and (2) displayed trend-level higher CES-D depressive-like scores in the white population, hence suggesting the SIRT5 C/C genotype as a probable risk factor for both biological brain age and related functional outcomes. PUBLIC HEALTH SIGNIFICANCE: Emotional and cognitive fitness is rapidly becoming a major determinant to the quality of life during old age. Study the genetic component of the brain aging as this SNP would help to 1) identify people at risk, and 2) address public health programs to achieve a successful aging.

Background Birth-weight and infant mortality are both important indicators of the health of populations. Unfortunately, these measures have not been studied to a great extent in India, where high rates of both birth-weight and infant mortality persist. This is, in part due to a dearth of quality data from India and lack of methods to adjust the existing data for digit preference (heaping). Beyond that, while there has been extensive study of the birth-weight to infant mortality relationship in the developed world, this topic has remained basically unexplored in India. In order to develop methods to reduce the high rates of IM in India and better understand the role of birth-weight as a determinant of infant mortality, population specific studies are needed. Methodology Using data from a cohort in rural South India, we developed a method of adjusting BW data to account for heaping. Using data from a nationally representative survey of all of India, and US vital statistics, we compared characteristics of the BW to IM relationship in India and the United States. Finally, we analyzed data from rural India to identify predictors of very small birth-weight and infant mortailty in that specific population. Results Our method of adjusting birth-weight data to account for heaping using modified statistical calibration and multiple imputation produced imputed birth-weight data sets that reduced heaping and preserved known associations. After comparing the US and India, we found that the relative contribution of birth-weight to infant mortality in India is reduced. We also found differences between the US and Indian birth-weight distributions and infant mortality curves. Finally, we determined that measures of sanitation and hygiene, acting as surrogates for infectious disease exposure, were significant predictors of both lower birth-weight and infant mortality in a rural population in South India. Conclusions While birth-weight and infant mortality have not been studied to a great extend in the developing world due to issues with data quality and sources, statistical methods can be used to address these issues. Being able to adjust birth-weight data and study it and infant mortality in an Indian population showed that characteristics of these measures are not the same across countries. Also, birth-weight may not be as important a factor in determining infant mortality in India as it is in the US. Therefore, finding other causes of infant mortality is extremely important to address this problem. To that end, we found that sanitation and hygiene are strongly associated with the high rates of infant mortality in a rural Indian population. Public Health Significance The methods developed here can be used and applied to study birth-weight data in other developing country populations. The comparison of the US and India highlighted the fact that current policies to reduce infant mortality in India may be misguided. Finally, our data suggest that an intervention to improve sanitation and hygiene in order to reduce infant mortality could be successful and could also be used in other populations with high rates of infant death.

The performance of vaccine logistics systems (i.e., the steps in a supply chain necessary to get vaccines from manufacturers to patients) can impact whether vaccines are delivered at the right time, place and in the right condition for patients during immunization sessions. Immunization coverage in a population depends on a well-functioning vaccine supply chain. If target populations are not immunized before exposure, they are left unprotected against vaccine preventable diseases (VPDs) and can contribute to infectious disease transmission in their communities. Changes may be made to logistics systems without considering their potential effects on vaccine distribution and availability at vaccinating health centers. The combined works of this dissertation illustrate such changes and resulting impacts on vaccine availability, including: changes to vaccine presentations, changes to the vaccine supply chain structure, and changes to a vaccine regimen. The Vaccine Modeling Initiative (VMI) developed the Highly Extensible Resource for Modeling Supply chains (HERMES), a stochastic, discrete-event simulation model. VMI collected information on vaccine cold chain equipment (e.g., refrigerators and freezers), transportation fleets, demographic indicators for target populations, and supply chain operating policies (e.g., shipping frequencies) for the country Niger and for Trang province in Southern Thailand. HERMES was then used to evaluate various supply chain interventions and determine their impacts on logistics indicators including: vaccine availability at health centers, transportation and storage utilization, and additional capacity requirements. With over a dozen new vaccines being introduced into national immunization programs in the next decade, logistics systems will be further pressed to ensure vaccines are delivered to their target populations. These studies will highlight the importance of considering vaccine logistics systems when making changes to immunization programs, and suggest potential alternative strategies to improve the performance of supply chains and ultimately vaccination coverage rates. Furthermore, these studies will demonstrate the utility in using computational models to evaluate and provide solutions for public health challenges by representing relationships that would not otherwise be apparent.

<p> <u>Aim</u>: The objective of this study was to investigate socioeconomic and personal network factors as predictors for Major Depressive Disorder (MDD) in women, especially within their reproductive transition period. </p><p> <u>Design</u>: Cross-sectional </p><p> <u>Methods</u>: Questionnaire data from the 2008 Behavioral Risk Factor Surveillance Survey (BRFSS) in combination with a DSM-IV diagnostic algorithm was used to assess the risk factors associated with female depression. A total of 19,771 women were grouped according to age based upon clinically defined reproductive status: 18-35, 36-45, >45 years. A scoring system of 0 to 24 was created to assess for severity of depressive symptoms, and female participants with outcomes &ge;10 met the criteria for MDD. Logistic regression was used to determine predictive factors stratified by each age group of women. </p><p> <u>Results</u>: Unemployment was a significant predictor of MDD for women in their transition period (OR = 2.05, CI 90% 1.21, 3.47). Reproductive transitioning women also had higher odds of MDD when there was little to no emotional support (OR = 4.59, CI 90% 2.86, 7.38), and poor self-reported health (OR= 2.73, CI 90% 1.44, 5.17). More frequent days of poor health and inadequate rest were also significant for the women during their menopausal transition. </p><p> <u>Conclusion</u>: The following study provides a significant platform for improved research on female mental health, particularly across the life span. More intensive research is needed to understand possible associative relationships between female age and depression, in order to initiate appropriate intervention programs.</p>

In this dissertation, I conducted epidemiological secondary data analysis of two serial cross-sectional surveys to explore prevalence and risk factors for HIV and syphilis among men who have sex with men (MSM) in Chongqing City in southwestern China. I first looked into the predictors, barriers, and facilitators of HIV testing. Among 492 MSM surveyed in 2010, 58% had ever been tested for HIV. Prior HIV testing was associated with having a college degree (adjusted odds ratio [aOR]: 1.7, 95% confidence interval [CI]: 1.2-2.6), having used condoms with the most recent male partner (aOR: 2.9, 95% CI: 1.3-6.6), and preferring receptive anal sex roles (aOR: 0.6, 95% CI: 0.4-0.9). Fear of knowing a positive result was the major barrier. I then assessed predictors for HIV infection itself among 975 MSM in 2009 and 2010, excluding duplicate participants in 2010. The HIV prevalence was 15.1% and syphilis prevalence was 5.7%. HIV infection was associated with non-Han minorities (aOR: 0.2, 95% CI: 0.1-0.6), non-student MSM who attained (aOR: 2.7, 95% CI: 1.2-5.9) or who did not attain a college degree (aOR: 6.9, 95% CI: 3.2-15.2), and syphilis infection (aOR: 5.8, 95% CI: 3.0-11.4). I further examined HIV risks among student MSM. Among 503 MSM surveyed in 2009, 36% were registered students with an HIV prevalence of 5.5%. Both non-student college graduates (aOR: 3.5; 95% CI: 1.3-9.5) and non-college graduates (aOR: 5.7; 95% CI: 1.8-18.4) had higher risk of HIV infection than but similar risky sexual behaviors with student MSM Finally, I did a systematic review of Internet-based behavioral interventions for HIV prevention among MSM, anticipating new interventions to be considered . Among MSM aged 18 years or older, 5128 were enrolled in six eligible randomized controlled trials and one quasi-experimental study. Intervention effectiveness was inconsistent. A pooled effect estimate was unable to be calculated due to significant heterogeneity of the interventions and the outcomes. In summary, MSM in Chongqing, China, are at very high risk for HIV and syphilis infections, including risk among college students. These analyses provide an evidence-base for planning focused interventions in key sub-populations to maximize testing, prevention, and therapy.

Risk of miscarriage (i.e. a pregnancy loss before 20 completed weeks of gestation) is known to differ by race but timing of loss is not well established in the literature. The gap between biological pregnancy loss identified by ultrasound and clinical manifestation of that loss may bias effect estimates for early-pregnancy exposures associated with miscarriage. Right from the Start (RFTS) is a unique and diverse prospective pregnancy cohort that captures uniform early first-trimester ultrasound information and pregnancy-related behaviors from first-trimester interviews in order to study the distribution of this gap. Nearly 13% of women in this cohort experienced a pregnancy loss (n=697), the majority of whom have ultrasound data available (73%, n=509). Ultrasounds were conducted between 40 and 95 days gestation from last menstrual period (LMP) for this cohort. Gestational arrest prior to miscarriage was observed in 38.7% of losses (n=197). The mean gap between LMP and estimated gestational age at arrested development (GAAD) was 19.3 ± 15.0 days (median GAAD gap was 19 days). The GAAD gap did not differ by race or pregnancy intention. In order to determine if failing to account for this gap influences effect estimates we assessed exposures commonly associated with pregnancy loss. We compared models that estimated gestational age based on self-reported LMP and models that incorporated gestational age at time of arrested development (GAAD). We used bootstrap methods to determine the magnitude of bias for both models. Smoking during pregnancy was not modified by race and was not associated with miscarriage risk within this cohort for either current or former smokers compared to never smokers in either model. Stratified by race and adjusted for confounding, the protective effect of vitamin use on miscarriage risk was stronger among White women than Black women when using the LMP models (Whites aHR=0.34, 95% CI [0.21, 0.54]; Blacks aHR=0.53, 95% CI [0.33, 0.84]), while no substantial difference by race was observed with the GAAD models (Whites aHR=0.43, 95% CI [0.24, 0.76]; Blacks aHR=0.44, 95% CI [0.26, 0.74]). Models that use self-reported LMP to estimate gestational age underestimate the true value of first-trimester smoking exposure on miscarriage risk by as much as 15% for current smokers and 5% of former smokers when compared to models that use GAAD (the bootstrap bias ratio between models for current smokers ratio=0.85, 95% CI [0.75, 0.94]; for former smokers ratio=0.95, 95% CI [0.92, 0.97]). When stratified by race, the bias was nearly 20% for both Whites and Blacks for miscarriage risk associated with early pregnancy vitamin exposure (Whites bias ratio= 0.79, 95% CI [0.62, 0.87]; Blacks bias ratio=1.19, 95% CI [1.13, 1.45]). These results suggest that early-pregnancy exposures associated with miscarriage risk are influenced by proper classification of gestational arrest prior to loss, and that the magnitude and direction of bias differs by race. By more accurately identifying which insults have occurred prior to pregnancy arrest and differentiating them from exposures that occur after developmental arrest but before the onset of bleeding, we have a more optimal method to assess miscarriage risk by not mis-assigning exposure time.

Diss. (sammanfattning) Stockholm : Karol. inst. / Härtill 7 uppsatser.

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Residential energy efficiency is a major priority in the United States and abroad due to concerns related to climate change and the economic impacts of energy consumption. Energy retrofits can provide direct private and public savings as well as population health co-benefits as a result of reduced emissions from residential combustion and electricity generating units (EGUs). However, retrofits such as weatherization may also lead to reduced air exchange rates and accumulations of indoor-sourced pollutants. To protect indoor air quality (IAQ) and resident health, current building standards recommend coupling weatherization measures with ventilation; however, the combined impacts of these measures on energy costs, resident health, and general population health across diverse housing conditions have not been well-established. In this study, we used the multizone airflow and IAQ analysis program CONTAM to simulate the IAQ impacts of a real-world energy intervention in a specific low-income, low-rise multifamily housing complex. We evaluated the differential impact of indoor source activities, such as cooking and smoking, on indoor concentrations of PM2.5 and NO2. By co-simulating the CONTAM model with the energy simulation software EnergyPlus, we also examined the potential energy and IAQ trade-offs of meeting energy and ventilation building standards in a typical gas-heated midrise multifamily building. Lastly, we linked IAQ and energy simulation results from the midrise multifamily building to an energy-to-emissions model and health impact model to estimate the impacts of interventions on direct energy costs and monetized resident health and general population health. All building templates were located in Boston, MA. Overall, we found that combined investments in weatherization and ventilation retrofits could lead to energy savings and IAQ-related benefits; however, the direction and magnitude of benefits and/or disbenefits varied by intervention type and intensity, season, indoor source activity, and baseline ventilation parameters. Results suggest that some combinations of retrofits that provide energy savings may also lead to IAQ disbenefits for certain multifamily subpopulations, such as smokers in buildings without whole-building ventilation or filtration. We also found that weatherization interventions without ventilation upgrades led to increases in indoor PM2.5 levels and monetized resident health disbenefits that greatly outweighed direct energy savings and population health benefits. Together, results emphasize the importance of holistic energy-efficient interventions that explicitly consider IAQ and health. Our analytical framework can be utilized in future trade-off analyses to inform health-protective, cost-effective implementation approaches and building standards.

<p> Meningococcal meningitis is a burden in the African meningitis belt. Before 2010, <i>Neisseria meningitidis</i> serogroup A (<i> N. meningitidis</i> A) was the predominant pathogen causing deathly epidemics. MenAfriVac^&reg; vaccine protects against <i>N. meningitidis </i> A. It was introduced in 2010 into highest meningitis risk health districts. There was limited data on the effects of MenAfriVac^&reg;, mainly on the degree of relationship between <i>N. meningitidis </i> A and the MenAfriVac^&reg; immunization. The social ecological model was used as a theoretical framework for this study. The purpose of this quantitative study was to assess the effectiveness of MenAfriVac^&reg; from 2010 to 2017 in 21 out of 26 countries of the African meningitis belt. The four research questions contributed to establishing the effects of MenAfriVac^&reg;. An interrupted time series design and nonprobability sampling were used. Secondary data were retrieved from World Health Organization database. The binomial negative regression and Pearson&rsquo;s Chi-Square tests were used. The study found that after the MenAfriVac^&reg; introduction there were 39% decline of incidence rate of the meningitis suspected cases (IRR 0.61, 95% CI 0.48 &ndash; 0.79, p &lt; .001), a high degree of relationship between <i>N. meningitidis</i> A and MenAfriVac^&reg; immunization (&khgr;² (1) = 11039.49, p = 0.000, Phi = 0.657, P=0.000), 99% decline of the risk of <i>N. meningitidis </i> A (RR 0.01, 95% CI 0.08-0.013), and 99.6% decline of risk of epidemic due to <i>N. meningitidis</i> A (RR 0.004, 95% CI 0.001-0.016). The study demonstrated that high MenAfriVac^&reg; coverage and enhanced surveillance are pivotal to reduce the meningitis burden. Results will be used to inform policy and public health practice to reduce the meningitis cases and improve quality of live in the community.</p><p>