Suspected outbreak of dengue fever in Houston: Clinical characteristics and determination of autochthonous transmission between 2003 and 2005

Houston, Texas maintains the appropriate climate and mosquito populations to support the circulation of dengue viruses. The city is susceptible to the introduction and subsequent local transmission of dengue virus with its proximity to dengue-endemic Mexico and the high degree of international travel routed through its airports. In 2008, a study at the University of Texas School of Public Health identified 58 suspected dengue fever cases that presented at hospitals and clinics in the Houston area. Serum or CSF samples of the 58 samples tested positive or equivocal for the presence of anti-dengue IgM antibodies (Rodriguez, 2008). Here, we present the results of an investigation aimed to describe the clinical characteristics of the 58 suspected dengue fever cases and to determine if local transmission had occurred. Data from medical record abstractions and personal telephone interviews were used to describe clinical characteristics and travel history of the suspected cases. Our analysis classified six probable dengue fever cases based on the case definition from the World Health Organization. Three of the probable cases for which we were able to obtain travel history had not recently traveled to an endemic area prior to onset of symptoms suggesting the illnesses were locally acquired in Houston. Further analysis led us to hypothesize that additional cases of dengue fever are present in our study population. Fifty-one percent of the study population was diagnosed with meningitis and/or encephalitis. Sixty percent of the individuals who received a lumbar puncture had abnormal CSF. Together these findings indicate viral infection with neurological involvement, which has been reported to occur with dengue fever. Among the individuals who received liver enzyme analysis, 54% had evidence of abnormal liver enzyme levels, a clinical sign commonly observed with dengue. Our results indicate that a suspected outbreak of dengue fever with autochthonous transmission occurred in the Houston area between 2003 and 2005. ^

Is depression associated with insulin resistance? A systematic review

Studies suggest that depression affects glucose metabolism, and therefore is a risk factor for insulin resistance. The association between depression and insulin resistance has been investigated in a number of studies, but there is no agreement on the results. The objective of this study is to survey the epidemiological studies, identify the ones that measured the association of depression (as exposure) with insulin resistance (as outcome), and perform a systematic review to assess the reliability and strength of the association. For high quality reporting, and assessment, this systematic review used the outlined procedures, guidelines and recommendations for reviews in health care, suggested by the Centre for Reviews and Dissemination, along with recommendations from the STROBE group (Strengthening the Reporting of Observational Studies in Epidemiology). Ovid MEDLINE 1996 to April Week 1 2010, was used to identify the relevant epidemiological studies. To identify the most relevant set of articles for this systematic review, a set of inclusion and exclusion criteria were applied. Six studies that met the specific criteria were selected. Key information from identified studies was tabulated, and the methodological quality, internal and external validity, and the strength of the evidence of the selected studies were assessed. The result from the tabulated data of the reviewed studies indicates that the studies either did not apply a case definition for insulin resistance in their investigation, or did not state a specific value for the index used to define insulin resistance. The quality assessment of the reviewed studies indicates that to assess the association between insulin resistance and depression, specifying a case definition for insulin resistance is important. The case definition for insulin resistance is defined by the World Health Organization and the European Group for the Study of Insulin Resistance as the insulin sensitivity index of the lowest quartile or lowest decile of a general population, respectively. Three studies defined the percentile cut-off point for insulin resistance, but did not give the insulin sensitivity index value. In these cases, it is not possible to compare the results. Three other studies did not define the cut-off point for insulin resistance. In these cases, it is hard to confirm the existence of insulin resistance. In conclusion, to convincingly answer our question, future studies need to adopt a clear case definition, define a percentile cut-off point and reference population, and give value of the insulin resistance measure at the specified percentile.^

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^

Subjective well -being as predictor of mortality, heart disease, and obesity: Prospective evidence from the Alameda County Study

Based on the World Health Organization's (1965) definition of health, understanding of health requires understanding of positive psychological states. Subjective Well-being (SWB) is a major indicator of positive psychological states. Up to date, most studies of SWB have been focused on its distributions and determinants. However, study of its consequences, especially health consequences, is lacking. This dissertation research examined Subjective Well-being, as operationally defined by constructs drawn from the framework of Positive Psychology, and its sub-scores (Positive Feelings and Negative Feelings) as predictors of three major health outcomes—mortality, heart disease, and obesity. The research used prospective data from the Alameda County Study over 29 years (1965–1994), based on a stratified, randomized, representative sample of the general public in Alameda County, California (Baseline N = 6928). ^ Multivariate analyses (Survival analyses using sequential Cox Proportional Hazard models in the cases of mortality and heart disease, and sequential Logistic Regression analyses in the case of obesity) were performed as the main methods to evaluate the associations of the predictors and the health outcomes. The results revealed that SWB reduced risks of all-cause mortality, natural-cause mortality, and cardiovascular mortality. Positive feelings not only had an even stronger protective effect against all-cause, natural-cause and cardiovascular mortality, but also predicted decreased unnatural-cause mortality which includes deaths from suicide, homicide, accidents, mental disorders, drug dependency, as well as alcohol-related liver diseases. These effects were significant even after adjusted for age, gender, education, and various physical health measures, and, in the case of cardiovascular mortality, obesity and health practices (alcohol consumption, smoking, and physical activities). However, these two positive psychological indicators, SWB and positive feelings, did not predict obesity. And negative feelings had no significant effect on any of the health outcomes evaluated, i.e., all-cause mortality, natural- and unnatural-cause mortality, cardiovascular mortality, or obesity, after covariates were controlled. These findings were discussed (1) in comparison with relevant existing studies, (2) in terms of their implications in health research and promotion, (3) in terms of the independence of positive and negative feelings, and (4) from a Positive Psychology perspective and its significance in Public Health research and practice. ^