Social media mining for identification and exploration of health-related information from pregnant women

Widespread use of social media has led to the generation of substantial amounts of information about individuals, including health-related information. Social media provides the opportunity to study health-related information about selected population groups who may be of interest for a particular study. In this paper, we explore the possibility of utilizing social media to perform targeted data collection and analysis from a particular population group -- pregnant women. We hypothesize that we can use social media to identify cohorts of pregnant women and follow them over time to analyze crucial health-related information. To identify potentially pregnant women, we employ simple rule-based searches that attempt to detect pregnancy announcements with moderate precision. To further filter out false positives and noise, we employ a supervised classifier using a small number of hand-annotated data. We then collect their posts over time to create longitudinal health timelines and attempt to divide the timelines into different pregnancy trimesters. Finally, we assess the usefulness of the timelines by performing a preliminary analysis to estimate drug intake patterns of our cohort at different trimesters. Our rule-based cohort identification technique collected 53,820 users over thirty months from Twitter. Our pregnancy announcement classification technique achieved an F-measure of 0.81 for the pregnancy class, resulting in 34,895 user timelines. Analysis of the timelines revealed that pertinent health-related information, such as drug-intake and adverse reactions can be mined from the data. Our approach to using user timelines in this fashion has produced very encouraging results and can be employed for other important tasks where cohorts, for which health-related information may not be available from other sources, are required to be followed over time to derive population-based estimates.Comment: 9 page

Dental amalgam fillings: An under-investigated source of mercury exposure

Dental amalgam fillings, which contain about 50% mercury, have been used since the early 19th century. However, their use has been controversial, particularly because they continually release small amounts of mercury. Inorganic mercury is known to be highly toxic, particularly to the nervous system and kidneys, but exposures from amalgam fillings are generally well below those established as toxic. However, uncertainties about threshold concentrations of effect and the nature of any long-term exposure effects remain. Considering the long-standing and widespread use of these fillings, there has been remarkably little investigation of their safety and most epidemiologic studies have been relatively recent. In general, investigations to date have shown little evidence of effects on general chronic disease incidence or mortality. There have been few studies so far of neurodegenerative diseases and results have been equivocal. Assessments of the safety of dental amalgam have mainly been based on studies of occupationally exposed populations. However, the amalgam-exposed population contains a broader, potentially more susceptible, spectrum of people. In that regard, a number of studies of children that have found no evidence of health effects have provided some reassurance

Compounded Disadvantage: Race, Incarceration, and Wage Growth

Based on 14-year panel data on ex-prisoners, this paper reports the impact of incarceration on future job prospects. Black men, in addition to facing greater risk of ending up in prison, are more negatively affected by imprisonment than white men. The expansion of the U.S. criminal justice system is therefore responsible for compounding the disadvantages of African Americans

Drug Adverse Event Detection in Health Plan Data Using the Gamma Poisson Shrinker and Comparison to the Tree-based Scan Statistic

Background: Drug adverse event (AE) signal detection using the Gamma Poisson Shrinker (GPS) is commonly applied in spontaneous reporting. AE signal detection using large observational health plan databases can expand medication safety surveillance. Methods: Using data from nine health plans, we conducted a pilot study to evaluate the implementation and findings of the GPS approach for two antifungal drugs, terbinafine and itraconazole, and two diabetes drugs, pioglitazone and rosiglitazone. We evaluated 1676 diagnosis codes grouped into 183 different clinical concepts and four levels of granularity. Several signaling thresholds were assessed. GPS results were compared to findings from a companion study using the identical analytic dataset but an alternative statistical method—the tree-based scan statistic (TreeScan). Results: We identified 71 statistical signals across two signaling thresholds and two methods, including closely-related signals of overlapping diagnosis definitions. Initial review found that most signals represented known adverse drug reactions or confounding. About 31% of signals met the highest signaling threshold. Conclusions: The GPS method was successfully applied to observational health plan data in a distributed data environment as a drug safety data mining method. There was substantial concordance between the GPS and TreeScan approaches. Key method implementation decisions relate to defining exposures and outcomes and informed choice of signaling thresholds

Sources, blood concentrations, and approaches for reducing exposure to lead: A critical appraisal on lead poisoning

Lead, a non-essential metal, enters the body in various ways, making it a major public health issue. Painters and smelters report lead poisoning in children and staff. Mining and battery workers risk lead exposure. Traditional and cultural remedies may include dangerous quantities of lead, producing lead poisoning. These drugs must be properly understood and regulated to avoid toxicity. Lead poisoning symptoms vary by duration and severity. Lead first impairs cognition, development, and behaviour by damaging the neural system. Time degrades reproductive and haematological systems. Lead's quiet entry into the body makes it deadly. Acute lead nephropathy damages kidneys at 100mg/dL. Lead levels exceeding 150mg/dL may induce encephalopathy. Blood lead levels indicate lead poisoning severity. Lead levels over 10g/dL in children and 40g/dL in adults are hazardous. Lead toxicity affects various organs. Lead may induce hypertension and cardiovascular disease. It may also cause chronic kidney disease and renal failure. Lead exposure may impede fertility, cause miscarriages, and alter foetal development; hence the reproductive system is vulnerable. Symptoms and lead levels may be treated with different approaches. Lead chelation treatment is frequent. Other vitamins and medications may enhance organ function and treat lead poisoning. Lead poisoning prevention requires widespread awareness. Strict standards and education regarding lead-contaminated products and conventional remedies should reduce occupational lead exposure. Regular blood lead level monitoring, especially in youngsters and lead workers, may help detect and treat lead poisoning early. Lead poisoning has serious health consequences. Understanding lead exposure pathways, identifying symptoms, and preventing lead poisoning is essential to public health and organ system protection