Does more education always lead to better health? Evidence from rural malaysia

Background. Education is usually associated with improvement in health; there is evidence that this may not be the case if educationis not fully utilised at work. This study examines the relationship between education level, occupation, and health outcomes ofindividuals in rural Malaysia. Results. The study finds that the incidence of chronic diseases and high blood pressure are higher fortertiary educated individuals in agriculture and construction occupations. This brings these individuals into more frequent contactwith the health system. These occupations are marked with generally lower levels of education and contain fewer individuals withhigher levels of education. Conclusions. Education is not always associated with better health outcomes. In certain occupations,greater education seems related to increased chronic disease and contact with the health system, which is the case for workersin agriculture in rural Malaysia. Agriculture is the largest sector of employment in rural Malaysia but with relatively few educatedindividuals. For the maintenance and sustainability of productivity in this key rural industry, health monitoring and job enrichmentpolicies should be encouraged by government agencies to be part of the agenda for employers in these sectors

A pilot microbial assessment of beef sold in the Ashaiman market, a suburb of Accra, Ghana

Food safety is a matter of great public health concern worldwide and particularly crucial if the environment in which the food is handled is heavily contaminated. Most fresh foods particularly that of animal origin like beef is highly susceptible to microbial invasion and food poisoning. In poorly managed market environment particularly in Ghana, unhygienic practice is the major cause for food contamination. This study observed the hygienic practices and microbiological food safety standards of butchers who specifically sold beef in the Ashaiman market in Accra, Ghana. Hygienic practices of sixteen (16) butchers were randomly selected in a cross sectional study using an eight point scale checklist weekly over a period of four weeks. The microbial quality of one hundred and twenty-eight (128) fresh beef samples were aseptically collected and analysed using standard microbiological techniques. It was observed that majority of the butchers did not practice safe hygiene standards as recommended by the Ghana Food and Drugs Board and the Ghana Standards Board. The beef samples were contaminated with Aerobic mesophiles (189-23000 cfu/g), Staphylococcus aureus (22-59 cfu/g), Bacillus cereus (17-41 cfu/g), Clostridium perfringens (21-48 cfu/g) and Escherichia coli (31-2200 cfu/g). The pH of the beef samples were between 6.50 and 6.90. The butchers in Ashaiman market supplied fairly contaminated beef to the general public. Escherichia coli , which is a sign of faecal contamination, was the predominant microbial contaminant in the samples examined. The result of unhygienic practices and poor handling of beef by butchers in the Ashaiman market is the major cause of contaminated beef. There are chances that other meat sold by virtually the same group of persons could equally or even more be contaminated by food borne pathogens. Hence food industry and consumers should be made aware of the potential risk of food borne pathogens in beef sold by butchers in Ashaiman market

Humans as Animal Sentinels for Forecasting Asthma Events: Helping Health Services Become More Responsive

The concept of forecasting asthma using humans as animal sentinels is uncommon. This study explores the plausibility of predicting future asthma daily admissions using retrospective data in London (2005-2006). Negative binomial regressions were used in modeling; allowing the non-contiguous autoregressive components. Selected lags were based on partial autocorrelation function (PACF) plot with a maximum lag of 7 days. The model was contrasted with naïve historical and seasonal models. All models were cross validated. Mean daily asthma admission in 2005 was 27.9 and in 2006 it was 28.9. The lags 1, 2, 3, 6 and 7 were independently associated with daily asthma admissions based on their PACF plots. The lag model prediction of peak admissions were often slightly out of synchronization with the actual data, but the days of greater admissions were better matched than the days of lower admissions. A further investigation across various populations is necessary. © 2012 Soyiri, Reidpath

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub1117

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries

Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019

Evolving forecasting classifications and applications in health forecasting

Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation

The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths.Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/ temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1).The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2)This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept. © 2013 Soyiri, Reidpath

Semistructured black-box prediction: proposed approach for asthma admissions in London

Asthma is a global public health problem and the most common chronic disease among children. The factors associated with the condition are diverse, and environmental factors appear to be the leading cause of asthma exacerbation and its worsening disease burden. However, it remains unknown how changes in the environment affect asthma over time, and how temporal or environmental factors predict asthma events. The methodologies for forecasting asthma and other similar chronic conditions are not comprehensively documented anywhere to account for semistructured noncausal forecasting approaches. This paper highlights and discusses practical issues associated with asthma and the environment, and suggests possible approaches for developing decision-making tools in the form of semistructured black-box models, which is relatively new for asthma. Two statistical methods which can potentially be used in predictive modeling and health forecasting for both anticipated and peak events are suggested. Importantly, this paper attempts to bridge the areas of epidemiology, environmental medicine and exposure risks, and health services provision. The ideas discussed herein will support the development and implementation of early warning systems for chronic respiratory conditions in large populations, and ultimately lead to better decision-making tools for improving health service delivery. © 2012 Soyiri and Reidpath, publisher and licensee Dove Medical Press Ltd

Public health significance of viral contamination of drinking water

Water-borne enteric viruses pose a threat to both human and animal life causing a wide range of illnesses. Groundwater is the commonest transmission route for these viruses. About 50% of groundwater related disease outbreaks are attributable to viruses. Recent studies in developed countries have focused on public water systems, unfortunately, without much attention to private household wells and storage facilities. This paper reviews disease outbreaks attributed to water-borne viruses, the public health significance of enteric viral diseases and problems encountered in the development of diagnostic assays. The objective of this review is to confer the rationale for more research to provide reliable baseline information on the significance of water-borne viruses in the developing world. Since the virological quality of drinking water can no longer be compromised, rapid and sensitive methods for detecting enteric viruses in drinking water, recreational water and their sources is a necessity. As a preventive measure, ground, surface and treated drinking water must be protected from viral contamination. Enforcement of legislative measures for regular viral monitoring of drinking water in the industry will ensure safety of consumers