Displaying publications 81 - 100 of 101 in total

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  1. Soyiri IN, Reidpath DD, Sarran C
    Chron Respir Dis, 2013 May;10(2):85-94.
    PMID: 23620439 DOI: 10.1177/1479972313482847
    Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.
  2. Reidpath DD, Ling ML, Wellington E, Al-Sadat N, Yasin S
    Nicotine Tob Res, 2013 Mar;15(3):729-33.
    PMID: 22990215 DOI: 10.1093/ntr/nts177
    INTRODUCTION: It is held that younger smoking initiates are more likely to become regular smokers. The definitions of smoking initiation (a puff, part of a cigarette, a whole cigarette) are inconsistent and raise questions about the robustness of the view. We sought to re-examine the relationship using adolescent smoking data from 3 European countries.
    METHODS: A stratified secondary, logistic regression analysis of Global Youth Tobacco Survey data was conducted using a design-based analysis. Subgroup analyses were conducted of 13- to 15-year olds from Latvia (high smoking prevalence), Slovenia (moderate prevalence), and Montenegro (low prevalence) who had initiated smoking. The outcome was current smoking--smoking everyday for the past 30 days, or smoking 10 or more days in the past 30 days. Smoking initiation was operationalized as a single puff of a cigarette, and age of smoking initiation was a derived continuous measure.
    RESULTS: In Latvia, there was a significant association between age of smoking initiation and current smoking for males (p < .05) and females (p < .001) when smoking was operationalized as smoking every day. It was only significant in female adolescents (p < .001) for smoking 10 or more days. In Slovenia and Montenegro, there was no significant relationship between age of smoking initiation and current smoking for either males or females.
    CONCLUSIONS: The evidence about the relationship between age of smoking initiation and current smoking is not clear. Explanations for the findings may relate to a lack of power, the specificity of the measure, or problems with the theory.
  3. Soyiri IN, Reidpath DD
    Environ Health Prev Med, 2013 Jan;18(1):1-9.
    PMID: 22949173 DOI: 10.1007/s12199-012-0294-6
    Health forecasting is a novel area of forecasting, and a valuable tool for predicting future health events or situations such as demands for health services and healthcare needs. It facilitates preventive medicine and health care intervention strategies, by pre-informing health service providers to take appropriate mitigating actions to minimize risks and manage demand. Health forecasting requires reliable data, information and appropriate analytical tools for the prediction of specific health conditions or situations. There is no single approach to health forecasting, and so various methods have often been adopted to forecast aggregate or specific health conditions. Meanwhile, there are no defined health forecasting horizons (time frames) to match the choices of health forecasting methods/approaches that are often applied. The key principles of health forecasting have not also been adequately described to guide the process. This paper provides a brief introduction and theoretical analysis of health forecasting. It describes the key issues that are important for health forecasting, including: definitions, principles of health forecasting, and the properties of health data, which influence the choices of health forecasting methods. Other matters related to the value of health forecasting, and the general challenges associated with developing and using health forecasting services are discussed. This overview is a stimulus for further discussions on standardizing health forecasting approaches and methods that will facilitate health care and health services delivery.
  4. Bonsu KO, Kadirvelu A, Reidpath DD
    Vasc Health Risk Manag, 2013;9:303-19.
    PMID: 23807852 DOI: 10.2147/VHRM.S44499
    Statins lower serum cholesterol and are employed for primary and secondary prevention of cardiovascular events. Clinical evidence from observational studies, retrospective data, and post hoc analyses of data from large statin trials in various cardiovascular conditions, as well as small scale randomized trials, suggest survival and other outcome benefits for heart failure. Two recent large randomized controlled trials, however, appear to suggest statins do not have beneficial effects in heart failure. In addition to lowering cholesterol, statins are believed to have many pleotropic effects which could possibly influence the pathophysiology of heart failure. Following the two large trials, evidence from recent studies appears to support the use of statins in heart failure. This review discusses the role of statins in the pathophysiology of heart failure, current evidence for statin use in heart failure, and suggests directions for future research.
  5. Soyiri IN, Reidpath DD
    PLoS One, 2013;8(10):e78215.
    PMID: 24147122 DOI: 10.1371/journal.pone.0078215
    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.
  6. Reidpath DD, Cheah JC, Lam FC, Yasin S, Soyiri I, Allotey P
    Nutr J, 2013;12:135.
    PMID: 24093886 DOI: 10.1186/1475-2891-12-135
    BACKGROUND: Measures of central adiposity are better predictors of adverse health events than BMI. Nonetheless, BMI is more widely used in health research. One reason for this may be the limited research supporting the self-measurement of waist and hip circumference. The lack of validity studies is particularly acute in Asia. The main objective was to establish the validity of self-measurement of waist and hip circumference in a community setting and the correlation of those measures with BMI, blood pressure, and blood glucose levels.
    METHODS: A community based, cross-sectional survey. A "healthy living expo" at a shopping mall in a rural town on peninsular Malaysia One hundred and thirty six (136) individuals volunteered to participate in the study, 125 of whom met the inclusion criteria. The ethnic distribution of the participants was 80% Chinese, 17% Malay and 3% Indian. Most participants were female (60%), with participants' ages ranging from 18 to 78 years (mean, 47.2). Self and assisted measurements of waist and hip were taken. Blood pressure, non-fasting blood glucose, height, and weight were also measured. Bland Altman plots and Lin's concordance coefficient were used to measure agreement between self and assisted measures. Pearson's correlation was used to examine the association of self and assisted measures with blood pressure, blood glucose, and BMI.
    RESULTS: There was a downwards bias in self measured waist (-0.81 cm) and hip (-1 cm) circumferences compared with assisted measures. The concordance for the self and assisted measures of waist, hip and the ratio of the two were, respectively, .96, .93 , and .84. The correlation between measures of central adiposity and BMI, blood pressure and blood glucose were similar for self and assisted measures.
    CONCLUSION: The results provide additional support for the use of self-measurement of waist and hip circumference studies of central adiposity, but is limited by the specificity of the setting.
  7. Bonsu KO, Kadirvelu A, Reidpath DD
    Syst Rev, 2013;2:22.
    PMID: 23618535 DOI: 10.1186/2046-4053-2-22
    Statins are known to reduce cardiovascular morbidity and mortality in primary and secondary prevention studies. Subsequently, a number of nonrandomised studies have shown statins improve clinical outcomes in patients with heart failure (HF). Small randomised controlled trials (RCT) also show improved cardiac function, reduced inflammation and mortality with statins in HF. However, the findings of two large RCTs do not support the evidence provided by previous studies and suggest statins lack beneficial effects in HF. Two meta-analyses have shown statins do not improve survival, whereas two others showed improved cardiac function and reduced inflammation in HF. It appears lipophilic statins produce better survival and other outcome benefits compared to hydrophilic statins. But the two types have not been compared in direct comparison trials in HF.
  8. Tan MM, Chan CK, Reidpath DD
    PMID: 24319472 DOI: 10.1155/2013/146214
    Objectives. To systematically review articles investigating the relationship between religion and spirituality (R/S) and fruit, vegetable, and fat intake. Methods. PubMed, CINAHL, and PsycInfo were searched for studies published in English prior to March 2013. The studies were divided into two categories: denominational studies and degree of R/S studies. The degree of R/S studies was further analyzed to (1) determine the categories of R/S measures and their relationship with fruit, vegetable, and fat intake, (2) evaluate the quality of the R/S measures and the research design, and (3) determine the categories of reported relationship. Results. Thirty-nine studies were identified. There were 14 denominational studies and 21 degree of R/S studies, and 4 studies were a combination of both. Only 20% of the studies reported validity and 52% reported reliability of the R/S measures used. All studies were cross-sectional, and only one attempted mediation analysis. Most studies showed a positive association with fruit and vegetable intake and a mixed association with fat intake. Conclusion. The positive association between R/S and fruit and vegetable intake may be one possible link between R/S and positive health outcome. However, the association with fat intake was mixed, and recommendations for future research are made.
  9. Reidpath DD, Ling ML, Yasin S, Rajagobal K, Allotey P
    Glob Health Action, 2012;5:14876.
    PMID: 22761601 DOI: 10.3402/gha.v5i0.14876
    INTRODUCTION: Population monitoring and screening of blood pressure is an important part of any population health strategy. Qualified health workers are expensive and often unavailable for screening. Non-health workers with electronic blood pressure monitors are increasingly used in community-based research. This approach is unvalidated. In a poor, urban community we compared blood pressure measurements taken by non-health workers using electronic devices against qualified health workers using mercury sphygmomanometers.
    METHOD: Fifty-six adult volunteers participated in the research. Data were collected by five qualified health workers, and six non-health workers. Participants were randomly allocated to have their blood pressure measured on four consecutive occasions by alternating a qualified health worker with a non-health worker. Descriptive statistics and graphs, and mixed effects linear models to account for the repeated measurement were used in the analysis.
    RESULTS: Blood pressure readings by non-health workers were more reliable than those taken by qualified health workers. There was no significant difference between the readings taken by qualified health workers and those taken by non-health workers for systolic blood pressure. Non-health workers were, on average, 5-7 mmHg lower in their measures of blood pressure than the qualified health workers (95%HPD: -2.9 to -10.0) for diastolic blood pressure.
    CONCLUSION: The results provide empirical evidence that supports the practice of non-health workers using electronic devices for BP measurement in community-based research and screening. Non-health workers recorded blood pressures that differed from qualified health workers by no more than 10 mmHg. The approach is promising, but more research is needed to establish the generalisability of the results.
    KEYWORDS: Malaysia; blood pressure; community workers; hypertension; measurement; screening
    Study site: urban, low-income community, of the Klang Valley near Kuala Lumpur, Malaysia
    Device: Mercury sphygmomanometers (Spirit brand, model number CK-101C), electronic, automatic blood pressure monitors (Omron brand model HEM-7203)
  10. Reidpath DD, Olafsdottir AE, Pokhrel S, Allotey P
    BMC Public Health, 2012;12 Suppl 1:S3.
    PMID: 22992346 DOI: 10.1186/1471-2458-12-S1-S3
    In the health systems literature one can see discussions about the trade off between the equity achievable by the system and its efficiency. Essentially it is argued that as greater health equity is achieved, so the level of efficiency will diminish. This argument is borrowed from economics literature on market efficiency. In the application of the economic argument to health, however, serious errors have been made, because it is quite reasonable to talk of both health equity being a desirable output of a health system, and the efficient production of that output. In this article we discuss notions of efficiency, and the equity-efficiency trade off, before considering the implications of this for health systems.
  11. Allotey P, Yasin S, Tang S, Chong SL, Cheah JC, Reidpath DD
    BMC Public Health, 2012;12 Suppl 1:S1.
    PMID: 22992275
  12. Allotey P, Verghis S, Alvarez-Castillo F, Reidpath DD
    BMC Public Health, 2012;12 Suppl 1(Suppl 1):S2.
    PMID: 22992314 DOI: 10.1186/1471-2458-12-S1-S2
  13. Soyiri IN, Reidpath DD
    PLoS One, 2012;7(10):e47823.
    PMID: 23118897 DOI: 10.1371/journal.pone.0047823
    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.
  14. Soyiri IN, Reidpath DD
    Int J Gen Med, 2012;5:381-9.
    PMID: 22615533 DOI: 10.2147/IJGM.S31079
    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.
  15. Soyiri IN, Reidpath DD
    Int J Gen Med, 2012;5:693-705.
    PMID: 22973117 DOI: 10.2147/IJGM.S34647
    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.
  16. Allotey P, Reidpath DD, Yasin S, Chan CK, de-Graft Aikins A
    Lancet, 2011 Feb 5;377(9764):450-1.
    PMID: 21074257 DOI: 10.1016/S0140-6736(10)61856-9
  17. Reidpath DD, Allotey P, Pokhrel S
    Health Res Policy Syst, 2011 Jan 06;9:1.
    PMID: 21210997 DOI: 10.1186/1478-4505-9-1
    BACKGROUND: There are strong arguments for social science and interdisciplinary research in the neglected tropical diseases. These diseases represent a rich and dynamic interplay between vector, host, and pathogen which occurs within social, physical and biological contexts. The overwhelming sense, however, is that neglected tropical diseases research is a biomedical endeavour largely excluding the social sciences. The purpose of this review is to provide a baseline for discussing the quantum and nature of the science that is being conducted, and the extent to which the social sciences are a part of that.

    METHODS: A bibliographic analysis was conducted of neglected tropical diseases related research papers published over the past 10 years in biomedical and social sciences. The analysis had textual and bibliometric facets, and focussed on chikungunya, dengue, visceral leishmaniasis, and onchocerciasis.

    RESULTS: There is substantial variation in the number of publications associated with each disease. The proportion of the research that is social science based appears remarkably consistent (<4%). A textual analysis, however, reveals a degree of misclassification by the abstracting service where a surprising proportion of the "social sciences" research was pure clinical research. Much of the social sciences research also tends to be "hand maiden" research focused on the implementation of biomedical solutions.

    CONCLUSION: There is little evidence that scientists pay any attention to the complex social, cultural, biological, and environmental dynamic involved in human pathogenesis. There is little investigator driven social science and a poor presence of interdisciplinary science. The research needs more sophisticated funders and priority setters who are not beguiled by uncritical biomedical promises.

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