Kenny D Lawson
James Cook University
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Featured researches published by Kenny D Lawson.
Journal of Epidemiology and Community Health | 2012
Peter Craig; C Cooper; David Gunnell; Sally Haw; Kenny D Lawson; Sally Macintyre; David Ogilvie; Mark Petticrew; Barnaby C Reeves; Matt Sutton; Simon G. Thompson
Natural experimental studies are often recommended as a way of understanding the health impact of policies and other large scale interventions. Although they have certain advantages over planned experiments, and may be the only option when it is impossible to manipulate exposure to the intervention, natural experimental studies are more susceptible to bias. This paper introduces new guidance from the Medical Research Council to help researchers and users, funders and publishers of research evidence make the best use of natural experimental approaches to evaluating population health interventions. The guidance emphasises that natural experiments can provide convincing evidence of impact even when effects are small or take time to appear. However, a good understanding is needed of the process determining exposure to the intervention, and careful choice and combination of methods, testing of assumptions and transparent reporting is vital. More could be learnt from natural experiments in future as experience of promising but lesser used methods accumulates.
The Lancet | 2016
Ding Ding; Kenny D Lawson; Tracy Kolbe-Alexander; Eric A. Finkelstein; Peter T. Katzmarzyk; Willem van Mechelen; Michael Pratt
BACKGROUND The pandemic of physical inactivity is associated with a range of chronic diseases and early deaths. Despite the well documented disease burden, the economic burden of physical inactivity remains unquantified at the global level. A better understanding of the economic burden could help to inform resource prioritisation and motivate efforts to increase levels of physical activity worldwide. METHODS Direct health-care costs, productivity losses, and disability-adjusted life-years (DALYs) attributable to physical inactivity were estimated with standardised methods and the best data available for 142 countries, representing 93·2% of the worlds population. Direct health-care costs and DALYs were estimated for coronary heart disease, stroke, type 2 diabetes, breast cancer, and colon cancer attributable to physical inactivity. Productivity losses were estimated with a friction cost approach for physical inactivity related mortality. Analyses were based on national physical inactivity prevalence from available countries, and adjusted population attributable fractions (PAFs) associated with physical inactivity for each disease outcome and all-cause mortality. FINDINGS Conservatively estimated, physical inactivity cost health-care systems international
International Journal of Environmental Research and Public Health | 2010
Paula Lorgelly; Kenny D Lawson; Elisabeth Fenwick; Andrew Briggs
(INT
International Journal for Equity in Health | 2013
Kenny D Lawson; Stewart W. Mercer; Sally Wyke; Eleanor Grieve; Bruce Guthrie; Graham Watt; Elisabeth A.E. Fenwick
) 53·8 billion worldwide in 2013, of which
Diabetes Care | 2009
Monique A. M. Jacobs-van der Bruggen; Pieter van Baal; Rudolf T. Hoogenveen; Talitha Feenstra; Andrew Briggs; Kenny D Lawson; Edith J. M. Feskens; Caroline A. Baan
31·2 billion was paid by the public sector,
Heart | 2010
Kenny D Lawson; Elisabeth Fenwick; Alastair C.H. Pell; Jill P. Pell
12·9 billion by the private sector, and
Pain | 2014
Nicola Torrance; Kenny D Lawson; Ebenezer Afolabi; Michael I. Bennett; Michael Serpell; Kate M. Dunn; Blair H. Smith
9·7 billion by households. In addition, physical inactivity related deaths contribute to
Annals of Family Medicine | 2015
Harry H.X. Wang; Jia Ji Wang; Kenny D Lawson; Samuel Y. S. Wong; Martin C.S. Wong; Fang Jian Li; Pei Xi Wang; Zhi Heng Zhou; Chun Yan Zhu; Yao Qun Yeong; Sian Griffiths; Stewart W. Mercer
13·7 billion in productivity losses, and physical inactivity was responsible for 13·4 million DALYs worldwide. High-income countries bear a larger proportion of economic burden (80·8% of health-care costs and 60·4% of indirect costs), whereas low-income and middle-income countries have a larger proportion of the disease burden (75·0% of DALYs). Sensitivity analyses based on less conservative assumptions led to much higher estimates. INTERPRETATION In addition to morbidity and premature mortality, physical inactivity is responsible for a substantial economic burden. This paper provides further justification to prioritise promotion of regular physical activity worldwide as part of a comprehensive strategy to reduce non-communicable diseases. FUNDING None.
BMC Public Health | 2015
Roxanne Bainbridge; Komla Tsey; Janya McCalman; Irina Kinchin; Vicki Saunders; Felecia Watkin Lui; Yvonne Cadet-James; Adrian Miller; Kenny D Lawson
Public health interventions have received increased attention from policy makers, and there has been a corresponding increase in the number of economic evaluations within the domain of public health. However, methods to evaluate public health interventions are less well established than those for medical interventions. Focusing on health as an outcome measure is likely to underestimate the impact of many public health interventions. This paper provides a review of outcome measures in public health; and describes the benefits of using the capability approach as a means to developing an all encompassing outcome measure.
Frontiers in Public Health | 2016
Komla Tsey; Kenny D Lawson; Irina Kinchin; Roxanne Bainbridge; Janya McCalman; Felecia Watkin; Yvonne Cadet-James; Allison Rossetto
ObjectiveTo investigate the association between multimorbidity and Preference_Weighted Health Related Quality of Life (PW_HRQoL), a score that combines physical and mental functioning, and how this varies by socioeconomic deprivation and age.DesignThe Scottish Health Survey (SHeS) is a cross-sectional representative survey of the general population which included the SF-12, a survey of HRQoL, for individuals 20 years and over.MethodsFor 7,054 participants we generated PW_HRQoL scores by running SF-12 responses through the SF-6D algorithm. The resulting scores ranged from 0.29 (worst health) to 1 (perfect health). Using ordinary least squares, we first investigated associations between scores and increasing counts of longstanding conditions, and then repeated for multimorbidity (2+ conditions). Estimates were made for the general population and quintiles of socioeconomic deprivation. For multimorbidity, the analyses were repeated stratifying the population by age group (20–44, 45–64, 65+).Results45% of participants reported a longstanding condition and 18% reported multimorbidity. The presence of 1, 2, or 3+ longstanding conditions were associated with average reductions in PW_HRQoL scores of 0.081, 0.151 and 0.212 respectively. Reduction in scores associated with multimorbidity was 33% greater in the most deprived quintile compared to the least deprived quintile, with the biggest difference (80%) in the 20–44 age groups. There were no significant gender differences.ConclusionsPW_HRQoL decreases markedly with multimorbidity, and is exacerbated by higher deprivation and younger age. There is a need to prioritise interventions to improve the HRQoL for (especially younger) adults with multimorbidity in deprived areas.Box 1What Is Known?Prevalence and premature onset of multimorbidity increases as socioeconomic position worsens. Previous studies have investigated the effect of multimorbidity on Health Related Quality of Life (HRQoL) on separate physical and mental health states. There is limited data on how HRQoL falls as the number of conditions increase, and how estimates vary across the general population.Leaving physical and mental health as separate categories can inhibit assessment of overall HRQoL. The use of a Preference_Weighted Health Related Quality of Life (PW_HRQoL) score provides a single summary measure of overall health, by weighting mental and physical states by their perceived importance as part of overall HRQoL. The use of a single score enables a simple and consistent assessment of the impact of conditions and how this varies across the population. Economists term PW_HRQoL scores health utilities.What this study adds?This is the first study to estimate how the impact of multimorbidity on PW_HRQoL scores varies by age group and socioeconomic deprivation. Multimorbidity has a substantial negative impact on HRQoL which is most severe in areas of deprivation, especially in younger adults.Measuring the burden of multimorbidity using PW_HRQoL provides consistency with how economists measure HRQoL; changes in which can be used in economic evaluation to assess the cost effectiveness of interventions.