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Use of data linkage to measure the population health effect of non-health-care interventions
by
Lyons, Ronan A
, Ford, David V
, Rodgers, Sarah E
, Moore, Laurence
in
Advantages
/ Behavior
/ Biological and medical sciences
/ Chronic illnesses
/ Data Collection
/ Disease
/ Education
/ Epidemiology
/ General aspects
/ Health care
/ Health informatics
/ Health Promotion
/ Health services
/ Health Services Research
/ Households
/ Humans
/ Internal Medicine
/ Intervention
/ Medical research
/ Medical sciences
/ Methods
/ Observational studies
/ Prevention
/ Primary Prevention
/ Public Health
/ Social research
/ Studies
/ United Kingdom
/ Vaccines
2014
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Use of data linkage to measure the population health effect of non-health-care interventions
by
Lyons, Ronan A
, Ford, David V
, Rodgers, Sarah E
, Moore, Laurence
in
Advantages
/ Behavior
/ Biological and medical sciences
/ Chronic illnesses
/ Data Collection
/ Disease
/ Education
/ Epidemiology
/ General aspects
/ Health care
/ Health informatics
/ Health Promotion
/ Health services
/ Health Services Research
/ Households
/ Humans
/ Internal Medicine
/ Intervention
/ Medical research
/ Medical sciences
/ Methods
/ Observational studies
/ Prevention
/ Primary Prevention
/ Public Health
/ Social research
/ Studies
/ United Kingdom
/ Vaccines
2014
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Do you wish to request the book?
Use of data linkage to measure the population health effect of non-health-care interventions
by
Lyons, Ronan A
, Ford, David V
, Rodgers, Sarah E
, Moore, Laurence
in
Advantages
/ Behavior
/ Biological and medical sciences
/ Chronic illnesses
/ Data Collection
/ Disease
/ Education
/ Epidemiology
/ General aspects
/ Health care
/ Health informatics
/ Health Promotion
/ Health services
/ Health Services Research
/ Households
/ Humans
/ Internal Medicine
/ Intervention
/ Medical research
/ Medical sciences
/ Methods
/ Observational studies
/ Prevention
/ Primary Prevention
/ Public Health
/ Social research
/ Studies
/ United Kingdom
/ Vaccines
2014
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Use of data linkage to measure the population health effect of non-health-care interventions
Journal Article
Use of data linkage to measure the population health effect of non-health-care interventions
2014
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Overview
Health is largely determined by the interactions between social, economic, and physical environments and inherited characteristics, which together affect exposures and behaviours.1,2 Despite an improving evidence base showing the cost-effectiveness of disease prevention with non-health-care interventions, most investments into improving health continue to focus on health service treatment of acute and chronic illnesses, with little mainstreaming of effective preventive interventions other than vaccination or screening.3 Even within the prevention model there is a tendency towards investment in medical models of individual behaviour change, despite growing evidence showing that environmentally-based interventions often provide better value for money.4 Resource-constrained health organisations are generally disinclined to invest in non-health-care interventions, unless the quality of supporting evidence approximates that from randomised trials. The evidence base for many broad non-health-care interventions is often less extensive--eg, evidence for the health and societal effects of improved housing is largely based on findings from logic, extrapolation, and observational studies, albeit supported by a small but growing amount of interventional research.5 Assessment of non-health-care interventions needs recognition of the complexity of real-life settings, and hence adoption of socioecological and life-course perspectives in which multiple exposures and interventions interact at different levels over long periods.6 This scenario is in stark contrast with that used for the testing of pharmaceutical agents, which generally involves well funded, short-term trials of simple interventions in atypical disease-specific populations that are free of comorbidities.
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