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Steven Cummins

Bio: Steven Cummins is an academic researcher from University of London. The author has contributed to research in topics: Population & Neighbourhood (mathematics). The author has an hindex of 54, co-authored 195 publications receiving 14670 citations. Previous affiliations of Steven Cummins include University of Glasgow & Harvard University.


Papers
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Journal ArticleDOI
TL;DR: Using a framework of universal human needs as a basis for thinking about how places may influence health is suggested, and the testing of hypotheses about specific chains of causation that might link place of residence with health outcomes is recommended.

1,952 citations

Journal ArticleDOI
TL;DR: This tutorial uses a worked example to demonstrate a robust approach to ITS analysis using segmented regression and describes the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders.
Abstract: Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.

1,778 citations

Journal ArticleDOI
TL;DR: It is argued that research in place and health should avoid the false dualism of context and composition by recognising that there is a mutually reinforcing and reciprocal relationship between people and place.

1,205 citations

Journal ArticleDOI
TL;DR: This commentary focuses exclusively on environmental issues in energy intake in the developed world and provides an overview of recent findings on obesogenic environments and points to cross national variations in their distribution.
Abstract: Obesity arises from an imbalance between energy input and output 1 but in this commentary we focus exclusively on environmental issues in energy intake in the developed world. Our aim is both to provide an overview of recent findings on obesogenic environments 2 and to point to cross national variations in their distribution. It has recently been suggested that individually focused interventions attempting to reduce obesity have had limited success, 3 and that the widespread and increasing prevalence of obesity is inadequately explained by individual-level psychological and social factors associated with diet or physical activity. 1,2,4,5 This suggestion is part of a broader critique of the over-emphasis on the role of individual health behaviours, which has tended to ignore the influence of the complex social and physical contexts in which individual behavioural decisions are made. 4,6 Such critiques have led to a new focus on ‘environmental’ exposures that encourage excessive food intake and discourage physical activity. 7–10

700 citations


Cited by
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Journal ArticleDOI
TL;DR: The Multi-Ethnic Study of Atherosclerosis was initiated in July 2000 to investigate the prevalence, correlates, and progression of subclinical cardiovascular disease (CVD) in a population-based sample of 6,500 men and women aged 45-84 years for identification and characterization of CVD events.
Abstract: The Multi-Ethnic Study of Atherosclerosis was initiated in July 2000 to investigate the prevalence, correlates, and progression of subclinical cardiovascular disease (CVD) in a population-based sample of 6,500 men and women aged 45-84 years. The cohort will be selected from six US field centers. Approximately 38% of the cohort will be White, 28% African-American, 23% Hispanic, and 11% Asian (of Chinese descent). Baseline measurements will include measurement of coronary calcium using computed tomography; measurement of ventricular mass and function using cardiac magnetic resonance imaging; measurement of flow-mediated brachial artery endothelial vasodilation, carotid intimal-medial wall thickness, and distensibility of the carotid arteries using ultrasonography; measurement of peripheral vascular disease using ankle and brachial blood pressures; electrocardiography; and assessments of microalbuminuria, standard CVD risk factors, sociodemographic factors, life habits, and psychosocial factors. Blood samples will be assayed for putative biochemical risk factors and stored for use in nested case-control studies. DNA will be extracted and lymphocytes will be immortalized for genetic studies. Measurement of selected subclinical disease indicators and risk factors will be repeated for the study of progression over 7 years. Participants will be followed through 2008 for identification and characterization of CVD events, including acute myocardial infarction and other coronary heart disease, stroke, peripheral vascular disease, and congestive heart failure; therapeutic interventions for CVD; and mortality.

3,367 citations

Book
16 Dec 2005
TL;DR: Systematic review methods have been widely used in health care, and are becoming increasingly common in the social sciences (fostered by the work of the Campbell Collaboration) as mentioned in this paper.
Abstract: Such diverse thinkers as Lao-Tze, Confucius, and U.S. Defense Secretary Donald Rumsfeld have all pointed out that we need to be able to tell the difference between real and assumed knowledge. The systematic review is a scientific tool that can help with this difficult task. It can help, for example, with appraising, summarising, and communicating the results and implications of otherwise unmanageable quantities of data. This is important because quite often there are so many studies, and their results are often so conflicting, that no policymaker or practitioner could possibly carry out this task themselves.Systematic review methods have been widely used in health care, and are becoming increasingly common in the social sciences (fostered, for example, by the work of the Campbell Collaboration). This book outlines the rationale and methods of systematic reviews, giving worked examples from social science and other fields. It requires no previous knowledge, but takes the reader through the process stage by stage. It draws on examples from such diverse fields as psychology, criminology, education, transport, social welfare, public health, and housing and urban policy, among others.The book includes detailed sections on assessing the quality of both quantitative, and qualitative research; searching for evidence in the social sciences;meta-analytic and other methods of evidence synthesis; publication bias; heterogeneity; and approaches to dissemination.

3,263 citations

Journal ArticleDOI
TL;DR: It is concluded that multiple Imputation for Nonresponse in Surveys should be considered as a legitimate method for answering the question of why people do not respond to survey questions.
Abstract: 25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

3,216 citations

Journal ArticleDOI
TL;DR: Obesity has increased at an alarming rate in the United States over the past three decades and the associations of obesity with gender, age, ethnicity, and socioeconomic status are complex and dynamic.
Abstract: This review of the obesity epidemic provides a comprehensive description of the current situation, time trends, and disparities across gender, age, socioeconomic status, racial/ethnic groups, and geographic regions in the United States based on national data. The authors searched studies published between 1990 and 2006. Adult overweight and obesity were defined by using body mass index (weight (kg)/height (m) 2 ) cutpoints of 25 and 30, respectively; childhood ‘‘at risk for overweight’’ and overweight were defined as the 85th and 95th percentiles of body mass index. Average annual increase in and future projections for prevalence were estimated by using linear regression models. Among adults, obesity prevalence increased from 13% to 32% between the 1960s and 2004. Currently, 66% of adults are overweight or obese; 16% of children and adolescents are overweight and 34% are at risk of overweight. Minority and low-socioeconomic-status groups are disproportionately affected at all ages. Annual increases in prevalence ranged from 0.3 to 0.9 percentage points across groups. By 2015, 75% of adults will be overweight or obese, and 41% will be obese. In conclusion, obesity has increased at an alarming rate in the United States over the past three decades. The associations of obesity with gender, age, ethnicity, and socioeconomic status are complex and dynamic. Related population-based programs and policies are needed.

2,780 citations

Journal ArticleDOI
TL;DR: This chapter summarizes key work in this area with a particular focus on chronic disease outcomes (specifically obesity and related risk factors) and mental health ( specifically depression and depressive symptoms) and empirical work is classified into two main eras.
Abstract: Features of neighborhoods or residential environments may affect health and contribute to social and race/ethnic inequalities in health. The study of neighborhood health effects has grown exponentially over the past 15 years. This chapter summarizes key work in this area with a particular focus on chronic disease outcomes (specifically obesity and related risk factors) and mental health (specifically depression and depressive symptoms). Empirical work is classified into two main eras: studies that use census proxies and studies that directly measure neighborhood attributes using a variety of approaches. Key conceptual and methodological challenges in studying neighborhood health effects are reviewed. Existing gaps in knowledge and promising new directions in the field are highlighted.

2,471 citations