Anna Hansell

Chronic obstructive pulmonary disease: current burden and future projections

SERIES “THE GLOBAL BURDEN OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE” Edited by K.F. Rabe and J.B. Soriano Number 2 in this Series ### Summary ⇓Information about the comparative magnitude of the burden from various diseases and injuries is a critical input into building the evidence base for health policies and programmes. Such information should be based on a critical evaluation of all available epidemiological data using standard and comparable procedures across diseases and injuries, including information on the age at death and the incidence, duration and severity of cases who do not die prematurely from the disease. A summary measure, disability-adjusted life yrs (DALYs), has been developed to simultaneously measure the amount of disease burden due to premature mortality and the amount due to the nonfatal consequences of disease. Approximately 2.7 million deaths from chronic obstructive pulmonary disease (COPD) occurred in 2000, half of them in the Western Pacific Region, with the majority of these occurring in China. About 400,000 deaths occur each year from COPD in industrialised countries. The increase in global COPD deaths between 1990 and 2000 (0.5 million) is likely to be partly real, and partly due to better methods and more extensive data availability in 2000. The regional (adult) prevalence in 2000 varied from 0.5% in parts of Africa to 3–4% in North America. ### Introduction Health systems must increasingly address a broad spectrum of health issues, ranging from epidemic outbreaks to advanced therapeutic care. They must, or should, also support disease prevention and health-promotion activities. Recognising that resources for health were unlikely to grow as quickly as demand, in 1993, the World Bank proposed a series of intervention packages for countries at different stages of development which, if implemented, would probably lead to the greatest gains in population health at affordable cost. The evidence for these recommendations was based …

Epidemiology of pneumothorax in England

BACKGROUND Little is known of the epidemiology of pneumothorax. Routinely available data on pneumothorax in England are described. METHODS Patients consulting in primary care with a diagnosis of pneumothorax in each year from 1991 to 1995 inclusive were identified from the General Practice Research Database (GPRD). Emergency hospital admissions for pneumothorax were identified for the years 1991–4 from the Hospital Episode Statistics (HES) data. Mortality data for England & Wales were obtained for 1950–97. Analyses of pneumothorax rates by age and sex were performed for all data sources. Seasonal and geographical analyses were carried out for the HES data. RESULTS The overall person consulting rate for pneumothorax (primary and secondary combined) in the GPRD was 24.0/100 000 each year for men and 9.8/100 000 each year for women. Hospital admissions for pneumothorax as a primary diagnosis occurred at an overall incidence of 16.7/100 000 per year and 5.8/100 000 per year for men and women, respectively. Mortality rates were 1.26/million per year for men and 0.62/million per year for women. The age distribution in both men and women showed a biphasic distribution for both GP consultations and hospital admissions. Deaths showed a single peak with highest rates in the elderly. There was an urban-rural trend observed for hospital admissions in the older age group (55+ years) with admission rates in the conurbations significantly higher than in the rural areas. Analysis for trends in mortality data for 1950–97 showed a striking increase in the death rate for pneumothorax in those aged 55+ years between 1960 and 1990, with a steep decline in the 1990s. Mortality in the younger age group (15–34 years) remained low and constant. CONCLUSION There is evidence of two epidemiologically distinct forms of spontaneous pneumothorax in England. The explanation for the rise and fall in mortality for secondary pneumothorax is obscure.

Size matters: just how big is BIG? Quantifying realistic sample size requirements for human genome epidemiology

Background Despite earlier doubts, a string of recent successes indicates that if sample sizes are large enough, it is possible—both in theory and in practice—to identify and replicate genetic associations with common complex diseases. But human genome epidemiology is expensive and, from a strategic perspective, it is still unclear what ‘large enough’ really means. This question has critical implications for governments, funding agencies, bioscientists and the tax-paying public. Difficult strategic decisions with imposing price tags and important opportunity costs must be taken. Methods Conventional power calculations for case–control studies disregard many basic elements of analytic complexity—e.g. errors in clinical assessment, and the impact of unmeasured aetiological determinants—and can seriously underestimate true sample size requirements. This article describes, and applies, a rigorous simulation-based approach to power calculation that deals more comprehensively with analytic complexity and has been implemented on the web as ESPRESSO: (www.p3gobservatory.org/powercalculator.htm). Results Using this approach, the article explores the realistic power profile of stand-alone and nested case–control studies in a variety of settings and provides a robust quantitative foundation for determining the required sample size both of individual biobanks and of large disease-based consortia. Despite universal acknowledgment of the importance of large sample sizes, our results suggest that contemporary initiatives are still, at best, at the lower end of the range of desirable sample size. Insufficient power remains particularly problematic for studies exploring gene–gene or gene–environment interactions. Discussion Sample size calculation must be both accurate and realistic, and we must continue to strengthen national and international cooperation in the design, conduct, harmonization and integration of studies in human genome epidemiology.

What do chronic obstructive pulmonary disease patients die from? A multiple cause coding analysis

Information on obstructive lung disease (OLD) deaths is generally derived from the underlying cause of death on the death certificate. This neglects information on other conditions mentioned and may underestimate the burden of disease. Descriptive analyses of all conditions mentioned on the death certificate for all decedents where OLD (chronic obstructive pulmonary disease or asthma) was mentioned as a contributing cause of death were conducted for England and Wales for 1993–1999. OLD was mentioned in 312,664 or 8.0% of all deaths. OLD comprised the underlying cause of death in 59.8% of deaths with any mention of OLD. Where OLD was not the underlying cause of death, the leading causes by the International Classification of Disease version 9 chapter were diseases of the circulatory system, neoplasms, and non-OLD diseases of the respiratory system. The top single causes were acute myocardial infarction, other ischaemic heart disease, and lung cancer. The current analysis confirms that using the underlying cause of death underestimates the contribution of obstructive lung disease to mortality in England and Wales, in contrast to myocardial infarction where underlying cause of death captures most (94%) mentions on the death certificate.

Use of the General Practice Research Database (GPRD) for respiratory epidemiology: a comparison with the 4th Morbidity Survey in General Practice (MSGP4)

BACKGROUND The General Practice Research Database (GPRD) covers over 6% of the population of England and Wales and holds data on diagnoses and prescribing from 1987 onwards. Most previous studies using the GPRD have concentrated on drug use and safety. A study was undertaken to assess the validity of using the GPRD for epidemiological research into respiratory diseases. METHODS Age-specific and sex-specific rates derived from the GPRD for 11 respiratory conditions were compared with patient consultation rates from the 4th Morbidity Survey in General Practice (MSGP4). Within the GPRD comparisons were made between patient diagnosis rates, patient prescription rates, and patient “prescription plus relevant diagnosis” rates for selected treatments. RESULTS There was good agreement between consultation rates in the MSGP4 and diagnosis or “prescription plus diagnosis” from the GPRD in terms of pattern and magnitude, except for “acute bronchitis or bronchiolitis” where the best comparison was the combination category of “chest infection” and/or “acute bronchitis or bronchiolitis”. Within the GPRD, patient prescription rates for inhalers, tuberculosis or hayfever therapy showed little similarity with diagnosis only rates but a similarity was seen with the combination of “prescription plus diagnosis” which may be a better reflection of morbidity than diagnosis alone. CONCLUSIONS The GPRD appears to be valid for primary care epidemiological studies by comparison with MSGP4 and offers advantages in terms of large size, a longer time period covered, and ability to link prescriptions with diagnoses. However, careful interpretation is needed because not all consultations are recorded and the coding system used contains terms which do not directly map to ICD codes.

Proportional classifications of COPD phenotypes

Background: Chronic obstructive pulmonary disease (COPD) encompasses a group of disorders characterised by the presence of incompletely reversible airflow obstruction with overlapping subsets of different phenotypes including chronic bronchitis, emphysema or asthma. The aim of this study was to determine the proportion of adult subjects aged >50 years within each phenotypic subgroup of COPD, defined as a post-bronchodilator ratio of forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.7, in accordance with current international guidelines. Methods: Adults aged >50 years derived from a random population-based survey undertook detailed questionnaires, pulmonary function tests and chest CT scans. The proportion of subjects in each of 16 distinct phenotypes was determined based on combinations of chronic bronchitis, emphysema and asthma, with and without incompletely reversible airflow obstruction defined by a post-bronchodilator FEV1/FVC ratio of 0.7. Results: A total of 469 subjects completed the investigative modules, 96 of whom (20.5%) had COPD. Diagrams were constructed to demonstrate the relative proportions of the phenotypic subgroups in subjects with and without COPD. 18/96 subjects with COPD (19%) had the classical phenotypes of chronic bronchitis and/or emphysema but no asthma; asthma was the predominant COPD phenotype, being present in 53/96 (55%). When COPD was defined as a post-bronchodilator FEV1/FVC less than the lower limit of normal, there were one-third fewer subjects with COPD and a smaller proportion without a defined emphysema, chronic bronchitis or asthma phenotype. Conclusion: This study provides proportional classifications of the phenotypic subgroups of COPD which can be used as the basis for further research into the pathogenesis and treatment of this heterogeneous disorder.

Size matters: just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology.

Background Despite earlier doubts, a string of recent successes indicates that if sample sizes are large enough, it is possible—both in theory and in practice—to identify and replicate genetic associations with common complex diseases. But human genome epidemiology is expensive and, from a strategic perspective, it is still unclear what ‘large enough’ really means. This question has critical implications for governments, funding agencies, bioscientists and the tax-paying public. Difficult strategic decisions with imposing price tags and important opportunity costs must be taken. Methods Conventional power calculations for case–control studies disregard many basic elements of analytic complexity—e.g. errors in clinical assessment, and the impact of unmeasured aetiological determinants—and can seriously underestimate true sample size requirements. This article describes, and applies, a rigorous simulation-based approach to power calculation that deals more comprehensively with analytic complexity and has been implemented on the web as ESPRESSO: (www.p3gobservatory.org/powercalculator.htm). Results Using this approach, the article explores the realistic power profile of stand-alone and nested case–control studies in a variety of settings and provides a robust quantitative foundation for determining the required sample size both of individual biobanks and of large disease-based consortia. Despite universal acknowledgment of the importance of large sample sizes, our results suggest that contemporary initiatives are still, at best, at the lower end of the range of desirable sample size. Insufficient power remains particularly problematic for studies exploring gene–gene or gene–environment interactions. Discussion Sample size calculation must be both accurate and realistic, and we must continue to strengthen national and international cooperation in the design, conduct, harmonization and integration of studies in human genome epidemiology.

Health Hazards from Volcanic Gases: A Systematic Literature Review

Abstract Millions of people are potentially exposed to volcanic gases worldwide, and exposures may differ from those in anthropogenic air pollution. A systematic literature review found few primary studies relating to health hazards of volcanic gases. SO2 and acid aerosols from eruptions and degassing events were associated with respiratory morbidity and mortality but not childhood asthma prevalence or lung function decrements. Accumulations of H2S and CO2 from volcanic and geothermal sources have caused fatalities from asphyxiation. Chronic exposure to H2S in geothermal areas was associated with increases in nervous system and respiratory diseases. Some impacts were on a large scale, affecting several countries (e.g., Laki fissure eruption in Iceland in 1783–4). No studies on health effects of volcanic releases of halogen gases or metal vapors were located. More high quality collaborative studies involving volcanologists and epidemiologists are recommended.

Novel insights into the genetics of smoking behaviour, lung function, and chronic obstructive pulmonary disease (UK BiLEVE): a genetic association study in UK Biobank.

Summary Background Understanding the genetic basis of airflow obstruction and smoking behaviour is key to determining the pathophysiology of chronic obstructive pulmonary disease (COPD). We used UK Biobank data to study the genetic causes of smoking behaviour and lung health. Methods We sampled individuals of European ancestry from UK Biobank, from the middle and extremes of the forced expiratory volume in 1 s (FEV1) distribution among heavy smokers (mean 35 pack-years) and never smokers. We developed a custom array for UK Biobank to provide optimum genome-wide coverage of common and low-frequency variants, dense coverage of genomic regions already implicated in lung health and disease, and to assay rare coding variants relevant to the UK population. We investigated whether there were shared genetic causes between different phenotypes defined by extremes of FEV1. We also looked for novel variants associated with extremes of FEV1 and smoking behaviour and assessed regions of the genome that had already shown evidence for a role in lung health and disease. We set genome-wide significance at p<5 × 10−8. Findings UK Biobank participants were recruited from March 15, 2006, to July 7, 2010. Sample selection for the UK BiLEVE study started on Nov 22, 2012, and was completed on Dec 20, 2012. We selected 50 008 unique samples: 10 002 individuals with low FEV1, 10 000 with average FEV1, and 5002 with high FEV1 from each of the heavy smoker and never smoker groups. We noted a substantial sharing of genetic causes of low FEV1 between heavy smokers and never smokers (p=2·29 × 10−16) and between individuals with and without doctor-diagnosed asthma (p=6·06 × 10−11). We discovered six novel genome-wide significant signals of association with extremes of FEV1, including signals at four novel loci (KANSL1, TSEN54, TET2, and RBM19/TBX5) and independent signals at two previously reported loci (NPNT and HLA-DQB1/HLA-DQA2). These variants also showed association with COPD, including in individuals with no history of smoking. The number of copies of a 150 kb region containing the 5′ end of KANSL1, a gene that is important for epigenetic gene regulation, was associated with extremes of FEV1. We also discovered five new genome-wide significant signals for smoking behaviour, including a variant in NCAM1 (chromosome 11) and a variant on chromosome 2 (between TEX41 and PABPC1P2) that has a trans effect on expression of NCAM1 in brain tissue. Interpretation By sampling from the extremes of the lung function distribution in UK Biobank, we identified novel genetic causes of lung function and smoking behaviour. These results provide new insight into the specific mechanisms underlying airflow obstruction, COPD, and tobacco addiction, and show substantial shared genetic architecture underlying airflow obstruction across individuals, irrespective of smoking behaviour and other airway disease. Funding Medical Research Council.

Aircraft noise and cardiovascular disease near Heathrow airport in London: small area study

Objective To investigate the association of aircraft noise with risk of stroke, coronary heart disease, and cardiovascular disease in the general population. Design Small area study. Setting 12 London boroughs and nine districts west of London exposed to aircraft noise related to Heathrow airport in London. Population About 3.6 million residents living near Heathrow airport. Risks for hospital admissions were assessed in 12 110 census output areas (average population about 300 inhabitants) and risks for mortality in 2378 super output areas (about 1500 inhabitants). Main outcome measures Risk of hospital admissions for, and mortality from, stroke, coronary heart disease, and cardiovascular disease, 2001-05. Results Hospital admissions showed statistically significant linear trends (P<0.001 to P<0.05) of increasing risk with higher levels of both daytime (average A weighted equivalent noise 7 am to 11 pm, LAeq,16h) and night time (11 pm to 7 am, Lnight) aircraft noise. When areas experiencing the highest levels of daytime aircraft noise were compared with those experiencing the lowest levels (>63 dB v ≤51 dB), the relative risk of hospital admissions for stroke was 1.24 (95% confidence interval 1.08 to 1.43), for coronary heart disease was 1.21 (1.12 to 1.31), and for cardiovascular disease was 1.14 (1.08 to 1.20) adjusted for age, sex, ethnicity, deprivation, and a smoking proxy (lung cancer mortality) using a Poisson regression model including a random effect term to account for residual heterogeneity. Corresponding relative risks for mortality were of similar magnitude, although with wider confidence limits. Admissions for coronary heart disease and cardiovascular disease were particularly affected by adjustment for South Asian ethnicity, which needs to be considered in interpretation. All results were robust to adjustment for particulate matter (PM10) air pollution, and road traffic noise, possible for London boroughs (population about 2.6 million). We could not distinguish between the effects of daytime or night time noise as these measures were highly correlated. Conclusion High levels of aircraft noise were associated with increased risks of stroke, coronary heart disease, and cardiovascular disease for both hospital admissions and mortality in areas near Heathrow airport in London. As well as the possibility of causal associations, alternative explanations such as residual confounding and potential for ecological bias should be considered.