Journal of Pulmonology and Respiratory Diseases
Open Access

Chronic obstructive pulmonary disease (COPD); Global burden of disease (GBD); Disability-adjusted life years (DALYs); Noncontagious diseases (NCDs)

Introduction

Information on the relative amount of the burden posed by various diseases and injuries is an important component of developing the evidence base for health policies and programmes. Such statistics should be based on a rigorous review of all available epidemiological data across diseases and injuries using standard and similar processes, including information on the age at death and the incidence, duration, and severity of cases who do not succumb to the disease prematurely. Disability-adjusted life years (DALYs), a summary metric, has been devised to evaluate the amount of disease burden owing to premature mortality as well as the amount due to nonfatal effects of disease.

In the year 2000, over 2.7 million people died from chronic obstructive pulmonary disease (COPD), half of them died in the Western Pacific Region, with China accounting for the majority of these deaths. COPD kills about 400,000 people each year in developed countries. The 0.5 million rise in global COPD mortality between 1990 and 2000 is likely due to a combination of better procedures and more broad data availability in 2000. In the year 2000, the regional (adult) frequency ranged from 0.5 percent in regions of Africa to 3–4% in North America.

Health-care systems are increasingly being called upon to deal with a wide range of concerns, from epidemic outbreaks to advanced therapeutic care. They must, or should, also support disease prevention and promotion efforts. Recognizing that health-care resources were unlikely to keep pace with demand, the World Bank proposed a series of intervention packages for countries at various stages of development in 1993, which, if implemented, would likely result in the greatest improvements in population health at the lowest cost. The evidence for these suggestions came from a research of the global burden of disease caused by various disorders, as well as a cost-effectiveness analysis of existing therapies [1].

The Global Burden of Disease (GBD) Study, commissioned for the Bank Report, was the first systematic attempt to evaluate the burden of premature mortality and nonfatal sickness caused by more than 100 diseases and injuries over the world at the same time. A summary measure of population health, DALYs, was used to quantify burden, with the stream of Years of Life Lost (YLL) or Years Lived with Disability (YLD) being evaluated separately. Premature mortality was calculated for any sickness or injury I (for example, lung cancer, traffic accidents, and measles).

Every year, data on causes of death in their populations is reported by more than 100 countries using data from their vital registry systems. These statistics vary greatly in terms of quality and coverage, yet they are extremely important for public health. The "gold standard" for determining causes of death is to employ vital registration systems that record all deaths in a community and include a medical certificate completed by a certified practitioner as to the medical conditions that led up to death [2]. However, in many countries, these systems either do not catch all deaths, do not provide a definitive clinical diagnosis as to the underlying cause of death, or provide an inaccurate cause of death. Even developed countries are guilty of this. As a result, many deaths recorded as heart failure or ventricular dysrhythmias in countries like Japan, Spain, or France would be more likely to be classified as ischemic heart disease in the United States, United Kingdom, or Australia. The consequences of such a code error can be severe. When correction methods for vascular disease miscoding were applied to the 1990 GBD Study, it was estimated that ischemic heart disease mortality rates in Japan, France, Brazil, and numerous other nations were 50-200 present higher than reported. Although studies of multiple-cause coding imply that there may be, it is uncertain whether there are similar systematic certification and coding biases for COPD across nations [3].

Other sources of cause-specific mortality data for populations were identified and evaluated in addition to vital registration, including large-scale epidemiological surveillance systems on a sample basis in China and Tanzania, and community-based epidemiological research studies and disease registers, where available (e.g. cancer). Because claims concerning causes of death are frequently made by diseasespecific groups working in isolation (e.g., HIV, malaria), they are frequently inflated and, when added together, substantially surpass independent demographic estimates of total mortality in any given age or sex group. This is especially true for children and young people, who bear the brunt of the effects of most major communicable diseases and poverty [4]. The "envelope" of mortality by age, sex, and location was first determined from demographic databases and the estimates of cause-specific mortality from the GBD Study's >100 causes were limited to add up to this number of deaths [5].

Methods

Data: COPD and population information for European country and Wales 1945–1999 by 5-yr age band were obtained from the workplace for National Statistics (ONS) 50-54. Codes used for COPD enclosed those for bronchial asthma, bronchitis and respiratory disorder thanks to issues concerning distinctive between these conditions mistreatment death certificate information 55; bronchial asthma official of deaths over this point amount. Population projections for 2000-2009 onward were obtained from the govt. computer Dept. (London, UK) [6].

Statistical model: The statistical procedure is represented in additional detail elsewhere 49. In brief, the underlying assumption on that the applied math model is predicated is that determined mortality rates result from a relentless rate changed by age, amount and cohort effects, and unobserved covariates. The model is enforced in a very theorem framework and could be a development of labour by Clayton and Schifflers 62 and Berzuini et al. 63. Differing assumptions (prior beliefs or priors) concerning the smoothness of the age, amount and cohort parameters can be incorporated into the model [7]. The smoothing previous outlined as stochastic process (RW)1 favoured answer parameters with constancy of first-order variations old-time, amount or cohort parameters, thereby forward a smoothness old-time, amount and cohort trends, whereas the RW2 previous fined deviations from a linear trend of the second-order variations old-time, amount or cohort parameters, forward a smoothness of the speed of modification of parameters [8].

Conclusion

In conclusion, predicting future trends in a disease is difficult. Both risk factor and age–period–cohort approaches are based on a number of assumptions; for example, that the dose–response coefficient of the risk factor will remain constant into the future or that current age, period and cohort trends will continue. The extent to which projection methods can predict existing data should be readily available for published projections. As all methods have flaws, a more complete assessment can be made by comparing projections obtained using risk factor and extrapolation methods.

Finally, the most results from this study area unit estimates of COPD prevalence rates, that area unit per a corresponding set of prevalence and mortality rates and, a lot of significantly, seem to be a lot of comparable those in national burden of illness studies and therefore the printed literature than the previous (1990) estimates. Despite the uncertainty in estimates thanks to information limitations, the GBD Study suggests that COPD could be a major reason behind death and incapacity altogether regions. Over 2.5 million individuals die of the illness annually or regarding identical range as HIV and most of those deaths area unit in poor countries.

Acknowledgement

None

Conflict of Interest

None

1. Mannino DM, Brown C, Giovino GA (1997) Obstructive lung disease deaths in the United States from 1979 through 1993. An analysis using multiple-cause mortality data. Am J Respir Crit Care Med 156:814-818.

Indexed at, Google Scholar, Indexed at

2. Chen JC, Mannino DM (1999) Worldwide epidemiology of chronic obstructive pulmonary disease. Curr Opin Pulm Med: 93-99.

Indexed at, Google Scholar, Indexed at

3. Rennard SI (1998) COPD: overview of definitions, epidemiology, and factors influencing its development. Chest 113: 235S-241S.

Indexed at, Google Scholar, Indexed at

4. Behera D, Jindal SK (1991) Respiratory symptoms in Indian women using domestic cooking fuels. Chest 100: 385-388.

Indexed at, Google Scholar, Indexed at

5. Anthonisen NR, Connett JE, Kiley JP, Altose MD, Bailey WC, et al. (1994) Effects of smoking intervention and the use of an inhaled anticholinergic bronchodilator on the rate of decline of FEV1. The Lung Health Study. JAMA 272: 1497-1505.

Indexed at, Google Scholar, Indexed at

6. Nickels AS, Joshi AY, Dinakar C (2014) Electronic cigarettes: navigating the vapor. Ann Allergy Asthma Immunol 112: 481-483.

Indexed at., Google Scholar, Indexed at

7. Bohadana A, Teculescu D, Martinet Y (2004) Mechanisms of chronic airway obstruction in smokers. Respir Med 98: 139-151.

Indexed at, Google Scholar, Indexed at

8. Clayton D, Schifflers E (1987) Models for temporal variation in cancer rates. II: Age-period-cohort models. Stat Med 6: 469-478.

Indexed at, Google Scholar, Indexed at