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Non communicable diseases epidemeology

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Non communicable diseases epidemeology

  1. 1. Diseases of Non-communicable Diseases By Epidemiology Dep’t Group 2 1 Bahir Dar University, Ethiopia November 11, 2019 College of Medicine and Health Sciences School of Public Health Department of Epidemiology and Biostatics
  2. 2. Group members  Getenet Dessie (BSc,MSc)  Amsalu Worku (MD,Assistant professor in obey/gyn)  Biniyam Teshome (MD,FCS Orthopedic Surgeon)  Temesgen Assefa (MD,Assistant professor in internal medicine)  Waltenigus Guadie (MD,Assistant professor in obey/gyn)  Yihun Miskir (BSc, Assistant professor in EMCCN)  Minyichil Birhanu (BSc,MSc)  Tadios Lidetu (BSc)  G/Medihin Getu (BSc)  Ayalew Kassie (BSc) 2
  3. 3. Presentation outline  Objectives  Epidemiology of NCD  Distribution and pattern of tope five non communicable diseases (CVD,CA,DM,CRD&MI  Impact of non-communicable diseases on life expectancy  Summary 3
  4. 4. Non communicable Diseases Objectives  To define NCD  To describe global, regional and national distribution of non- communicable diseases  To analysis global, regional and national pattern of tope five non communicable diseases that accounts for high mortality and morbidity across the globe  To analysis the impact of non-communicable diseases on life expectancy YLL DALYs 4
  5. 5. Method of accessing informations  Electronic web-based search of PubMed,,CINHAL, EMBASE, SCOPUS, African Index Medicus, lancet and African Journals  For PUBMED advance search, Medical Subject Headings (MeSH terms) were used to help expand the search strategy.  We built a search strategy by using the Boolean operator separately and/or in combination of keywords 5
  6. 6.  Chronic conditions that do not result from an (acute) infectious process and hence are “not communicable.” • A disease that has a prolonged course, that does not resolve spontaneously, and for which a complete cure is rarely achieved.  Tunstall-Pedoe, 2006 Definition of NCDs 6
  7. 7.  Complex etiology (causes)  Multiple risk factors  Long latency period  Non-contagious origin (noncommunicable)  Prolonged course of illness  Functional impairment or disability  (Capps, 2001). Nature & Characteristics of NCDs 7
  8. 8.  Cardiovascular disease (e.g., Coronary heart disease, Stroke, HPN)  Cancer  Chronic respiratory disease  Diabetes  Mental illness  account for the majority of deaths and disabilities (Gouda et al., 2019; WHO, 2018). Types of NCDs 8
  9. 9. Epidemiology of NCDs  Before :- The “diseases of modern life”  Currently:- they are becoming the leading causes of morbidity and mortality in many developing countries too >85%  Health challenges of the 21st century.  Epidemiologic transition in many developing countries  (Capps, 2001). 9
  10. 10. Epidemiology of NCDs…..  Epidemiologic transition starts since the end of World War II  Antibiotics ,  Vaccines,  along with improved living standards, sanitation, nutrition, and safe water, (Capps, 2001). 10
  11. 11. Epidemiology of NCDs….. 11
  12. 12. Major NCDs responsible for deaths Globally from all global deaths 31%7% 16% 12 3% 57% Cancers Diabetes (Kisa & Collaboration, 2019).
  13. 13. “The World Health Report 2016”85 % 4% 22% 44% 9 % Respiratory diseases Cancers Diabetes “The World Health Organization Report 2016” Five major NCDs responsible for deaths Globally from all NCDS 3 % Mental illness 13
  14. 14. Epidemiology of NCDs….. Figure 1: DALYs for non-communicable diseases by age and sex, 2017 14
  15. 15. Epidemiology of NCDs…..  75% of premature adult deaths (occurring in those aged 30–69 years) were caused by NCDs  NCDs are not solely a problem for older populations.  The probability of premature death among adults due to NCD:-  Eastern Mediterranean 24%  South-East Asian 23% regions  African 22%  Americas (15%),  European (17%)  Western Pacific (16%) regions.  The risk of dying from any one of the four main NCDs for those aged 30–69 years, decreased from 22% in 2000 to 18% in 2016 (Moraga & Collaborators, 2017). 15
  16. 16. Epidemiology of NCDs…..  In all WHO regions, the probability of dying from a NCD was greater for males than for females (Moraga & Collaborators, 2017).  From income level perspective a clear relationship is evident  In 2016, 78% of all NCD deaths, and 85% of premature adult NCD deaths, occurred in low- and middle- income countries  NCD related premature deaths in developed country (25%) ; low-income (43%) and lower-middle-income (47%) countries (Moraga & Collaborators, 2017). 16
  17. 17. Epidemiology of NCDs….. Figure 1: proportion of NCD death occurring among those aged 30-69 years, by income group, 2016. 17
  18. 18. Epidemiology of NCDs….. Figure 1 : Proportion of NCD death occurring among those aged 30-69 years, by WHO region, 2016. 18
  19. 19. Non communicable diseases in sub- Saharan Africa  Between 1990 and 2017, the total number of DALYs due to NCDs for all ages increased rapidly in the region  From around 90·6 million to 151·3 million, representing a 67·0% increase.  Of the total burden of disease, the proportion of NCDs contribution on total DALYs increased from 18·6% to 29·8%  (Gouda et al., 2019). 19
  20. 20. NCDs in sub-Saharan Africa ………………  CMNN diseases declined Vs High NCD burden increase  The growth in population size was the key driver of NCD burden over this period  The age-standardized DALY rate due to NCDs (21 757·7 DALYs per 100 000 population is now almost equivalent to that for CMNN diseases (26 491·6 DALYs per 100 000 population [25 165·2–28 129·8] (Gouda et al., 2019). 20
  21. 21. NCDs in sub-Saharan Africa ………………  The increase in total DALYs due to NCDs can be largely explained by the population growth and in lesser extent, by population ageing (Gouda et al., 2019).  Only in southern sub-Saharan Africa were changes substantially explained by an ageing population.  Zimbabwe and Lesotho, have seen rapid increases in NCD burden in terms of both absolute DALYs and DALY rates, in contrast to other countries in sub-Saharan Africa, where age-standardized DALY rates have decreased (Gouda et al., 2019). 21
  22. 22. NCDs in sub-Saharan Africa …… 22 Burden of non-communicable diseases by country in sub-Saharan Africa, 2017(GBD,20176)
  23. 23. NCDs in sub-Saharan Africa ………………  Compared with global estimates, sub-Saharan Africa had a high burden of NCDs overall in 2017 (Gouda et al., 2019). Figure 1: Burden of NCD globally and by sub-Saharan African region, 2017. 23
  24. 24. NCDs in Ethiopia  Successful in reducing deaths related to CMNN diseases and injuries by 65%,  However, NCD join to be the leading causes of premature mortality and death rates in 2015 (Misganaw et al., 2017). Figure 1: National Proportional Mortality of NCDs in Ethiopia, 2018 (Organization, 2018). 16% 7%2% 2% 9% 9% Proportion of mortality due to non comunicable diseases Cardiovascular disease Cancers Respiratory disease Diabetes Injuries Other NCD 24
  25. 25. NCDs in Ethiopia……….. 1990–2015 Deaths due to NCDs declined by 37% ( Misganaw et al., 2017) Despite incensement of the prevalence of NCD in Ethiopia,risk of premature death due to NCDs is decreasing from 2000 to 2025 WHO, 2018 . Figure1 : Trend of risk of premature death due to NCDs in ethiopia,2018(WHO, 2018) 25
  26. 26. Global trends in healthy life expectancy early death and disability explained by NCDs  Globally, in 2017, life expectancy was 73 years, but healthy life expectancy was only 63 years.  This means on average 10 years of life were spent in poor health in 2017.  This is mainly due to the trend of communicable and non- communicable diseases. (Metrics & Evaluation, 2018). 26
  27. 27. life expectancy and NCDs…… Figure 7: life expectancy at birth for both sexes across the region, 2017. 27
  28. 28. life expectancy and NCDs……  The next two decades will see dramatic changes in the health needs of the world's populations.  Developing regions (four-fifths of the planet's people live)  Non-communicable diseases such as depression and heart disease are fast replacing traditional enemies;  infectious diseases malnutrition, as the leading causes of disability and premature death (A. D. Lopez & C. C. Murray, 1998). 28
  29. 29. life expectancy and NCDs……  In 2020, NCD are expected to account for seven out of every ten deaths in the developing regions, compared with less than half today.  GBD 2016 ; out of the top 10 causes of death 3 were accounted due to non-communicable diseases and this toll is expected to increases to 8 in 2040 (Metrics & Evaluation, 2018).  In all regions the rapidity of change, will pose serious challenges to health-care systems scarce resources allocation (A. D. Lopez & C. C. Murray, 1998). 29
  30. 30. 30 Antibiotics,s anitati,good nutrition MCH Death by CMN N by 41%. death by NCDs by 40% • Population growth • Aging population • Sedentary life style • Irresponsible feeding • Late dx • Poor self care adherence (Metrics & Evaluation, 2018). Vs life expectancy and NCDs……
  31. 31. 31
  32. 32. 32
  33. 33. World map showing the probability of dying early from chronic disease between 30 and 70 years of age Most nations falling short of targets to cut early deaths from chronic disease in 2018 by Ryan O'Hare ,2018 33
  34. 34. Global trends in risk factors leading to early death and disability……. Figure 1: Leading causes of early death, 2016 and 2040†(Metrics & Evaluation, 2018) 34
  35. 35. Life expectance and NCDs in Ethiopia  NCDs are estimated to account for 30% of total deaths in 2014  the probability of dying between ages 30 and 70 years from the 4 main NCDs is 15% (WHO,2014).  NCD causes ,42% death;27% premature  DALYs ; below 20% in 1990 to 69% in 2015 (Fassil Shiferaw,2018)  . Figure 1: Premature mortality due to NCDs from 2000-2012, Ethiopia. 35
  36. 36. The five major non communicable diseases 1. Cardiovascular diseases  38% causes of non-communicable diseases (NCDs) worldwide (WHO, 2017).  Globally, Cardiovascular disease is the cause for an estimated death of 17 .3 million people every year & this amount is likely to rise to 23.6 million by the end of 2030 (WHO, 2017)  Eastern Europe with highest estimated age-standardized prevalence of IHD in 2015),  Followed by Central Asia and then Central Europe. Eastern sub- Saharan Africa, the Middle East/North Africa region, and South Asia (2,000 prevalent cases per 100,000) ("Roth GA et al, 2017) 36
  37. 37. Global Distribution of the Burden of Cardiovascular Diseases in 2015 37 Source: American College of Cardiology web page
  38. 38. Lauren Wilson,2013 38
  39. 39. Cardiovascular diseases in Africa  In 2013, an estimated 1 million deaths were attributable to CVD in sub-Saharan Africa ( 5.5% of all global CVD related deaths , and 11.3 % of all deaths in Africa.  Almost two fold increases in prevalence of CVD have been reported since 1990.  This dramatic change in the profile of CVD in Africa can be directly linked to population dynamics & epidemiologic transition ("Cardiovascular disease in Africa :epidemiological profile and challenges," 2017). 39
  40. 40. Cardiovascular diseases in Ethiopia  Ischemic Heart disease & Stroke are the 5th & 6th leading cause of death in Ethiopia as of 2018 ("CDC - Ethiopia report on leading causes of diseases in Ethiopia, August 2019,")  Prevalence of cardiovascular disease is rising in incidence ,prevalence & as a cause of death.  From 2014 to 2016), cardiovascular disease is the commonest cause of mortality among Non-communicable diseases ("National strategic Action plan for prevention & control of Non Communicable Diseases in Ethiopia ,2014 -2016,") 40
  41. 41. 2.Cancer  Globally, the odds of developing cancer during a lifetime (ages 0-79 years) were 1 in 3 for men and 1 in 4 for women .  In 2017, skin; tracheal, bronchus, and lung (TBL); and prostate cancers (the most common), accounting for 54% of all cancer cases among men.  For women in 2017, the most common incident cancers were nonmelanoma skin cancer , breast cancer, and colorectal cancer, accounting for 54% of all incident cases (Kisa & Collaboration, 2019). 41
  42. 42. Epidemiology  The largest increase in cancer incident cases between 2007 and 2017 occurred In middle SDI countries with a 52% increase  changing age structure contributed 24%,  population growth 10%  In the lowest SDI quintile, population growth is the major contributor  In high SDI countries, increased incidence is mainly driven by population aging  (Kisa & Collaboration, 2019). 42
  43. 43. Age specific incidence rate 43 Figure 10: Average Annual Percentage Change in Age-Standardized Incidence Rate in Both Sexes for All Cancers from 2007 to 2017.
  44. 44. Age specific mortality rate 44
  45. 45. Cancer incidence and mortality based on SDI 45
  46. 46. Cancer incidence and mortality based on SDI 46
  47. 47. Cancer in Ethiopia Incidence of the three commonest cancers in men across different age categories in Ethiopia, 2015 (Memirie et al., 2018) 47
  48. 48. Cancer in Ethiopia Incidence of the three commonest cancers in women across different age categories Ethiopia,2015 (Memirie et al., 2018 48
  49. 49. 3.Diabetes 49 Figure 1: Ten countries with the largest number of adults with diabetes in 1980 and 2014.
  50. 50. Worldwide distribution of diabetes …. 50 Figure 1: trends in prevalence of diabetes, 1980–2014, by country income group (Roglic, 2016).
  51. 51. Trends in the number of adults with diabetes by region 51 Figure 1: Trends in the number of adults with diabetes by region (A) and decomposed into the contributions of population growth and ageing rise in prevalence, and interaction between the two (B).
  52. 52. Diabetes in Ethiopia  In 2016, overall diabetes prevalence among male and female was 4.0% and 3.6% respectively (WHO, 2016). 52 Figure 1: Trends in age-standardized prevalence of diabetes in Ethiopia,2016 (Organization, 2016).
  53. 53. 4.Chronic respiratory diseases  In 2015, 3.2 million people died from COPD worldwide, an increase of 11.6% compared with 1990.  From 1990 to 2015, the prevalence of COPD increased by 44.2%  In 2015, 0.40 million people (0.36 million to 0.44 million) died from asthma  The prevalence of asthma increased by 12.6% (9.0 to 16.4), 17.7% (15.1 to 19.9) (Soriano et al., 2017).  However age-standardized prevalence decreased for both diseases 53
  54. 54. Age-standardized DALY due to asthma 54 Figure 1: Age-standardized DALY rate per 100 000 people due to asthma, by country, both sexes, 2015
  55. 55. 5.Epidemiology of mental illness  Mental illness comprised 13% of the total global burden of disease in 2000 – a figure that is expected to rise to 15% by the year 2020. (Heron MP,2018)  Between 35% and 50% of people with severe mental health problems in developed countries; 76 – 85% in developing countries, receive no treatment.  Mental health problems are a growing public health concern (Saxena S, 2014). 55
  56. 56. Epidemiology of mental illness…..56 WHO,2018
  57. 57. Disability-adjusted life years (DALYs) distribution by country (%) 57 WHO,2018
  58. 58. Mental illness epidemiology in Africa  Mental health problems appear to be increasing in importance in Africa.  Between 2000 and 2015 the number of years lost to disability as a result of mental and substance use disorders increased by 52%.  In 2015, 17·9 million years were lost to disability as a consequence of mental health problems.  Such disorders were almost as important a cause of years lost to disability as were infectious and parasitic diseases, which accounted for 18·5 million years lost to disability (WHO Global Health Estimates 2016 58
  59. 59. Mental illness epidemiology in Ethiopia  The average prevalence of mental disorders in Ethiopia was 18 % for adults and 15% for children.  Families now do not need much agitation to seek medical help for their mentally ill members.  By consequence, a large number of the adolescent is homeless, and lives on the street  (Sathiyasusuman A. 2011).  rural area of Ethiopia comprised 11% of the total burden of disease, with schizophrenia and depression  (Fdroemo H. 2015/16.). 59
  60. 60. Summary  NCDs are global health and socio-economic threat both in developing and developed countries  Becomes High in developing countries Growth and aging of populations;  it needs sustainable multi-sectoral intensive efforts and resources to achieve the target goals. 60
  61. 61. 61
  62. 62. Acknowledgement Dr. Achenef Motbainor (BSc,MPH,PhD) Author of all findings 62
  63. 63. 63

Notas del editor

  • do not have a single genetic cause—they are likely associated with the effects of multiple genes (polygenic) in combination with lifestyle and environmental factors. Conditions caused by many contributing factors are called complex or multifactorial disorders.
    Although complex disorders often cluster in families, they do not have a clear-cut pattern of inheritance.
  • Today's health challenges are formidable, including an ageing population; unhealthy lifestyles; the burden of behavioural determinants leading to increased mortality and morbidity from noncommunicable diseases;
  • Life style related
  • Metrics: Disability-Adjusted Life Year (DALY)
    Quantifying the Burden of Disease from mortality and morbidity
    One DALY can be thought of as one lost year of "healthy" life. The sum of these DALYs across the population, or the burden of disease, can be thought of as a measurement of the gap between current health status and an ideal health situation where the entire population lives to an advanced age, free of disease and disability.
    DALYs for a disease or health condition are calculated as the sum of the Years of Life Lost (YLL) due to premature mortality in the population and the Years Lost due to Disability (YLD) for people living with the health condition or its consequences:
    The YLL basically correspond to the number of deaths multiplied by the standard life expectancy at the age at which death occurs. The basic formula for YLL (without yet including other social preferences discussed below), is the following for a given cause, age and sex:
    N = number of deaths
    L = standard life expectancy at age of death in years
    Because YLL measure the incident stream of lost years of life due to deaths, an incidence perspective has also been taken for the calculation of YLD in the original Global Burden of Disease Study for year 1990 and in subsequent WHO updates for years 2000 to 2004.
    To estimate YLD for a particular cause in a particular time period, the number of incident cases in that period is multiplied by the average duration of the disease and a weight factor that reflects the severity of the disease on a scale from 0 (perfect health) to 1 (dead). The basic formula for YLD is the following (again, without applying social preferences):
    I = number of incident cases
    DW = disability weight
    L = average duration of the case until remission or death (years)
    Prevalence YLD
    The recent GBD 2010 study published by IHME in December 2012 used an updated life expectancy standard for the calculation of YLL and based the YLD calculation on prevalence rather than incidence:
    P = number of prevalent cases
    DW = disability weight
    Social value weights (age-weighting and discounting)
    The original Global Burden of Disease Study and WHO updates for years 2000-2004 also applied several social value weights in the calculation of DALYs for diseases and injuries. Apart from the disability weights, these also included time discounting and age weights. For more information on these, select the link on the right-hand side of this page.
  • Eastern meditrinian :Cyprus, Greece, Lebanon, Syria, Israel, Palestine, Turkey, Egypt,[5] Libya, and Jordan
    Countries in the WHO Western Pacific Region
    This map is an approximation of actual country borders.
    Brunei Darussalam
    Cook Islands
    Lao People's Democratic Republic
    Marshall Islands
    Micronesia (Federated States of)
    New Zealand
    Papua New Guinea
    Republic of Korea
    Solomon Islands
    Viet Nam
  • communicable, maternal, neonatal, and nutritional (CMNN)
  • Vs
  • 2,00 equal for all
  • constituid
  • WHO,2018