Risking our future


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GHME 2013 Conference
Session: Global and national Burden of Disease II
Date: June 17 2013
Presenter: Kyle Heuton
Institute for Health Metrics and Evaluation (IHME), University of Washington

Published in: Health & Medicine
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  • Thank you,First, I’ll talk about the data, which risk factors were selected, and how this sets the boundaries of the conclusions we can draw from this study.Next I’ll share the results and highlight some of the features on the diverse landscape of the risks affecting young people. I’ll talk about the risks affecting young people in 3 distinct age groups, 10-14, 15-19, and 20-24.For 15-19 year olds, I’ll focus on the risks affecting females and the contribution of these risk factors to mental health outcomes.In the 20-24 year old age group, I’ll focus on the results for males, and show the more detailed understanding of the health of young people that can be gained from country level estimates Next, I’ll share the role that this stage of life plays in later health outcomes, and how studying the risk factors of young people can result in future health gainsFinally, I’ll conclude by talking about what we can learn from these data and what we still have left to study.
  • All data used in these analyses come from the Comparitve Risk Assessment of the Global Burden of Disease 2010 study.Although this study included 67 risk factors, only these 9 contribute to the burden of disease and injury for 10 to 24 year olds. Risk factors such as smoking and diet were excluded from these age groups as the cardiovascular and cancer outcomes that these risk factors cause typically do not occur until later in life. Another notable absence is unsafe sex, which was included as a risk factor in the 2000 global burden of disease study, but excluded in this iteration due to the absence of robust estimates of exposure. Although this universe of risk factors studied is relatively small, I’ll show that these risks contribute to the leading causes of death and disability in these age groups. Furthermore, these risk factors largely cause non-communicable and injury outcomes, the study of which will become increasingly important as the world of global health undergoes an epidemiological transition away from maternal, communicable, and nutritional deficiencies towards non-communicable diseases and injuries.
  • Now, I’d like to take a look at the results. I’ll be sharing the results in three different age groups, 10-14, 15-19, and 20-24. The reason for this is that both the risk factors themselves as well the magnitude of their impact vary greatly between age groups. Here are the leading risk factors with 95% confidence intervals for 10-14 year olds, globally in 2010. On the y-axis we have the percentage of all Disability Adjusted Life Years, or DALYs, attributable to each risk factor, and along the x axis we have the leading risk factors in decreasing rank. The picture for ten year olds, is largely homogenous: iron deficiency has a far larger impact than any other risk factor globally, and is the leading risk in nearly every country. We can see from this that although as age increases, the 10-14 year old age group is the first age group where non-communicable diseases are responsible for the largest share of the burden, there is still work do be done treating preventable nutritional deficiencies.
  • Moving on to 15-19 year olds, we see a dramatically different risk factor distribution. Alcohol use is now the leading risk, and this is the first age group where occupational risks are tracked, and it is responsible for the second largest share of burden. We still see iron defficiency accounting for 3% of all DALYs for 15-19 year olds, and intimate partner violence is the fourth leading risk factor in this age group. Unlike in 10-14 year olds, there is substantial overlap between the 95% confidence intervals for the estimated effect of the leading risk factors. What this means is that the relative order of risk factors should not be used as strict guidelines for priority setting, but as indications of the probable magnitude of the effect of each risk. Also in 15-19 year olds, the risk distribution varies greatly between the sexes, so for 15-19 year olds, I will focus on the risks affecting females.
  • Here we have a stacked bar chart showing the leading risk factors for 15-19 year old females, and the health outcomes that result. On the y-axis are the leading risk factors, and along the x axis is the percent of total burden attributable to each. Within each bar, the colors represent the different outcomes that each risk factor causes. What this graph shows is that while iron deficiency remains the leading risk factor, we see in this age group a large attribution to mental health outcomes and injuries. The mental health outcomes can be seen in the large green bars in intimate partner violence, alcohol and drug use, and childhood sexual abuse. The small purple bars show transportation injuries, but the far larger source of injuries here are the pink intentional injury pars seen in intimate partner violence and, to a lesser extent, alcohol use, drug use, and childhood sexual abuse. Now I’d like to talk about how these risk factors relate to the burden of disease for 15-19 year old females.
  • Here we have a tree map, or a square pie chart, showing the burden of disease and injury for 15-19 year old females. The size of each box is proportional to the number of DALYs associated with each health outcome. We see that the leading causes for females aged 15-19 are Major Depressive Disorder, or MDD on the graph, at 7.74% of the total burden, and the second largest cause is self harm at 5%. The first thing this graph shows, is the progress we’ve made since 1990. In 1990, Maternal disorders were the 2nd largest contributor to total burden. This is a reflection of the epidemiological transition in health, as we get better at treating maternal causes, communicable diseases, and nutritional deficiencies, a larger share of the burden will be due injuries and non communicable diseases. And now, we can see the value of these risk factors in understanding the burden of disease. In this graph, the darker areas are the areas associated with intimate partner violence. This shows that this risk factor is a major contributor to the leading causes in 15-19 year old females. And so, as we shift our attention increasingly toward depression, self harm, and other non-communicable diseases and injuries, these risk factors will be a key input to understanding the source of and preventing these causes.
  • Now, I’d like to move to 20-24 year olds, and we have here the leading risk factors for both sexes in this age group, globally in the year 2010. These results look similar to the risk distrubtion for 15-19 year olds, and indeed the only difference in the relative ordering is that drug use has risen from 5th to 3rd. However, I decided to separate them because the magnitude of the effects are larger: the total burden of disease is larger for this age group, as well as the proportion that can be attributed to risk factors, so combining 15-24 year olds would hide some truth about the true magnitude of the effect for each age group. Additionally, the burden of injuries is much larger in this age group, there are one third as many DALYs due to injuries in 20-24 year olds as there are in 15-19 year olds. This injury problem is far greater for males than females, so I’d like to focus on males for this age group
  • Here we have the leading risk factors for males aged 20-24 globally in 2010. What jumps out is that alcohol use and occupational risks are responsible for a much larger share of the burden in males than females. Nearly 9% of all DALYs for 20-24 year old males are attributable to alcohol use, and over 7 and a half percent are attributable to occupational risks. Additionally, drug use is responsible for over 4.5% of the burden of disease and injury. When we look at the causes of death and disability that these risk factors result in, we see that a large share, from the dark purple bars and to the right, are injuries, and the green bars, representing drug and alcohol use disorders, are non communicable diseases. This relative ranking of alcohol as the leading cause and occupational risks second is an artifact of aggregating the risks globally. If we look at the country level results, we can see how the picture changes between regions
  • Looking at this map of the leading risk factors for 20-24 year old males, we can see that there are many countries where occupational risks are the leading risk factor. This is true for three of the worlds largest countries: China, India, and Indonesia. Another reason why global and even regional aggregation hides the realties of health risks, is that the magnitude of the effect can vary greatly between countries. Looking at the share of the total burden for 20-24 year old males attributable to alcohol, we see that although alcohol was the leading risk factor in many regions of the world, nowhere is the problem as severe as it is in Eastern Europe, where over 40% of the burden is attributable to alcohol.
  • And now, finally, I’d like to step away from this comparative risk assessment a bit, and talk about the risks of later life, and the role that the adolescent years can play in these. Here we have the leading risk factors for the next 15-year age group, 25-39 year olds in 2010. While the top two risk factors are the same, alcohol use and occupational risks. What we see here that is new is the light blue bars that are risk factors that contribute to cardiovascular outcomes and cancers. Dietary risk appears in this age group as the 3rd largest risk, and smoking, a risk after 25, also appears as the 6th leading risk factor. We know that many of these risk factors, such as smoking, begins in adolescence. By tracking the exposure to these risks at young ages, we could begin to think about future health gains that could be realized by preventing risky behaviors in the 10-24 age range. Knowing the risk exposure at young ages, amount of change in risk exposure at each age, and the relative risk of exposure for health outcomes at older ages, preventative interventions could more accurately estimate future health gains.
  • In summation, the comparative risk assessment of the GBD 2010 study shows large differences in the risks affecting 10-24 year olds, between the sexes, and between countries, and between the 5-year age groups within 10-24 year olds. These differences make study of risk factors at 5 year age groups at the country level critically important. The lessons we learn from these differences can help focus policy as attention shifts toward non-communicable diseases and injuries. A larger focus on drug and alcohol abuse will be crucial to reducing injuries and drug and alcohol use disorders. As the global health community begins to grapple with depression and self harm as major contributors to the burden of disease, understanding the contribution of intimate partner violence will be necessary. However, we saw that, particularly for females, iron deficiency remains a leading risk and there is still work to be done on this front. Furthermore, the risk factors studied here do not comprise the entirety of risks affecting 10-24 year olds. While these risks do contribute to the leading causes of death and disability, more data on the exposure to risk and the relative risk of this exposure is necessary for a complete understanding of what risks contribute to the burden for this age group.
  • Risking our future

    1. 1. Risking our future: June 17, 2013 Kyle Heuton Post-Bachelor Fellow A Comparative Risk Assessment of the Burden of Disease and Injury in Young People Aged 10 to 24, 1990-2010
    2. 2. Outline I. Risk factor selection II. Results A. 10- to 14-year-olds B. 15- to 19-year-olds i. Females aged 15 to 19 ii. Risk factors’ contribution to mental health C. 20- to 24-year-olds i. Males aged 20 to 24 ii. Global variation at the country level III. Conclusions and future directions 2
    3. 3. Methods: choice of risks 3 Alcohol use Intimate partner violence Drug use Childhood sexual abuse Sanitation Lead Unimproved water Occupational risks Iron deficiency
    4. 4. 4 Iron deficiency Leading risk factors and uncertainty 10- to 14-year-olds globally, both sexes Alcohol use Sanitation Childhood sexual abuse Unimproved water Drug use Lead
    5. 5. 5 Leading risk factors and uncertainty 15- to 19-year-olds globally, both sexes Occupational risks Alcohol use Iron deficiency Intimate partner violence Childhood sexual abuse Drug use Sanitation Unimproved water
    6. 6. 6 Leading risk factors and attributable outcomes 15- to 19-year-olds globally, females
    7. 7. Global DALYs, 15- to 19-year-old females 7 DALYs attributable to intimate partner violence DALYs not attributable to intimate partner violence
    8. 8. 8 Leading risk factors and uncertainty 20- to 24-year-olds globally, both sexes Occupational risks Alcohol use Iron deficiency Intimate partner violence Childhood sexual abuse Drug use Sanitation Unimproved water
    9. 9. 9 DALYs attributable to risk factors 20- to 24-year-old males globally
    10. 10. Global variations: 20- to 24-year-old males, 2010 10 Leading risk factorsPropotion of DALYs attributable to alcohol use
    11. 11. The future of these young people 11 Leading risk factors for 25- to 39-year-olds globally, 2010
    12. 12. The future of these results 12 • Crucial to study five-year age groups at the country level • A larger focus on drug and alcohol abuse and intimate partner violence and their effects on outcomes of injuries and mental health • More work on nutritional deficiencies • A need for more exposure and relative risk data on young people