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Post by Admin on Aug 13, 2021 19:34:10 GMT
Thanks for participating in Module 1! Please complete the activity below and post your response. Feel free to comment on other's findings and ask questions. Use the IHME Global Burden of Disease tool we introduced during the first lecture to explore a disease process that falls within your field of interest. Notice the geographic differences in DALYs for your selected disease process. Notice how DALYs change in a particular location over time. You can also sort DALYs by income groups. Also explore the " Deaths" and "YLD- Years Lived With Disease" setting. Take a screenshot of 1-2 interesting findings you have made, post it, and comment. Let us know what we are looking at, and bonus if you find an article or event that explains the trend in DALYs or your selected metric. Follow this link: vizhub.healthdata.org/gbd-compare/ and gather data. For more specific details on how to use, please refer to your pre-reading handout. |
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Post by christyhenderson on Aug 14, 2021 15:27:15 GMT
 I searched through the change in DALY's in Mexico from one of the years I lived there, to now. What most stood out to me was that violence and self-harm have actually increased significantly over time. |
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Silky
New Member
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Post by Silky on Aug 17, 2021 14:08:48 GMT
Thank you for organizing this course! Love the IHME GBD tool. My focus is on neuro-oncology, so took a deeper dive on Brain and Central Nervous System cancer. Below is the screenshot of DALYs for Brain and CNS tumors for all ages over the years. Interestingly, DALYs per 100,000 was higher for HIC compared to LIC and LMIC. No major change in this trend was noted over the years. Similar trends were noted for mortality rates - Deaths per 100,000 are higher 4-5/100,000 in HIC, which have increased by 1 per 100,000 over years. For LIC and LMIC, the deaths per 100,000 are lower compared to HIC (range of 1-2 per 100,000) and these has not changed over the years. Another interesting finding - for age < 5 years or 5-14 years, the DALYs for HIC is lower so is the death per 100,000 compared to LIC. For all ages, the higher DALYs in HIC might be from loss of functional health driven by a combination of aging population and stagnant age-specific rates of years lived with disability - higher YLDs compared to some LIC and LMIC. A part of this trend could also be due to the effect of accurate reporting. The reporting of prevalence, death and disability is a challenge for LIC and LMIC given lack of registry based resources and personnel - this might effect the DALYs reported and hence the trend.   |
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Silky
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Post by Silky on Aug 17, 2021 14:25:15 GMT
Sharing findings from a nicely done paper on GBD for Brain and CNS tumors. Below are few tables and figures to highlight interesting conclusions. As summarized in the table, for all countries, the prevalence and incidence of Brain and CNS tumors has increased from 1990 to 2017, death rate has slightly increased, DALYs and YLDs have increased while YLL has decreased. The authors used QCI - Quality Care Index, to compare the quality of care provided in various countries. Figure/Map with shades of green color, where QCI is plotted in the range of 0-100, higher number is represented by light green color and reflects better care, whereas the dark green color reflects lower quality. Patients managed in HIC had higher QCI compared to those managed in LIC . This finding was intuitive for most part with exception for some LMIC where QCI was close to 75. Another interesting finding was difference in GDR/Gender discrimination ratio. This is demonstrated in map with shades of red and blue, where blue color represent equal distribution whereas red presents distribution favoring male patients. The inequality of distribution was noted in both HIC and LIC but more so in LIC. Here's the article - PMID: 33617563   Attachments:
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Post by mollybrazil on Aug 24, 2021 1:39:22 GMT
I looked at ischemic heart disease DALYs and Deaths per 100,000 in the different World Bank income levels. I thought it was interesting that despite three quarters of deaths due to IHD occurring in low and middle income countries, the death rate in low income countries was actually by far the lowest of the income levels. I found a paper that looks at the factors that affect this, including the epidemiologic transition that is occurring as countries go through industrial and economic development at different times. _  _  _ www.ncbi.nlm.nih.gov/pmc/articles/PMC2864143/ |
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Post by mollybrazil on Aug 24, 2021 1:44:42 GMT
In response to Christy, it's interesting to think about what led to this trend. I think there are numerous things we can probably point to as a contributor, including climate change disrupting agricultural exports, leading to less jobs. The illegal drug trade and Cartels seems to also be a major issue right now, though I won't pretend to be an expert in that field.
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Post by Admin on Aug 26, 2021 19:44:32 GMT
Thank you Christy, Molly, and Silky for getting the discussion going! This exercise is a great way to think about the data we end up seeing in the literature - and all the factors that lead to that outcome. Great work!
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Post by shobanaram on Aug 30, 2021 0:21:17 GMT
I spent some time in medical settings in Bhutan and India, and I wanted to use the IHME tool to look at mental health and substance use within these two countries over time. One aspect of Bhutan's political climate that was always intriguing to me was the emphasis on the happiness level of the community. A prior King of Bhutan developed the Gross National Happiness Index (as a marker to be viewed as valuable as GDP) and Bhutan has previously been listed as the happiest country in South Asia. I was surprised to see on the IHME tool that comparing the 1990s to now, Bhutan has had increased levels of depression and substance use (specifically alcohol use) compared to prior. Increasing rates of youth unemployment, and climate change's effects on energy sources might be part of what is contributing to this per this article: www.npr.org/sections/parallels/2018/02/12/584481047/the-birthplace-of-gross-national-happiness-is-growing-a-bit-cynicalAttachments:
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Post by strainsk on Sept 6, 2021 18:49:32 GMT
The global burden of pancreatic cancer has been noted to have significantly increased since the 1990s (https://www.thelancet.com/journals/langas/article/PIIS2468-1253(19)30347-4/fulltext#seccestitle170). I was curious as to what countries had the higher YLD and DALYs given this significant finding. To my surprise, Japan has the highest YLD that has yet to plateau according to the chart below.  We know that age is a significant risk factor for pancreatic cancer but the other notable risk factors such as obesity, smoking, and diabetes aren't as prevalent in this country. In fact, according to the GBD comparison risks comparisons, the rate of smoking is decreasing in Japan and the rates of metabolic and diet risk factors have remained constant over time. Is the trend truly age driven? |
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Post by strainsk on Sept 6, 2021 19:02:27 GMT
In response to the post below: it would be interesting to see how the QCI would begin to change, even for the light green colored countries, as the genetic subtype is now becoming "standard" when making a diagnosis for various brain tumors. For example, would a patient with an IDH-mutant astrocytoma necessarily have a better QCI as compared to a higher grade IDH-wt tumor? As in, would this be tumor biology dependent at all? Would this also reflect the data you discussed on the difference between males vs. females? I know this would be a long way to go to connect specific tissue diagnosis to GBD data but would be interesting to see how this played out if it were able to be put together. Sharing findings from a nicely done paper on GBD for Brain and CNS tumors. Below are few tables and figures to highlight interesting conclusions. As summarized in the table, for all countries, the prevalence and incidence of Brain and CNS tumors has increased from 1990 to 2017, death rate has slightly increased, DALYs and YLDs have increased while YLL has decreased. The authors used QCI - Quality Care Index, to compare the quality of care provided in various countries. Figure/Map with shades of green color, where QCI is plotted in the range of 0-100, higher number is represented by light green color and reflects better care, whereas the dark green color reflects lower quality. Patients managed in HIC had higher QCI compared to those managed in LIC . This finding was intuitive for most part with exception for some LMIC where QCI was close to 75. Another interesting finding was difference in GDR/Gender discrimination ratio. This is demonstrated in map with shades of red and blue, where blue color represent equal distribution whereas red presents distribution favoring male patients. The inequality of distribution was noted in both HIC and LIC but more so in LIC. Here's the article - PMID: 33617563 View AttachmentView Attachment |
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Post by danika on Sept 10, 2021 1:16:46 GMT
Hi everyone! I had never used the IHME tools before so I found this resource and exercise very eye opening and plan to use it in the future. The disease process I chose to look at is Epilepsy, as it is a clinical and research interest of mine. Although epilepsy is prevalent worldwide, I typically just focus on this disease and its treatment within a domestic context, so wanted to learn more about its global impact. The first graph shows idiopathic epilepsy DALYs per 100,000 from 1990-2019 in 4 world bank income class groups (High, Upper middle, Lower middle, Low). I was surprised to see the high income group did not change much during this time period and glad to see the other three categories decreased pretty linearly over this time span. The second graph shows deaths per 100,000 for the same disease, time span and income class groups. The most interesting finding is that the death rate in the high income group is NOT the lowest and in fact the only group of the four that is on the rise, crossing over with the upper middle income group around 2005. I'm not sure why this might be, but perhaps because high income groups are more likely to pursue surgical treatment for their epilepsy, which carries surgical risk of mortality. The last graph is YLD or years of life lost to disability for the same group, timespan and income groups. This metric has not changed much in 20 years and is as expected with low income highest and high/upper middle comparable and lower. ![]()    Here is a related article on the systematic analysis of the global burden of epilepsy from 1990-2016 (figure 4 demonstrates the trend in DALYs) www.thelancet.com/journals/laneur/article/PIIS1474-4422(18)30454-X/fulltext |
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Post by danika on Sept 10, 2021 1:27:33 GMT
Thank you for organizing this course! Love the IHME GBD tool. My focus is on neuro-oncology, so took a deeper dive on Brain and Central Nervous System cancer. Below is the screenshot of DALYs for Brain and CNS tumors for all ages over the years. Interestingly, DALYs per 100,000 was higher for HIC compared to LIC and LMIC. No major change in this trend was noted over the years. Similar trends were noted for mortality rates - Deaths per 100,000 are higher 4-5/100,000 in HIC, which have increased by 1 per 100,000 over years. For LIC and LMIC, the deaths per 100,000 are lower compared to HIC (range of 1-2 per 100,000) and these has not changed over the years. Another interesting finding - for age < 5 years or 5-14 years, the DALYs for HIC is lower so is the death per 100,000 compared to LIC. For all ages, the higher DALYs in HIC might be from loss of functional health driven by a combination of aging population and stagnant age-specific rates of years lived with disability - higher YLDs compared to some LIC and LMIC. A part of this trend could also be due to the effect of accurate reporting. The reporting of prevalence, death and disability is a challenge for LIC and LMIC given lack of registry based resources and personnel - this might effect the DALYs reported and hence the trend. View AttachmentView AttachmentNice post, silky. It is surprising that DALYs and deaths are higher in the high income groups - I wonder how this may be related to tumor severity/prevalence since higher income countries have a longer life expectancy and probably have higher rates of tumors because of that. Perhaps also because patients in higher income countries are more likely to receive/pursue surgical treatment which carries its own mortality. Also may be related to better reporting/recording of cases and organization of data for analysis in higher income countries. Would be interesting to see how this breaks down further by tumor subtype and with surgical vs medical treatments. Thanks for sharing! |
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Post by rachaelpellegrino on Oct 13, 2021 23:24:54 GMT
I have recently been working on a project looking at disparities in premature mortality in our HIV clinic and we were using years of potential life lost (YPLL) as a measure of premature mortality and found that women had higher rates of YPLL than men. I used the IHME tool to look at YPLL for HIV and STIs by sex and by country and it was interesting to see the differences in this data and the significant variation by country. Many of these countries have higher HIV prevalence among women than in the US and it would be interesting to discuss country specific factors that are contributing.
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Post by alyssaseibold on Apr 18, 2022 22:44:22 GMT
I found it super interesting to utilize the Global Health Data Exchange to see how DALY have changed over time in the various countries. As i spent a year abroad in Cameroon, it was especially interesting to see how it had changed with increase in HIV/STI as well as malaria. I thought this was interesting as there has been a significant amount of time invested in these, however, it has increased over time.
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