Understanding Women’s Health Gap – Asrar Qureshi’s Blog Post #995

Understanding Women’s Health Gap – Asrar Qureshi’s Blog Post #995

Dear Colleagues! This is Asrar Qureshi’s Blog Post #995 for Pharma Veterans. Pharma Veterans Blogs are published by Asrar Qureshi on its dedicated site https://pharmaveterans.com. Please email to aq.pharmaveterans@gmail.com for publishing your contributions here.

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26 August was Women’s Equality Day. Their health gap is a major challenge in achieving equality. Links of resources for this post at the end.

Women live longer than men, but they spend 25 percent more of that time in poor health. Closing this gap can add more healthy years to their lives. It must be recognized that women’s health is not just a scaled down version of men’s health, but that it is biologically distinct and different.

McKinsey Health Institute – MHI – in collaboration with World Economic Forum, has done detailed research and analysis on country-wise situation of women’s health, their specific diseases and challenges, and its economic impact. I shall share some of this information here. 

To put things in perspective, it should be understood that women’s health is not a standalone matter, but rather one that affects individuals, families, and the economy. 

Women’s health encompasses the range of health experiences that affect women uniquely, differently, and disproportionately than men. Women are not simply smaller versions of men; their biology is uniquely different which goes beyond differences in reproductive organs. Sexual and Reproductive Health – SRH – and maternal, neonatal, and child health account for only 5 percent of women’s health burden. More than half of the women’s health burden reflects conditions that affect women disproportionately or differently, with most of the impact affecting women’s working years. 

Let us have a look at some data to understand more deeply.

All Countries – Gap for efficacy and care delivery, by 2040, million DALYs (Disease Adjusted Life Years)

The gap for care, delivery, and efficacy, in all countries for all conditions, is 69.4 million DALYs. Additionally, the data gap contributes to 5.5 million DALYs.

• Cardiovascular diseases         17.9 million DALYs

• Cancer         12.4 million

• Gynecological diseases          5.9 million

• Maternal and Newborn disorders 4.4 million

• Mental disorders         4.3 million

• Chronic respiratory diseases 3.7 million

• Neurological disorders         3.3 million

• Intestinal infections 3.2 million

• Bone & joint diseases 3.0 million

• Respiratory infections & TB 2.9 million

• Neglected tropical diseases 2.2 million

• Diabetes & kidney diseases 2.0 million

• Digestive diseases        1.8 million

• Sense organ diseases 1.0 million

• Substance use disorders         0.67 million

• HIV/AIDS & STIs        0.59 million

It will be instructive to see Pakistan and a few regional countries’ data to establish the context.

Pakistan – Population of 250 million. The gap for care delivery and efficacy, for all conditions is 2.2 million DALYs. Additionally, the data gap contributes to 165,618 DALYs.

• Maternal & newborn disorders 0.63 million DALYs

• Cancer         0.27 million

• Cardiovascular diseases         0.25 million

• Intestinal infections 0.20 million

• Respiratory diseases & TB 0.20 million

• Gynecological diseases         0.17 million

• Mental disorders         0.10 million

• Chronic respiratory diseases 0.07 million

• Neurological disorders         0.06 million

• Diabetes & kidney diseases 0.06 million

• Digestive diseases         0.05 million

• Bone & joint diseases 0.04 million

• Sense organ diseases 0.03 million

• Neglected tropical diseases 0.02 million

• HIV/AIDS & STIs         0.008 million

• Substance use disorders         0.008 million

Pakistan – by age group

• Under 10 years of age 0.66 million DALYs

• 10 – 19 years 0.17 million

• 20 – 29 years 0.30 million

• 30 – 39 years 0.28 million

• 40 – 49 years 0.24 million

• 50 – 59 years 0.19 million

• 60 – 69 years 0.17 million

• 70 – 79 years 0.11 million

• 80 – 89 years 0.04 million

Our biggest loss is in under 10 years category. However, during the productive/ work years, 20 – 60 years of age, our loss adds up to about one million, which is 50% of total loss. This is extremely significant because it has direct impact on the economic activity.

Regional Countries

India – with a population of over 1.25 billion, five times that of Pakistan, the gap for care delivery and efficacy, for all conditions, is 10.4 million DALYs. Their top three categories are: cardiovascular diseases – 1.66 million; cancer – 1.3 million; and gynecological diseases – 1.1 million.

Bangladesh – Population 172 million. The gap for care delivery and efficacy, for all conditions, is 1.0 million DALYs. Their top three categories are: cardiovascular diseases – 0.17 million; cancer – 0.13 million; and gynecological diseases – 0.13 million. 

Sri Lanka – Population 22 million. The gap for care delivery and efficacy, for all conditions, is 131,476 DALYs. Their top three categories are: cardiovascular diseases – 0.03 million; cancer – 0.02; and chronic respiratory diseases – 0.02 million.

Iran – Population 88 million. The gap for care delivery and efficacy, for all conditions, is 606,392 DALYs. Their top three categories are: cardiovascular diseases – 0.02 million; gynecological diseases – 0.009 million; and mental disorders – 0.008 million.

Afghanistan – Population 42 million. The gap for care delivery and efficacy, for all conditions, is 367,907 DALYs. Their top three categories are: maternal &newborn disorders – 0.07 million; cardiovascular diseases – 0.06 million; and neurological disorders – 0.04 million.

Discussion

You would have noticed that cardiovascular diseases are among the top three diseases in all countries listed above. Ordinarily, cardiovascular diseases are associated with men because of their lifestyle and level of stress, but women are not far behind. Similar notion is carried about cancer.

I may also mention here that this data, which is collected by Institute of Health Metrics and Evaluation, National Transfer, OECD, Oxford Economics, and MHI, may still suffer from historical underreporting and data gaps in women’s health conditions. Moreover, race, ethnicity, socioeconomic status, disability, and age may impact the data in some way due to discrimination and disadvantage. 

Women make over 50 percent of the population, and they are becoming part of workforce in greater number everywhere. In Pakistan, girls are leading in education and therefore, will be a major part of workforce. It is imperative to look at women’s health more seriously and make arrangements, policies, resources, tools, to do more for this cause.

Concluded.

Disclaimers: Pictures in these blogs are taken from free resources at Pexels, Pixabay, Unsplash, and Google. Credit is given where available. If a copyright claim is lodged, we shall remove the picture with appropriate regrets.

For most blogs, I research from several sources which are open to public. Their links are mentioned under references. There is no intent to infringe upon anyone’s copyrights. If, however, it happens unintentionally, I offer my sincere regrets.

References:

https://www.mckinsey.com/featured-insights/themes/closing-the-womens-health-gap?cid=other-eml-alt-mip-mck&hlkid=8a3a6b3589c748af830d97548921af9a&hctky=2208791&hdpid=0b5d87a9-3a04-4a8d-88d2-7d1bfb5030fd

https://www.mckinsey.com/mhi/our-insights/bridging-the-womens-health-gap-a-country-level-exploration?stcr=2ED978A265834D2486CAC12847593914&cid=other-eml-alt-mip-mck&hlkid=6dd7c240d99f42ac928da08e1ce10b58&hctky=2208791&hdpid=0b5d87a9-3a04-4a8d-88d2-7d1bfb5030fd