Are women's health issues underfunded?

In fact, in almost three-quarters of cases where a disease mainly affects one gender, so-called “men's diseases” are overfunded, while “women's diseases” receive severely underfunding. Can't log in? Have you forgotten your password? If the address matches an existing account, you'll receive an email with instructions to reset your password. Can't log in? Forgot your username? If the address matches an existing account, you will receive an email with instructions to recover your username. Gender bias has been an ongoing problem in health care and has manifested itself in different ways.

Other examples include the underrepresentation of women in health studies, the trivialization of women's complaints and discrimination in the granting of research grants. In this paper, we extend the analysis of Mirin et al., 4 to examine the gender disparity between the full spectrum of NIH-funded diseases. That analysis used statistical regression to compare the funding of diseases in relation to the burden of disease, using data from the NIH, to develop an estimate of funding proportional to the burden. Actual funding was compared to burden-proportional funding to determine which diseases are relatively underfunded or overfunded.

Here, we correlate the degree of underfunding or overfunding with the gender prevalence of each disease. Our approach to comparing disease funding is to use the burden of disease as a normalizing factor. Compared to the simplest measure of dollars per patient, normalization with respect to burden creates a more meaningful comparison by taking into account the impact of disease. The burden of disease is most commonly measured in terms of morbidity (the degree of disability) and mortality (the rate and prematurity of death), although economic and sociological factors could also be considered, 15 For the purpose of this study, we quantify the burden using the disability-adjusted year of life (DALY), a measure that estimates the number of years lost due to illness.

The DALY was developed by the World Health Organization16 and has been used by the NIH to compare its allocation of funds between selected diseases.17 DALY folds prevalence, morbidity and mortality into a single measure that represents the sum of years lost due to disability (ADL) and years lost due to disability (ADL) death (YLL). Therefore, it can be used to compare the impacts of primarily disabling diseases with those of primarily life-threatening diseases. The DALY can be defined using the incidence or prevalence of the disease. The Global Burden of Disease (GBD) study18, from which NIH obtains its burden data, uses the prevalence-based method, through which the results of that analysis are reproduced here (Fig.

Each blue dot represents an NIH-funded disease, with the horizontal axis measuring burden (in DALYs) and the vertical axis measuring funding. Each axis is plotted on a logarithmic scale to represent numerical variations in several orders of magnitude. Therefore, the resulting data-adjusted power law (shown in green) is presented as a straight line. Due to the logarithmic scale, the vertical distance between two points measures a percentage difference between actual funding and that corresponding to the burden of disease.

For each of the 74 diseases, we calculated the ratio of actual funding to burden-proportional funding, as represented by the green trend line (Fig. We label a disease as underfunded if that ratio is 1 (its point will be above the green line). Ethical judgment is not intended; this is simply a way of categorizing whether funding for a particular disease is lower or greater than the value commensurate with its burden. We assess whether each disease proportionately affects more American women or men, and for this purpose we only use the dominant female or male terminology.

This categorization is achieved through an extensive literature search, in which multiple sources have been identified for each disease (see Complementary Appendix SA. For a disease to be labeled as gender dominant, at least 60% of those affected are required to be of that particular gender. This is to allow for prevalence, inaccuracies, and variation of information between sources. We also identify diseases in which 55-60% of those affected are of a particular genus and we label them as semi-dominant.

This characterization is strictly based on prevalence and does not consider whether a disease most adversely affects a particular gender. ADD, attention deficit disorder; DALY, disability-adjusted year of life; HIV, human immunodeficiency virus; AIDS, acquired immunodeficiency syndrome; NIDA, national institute on drug abuse. MS, myalgic encephalomyelitis; CFS, chronic fatigue syndrome; LBW, low birth weight. Deviation measures the extent to which funding differs (multiplicatively) from what is proportional to the burden.

Our effort to assess disease prevalence by gender was based on articles from journals, government websites, medical websites, university websites, newspaper articles and other diverse sources, in some cases spanning more than a decade. In some cases, we initially found inconsistencies and expanded our literature search to include additional published sources to resolve these inconsistencies. We didn't take into account the fact that women make up 51% of the U.S. UU.

For example, if a source cited a prevalence of 60% for men and 40% for women, we treat it the same as if the source had said that 60% of those affected were men. As a countermeasure to an inaccurate assessment of gender prevalence, we required that at least 60% of those affected be of a particular gender in order for that disease to be labeled as gender dominant. For a disease to be considered overfunded or underfunded, we require that its actual funding differ from that proportional to its burden by at least 3% (this affected only one disease in each of the analyses). The approach of evaluating proposals based on scientific merit and expecting that the resulting portfolio will somehow reflect the burden of disease can only be brought to fruition by chance.

One idea is for the NIH to use RCDC and burden data to conduct a fund-versus-burden analysis to identify deficits and excesses and assess the reason for these discrepancies. This information could be used to guide the funding process for the coming years. The same can be said when it comes to addressing gender disparity in funding. An important first step is for the NIH to recognize that there is a problem before they can try to improve it.

NIH could invoke a methodology of its choice (such as that found in this document) to analyze correlations between funding and affected gender. The NIH could then set aside funds for diseases with insufficient funds that primarily affect women. Another approach, although more complicated, would be to award bonus points to proposals in designated areas to reduce gender disparity. Women Need More Health Care, But They're Also More Likely to Be Poor.

Health Care Costs Threaten Your Health and Economic Security. Women are more likely than men to need medical care throughout their lives. Are more likely to suffer from chronic diseases that require ongoing medical treatment. Are more likely, on average, to use prescription drugs.

Certain mental health problems, such as depression, affect twice as many women as men. Throughout their reproductive years, regardless of whether they have children, women need substantially more contact with medical providers than men their age. A study that compared women who terminated a pregnancy with those who wanted to have an abortion but were unable to do so, found that women who were denied an abortion were more likely to be in poverty, less likely to be employed in a full-time job, and more likely to receive public assistance for the next four years. For example, it cut cost-sharing reduction payments to insurers, which are so vital to helping low-income women pay for health insurance.

This includes more than 33 million women of color, who have historically been more likely to be uninsured, poor, and left without health care because of the cost. Comer Sees the WHAM Report as an Opportunity to Change the Conversation on Women's Health Research. Alzheimer's disease is by no means the only area where increased research funding could improve health outcomes, and WHAM plans to publish additional studies in the fall on the impact of research funding for autoimmune and cardiovascular diseases on the results of health. Congress passed a law requiring clinical research funded by the National Institutes of Health (NIH) to include women.

Cost as a barrier can be particularly damaging to certain groups of women, such as black women, who are more likely than white women to receive a diagnosis of chronic diseases such as diabetes and hypertension. The ACA reforms the private insurance industry, helps people pay for health coverage and expands Medicaid eligibility, all of which are vitally important for women struggling to make ends meet. Although data suggest that women submitting grant applications (ROs) for NIH research projects for the first time have the same grant success rate as men4, they are half as likely to apply for such grants5, despite the fact that there are as many women as men who receive advanced degrees. Equally important will be the inclusion of diversity and the expansion of the research agenda to include critical social science issues, health disparities and the social determinants of health.

A woman's health is known to have an impact on her family, including the younger and older generations, so strategies to address women's health are essential. By providing non-employment health coverage, the ACA allows women to seek positions that can offer higher wages or better opportunities. As an example, a recent article describing a research strategy for women's health with 17 authors included only 4 (24%) women. Preventing those patients from going to Planned Parenthood health centers would leave many with nowhere else to go for critical preventive care, because other providers can't fill the gap.

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Derrick Bekhit
Derrick Bekhit

Typical tvaholic. Freelance internet maven. Hipster-friendly pop culture fanatic. Professional foodaholic. Avid troublemaker.