Are Women’s Health
Concerns Prioritized at the
NIH and the FDA?
Nicole C. Quon, Ph.D.
Assistant Professor
Indiana University
Scientific Agencies

Scientific agencies use scientists and
scientific evidence to make science policy

Likely to seek bureaucratic autonomy

May respond to external pressure under
certain conditions
Women’s Health Movement

Relied on frames of gender inequity

Concerns about medical research
– Increasing attention to women’s health
– Participation of women in clinical trials
– Research funding for women’s health issues,
especially breast cancer
Mobilizing Resources

Scientific agencies may consider the
demands of resource-rich groups
Mean
Range
General women’s health groups
7.5
2 – 14
Disease-specific women’s health groups
1.1
0–9
Other disease-specific groups
5.0
0 – 56
401.8
0 – 743
National Women’s Health Network budget ($1000)
Raising Awareness
Scientific agencies may respond to signals
of issue importance
 Political/social influence vs. scientific
influence

Mean
Range
Congressional oversight index (alpha=0.62)
17.8
0 – 42
Media coverage index (alpha=0.91)
21.4
0-277
Scientific journal articles
331.1
0 – 3467
Reducing Monitoring Costs

Administrative procedures
– Introduce decision makers who share the
same values
Mean
Range
Women in senior NIH positions
3.6
0–9
Women in NIH study sections (% change)
0.8
-1.8 – 5.2
Gender Politics

Issues related to gender may become
more salient under certain conditions
Mean
Range
Women in Congressional committees (%)
6.5
1.0 – 16.7
Positive gender gap in Presidential election (%)
1.7
0 – 11
Negative gender gap in Presidential election (%)
-4.9
-10 – 0
Partisanship in Congress
1.1
0.9 – 1.4
Disease Burden
Agency missions reflect public health
goals
 Rate for women or men could influence
priority setting

Mean
Range
1427.8
1153 – 1960
Overall death rate for men
94.5
85 – 109
Prevalence rate for women
982.0
0 – 7660
3.0
0 – 42
Hospital admission rate for women
Disease-specific death rate for men
NIH Dependent Measures

Related to decisions in the NIH grants program
– Grants for “women or female” studies
 Extramural program (n=556)
 Intramural program (n=418)
– Grants for studies on 23 diseases on the women’s
health agenda
 Extramural program (n=749)
 Intramural program (n=660)

Collected from the CRISP database of funded
grants from 1972 to 2004

Keyword searches of grant titles and abstracts
NIH Independent Variables
Mobilization of resources
 Raising awareness
 Reducing monitoring costs
 Gender politics
 Disease burden
 Other variables

– Female medical school faculty, year trend,
presidential dummies
NIH Model Specification

Count data
– Data was overdispersed
– Data was a panel design
 32 years
 23 institutes or 23 diseases

Random effects negative binomial models

Offset to account for varying institute sizes

Lagged independent variables
NIH Extramural Priorities Models
Studies on
Women or Females
Coeff.
S.E.
Studies on
23 Disease Priorities
Coeff.
S.E.
Mobilizing Resources
General women’s health groups
-0.0013
0.0108
-0.0811 *
0.0470
Disease-specific women’s health groups
--
-0.1457 ***
0.0213
Other disease-specific groups
--
0.0471 ***
0.0041
National Women’s Health Network budget
0.0003
0.0003
0.0017
0.0018
-0.0003
0.0003
Raising Awareness
Congressional oversight
On women’s health
On specific disease
0.0075 ***
0.0018
0.0132 **
0.0060
Media coverage
-0.0003
0.0003
0.0040 ***
0.0008
Scientific journal articles
-0.0002
0.0002
-0.0003 ***
0.0001
* p<0.10, ** p<0.05, *** p<0.01
NIH Extramural Priorities Models
Studies on
Women or Females
Studies on
23 Disease Priorities
Coeff.
S.E.
Coeff.
S.E.
Reducing Monitoring Costs
Women in senior NIH positions
0.0319 *
0.0168
0.0270
0.0174
Women in NIH study sections
0.0063
0.0172
-0.0163
0.0117
Women in Congressional committees
0.0215
0.0224
0.0389 **
0.0189
Positive gender gap in Presidential election
0.0252 *
0.0150
0.0325 ***
0.0096
Negative gender gap in Presidential election
0.0020
0.0150
-0.0449
0.2535
Political Salience
Partisanship in Congress
* p<0.10, ** p<0.05, *** p<0.01
-0.0159 *
0.2102
0.0093
0.1823
NIH Extramural Priorities Models
Studies on
Women or Females
Studies on
23 Disease Priorities
Coeff.
S.E.
Coeff.
-0.0001
0.0001
Hospital admission rate for men
0.0003
0.0002
Overall death rate for women
0.0185
0.0246
-0.0501
0.0358
S.E.
Disease Burden
Hospital admission rate for women
Overall death rate for men
Prevalence rate for women
0.0001 ***
0.0000
Prevalence rate for men
-0.0001
0.0001
Disease-specific death rate for women
-0.1570 ***
0.0151
0.1497 ***
0.0126
Disease-specific death rate for men
* p<0.10, ** p<0.05, *** p<0.01
NIH Intramural Priorities Models

Fewer influences seem to matter compared to
extramural program decisions

Studies on women or females
– Gender politics: negative gender gap

Studies on 23 disease priorities
– Mobilizing resources: other disease-specific groups
– Raising awareness: congressional oversight on
specific diseases
– Disease burden: death rate for men
FDA Dependent Measures

Related to decisions for new drug approval
– Assignment of “priority” review
– Speed of new drug review in months

Approval dates from 1970 to 2004

Focused on drugs approved for diseases
on the women’s health agenda (n=131)
FDA Independent Measures

Mobilizing of resources
– Interest groups

Raising awareness
– Congressional oversight, media coverage,
scientific articles
Disease burden
 Other variables

– FDA workload, previous firm success, PDUFA
FDA Model Specification

Logistic regression to examine assignment
of priority review

Proportional hazards regression to
examine the speed of drug review
FDA Priorities Models
Priority Review
Coeff.
S.E.
Drug Review Times
Coeff.
S.E.
Mobilizing Resources
Disease-specific women’s health groups
0.1963
0.2049
-0.0817
0.0734
Other disease-specific groups
0.0191
0.0928
0.0259
0.0178
-0.7353
0.6461
0.0213
0.0906
Media coverage
0.0969
0.5312
-0.0325
0.1793
Scientific journal articles
0.1076
0.0657
Raising Awareness
Congressional oversight on specific diseases
* p<0.10, ** p<0.05, *** p<0.01
0.0229 *** 0.0081
FDA Priorities Models
Priority Review
Drug Review Times
Coeff.
S.E.
Coeff.
S.E.
Prevalence rate for women
-0.0007
0.0010
0.0002
0.0003
Prevalence rate for men
-0.0039
0.0037
0.0000
0.0002
Disease-specific death rate for women
-0.5468
1.2130
0.1310
0.1259
Disease-specific death rate for men
-2.4601 *
1.4444
-0.1057
0.1128
Disease Burden
Priority rating
--
--
1.4061 ***
0.3556
-0.0270
2.0056
-0.5728
0.6231
0.2718
0.7708
0.3145
0.3401
-0.0208
0.1190
0.0871
0.0456
Other Variables
FDA workload
Previous firm success
PDUFA trend
* p<0.10, ** p<0.05, *** p<0.01
Summary of Main Results
The FDA was responsive to the women’s
health movement
 But not in priority setting for new drug
approval
 Female leadership (scientific and political)
are associated with increased priority
setting at the NIH
 Congressional oversight and some signals
from health advocates are also important

Study Limitations
NIH dependent measures collected using
keywords
 Data on grant applications unavailable
 Women’s health advocacy measure is
crude
 Few drugs for diseases on the women’s
health agenda

Policy Implications

Scientific agencies are not insulated from
gender politics

Influence depends on the type of decision and
agency culture

Some pathways of influence seem more
effective
– Collaborations between interest groups and Congress
– Increasing the role of women leaders
Pathways of External Influence

“External signals” theory
– Josckow, Olson
– Mobilizing resources
– Raising awareness

“Political control” theory
– Weingast and Moran, McNollGast, McCubbins and
Schwartz
– Reducing monitoring costs

Political salience
Agency Mandates and Culture

Research scientific agencies
– NIH intramural grants program

Distributive scientific agencies
– NIH extramural grants program

Regulatory scientific agencies
– FDA Center for Drug Evaluation and Research
NIH Independent Variable Lags

Agencies respond to most recently
available information

1 year lag: Congressional oversight,
media, and scientific journal coverage

2 year lag: interest groups

3 year lag: disease burden
Percent of Total NIH Grants
Grants for Women's Health
Agenda Diseases
Year
Studies on Women or Females (%)
1972-1974
1%
1-5 %
5-10 %
>10%
Studies on Women or Females (%)
1972-1974
1982-1984
1%
1-5 %
1992-1994
2002-2004
5-10 %
>10%
NIH Results Summary

Priority setting in the NIH extramural and
intramural programs for women’s health is
not insulated from politics

All four pathways of external influence
seem to matter

Extramural decisions are associated with
more external influences
Priority Review of New Drugs
40%
30%
34%
30%
20%
10%
0%
All drugs (n=653)
Women's health drugs (n=131)
Mean Drug Review Times
(in months)
30
23.6
24.2
20
10
0
All drugs (n=653)
Women's health drugs (n=131)
FDA Independent Measures I
Mean
Range
Disease-specific women’s health groups
1.4
0 – 10
Other disease-specific groups
7.6
0 – 46
2.1
0 – 16
Media coverage index
136.88
0 – 923
Scientific journal articles
3004.4
0 – 12097
Mobilizing Resources
Raising Awareness
Congressional oversight index
FDA Independent Measures II
Mean
Range
Prevalence rate for women
606.6
0 – 4498
Prevalence rate for men
403.1
0 – 5590
Death rate for women
4.4
0 – 30
Death rate for men
5.5
0 – 40
1.1
0.7-1.8
Disease burden per 10,000 population
Other Variables
FDA workload
% of firms with previous success
73%
Directions for Future Research

Examine impact of women’s and women’s
health movement on other scientific
agencies

Study whether other disease groups that
do not have historical gender inequities
have influenced scientific agencies
decisions