Age Trends in CIHR's Research Community
What the Data Say – July 2026
Questions about age and career stage have become increasingly prominent across the research ecosystem. In Canada, Statistics Canada has reported that the proportion of full-time university teaching staff aged 65 and older has risen gradually since 2000-01Footnote 1. Similar patterns have been noted in the United Kingdom, where older age groups make up a sizeable share of academic staff, and in the United States, where the National Institutes of Health (NIH) has tracked long-term age trends among investigators receiving their first major awardsFootnote 2Footnote 3Footnote 4. Against that broader backdrop, we looked at age trends in the CIHR research community through the lens of grant and award applications submitted between 2005 and 2024.
Rather than pointing to a single story, the results show that age trends vary depending on what part of the CIHR funding system is being examined. The overall applicant pool has shifted over time, but those shifts do not look the same across grants and awards, across research areas, or across major programs. Furthermore, looking separately at first-time applications adds an important dimension to the data.
We took the following approach:
- Application age reflects the age of the nominated principal applicant (NPA) at the time the application was submitted from 2005 to 2024
- First-time applications were identified as the first instance in which each NPA submitted a grant application and the first instance in which each NPA submitted an awards application to CIHR. These were treated as distinct instances.
- Common CV person sex was used for sex breakdowns of age trends. Subgroup counts with less than 10 individuals were suppressed as per privacy requirements. NPAs with no CCV sex values were excluded from this analysis (approximately 3% of all historical applications during this period).
- Data Limitations: CIHR does not have unfunded application data for programs that are allocation-based and/or managed by other organizations. Some examples include the Canadian Graduate Scholarships - Master's awards (CGS-M) and the Canada Research Chairs program.
Age Distributions: Then and Now
Figure 1: Distribution of Applicant Age Over Time
Figure 1 – Long Description
| Competition Year | NPA Sex | Application Count | Average Age | Median Age | Q1 Age | Q3 Age | Min. Age | Max. Age |
|---|---|---|---|---|---|---|---|---|
| 2005 | Male | 4,796 | 43.3 | 43 | 35 | 51 | 20 | 80 |
| 2005 | Female | 2,978 | 37.7 | 36 | 28 | 46 | 19 | 71 |
| 2010 | Male | 5,961 | 43.1 | 43 | 34 | 52 | 20 | 84 |
| 2010 | Female | 5,008 | 37.2 | 35 | 28 | 45 | 20 | 70 |
| 2015 | Male | 4,738 | 43.1 | 42 | 33 | 52 | 19 | 81 |
| 2015 | Female | 4,295 | 37.5 | 35 | 28 | 46 | 19 | 78 |
| 2020 | Male | 5,535 | 45.7 | 45 | 37 | 55 | 19 | 90 |
| 2020 | Female | 4,888 | 39.5 | 38 | 29 | 48 | 20 | 78 |
| 2024 | Male | 4,504 | 46.5 | 47 | 38 | 55 | 19 | 86 |
| 2024 | Female | 4,791 | 40.6 | 41 | 30 | 49 | 20 | 85 |
Figure 1 and the table found within its Long Description show the distribution of NPA age on CIHR applications submitted in selected competition years between 2005 and 2024, disaggregated by NPA sex. The split violin plot shows the age distribution within each competition year, with violin width scaled by the number of applications in each group. This scaling provides context for the relative size of each group, but the main pattern of interest is the upward shift in age over time.
Between 2005 and 2015, average age trends did not change much for both NPA sexes. However, in the last decade, average age has increased from 43.1 to 46.5 among male NPAs and from 37.7 to 40.6 among female NPAs. Median age also increased, from 42 to 47 among male NPAs and from 35 to 41 among female NPAs. The boxplots show that this shift was not limited to averages: the central portion of the distribution also moved upward, with Q1 and Q3 increasing for both groups over the period.
Note: NPA with ages below 18 and above 90 years old on applications were excluded from this analysis as the majority of these were due to date of birth input errors.
Application Age Over Time
Figure 2: Application NPA Age Trends
Figure 2 – Long Description
| Program | Pillar | Sex | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Awards | All | Female | 29.9±0.17 (1,360) |
30.3±0.18 (1,400) |
30.3±0.19 (1,343) |
30±0.17 (1,440) |
29.7±0.16 (1,748) |
29.6±0.13 (2,383) |
30.3±0.14 (2,395) |
30.1±0.13 (2,522) |
30±0.12 (3,067) |
29.9±0.13 (2,440) |
29.9±0.14 (2,314) |
29.8±0.15 (2,158) |
29.5±0.14 (2,203) |
29.3±0.13 (2,329) |
29.4±0.14 (1,989) |
29±0.13 (2,065) |
28.7±0.15 (1,920) |
28.2±0.14 (1,881) |
29.6±0.16 (2,061) |
28.7±0.15 (1,730) |
| Awards | All | Male | 31.6±0.19 (1,102) |
31.1±0.18 (1,070) |
31.3±0.19 (1,067) |
31±0.18 (1,049) |
30.3±0.17 (1,207) |
30.5±0.15 (1,570) |
30.5±0.14 (1,593) |
30.3±0.14 (1,707) |
30.2±0.13 (2,082) |
30.1±0.15 (1,492) |
30.1±0.16 (1,506) |
29.4±0.15 (1,372) |
29.9±0.17 (1,382) |
29.4±0.15 (1,443) |
29.8±0.18 (1,193) |
29.8±0.16 (1,221) |
29.5±0.19 (1,017) |
29.2±0.18 (948) |
30±0.21 (945) |
29.4±0.19 (862) |
| Awards | Biomedical | Female | 28.6±0.17 (770) |
28.8±0.19 (742) |
29±0.2 (675) |
28.7±0.19 (705) |
28.7±0.19 (823) |
28.5±0.16 (1,068) |
29.1±0.17 (1,009) |
28.9±0.15 (1,031) |
28.7±0.14 (1,257) |
28.4±0.15 (986) |
28.4±0.17 (905) |
28.1±0.18 (854) |
28.1±0.18 (870) |
27.8±0.18 (925) |
27.6±0.19 (756) |
27.8±0.18 (846) |
26.9±0.2 (803) |
26.6±0.17 (797) |
28.1±0.21 (800) |
27.6±0.2 (715) |
| Awards | Biomedical | Male | 31±0.2 (852) |
30.5±0.2 (796) |
30.5±0.21 (762) |
30.3±0.19 (748) |
29.8±0.19 (867) |
29.9±0.17 (1,099) |
30±0.16 (1,115) |
29.5±0.15 (1,150) |
29.5±0.14 (1,403) |
29.2±0.17 (958) |
29.4±0.18 (980) |
28.6±0.17 (850) |
28.9±0.18 (848) |
28.9±0.18 (904) |
28.8±0.21 (732) |
29.3±0.19 (762) |
28.5±0.21 (648) |
28.9±0.22 (591) |
28.8±0.24 (565) |
28.7±0.22 (527) |
| Awards | Clinical | Female | 30.1±0.4 (256) |
30.3±0.36 (293) |
30±0.39 (294) |
29.7±0.33 (342) |
29.7±0.33 (434) |
29.1±0.24 (641) |
29.7±0.25 (630) |
29.1±0.24 (678) |
29.4±0.24 (791) |
29.3±0.25 (648) |
29.1±0.25 (602) |
29.1±0.26 (595) |
28.8±0.26 (593) |
29±0.24 (634) |
28.6±0.24 (513) |
28.9±0.24 (553) |
28±0.26 (464) |
27.8±0.26 (480) |
28.4±0.27 (503) |
27.8±0.28 (442) |
| Awards | Clinical | Male | 32.7±0.56 (123) |
31.9±0.48 (158) |
33.1±0.52 (170) |
31.6±0.55 (151) |
30.6±0.4 (194) |
30.8±0.4 (252) |
30.9±0.35 (254) |
30.6±0.33 (280) |
30.8±0.34 (321) |
30.1±0.36 (276) |
30.1±0.39 (264) |
29.6±0.36 (256) |
30.1±0.4 (258) |
29.1±0.33 (266) |
29.8±0.38 (221) |
29±0.32 (254) |
28.9±0.42 (177) |
28.3±0.41 (200) |
29.7±0.45 (168) |
29.1±0.41 (178) |
| Awards | Health systems/ services |
Female | 33.2±0.65 (142) |
34.5±0.73 (127) |
34.2±0.74 (149) |
33.5±0.68 (170) |
32.6±0.58 (200) |
33±0.51 (250) |
34.2±0.54 (286) |
33±0.46 (321) |
33.1±0.42 (401) |
32.4±0.44 (302) |
32.5±0.4 (313) |
33.4±0.49 (298) |
32.2±0.39 (353) |
31.7±0.37 (363) |
32.5±0.4 (365) |
31.2±0.39 (300) |
31.3±0.4 (302) |
30.9±0.42 (306) |
32.3±0.38 (413) |
31.3±0.44 (278) |
| Awards | Health systems/ services |
Male | 34.7±1.1 (52) |
33.6±0.88 (49) |
34±0.89 (49) |
36.3±0.89 (77) |
32.9±0.99 (62) |
32.5±0.7 (85) |
32.3±0.7 (102) |
34±0.75 (125) |
32.4±0.58 (148) |
32.8±0.66 (102) |
33.1±0.62 (117) |
32.7±0.68 (132) |
33.5±0.77 (146) |
31.6±0.57 (152) |
32.5±0.7 (130) |
32.5±0.74 (107) |
33.8±0.74 (102) |
31.4±0.64 (80) |
33.5±0.68 (98) |
32±0.68 (79) |
| Awards | Social/ Cultural/ Environmental/ Population Health |
Female | 32.8±0.6 (192) |
32.9±0.54 (238) |
32.3±0.54 (225) |
31.6±0.49 (223) |
30.7±0.43 (291) |
31.2±0.36 (424) |
31.3±0.33 (470) |
32.3±0.36 (492) |
31.1±0.3 (618) |
31.9±0.33 (504) |
31.8±0.36 (494) |
31.7±0.35 (411) |
31.2±0.38 (387) |
30.9±0.36 (407) |
31.2±0.36 (355) |
30.2±0.34 (366) |
31.4±0.41 (351) |
30.5±0.43 (298) |
31.9±0.45 (345) |
30.4±0.43 (295) |
| Awards | Social/ Cultural/ Environmental/ Population Health |
Male | 34.4±0.99 (75) |
34.6±1.09 (67) |
34.1±0.87 (86) |
31.4±0.67 (73) |
32.9±0.79 (84) |
33.2±0.65 (134) |
32.1±0.59 (122) |
32.9±0.6 (152) |
32.6±0.54 (210) |
33.4±0.58 (156) |
32.5±0.6 (145) |
31.3±0.53 (134) |
32.6±0.68 (130) |
31.6±0.58 (121) |
33.3±0.68 (110) |
32.3±0.67 (98) |
32.6±0.8 (90) |
31.4±0.74 (77) |
33.2±0.74 (114) |
32.3±0.86 (78) |
| Grants | All | Female | 45.2±0.22 (1,365) |
44.9±0.22 (1,374) |
45.7±0.23 (1,253) |
45.8±0.23 (1,291) |
46.4±0.22 (1,510) |
46.2±0.2 (1,705) |
46.4±0.2 (1,956) |
47±0.18 (2,295) |
47.1±0.18 (2,321) |
46.9±0.21 (1,856) |
47.7±0.21 (1,705) |
47.4±0.16 (2,727) |
47.5±0.2 (1,829) |
47.6±0.18 (2,223) |
47.4±0.18 (2,281) |
47.7±0.18 (2,619) |
47.8±0.19 (2,015) |
47.4±0.2 (1,959) |
47.7±0.2 (2,116) |
47.7±0.17 (2,754) |
| Grants | All | Male | 47.2±0.15 (3,185) |
47.3±0.16 (3,274) |
47.4±0.16 (2,826) |
47.9±0.16 (2,964) |
48.2±0.15 (3,425) |
48.4±0.15 (3,603) |
48.9±0.15 (3,645) |
48.8±0.15 (3,848) |
49±0.15 (3,860) |
48.5±0.17 (3,132) |
49.5±0.17 (2,962) |
49.3±0.13 (5,273) |
49.6±0.17 (3,133) |
49.9±0.16 (3,814) |
49.9±0.17 (3,440) |
50.4±0.15 (4,158) |
50.6±0.18 (3,110) |
51.2±0.2 (2,724) |
50.9±0.19 (2,962) |
50.8±0.17 (3,468) |
| Grants | Biomedical | Female | 44.1±0.33 (576) |
44.5±0.31 (669) |
45.1±0.32 (582) |
45.5±0.33 (575) |
46.3±0.32 (620) |
46.9±0.31 (686) |
46.9±0.32 (684) |
47.3±0.29 (780) |
47.5±0.29 (752) |
47±0.34 (600) |
48.3±0.33 (630) |
48.1±0.25 (1,102) |
48.6±0.34 (655) |
49±0.29 (852) |
48.7±0.31 (769) |
48.2±0.32 (785) |
48.9±0.34 (702) |
49.2±0.36 (626) |
49.4±0.34 (717) |
49.9±0.31 (869) |
| Grants | Biomedical | Male | 47.2±0.18 (2,239) |
47.3±0.18 (2,398) |
47.5±0.19 (2,048) |
47.9±0.19 (2,133) |
48.6±0.18 (2,392) |
48.9±0.18 (2,495) |
49.3±0.18 (2,339) |
49.3±0.18 (2,457) |
49.4±0.18 (2,446) |
49.2±0.21 (1,989) |
50.1±0.21 (1,994) |
49.8±0.15 (3,779) |
50.3±0.21 (2,104) |
50.6±0.19 (2,586) |
51±0.22 (2,157) |
51.3±0.2 (2,396) |
51.8±0.22 (1,938) |
52.7±0.25 (1,675) |
52.4±0.24 (1,855) |
52.2±0.21 (2,181) |
| Grants | Clinical | Female | 44.6±0.54 (214) |
43.1±0.55 (211) |
44.1±0.53 (216) |
44.7±0.54 (220) |
45.5±0.49 (295) |
44.7±0.44 (370) |
44.9±0.38 (441) |
45.8±0.38 (473) |
46.2±0.4 (474) |
46±0.43 (392) |
47±0.45 (386) |
46.1±0.33 (648) |
45.7±0.4 (423) |
45.9±0.32 (545) |
46.3±0.33 (567) |
46.8±0.35 (609) |
46.5±0.38 (468) |
46.4±0.38 (486) |
46.5±0.37 (494) |
46.7±0.33 (628) |
| Grants | Clinical | Male | 47.1±0.43 (409) |
47±0.45 (431) |
46.7±0.45 (372) |
47.4±0.44 (393) |
47.2±0.43 (476) |
47.5±0.41 (538) |
48±0.38 (574) |
47.5±0.37 (637) |
47.9±0.35 (705) |
46.9±0.38 (558) |
48.2±0.41 (467) |
48.5±0.34 (807) |
48.5±0.42 (527) |
48.6±0.38 (670) |
48.2±0.35 (693) |
49.4±0.34 (824) |
48.7±0.38 (631) |
49.4±0.38 (583) |
49.3±0.39 (565) |
48.7±0.37 (675) |
| Grants | Health systems/ services |
Female | 45.7±0.62 (187) |
46.8±0.62 (185) |
46.9±0.54 (211) |
46.5±0.53 (232) |
47±0.57 (257) |
46.6±0.47 (276) |
47.2±0.47 (381) |
47.9±0.37 (555) |
47.4±0.39 (538) |
47±0.44 (417) |
47.4±0.46 (356) |
47.1±0.4 (477) |
47.5±0.5 (324) |
46.7±0.46 (385) |
46.4±0.42 (466) |
47.6±0.38 (574) |
47±0.45 (395) |
46.2±0.42 (429) |
47.9±0.45 (429) |
46.4±0.38 (568) |
| Grants | Health systems/ services |
Male | 46.5±0.58 (211) |
47.6±0.61 (193) |
46.8±0.61 (178) |
46.9±0.64 (198) |
46.9±0.54 (266) |
47.6±0.56 (262) |
48.8±0.52 (292) |
47.8±0.49 (368) |
48.7±0.5 (374) |
47.9±0.57 (274) |
47.9±0.59 (238) |
47.1±0.54 (304) |
47.6±0.65 (216) |
47.2±0.57 (227) |
48±0.54 (281) |
49.6±0.5 (436) |
47.8±0.62 (260) |
48.4±0.67 (235) |
47.4±0.6 (249) |
47.6±0.57 (258) |
| Grants | Social/ Cultural/ Environmental/ Population Health |
Female | 46.8±0.42 (388) |
46.1±0.49 (309) |
47.4±0.55 (244) |
46.9±0.58 (264) |
46.7±0.49 (338) |
46.2±0.44 (373) |
46.4±0.44 (450) |
46.9±0.43 (487) |
46.8±0.41 (557) |
47.3±0.46 (447) |
47.8±0.5 (333) |
47.7±0.43 (500) |
47.8±0.44 (427) |
47.6±0.43 (441) |
47.4±0.41 (479) |
48.1±0.36 (651) |
48±0.4 (450) |
47.4±0.46 (418) |
46.5±0.4 (476) |
47.1±0.34 (689) |
| Grants | Social/ Cultural/ Environmental/ Population Health |
Male | 47.9±0.49 (326) |
47.6±0.61 (252) |
48.2±0.65 (228) |
49.7±0.67 (240) |
48±0.58 (291) |
47.2±0.54 (308) |
48.3±0.48 (440) |
48.6±0.52 (386) |
48.5±0.57 (335) |
47.7±0.55 (311) |
48.6±0.59 (263) |
48.5±0.52 (383) |
48.1±0.61 (286) |
48.6±0.57 (331) |
48±0.6 (309) |
48.5±0.46 (502) |
49.3±0.67 (281) |
47.6±0.69 (231) |
47.6±0.6 (293) |
48.5±0.55 (354) |
Figure 2 traces average application age from 2005 to 2024 and shows that grants and awards follow different trajectories. Average age on grant applications (2A) increased over the period, rising from 45 in 2005 to 48 in 2024 for female NPAs, and 47 to 51 for male NPAs. Over the same period, average age on award applications (2B) moved in the opposite direction, declining from 30 to 29 for female NPAs and 32 to 29 for male NPAs.
Within grants, the increase over time was driven largely by changes in the biomedical and clinical research areas. Average age increased from 44 to 50 for female NPAs and 47 to 52 for male NPAs on biomedical grant applications. On clinical grant applications, the average age rose from 45 to 47 for females and 47 to 49 for males. By contrast, the age profile for awards has shifted downward across all research pillars. This widening gap between grants and awards is most pronounced in biomedical research, where the difference in applicant age grew from roughly 16 years in 2005 to 23 years in 2024.
Age Trends in Major CIHR Programs
Figure 3: Application NPA Age on Major Programs
Figure 3 – Long Description
| Program | Sex | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Project/OOGP | Female | 44.5±0.27 (872) |
44.8±0.25 (983) |
45.2±0.25 (989) |
45.1±0.27 (941) |
45.9±0.26 (999) |
45.9±0.23 (1,248) |
46.3±0.23 (1,320) |
46.8±0.22 (1,359) |
47.2±0.22 (1,451) |
47.8±0.29 (889) |
48.2±0.29 (840) |
47.4±0.19 (1,983) |
47.4±0.26 (1,029) |
47.7±0.21 (1,626) |
47.8±0.22 (1,512) |
47.5±0.23 (1,468) |
48±0.23 (1,446) |
47.8±0.24 (1,371) |
48.3±0.23 (1,430) |
48.6±0.21 (1,761) |
| Project/OOGP | Male | 46.9±0.18 (2,257) |
47.3±0.18 (2,487) |
47.1±0.18 (2,313) |
47.5±0.18 (2,372) |
48.3±0.18 (2,671) |
48.4±0.17 (2,935) |
48.7±0.17 (2,871) |
48.6±0.17 (2,882) |
49±0.17 (2,963) |
49.5±0.21 (1,759) |
49.5±0.22 (1,634) |
49.2±0.14 (4,208) |
49.5±0.21 (2,110) |
50±0.17 (3,074) |
50.3±0.19 (2,742) |
50.1±0.19 (2,653) |
50.5±0.19 (2,606) |
51.5±0.21 (2,297) |
51.3±0.2 (2,483) |
51.3±0.19 (2,818) |
| Catalyst Grants | Female | 46.7±1.18 (41) |
44.4±1.13 (53) |
45.9±1.02 (50) |
46.2±0.91 (93) |
45.9±0.61 (218) |
46.5±0.7 (162) |
45.7±0.93 (64) |
47.5±1 (69) |
46.3±1.11 (63) |
44.8±1.46 (46) |
47.2±1.19 (58) |
47.4±0.75 (129) |
48.8±0.56 (264) |
46.8±0.78 (117) |
46.8±0.65 (153) |
48.4±1.31 (47) |
46.8±1.07 (80) |
45.1±0.66 (154) |
45.9±0.74 (161) |
46.4±0.58 (239) |
| Catalyst Grants | Male | 44.6±1.13 (38) |
45.4±1.32 (43) |
44.2±1.06 (59) |
45.5±0.76 (153) |
46.1±0.53 (273) |
45±0.6 (201) |
46.7±0.9 (98) |
49.5±0.98 (92) |
46.8±1.09 (85) |
44.5±1.64 (25) |
49.4±1.11 (79) |
47.2±1.05 (104) |
48.1±0.54 (342) |
47.8±0.9 (126) |
46.1±0.88 (112) |
47.6±1.15 (64) |
47.1±1.53 (48) |
47±1.14 (79) |
46.5±0.9 (110) |
47.6±0.71 (179) |
| Operating Grants | Female | 47±1.17 (47) |
45.8±1.02 (76) |
47.5±0.91 (73) |
46.3±0.86 (89) |
49±0.87 (106) |
45±0.81 (116) |
46.1±0.6 (218) |
42.1±0.87 (86) |
47.3±0.85 (95) |
47.6±0.79 (122) |
47.1±0.69 (152) |
47.1±0.68 (177) |
46.4±0.66 (189) |
46.1±0.6 (215) |
45.4±0.66 (178) |
48.3±0.3 (896) |
47±0.47 (364) |
45.7±0.75 (148) |
45.3±0.63 (185) |
44.8±0.58 (249) |
| Operating Grants | Male | 48.3±1.21 (53) |
49.3±0.92 (101) |
48.4±0.94 (91) |
48.1±1.05 (81) |
46.5±0.94 (104) |
45.7±0.79 (136) |
48.4±0.64 (216) |
46.4±0.92 (108) |
50.9±0.98 (104) |
49.6±0.78 (131) |
49.9±0.75 (136) |
49.5±0.7 (220) |
47.7±0.63 (191) |
48.7±0.74 (182) |
47.6±0.88 (121) |
51.6±0.31 (1,189) |
50.4±0.52 (387) |
50.2±0.78 (160) |
50.8±0.85 (151) |
46.4±0.79 (124) |
| Postdoctoral | Female | 32.4±0.24 (474) |
32.4±0.24 (489) |
33±0.25 (434) |
32.6±0.23 (460) |
33.3±0.24 (500) |
32.7±0.17 (796) |
32.8±0.19 (723) |
32.5±0.17 (749) |
32.6±0.15 (1,030) |
32.2±0.17 (747) |
32.2±0.17 (656) |
32.8±0.2 (619) |
32.3±0.18 (663) |
32.8±0.2 (629) |
32.7±0.19 (553) |
32.9±0.2 (690) |
32.8±0.22 (507) |
33±0.22 (444) |
33±0.22 (466) |
33.1±0.23 (489) |
| Postdoctoral | Male | 32.4±0.19 (482) |
31.7±0.18 (446) |
32±0.18 (439) |
32.4±0.17 (434) |
32.4±0.17 (468) |
32.4±0.14 (723) |
32.5±0.16 (679) |
32.2±0.15 (686) |
32.3±0.13 (899) |
31.9±0.17 (560) |
32.4±0.19 (529) |
32.3±0.17 (569) |
32.5±0.17 (547) |
32.5±0.18 (552) |
32.7±0.2 (486) |
32.7±0.18 (535) |
33.1±0.24 (388) |
33.1±0.21 (380) |
33.1±0.24 (365) |
32.8±0.22 (393) |
| Doctoral | Female | 27.2±0.23 (474) |
27.8±0.24 (499) |
27.7±0.23 (516) |
27.9±0.24 (573) |
27.8±0.2 (800) |
27.8±0.18 (1,022) |
28.1±0.18 (1,105) |
28.1±0.19 (920) |
28.2±0.2 (886) |
27.9±0.18 (904) |
27.8±0.19 (835) |
28.1±0.19 (876) |
27.7±0.17 (875) |
27.6±0.16 (847) |
27.5±0.19 (553) |
27.5±0.17 (678) |
27.6±0.2 (674) |
27.5±0.2 (681) |
27.5±0.21 (627) |
27.4±0.19 (654) |
| Doctoral | Male | 27.1±0.21 (286) |
27.5±0.25 (288) |
27.2±0.23 (302) |
27.2±0.25 (338) |
27.1±0.22 (427) |
27±0.21 (473) |
27.2±0.19 (595) |
27.1±0.2 (537) |
27.6±0.24 (517) |
27.2±0.22 (454) |
27.3±0.22 (467) |
27.2±0.21 (442) |
27.4±0.24 (469) |
27.1±0.2 (455) |
27.2±0.24 (285) |
27.4±0.23 (334) |
27.1±0.24 (335) |
27.2±0.22 (313) |
27.1±0.23 (255) |
27.5±0.27 (251) |
| Master's | Female | 25.8±0.27 (221) |
25.5±0.28 (229) |
25.2±0.25 (238) |
25.1±0.23 (250) |
25.3±0.22 (340) |
25±0.19 (418) |
25.5±0.27 (256) |
25.2±0.23 (311) |
24.8±0.2 (528) |
24.2±0.27 (250) |
24.2±0.26 (252) |
24±0.22 (245) |
23.8±0.24 (254) |
24.1±0.21 (359) |
23.8±0.19 (340) |
24±0.2 (364) |
23.8±0.15 (538) |
23.5±0.15 (522) |
23.7±0.19 (456) |
23.7±0.15 (419) |
| Master's | Male | 25.3±0.37 (91) |
24.9±0.28 (105) |
25.6±0.39 (110) |
25.2±0.38 (91) |
25.1±0.27 (136) |
24.5±0.22 (188) |
25±0.28 (107) |
24.9±0.28 (137) |
24.2±0.18 (285) |
23.8±0.28 (143) |
24.2±0.29 (139) |
23.8±0.25 (151) |
24±0.25 (142) |
23.6±0.22 (147) |
24.1±0.27 (182) |
24±0.26 (162) |
24.1±0.23 (212) |
24±0.27 (198) |
24±0.26 (177) |
23.6±0.23 (172) |
Figure 3 narrows the lens on applicant age trends to selected major programs. Among awards, average application age on the Canada Graduate Scholarships - Master's awards (CGS-M) declined from 26 to 24. While the doctoral equivalent (CGS-D) and CIHR's postdoctoral fellowship awards remained relatively stable at approximately 27 and 33, respectively.
Among grant programs, average age in the Open Operating Grant Program/Project Grant competitions trended upward from 45 to 49 for female NPAs and 47 to 51 for males. The average age on Catalyst and Operating grant applications ranged between 43 and 52 for both sexes across this period. Taken together, these program-level patterns point to a notable gap of more than a decade between the average age on postdoctoral fellowship applications and the average age observed on applications to major grant programs.
First-time Application Age Trends
Figure 4: First-time Application NPA Age Trends
Figure 4 – Long Description
| Program | Pillar | Sex | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Awards | All | Female | 30±0.17 (1,299) |
30.4±0.21 (1,028) |
30±0.22 (950) |
29.4±0.2 (970) |
29.3±0.19 (1,176) |
29.2±0.17 (1,425) |
29.6±0.2 (1,215) |
29.3±0.2 (1,188) |
28.6±0.17 (1,479) |
28.5±0.2 (1,042) |
28.3±0.21 (1,003) |
28.4±0.21 (1,022) |
28.1±0.19 (1,083) |
27.7±0.18 (1,136) |
27.9±0.21 (960) |
27.6±0.17 (1,111) |
27.1±0.18 (1,092) |
27.1±0.19 (1,102) |
28±0.21 (1,083) |
27.6±0.21 (920) |
| Awards | All | Male | 31.6±0.19 (1,047) |
31.2±0.22 (816) |
31±0.22 (782) |
30.2±0.22 (672) |
29.6±0.23 (717) |
29.9±0.2 (942) |
29.8±0.2 (816) |
29.5±0.21 (841) |
29±0.19 (1,020) |
28.5±0.21 (691) |
29.1±0.24 (718) |
28.5±0.22 (700) |
29.3±0.26 (694) |
28.4±0.22 (706) |
28.3±0.26 (583) |
28.5±0.22 (636) |
28.1±0.26 (525) |
28.4±0.26 (522) |
28.8±0.29 (498) |
28.4±0.27 (478) |
| Awards | Biomedical | Female | 28.6±0.17 (738) |
28.8±0.23 (526) |
28.8±0.25 (466) |
28.4±0.23 (486) |
28.2±0.23 (547) |
28.3±0.21 (642) |
28.6±0.24 (531) |
28.2±0.24 (496) |
27.3±0.19 (615) |
27.4±0.22 (461) |
27±0.25 (420) |
26.9±0.27 (430) |
26.8±0.23 (473) |
26.5±0.24 (464) |
26.7±0.26 (411) |
26.7±0.23 (474) |
25.9±0.22 (506) |
25.5±0.21 (475) |
26.7±0.27 (451) |
26.7±0.28 (386) |
| Awards | Biomedical | Male | 31.1±0.21 (812) |
30.6±0.23 (598) |
30.3±0.24 (556) |
29.7±0.24 (474) |
29.1±0.25 (520) |
29.2±0.21 (640) |
29.4±0.24 (551) |
28.8±0.23 (558) |
28.3±0.2 (696) |
27.9±0.23 (448) |
28.4±0.26 (471) |
27.9±0.25 (453) |
28.1±0.26 (428) |
27.7±0.26 (434) |
27.6±0.31 (385) |
28.2±0.27 (389) |
26.8±0.28 (320) |
28.2±0.32 (313) |
27.7±0.36 (292) |
27.6±0.32 (286) |
| Awards | Clinical | Female | 30.2±0.42 (244) |
30.2±0.42 (215) |
30±0.48 (215) |
29.3±0.43 (218) |
29.3±0.42 (283) |
28.6±0.32 (364) |
28.5±0.35 (298) |
28.2±0.36 (321) |
27.9±0.31 (381) |
28±0.38 (272) |
27±0.31 (261) |
27.6±0.36 (278) |
27.6±0.38 (274) |
27.4±0.34 (299) |
27.4±0.37 (248) |
27.5±0.32 (301) |
26.6±0.35 (253) |
26.8±0.35 (269) |
27.4±0.36 (276) |
26.8±0.37 (233) |
| Awards | Clinical | Male | 32.7±0.57 (117) |
31.6±0.57 (122) |
32.9±0.62 (130) |
31±0.67 (105) |
29.7±0.51 (107) |
30±0.53 (153) |
30.1±0.45 (134) |
29.5±0.49 (136) |
29.3±0.5 (157) |
28.2±0.54 (125) |
28.3±0.56 (124) |
28.4±0.52 (121) |
29±0.6 (125) |
27.7±0.46 (140) |
28±0.56 (96) |
27.6±0.37 (150) |
28.4±0.58 (107) |
27.7±0.6 (120) |
28.5±0.6 (91) |
28.2±0.52 (105) |
| Awards | Health systems/ services |
Female | 33.2±0.67 (135) |
34.7±0.88 (95) |
34.1±0.88 (109) |
31.8±0.75 (113) |
31.4±0.65 (141) |
32.1±0.71 (143) |
33.1±0.87 (132) |
32±0.71 (147) |
31.9±0.65 (192) |
31±0.71 (125) |
30.8±0.67 (116) |
32.2±0.76 (138) |
31.1±0.61 (161) |
29.4±0.52 (153) |
30.4±0.72 (141) |
28.8±0.48 (140) |
29±0.59 (144) |
29.3±0.58 (174) |
30.4±0.59 (185) |
29.6±0.66 (143) |
| Awards | Health systems/ services |
Male | 34.4±1.09 (51) |
33.5±1.03 (38) |
32.9±0.96 (37) |
32.4±0.81 (40) |
31.3±1.08 (37) |
31.7±0.82 (54) |
31.1±0.95 (58) |
33.4±1.17 (62) |
30.8±0.79 (65) |
31.2±0.86 (52) |
32.4±1.02 (56) |
31.7±1.06 (65) |
33.7±1.18 (75) |
31.2±0.91 (70) |
30.4±1.08 (51) |
30.8±1.01 (51) |
32.4±1.11 (49) |
30.4±0.97 (43) |
32.5±1 (55) |
30.7±0.89 (45) |
| Awards | Social/ Cultural/ Environmental/ Population Health |
Female | 32.8±0.6 (182) |
33.1±0.6 (192) |
30.9±0.57 (160) |
31.2±0.6 (153) |
30.5±0.53 (205) |
30.7±0.45 (276) |
31.2±0.49 (254) |
31.6±0.56 (224) |
30.2±0.47 (291) |
30.2±0.56 (184) |
31.3±0.64 (206) |
30.6±0.57 (176) |
29.4±0.56 (175) |
29.4±0.47 (220) |
29.4±0.54 (160) |
28.8±0.45 (196) |
29.4±0.52 (189) |
29.8±0.59 (184) |
30.1±0.63 (171) |
28.9±0.56 (158) |
| Awards | Social/ Cultural/ Environmental/ Population Health |
Male | 33.6±0.92 (67) |
35.4±1.21 (58) |
32.7±0.91 (59) |
31.2±0.85 (53) |
33±1.14 (53) |
33.1±0.84 (95) |
31.6±0.75 (73) |
31.4±0.81 (85) |
32.5±0.87 (102) |
30.9±0.76 (66) |
32.7±1.1 (67) |
30±0.87 (61) |
32.5±1.06 (66) |
31.4±0.84 (62) |
32±1.04 (51) |
31.8±1.13 (46) |
31.5±1.08 (49) |
30.1±0.97 (46) |
31.6±0.9 (60) |
31.6±1.24 (42) |
| Grants | All | Female | 44.9±0.26 (954) |
44.3±0.4 (493) |
44.4±0.47 (309) |
43.9±0.59 (235) |
43±0.5 (276) |
43.4±0.53 (282) |
42.5±0.53 (303) |
43.1±0.5 (358) |
42.5±0.51 (325) |
40.7±0.54 (240) |
42.9±0.67 (169) |
41±0.46 (288) |
41.5±0.58 (246) |
42.8±0.57 (227) |
41.4±0.5 (267) |
42.9±0.44 (358) |
42.5±0.53 (201) |
41.4±0.54 (235) |
41.2±0.49 (261) |
41.6±0.45 (309) |
| Grants | All | Male | 47±0.19 (2,146) |
46.3±0.32 (937) |
45.3±0.4 (557) |
45.9±0.49 (392) |
45±0.48 (434) |
43.2±0.47 (372) |
44.1±0.55 (311) |
43±0.52 (351) |
43±0.52 (323) |
42.3±0.51 (305) |
42.2±0.62 (203) |
41.8±0.48 (354) |
42±0.57 (242) |
42.2±0.57 (245) |
42.2±0.53 (253) |
43.8±0.48 (390) |
41.3±0.72 (142) |
41.7±0.63 (164) |
42.4±0.57 (195) |
42.4±0.51 (234) |
| Grants | Biomedical | Female | 43.9±0.4 (404) |
43.7±0.64 (198) |
42.6±0.77 (110) |
40.7±0.96 (63) |
41±0.79 (70) |
41.6±0.94 (58) |
39.9±1.05 (65) |
41.8±1.02 (70) |
39.1±0.86 (62) |
40.4±0.99 (52) |
42.5±1.54 (32) |
39.7±0.85 (69) |
39.6±1.18 (56) |
41.3±1.28 (53) |
39.4±0.72 (58) |
39.5±0.69 (74) |
40.8±0.91 (44) |
39.9±1.02 (29) |
38.8±0.87 (53) |
41.3±0.9 (65) |
| Grants | Biomedical | Male | 46.9±0.23 (1,488) |
46.3±0.39 (635) |
45±0.5 (347) |
45.2±0.63 (228) |
44.4±0.67 (221) |
42.5±0.71 (169) |
42.8±0.71 (153) |
41.9±0.76 (139) |
41.1±0.73 (135) |
40.9±0.6 (160) |
40.8±0.84 (96) |
41±0.58 (194) |
41±0.77 (118) |
41.7±0.82 (117) |
41.2±0.83 (89) |
42.2±0.67 (137) |
41.2±1.08 (59) |
41.1±0.88 (67) |
41±0.79 (82) |
42.6±0.86 (87) |
| Grants | Clinical | Female | 44.6±0.61 (165) |
42.6±0.87 (92) |
44.1±1 (65) |
44.3±1.09 (48) |
42.1±0.96 (72) |
41.6±0.93 (84) |
42.9±1.14 (58) |
42.1±1.05 (79) |
43.2±1.2 (61) |
39.5±0.97 (62) |
42.3±1.19 (51) |
40.6±0.75 (87) |
39.4±0.97 (65) |
40.8±0.81 (59) |
42.4±1.02 (68) |
42.7±0.93 (81) |
41.2±1.01 (60) |
40.8±1.11 (58) |
41.1±1.01 (57) |
41.2±0.77 (68) |
| Grants | Clinical | Male | 47.1±0.52 (290) |
45.6±0.83 (143) |
45.6±0.93 (97) |
46.4±1.12 (61) |
44.3±1.08 (91) |
43.1±0.93 (93) |
44±1.41 (61) |
41.6±0.89 (89) |
43.5±0.92 (93) |
42.8±0.99 (76) |
43.8±1.2 (52) |
42.7±1.19 (78) |
42.7±1.14 (56) |
42.5±1.01 (60) |
41.7±0.74 (81) |
43±1.02 (88) |
41.7±1.29 (45) |
43.4±1.17 (44) |
42.2±0.94 (46) |
41.9±0.75 (77) |
| Grants | Health systems/ services |
Female | 46.3±0.75 (129) |
47.2±1.09 (68) |
45.4±1 (64) |
45.7±1.23 (45) |
44.1±1.07 (64) |
46.1±1.25 (50) |
45±1.05 (71) |
44.9±0.95 (99) |
43.5±0.98 (98) |
40.7±0.96 (63) |
42.4±1.32 (49) |
42±1.13 (68) |
41.6±1.18 (48) |
43.1±1.19 (60) |
40.8±1.05 (73) |
43.4±0.96 (83) |
44.9±1.16 (47) |
41.9±1.05 (75) |
42.8±1.01 (80) |
42.2±0.96 (79) |
| Grants | Health systems/ services |
Male | 46.8±0.72 (148) |
46.5±1.02 (69) |
45.1±1.25 (48) |
45.9±1.37 (53) |
46.2±1.2 (64) |
43±1.28 (42) |
46.1±1.8 (31) |
44.4±1.36 (68) |
44.6±1.47 (47) |
45.4±1.8 (31) |
43.2±1.94 (30) |
41.3±1.43 (35) |
41±1.77 (27) |
43.7±1.67 (26) |
44.7±1.59 (43) |
45.7±1.35 (68) |
40.8±1.86 (23) |
41.5±1.84 (27) |
44.7±1.63 (38) |
40.9±1.22 (35) |
| Grants | Social/ Cultural/ Environmental/ Population Health |
Female | 46.1±0.52 (256) |
44.9±0.77 (135) |
46.7±1.02 (70) |
45.2±1.19 (79) |
44.8±1.12 (70) |
44.9±1.03 (90) |
42.3±0.95 (109) |
42.9±0.93 (110) |
43±0.95 (104) |
42±1.29 (63) |
44.6±1.39 (37) |
42±1 (64) |
44.5±1.13 (77) |
45.9±1.14 (55) |
42.7±1.04 (68) |
44.7±0.81 (120) |
43.3±1.04 (50) |
41.9±0.95 (73) |
41.3±0.91 (71) |
41.6±0.91 (97) |
| Grants | Social/ Cultural/ Environmental/ Population Health |
Male | 47.7±0.62 (220) |
47.4±1.1 (90) |
46.9±1.33 (65) |
48.1±1.58 (50) |
47.4±1.34 (58) |
45±1.13 (68) |
46.4±1.27 (66) |
46.4±1.51 (55) |
45.8±1.63 (48) |
44.7±1.95 (38) |
42.7±1.84 (25) |
43.6±1.57 (47) |
44.6±1.6 (41) |
42.1±1.73 (42) |
42.8±1.66 (40) |
45.5±1.04 (97) |
40.5±2.48 (15) |
40.5±1.76 (26) |
43.3±1.67 (29) |
44.5±1.61 (35) |
Figure 4 tells a different and perhaps more surprising story. When the analysis is limited to first-time applications, average age trends downward on both grant and awards applications. Over the last two decades, the average age on first-time grant applications (4A) has decreased from 45 to 42 for female NPAs and 47 to 42 for male NPAs. In contrast, average age on first-time award applications mirrored the overall application trends observed in Figure 2B. This is unsurprising as the window of eligibility for awards programs is narrowly defined by career stage, which often corresponds to age, and for many awards programs applicants can apply only once during the appropriate career stage.
This contrast suggests that the observed aging of the broader applicant pool is likely driven by established applicants staying in the system longer, rather than new researchers entering the system later in their careers. These trends also show in that notable gap observed in Figure 3, between postdoctoral applications and grant applications, is filled with first-time grant applicants that are trending younger.
Closing Thoughts
This analysis highlights that age trends in the CIHR research community are a set of related but distinct patterns. While the overall pool is older, first-time applicants are entering at younger ages than they were two decades ago. The analysis also points to meaningful variation across programs, including a gap of more than a decade between the average age on postdoctoral fellowship applications and the average age observed on applications to major grant programs. This descriptive analysis highlights patterns, such as the divergence between grants and awards, without assigning a single cause. These data provide a baseline for understanding how CIHR's research ecosystem continues to shift and renew itself.
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