Does this mean the IRR is the estimated rate ratio for a 1% increase
in % Hispanic?
Yes.
Is there a way I can scale this so it can be interpreted to be the
estimated rate ratio for a 10% increase in the % Hispanic?
Divide the variable by 10 before you run your regression.
They indeed used Poisson distribution ("We calculated crude incidence rates as the number of events divided by the total number of person-years at risk following MGUS diagnosis, and 95% confidence intervals (CIs) were based on a Poisson distribution").
We can infer the likely follow-up times: round( sapply( 1:20, function( x ) poisson.test( 52*x, T = x )$conf.int ), 0 ) so something between 11,000 and 15,000 seems to work for the MGUS group (where we had a mortality rate of 52 [95% CI 48-56] per 1000 patient-years), and round( sapply( seq( 0.1, 1, 0.1 ), function( x ) poisson.test( round( 29*x ), T = x )$conf.int ), 0 ) suggests around 300 py (where the rate was 29 [14-58] per 1000 patient-years).
This seems extremely unbalanced, but so was the sample: they had 2,891 MGUS and 44 MGRS patients. They write that "Overall follow-up time for the 2935 patients was 11,050 person-years" so everything seems to check.
UPDATE: AAh, this whole calculation was unnecessary: they've given the number of deaths! "Of the 2891 MGUS patients 566 (20%) and of the 44 MGRS patients eight (18%) died during follow-up." So we actually know the follow-up time (up to rounding): $566/52=10.9$ in the MGUS group, $8/29=0.28$ in the MGRS (in 1000 py). poisson.test(566,10.9) and poisson.test(8,0.28) checks basically OK (I mean the CIs match the presented ones, with a little difference in the MGRS group), and $10.9+0.28= 11.18$ also checks out more-or-less with their presented overall follow-up time.
(I don't know what is the reason for the difference in the MGRS group; I checked that no follow-up time for which the rate is rounded to 29 will result in the CI they presented in the paper. Perhaps its just a rounding error on their part; my best idea is to write an email to the corresponding author.)
Best Answer
Let's assume you followed 100 people. 50 of them you followed for 2 years and nothing happened. 25 newly developed the disease of interest after being observed for on average 1 year (not counting time after developing the diagnosis). 25 could not be observed for the full two years (on average you observed them for 0.5 years).
In that case you observed 25 cases in 137.5 (=2×50+1×25+0.5×25) patient years of follow-up or 18.18 (=25/137.5×100) per 100 patient years.