If you have the actual event (c section) counts for all the states and the state populations, which presumably are the numerators and denominators of the rates, then I assume the sums of the counts divided by the sums of the populations would equal the 22.5 US rate. In that case, I think what you are looking for is what the DIFF=ANOM option in the LSMEANS statement can provide. This shows an example with such data. Note that the log of the state populations is used as the offset.
proc genmod;
class state;
model cseccount=state / dist=poisson offset=logstpop;
lsmeans state / ilink diff=anom;
run;
An example involving proportions rather than rates can be found in this note.
But if you only have the rates as in your example table, then I guess the best you could do is to treat the US rate as a constant and test each state rate against it. The easiest way to do that is with a set of LSMESTIMATE statements that use the TESTVALUE= option to specify log(22.5) as the comparison value. Note that the LSMESTIMATE statement will compare the ESTIMATE value, which is the log rate, to the TESTVALUE. The following statements do this for the first two states. Note that the states will be in alphabetic order, so AK is first, followed by AL.
proc genmod;
class state;
model strate=state / dist=poisson;
lsmestimate state 'AK' 1 / ilink testvalue=%sysfunc(log(22.5));
lsmestimate state 'AL' 0 1 / ilink testvalue=%sysfunc(log(22.5));
run;
