From the description you provided, your first question is about the distribution of people's age. Normal (i.e. Gaussian) distribution applies to such kind of applications.
It will be helpful if you know how the confidence interval (CI) was calculated, because there are many different possible ways that the CI was calculated. For instance, if the distribution is of normal distribution, and the CI was calculated using t-test, then the SD can be estimated with following equation:
SD = sqrt(n)*(ci_upper - ci_lower)/(2 * tinv((1-CL)/2; n-1)),
where CL is the confidence level, ‘ci_upper’ and ‘ci_lower’ are the upper and lower limits of CI respectively, and 'tinv()' is the inverse of Student's T cdf.
Otherwise, if it is of normal distribution, but a known SD was used in calculating CI, then the SD can be calculated with following equation:
SD = sqrt(n)*(ci_upper - ci_lower)/(sqrt(8) * erfinv(CL)),
where 'erfinv ()' is the inverse error function.
Your second question is about the distribution of people's sex (i.e. male or female). From the data you provided, it sounds that there are k=274 males among n=427 of whole samples. Bernoulli distribution applies to this application. In this case, the variance (of male's population) = p*(1-p) = 0.2299, and SD = sqrt(0.2299) = 0.4795, where p is the mean value. Note that "valiance = mean*(1-mean)" is applicable to Bernoulli distribution only.