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Use the ",{"type":42,"tag":188,"props":836,"children":838},{"href":837},"/tools/power-analysis",[839],{"type":48,"value":840},"Power Analysis Calculator",{"type":48,"value":842}," to determine sample size needed to detect a given difference in age-standardized rates.",{"type":42,"tag":43,"props":844,"children":846},{"id":845},"frequently-asked-questions",[847],{"type":48,"value":848},"Frequently Asked Questions",{"type":42,"tag":51,"props":850,"children":851},{},[852,857,859,863,865,870],{"type":42,"tag":55,"props":853,"children":854},{},[855],{"type":48,"value":856},"When should I use direct vs indirect standardization?",{"type":48,"value":858},"\nUse ",{"type":42,"tag":55,"props":860,"children":861},{},[862],{"type":48,"value":78},{"type":48,"value":864}," when: you have reliable age-specific rates for your study populations (sufficient events per stratum); you want to produce a summary rate that can be directly compared across multiple groups; you are producing official public health statistics. Use ",{"type":42,"tag":55,"props":866,"children":867},{},[868],{"type":48,"value":869},"indirect standardization (SMR)",{"type":48,"value":871}," when: your study population is small and age-specific rates are unstable due to sparse counts; you want to compare to a well-established national or international reference; you are analyzing occupational cohorts or disease registries where the study population is well-defined but small. The SMR is more stable with small numbers but is harder to compare across studies with different reference populations.",{"type":42,"tag":51,"props":873,"children":874},{},[875,880,882,887,889,894],{"type":42,"tag":55,"props":876,"children":877},{},[878],{"type":48,"value":879},"What is the WHO 2000 World Standard Population?",{"type":48,"value":881},"\nThe ",{"type":42,"tag":55,"props":883,"children":884},{},[885],{"type":48,"value":886},"WHO 2000 World Standard Population",{"type":48,"value":888}," is a reference age distribution created by WHO based on the average world age structure around the year 2000. It consists of proportions for 18 five-year age groups from 0–4 to 85+. Because it is internationally standardized, using it allows direct comparison of age-standardized rates across all countries and time periods — a study from Brazil using the WHO 2000 standard produces an ASR directly comparable to a study from Sweden using the same standard. The ",{"type":42,"tag":55,"props":890,"children":891},{},[892],{"type":48,"value":893},"US 2000 Standard Population",{"type":48,"value":895}," is an alternative used by the US CDC for domestic comparisons; it produces slightly different ASRs because the US age distribution differs from the global average. Always report which standard population you used.",{"type":42,"tag":51,"props":897,"children":898},{},[899,904,906,911,913,918,920,925,927,932,934,939],{"type":42,"tag":55,"props":900,"children":901},{},[902],{"type":48,"value":903},"Why does my age-standardized rate differ from published figures?",{"type":48,"value":905},"\nCommon reasons for discrepancies: (1) ",{"type":42,"tag":55,"props":907,"children":908},{},[909],{"type":48,"value":910},"Different standard population",{"type":48,"value":912}," — WHO 2000 vs US 2000 vs European Standard Population give different ASRs; (2) ",{"type":42,"tag":55,"props":914,"children":915},{},[916],{"type":48,"value":917},"Age group boundaries",{"type":48,"value":919}," — some sources use 0–4, 5–9, ..., 85+ while others use 0–14, 15–44, 45–64, 65+; (3) ",{"type":42,"tag":55,"props":921,"children":922},{},[923],{"type":48,"value":924},"Population denominator",{"type":48,"value":926}," — mid-year population vs person-years at risk; (4) ",{"type":42,"tag":55,"props":928,"children":929},{},[930],{"type":48,"value":931},"Event definition",{"type":48,"value":933}," — underlying cause of death vs contributing cause; (5) ",{"type":42,"tag":55,"props":935,"children":936},{},[937],{"type":48,"value":938},"Reference year",{"type":48,"value":940}," — rates are often published with 2–3 year lag. Always compare methods and standard populations to reconcile differences before reporting.",{"type":42,"tag":51,"props":942,"children":943},{},[944,949,951,956],{"type":42,"tag":55,"props":945,"children":946},{},[947],{"type":48,"value":948},"How do I interpret a Standardized Mortality Ratio (SMR) of 1.4?",{"type":48,"value":950},"\nAn SMR of 1.4 means the study population experienced ",{"type":42,"tag":55,"props":952,"children":953},{},[954],{"type":48,"value":955},"40% more deaths",{"type":48,"value":957}," than expected based on the reference population's age-specific death rates applied to the study population's age structure. An SMR > 1 indicates excess mortality; SMR \u003C 1 indicates lower-than-expected mortality. The SMR's 95% confidence interval determines whether the excess is statistically significant: if the CI excludes 1.0, the difference is significant at the 5% level. When the CI includes 1.0 (e.g., SMR = 1.4, 95% CI: 0.9–2.1), the excess could be due to chance. Always report the observed and expected event counts alongside the SMR, as a ratio of 14/10 and 140/100 both give SMR = 1.4 but carry very different statistical weight.",{"title":7,"searchDepth":959,"depth":959,"links":960},2,[961,962,963,964,965,966,967,968],{"id":45,"depth":959,"text":49},{"id":114,"depth":959,"text":117},{"id":205,"depth":959,"text":208},{"id":432,"depth":959,"text":435},{"id":588,"depth":959,"text":591},{"id":735,"depth":959,"text":738},{"id":795,"depth":959,"text":798},{"id":845,"depth":959,"text":848},"markdown","content:tools:071.age-standardized-rate.md","content","tools/071.age-standardized-rate.md","tools/071.age-standardized-rate","md",{"loc":4},1775502471986]