Older subjects with elevated creatinine and ESR or CRP were thus excluded from our calculations. None of these had an effect in the younger subjects, but in older subjects a serum creatinine of more than 106 μM (1.4 mg/dL) and elevated inflammatory markers (ESR > 30 in women and ESR > 20 in men or CRP > 1 mg/dL) were associated with significantly lower mean hemoglobin values. We were also able to determine whether excessive alcohol intake, diabetes mellitus, renal failure, or inflammatory markers (C-reactive protein in NHANES, erythrocyte sedimentation rate in Scripps-Kaiser, elevated serum ferritin, or leukocytosis) affected the hemoglobin concentrations in these populations. This serves to eliminate most subjects with iron deficiency anemia and also many of those with the anemia of chronic inflammation, in which the transferrin saturation is also usually low. Both the Scripps-Kaiser and the NHANES databases included transferrin saturation and serum ferritin levels, and we were therefore able to exclude subjects with a transferrin saturation of less than 16% or a serum ferritin level less than 10 μg/L. In any analysis, elimination of subjects from consideration is constrained by the data that are available. Because there are virtually no differences in hemoglobin values of men in the age range of 20 to 59 or in women aged 20 through 49 in our data or in the analysis of the NHANES-III hemoglobin values, 12 we have used these age ranges representing younger adults, and the ages beyond these ranges to represent older adults. This type of analysis is shown in Table 2. In these and many other previous analyses of hematologic data the subjects have been divided into age in deciles. 13 Moreover, data derived from white subjects are not provided.
12 The other report uses exclusion criteria that are so draconian that less than 40% of the subjects remain in the data set. The data in these compilations are valuable, but unfortunately the hemoglobin values in one report are derived from the entire population, not corrected for subjects with disease states that may be associated with anemia. The NHANES-III database has recently been “mined” for hematologic values. However, this has not been documented by the study of genetic markers in either data set. It is likely that more of the black population of San Diego originates from the Northeast and the Midwest therefore, San Diego may have greater white admixture than the NHANES sample. The NHANES database attempts to reach a nationwide balance. Among black Americans there are varying degrees of admixture with non-African ancestry. Data regarding ancestral origin are available in the Scripps Kaiser database but not in NHANES-III, so that direct comparison is not possible. White Americans are a genetic mixture of persons from various parts of Europe and the Middle East. 10, 11 The ethnic origin of the individuals designated as white in these 2 databases is probably very similar.
One is the NHANES-III (the third US National Health and Nutrition Examination Survey) database, the other the Scripps-Kaiser database that we collected in the San Diego area between 19. Fortunately, at least 2 such databases now exist. How is one, then, to find a hemoglobin concentration above which 95% or 97.5% of the normal subjects are included? In the past, a part of the problem has been the availability of large databases that are sufficiently well documented to allow exclusion of individuals who are not “normal.” The systematic exclusion of such population members is important in dealing with an abnormality that is as common as is anemia, particularly in women. Conversely, if the WHO standards were correct, the cutoff value given by Jandl 3 would result in adjudging 22% of all healthy men to be anemic. For example, assuming a Gaussian distribution of the data one may calculate that if the 142-g/L(14.2-g/dL) cutoff proposed by Jandl 3 is correct, a man with a 130-g/L(13-g/dL) hemoglobin concentration, therefore passing the WHO standard for anemia, would be in the lowest 0.01% of the distribution of hemoglobin values. The differences in the stated lower limits of normal may seem small, but in their application they are far from trivial. To convert hemoglobin from grams per deciliter to grams per liter, multiply grams per deciliter by 10.
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