The development of MUAC-for-age reference data recommended by a WHO Expert Committee.

Research/Recherche The development of MUAC-for-age reference data recommended by a WHO Expert Committee M. de Onis,1 R. Yip,2 & Z. Mei3 Low mid-upper-arm circumference (MUAC), determined on the basis of a fixed cut-off value, has commonly been used as a proxy for low weight-for-height (wasting). The use of a fixed cut-off value was based on the observation that MUAC showed small age- and sex-specific differences. However, in 1993, a WHO Expert Committee concluded that age independence is not reflected in the true pattern of mid-upper arm growth, recommended the use of MUAC-for-age, and presented age- and sex-specific MUAC reference data developed with observations obtained from a representative sample of children in the USA aged 6-59 months. In this article, we explain the methodology for the development of these data, present age- and sex-specific growth curves and tables and discuss the applications and limitations of MUAC as a nutritional indicator. To develop the reference data, estimates were first obtained for the mean and standard deviation of MUAC for each month of age using 7-month segmental regression equations; a 5th-degree and a 3rd- degree polynomial in age was then used to describe the mean and standard deviation, respectively, of MUAC-for age. These curves show important age-specific differences, and significant sex-specific differ- ences for boys and girls <24 months of age. Correct interpretation of MUAC with regard to nutritional status requires the use of MUAC-for-age reference data such as those presented here. Introduction For many years, mid-upper-arm circumference (MUAC) has been used as an alternative indicator of nutritional status if the collection of height and weight measurements was difficult, such as during emergencies, famines, or refugee crises. In such cases, low MUAC, determined on the basis of a sin- gle cut-off value, has been used as a proxy for low weight-for-height (i.e. wasting). Comparisons of the two indicators, however, show that they are poorly correlated (1, 2). Moreover, in community-based studies, MUAC appears to be a better predictor of childhood mortality than height- and weight-based anthropometric indicators (3-6). This has led to the Medical Officer, Nutrition unit, World Health Organization, 1211 Geneva 27, Switzerland. Correspondence should be sent to this author. 2 Senior Project Officer, UNICEF, Jakarta, Indonesia; and Division of Nutrition and Physical Activity, Centers for Disease Control and Prevention, Atlanta, GA, USA. I Visiting scientist, Maternal and Child Health Branch, Division of Nutrition and Physical Activity, Centers for Disease Control and Prevention, Atlanta, GA, USA. Reprint No. 5748 proposal that MUAC should be used as an inde- pendent indicator for routine nutritional assessment. The operational advantages of MUAC include the portability of measuring tapes and the fact that a single cut-off value (generally 12.5cm or 13.0cm) has been used for children <5 years of age. The use of a fixed cut-off value was based on the observation in the early 1960s that for normal, well-fed Polish chil- dren MUAC increased by only about 1 cm between the ages of 1 year and 4 years, and that there was a difference of only a few millimetres between boys and girls at most ages (7, 8). However, the assump- tion that MUAC is age- and sex-independent in young children has recently been questioned, and it has been suggested that MUAC Z-scores that adjust for differences between age and sex are a more use- ful indicator of nutritional status (9, 10). In 1993, a WHO Expert Committee reviewed the scientific evidence underlying the use and inter- pretation of MUAC (11). The Committee examined mean MUAC data across ages from the National Center for Health Statistics (NCHS) sample of children in the USA, and for a cohort of Malawian children; for both populations MUAC increased by approximately 2 cm between 6 and 59 months of age. Bulletin of the World Health Organization, 1997, 75 (1): 11-18 ©D World Health Organization 1997 11 M. de Onis et al. When a MUAC-for-age reference for both boys and girls was constructed from the NCHS data and applied to the Malawian children, important differences were observed between the age-specific prevalences of low MUAC when either MUAC-for- age Z-scores or a cut-off value of 13.0cm were used (11). A fixed cut-off value preferentially identified younger children as malnourished. The Committee concluded that the assumption of age independence did not reflect the true pattern of mid-upper-arm growth and recommended that proper interpretation of MUAC required the use of age-specific reference data (12). In this article, we explain the methodology for the development of these data, present age- and sex-specific growth curves and tables and discuss the applications and limitations of MUAC as a nutritional indicator. Methods To construct the MUAC-for-age growth reference data, we used growth data for children 6-59 months of age from the first and second National Health and Nutrition Examination Surveys in the USA (NHANES I, NHANES II). Both NHANES I and NHANES II used a complex, multistage, probabil- ity-sampling design to obtain a representative sam- ple of the non-institutionalized civilian population aged 6 months to 74 years in the USA. Detailed descriptions of the samples have been published pre- viously (13, 14). Data from both surveys were com- bined in order to increase sample size. A total of 2310 measurements of MUAC for NHANES I and 3309 measurements for NHANES II were available for children aged 6-59 months. We verified that age- and sex-specific growth status were comparable in both surveys. We estimated the mean and standard deviation (SD) of MUAC for each month of age by combining MUAC data for the relevant month of age with data for the 3 months before and 3 months after the age concerned.a A linear regression of the resulting 7-month segment of MUAC data by age provides a more stable estimate of the mean and SD of MUAC at the mid-point month than that based on the data for that month only. In using this segmental re- gression approach the sample size was effectively expanded by "borrowing" the MUAC values of children within +3 months of age, without, however, assuming that there was no MUAC growth during the 7-month period. Mean MUAC for each month of age, as obtained from the segmental regression equations, and the 95% range of the MUAC by age regression were used to estimate the SD for each month of age. MUAC growth curves representing the mean and +1, 2, and 3 SDs were constructed with the monthly estimates of the mean and SD of MUAC obtained from the regression equations. For each of the curves thus developed, a 5th-degree polynomial equation in age was used to describe the mean, and a 3rd-degree polynomial to describe the SD. This approach assumes that the distribution of MUAC is normal and that MUAC growth within a 7-month period can be adequately characterized using a simple linear equation. The SD values of both sexes were not statistically different at the 5% level: thus we used the sex-combined SD value for all three curves in order to obtain more stable SD esti- mates. The reference data and growth curves were developed using the Centers for Disease Control and Prevention mainframe. a Since no data were available for children younger than 6 months, for the ages 6, 7, and 8 months the MUAC data used were, respectively, those for 6-9 months, 6-10 months, and 6-11 months. For the upper end of the curves there were MUAC data available beyond 59 months. Table 1: Constant and coefficients of best-fit polynomial equationsa for the mean and SD of MUAC-for-age b Mean: Coefficient Boys Girls Both sexes SD C, 13.610 11.534 12.408 1.0566 C0 2.9288 x 10 5.1060 x 10 4.2700 x 10 2.0731 x 10 2 C2 -1.3705 x 10 2 -2.3408 x 10 2 -1.9924 x 10 2 -5.0945 x 10 4 C3 3.3561 x 10 4 5.4240 x 10 4 4.7333 x 10 4 5.2768 x 10 6 C4 -3.8818 x 10 6 -5.9797 x 10 6 -5.3372 x 10 6 - C5 1.7218 x 10 8 2.5431 x 10 8 2.3154 x 10 8 _ a MUAC-for-age Mean = C, + C,(age) + C2(age)2 + C3(age)3 + C4(age)4 + C5(age)5; MUAC-for-age SD = Co + C,(age) + C2(age)2 + C3(age)3. b MUAC-for-age = mid-upper-arm-circumference-for-age. 12 WHO Bulletin OMS. Vol 75 1997 MUAC-for-age reference data Fig. 1. MUAC-for-age growth reference curve for boys aged 6-59 months. 22 +3 SD +25SD +1 SD 18 O ~~~~~~~~~Mean <D 6- - -1 SD 14 --2 SD 12 - ~~~~~~~~~-3SD 6 12 18 24 30 36 42 48 54 59 Age (months) Fig. 2. MUAC-for-age growth reference curve for girls aged 6-59 months. 22 +2 SD +1 SD 18 O ~~~~~~~~~Mean <16 --1 SD D 14 -2 SD 12 -3 SD 10 I I6 12 182430 3642 48 54 59 Age (months) Fig. 3. Combined MUAC-for-age growth reference curve for boys and girls aged 6-59 months. 22 +--3 SD +2 SD +1 SD E 18 o ~~~~~~~~~Mean C)~ ~~~~------<16 1 SD D 2 14 --------25SD -3 SD 120 6 12 18 24 30 36 42 48 54 59 Age (months) Results The best-fit polynomial equations for the MUAC- for-age growth data are presented in Table 1. Figures 1-3 show sex-specific and sex-combined MUAC- tor-age reterence growth curves for children aged 6- 59 months. Tables 2-4 present the numerical refer- ence data. Although most of the variation in MUAC is captured by the sex-combined MUAC-for-age curves, there are none the less significant sex-specific differences for children <24 months of age. Discussion Data from both affluent and non-affluent popu- lations show that MUAC is age dependent; this results in the overdiagnosis of wasting among younger children, and its underdiagnosis among older ones when a fixed cut-off value is used (1]). This age-specific variability in MUAC would explain the poor correlation of low MUAC (deter- mined relative to a fixed cut-off value) with low weight-for-height (15). This bias may also account for the good predictive value of low MUAC (de- termined relative to a fixed cut-off value) for mor- tality; younger children are more likely to have both lower MUAC and higher rates of mortality than older children. As shown by the Expert Com- mittee's analyses, the superior performance of low MUAC as a predictor for mortality declined significantly after the adjustment of MUAC for age. In fact, the performance of unadjusted MUAC in predicting mortality was comparable to that of age, height, or weight indicators developed on the basis of fixed cut-off points (i.e. unadjusted for age) (11). Recent data show that MUAC Z-scores that adjust for differences of age and sex are a more useful indicator of nutritional status than a fixed cut- off value. For example, among Bangladeshi children 12 59 months of age, the prevalence of under- nutrition as determined by MUAC Z-scores was only marginally higher among girls than boys. In contrast, the use of a fixed cut-off value (12.5cm) indicated that there was a markedly higher pre- valence of undernutrition among girls. Differences according to age were also striking; a high propor- tion of children >3 years of age had low MUAC Z- scores, even though only very few of them had a MUAC value <12.5cm (9). Although low MUAC Z-scores still showed younger children to be more often undernourished than older ones, under- nutrition between 6 and 59 months of age was more evenly distributed, with a greater proportion of older children identified as undernourished, when cut-off values developed on the basis of MUAC-for-age Z- scores were used (9. II). WHO Bulletin OMS. Vol 75 1997 13 M. de Onis et al. Table 2: MUAC-for-age reference data for boys aged 6-59 monthSa -3 SD 11.5 11.6 11.7 11.7 11.8 11.9 11.9 12.0 12.0 12.1 12.1 12.1 12.1 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.3 12.3 12.3 12.3 12.3 12.3 12.3 12.4 12.4 12.4 12.4 12.4 12.4 12.5 12.5 12.5 12.5 12.5 12.5 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 -2 SD 12.6 12.7 12.8 12.9 13.0 13.1 13.2 13.2 13.3 13.3 13.4 13.4 13.4 13.5 13.5 13.5 13.5 13.5 13.6 13.6 13.6 13.6 13.6 13.7 13.7 13.7 13.7 13.7 13.8 13.8 13.8 13.8 13.8 13.9 13.9 13.9 13.9 14.0 14.0 14.0 14.0 14.0 14.1 14.1 14.1 14.1 14.1 14.1 14.2 14.2 14.2 14.2 14.2 14.2 1 SD Mean 13.8 13.9 14.0 14.2 14.2 14.3 14.4 14.5 14.5 14.6 14.6 14.7 14.7 14.8 14.8 14.8 14.9 14.9 14.9 14.9 14.9 15.0 15.0 15.0 15.0 15.1 15.1 15.1 15.1 15.2 15.2 15.2 15.2 15.3 15.3 15.3 15.4 15.4 15.4 15.4 15.5 15.5 15.5 15.6 15.6 15.6 15.6 15.7 15.7 15.7 15.7 15.8 15.8 15.8 14.9 15.1 15.2 15.4 15.5 15.6 15.7 15.7 15.8 15.9 15.9 16.0 16.0 16.1 16.1 16.1 16.2 16.2 16.2 16.3 16.3 16.3 16.3 16.4 16.4 16.4 16.5 16.5 16.5 16.5 16.6 16.6 16.6 16.7 16.7 16.7 16.8 16.8 16.8 16.9 16.9 17.0 17.0 17.0 17.1 17.1 17.1 17.2 17.2 17.2 17.3 17.3 17.3 17.4 ±1 SD 16.1 16.3 16.4 16.6 16.7 16.8 16.9 17.0 17.1 17.1 17.2 17.3 17.3 17.4 17.4 17.5 17.5 17.5 17.6 17.6 17.6 17.7 17.7 17.7 17.8 17.8 17.8 17.9 17.9 17.9 18.0 18.0 18.0 18.1 18.1 18.1 18.2 18.2 18.3 18.3 18.4 18.4 18.4 18.5 18.5 18.6 18.6 18.7 18.7 18.8 18.8 18.9 18.9 19.0 +2 SD 17.3 17.5 17.6 17.8 17.9 18.0 18.1 18.2 18.3 18.4 18.5 18.6 18.6 18.7 18.7 18.8 18.8 18.9 18.9 18.9 19.0 19.0 19.1 19.1 19.1 19.2 19.2 19.2 19.3 19.3 19.3 19.4 19.4 19.5 19.5 19.6 19.6 19.7 19.7 19.8 19.8 19.9 19.9 20.0 20.0 20.1 20.1 20.2 20.2 20.3 20.4 20.4 20.5 20.6 a Some data previously published in WHO Technical Report Series, No. 854 (ref. 1 1). ~~~~~~~~~~~~~~~~~~~~~~~~~~~WHO Bulletin OMS. Vol 75 1997 Age (months) 6 7 8 9 10 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 -4 SD 10.3 10.4 10.5 10.5 10.6 10.6 10.7 10.7 10.8 10.8 10.8 10.8 10.8 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 ±3 SD 18.4 18.6 18.8 19.0 19.1 19.3 19.4 19.5 19.6 19.7 19.8 19.8 19.9 20.0 20.0 20.1 20.1 20.2 20.2 20.3 20.3 20.4 20.4 20.4 20.5 20.5 20.6 20.6 20.6 20.7 20.7 20.8 20.8 20.9 20.9 21.0 21.0 21.1 21.1 21.2 21.3 21.3 21.4 21.4 21.5 21.6 21.6 21.7 21.8 21.8 21.9 22.0 22.1 22.2 14 MUAC-for-age reference data Table 3: MUAC-for-age reference data for girls aged 6-59 monthSa -1 SD 12.7 13.0 13.2 13.4 13.6 13.7 13.9 14.0 14.1 14.2 14.3 14.4 14.4 14.5 14.5 14.6 14.6 14.7 14.7 14.7 14.7 14.8 14.8 14.8 14.8 14.9 14.9 14.9 14.9 15.0 15.0 15.0 15.0 15.1 15.1 15.1 15.2 15.2 15.2 15.3 15.3 15.3 15.4 15.4 15.4 15.5 15.5 15.5 15.6 15.6 15.6 15.7 15.7 15.7 Mean 13.9 14.1 14.4 14.6 14.8 15.0 15.1 15.2 15.4 15.5 15.6 15.7 15.7 15.8 15.8 15.9 15.9 16.0 16.0 16.1 16.1 16.1 16.1 16.2 16.2 16.2 16.3 16.3 16.3 16.3 16.4 16.4 16.4 16.5 16.5 16.6 16.6 16.6 16.7 16.7 16.7 16.8 16.8 16.9 16.9 17.0 17.0 17.0 17.1 17.1 17.2 17.2 17.3 17.3 +1 SD 15.0 15.3 15.6 15.8 16.0 16.2 16.4 16.5 16.6 16.7 16.8 16.9 17.0 17.1 17.2 17.2 17.3 17.3 17.4 17.4 17.4 17.5 17.5 17.5 17.6 17.6 17.6 17.7 17.7 17.7 17.8 17.8 17.8 17.9 17.9 18.0 18.0 18.1 18.1 18.1 18.2 18.2 18.3 18.3 18.4 18.4 18.5 18.6 18.6 18.7 18.7 18.8 18.8 18.9 ±2SD +3SD 16.2 16.5 16.8 17.0 17.2 17.4 17.6 17.7 17.9 18.0 18.1 18.2 18.3 18.4 18.5 18.5 18.6 18.6 18.7 18.7 18.8 18.8 18.9 18.9 18.9 19.0 19.0 19.0 19.1 19.1 19.2 19.2 19.2 19.3 19.3 19.4 19.4 19.5 19.5 19.6 19.6 19.7 19.8 19.8 19.9 19.9 20.0 20.1 20.1 20.2 20.3 20.3 20.4 20.5 17.4 17.7 18.0 18.2 18.4 18.6 18.8 19.0 19.2 19.3 19.4 19.5 19.6 19.7 19.8 19.8 19.9 20.0 20.0 20.1 20.1 20.2 20.2 20.3 20.3 20.3 20.4 20.4 20.5 20.5 20.5 20.6 20.6 20.7 20.7 20.8 20.8 20.9 21.0 21.0 21.1 21.2 21.2 21.3 21.4 21.4 21.5 21.6 21.7 21.7 21.8 21.9 22.0 22.1 aSome data previously published in WHO Technical Report Series, No. 854 (ref. 1 1). WHO Bulletin OMS. Vol 75 1997 Age (months) -4 SD 6 7 8 9 10 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 9.2 9.4 9.6 9.8 9.9 10.0 10.1 10.2 10.3 10.4 10.4 10.5 10.5 10.6 10.6 10.6 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.9 10.9 10.9 10.9 10.9 10.9 10.9 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 11.0 -3 SD 10.4 10.6 10.8 11.0 11.1 11.3 11.4 11.5 11.6 11.7 11.7 11.8 11.8 11.9 11.9 11.9 12.0 12.0 12.0 12.0 12.1 12.1 12.1 12.1 12.1 12.1 12.1 12.2 12.2 12.2 12.2 12.2 12.2 12.3 12.3 12.3 12.3 12.4 12.4 12.4 12.4 12.4 12.4 12.5 12.5 12.5 12.5 12.5 12.5 12.5 12.5 12.5 12.5 12.5 -2 SD 11.5 11.8 12.0 12.2 12.3 12.5 12.6 12.7 12.8 12.9 13.0 13.1 13.1 13.2 13.2 13.3 13.3 13.3 13.4 13.4 13.4 13.4 13.4 13.5 13.5 13.5 13.5 13.5 13.6 13.6 13.6 13.6 13.6 13.7 13.7 13.7 13.8 13.8 13.8 13.8 13.9 13.9 13.9 13.9 14.0 14.0 14.0 14.0 14.0 14.1 14.1 14.1 14.1 14.1 15 M. de Onis et al. Table 4: Combined MUAC-for-age reference data for boys and girls aged 6-59 monthSa Age (months) 6 7 8 9 10 1 1 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 -4 SD 9.7 9.9 10.0 10.1 10.2 10.3 10.4 10.5 10.5 10.6 10.6 10.7 10.7 10.7 10.7 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.8 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 10.9 11.0 11.0 11.0 11.0 11.0 11.0 11.0 -3 SD 10.9 11.0 11.2 11.3 11.5 11.6 11.7 11.7 11.8 11.9 11.9 12.0 12.0 12.0 12.1 12.1 12.1 12.1 12.1 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.3 12.3 12.3 12.3 12.3 12.3 12.4 12.4 12.4 12.4 12.4 12.5 12.5 12.5 12.5 12.5 12.5 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 12.6 -2 SD 12.0 12.2 12.4 12.5 12.7 12.8 12.9 13.0 13.1 13.1 13.2 13.2 13.3 13.3 13.4 13.4 13.4 13.4 13.5 13.5 13.5 13.5 13.5 13.6 13.6 13.6 13.6 13.6 13.7 13.7 13.7 13.7 13.7 13.8 13.8 13.8 13.8 13.9 13.9 13.9 13.9 14.0 14.0 14.0 14.0 14.1 14.1 14.1 14.1 14.1 14.1 14.1 14.2 14.2 -1 SD 13.2 13.4 13.6 13.7 13.9 14.0 14.1 14.2 14.3 14.4 14.5 14.5 14.6 14.6 14.7 14.7 14.7 14.8 14.8 14.8 14.9 14.9 14.9 14.9 14.9 15.0 15.0 15.0 15.0 15.1 15.1 15.1 15.1 15.2 15.2 15.2 15.3 15.3 15.3 15.4 15.4 15.4 15.5 15.5 15.5 15.5 15.6 15.6 15.6 15.7 15.7 15.7 15.7 15.8 Mean 14.3 14.6 14.8 14.9 15.1 15.2 15.4 15.5 15.6 15.7 15.8 15.8 15.9 15.9 16.0 16.0 16.1 16.1 16.1 16.2 16.2 16.2 16.3 16.3 16.3 16.3 16.4 16.4 16.4 16.4 16.5 16.5 16.5 16.6 16.6 16.6 16.7 16.7 16.8 16.8 16.8 16.9 16.9 17.0 17.0 17.0 17.1 17.1 17.2 17.2 17.2 17.3 17.3 17.3 +1 SD 15.5 15.7 16.0 16.2 16.3 16.5 16.6 16.7 16.8 16.9 17.0 17.1 17.2 17.2 17.3 17.3 17.4 17.4 17.5 17.5 17.5 17.6 17.6 17.6 17.7 17.7 17.7 17.8 17.8 17.8 17.9 17.9 17.9 18.0 18.0 18.1 18.1 18.1 18.2 18.2 18.3 18.3 18.4 18.4 18.5 18.5 18.6 18.6 18.7 18.7 18.8 18.8 18.9 18.9 a Some data previously published in WHO Technical Report Series, No. 854 (ref. 1 1). ~~~~~~~~~~~~~~~~~~~~~~~~~~~WHO Bulletin OMS. Vol 75 1997 +2 SD 16.7 16.9 17.2 17.4 17.5 17.7 17.9 18.0 18.1 18.2 18.3 18.4 18.5 18.5 18.6 18.7 18.7 18.8 18.8 18.8 18.9 18.9 19.0 19.0 19.0 19.1 19.1 19.1 19.2 19.2 19.3 19.3 19.3 19.4 19.4 19.5 19.5 19.6 19.6 19.7 19.7 19.8 19.8 19.9 20.0 20.0 20.1 20.1 20.2 20.3 20.3 20.4 20.5 20.5 +3 SD 17.8 18.1 18.3 18.6 18.8 18.9 19.1 19.2 19.4 19.5 19.6 19.7 19.8 19.8 19.9 20.0 20.0 20.1 20.1 20.2 20.2 20.3 20.3 20.4 20.4 20.4 20.5 20.5 20.6 20.6 20.6 20.7 20.7 20.8 20.8 20.9 20.9 21.0 21.1 21.1 21.2 21.2 21.3 21.4 21.4 21.5 21.6 21.6 21.7 21.8 21.9 21.9 22.0 22.1 16 MUAC-for-age reference data These findings relating to the use of MUAC- for-age underline the need to evaluate more thor- oughly the less-commonly used indicator MUAC- for-height, measured with the QUAC stick (16), which is a simple tool for adjusting MUAC cut- off values according to height. MUAC-for-height may prove to be a useful proxy for MUAC-for- age when accurate age information is not available (17). The Centers for Disease Control and Preven- tion and WHO are currently developing MUAC- for-height Z-scores for preschool children on the basis of the data collected for NHANES I and NHANES II. Although there are advantages to using MUAC with a single cut-off value, using MUAC-for-age ref- erence data in the field is no more difficult than using weight-for-height reference data, a common feature of rapid nutritional assessment surveys. Moreover, the equipment required to measure MUAC is sim- pler and less expensive than that required for meas- uring weight and height. A disadvantage of using MUAC-for-age in field surveys, however, is the need to determine age accurately, which can be difficult. Another limitation is the relatively large variability in MUAC measurements made by different workers, indicating the need for careful training and standardization. Although low MUAC is confounded by age when a fixed cut-off value is used, it is still appro- priate for certain applications. For example, in some settings it may be desirable to use a more sen- sitive, less specific indicator for young children in view of their higher risk of morbidity and mortality. However, the proper interpretation of MUAC re- garding nutritional status, or its causal relationship with functional outcomes, requires the use of MUAC-for-age reference data. Acknowledgements We are grateful to Dr D. Pelletier for providing the nutri- tional data from Malawi and for his helpful comments. We thank Ms M. Blossner for her assistance in developing the reference data. Resume Etablissement des donnees de reference pour l'indicateur MUAC/age recommandees par un Comite d'experts de l'OMS Depuis des annees, le perimbtre brachial a mi- hauteur (MUAC) est utilis6 comme indicateur de remplacement pour 1'etat nutritionnel si la mesure du poids et de la taille est difficile a r6aliser. Un MUAC faible, estim6 par rapport a une valeur seuil etablie pour tous les enfants de moins de cinq ans, est utilis6 en remplacement de l'indica-teur poids/ taille pour 6valuer l'6maciation. L'emploi d'un seuil fixe est fond6 sur l'observation selon laquelle le MUAC augmente tres peu entre un et quatre ans, et ne presente qu'une diff6rence n6gligeable entre filles et garqons. Ces questions ont et6 examin6es en 1993 par le Comit6 OMS d'experts sur l'utilisa- tion et l'interpretation de l'anthropom6trie, qui a conclu que le postulat de l'independance du MUAC par rapport a l'age ne reflete pas r6ellement la croissance au niveau du bras. Pour construire une courbe de ref6rence pour l'indicateur MUAC/age nous avons utilis6 des don- nees class6es par sexe recueillies chez des enfants de 6 a 59 mois au cours des premiere et deuxieme enquetes nationales sur la sant6 et la nutrition (Na- tional Health and Nutrition Examination Surveys) aux Etats-Unis d'Amerique. Suivant une m6thode d'estimation a plusieurs degres, la moyenne et l'ecart type du MUAC/age ont ete calcul6s, et une relation polynomiale avec l'age a et6 utilisee pour ajuster les courbes de croissance lissees. Les courbes obtenues montrent d'importantes diff6rences en fonction de l'age et du sexe, notamment chez les enfants de moins de 24 mois. L'utilisation d'un seuil fixe pour d6terminer les valeurs faibles du MUAC surestime systematique- ment la pr6valence de la malnutrition chez les jeunes enfants et la sous-estime chez les enfants plus ages. Lorsqu'on recherche un indicateur plus sensible et moins sp6cifique de la malnutrition chez les jeunes enfants, on peut encore utiliser un seuil fixe, mais l'interpr6tation du MUAC du point de vue de l'etat nutritionnel, ou en tant que facteur causal de trou- bles fonctionnels, exige l'utilisation de donn6es de reference telles que celles qui sont pr6sent6es ici. L'utilisation du MUAC a des r6percussions importantes sur l'6valuation rapide du bilan nutri- tionnel, car cet indicateur est plus facile a mesurer que la taille et le poids. De plus, dans les cas ou il n'existe pas de donnees fiables sur 1'age, il est possible d'utiliser le MUAC/taille comme indicateur. L'OMS et les Centers for Disease Control and Prevention (Etats-Unis d'Am6rique) 6tablissent actuellement des donn6es de ref6rence pour le rap- port MUAC/taille dans cette optique. References 1. Gayle HD et al. Arm circumference versus weight-for- height in nutritional assessment: are the findings com- WHO Bulletin OMS. Vol 75 1997 17 M. de Onis et al. parable? Journal of tropical pediatrics, 1988, 34: 213- 217. 2. Trowbridge FL, Staeling N. Sensitivity and specificity of arm circumference indicators in identifying mal- nourished children. American journal of clinical nutri- tion, 1980, 33: 687-696. 3. Chen LC, Chowdhury A, Huffman SL. Anthropo- metric assessment of energy-protein malnutrition and subsequent risk of mortality among preschool aged children. American journal of clinical nutrition, 1980, 33: 1836-1845. 4. Trowbridge FL, Sommer A. Nutritional anthropo- metry and mortality risk. American journal of clinical nutrition, 1981, 34: 2591-2592. 5. Briend A, Wojtyniak B, Rowlands MG. Arm circum- ference and other factors in children at high risk of death in rural Bangladesh. Lancet, 1987, ii: 725- 728. 6. Vella V et al. Anthropometry and childhood mortality in Northwest and Southwest Uganda. American jour- nal of public health, 1993, 83: 1616-1618. 7. Jelliffe DB. The assessment of the nutritional status of the community. Geneva, World Health Organization, 1966 (WHO Monograph Series, No. 53). 8. Jelliffe DB, Jelliffe EFP. The arm circumference as a public health index of protein-calorie malnutrition in early childhood. Journal of tropical pediatrics, 1969, 15: 177-260. 9. Hall G, Chowdhury S, Bloem M. Use of mid-upper- arm circumference Z-scores in nutritional assess- ment. Lancet, 1993, 341: 1481. 10. Van den Broeck J, Eeckels R, Vuylsteke J. Influ- ence of nutritional status on child mortality in rural Zaire. Lancet, 1993, 341: 1491-1495. 11. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. Geneva, World Health Organization, 1995 (WHO Technical Report Series, No. 854). 12. de Onis M, Habicht JP. Anthropometric reference data for international use: recommendations from a World Health Organization Expert Committee. American journal of clinical nutrition, 1996, 64: 650- 658. 13. Plan and operation of the Health and Nutrition Exami- nation Survey. United States: 1971-1973. Rockville, MD, USA, National Center for Health Statistics, 1973 (Vital health statistics, Series 1, No. 1 Oa). 14. McDowell A et al. Plan and operation of the second National Health and Nutrition Exami-nation Survey. United States: 1976-1980. Rockville, MD, USA, Na- tional Center for Health Statistics, 1981 (Vital health statistics, Series 1, No. 15). 15. Bern C, Nathanail L. Is mid-upper-arm circumference a useful tool for screening in emergency settings? Lancet, 1995, 345: 631-633. 16. Sommer A, Loewenstein MS. Nutritional status and mortality: a prospective validation of the QUAC stick. American journal of clinical nutrition, 1975, 28: 287- 292. 17. Oshaug A et al. Problems and pitfalls in the use of estimated age in anthropometric measurements of children from 6 to 60 months of age: a case from Mali. Journal of nutrition 1994, 124: 636-644. 18 WHO Bulletin OMS. Vol 75 1997