A. Equations for predicting BMR from weight (kg) and height (m)
|(kcalth in parentheses)|
|Men||10–18||69.4W + 322.2H + 2 392||0.89||418|
|(16.6W + 77H + 572)||(100)|
|18–30||64.4W - 113.0H + 3 000||0.65||632|
|(15.4W - 27H + 717)||(151)|
|30–60||47.2W + 66.9H + 3 769||0.60||686|
|(11.3W + 16H + 901)||(164)|
|> 60||36.8W + 4 719.5H - 4 481||0.84||552|
|(8.8W + 1 128H - 1 071)||(132)|
|Women||10–18||30.9W + 2 016.6H + 907||0.77||473|
|(7.4W + 482H + 217)||(113)|
|18–30||55.6W + 1 397.4H + 146||0.73||502|
|(13.3W + 334H + 35)||(120)|
|30–60||36.4W - 104.6H + 3 619||0.70||452|
|(8.7W - 25H + 865)||(108)|
|> 60||38.5W + 2 665.2H - 1 264||0.82||393|
|(9.2W + 637H - 302)||(94)|
ar = correlation coefficient.
bRSD = residual standard deviation.
The values for r and RSD are very close to those obtained using the equations predicting from weight only (Table 5), showing that inclusion of height does not significantly improve the precision of prediction.
B. Comparison of values of BMR in MJ (kcalth) predicted from weight only (I) (Table 6) or from weight and height (II)
|Age range||Wta||Htb||BMRc||% difference in|
predicted BMR for 5-cm
difference in heightd
|Men||10–18b||45||1.58||6.02||(1 440)||6.02||(1 440)||0.3|
|18–30||65||1.72||7.01||(1 675)||6.99||(1 670)||0.1|
|30–60||65||1.72||6.84||(1 635)||6.97||(1 665)||0.05|
|> 60||65||1.72||5.71||(1 365)||6.02||(1 440)||3.9|
|Women||10–18b||44||1.54||5.35||(1 280)||5.26||(1 285)||1.9|
|18–30||55||1.62||5.46||(1 305)||5.48||(1 310)||1.3|
|30–60||55||1.62||5.48||(1 310)||5.46||(1 305)||0.1|
|> 60||55||1.62||4.91||(1 175)||5.16||(1 235)||2.6|
a Subjects of median weight for height.
b Children aged 13–14 years, of median weight and height for age.
c The two sets of equations give good absolute agreement, except in the elderly.
d The effect of height on predicted BMR is negligible except in teenage girls and the elderly.
There is a significant effect of height (at a fixed weight) on the predicted BMR in children, but the data are not given because the BMR has not been used for estimating energy expenditure in children below 10 years.
A. Weight (kg) for age of children a
|- 2SD||Median||+ 2SD||- 2SD||Median||+ 2SD|
a Figures taken from United States Public Health Service, Health Resources Administration NCHS growth charts. Rockville, MD, 1976 (HRA 76–1120, 25, 3).
Full details on weight for age, height for age, and weight for height are given in the original publication as reproduced by WHO (Measuring change in nutritional status. Geneva, World Health Organization, 1983).
B. Median weight (kg) for age and height of adolescent boys and girls
1. Adolescent boys a
a Data from Baldwin (1925) as reproduced by Jelliffe, D. B. The assessment of the nutritional status of the community, Geneva, World Health Organization, 1966.The range of variation in weights at a given age is much greater than the range of variations at a given height, this reflects the variable timing of the pubertal growth spurt.
2. Adolescent girls
C. The average and the range of desirable weights for height in adults a
|Height without shoes||Men||Women|
|(m)||Weight without clothes (kg)||Weight without clothes (kg)|
a Source: Bray, G.A., ed., Obesity in America. Proceedings of the 2nd Fogarty International Center Conference on Obesity, Report No. 79. Washington, DC, Department of Health, Education and Welfare, 1979. Based on: Mortality among overweight men and women, Statistical Bulletin 41. New York, Metropolitan Life Insurance Co., 1960.
b Body mass index (BMI) = Wt (kg)/Ht2(m).
(expressed as a ratio to the BMR)
|Sex||Body weight||Age||Speed of walking (m per min)|
|Range of ratios||2.18–2.58||2.77–3.29||(3.54–4.21)||(4.52–5.37)|
The ratio of the gross energy cost of level walking to the BMR was calculated from an earlier analysis.a Gross energy varied with sex, weight, and speed but not with age.
The BMR estimates were derived from those given in Table 5 and varied with sex, weight, and age.
a McDonald, I. Nutrition abstracts and reviews, 31: 739–762 (1961).
|Infants, recovering from malnutrition||(4)||5.55||23.2|
|Adults, recovering from anorexia nervosa||(9)||6.4||26.7|
|Adults, intentional overfeeding||(10)|
a Calculated as 80 000 kcalth (335 MJ) stored (see section 6.2.1) for 12.5 kg of weight gain.
Preliminary assessment of data (expressed in terms of the basal metabolic rate multiplied by a metabolic constant b)
|A.||Males - Developed and developing societies|
|Sleeping||1.0||(i.e.,BMR × 1.0)|
|singing and dancing||3.2|
|making bows and arrows, bags, etc.||2.7|
|“around” or strolling||2.5|
|at normal pace||3.2|
|with 10-kg load||3.5|
|at normal pace||5.7|
|at normal pace with 10-kg load||6.7|
|at normal pace||3.1|
|carving plates, combs, etc.||2.1|
|moderate cleaning (polishing, window cleaning, chopping firewood)||3.7|
|sitting at desk||1.3|
|standing and moving around||1.6|
|motor vehicle repairs||3.6|
|machine tool industry||3.1|
|decorating and painting||2.8|
|milking cows by hand||2.9|
|collecting and spreading manure||5.2|
sorghum harvest-cutting ears
uprooting sweet potatoes
kneeling sorting sweet potatoes
|lifting grain sacks for weighing||3.7|
|loading sacks on lorry||7.4|
|clearing ground (depending on type of land)||2.9–7.9|
|tying fence posts||2.7|
|splitting wood for posts||4.2|
|digging holes for posts||5.0|
|cutting grass with machete||4.7|
|digging irrigation channels||5.5|
|Hunting and fishing|
|fishing from canoe||2.2|
|fishing with line||2.1|
|fishing with spear||2.6|
|felling with axe||7.5|
|trimming branches off trees||7.3|
|making mud bricks - squatting||3.0|
|digging earth to make mud||5.7|
|weaving bamboo wall||2.9|
|cutting palm tree trunks||4.1|
|collecting (including climbing trees)||4.6|
|putting in bags||4.0|
|working with pick||6.0|
|erecting roof supports||4.9|
normal and low-level flying
|sedentary (playing cards, etc.)||2.2|
|light (billiards, bowls, cricket, golf, sailing, etc.)||2.2–4.4|
|moderate (dancing, swimming, tennis, etc.)||4.4–6.6|
|heavy (football, athletics, jogging, rowing, etc.)||6.6+|
|Sleeping||1.0||(i.e., BMR × 1.0)|
|sewing pandanus mat||1.5|
|weaving carrying bag||1.5|
|“around” or strolling||2.4|
|at normal pace||3.4|
|uphill:||at normal pace||4.6|
|at normal pace||3.0|
|moderate cleaning (polishing, window cleaning, etc.)||3.7|
|fetching water from well||4.1|
|chopping wood with machete||4.3|
|Food preparation and cooking|
|collecting leaves for flavouring||1.9|
|catching fish by hand||3.9|
|grinding grain on millstone||3.8|
|removing beans from pod||1.5|
|breaking nuts (like peanuts)||1.9|
|peeling sweet potato||1.4|
|loading earth oven with food||2.6|
|machine tool industry||2.7|
|digging holes for planting||4.3|
|planting root crops||3.9|
|cutting grass with machete||5.0|
|harvesting root crops||3.1|
|winnowing corn or rice||1.7|
|cutting fruit from tree||3.4|
|sedentary (playing cards, etc.)||2.1|
|light||cf. male categories||2.1–4.2|
b These values apply only as approximate mean values for the time actually working at the relevant tasks,and not to the total day's shift: e.g., a labourer might be able to work for less than half of his 7- or 8-hour working shift, and the remainder would be more or less rest time.
b These values apply only as approximate mean values for the time actually working at the relevant tasks,and not to the total day's shift: e.g., a worker might be able to work for less than half of his 7- or 8-hour working shift, and the remainder would be more or less rest time.
a The data in this annex were assembled by Professor J.V.G.A. Durnin, Institute of Physiology, University of Glasgow, Scotland.
b For example, if an individual's BMR is 1.08 kcalth/min (4.51 KJ/min) and the energy cost for a task is 3.24 kcalth/min (13.55 KJ/min) the metabolic constant would be 3.24 divided by 1.08 = 3.0 (13.55 divided by 4.51 = 3.0).
|(for N loss/day)||(with numbers observed)|
|Young infants||mg||40–250||(3, 4)|
|Infants 1 year||mg/kg||7.8±2.9 (12)||(5)|
|Boys 1.5 years||mg/kg||8–12 (4)||(6)|
|Children 7.5–9.5 years||mg/kg||7–11 (27)||(7, 8)|
|Hair and nails|
|Mature women||mg/dayd||43±24 (6)||(11)|
|Hormonal contraceptives (oral||mg/dayd||20||(12)|
|IUDs - plastic or copper||mg/dayd||57–104||(13)|
|Semen and fluids||mg/ejaculation||37±10||(1)|
|Excreta rests on tissue|
a Adults unless otherwise specified.
b Temperate conditions, light activity. Increases with heat and physical activity. See text.
c Inoue, G. & Fujita, Y. Unpublished data, 1971.
d Averaged over a 28-day cycle.
|BMR/dayc||1 215||1 299||1 367||1 474||1 572||1 666||1 748||1 789|
|5 084||5 435||5 720||6 167||6 577||6 971||7 314||7 485|
|Calculation of energy expenditure|
|BMR||24 h||24 h||24 h||24 h||24 h||24 h||24 h||24 h|
|1 215||1 299||1 367||1 474||1 572||1 666||1 748||1 789|
|5 084||5 435||5 720||6 167||6 577||6 971||7 314||7 485|
|School (+ 0.6 BMR)||4 h||5 h||5 h||5 h||6 h||6 h||6 h||6 h|
|508||679||715||771||987||1 046||1 097||1 123|
|Light activity (+ 0.6 BMR)||4 h||4 h||5 h||6 h||7 h||7 h||7 h||7 h|
|508||544||715||925||1 151||1 220||1 280||1 310|
|Moderate activity||6.5 h||5.5 h||4.5 h||3.5 h||2.5 h||2.5 h||2.5 h||2.5 h|
|( + 1.5 BMR)||494||466||384||332||246||260||273||280|
|2 065||1 868||1 609||1 349||1 028||1 089||1 143||1 170|
|High activity (+ 6.0 BMR)||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h|
|Total daily energy||2 140||2 244||2 314||2 445||2 592||2 697||2 801||2 867|
|expenditure||8953||9388||9681||10 230||10 847||11 283||11 721||11 997|
|Daily energy expenditure/||66.5||60.6||56.6||52.0||49.3||47.0||44.7||44.1|
|kg body weight||278.0||253.7||236.7||217.7||206.1||195.0||186.9||184.6|
|BMR/dayc||1 157||1 218||1 282||1 341||1 373||1 393||1 405||1 410|
|4 841||5 096||5 364||5 611||5 745||5 828||5 879||5 899|
|Calculation of energy expenditure|
|BMR||24 h||24 h||24 h||24 h||24 h||24 h||24 h||24 h|
|1 157||1 218||1 282||1 341||1 373||1 393||1 405||1 410|
|4 841||5 096||5 364||5 611||5 745||5 828||5 879||5 899|
|School (+0.5 BMR)||4 h||5 h||5 h||5 h||6 h||6 h||6 h||6 h|
|Light activity (+0.5 BMR)||4 h||4 h||5 h||6 h||7 h||7 h||7 h||7 h|
|Moderate activity||6.5 h||5.5 h||4.5 h||3.5 h||2.5 h||2.5 h||2.5 h||2.5 h|
|1 572||1 402||1 205||983||719||729||734||738|
|High activity (+5.0 BMR)||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h||0.5 h|
|Total daily energy||1 910||1 982||2 054||2 117||2158||2140||2133||2142|
|Daily energy expenditure/||56.7||51.2||46.7||43.4||42.0||40.4||39.5||39.4|
|kg body weight||237.2||214.3||195.3||181.5||175.7||169.0||165.3||164.7|
a The figures in italics give the daily duration of the activity in question; the balance, up to 24 h, is made up by the period of sleep (1.0 BMR). The figures in bold type give the amount of energy in kcalth and those in ordinary type(unless otherwise stated) the amount of energy in kJ.
b In calculating the total daily energy expenditure, the BMR is applied to the whole 24 h, additional amounts being added for the various specified types of activity, e.g., for boys aged 10.5 years, + 0.6 BMR for 4 h of light activity.
c BMR (kcalth/day): for boys = 17.5 W + 651; for girls = 12.2 W + 746.
d The energy expenditure on growth was taken as 8 kJ/kg of body weight at 10–15 years; 4 kJ/kg at 15 years;and 2 kJ/kg at 16–18 years.
In section 9 it was suggested that catch-up growth requires a relatively greater increase in the supply of protein than of energy. The expected rate of catch-up in weight at any given level of protein intake can be calculated from a simple model if it is assumed:
For children, the levels shown in the examples (Fig. 2 of this Annex) correspond to one or other of the strategies set out in Table 52.
If I = protein intake (g/day);
F = efficiency of utilization of protein for tissue deposition (taken as 0.7 — see section 6.3.2);
A = grams of tissue deposited per gram of protein retained (taken as 7.0, corresponding to a protein content of 14.3%);
M = maintenance requirement, grams protein/gram body weight;
Wt = weight (grams) at time t;
Then dW/dt = AF(I - MW) and
Wt = I/M + Cexp(-pt)
where C is the constant of integration, and p = A × F × M.
This expression generates the curves shown in Fig. 1 and 2.
Fig. 1. Expected rate of weight gain of an adult, height 1.78 m, median Wt for Ht 70 kg (BMI 22), actual weight 50 kg (BMI 15.7)
• Protein intake based on median Wt for Ht = 0.75 × 70 g/day = 52.5 g/day.
• The dotted line represents the lower level of acceptable Wt for Ht (BMI 19).
• The curve shows that it takes 4 months to enter the zone of acceptable weight, and 10 months to reach median Wt for Ht. The curve eventually reaches a weight of more than 70 kg because the intake represents the safe level, whereas the value used for the maintenance requirement is the average (100 mg N/kg per day).
Fig. 2. Expected rate of weight gain of a child aged 2 years, initial weight 9 kg, height/age 1 year, at 3 levels of protein intake (see Table 51)
Curve C represents the approach recommended by the 1977 informal consultation.1 If no further setbacks occur, satisfactory catch-up would be achieved in 5–6 months.
An example, for the conditions illustrated by Curve A of Fig. 2, would be:
At t = 0, W = 9 × 103 g
I = 10.35 g/day
M = 0.69 × 10-3 grams/gram body weight/day.
Therefore, I/M = 15 × 103 g. The exponential term = 1, therefore, C = -6 × 103 g.
1 World Health Organization. Protein and energy requirements: a joint FAO/WHO memorandum. Bulletin of the World Health Organization, 57: 65–79 (1979).
At infinite time W = I/M = 15 × 103 g. This is the limit to which the weight tends at a fixed protein intake. For intermediate times the value of p, in the given conditions, is 7 × 0.7 × 0.69 × 10-3 = 0.0034/day.
A. Derivation of reference PE ratio, individual diets
The following equation1 will provide an estimate of the PE ratio that ensures, with whatever probability is desired, that a diet with the calculated PE ratio will meet or exceed the actual protein requirements on the condition that enough is consumed to meet the energy requirements of the randomly selected individual. For explanation and comment on interpretation, see section 10.
Rα is the value of the PE ratio requirement that would be expected to be exceeded
by a certain proportion (α) of individuals (changing α alters the probability of
adequacy or inadequacy of the ratio for the random individual).
Zα is the standardized normal deviation above which α of the distribution lies (e.g., Z.025 = 1.96).
E is the average energy requirement for the specified class of individual (specified by age, weight, activity, etc.).
P is the average protein requirement for the specified class of individual, expressed as energy equivalents.
SE is the standard deviation of energy requirements.
SP is the standard deviation of protein requirements.
r is the correlation between energy and protein requirements among individuals in the specified class.
(Note that the equation is written in two parts only for convenience).
1 Derived from the equations presented in: Beaton, G.H. & Swiss, L.D. Evaluation of the nutritional quality of food supplies: prediction of “desirable” or “safe” protein : calorie ratios. American journal of clinical nutrition, 27: 485–504 (1974). (Based on the arguments and approach of Lorstad, M. FAO Nutritional Newsletter, 9 (No. 1): 18 (1971).
B. Derivation of variance for protein requirement per person per day: estimation of the variance of a product.
The coefficient of variation of protein requirement is 12.5% when requirement is expressed as g/kg per day. If weight is omitted from this expression and requirement is expressed as g/day referring to a group of persons with differing weights, the variance and coefficient of variation will increase since there are now two sources of variation —requirement per unit weight and weight. Statistical estimates of the new variance can be obtained as outlined below.
If weight and requirement are not correlated, and
R = [RW × W] + [r × V(W) × V(RW], if the correlation between them is r, given a knowledge of
W mean weight of the group
V(W) variance of the weight within the group
RW mean requirement per unit body weight
V(RW) variance of the requirement per unit body weight (in the case of protein this would be 12.5% of the mean requirement)
then R, mean requirement per day, may be calculated as R = RW × W.
Further, V(R) variance of the requirement per day, may be calculated by the following equations:
Some caution must be exercised in the use and interpretation of V(R). First, although equation (i) is an exact equation given no correlation, equation (ii) is an approximation only.1 Perhaps more important, it is unlikely that the distribution of a product of two variables will be Gaussian. Therefore the mean ± a constant times the standard deviation may not be readily interpretable as covering a fixed percentage of the population, as in the probability approach described in section 11. (As presented, that approach assumes that requirement has an essentially normal distribution). However, on an empirical basis it is found that if weight and requirement per unit weight both have distributions close to normal, and if the variances are small in comparison to the means (low CVs) then the distribution of the product, requirement per person per day, gives a reasonable approximation of the Gaussian distribution and may be used in the probability approach. The shapes of the original distributions are important. If actual weights are known, it would be much better to describe intakes and requirements per unit body weight and to make interpretive judgements on that base.
1 For a more exact expression, see Mood, A.M. et al. Introduction to the theory of statistics, 3rd ed. New York, McGraw-Hill, 1973.
Two examples are offered, assuming a Gaussian distribution and no correlation between requirement per kg and body weight. Consider adult men with an average body weight of 70 kg and an average protein requirement of 0.6 g/kg per day. The CV of requirement in this unit is 12.5%. If the CV of body weight is 10%, then the mean protein requirement would be 42 g per day, with a CV of about 16%. The safe level of protein intake would be about 55 g/day rather than the 52.5 g/day that might have been assumed. If the CV of body weight were 15%, then the CV of requirement per person per day would increase to about 19.5% and the safe level of intake would increase to about 58 g/day. To generate probability statements, the intervals shown in Table 54 would have to be adjusted to reflect the new CV estimates.
In working with children, the statistical issues are somewhat more complex since the protein requirement per kg body weight changes with age. If all children in the interest group were the same age, then the approach would be the same as described above for adults. However, if different ages are included in the group then consideration would have to be given to including still another component of variance (age) and to recognition that, across age, there would be some relationship between mean body weight and protein requirement per kg. In older children it is likely that these effects could be ignored and only the distribution of weights need be considered. In young children, when protein requirements per kg change rapidly with age, the effects of age would have to be considered.
C. Some considerations relevant to the impact of variability of activity on the estimated variability of energy requirement
The present report adopts a factorial approach to the estimation of energy requirements. That is, for adults, total energy requirement is estimated as the sum of energy needed for BMR and the additional energy needed for specific activities. BMR is predictable from a knowledge of the age, sex, and body size of the individual (Table 5 and Annex 1). The additional costs of specific activities are estimated from a knowledge of the time spent in various activities and the estimated energy cost of those activities (Annex 5). The report suggests that the variance of BMR has a CV of about 12.5% and that this may be a reasonable descriptor of the variability of energy requirement of any specific activity expressed as a multiple of BMR. Thus, for the individual for whom a record of actual activities is available, it is reasonable to assume that the CV attached to the total energy requirement estimate is about 12.5%.
However, at present there are limited data describing the profiles of activities for different individuals. For that reason, there are not available good estimates of the variability that should be associated with groups of individuals performing different profiles of activity -or the variance that should be attached to any assumption of an average energy expenditure for activity. Below, the potential impact of this gap in present information is discussed.
The report presents examples of estimated total energy expenditures associated with various types of occupation (Section 6.1, Tables 10–13). These suggest that total mean requirements may range between 1.5 and 2.1 BMR or that the additional cost of activities above basal metabolic rate may be 0.5 to 1.1 BMR (group means). Using this as an extreme example of the range that might exist in a population group, some estimates can be made for the worst case situation:
where is the average total energy expenditure for a population in which the average additional cost of activity is 0.75 BMR and it is assumed that:
Then the variance of E estimated as the sum of the variances of the two terms of the equation, again assuming no correlation, would be:
and the coefficient of variation of total energy requirement would be:
In this worst-case situation, where it is assumed that the CV of the additional costs of activity is 50% of the average additional cost, and in which a fairly high average additional cost is assumed, the predicted impact would be to raise the coefficient of variation from 12.5% to about 23%.1 A variability estimate of this order of magnitude seems consistent with information in the literature although direct comparison is not justified. The observed variance would be affected by the actual range of activities involved and by the range of weights of the individuals performing them.
This may be a measure of the potential impact of having to assume an average profile of activity rather than having detailed information about the individuals.
As for studies of food intake, the activity descriptors must describe patterns of “usual activity” persisting over moderate periods of time. If information is available only for activity (and energy expenditure) on a single day, there is likely to be a major error in the description of usual energy needs attributable to intraindividual variation (see discussion of time-frame of requirement and intake, section 11.3).
1 If it is assumed that there is a correlation between basal metabolism (B) and the additional need for activity (A) then the correct equation for the estimation of the variance of the sum would be:
V(R) = V(B) + V(A) + 2 Corr(B,A) × SD(B) × SD(A)
Such an assumption would be reasonable if it is believed that the relative efficiency of energy metabolism is comparable in the maintenance and activity components of total requirement. (This may be taken as implicit in the approach used to describe energy requirement as multiples of BMR but there is no direct experimental evidence to support it). Perfect correlation (r = 1) would raise the CV to 30.4%.
Dr T. Atinmo, Department of Human Nutrition, University of Ibadan, Ibadan, Nigeria
Professor G.H. Beaton, Professor and Chairman, Department of Nutrition and Food Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
Dr D. Calloway, Professor of Nutrition and Chairman, Department of Nutrition Sciences, University of California, Berkeley, CA, USA
Dr Chen Xue-cun, Institute of Health, Chinese Academy of Medical Sciences, Beijing, China
Professor G. Debry, Department of Nutrition and Metabolic Disorders, University of Nancy, Nancy, France
Professor J. Durnin, Department of Physiology, University of Glasgow, Glasgow, Scotland
Dr A. Ferro-Luzzi, National Institute of Nutrition, Rome, Italy
Dr G.B. Forbes, Professor of Pediatrics, The University of Rochester Medical Center, Rochester, NY, USA
Dr L. Garby, Department of Physiology, Odense University, Odense, Denmark
Dr G. Inoue, Department of Nutrition, School of Medicine, Tokushima City, Tokushima Prefecture, Japan
Dr H. Munro, Human Nutrition Research Centre on Aging at Tuft's University, Boston, MA, USA (Rapporteur)
Dr I. Ozalp, Hacettepe University, Department of Biochemistry, Faculty of Medicine, Haceteppe, Ankara, Turkey
Dr J. Parizkova, Research Institute FTVS, Charles University, Prague, Czechoslovakia
Dr S.G. Srikantia, Jayalakshmipuram, Mysore, India
Dr Kraisid Tontisirin, Institute of Nutrition, c/o Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
Dr B. Torún, Chief, Division of Biology and Human Nutrition, Institute of Nutrition of Central America and Panama (INCAP), Guatemala, Guatemala
Dr R. Uauy, Institute of Nutrition and Food Technology (INTA), University of Chile, Santiago, Chile
Professor J.C. Waterlow, Professor of Human Nutrition, London School of Hygiene and Tropical Medicine, London, England (Chairman)
Dr R.C. Whitehead, Director, MRC Dunn Nutrition Unit, Dunn Nutritional Laboratory, Cambridge, England
Dr V. Young, Department of Nutrition and Food Science, Massachusetts Institute of Technology, Cambridge, MA, USA
Dr H.J.L. Burgess, Secretary, ACC Sub-Committee on Nutrition, Food and Agriculture Organization of the United Nations, Rome, Italy
Professor Dr F. Fidanza, Institute of Nutrition and Food Science, Perugia, Italy
Dr M. Béhar, Chief, Nutrition, WHO, Geneva, Switzerland
Dr E.M. DeMaeyer, Medical Officer, Nutrition, WHO, Geneva, Switzerland (Joint Secretary)
Dr P. François, Nutrition Officer, Nutrition Planning Assessment and Evaluation Service, FAO, Rome, Italy
Dr W. James, Assistant Director, Dunn Nutritional Laboratory, Cambridge, England (Temporary Adviser)
Dr W. Keller, Medical Officer, Nutrition, WHO, Geneva, Switzerland (Joint Secretary)
Dr P. Lunven, Chief, Nutrition Planning Assessment and Evaluation Service, FAO, Rome, Italy
Mr L. Naiken, Statistics Officer, Statistics Division, FAO, Rome, Italy
Dr C.L. Quance, Director, Statistics Division, FAO, Rome, Italy
Dr J. Périssé, Senior Officer, Nutrition Planning, Assessment and Evaluation Service, FAO, Rome, Italy (Joint Secretary)
Dr W.M. Rand, Research Coordinator UNU/WHP, Massachusetts Institute of Technology, Cambridge, MA, USA (Temporary Adviser)
Dr Z.I. Sabry, Director, Food Policy and Nutrition Division, FAO, Rome, Italy
Dr N. Scrimshaw, Senior Advisor, World Hunger Programme, UNU, Massachusetts Institute of Technology, Cambridge, MA, USA
Dr V. Valverde, Division of Human Development, Institute of Nutrition of Central America and Panama, Guatemala CA, Guatemala (Temporary Adviser)
Dr R. Weisell, Nutrition Officer, Nutrition Planning, Assessment and Evaluation Service, FAO, Rome, Italy
WORLD HEALTH ORGANIZATION TECHNICAL REPORT SERIES
|682||(1982) Bacterial and viral zoonoses|
|Report of a WHO Expert Committee with the participation of FAO (146 pages)||11.-|
|683||(1982) Evaluation of certain food additives and contaminants|
|Twenty-sixth report of the Joint FAO/WHO Expert Committee on Food Additives (51 pages)||5.-|
|684||(1983) Recommended health-based occupational exposure limits for selected vegetable dusts|
|Report of a WHO Study Group (78 pages)||6.-|
|685||(1983) The use of essential drugs|
|Report of a WHO Expert Committee (46 pages)||4.-|
|686||(1983) Primary prevention of essential hypertension|
|Report of a WHO Scientific Group (40 pages)||4.-|
|687||(1983) WHO Expert Committee on Biological Standardization|
|Thirty-third report (184 pages)||13.-|
|688||(1983) Integrated vector control|
|Seventh report of the WHO Expert Committee on Vector Biology and Control (72 pages)||6.-|
|689||(1983) A rational approach to radiodiagnostic investigations|
|Report of a WHO Scientific Group on the Indications for and Limitations of Major X-Ray Diagnostic Investigations (49 pages)||5.-|
|690||(1983) New approaches to health education in primary health care|
|Report of a WHO Expert Committee (44 pages)||4.-|
|691||(1983) Prevention of liver cancer|
|Report of a WHO Meeting (30 pages)||4.-|
|692||(1983) Gestational trophoblastic diseases|
|Report of a WHO Scientific Group (81 pages)||7.-|
|693||(1983) Viral vaccines and antiviral drugs|
|Report of a WHO Scientific Group (72 pages)||6.-|
|694||(1983) Research for the reorientation of national health systems|
|Report of a WHO Study Group (71 pages)||7.-|
|695||(1983) Smoking control strategies in developing countries|
|Report of a WHO Expert Committee (92 pages)||8.-|
|696||(1983) Evaluation of certain food additives and contaminants|
|Twenty-seventh report of the Joint FAO/WHO Expert Committee on Food Additives (47 pages)||5.-|
|Report of a WHO Expert Committee (68 pages)||7.-|
|698||(1984) Mental health care in developing countries: a critical appraisal of research findings|
|Report of a WHO Study Group (59 pages)||6.-|
|699||(1984) Chemistry and specifications of pesticides|
|Eighth report of the WHO Expert Committee on Vector Biology and Control (46 pages)||5.-|
|700||(1984) WHO Expert Committee on Biological Standardization|
|Thirty-fourth report (75 pages)||7.-|
|701||(1984) The leishmaniases|
|Report of a WHO Expert Committee (140 pages)||11.-|
|702||(1984) Lymphatic filariasis|
|Fourth report of the WHO Expert Committee on Filariasis (112 pages)||9.-|
|703||(1984) Road traffic accidents in developing countries|
|Report of a WHO Meeting (36 pages)||5.-|
|704||(1984) WHO Expert Committee on Specifications for Pharmaceutical Preparations|
|Twenty-ninth report (54 pages)||6.-|
|705||(1984) The role of food safety in health and development|
|Report of a Joint FAO/WHO Expert Committee on Food Safety (79 pages)||7.-|
|706||(1984) The uses of epidemiology in the study of the elderly|
|Report of a WHO Scientific Group on the Epidemiology of Aging (84 pages)||8.-|
|707||(1984) Recommended health-based occupational exposure limits for respiratory irritants|
|Report of a WHO Study Group (154 pages)||14.-|
|708||(1984) Education and training of nurse teachers and managers with special regard to primary health care|
|Report of a WHO Expert Committee (54 pages)||6.-|
|709||(1984) WHO Expert Committee on Rabies|
|Seventh report (104 pages)||9.-|
|710||(1984) Evaluation of certain food additives and contaminants|
|Twenty-eighth report of the Joint FAO/WHO Expert Committee on Food Additives (44 pages)||5.-|
|711||(1984) Advances in malaria chemotherapy|
|Report of a WHO Scientific Group (218 pages)||20.-|
|712||(1984) Malaria control as part of primary health care|
|Report of a WHO Study Group (73 pages)||8.-|
|713||(1984) Prevention methods and programmes for oral diseases|
|Report of a WHO Expert Committee (46 pages)||5.-|
|714||(1985) Identification and control of work-related diseases|
|Report of a WHO Expert Committee (71 pages)||7.-|
|715||(1985) Blood pressure studies in children|
|Report of a WHO Study Group (36 pages)||5.-|
|716||(1985) Epidemiology of leprosy in relation to control|
|Report of a WHO Study Group (60 pages)||6.-|
|717||(1985) Health manpower requirements for the achievement of health for all by the year 2000 through primary health care|
|Report of a WHO Expert Committee (92 pages)||8.-|
|718||(1985) Environmental pollution control in relation to development|
|Report of a WHO Expert Committee (63 pages)||6.-|
SELECTED WHO PUBLICATIONS OF RELATED INTEREST
|Beghin, I., Cap, M. & Dujardin, B. A guide to nutritional assessment. 1988 (80 pages)||14.-|
|Diet, nutrition, and the prevention of chronic diseases|
|Report of a WHO Study Group|
|WHO Technical Report Series, No. 797, 1990 (203 pages)||26.-|
|Akré, J. (ed.) Infant feeding. The physiological basis|
|Supplement to Vol. 67 of the Bulletin of the World Health Organization. 1990 (108 pages)||20.-|
|Lipton, M. & de Kadt, E. Agriculture-health linkages|
|WHO Offset Publication, No. 104, 1988 (111 pages)||17.-|
|Nutrition learning packages|
|1989 (vii + 170 pages)||30.-|
|Weaning - from breast milk to family food|
|1988 (36 pages)||9.-|
|Vitamin A supplements. A guide to their use in the treatment and prevention of vitamin A deficiency and xerophthalmia|
|1988 (24 pages)||8.-|
|Guidelines for training community health workers in nutrition, 2nd ed. 1986|
|(vii + 121 pages)||16.-|
|The quantity and quality of breast milk|
|Report on the WHO Collaborative Study on Breast-feeding. 1985|
|(viii + 148 pages)||17.-|
|Minor and trace elements in breast milk|
|Report of a Joint WHO/IAEA Collaborative Study. 1989 (xii + 159 pages)||30.-|
Further information on these and other World Health Organization publications can be obtained from Distribution and Sales, World Health Organization, 1211 Geneva 27, Switzerland.
* Prices in developing countries are 70% of those indicated here.