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close this bookThe Functional Significance of Low Body Mass Index (IDECG, 1992, 203 p.)
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close this folderIntroduction: the challenge of adult chronic energy deficiency
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View the documentIndices of chronic energy deficiency in adults
View the documentThe FAO initiative
View the documentA simplification in the approach to adult CED
View the documentThe use of BMI alone in CED diagnosis
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View the documentThe functional significance of modest reductions in BMI
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close this folderPopulation differences in body composition in relation to the body mass index
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View the documentBMI and body composition: theoretical considerations
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close this folderBody mass index: its relationship to basal metabolic rates and energy requirements
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View the documentNutritional anthropometric indices and their relationship to BMR
View the documentDo population groups in developing countries in the tropics have lower BMRs?
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View the documentChanges in body weights and stature and their influence on BMI and energy requirements
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close this folderLow body mass index, physical work capacity and physical activity levels
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View the documentWork capacity or 'stress'
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close this folderBody mass index and economic productivity
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View the documentEvidence of nutrition/productivity links
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close this folderMaternal body mass index: the functional significance during reproduction
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View the documentThe East Java Pregnancy Study (EJPS)
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close this folderMaternal body mass index and pregnancy outcome in the nutrition collaborative research support program
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View the documentThe Nutrition CRSP
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View the documentBMI and maternal weight gain
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View the documentAdditional analyses from the Mexico CRSP
View the documentMaternal BMI and size of the infant at birth
View the documentMaternal BMI and infant size during early lactation
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close this folderBody mass index and lactation performance
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View the documentBasic physiology of lactation
View the documentIs BMI a useful discriminator of lactation performance in terms of breast-milk quantity?
View the documentIs BMI a useful discriminator of lactation performance in terms of breast-milk quality?
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close this folderAssessing the linkages between low body mass index and morbidity in adults: evidence from four developing countries
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close this folderBody mass index and illness in rural Sarawak
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close this folderAn assessment of nutritional factors affecting the BMI of a population
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close this folderBody mass index: its relationship with food consumption and socioeconomic variables in Brazil
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View the document1. BMI of adults and food consumption: some methodological issues
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close this folderUse of body mass index in the assessment of adult nutritional status in Vietnam
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close this folderBody mass index: a measure of the nutritional status Indian populations
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close this folderIs body mass index sensitively related to socio-economic status and to economic adjustment? a case study from the Congo
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close this folderThe body mass index of Chinese adults in the 1980s*
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close this folderBody mass index values in the Cuban adult population
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close this folderBody mass index defines the risk of seasonal energy stress in the third world
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View the documentThe big-ecology of seasonality
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close this folderThe choice of cut-off point for distinguishing normal body weights from underweight or 'chronic energy deficiency' in adults
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View the documentOptimum population BMIs in men
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close this folderUse of BMI for monitoring and surveillance, practical issues
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close this folderAnalysing cross-sectional anthropometric data
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Methods

Subjects

The parents of the subjects selected for the sample of the second growth and development study (Berdasco et al., 1991) were the subjects of this survey. After cleaning the data, the total number of adults was 31 662, of whom 11912 were males and 19 750 were females. This difference in the numbers was probably due to the better attendance of mothers for their appointments.

Field work

The adults attended the measuring centres where they were weighed, and had their height, upper arm circumference, triceps and subscapular fat-folds measured. The survey was undertaken by eight measuring teams (two anthropometrists each) working simultaneously from May to December 1982. Individuals living in the country's 14 provinces were measured.

In order to assure the best possible quality in the primary data, anthropometrists were trained in the same measuring procedures utilized in the first national growth and development study (Jordan, 1979), namely, those recommended by UN International Biological Programme (Weiner & Laurie, 1969). The quality of the measurements was also guaranteed through technical supervision by the investigators, and two quality control sessions. In this way, a correct application of measuring techniques was assured and consequently, consistent and uniform measurements were obtained. The adults were measured without shoes and with the lightest clothing possible (underwear and trousers or skirt) from which their nude weight could be estimated as 1 kg less than the recorded weight.

Criteria to define urban or rural dwelling

The basic definitions of the 1981 Cuban Population and Housing Census were used (Comitstatal de Estadisticas, 1984).

Urban dwellings were categorized as:

(a) all places with a population of 2000 or more inhabitants;

(b) all places with a population of 500 to 2000 inhabitants with electricity and three or more facilities such as an aqueduct, paved streets, a sewerage system, medical services and an educational centre; or

(c) all places with a population of 200 to 500 inhabitants with electricity and all of the five facilities listed in (b).

All places with a population of less than 200 inhabitants were considered rural. This category also included places with a population between 200 and 2000 inhabitants and without the facilities available in urban places.

Classification criteria related to educational level

Adults were classified into the following four groups based on the last grade passed:

Group 1: 12th or over (high school graduates, university graduates or students)
Group 2: 9th to 11th (junior high school graduates)
Group 3: 6th to 8th (junior high school not completed; elementary school graduates)
Group 4: 6th grades (elementary school not completed).

Classification criteria related to the type of occupation

Occupation was recorded by questioning the subjects at an interview. They were then classified as follows:

Group 1: Production and service workers (moderate to intense physical activity)
Group 2: Professional, technical and administrative workers (light physical activity)
Group 3: Agricultural workers and small farm workers (mainly intense physical activity)
Group 4: Housewives and students.

Data processing

After cleaning the data, the following indices were calculated: weight/height, Rohrer, Sheldon, Ponderal, Benn (data not shown except for BMI). Correlations were established (Pearson's linear correlation coefficients) with weight, height, triceps fat-fold, subscapular fat-fold and the sum of both fat-folds.

Percentiles 3, 10, 25, 50, 75, 90, 97 of BMI were estimated for each year of age, by sex and by sex and place of dwelling i.e. urban and rural. Calculations were also made by 10 year groups categorized by sex and by sex and place of dwelling. Classification of the BMI was also carried out with the cut-off points proposed by James, Ferro-Luzzi & Waterlow (1988) for CED:

CED 3 BMI <16.0
CED 2 BMI 16.0-16.9
CED 1 BMI 17.0-18.4.

To this classification were added the following categories:

Underweight BMI 18.5-19.9
Normal BMI 20.0-24.9
Obese 1 BMI 25.0-29.9
Obese 2 BMI 30.0-39.9
Obese 3 BMI 240.0.

These groupings were used to classify BMI by 10 year intervals and by sex, sex and place of dwelling, sex and educational level, sex and occupation, sex and height (where the shortest < percentile 3, and the tallest were > percentile 97). Another classification was also made by percentiles of BMI and height by sex. Finally, the cut-off points of 'normal' BMI for the Cuban population were estimated by the percentage distribution of individuals by category of fat-folds in relation to the BMI groups and by sex and two age groups, 20-39 and 40-59 years. More detailed information of the data processing may be found elsewhere (Berdasco & Romero, 1992).