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Household dietary adequacy and individual nutrition status: Relationships and seasonal effects in a Sahelian community in Chad - France Begin, Mariam Alladoumgué, Korite Nandjingar, and Helene Delisle


A survey was conducted in a local area in the Sahelian zone of Chad to assess the relationship between household food consumption and individual nutrition status in two different seasons. Eighty households were surveyed during the non-harvest and harvest seasons. Household consumption was measured by weighing food items over two consecutive days.

The intake of energy, protein, and iron was adequate. The median intake of vitamin A was low, particularly in the non-harvest season, 48% of FAO/ WHO/UNU recommendations. Seasonal differences were detected only for vitamin A and iron. The mean child weight-for-height Z score and mean adult body mass index were lower at the harvest season (p< .05). Household vitamin A adequacy was a significant predictor of child weight for height and adult body mass index at the harvest season, even when energy adequacy was controlled for.

This study shows that the weak relationship between household dietary intake and individual nutrition status changed with the seasons, and that both provided complementary information on household nutrition. It is suggested that where household energy supply is not limiting, monitoring the consumption of major sources of vitamin A may help to identify malnourished households.


Household food consumption and child anthropometric status are among the indicators commonly used to assess dietary adequacy and nutrition status at the household level. Child growth indices are often the only indicators used to identify malnourished households, to target rural development projects, and to evaluate their impact. Such projects usually focus on agricultural production, household food supply, and consumption. However, these factors do not necessarily affect child nutrition, particularly when infection is also an important determinant of nutrition status.

The relationship between household dietary supply and the nutrition status of young children must be understood better with respect to energy as well as other nutrients. Findings in Thailand, Malaysia, and Sudan indicate that available dietary energy at the household level may not be a precise indicator of children's nutrition status [1]. In the Philippines, targeting households that did not meet their energy needs captured only a small proportion of malnourished children [2]. In Bangladesh, children and women suffer from moderate or severe malnutrition even in energy-sufficient households [3]. Because of intrahousehold food distribution and other factors, the diet and nutrition status of children do not necessarily reflect consumption at the household level. Furthermore, the effect of season on the relationship between household consumption and child nutrition is unclear. A study of this relationship is of practical relevance, as measuring individual dietary intake is cumbersome where household members usually eat from a common dish.

The relationship between household dietary supply and adult nutrition status also must be better understood. In Bangladesh, no direct relationship was found between household energy adequacy and individual nutrition status because of unequal food allocation within the family [3]. In Senegalese pastoralists, household energy deficit was accompanied by a decrease in subcutaneous fat and weight loss in adults during the wet season [4]. Studies of rural women in Ethiopia [5], Benin [6], and India [7] have suggested that changes in body weight and basal metabolic rate may be the main mechanisms of adaptation to seasonal fluctuations in individual energy intake. These studies revealed that diminished expenditure played only a minor role as an energy-sparing mechanism [8], thereby challenging previous reports [9, 10]. It should be considered that the studies mentioned related adult nutrition status to individual intake, but much less is known about its relationship with household intake.

The purpose of our study was to assess the relationship between household food consumption and the nutrition status of the individual at two seasons in a rural community of Chad. We focused on anthropometry of adults and of children under five years of age. More specifically, we addressed three questions:


A cross-sectional survey of food consumption and nutrition status was conducted in 1988 in a random sample of 225 households involved in wadi agriculture in three adjacent areas of Kanem Prefecture, in the Sahelian zone of Chad. Some of the results have been published [11]. This paper presents results from Mao, one of the three areas, where households were surveyed twice. The first survey took place at the end of the dry season, when the food supply becomes scarce. It was repeated seven months later, shortly after the rainy season, just as the harvest began. We refer to non-harvest and harvest seasons, although the periods are not sharply opposed.

Wadis are relatively fertile land depressions between sand dunes. Because of wadi cultivation, agricultural labour is carried on for most of the year (fig. 1). Men are usually responsible for the more physically demanding tasks of cereal production, such as ploughing and harvesting. Women are involved in planting and in irrigation and harvesting. They also dry vegetables for later consumption. A more detailed description of the area and of the households

involved in wadi agriculture can be found elsewhere [11].

FIG. 1. Agricultural calendar in the survey area. Mao, Chad

Only households with children under six years old were included in the study. Seventy-five households, comprising of 80 preschoolers and 131 adults for whom complete anthropometric data were recorded, participated in both survey rounds. Five additional households were surveyed only once, as they had moved out of the area before the harvest season. No households refused to participate in either survey.

Household food consumption and anthropometric data were collected at both seasons by the same five enumerators, under the supervision of two nutritionists. For two consecutive days, all foods prepared or consumed in the household were weighed using standard kitchen scales accurate to within 0.1 g. The age, sex, and relationship to the household head of all household members and guests taking part in meals were recorded. The body weight and height of all household members and guests were measured when possible.

Children up to five years of age were weighed in light clothing to the nearest 0.1 kg with a Salter spring scale. Adults were weighed to the nearest 0.5 kg with a Seca household scale. Children less than 24 months old were measured in a supine position and older children were measured standing, using a wooden board with a sliding rule; length or standing height was recorded to the nearest 0.1 cm.

The total amounts of all foods consumed in the household during the observation period were converted into energy and nutrient intake using the FAO food composition table for Africa [12] as the main source of data, with adjustments made to take into account the edible portions of the foods. Energy, macronutrients, iron, and vitamin A were computed, as it is recognized that these are generally the most limiting nutrients. Total energy intake was reduced by 5% to take into account the high fibre content of the average diet [13]. Total protein intake was adjusted down for digestibility, using 85%, as suggested for diets based on coarse grains [13].

Daily household consumption of food, energy, and nutrients was calculated per adult equivalent rather than per capita [11]. Adjustments were made for absent members, for visitors at family meals, and for food given away. There was no plate waste since leftovers were eaten later.

Individual energy and protein requirements were estimated according to the age- and sex-specific recommendations of the joint FAO/WHO/UNU expert consultation [13]. For children and adolescents, they were estimated on the basis of median acceptable body weight for median acceptable height rather than on actual weight and height, in order to allow for optimal growth. For children up to 11 years of age, the protein requirements had to be corrected for the low lysine content of the average diet. No adjustment was made for losses due to infection and parasites.

Adult energy requirements were computed from the predicted basal metabolic rate (BMR) based on the median acceptable body weight for actual height. Using actual body weight would underestimate the energy requirements of adults who are markedly underweight. These adult basal requirements were then multiplied by an incremental factor to allow for physical activity, using multipliers determined on the basis of random observations and recalls of daily activities. Activities were grouped into four categories of energy expenditure expressed in BMR multiples. Time spent in each activity category was used to obtain the daily average BMR multiplier [13]. The same multiplier was used for both seasons since activity patterns were comparable. The BMR factors so calculated [11] correspond to moderate activity for men and slightly above for women [13].

Adult protein requirements were similarly based on acceptable body weight. Energy and protein allowances for pregnancy and lactation were those recommended by FAO/WHO/UNU [13]. Safe levels of vitamin A intake and the median baseline iron requirement (for a diet with low iron bioavailability) were taken from FAD/WHO [14]. Vitamin A intake was expressed in retinol equivalents (RE), and adequacy of household diets to total intake as a percentage of the total requirement.

Child weight-for-height (WH) and height-for-age (HA) indices are expressed as Z scores of the Fels NCHS international reference population [15]. A WH Z score below -2 is indicative of wasting or acute protein-energy malnutrition (PEM). Chronic PEM or stunting was defined as an HA Z score less than - 3, which corresponds to severe stunting. We selected - 3 rather than - 2 as the cutoff point because the mean HA Z score was less than - 2 in the study population. One of the aims of cut-off points is to identify those most at risk [17]. Where malnutrition is widespread and resources for intervention are limited, the cut-off point can be lowered to select the most severe cases. Weight for age, which does not distinguish between acute and chronic PEM [16], is not considered here.

The body mass index (BMI = weight [kg]/height2 [m²]) was computed for men and non-pregnant women 18 years old or over. Lactating women were included except during the first six months of lactation. We used a BMI of 18.5 as the criterion of adult chronic energy deficiency [18].

Data were processed using SPSS-X*. The US center for Disease Control anthropometric software package (version 3.0,1987) was used for preliminary analysis of the anthropometric data of preschool children. Means of individual anthropometric indices and household dietary adequacy were compared using paired or unpaired t tests and one-way analysis of variance (with Scheffe's multiple range test) as appropriate. Rates of low household intake, low adult BMI, and childhood PEM were compared using the chi-square test or the McNemar test when referring to paired groups. The Pearson correlation coefficient was used to study the association between two continuous variables. All correlations with child HAZ scores were partial correlations controlling for age.

A natural-log transformation was applied to household vitamin A intake and adequacy. Because of the positive skewness of the vitamin A intake distribution, Spearman correlation coefficients were also calculated. Multiple regression analyses of child and adult anthropometric status on household energy and vitamin A adequacy were performed.

Results and discussion

Seasonal variation in food consumption and dietary adequacy

Mean household energy and nutrient intakes at the nonharvest and harvest seasons are presented in table 1. Household energy and macronutrient intake did not change markedly between the seasons; changes in the type of food consumed were mainly reflected in vitamin A and iron intake. The percentage of total energy provided by carbohydrate and fat was not significantly different between the seasons, but the contribution of protein to energy intake was higher at the non-harvest season.

Sahelian diets consist predominantly of cereals, which accounted for nearly 75% of the total dietary energy in Mao in both seasons. Millet, maize, and wheat were the main non-harvest season crops, and millet was the main cereal available at the beginning of harvest. As a result of the higher millet consumption in the harvest season, iron intake was significantly (p<.001) higher then since millet contains more iron than other cereals. Fats, mainly in the form of groundnut (peanut) oil, were the second energy-supplying food. Groundnut oil provided 9.8% of total dietary energy intake at non-harvest and 7.3% at harvest (p < .01). The oil is used to cook a soup-like sauce served with a thick cereal paste. Sugar provided 5.3% and 4.0% (p <.01) of the total dietary energy at non-harvest and harvest respectively. Sugar is used mainly in tea, which is an essential element in the diet of all Muslim people in the region, whether rich or poor. Legumes and tubers were only minor food items.

TABLE 1. Mean household energy and nutrient intakes per adult equivalent per day (N = 75)




P value

Energy (kcal)
Protein (g)
Fat (g)
Carbohydrate (g)

Iron (mg)
Total vitamin A (g RE)
Beta-carotene (pa)

2,779 ± 831
70 ± 22
54 ± 26
560 ± 164

44 ± 17
403 ± 271
5.8 ± 0.7
2,209 ± 1,594

2,978 ± 760
69 ± 18
52 ± 26
605 ± 157

62 ± 17
542 ± 319
6.1 ± 0.6
2.449 ± 1,489




Percentage of total calories from carbohydrate protein fat

77 ± 5
11 ± 2
16 ± 5

77 ± 6
9 ± 1
14 ± 5


principal values arc means + SD.

a. Paired t test.

*p < .01.

Meat was little consumed at either season. Cow's and goat's milk were the main sources of animal protein, accounting for 3.2% and 6.4% of total protein intake for each season respectively (p<.001). However, milk is usually consumed in small amounts and mainly by children. Thirtynine percent and 60% of the households consumed milk at non-harvest and harvest respectively. The higher figure partly explains the significantly higher seasonal intake of vitamin A. Milk accounted for 6.5% of total vitamin A intake at non-harvest and 15% at harvest (p < .001).

Overall in Africa, 87% of total vitamin A comes from carotenoids [19]. In our study, beta-carotene intake did not vary significantly between seasons, accounting for more than 80% of total vitamin A intake in both seasons. Vegetables, especially tomatoes, pimientos, wild green leaves, and sweet potatoes, accounted for 71% and 57% of total vitamin A intake at non-harvest and harvest respectively (p £ .001). Spirulina, a blue alga not included in the vegetable group, is an important local source of carotene. At non-harvest it was a more important source of vitamin A than milk (p < .001), whereas at harvest the two were equally important.

The household adequacy of energy, protein, vitamin A, and iron intake at each season is shown in table 2. No significant seasonal differences in energy and protein adequacy were observed. Overall, energy consumption could be considered adequate at both seasons; the mean energy intake was close to 100% of estimated requirements. Comparable figures have been reported for the same seasons in other Sahelian countries [20]. It can be seen in table 2 that more households tended to be short of energy at the non-harvest season. It is unlikely that they could successfully adapt to continued energy intakes below 90% of requirements while continuing to work actively [21]. Estimated protein requirements were generally met, although nearly 5% of the households were below 75% of the safe level of intake at both seasons.

Since the distribution of household vitamin A intake was positively skewed, both the median and the mean adequacy percentage are given in table 2. The median adequacy was 48% at non-harvest and increased somewhat at harvest (69%). The seasonal difference (using the log of the household adequacy percentage) was significant (p < .01). The WHO [22] classifies the Sahelian zone of Chad as a region where vitamin A deficiency is probably a significant public health problem. Our data provide further in direct evidence of this, since 61% and 42% (p < .01) of households were below 60% of the safe level of vitamin A intake at the non-harvest and harvest seasons respectively.

TABLE 2. Adequacy of household energy and nutrient intakes (N = 75)




p valuea

mean adequacy %
households < 90% (%)
households <60% (%)

mean adequacy %
households <75% (%)

Vitamin A
mean adequacy %
log of % safe level
households < 60% (%)

mean adequacy
households < 100% ( % )

92 ± 27

138 ± 43

60 ± 41
3.9 ± 0.7

178 ± 69

98 ± 26

138 ± 37

78 ± 46
4.2 ± 0.6

246 ± 76




.008* *

a. Paired tests on means McNemar test on percentage thresholds.

*p < 05. **p < .01.

The mean household iron adequacy was above the median basal requirement at both seasons, although it was significantly higher at harvest. Nevertheless, 11% of the households had inadequate iron intake at non-harvest. In contrast with vitamin A, a maximum safe level of iron intake has not been established because most diets would not normally provide that much 114]. As the median basal requirement does not allow for appreciable iron storage or for potential iron loss caused by parasitic infection, nothing can be said of the status of the study population on the sole basis of observed intake. Furthermore, tea consumption is high in the area, and, as it is known that tannins interfere with iron absorption [23], this may contribute to poor use of dietary iron.

Seasonal variation in children's and adults' nutrition status

Child and adult anthropometric indices are given in tables 35. The data for the two seasons pertain to the same individuals.

The rate of child wasting or severe stunting was high, reaching a total of around 50% of children at each season (table 3). Seasonal changes in children's nutrition status were significant, although WH and HA varied in opposite directions (table 4). Mean WH was significantly lower (p < .05) at harvest, that is, right after the rainy (lean) season, although the prevalence of wasting was not significantly increased. On the other hand, mean HA was significantly higher and the rate of stunting lower at harvest. Sex differences were not observed in any of the growth indices. Among Serere children of Senegal, growth rates for both height and weight were affected by seasonal food scarcity, although there was a time lag in the response of height [24]. Comparable findings have also been reported for Bangladesh [25, 26]. We might have observed an adverse seasonal effect on child HA if the measurements had been taken a few months later.

When the data are broken down by age group, at the time of the first survey (non-harvest) the children who were then under one year old had the highest mean HA and WH Z scores, but their scores had declined significantly seven months later. The scores of the children between 12 and 35 months old at the time of the first survey did not change significantly. Those of the children three years old and over went in opposite directions: their HA improved significantly at the harvest season, but the WH of two of the three age groups (36-47 months and 60-71 months) declined significantly. The observed decreases in both HA and WH in the youngest children may be due to the fact they had entered the difficult transition period from breast to family food, were more vulnerable because of rapid growth, and were more affected by the way their mothers struggled with the lean season prior to harvest. The opposing trends in HA and WH Z scores after three years of age tends to confirm that there is a time lag in the response of height to the lean season [24] but that this occurs mainly in older children. Our results are therefore consistent with an age-related effect of season on children's growth.

TABLE 3. Prevalence of malnourishment in children under six years old (N= 80)


Malnourished (%)

P value








Severely stunted




Wasted and stunted




a. McNemar test.
b. WH below -2.
c. HA below -3

*p < .05.

TABLE 4. Mean child HA and WH Z scores




Height for age

Height for height



p value



p valueb

























































a. Ages at time of first survey (nonharvest).
b Paired t tests.

*p < .05. **p < .01.


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