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In all, 253 households were studied in Campinas between May and June 1987.
The principal socio-economic characteristic of the sample is low income level. The average monthly income of the families was approximately 5.3 minimum wages. Table 2 shows the distribution of income using the minimum wage as a unit of measure. About 66% of the families earned a monthly income of five minimum wages or less, 22% had income between five and ten, and only 12% had income above ten.
TABLE 2. Distribution of sample households according to income level
|Monthly income (MW)||% of households||Cumulative: %|
MW = units of minimum wage.
In spite of their low income, the families reported that they possessed the basic amenities consistent with a moderate Brazilian standard of living. This was evident by the various indicators of possession of goods and access to basic services. Some other observations are as follows.
Sixty-two per cent of the families were living in their own homes. This proportion was 39% for families with incomes up to 2.5 MW, and 66% and 78% respectively for those earning 2.6 to 5 and more than 5.1 MW. Seventy-six percent of the residences were constructed of masonry or were apartments; the remaining 24% were classified as shacks. Ninety-three per cent of the families had access to treated water (either direct hook-up or a collective tap) and to electricity. Eighty-three per cent owned a refrigerator and a television, including 67% for those in the lowest income category. Finally, 35% owned a car. For the highest category of income the figure reached 61%.
Size and composition of the households
Size and composition of the family are important determinants of the nutrition status of individual members. Size affects the income per capita, so that, for low-income families particularly, variation in the number of household members can influence the availability of adequate food for each member. Access to food is also related to the composition of the family, particularly the proportion of adults and children. Families of the same size, but with a different distribution of adults and children, may attain their nutritional needs differently.
The average size of the households was 4.5 people (table 3). Contrary to what was expected, size appears directly related to income level. Despite the level of aggregation used, the households with lower calorie or protein consumption were larger across all income groups.
TABLE 3. Average household size by income level and consumption of calories and protein per capita per day
|Monthly Income (MW)||Calories (kcal)||Protein (g)||Total|
|< 2,300||>2,300||< 60||>60|
Thus, for example, the households with income between 2.5 and 5 MW, and with consumption below 2,300 calories, were on average 25% larger than families of the same income group with consumption above 2,300 calories. With respect to protein consumption, families with consumption below 60 g were 35% larger than those with consumption above this level. These figures suggest that household size may be an important variable determining calorie and protein consumption among low-income families.
Availability of food
The families reported an average daily per capita availability of 2,418 calories and 61 g protein. These figures are slightly lower than other estimates cited in the literature. These include 2,621 calories and 68 g protein  and 3,986 calories and 79 g protein  for Brazil overall, and 2,771 calories and 59.9 g protein for the city of São Paulo during 1981-1982 .
Various factors contribute to the differences between these estimates. First, households in this study had a lower average income than is encountered for Brazil as a whole. As a consequence, it was expected that the average per capita availability of calories and protein for them would also be lower than that of the Brazilian population. Second, the survey was undertaken during a period of great economic instability that coincided with the end of the Plano Cruzado. In May 1987 the economy experienced an accentuated decline in activity. Real average salaries had dropped 20% in the previous six months when food prices rose sharply, reaching monthly increases much greater than 30% Therefore, it is probable that this negatively affected the demand for food, principally for families with less purchasing power and a higher income elasticity for food. Finally, these studies adopted different methodologies largely associated with the use of primary or secondary data, which certainly affected the results.
TABLE 4. Average daily availability of calories and protein per capita by income level
|Monthly income (MW)||% of households||Calories (kcal)||Protein (g)|
|2.6 - 5.0||38||2.473||63|
Table 4 shows that the average availability of calories and protein varies significantly among the income classes. As was expected, families with income below 2.5 MW demonstrate the greatest deficiency. In addition to Engel's law (i.e., as income rises, food expenditures increase proportionately less than total expenditures), which can explain part of this difference, there is also the fact that nearly 40% of the household heads with income below 2.5 MW were unemployed during the survey period. This most probably increased uncertainty regarding the future and, therefore, negatively influenced the consumption and savings decisions of families with less purchasing power.
In terms of specific food items, rice and beans are, respectively, the principal sources of calories and protein (table 5). Other important sources of calories are sugar and oils. With respect to protein, milk and meat are most notable, contributing about 17% of the total protein consumed.
TABLE 5. Daily availability of calories and protein per capita by principal foods
|kcal||% of total||g||% of total|
It is interesting that the contribution of meat is less than expected, given the Brazilian pattern of consumption. The reverse is true for milk . A possible explanation is that the survey took place during the first off-season beef-cattle slaughter when meat prices normally rise; however, because it was just after an extended period of price controls, prices rose much more sharply. In addition, it should be emphasized that the milk programme, in contrast to other nutrition programmes, expanded considerably. According to data from the Secretary of the Treasury, the disbursement of funds for this programme increased from US$42 million to nearly US$230 million. It is therefore quite possible that there was considerable substitution of other protein sources, particularly milk, for meat.
Finally, the per capita availability of calories and protein was concentrated within a greatly reduced basket of goods. Four products alone (rice, sugar, pasta, and oil) comprised nearly 50% of the average calories consumed. With respect to protein, beans, rice, milk, and meat represented about 70% of the total.
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