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CHAPTER 4: ANALYSIS OF THE DIFFERENT PROBLEMS AND CAUSES RELATED TO NUTRITIONAL STATUS


Introduction
Who are the malnourished?
The pattern of vulnerability in Tanzania

Introduction

By using the TFNC/UNICEF conceptual framework of the determinants of malnutrition, it is possible to distinguish three major levels of problems and causes related to malnutrition. These are:-

Level of problem

General causes

a) Immediate causes

i. Inadequate food intake


ii. Infectious Diseases



b) Underlying causes

i. Inadequate Household Food Security


ii. Inadequate Caring Capacity and women’s control of resources


iii. Inadequate provision of essential services like health, education, water and sanitation and housing.



c) Basic causes

i. Economic


ii. Ecological


iii. Political/Policies


iv. Culture and beliefs


v. Institutional


Both the level of the problem and the causes are interrelated. It is, therefore, important to stress especially at the level of underlying causes of food, care and essential services that while all three are necessary conditions for good nutrition, none is sufficient on its own.

The idea of putting a label on groups of issues as done in the model is only to facilitate communication and analysis. The model is neither predictive nor fixed; and issues can be transferred from one group to another without loosing anything fundamental. The specific problems and causes related to nutrition will be discussed in further detail on the basis of the above model in the subsequent chapters. This chapter addresses the question of who are the malnourished?

Who are the malnourished?

The identification of the under-nourished or those at risk of being so is important not only for purposes of targeting interventions but also for purposes of taking preventive measures by providing adequate safety nets. Thus, the first question we need to ask when analysing the different problems and causes related to malnutrition is “who are the under-nourished?.” In answering this question, the concept of vulnerability will be used.

The vulnerable groups

Vulnerability refers both to biological and socioeconomic risks of becoming under-nourished. The biologically vulnerable groups are those groups who because of age (like children under-five years and the elderly) or physiological state (like pregnant and lactating women) are at a high risk of becoming under-nourished, because of their higher nutrient requirements for growth, or in relation to their physiological state. The socioeconomically vulnerable groups consist of the “poverty prone” groups who because of their low socioeconomic situation earn too little to get adequate socioeconomic access to proper nutrition. These consist of small farmers, the urban poor, and female-headed households. There are also the landless in areas where there is a shortage of land like in Kilimanjaro region. To this group must be added those without or with little education; and those living in geographically at risk areas like food growers in “drought/flood prone pockets” who face regular but transitory food insecurity. In addition there are those living in areas deficient of a specific nutrient, for example iodine. The HIV/AIDS pandemic has added another vulnerable group of households where one or both of the parents have died due to AIDS.

Since several of these groups overlap it is difficult to establish a global figure for the “nutritionally vulnerable population” of Tanzania. Moreover, since some of these “vulnerable groups” are delineated in terms of function (functional classification) they are mixed within our communities. We have already pointed out the institutional possibilities which exist for their identification in rural Tanzania. Their identification in the urban setting poses some problems and the British Overseas Development Agency (ODA) is funding a study to identify the malnourished in Mbeya Urban.

In the Report of the Task Force on Food Security in Africa (1988), the World Bank estimated that there were about 6.6 million people in Tanzania who were chronically food insecure in 1988. Thus, the most nutritionally vulnerable people are to be found in the groups shown in table 30. The figures given are gross estimates. Both the number and proportion of the poverty prone groups is increasing as a result of a low economic base, climatic shifts, high population growth, structural adjustment and the HIV/AIDS pandemic. The increase in poverty is typified by the increase in number of beggars especially in the urban areas; the new phenomenon of street children and a staggering youth unemployment who have emigrated from the rural areas to the urban areas in huge numbers. A visit to Kariakoo in Dar-Es-Salaam is an eye-sore to the problem of youth unemployment. Since for every one extra mouth to feed there are two hands to work, there is a need to create schemes to give them skills and employment.

Reductions in poverty lies in equitable economic growth and development. If the current 4 percent economic growth rate for Tanzania is stabilized across all sectors it seems that the fundamental economic reforms which have taken place during the last seven years have laid down a reasonable ground for further economic growth. It is hoped that in the process, the equity foundations laid down during the 1960s and 1970s will not be thrown overboard. It is acknowledged that the safety nets incorporated in the economic restructuring may not capture all the poor. But the poor have demonstrated that what they need is not charity but rational policies to enable them produce or earn a decent living. It is encouraging that all the political parties seem to have alleviation of poverty as one of their agendas, but they have varying grasps of the problem and, therefore, its solution. While the poor provide the parties something to talk about, something to promise to correct and something that enables them make a show of their humanity, what is needed is not promises, but concrete policies and strategies for poverty reduction, alleviation and prevention. Unless adequate political, social and economic conditions for the prevention of poverty are laid down, the poor shall always be with us.

The pattern of vulnerability in Tanzania

Under-nutrition in Tanzania shows a distinctive pattern with respect to age, sex, socioeconomic status and geographical location. This pattern may be slightly modified depending on the specific type of malnutrition being considered. The pattern confirms the usefulness of the concept of vulnerable groups.

Age and sex pattern

We have already shown in chapter three that children under-five years of age, adolescent girls and pregnant and lactating women are not only the most nutritionally vulnerable, but their consequences in terms of survival, development and reproduction are most serious. Suffice it to add here that the biological vulnerability with regard to age and sex is usually superimposed on socioeconomic vulnerability which worsens the situation. For women, there is an added gender vulnerability that constraints their extrication from their socioeconomic and even environmental susceptibility. This will further be discussed in the section on women and control of resources.

Table 30: The magnitude of the nutritionally vulnerable groups in Tanzania

Description of the vulnerable group

Estimated number of people involved

A.

Poverty prone groups

1.

Rural households with holdings too small to provide sufficient subsistence

700,000

2.

Rural households estimated to earn income below the absolute poverty line

2,000,000

3.

Rural minimum wage earners working on the state farms and estates

150,000

4.

Urban low-income workers, mostly engaged in informal sector activities

600,000

5.

Food growers living in “drought/flood prone pockets” that face “transitory” food insecurity (40% of population)

10,000,000

B.

Biologically vulnerable groups

1.

Pregnant women

1,500,000

2.

Toddlers from six months to three years who are passing through the weaning period

4,000,000

C.

Geographically vulnerable groups

1.

Every person living in iodine deficient areas (40 percent of the population)

10,000,000

Source: World Bank (1988) and TFNC report no. 1322
Rural and urban variations

Because of the generally low socioeconomic development of the rural areas, all forms of malnutrition are consistently higher in the rural than in the urban areas. The 1991/92 DHS data confirm these earlier observations (table 31).

Table 31: Rural and urban variations in Nutrition indicators in wider-five children in Tanzania, DHS, 1991/92

Area

N

Height-for-age (H/A)

Weight-for-height (W/H)

Weight-for-age (W/A)

-3SD

-2SD

-3SD

-2SD

-3SD

-2SD

Mainland

5,943

19.7

46.6

1.2

5.5

7.0

28.5

Dar-Es-Salaam

277

11.3

28.5

1.3

6.8

4.0

19.9

Other urban

965

15.5

44.8

0.6

4.4

4.2

27.4

Rural

4,701

21.1

48.1

1.3

5.6

7.7

29.2

Zanzibar

152

25.7

47.9

1.5

11.0

12.3

39.9

Tanzania

6,095

19.8

46.7

1.2

5.6

7.1

28.8

Source: URT/Bureau of Statistics, 1993
The rural-urban differentiation of the rates of malnutrition hide the observation that in the peri-urban areas and urban slums, the rates are similar to those in the rural areas. It is of particular concern to point out that Zanzibar which is mostly urban has higher malnutrition rates than even rural Tanzania mainland. The DHS data confirm earlier observations that while there is a general trend of an improvement in the nutrition situation in the mainland, the general trend for Zanzibar is one of deterioration as can be seen in table 32. The trend for IMR and U5MR for Zanzibar is one of general decline, contrary to previous estimates which had indicated some increase. However, the inter-censual decline is very small; only of 0.3 per annum compared to 1.9 for mainland. To reach the goal of an U5MR of 70 by the year 2,000 an annual reduction rate of 7.3 will be required against one of 6.9 for the mainland.

The trend for Zanzibar can be explained by the fact that Zanzibar including the rural areas depend mainly on imported food which has been adversely affected by the economic crisis. An indication of the realization of this problem by the government of Zanzibar, is the initiation of a campaign to grow their own food called “Mtakula” (You shall eat).

There are also geographical differences in the rates of malnutrition. The geographical variation in the severe forms of malnutrition is more pronounced than for total malnutrition. For PEM, the South (Mtwara, Lindi and Ruvuma), South-Western (Iringa, Mbeya and Rukwa) and Western (Kigoma) regions of mainland Tanzania are more affected than the other regions. In the Islands, Pemba is more affected than Unguja; and the northern regions of both Unguja and Pemba are more affected than the northern regions.

Table 32: Rate of infant and child mortality and malnutrition in Zanzibar


Year

Unguja

Pemba

Zanzibar

Urban

Rural

Infant Mortality

1975

112

121-132

123-128

125

1985

113

120-130

119-123

120

Child Mortality

1975

187

205-223

206-218

209

1985

188

200-220

200-206

202

Children underfive years (percent malnourished)

1985

37

?

38

37

1990

48

?

57

51

Children under-five years (percent severely malnourished)

1985

5

?

7

5

1986

6

?

12

8

Source: URT/UNICEF, 1990 and Bureau of Statistics, 1992
The differences in the rates of PEM seem to be related more to the level of socioeconomic development than climate or disease pattern. The agricultural systems which may be determined by climate have also been shown to affect the level of malnutrition. Generally speaking, agricultural systems dominated by livestock have lower rates of malnutrition than the other agricultural systems.

Socioeconomic vulnerability

The major socioeconomic factors which increase vulnerability to undernutrition are low education especially of the mother, low income and resource control by women and a large family size. Good parental education is usually a good proxy indicator for better access to services and good economic status. We shall discuss in more detail the situation with regard to these factors in subsequent relevant sections. Here we shall only indicate the major associations.

i) Education

Several studies which have looked at the influence of parental education particularly of the mother on the nutritional status of the children show that they positively affect nutritional status. In both the 1978 and 1988 censuses, infant and child mortality rates were lower in households with women possessing post-primary education than those with primary or no formal education. The 1991/92 DHS data give the most recent and most undisputed effect of education on several factors which affect nutritional status (table 33). In summary, those without formal education marry younger, have higher teenage pregnancies, are more polygamous, want more children and are less likely to use health facilities than those who have formal education. The higher the educational level the greater is the difference.

Though the relationship between education and survival is not always statistically demonstrated, education is normally the “key” to better opportunities for employment, accessibility to information and services and to independent and correct action with regard to survival and development. The instrumental role of education especially that of women in all nutrition related activities emphasizes education not only in relation to survival and development, but as a basic right.

Table 33: The effect of education on factors affecting nutritional status

Factor

Mean

No education

Primary education

Secondary or more

1. Age at first pregnancy (years)

18.8

18.3

19.1

23.4

2. Teenage pregnancy (percent)

23.2

29.1

23.7

3.1

3. Polygamy (percent)

27.5

35.4

22.2

14.2

4. Number of children wanted

6.0

7.3

5.6

4.2

5. Delivery at health facility (%)

53.2

38.3

59.4

81.4

Source: Family Planning Unit, MOH, 1992
ii) Vulnerability with regard to family size

The studies which have looked into the effect of family size on nutritional status, give variable results. Most studies however, have shown a worsening situation of the nutritional status with an increase in family size only in children under-five years while others have shown an increasing trend of higher malnutrition rates with increasing size of the household in general. The family composition is also an important factor, in that families with many members of relatively older ages could be contributing to the family resources than families with many younger members, who would mainly consume resources. Excluding the extended family system, birth spacing is a strong determining factor of child mortality which reflects the overall care. The higher the interval of birth spacing, and therefore smaller family size, the lower are the mortality rates and by implication lower malnutrition rates (table 34).

Table 34: Child spacing and mortality in Tanzania

Birth interval (years)

Neonatal Mortality Rate

Infant Mortality Rate (IMR)

Underfive year Mortality Rate (U5MR)

< 2

69

160

230

2 - 3

27

80

134

4 or more

25

65

93

Source: Family Planning Unit, MOH, 1922
iii) Economic vulnerability

At the household level, studies suggest that the smallholder sector could be divided into two distinct groups. The first is the resource weak families who comprise about 30-35 percent of total households. These are characterized by inadequate productive resources such as land, labour and cash, as well as entrepreneur skills and tend to be more malnourished with high mortalities and more vulnerable to seasonal adversity or adverse terms of trade. The second group are the relatively food secure majority, but who have to use a large proportion of their resources to achieve food security. Evidence suggest that both groups are at risk of food insecurity. Thus in the rural areas, food insecurity is widespread and chronic in the sense that there is always a certain degree of food deficit in the households during part of the year. It is not acute in the sense that no emergency action is required apart from disaster situations as those created by drought and floods.

Several studies in Tanzania have demonstrated the relationship between income classes and nutritional status of households. Using infant and child mortality rates as indicators of household nutritional status (table 35), it has been shown that (1) for all income classes (with the exception of the labourers and professional classes), infant and underfive child deaths are higher in the rural areas than urban areas; and (2) the higher the class or income, the lower the infant and underfive mortality rates in the household, with the highest income classes having two to three times less deaths.

Furthermore, analysis of the 1978 census data indicates that (1) life expectancy was higher among women with higher levels of education; (2) infant and child survival rates were also higher with higher levels of education among adults in their families, especially women; and (3) occupation and sources of livelihood (which are to a large degree determined by education) affected chances of survival. For example, women cultivators had lower survival rates than those with other occupations (made possible by education). On the education variable, rural people are likely to fair worse than urban ones. In this context, Tanzania’s policy emphasis on education for all should be appreciated, for education empowers individuals and communities to manage their lives and environments.

Table 35: Infant and Underfive mortality rates (IMR and U5MR) per 1,000 live births by occupation of head of household: Rural and urban comparisons


Cultivators

Labourers and other workers

Craftsmen and operators

Professional, managerial sales and clerical

Area

IMR

U5MR

IMR

U5MR

IMR

U5MR

IMR

U5MR

Rural

148

120

104

75

109

81

88

59

Urban

121

94

115

88

93

64

88

59

Source: Bureau of Statistics, 1978 Population Census, volume VIII, Dar es Salaam, Tanzania
In the rural areas, economic improvement does not automatically lead to improved nutritional status. For example in Njombe district in 1975 malnutrition levels in the purely subsistence section of the survey population were lower than in those areas where production for cash income was increasing [Jacobsen, 1975]. In the Iringa region nutrition survey of 1979/80 by TFNC [Ljungqvist, 1981] rates of malnutrition were found to be higher in villages with higher than with low crop production. In fact the village which had been chosen to be the best village because of its economic development had the highest rates of malnutrition. A study done in Kisarawe district Coast region in 1981 found no significant relationship between income, energy intake per capita and nutritional status in a sample of 2155 underfives [Kavishe, 1981]. On the other hand a relationship between socioeconomic level and birth-weight was found in two studies [Bantje 1987 and 1988].

An examination of available data on birth-weight in a longitudinal perspective from the 1940 to 1980s by Bantje (1985) suggest that, on the whole, there has been a slow rise of birth-weight, from a gross average of 2940 g in the 1950s to about 2994 g in the late seventies. This can broadly be attributed to improved standards of living, especially better health care, in the course of time.

An exciting question is whether the economic crisis of the early 1980’s would reflect itself in the nutritional status. Again Bantje (1985) finds no evidence of a decline in the remote rural stations where environmental conditions and the resulting food supply situation apparently were the decisive factors. In places closer to Dar es Salaam and the main road, therefore, presumably more closely linked to the national economy there was evidence of a rapid decline of birth-weight between 1979 and 1984 which are acknowledged as deep economic crisis years. In Ikwiriri (Coast region), Ilembula (Iringa region), Ifakara (Morogoro region) and Bagamoyo (Coast region), the subsequent improvement in the economy appears to have been reflected in a hesitant improvement of birth-weight. A similar trend was shown in Mbozi (Mbeya region) between 1983 and 1985 which may have been attributed to the expansion of the coffee industry and the fast increase of producer prices for coffee.

Seasonal vulnerability

Many studies have revealed the occurrence of seasonal variations in nutrition, health, vital events and economic social life, but the availability of such studies done in Tanzania is very limited. Seasonal variations found in one year sometimes do not recur in the next year, thus the length of the series needed to demonstrate such variations depend on the degree of internal variation in the ecosystem. A short series may be sufficient when the observed variations can be adequately explained from the available background information. We know for example that there is seasonal variation in food production and availability; heavy agricultural labour which affects caring capacity and the occurrence of diseases. To cope with the climatic uncertainties, the agricultural system in Tanzania displays a great deal of flexibility in terms of field sites, planting and replanting and the choice of crop varieties. All these variations must have an impact on the nutritional status of the population.

The FAO executed Women in Agriculture (WIA) project [FAO/TFNC, 1992] provide the most illustrative information with regard to the seasonal variation and causes of the nutritional status of under-fives and school children in Tanzania. For all types of malnutrition peak malnutrition rates were found during the rainy wet months of January to April and lowest rates were found after harvest during the months of September to November. According to the study the major determinants of the seasonality of malnutrition were the seasonal variations in food availability; disease rates and agricultural labour especially women labour which affect caring capacity.

This seasonal pattern also holds true for maternal nutrition as shown in a study by Bantje (1987 and 1988) using birth-weight as the indicator of maternal nutritional status. He attributed the seasonal differences to the different combinations of infection rates, dietary intake, reliability of food supply, food intake and the labour output of women which was reflected in a low mean maternal weight gain and variations in the mean birth-weight. The relatively high birth-weights he found during periods of food shortage without field labour suggested that heavy female labour had a decisive effect on birth-weight under conditions of inadequate food intake. Neuvians (1987), has also demonstrated a seasonal variation in the underfives year mortality rate (U5MR) and PEM related mortality in Bagamoyo district Coast region.

An examination of MCH data from selected districts [Brycesson et al, 1986] also show a seasonal variation in the incidence of malnutrition with consistently high incidence rates between July and September which contrasts inversely with community surveys. The major reason for seeing high malnutrition rates in MCH clinics during July to September, which is indicated by community surveys as the lowest malnutrition period, is that in July-September, the harvest season is over and women have more time to send their children to the clinic [FAO/TFNC 1992]. Thus the MCH peaks do not indicate an increase of malnutrition in the community but the availability of time for women to take children to the clinics.


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