Contents - Previous - Next

This is the old United Nations University website. Visit the new site at http://unu.edu

Public health nutrition

Determinants of childhood malnutrition in Jamaica

Bendley Melville, Maureen Williams, Valerie Francis, Owen Lawrence, and Lee Collins

Introduction

Malnutrition is a major public health problem in the developing countries. It contributes to child mortality, poor intellectual and physical development of children, and lowered resistance to diseases, and consequently stifles development. Its etiologies include low income, uneven household food distribution, poor sanitation, infection, food shortages, inadequate food marketing and preservation, and inadequate nutrition knowledge. Malnutrition is a very complex problem and multifaceted strategies are required to combat it. It is therefore important to determine its causative factors before appropriate intervention can be implemented.

A recent nutrition survey in Cornwall County, Jamaica, showed that malnutrition increased significantly between 1978 and 1984 [1] Moreover, the primary health care nutrition programme has had only modest success in alleviating the problem during the past 15 years [2]. Marchione [3] suggested that despite significant improvement in the Jamaican primary health care system, economic changes appear to be the major factor influencing the nutritional status of young children, and he stressed the need for programmes to develop individuals' self-reliance with respect to health care.

In these circumstances, it seems important to incorporate community development strategies within our primary health care nutrition programme. The success of the community development programmes will depend, to a large extent, on identifying the location, nature, extent, and causes of the nutritional problem, thereby ensuring that scarce resources are targeted to the needy. In this paper, we investigate various socioeconomic, demographic, and biological factors that might influence the nutritional status of children 4-35 months old in Cornwall County.

Jamaica is the third largest island of the Caribbean. In 1984 the estimated population was 2.3 million people, over one-third of whom were under 14 years of age [4] Unemployment rates were 26.7% and 25.4% in 1983 and 1984 respectively [4]. The substantial devaluation of the Jamaican dollar during 1982-1984 contributed to the increase of the consumer product index. Although the per capita gross national product is US$1,300 (1983 estimate) [5], this does not represent the true situation because income distribution is highly skewed.

Methods

The study was carried out from March through August 1984 in three parishes in Cornwall County, Jamaica. A three-stage cluster-sampling procedure was used. In the first stage, the parishes were stratified as urban or rural. In the second stage, 41 enumeration districts (clusters or sites) were randomly selected in both areas in the three parishes based on population distribution. Finally, 504 households were selected from the 41 clusters.

At each site, all households were visited, and the height and weight of one child 4-35 months old were measured in each household. Age was verified by examination of the child's birth certificate where possible. If more than one child in this age group was present, the youngest was selected. In all, 504 children were evaluated, with measurements taken in the manner described by Jelliffe [7]. A Detecto doctor's beam-balance scale was used to measure weight. Heights were measured with a locally constructed, portable wooden board.

A questionnaire was administered by Cornwall County nutrition staff to a responsible member of each household. It took an average of 30 minutes to complete and was checked at the end of the day. Questions included information on the socioeconomic, demographic, and biological circumstances of the household. The non-response rate was low, 3%.

Data for all anthropometric indices were expressed as percentages of the National Centre for Health Statistics medians [8]. Stepwise multiple-regression analysis was conducted to examine the effects of the independent variables on nutritional status, using weight for age as the dependent variable. As some households (cases) did not have complete data for all the independent variables, 455 cases were used in the regression equations. The data were analysed by an IBM microcomputer.

Results

The mean weekly family income was US$26, and the mean weekly household food expenditure was US$17. This means that families spent on average 67.4% of their total income on food. The average family size was 5.9, with a mean of 2.4 rooms per house. The mean number of pregnancies per mother was 3.1, and the mean number of children who died before their fifth birthday was 0.13.

More than half (67.0%) of the infants were breast-fed for six months or more. Thirty-four per cent of heads of households were married. Almost all the mothers were literate; 90.7% had completed primary and secondary school, and 7.9% had completed high school or a tertiary institution. Only 12.9% were employed. The children lived with their mothers in 41.8% of the households.

Forty-eight per cent of the sample cultivated various crops, of which most (77.8%) were starchy roots, fruits, and tubers. Some 17.8% of the sample raised goats. Twelve per cent of the households had flush toilets, and 15.2% had running water in their homes. Garbage was collected in 22.8% of the households, while 41.3% either burned or buried their garbage.

The average weight for age, weight for height, and height for age of the children were 89.2% (SD 2.2), 94.9% (SD 9.1), and 96.8% (SD 4.4) respectively.

Table 1 compares the nutritional status of the children in this study with that found in a 1982 nutrition survey conducted in St. James. It is noteworthy that both studies were done during the same period of the year and that the age groups of the children were similar. The children under three years old appeared to be worse off nutritionally in 1984 than in 1982.

TABLE 1. Nutritional status of children under three years of age in 1982 and 1984, Cornwall County, Jamaica

Two models were used in the multiple-regression analysis. Model I represents what might be called the basic regression results. In the second model we substituted three new variables for three others that were not statistically significant in model I.

The results of the analysis for model I are shown in table 2. Of the five economic variables, three were significant: household size, per capita food expenditure, and number of rooms. Weight for age declined as the number of persons in the household increased. This is in agreement with other studies [10-13]. On the other hand, per capita food expenditure was positively correlated with nutritional status. Similar results have been reported by others [9, 14]. The number of rooms was also positively correlated with weight for age, also in agreement with other studies [10, 15]. Land size was not significantly associated with weight for age. This has been substantiated by earlier investigators [9, 16, 17], although others have found a positive association [10, 18-20].

TABLE 2. Determinants of nutritional status (weight for age) of 455 children 4-35 months old, model I

a. Significance at 5% level was accepted. NS = not significant.

No significant association was observed between income and nutritional status. Similar results have been reported elsewhere [11-13], with a positive association noted by some authors [15, 18, 19, 21, 22].

The presence of a community health aide was positively associated with weight for age. These aides are responsible for screening, monitoring growth, providing nutrition education, distributing food supplements, and home visiting. This result suggests that the primary health care nutrition programme may have had some impact on child growth. This is in agreement with other studies [14, 23]. Boys were slightly better off nutritionally than girls. It is likely that this result is valid, especially since separate standards were used for the sexes. Many other studies have also found girls to be worse off nutritionally than boys [15, 18, 21, 23-26].

Longer duration of breast-feeding was positively associated with higher weight for age. This was also the case in St. Vincent [27]. Others, however, have reported a negative association between these variables [13, 28].

Disease is generally believed to be factor contributing to malnutrition. Both fever and diarrhoea were negatively correlated with weight for age, as substantiated elsewhere [9, 14, 18]. The common cold was positively correlated with nutritional status. This was surprising, as nutritional status is inversely related to disease rate. It is likely that most of the children reported as having a cold in fact had only a mild runny nose. This explanation is supported by the fact that a high percentage (47%) of the children were reported as having a cold the previous week compared with 15% and 9% for fever and diarrhoea respectively.

Age of child, birth order, and father's support were not significantly associated with weight for age. Others have found no significant association between birth order and nutritional status [10, 12, 25] and between age of child and nutritional status [21]. In contrast, some investigators have noted a negative association between age of child and weight for age [9, 11, 12, 18, 27]. Furthermore, in one study [21], birth order was negatively correlated with nutritional status. A positive association has been observed between father's support and weight for age [9, 11].

We were also interested in observing the effect of reduced income, birth order, and father's support from model I with three new social variables incorporated in model II: number of children under five years old, number of pregnancies, and mortality under the age of five years (table 3). The coefficient of determination for model I was 0.35, while that for model II was slightly higher, 0.37. Moreover, two of the three new variables were significant in model II (number of children under five years old and number of pregnancies), whereas the economic variables household size and number of rooms were no longer significant. This indicates that social characteristics of the household appear to be more important determinants of weight for age than economic characteristics.

TABLE 3. Determinants of nutritional status (weight for age) of 455 children 4-35 months old, model II

1. Significance at 5% level was accepted.
2. NC = nor significant

Discussion

In general, the findings of this study are in agreement with those of similar studies in other developing countries. Diseases, economic and social characteristics of the households, and duration of breast-feeding were the major determinants of nutritional status of the children in both regression models I and II.

Per capita food expenditure was the only economic variable that remained significant when the social variables were incorporated into model II. It was the second most important predictor of nutritional status in model II; income was dropped because of its correlation with per capita food expenditure (r = 0.45). Per capita food expenditure is in itself a fairly good indicator of household income. Income appears to be the major determinant of nutritional status [19, 21, 27, 29], although it may not be as critical in predicting nutritional status [30]. Clearly, interventions for improving the nutritional status of children other than increasing household income should be considered.

The duration of breast-feeding was the most important predictor of nutritional status in model I and the third most important in model II. Another study in Jamaica [9] and two in St. Vincent [27, 31] noted a significant positive association between the duration of breast-feeding and nutritional status. It therefore seems that national nutrition-education programmes aimed at encouraging prolonged breast-feeding may be helpful in improving the nutritional status of children.

Gastroenteritis and fever were important predictors of weight for age in both models, thereby emphasizing the importance of disease in the etiology of malnutrition. This suggests that a health-education programme that stresses the importance of good hygiene and the implications of bottle-feeding [34] may also contribute to improved nutritional status. In addition, efforts should be made to improve environmental sanitation [33]. This is crucial, especially as a recent study [34] showed that the determinants of infection in children with mild and moderate malnutrition are more closely related to the quality of the environment than to nutritional status; nutritional status has an impact mainly on the severity and duration of diarrhoea.

Sex was also a predictor of nutritional status in both models; however, there was no evidence that boys receive preference over girls in Jamaica. It is likely that boys are more adventurous than girls and therefore have greater access to "free goods" such as breadfruit, mangoes, and oranges.

The presence of community health aides, which was significant in model I, was no longer significant in model II. This indicates that social and economic characteristics were more important than health care activities in predicting nutritional status, thereby supporting the idea of developing national self-reliance in primary health care services [3]

By and large, this study also suggested that social characteristics of the household were more important predictors of nutritional status than economic characteristics. This has implications in planning programmes for alleviating malnutrition and indicates that emphasis should be placed on family-planning programmes, especially since the number of children in the family under five years old was the most significant predictor of weight for age in model II. Other studies have also found this factor to be significantly associated with weight for age [11, 20, 22, 27]. These results should be regarded with caution, however, especially as 9.7% of the original sample was not used in the final regression equation.

Finally, the importance of prolonged breast-feeding cannot be over-emphasized, especially since it has implications in preventing infections, providing nutrients for the children, and extending the interval between births.

The increase in malnutrition levels between 1982 and 1984 may be attributed to the substantial devaluation of the Jamaican dollar during this period (1982 US$1 = J$1.78; 1984 US$1 = J$4.95). As a result, the consumer price index escalated (see FIG. l. Annual increase of consumer price index in Jamaica, 1981-1984 (Source: ref. 6) ), causing the price of basic foodstuffs, for example, flour, rice, and cornmeal, to increase dramatically during that time. Consequently, the standard of living among the low income groups may have been eroded.

In conclusion, this study supports the general consensus that protein-energy malnutrition is a problem of poverty. It also underscores the need to establish programmes to develop self-reliance in primary health care services. The determinants of nutritional status identified in this study could be used to identify households at risk of malnutrition, thereby encouraging targeting of our scarce resources to those most in need. of infant growth in Guatemala. Santa Monica, Calif, USA: Rand Corp., 1981.

References

1. Melville B, Lawrence O, Williams M, Archer E, Francis V, Collins L. Childhood malnutrition in the parishes of St. James. Westmoreland and Trelawney. Final report. Kingston, Jamaica: Ministry of Health, 1984.
2. Melville B. Nutrition through primary health care: an assessment of the Jamaica experience. Unpublished, 1979.
3. Marchione TJ. Evaluation of primary health care and nutrition programmes in the context of national development. Soc Sci Med 1984;19:225-235.
4. The Statistical Institute of Jamaica. Statistical abstract, 1984. Kingston, Jamaica, 1985.
5. United Nations Children's Fund. The state of the world's children, 1986. Oxford, UK: Oxford University Press, 1985.
6. The Statistical Institute of Jamaica. Consumer price indices annual review, 1984. Kingston, Jamaica. 1985.
7. Jelliffe DB. The assessment of nutritional status of the community. WHO monograph series no. 53. Geneva: WHO, 1966.
8. World Health Organization. Measuring change in nutritional status. Geneva: WHO, 1983.
9. McLeod J. A study of under-nutrition, poverty and national development in Jamaica. PhD thesis. Mona, Jamaica: University of the West Indies, 1985.
10. Desai P, Standard KL, Miall WE. Socio-economic and cultural influences on child growth in rural Jamaica. J Biosoc Sci 1970;2:133-143.
11. Marchione TJ. Factors associated with malnutrition in children of western Jamaica. In: Jerome M, Pelto G, Kandel R, eds. Nutritional anthropology. New York: Redgrave Press, 1980.
12. Ryan JG, Bidinger PD, Prahlad Rao N, Pushpamma P. The determinants of individual diets and nutritional status in six villages of southern India. Research bulletin no. 7. Patancheru, Andhra Pradesh, India: International Crops Research Institute of the Semi-arid Tropics, 1984.
13. Wolfe BL, Behram JR. Determinants of child mortality, health and nutrition in a developing country. J Dev Econ 1982;11:163-193.
14. Drake WP. Fajardo LF. The promotora programme in Candelaria: a Colombian attempt to control malnutrition and disease, 1968-74. Ann Arbor, Mich, USA: Community Systems Foundation, 1976.
15. Clark CA. Demographic and socio-economic correlates of infant growth in Guatemala. Santa Monica, Calif, USA: Rand Corp., 1981
16. Cervantes S. Salazer S, Rojas Z. Socio-economic characteristics of functional groups of the malnourished population in Costa Rica. UNICEF Soc Stat Bull 1981 ;4(4): 1-9.
17. Victora CG, Vaughn FJ. Land tenure patterns and child health in southern Brazil: the relationships between agriculture production, malnutrition and child mortality. Int J Health Serv 1985;15:253-274.
18. Field JO, Miller RL, Drake WP. Kottar: malnutrition, intervention and development in a South India district, vol. III. Ann Arbor, Mich, USA: Community Systems Foundation, 1981.
19. V, Martorell R, Mesia-Pivaral V, Delgado H, Lechtig A, Teller C, Klein RE, Martorell R. Income and growth retardation in poor families with similar living conditions in rural Guatemala. Ecol Food Nutr 1981 ;10:241-248.
20. Rawson I, Valverde V. The etiology of malnutrition among preschool children in rural Costa Rica. J Trop Pediat Environ Child Health 1976;22:12-17.
21. Bairagi R. Is income the only constraint on child nutrition in rural Bangladesh? Bull WHO 1980;58:767-772.
22. Battad JR. Determinants of nutritional status of preschoolers. Philippine Econ J 1978;17:154-167.
23. Gwatkin DR, Wilcox GR, Wray, JD. The policy implications of field experiments in primary care and nutrition care. Soc Sci Med 1980;14C (2):121-128.
24. Alderman MN, Husted J, Levy B, Searle R. Minott OD. A young child nutrition programme in rural Jamaica. Lancet 1973;1:1166-1169.
25. Thompson P. Evaluation of the young child nutrition programme, Hanover, Jamaica. MPH dissertation. New Haven, Conn, USA: Yale University, 1977.
26. Livinson FJ. An economic analysis of malnutrition among young children in rural India. Cornell-MIT international nutrition policy series. Cambridge, Mass, USA: MIT Press, 1974.
27. Greiner T. Latham MC. Factors associated with nutritional status among young children in St. Vincent. Ecol Food Nutr 1981; 10: 135-141.
28. Martorell R, Leslie J, Moock P. Characteristics and determinants of child nutritional status in Nepal. Am J Clin Nutr 1984;39:74-86.
29. Kielman NS, Kielman AA, Greval GK. Etiological determinants of protein-calorie undernutrition in a rural child community Acta Tropica 1976;33:342-368
30. BL, Behram JR. Is income over-rated in determining adequate nutrition: Econ Dev Cult Change 1983;31:525-550
31. Antrobus ACK. Child growth and related factors in a rural community in St. Vincent. J Trop Pediatr 1971; 17: 187-209.
32. Everson S. Relationship between infant morbidity and breast-feeding versus artificial feeding in industrialized countries: a review of the literature. Geneva: WHO, 1982.
33. Henry FJ. Environmental sanitation infection and nutritional status of infants in rural St. Lucia, West Indies. Trans R Soc Trop Med Hyg 1981;75:507-513.
34. Martorell R, Sharma R. Trends in nutrition, food supply and infant mortality rate. In: Halsted SB et al., eds. Good health at low cost. Proceedings of a conference held in Bellagio, Italy. New York: Rockefeller Foundation, 1985.

Contents - Previous - Next