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* Helen Keller International, Gulshan 1212, Dhaka, Bangladesh;
Helen Keller International Asia-Pacific Regional Office, Jakarta Pusat, Indonesia; and
Helen Keller International, World Headquarters, New York, NY 10010
1To whom correspondence should be addressed. E-mail: htorlesse{at}hotmail.com.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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KEY WORDS: • Bangladesh • macroeconomic food policy • nutritional surveillance • preschool children • malnutrition
Malnutrition contributes to the deaths of over one half of preschool children in developing countries (1 ). Although the basic cause of malnutrition is poverty, malnutrition also contributes to poverty by increasing morbidity, impairing cognitive development, and reducing work capacity and productivity in adulthood (2 ,3 ). Governments and development organizations throughout the world recognize that poverty is the key constraint to development, and in the 1990s, world leaders agreed upon a common set of Millennium Development Goals (MDG) to measure progress toward the reduction of poverty and related social imbalances from 1990 to 2015, including a reduction in child mortality by two thirds (4 ). Because malnutrition underpins both child mortality and poverty, policies and programs that improve nutritional status are key to achieving these MDG (5 ,6 ). Macroeconomic food policies have the potential to reduce malnutrition by improving access to food through efficient growth of the food and agricultural sectors, generation of employment and income for the poor and improved food security (7 ). However, remarkably little is understood about the mechanisms and the magnitude of the effects of macroeconomic food policies on the nutritional status of the poor.
Many poor households in developing countries lack the resources they need to grow or purchase sufficient food, a necessary condition for good nutritional status; thus their diet is deficient in energy and nutrients. In South Asia, where nearly one half of preschool children are underweight (8 ) and one third are deficient in at least two micronutrients (9 ), most undernourished children live in rural areas. Here, population pressure on finite land has led to growing landlessness and a rise in the proportion of households that depend on markets for food. Because poor households use a large share of their income to purchase food, sharp increases in the price of foods can adversely affect their purchasing power by reducing their real income, that is, the amount of food and other commodities that their income can buy. The effect of price hikes on real income is particularly acute when food staples are affected because these foods account for the bulk of food expenditure among the poorest households. If these households react to rising food prices by reducing the amount or quality of food that they purchase, it follows that macroeconomic food policies that influence the price of staple foods have the potential to affect nutritional status.
Data collected in rural Bangladesh in the early 1990s by the Nutritional Surveillance Project (NSP) revealed that trends in the percentage of underweight children aged 6–59 mo closely followed trends in the price of rice, the main food staple (10 ). Rice provides rural households in Bangladesh with >70% of their energy intake and accounts for almost 50% of their food expenditure (11 ). A combination of weather conditions and government policies resulted in major fluctuations in the price of rice in Bangladesh throughout the 1990s (12 ). The specific objective of the analysis described in this paper was to explore the links between child underweight and rice price, consumption and expenditure in rural Bangladesh using data collected over 10 y by the NSP with a view to examining how macroeconomic policies that affect rice price influence the nutritional status of children.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Subjects.
The analysis used data collected on a total of 81,337 children aged 6–59 mo and their households in rural Bangladesh during rounds of data collection conducted in the month of June from 1992 to 2000 (Table 1). The data collection protocol complied with the principles enunciated in the Helsinki Declaration as revised in 1989 (13 ). The field teams were instructed to explain the purpose of the NSP and data collection to each child’s mother and, if present, the father and/or the household head; data collection proceeded only after verbal consent. Participation was voluntary and all subjects were free to withdraw at any stage.
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Over the course of nearly a decade, the NSP employed two different sampling schemes. Between June 1992 and June 1997, a multistage random cluster sampling design was used to select a new sample of 500 children every 2 mo from purposively selected subdistricts in rural areas, chosen because they were either at higher than average risk of natural disasters or representative of the six divisions of Bangladesh. In each subdistrict, half of the unions (the next lowest administrative level) were randomly selected. Twenty-five villages were identified from a list of all villages in the selected unions, and households were systematically sampled to obtain 20 children per village. No data were collected between August and December 1997 because the NSP conducted a national vitamin A survey during this period. In February 1998, a stratified multistage cluster sampling design was introduced to make the rural sample representative at the divisional and national levels. In this revised sampling scheme, data were collected from 300 households in four subdistricts in each of the six divisions of the country. These subdistricts were randomly selected and remained the same during each subsequent round of data collection. In each subdistrict, 10 mauza (smaller administrative units) were randomly selected, and within each mauza, 30 households were systematically sampled from one randomly selected village. In 2000, the sample size in each subdistrict was increased to 375 households by increasing the number of mauza from 10 to 15 and reducing the number of households sampled from each mauza from 30 to 25. Access to the Chittagong Hill Tracts was restricted at the time the two sampling procedures were implemented; thus, households in this area were not included. In each round of data collection, the sampling units were selected without replacement.
Data collection.
Data were collected by two-person field teams employed by the IPHN and NGO. A structured coded questionnaire was used to record data on children aged 6–59 mo, including anthropometric measurements, date of birth, sex, symptoms of night blindness, diarrhea and acute respiratory tract infection, breast-feeding and child feeding practices, and receipt of vitamin A capsules. The mother of the child or other adult member of the household was asked to provide information on the household’s composition, parental education, occupation of the main household earner, sanitary conditions, land ownership, food production and consumption, expenditure, exposure to natural disasters and domestic crises.
Data on the indicators used in the analysis described in this paper were collected as follows. The field teams measured and recorded the weight of each child aged 6–59 mo to a precision of 0.1 kg. Birth dates of the children were estimated using a calendar of local and national events. Z-scores of weight-for-age (underweight) were calculated using Anthro software (14 ), which uses the reference population of the United States National Center for Health Statistics and is recommended by the WHO (15 ). Children with Z-scores more than -2 SD below the reference median were classified as underweight. The total number of household members was obtained by asking the household respondent to count the number of people who lived together and ate from the same cooking pot. The respondent was also asked to recall the total amount (in kg) of rice consumed by the household during the previous 7 d from different sources, including a market, own production, relatives or friends and labor wages paid in kind; the number of days that any household members ate common nonrice foods in the previous 7 d, including dal (lentils), green leafy vegetables, yellow or orange fruit or vegetables, eggs and fish; and the amount of money that the household spent on food in the last 3 d. Data on the market price of rice were collected from traders in the villages in which the above-mentioned data were collected, and the mean value was calculated at the subdistrict level.
HKI provided training to new field teams, field supervisors and assistant field officers, and refresher training before each new round of data collection. During each round, a monitoring team from HKI visited all field sites to check and calibrate the equipment and supervise data collection. In addition, a quality control team from HKI revisited 5–10% of households without prior warning within 24 h of data collection by the field teams and recollected data on selected indicators, including anthropometric measurements. Data collected by these quality control teams were later compared with the data collected by the field teams to provide an assessment of the accuracy of the data.
Data management.
Data entry operators employed by the IPHN and each NGO entered the data from the questionnaire forms using a data entry/management software package developed by HKI. During data entry, a series of checks were made for keystroke errors, duplicate entries and to ensure that the data were collected and enumerated correctly. The data files from the IPHN and NGO were merged at the NSP/HKI office in Dhaka.
Data analysis.
The market price of rice and household food expenditure were converted to US$ using the government monthly exchange rates (16 ) to control for the devaluation of the taka, the currency of Bangladesh. Household food expenditure and the amount of rice consumed by the household were divided by the number of household members to obtain a per capita value and thereby control for the number of household members. Weekly expenditure on rice per capita was estimated by multiplying weekly rice consumption per capita in kg by rice price per kg; only rice that was purchased was included. Weekly expenditure on nonrice foods per capita was estimated by subtracting weekly expenditure on rice per capita from weekly expenditure on food per capita. Because the distribution of weekly nonrice expenditure per capita was negatively skewed, the data were transformed using natural logarithms before analysis.
Summary statistics were calculated for the data collected during June each year from 1992 to 2000, including means and 95% CI for normally distributed continuous variables and percentages and 95% CI for categorical variables. Bivariate correlations were used to examine the association between the percentage of children classified as underweight and mean rice prices, consumption and expenditure in June; the sample size for these analyses was 9, corresponding to the number of years for which the summary statistics were obtained. For data collected on nonrice food consumption in June 2000, differences between groups were examined using one-way ANOVA for continuous variables and 
2 for categorical variables. When ANOVA indicated a significant difference between the groups, a post-hoc multiple comparisons test for least significant differences was performed to determine which groups were significantly different. A P-value <0.05 was considered significant. Data analysis was conducted using SPSS for Windows version 7.5 (Chicago, IL).
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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The NSP collected data on the amount (in kg) of rice consumed during the previous week by household members beginning in August 1991. Weekly rice consumption per capita declined from 3.2 kg in June 1992 to 2.9 kg in June 2000 and did not appear to follow the large shifts in rice prices, which ranged from a low of US$ 0.21/kg in June 1993 to US$ 0.31/kg in June 1995 (Fig. 2 ). There was no association between rice price and weekly rice consumption per capita (r = 0.23, P = 0.55, n = 9).
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A comparison of demographic and socioeconomic characteristics of households sampled by the NSP in June 1997 and June 1998 did not reveal any discontinuities in the data that may have affected the analysis when the sampling design of the NSP was changed between 1997 and 1998. Furthermore, the results of the correlation analyses between the percentage of underweight children and the expenditure on rice and nonrice foods were similar if data from 1998 to 2000 were excluded: weekly expenditure on rice per capita, r = 0.88, P = 0.020, n = 6; the percentage of food expenditure spent on nonrice foods, r = -0.87, P = 0.023, n = 6; and weekly expenditure on nonrice foods per capita, r = -0.84, P = 0.037, n = 6.
To confirm that increased household expenditure on nonrice foods was associated with increased consumption of nonrice foods and a more diversified diet, we examined the relationship between household food expenditure on nonrice foods and the frequency with which household members consumed nonrice foods. The NSP collected data on the number of days that household members ate common nonrice foods in the previous week beginning August 1999. Households that ate dal (lentils), yellow or orange fruit or vegetables, eggs and fish most frequently during the previous week in June 2000 spent more on nonrice foods per capita than households that ate these foods least frequently (Fig. 5 , one-way ANOVA, n = 7530: dal, P < 0.001; green leafy vegetables, P = 0.038; yellow or orange fruit or vegetables, P < 0.001; eggs, P < 0.001; fish, P < 0.001). The number of nonrice foods consumed by the household at least once by any household member during the previous week provides an indicator of dietary diversity. Households with more diverse diets in June 2000 spent more on nonrice foods than households with less diverse diets (Fig. 6 , one-way ANOVA, P < 0.001, n = 7,530). When the data on the consumption of nonrice foods were analyzed separately for functionally landless (n = 4593) and landowning households (n = 2937), the associations represented in Figures 5 and 6 were also significant (P < 0.05).
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2, n = 7530: dal, P = 0.025; green leafy vegetables, P < 0.001; yellow or orange fruit or vegetables, P < 0.001; eggs, P < 0.001; fish, P = 0.023). The percentage of underweight children was also lower among households that had a more diverse diet, as indicated by the number of nonrice foods consumed by the household at least once by any household member during the previous week (2, P < 0.001, n = 7530). The latter finding was significant for both functionally landless (2, P < 0.001, n = 4593) and landowning (2, P = 0.009, n = 2937) households. |
DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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We draw the following conclusions from these analyses. When rice prices fall, households continue to consume a similar amount of rice; thus their expenditure on rice decreases. This allows households to spend more money on nonrice foods, and thereby to consume nonrice foods more frequently and to diversify their diet. Nonrice foods, particularly animal products, fruits, vegetables and oils, improve the quality of a rice-based diet because they tend to be a more concentrated source of micronutrients, higher quality protein and/or energy than rice. Because both the quantity and quality of the diet increase when households spend more on nonrice foods, the nutritional status of children improves.
To justify these conclusions, we must address possible limitations, sources of bias or lack of congruency in the analysis. First, the analysis used data from a series of cross-sectional surveys; thus, the statistical findings do not provide evidence of a cause and effect relationship between the price of rice and child nutritional status. There were general improvements in social and economic conditions in Bangladesh during the 1990s, and these developments may have caused the reduction in the percentage of underweight children. However, the data presented in Figures 3 and 4 indicate that the trend in the percentage of underweight children between 1992 and 2000 was not a simple downward trend, but exhibited considerable year-to-year fluctuation as well. The magnitude and direction of this fluctuation were similar to changes in household expenditure on rice and were correlated with the percentage of rice expenditure spent on nonrice foods. To our knowledge, there are no indicators of social and economic development in Bangladesh that followed a similar trend between 1992 and 2000. There are, however, unmeasured factors that cannot be ruled out, such as the effect of health and nutrition interventions during the 1990s. Nevertheless, a causal relationship between rice prices and child nutritional status is conceivable because changes in rice price can result in considerable savings, or losses, for poor rural households. Using the estimate of the rural population from the 1991 census, the large reduction in rice price between 1992 and 1993, which coincided with a large decrease in the percentage of underweight children, resulted in a saving of US$ 17 million/wk for the entire rural population. This saving amounts to US$ 884 million/y, which is considerably larger than the annual budgets of most health, nutrition and rural development programs; furthermore, the money went directly to the households themselves. Such savings increase real income and household purchasing power, important prerequisites for poverty reduction at the household level, and thereby increase the affordability of relatively expensive, nonrice foods.
It has previously been hypothesized (20 ) and demonstrated that the amount of money that households have available to spend on food, and do spend on food, determines the quantity and quality of foods consumed by children, thereby influencing growth. Data collected by the Nutrition and Health Surveillance System (NSS) in Indonesia after the economic crisis of the late 1990s also revealed an effect of rice price on dietary quality and nutritional status (21 ). The economic crisis led to a rapid increase in the price of rice which, together with rising unemployment, reduced the real income of households. Rice consumption did not change, but there was reduced consumption of relatively expensive nonrice food items, including animal products. The NSS documented a rise in the prevalence of anemia in preschool children, a proxy for micronutrient status, and a rise in the prevalence of chronic energy deficiency (body mass index <18.5 kg/m2) among mothers and adolescents (21 ,22 ). A study in Peru reported that the consumption of staple foods by children remained almost constant as household expenditure on food increased, but there was a large increase in the consumption of animal products, fruits and vegetables (23 ). The authors argued that households make quantitative and qualitative improvements in the diets of their children as more money became available to spend on food (23 ). Observational studies in Africa and South America have found that the growth of children increased with the consumption of animal products and fruits (24 ) and with dietary diversity (25 ).
Second, the sampling design of the NSP changed between 1997 and 1998. We argue that this change is unlikely to have affected the analysis because there were no discontinuities in indicators of household demography and socioeconomic status, and the results of the correlation analyses were similar if data collected between 1998 and 2000 were excluded.
Third, there was no significant change in the percentage of underweight children between 1994 and 1995 or between 1997 and 1998, despite a significant increase in weekly rice expenditure per capita (Fig. 3) . However, the percentage of food expenditure spent on rice did not change significantly between these years (Fig. 4) and there was a temporary halt in the otherwise downward trend in the percentage of underweight children.
Fourth, the analysis assumes that the dietary intake of children is directly affected by variation in food expenditure and consumption at the household level. Intrahousehold distribution of food favors adult men and boys in Bangladesh (26 ), and it is likely that young children, who are growing rapidly and have proportionately higher energy and nutrient requirements than other household members, and mothers, whose quality of breast-milk is affected by dietary intake, are most affected when food is scarce. Finally, the analysis assumes that there is a very short lag period between a change in rice price and a change in the percentage of child underweight. This is plausible because the scale of poverty, household food insecurity and child malnutrition is very severe in Bangladesh (11 ,27 ,28 ); thus, child nutritional status is likely to respond immediately to factors affecting household purchasing power.
The association of child underweight with expenditure on rice and nonrice foods suggests that macroeconomic food policies that affect rice prices have the potential to influence child nutritional status in Bangladesh. Although the fall in rice prices between 1992 and 1993 was the result of bumper rice harvests in 1993, and not a policy or program intervention, there were several changes to macroeconomic food policy that affected rice prices in rural Bangladesh during the last decade. Liberalization of the private rice trade in Bangladesh in 1994 helped to ensure the availability of rice and to stabilize prices after poor harvests in 1995/6, 1997/8 and 1998/9 (29 ,30 ). After a devastating flood in 1998, which covered two thirds of the country and damaged the aus rice crop in August 1988 and aman rice crop in December 1998 to January 1999, the government introduced incentives to private sector rice importers, including a policy of tax-free private food grain imports, rapid clearance of rice through customs and limitations on open market sales (30 ). It has been estimated that these actions, together with liberalization of the private food grain trade, enabled the government to avert a 40–60% rise in the price of rice after the flood (30 ).
In conclusion, findings from the NSP in rural Bangladesh suggest that between 1992 and 2000, child nutritional status improved when rice prices fell because households were able to purchase and consume more nonrice foods, and thereby increase the quantity and quality of their diet. On the basis of these findings, we hypothesize that macroeconomic food policies that keep the price of food staples low can contribute toward reducing the percentage of underweight children.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Manuscript received 29 April 2002. Initial review completed 17 June 2002. Revision accepted 14 January 2003.
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LITERATURE CITED |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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30. Dorosh, P. A. (1999) The Determination of Rice Prices in Bangladesh: Supply Shocks, Trade Liberalization and Cross-Border Trade. FMRSP Working Paper No. 2 1999 Food Management and Research Support Project, Ministry of Food, Government of the People’s Republic of Bangladesh and International Food Policy Research Institute Dhaka, Bangladesh.
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