Food consumption, energy and nutrient intake and nutritional status in ...

European Journal of Clinical Nutrition (2003) 57, 586–594 ß 2003 Nature Publishing Group All rights reserved 0954–3007/03 $25.00 www.nature.com/ejcn

ORIGINAL COMMUNICATION Food consumption, energy and nutrient intake and nutritional status in rural Bangladesh: changes from 1981 – 1982 to 1995 – 96 O Hels1*, N Hassan2, I Tetens1 and S Haraksingh Thilsted1 1 2

Research Department of Human Nutrition, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark; and Institute of Nutrition and Food Science, University of Dhaka, Dhaka, Bangladesh

Objective: To determine and evaluate changes in nutritional status, food consumption, energy and nutrient intake in rural Bangladesh, using appropriate statistical analyses. Design: Repeated cross-sectional surveys. Two seasons in 1981 – 1982 and 1995 – 1996. Setting: Two villages with different production patterns. Subjects: Anthropometric measurements of 1883 individuals, food consumption data of 404 households. Methods: Repeated measurements of one-day food weighing and anthropometry in two seasons in 1981 – 1982 and 1995 – 1996. Mixed model analyses were used to evaluate and quantify temporal changes and their interactions with determinants. Results: Prevalence of underweight children decreased from 82 to 70% (P ¼ 0.015), wasted children from 34% to 18% (P ¼ 0.009) and chronic energy deficient adults decreased from 78 to 64% (P < 0.0001). Intake of fish and green leafy vegetables increased from (l.s. mean s.e.) 23 3.0 to 40 1.8 g=person=day (P < 0.001) and from 28 4.5 to 41 2.7 g=person=day (P ¼ 0.019), respectively. Rice intake remained unchanged: 463 12 g raw=person=day in 1981 – 1982 and 450 7.3 g raw=person=day in 1995 – 1996 (P ¼ 0.355). Calcium and iron intakes increased by 40% (P < 0.0001) and 16% (P ¼ 0.0002), respectively, whereas vitamin A intake remained unchanged. Conclusions: Nutritional status improved and intakes of nutrient dense food groups, fat, iron and calcium increased from 1981 – 1982 to 1995 – 1996. Sponsorship: Supported by the Danish Council for Research in Developing Countries, the Bilateral Programme for Enhancement of Research Capacity in Developing Countries (ENRECA), Ministry of Foreign Affairs, Denmark and the Ford Foundation. European Journal of Clinical Nutrition (2003) 57, 586 – 594. doi:10.1038=sj.ejcn.1601567 Keywords: dietary trends; temporal change; nutritional status; mixed model analysis; Bangladesh

Introduction *Correspondence: O Hels, Research Department of Human Nutrition, The Royal Veterinary and Agricultural University, Rolighedsvej 30, 1958 Frederiksberg C, Denmark. E-mail: [email protected] Guarantor: O Hels. Contributors: OH performed the statistical modelling and analyses and wrote the first draft of the manuscript. SHT co-conceived the study and was involved in writing and revising the manuscript. IT was involved in the revisions of the manuscript and in the data processing. NH coconceived the study and was responsible for field work and data collection. All contributors were involved in preparing the final draft of the manuscript. Received 7 January 2002; revised 4 April 2002; accepted 17 June 2002

Since the 1996 World Food Summit, efforts towards alleviating food insecurity in developing countries have been strengthened. Accurate and relevant information generated from periodic and systematic measurements of food production and consumption and nutritional status provides a good foundation for estimating trends as a basis for taking appropriate actions to achieve food security. To evaluate the effects of political actions, as well as nutrition interventions and changes of food production systems (eg agriculture and aquaculture), changes in food consumption need to be monitored at an appropriate level. Two main types of dietary data which can be used for this purpose at a population level

Food consumption in rural Bangladesh O Hels et al

587 are obtained from national estimates of the food supply and results of dietary surveys involving a larger or smaller number of households or individuals sampled from the population. Some developed countries have established or conducted regular dietary surveys of representative population samples. These are sometimes carried out 5 or 10 y apart or done continuously (Pietinen & Ovaskainen, 1994; Briefel, 1994; Turrini et al, 2001; Kim et al, 2000). Studies in developed countries have also either used national food supply data alone to monitor national developments (Zilidis, 1993; Zizza, 1997) or compared national food supply data and dietary surveys (Crane et al, 1992; Rodriguez-Artalejo et al, 1996; Dobson et al, 1997; Harnack et al, 2000). It is recognized that surveys and food supply data provide partially different and sometimes inconsistent information. In developing countries, data from national dietary surveys are generally scarce. Results are often published in the form of reports that are not easily accessible. Many developing countries rely to a certain extent on food supply data and household budget surveys which may be combined with minor surveys on food consumption and=or health in the monitoring of the food security situation and estimation of changes and trends with time. The costs of regular dietary surveys of representative population samples may be prohibitive for many developing countries when recognized determinants of food consumption and nutritional status such as seasonality and regional differences are also considered. Lower-cost methodology procedures in developing countries such as data from minor periodic food consumption surveys analysed with advanced statistical methods can play a role in quantifying variation and estimates in trends in food security. In Bangladesh, the first national food consumption survey was carried out in 1962 – 1964, followed by two more in 1975 – 1976 and 1981 – 1982 (Hassan & Ahmad, 1984). The latest large-scale food consumption survey in Bangladesh was undertaken in 1995 – 1996 (Jahan & Hossain, 1998). Results from these surveys suggest that nutritional status improved from 1975 – 1976 to 1981 – 1982 but remained unchanged during the last two decades and intakes of energy and macronutrients in rural Bangladesh declined from 1962 – 1964 to 1981 – 1982 and 1995 – 1996. Intakes of iron, calcium and vitamin A declined between 1962 – 1964 and 1981 – 1982 but increased from 1981 – 1982 to 1995 – 1996 to a level similar to that in 1962 – 1964. Anaemia and vitamin A deficiency have remained unchanged during the last three decades and are persisting to be public health problems in Bangladesh (Ahmed, 1999, 2000). Although the overall food and nutrition situation in Bangladesh and other South-Asian countries has been described (Gopalan, 1996; FAO, 2000), changes in time have not been tested with the use of appropriate statistical methods. The objective of this study is to determine and evaluate changes in nutritional status, food consumption, energy and nutrient intake in two rural villages in Bangladesh by use of

appropriate statistical analyses, which adjust for seasonal, locational and socioeconomic variations.

Methods Study area The field work was conducted in two selected villages in Bangladesh: Falshatia and Jorbaria. Falshatia, in the Manikganj thana (subdistrict) is a flooded, double-cropped area, west of Dhaka and Jorbaria. Mymensingh is a non-flooded, triple-cropped area, north-east of Dhaka. In the Manikganj village, the agricultural production system can be characterized as traditional, whereas in the Mymensingh village the farming system practised can be characterized as modern, with the use of high-yielding rice varieties, irrigation, fertilizers and pesticides. In Bangladesh, the three rice harvest seasons comprise the Aman (November – December), the Aus (March – April), and the Boro (May – June). The Aman harvest was traditionally the most important, but in areas where high-yielding rice varieties and modern technology have been introduced, the Boro harvest has become more important during the last decade. The present study was undertaken to cover two seasons with respect to rice production: the lean season which includes October – November and the peak season which includes December – March. The study was conducted in 1981 – 1982 and 1995 – 1996.

Study population and sampling design In 1981 – 1982, the study population comprised 50 households in each village in both seasons (October – November 1981 and December 1981 – January 1982) and in 1995 – 1996, 152 households in each village in both seasons (October – November 1995 and January – March 96). The data collected in 1981 – 1982 was a part of the national nutrition survey of rural Bangladesh in 1981 – 1982 (Ahmad & Hassan, 1983). In 1995 – 1996, households were sampled and data collected using the same technique as in 1981 – 1982. The households were selected from four socioeconomic subgroups following the probability proportion to size method. The four subgroups were based on the Bangladesh rural population tax system: group A is the poorest, most certainly landless and not required to pay any local tax; group B is the less poor and pays a token tax. Group C may be regarded as a rural upper-middle class and pay an appreciable amount of tax, while group D is the richest group and pays the highest proportion of tax. In Manikganj, the proportions of sampled households in the two wealthiest groups were 14% in 1981 – 1982 and 36% in 1995 – 1996. In Mymensingh, the proportions of the wealthiest groups were 24% in 1981 – 1982 and 10% in 1995 – 1996, perhaps due to the concentration of landholding on fewer households. Of the 100 households studied in 1981 – 1982, data were missing from one household in December – January. Of the 304 households studied in October – November 1995, data were missing from 13 households in January – March. The European Journal of Clinical Nutrition


588 study covered a total of 510 individuals in October – November 1981, 512 individuals in December – January 1981 – 1982, 1373 individuals in October – November 1995 and 1281 individuals in January – March 1996. The characteristics of the surveyed households are shown in Table 1. Although the average household size was larger in 1981 – 1982 than in 1995 – 1996, the difference was not significant. The average number of consumption units for each season and year ranged from 4.4 to 5.3 and decreased from 5.2 (95% CI 4.9 – 5.6) in 1981 – 1982 to 4.5 (95% CI 4.3 – 4.7) in 1995 – 1996.

and 1995 – 1996 (Darnton-Hill et al, 1988). The foods consumed were divided into selected food groups on the basis of the above food composition table with the following modifications: pulses and legumes, green leafy vegetables and vegetables were pooled in the food group of vegetables; fats, oils and oil seeds were pooled in the food group of fats and oils and fish, meat, eggs, milk and milk products were pooled in the group of animal products. Fish were divided into small and large fish, of which all the small fish are indigenous and most of the large fish are cultured.

Dietary intake Dietary intakes of all members of the selected households were obtained by 24 h food weighing. Training of investigators comprised practising the techniques of food weighing and recording at the Institute of Nutrition and Food Science, University of Dhaka, Bangladesh for 2 weeks, followed by a pilot survey in a village close to Dhaka city. Exactly the same method was used in 1981 – 1982 and 1995 – 1996. All food that went into the household cooking pots was weighed as raw weight. Intake per person was calculated at household level by dividing the total intake of each single food in every household by the total number of consumption units in the household. An individual present at every meal within the one day period was counted as a full-time consumer, with the value of one consumption unit. All family members, including children and breast-fed infants, were valued similarly in terms of consumption unit. Arithmetical adjustments of the household’s number of consumption units were made for household members who were partially absent. If a household member was absent at one out of the usual three meals consumed in the household, twothirds of a consumption unit, instead of one, was allocated to this member (FAO, 1967). To avoid changes in energy and nutrient intakes caused by differences in food composition values, the values of all foods were computed using the same food composition table pertinent for the Bangladeshi diet for both 1981 – 1982

Anthropometry Height, weight and mid upper arm circumference (MUAC) of all members of the selected households were obtained by house visits during both seasons in 1981 – 1982 and 1995 – 1996. A portable beam balance was used to measure weight to the nearest 0.5 kg after removal of shoes and heavy clothing. The balances were frequently checked using standard weights. Two types of wooden scales were used for measuring height: one for recording recumbent length to the nearest cm of children under 24 months of age and the other for height to the nearest cm of older children and adults. The investigators collecting the anthropometric data underwent extensive training. The nutritional status of children between 6 and 59 months was expressed as height for age, chosen as the indicator for chronic nutritional status. Weight for height and weight for age were chosen as indicators for acute nutritional status and current malnutrition. Malnourished children were defined as those below 72 s.d. of the median of the WHO’s height-for-age (stunting), weight-for-height (wasting) and weight-for-age (underweight) values, respectively (WHO, 1983). The nutritional status of adults (here defined as above 18 y of age) was expressed as body mass index (BMI) and calculated as weight=height2 (kg=m2). The international criteria on classification of chronic energy deficiency (CED) was employed (BMI < 18.5 kg=m2).

Table 1

Characteristics of surveyed households in 1981 – 1982 and 1995 – 1996 in Bangladesh 1981 – 1982 October – November December – January

Number of households Household size, mean (s.d.) Consumption units, mean (s.d.) Age groups: 0–9 y 10 – 18 y 19 – 50 y > 50 y Pregnant females (%) Lactating females (%)

European Journal of Clinical Nutrition

1995 – 1996 October – November January – March

100 5.6 (2.8) 5.2 (2.3)

99 5.5 (3.1) 5.3 (2.8)

304 5.0 (2.0) 4.6 (2.3)

288 5.0 (2.1) 4.4 (2.4)

27% 25% 37% 11% 6% 25%

29% 25% 35% 11% 5% 26%

29% 19% 40% 12% 5% 21%

29% 20% 39% 12% 5% 19%


589 Nineteen children in 1995 – 1996 and two in 1981 – 1982 were excluded from the analyses of nutritional status due to recorded negative height difference between seasons. Because of unrealistic seasonal height differences, two adults were excluded in 1995 – 1996.

transform intakes of protein, fat iron, calcium, vitamin A and the food groups fats and oils and spices. Least square means (l.s. means) and standard errors (s.e.) were estimated and transformed back where necessary before presentation. Significance level was set to 0.05 for main effects, 0.01 for two factor interactions and 0.001 for three factor interaction to reduce probability of type I error. Only P-values for main fixed effects, significant interactions and the three factor interaction between year, village and season are presented.

Data analysis All analyses were performed with the Statistical Analysis Systems statistical software package version 8.1 (SAS, 2000). Prevalence of stunting, wasting and underweight among children and CED among adults were analysed by logistic regressions using the SAS procedure GENMOD. Year, village, season, gender and socioeconomic group were included as independent fixed variables. Individuals nested within both year, village and household and households nested within year and village were included as random effects in the statistical model. MUAC for children and adults and BMI for adults were analysed by ANOVA as described below. All main effects and two factor interactions between fixed effects were tested. Only P-values for year and significant fixed effects are presented. Univariate analyses of variance (ANOVA) were performed in the procedure MIXED (Littell et al, 1996). In the statistical model, consumption of food by food group, was evaluated as the dependent variable. Year, village, season and socioeconomic group were included as independent fixed variables. Households nested within both year and village were included as random effect in the statistical model to take into account that repeated measures were done in households within years but the households between years were different. All main effects were evaluated as well as two- and three-factor interactions between all fixed effects. To obtain sufficient numbers of individuals in each socioeconomic group, the two wealthiest groups were pooled (group C and D). Preliminary statistics showed that the two wealthiest groups were not significantly different. Homogeneity of variance and normal distribution among random effects were investigated by plots and histograms of residuals. Shapiro – Wilk’s test for normal distribution was performed. The investigations showed it necessary to log-

Results Nutritional status The prevalence of wasting and underweight children aged 6 – 59 months decreased from 1981 – 1982 to 1995 – 1996 (Table 2). MUAC increased significantly from 1981 – 1982 to 1995 – 1996 and an increase of 2.6 1.0 mm (mean s.e.) was detected between the two seasons in both years. Boys had a 4.4 1.8 mm higher MUAC (mean s.e.) than girls (P ¼ 0.015). The seasonal variation of wasting differed in the years studied: the prevalence was similar in both seasons in 1981 – 1982 (P ¼ 0.654), whereas it decreased from 23 to 13% in 1995 – 1996 (P < 0.010). Taking into consideration both years and seasons, the prevalence of underweight was 69% in the Manikganj village and 78% in the Mymensingh village (P ¼ 0.016), and the prevalence of wasting was 19 and 29%, respectively (P ¼ 0.062). Nutritional status expressed as the prevalence of CED as well as BMI and MUAC for adults improved from 1981 – 1982 to 1995 – 1996 by a decreased prevalence of 14%, increased BMI of 1.0 0.2 kg=m2 (mean s.e.) and increased MUAC of 8.8 1.7 mm (mean s.e.; Table 3). The Manikganj village had the best nutritional status (63% CED, BMI ¼ 18.2 kg=m2 and MUAC ¼ 229 mm) compared to the Mymensingh village (72% CED, BMI ¼ 17.4 kg=m2 and MUAC ¼ 226 mm). Both BMI and MUAC were highest for the wealthiest groups, which also had the lowest prevalence of CED. No significant differences between men and women were seen other than MUAC in women was 14 1.2 mm lower MUAC (mean s.e.) than that in men (P < 0.001).

Table 2 MUAC, prevalence and OR of stunting, wasting and underweight among children 6 – 59 months in 1981 – 1982 compared with 1995 – 1996 Year

a

MUAC (mm) Stuntingb (height-for-age < 72 s.d.)c Wastingd (weight-for-height < 72 s.d.)c e

Underweight (weight-for-age < 72 s.d.) a

c

Estimate

1981 – 1982, n ¼ 65

1995 – 1996, n ¼ 149

l.s. mean (s.e.) Prevalence OR (95%CI) Prevalence OR (95%CI) Prevalence OR (95%CI)

133 (1.5) 74 % 1.4 (0.7 – 2.6) 34 % 3.2 (1.3 – 3.9) 82 % 2.1 (1.1 – 3.8)

139 (1.5) 68 % reference 18 % reference 70 % reference

b

c

d

Year, P ¼ 0.003; season, P ¼ 0.010, gender, P ¼ 0.015. Year, P ¼ 0.267. Of WHO reference median. Year, e P ¼ 0.009; season, P ¼ 0.053; village, P ¼ 0.016, yearseason, P < 0.018. Year P ¼ 0.015.



590 Table 3 Prevalence of CED, BMI (kg=m2) and MUAC (mm) of non pregnant and non lactating adults over 18 y of age in 1981 – 1982 and 1995 – 1996 Year

a

CED (BMI > 18.5 kg=m BMIb (kg=m2) MUACc (mm)

2

Estimate

1981 – 1982, n ¼ 181

1995 – 1996, n ¼ 708

Prevalence OR (95%CI) l.s. mean (s.e.) l.s. mean (s.e.)

78% 2.4 (1.7 – 3.3) 17.3 (0.18) 223 (1.5)

64% reference 18.3 (0.11) 232 (0.9)

a

Year, P < 0.001; season, P ¼ 0.001; socioeconomic group, P ¼ 0.006; village, yearseason, P ¼ 0.008; villagesocioeconomic group, P ¼ 0.012. bYear, season, P < 0.001; socioeconomic group, P ¼ 0.018, village, P < 0.001. cYear, season, P < 0.001; socioeconomic group, P < 0.001; village, P ¼ 0.013; gender,

Food, energy and nutrient intakes Mean intakes of food groups (g=day) are shown in Table 4 and mean intakes of energy and nutrients are shown in Table 5. There were no overall significant differences between years, seasons and villages combined in food, energy and nutrient intakes. A statistically significant increased intake of food from 1981 – 1982 to 1995 – 1996 was seen for most food groups except cereals (P ¼ 0.123), rice (P ¼ 0.351), fruit and miscellaneous foods. The intake of fish nearly doubled from 1981 – 1982 to 1995 – 1996 while the proportion of households eating fish increased from 70% (61% in the Manikganj village and 80% in the Mymensingh village) to 82%. Both the frequency of eating large and small fish increased, from 29 to 44% and from 48 to 57%, respectively, from 1981 – 1982 to 1995 – 1996. The seasons covered were not seasons for fruit, and the fruit intake was accordingly low (6.5 1.0 g=person= day), with no significant differences. Miscellaneous foods mainly comprised sugar and sweets with no significant differences in intakes (8.6 1.3 g=person=day). The intakes of fat, iron and calcium increased from 1981 – 1982 to 1995 – 1996, whereas the intakes of energy and other nutrients were similar (Table 5). Intake of all food groups, energy and nutrients increased with increasing socioeconomic group. The seasonal variation in the intake of vegetables, energy, protein, carbohydrates and iron was different in 1995 – 1996 compared with 1981 – 1982. In 1981 – 1982, the intakes remained unchanged between seasons whereas in 1995 – 1996, they increased significantly from October – November to January – March, although there were no significant differences in comparing the intakes in October – November between the years. The intake of vegetables almost doubled from October – November to December – March. Consumption of animal foods and fish was lowest in December – March. Seasonal variation in the frequency of eating fish and the intake of roots and tubers, vegetables, green leafy vegetables, spices, energy and macronutrients were different for the two villages. In the Mymensingh village, the increase in vegetables, energy and macronutrients from October – November to December – March was significantly higher compared with the increase in the Manikganj village, although the intakes in the two villages in October – November were similar. European Journal of Clinical Nutrition

P ¼ 0.017; P < 0.001; P < 0.001; P < 0.001.

Intakes of roots and tubers nearly tripled and green leafy vegetables doubled from October – November to December – March in the Manikganj village. In the Mymensingh village, the opposite tendency was detected: a significant reduction in intakes of both roots and tubers and green leafy vegetables. However, the proportion of households eating green leafy vegetables on the specific day measured in the Manikganj village was 49% in October – November and 33% in December – March, compared with 33% and 55%, respectively, in the Mymensingh village.

Discussion Nutritional status Although the present study showed that nutritional status improved from 1981 – 1982 to 1995 – 1996, the prevalence of chronically malnourished children under 5 years and CED adults over 18 y was still high in 1995 – 1996. The crude mean values for MUAC, BMI and estimated prevalence of malnutrition found in other Bangladeshi rural studies (BBS, 1997; Jahan & Hossain, 1998) fall within the 95% confidence intervals of values found in this study. The improvement in nutritional status from 1981 – 1982 to 1995 – 1996 was similar for both socioeconomic groups. Better nutritional status in both children and adults was seen in the sample population in Manikganj village with traditional agricultural technology compared to that in Mymensingh with modern technology. Since a larger proportion of the households belonged to the wealthier group in Manikganj village, this may have resulted in a better nutritional status. In addition, the use of high-yielding varieties of rice resulted in an increased intake of rice and energy in Mymensingh, but at the same time, the workload with respect to irrigation, use of fertilizers and pesticides may have increased the physical activity. The increased energy intake in adults may not have compensated for the increased physical activity. Some studies have reported regional differences in the prevalence of malnourished children (Ahmed, 1993; Jahan & Hossain, 1998), but the differences were not statistically tested. Bangladesh Bureau of Statistics (BBS, 1997) reported

484 451 206 6 18 46 37 3 3 3 1 764

(20) (21) (18) (8.6) (9.6) (9.0) (5.1) (1.8) (0.9) (3.8) (5.0) (36)

459 444 144 43 41 22 15 2 3 1 2 675

(21) (21) (18) (8.7) (9.6) (9.1) (5.2) (1.8) (0.9) (3.8) (5.0) (37)

419 399 134 28 43 75 52 7 5 7 10 701

(12) (12) (10) (4.9) (5.4) (5.1) (2.9) (1.0) (0.5) (2.2) (2.8) (21)

474 454 215 49 101 62 37 5 6 7 13 887

(12) (12) (10) (5.0) (5.6) (5.3) (3.0) (1.0) (0.5) (2.2) (2.9) (21)

475 446 88 44 51 40 24 4 4 3 2 667

(20) (21) (18) (8.6) (9.5) (9.0) (5.1) (1.8) (0.9) (3.8) (5.0) (36)

533 513 120 17 18 30 16 2 2 11 12 727

(20) (21) (18) (8.6) (9.5) (9.0) (5.1) (1.8) (0.9) (3.8) (5.0) (36)

448 446 105 46 64 72 37 10 8 6 5 719

(12) (13) (11) (5.1) (5.6) (5.4) (3.0) (1.1) (0.5) (2.2) (2.9) (22)

514 502 258 37 37 69 30 9 6 9 11 914

(12) (13) (11) (5.2) (5.8) (5.5) (3.1) (1.1) (0.5) (2.3) (3.0) (22)

0.064 0.069 0.555 0.084 0.170 0.817 0.628 0.583 0.814 0.521 0.604 0.037

(MJ=day) (g=day) (g=day) (g=day) (mg=day) (mg=day) (IU=day)

7.9 9.0 48 397 24 335 2017

(0.4) (1.3) (2.3) (17) (1.6) (34) (339)

7.4 7.2 43 378 22 189 1655

(0.4) (1.3) (2.3) (17) (1.6) (34) (342)

7.5 13 44 362 24 339 1365

(0.2) (0.8) (1.3) (9.8) (0.9) (19) (193)

8.5 12 48 415 29 348 1938

(0.2) (0.8) (1.4) (10) (0.9) (20) (198)

7.9 8.6 47 392 26 272 2322

(0.4) (1.3) (2.3) (17) (1.6) (34) (337)

8.6 9.2 53 437 22 259 1043

(0.4) (1.3) (2.3) (17) (1.6) (34) (341)

8.0 15 46 390 25 387 1773

(0.2) (0.8) (1.4) (10) (0.9) (20) (200)

9.2 18 54 448 29 398 1553

(0.2) (0.8) (1.4) (11) (1.0) (20) (206)

0.115 0.872 0.141 0.066 0.910 0.011 0.455

a Pyearseasonvillage. Other significant P-values: Pyear < 0.05 for fat, iron and calcium. Pseason < 0.05 for energy, fat, protein, carbohydrates and iron. Pvillage < 0.05 for energy, fat, protein, carbohydates and iron. Psocioecnomic groups < 0.05 energy, fat, protein, carbohydates and iron. Pseasonvillage < 0.01 for energy, fat, protein and carbohydates. Pyearseason < 0.01 for energy, protein, carbohydates and calcium.

Energy Fat Protein Carbohydrates Iron Calcium Vitamin A

Manikganj Mymensingh 1981 – 1982 1995 – 1996 1981 – 1982 1995 – 1996 October – November December – January October – November January – March October – November December – January October – November January – March a n ¼ 50 n ¼ 49 n ¼ 152 n ¼ 145 n ¼ 50 n ¼ 50 n ¼ 152 n ¼ 143 P-value

Estimated daily intakes of energy and nutrients per consumption unit in sampled households in 1981 – 1982 and 1995 – 1996 by season and village (l.s. mean (s.e.))

Food group

Table 5

Pyearseasonvillage. Other significant P-values: Pyear < 0.05 for vegetables, green leafy vegetables, roots and tubers, animal foods, fish, fats and oils, spices and total intake. Pseason < 0.05 for all food groups except vegetables. Pvillage < 0.05 for cereals, rice, roots and tubers, animal foods, fish and fats and oils. Psocioecnomic groups < 0.05 for cereals, rice, animal food, fish, fats and oils, spices and total intake. Pseasonvillage < 0.01 for vegetables, green leafy vegetables and fats and oils. Pyearseason < 0.01 for vegetables and total intake. Pyearvillage < 0.01 for roots and tubers.

a

Cereals Rice Vegetables (total) Green leafy vegetables Roots and tubers Animal foods (total) Fish Fats and Oils Spices Fruits Miscellaneous Total intake

Food group (g=day)

Manikganj Mymensingh 1981 – 1982 1995 – 1996 1981 – 1982 1995 – 1996 October – November December – January October – November January – March October – November December – January October – November January – March n ¼ 50 n ¼ 49 n ¼ 152 n ¼ 145 n ¼ 50 n ¼ 50 n ¼ 152 n ¼ 143 P-valuea

Table 4 Estimated daily intakes of selected food groups per consumption unit in sampled households in 1981 – 1982 and 1995 – 1996 by season and village (l.s. mean (s.e.))


591



592 an unchanged prevalence of wasted rural children from 1985 – 1986 to 1995 – 1996, a larger reduction of stunting and a similar reduction in underweight as compared with this study. From the reported values, it is only possible to calculate difference of crude mean values of MUAC, BMI and prevalence of malnutrition in the estimation of change, which is insufficient for evaluating whether the change with time is statistically significant or whether it interacts with other factors which can affect change such as seasonality and regional variation. Therefore, the results of this study are better than those from previous studies because appropriate adjustments were made for seasonal, locational and socioeconomic variations.

Food, energy and nutrient intakes Total intakes of vegetables, intakes of green leafy vegetables, roots and tubers, total animal foods, fish, fats and oils and spices all contributed to an increased total intake of food from 1981 – 1982 to 1995 – 1996. At the same time, a nonsignificant decline in the intakes of cereals, rice, energy and carbohydrates was found, and thus these intakes remained similar in 1995 – 1996 compared with 1981 – 1982 in the two villages surveyed. Two rural villages in Bangladesh are insufficient to represent the total rural part of the country. The villages, however, were purpose chosen for their agricultural production systems and proneness to flooding and the results obtained therefore represent areas of the rural Bangladesh with these characteristics. In comparison, the ranges of intakes of vegetables, animal foods, energy and most nutrients were found to be higher in the present study compared with the 1995 – 1996 large-scale nutrition survey (Jahan & Hossain, 1998), perhaps because the large-scale nutrition survey included more locations and seasons than the present study. Nevertheless, the trends of increased intakes of roots and tubers, animal foods, fats and oils, fat and calcium and decreased intakes of cereals and rice from 1981 – 1982 to 1995 – 1996 described by Jahan and Hossain (1998) are in agreement with the trends found in the present study. From FAO’s food balance sheets (FAO, 2001), it is found that the domestic utilization of rice as food per capita increased from 143 kg raw rice=year in 1981 – 1982 to 146 and 152 kg raw rice=y in 1995 and 1996, respectively. Seasonal and regional variation in rice production limits national rice production as a single measure of availability for the sampled population. Other influential measures however, such as falling rice prices and increased income, tend to point towards increased availability of rice (Ahmed, 1993; Delgado et al, 1999). The increased availability of rice and an unchanged intake found in the present study suggest that rice intake in rural Bangladesh has reached and continues to be at a satiation point, although seasonal variation and minor variation by location still exist. The findings of both better nutritional status and increased consumption of nutrient-dense foods such as European Journal of Clinical Nutrition

vegetables, green leafy vegetables and fish point in the direction of an improved diet in the two rural villages. However, the increased intakes of some food groups, total food intake and fat did not result in a significant increased energy intake. That the increase in energy intake was insignificant while nutritional status improved, suggests that other determinants for nutritional status than energy intake have changed. Improvement of vaccination programmes for children and delivery of primary health care facilities between 1981 – 1982 and 1995 – 1996 might have improved public health and thereby contributed to the improved nutritional status despite unchanged energy intake. Other factors contributing to the improved nutritional status despite unchanged energy intake may have been decreased energy expenditure due to decreased physical activity between 1981 – 1982 and 1995 – 1996. However, there are no data on changes in physical activity available to illustrate this point. To improve adequacy of energy and nutrients in accordance with the goal of the World Food Summit, much larger increases are needed. If micronutrients are considered, the estimated intakes of calcium and iron increased significantly by 40% (P < 0.0001) and 16% (P ¼ 0.0002), respectively, whereas vitamin A intake remained unchanged. These changes remain valid even though they are based on the local food composition table, in which there are missing values for some foods as well as too high values for the iron content of some foods. Micronutrient malnutrition still remains a major problem in rural Bangladesh (Ahmed, 1999, 2000) and the detected improvements could be taken further by focussing on the potential of important food groups rich in micronutrients and increased intakes, in amounts as well as frequencies. Small fish, of which some are very high in micronutrient contents (Roos, 2001), and green leafy vegetables are good examples. At the same time, these foods can increase bioavailability of minerals by supplying increased amounts of enhancers such as fish protein, vitamin C and vitamin A (Garcı´a-Casal et al, 1998; Hallberg & Hulthen, 2000). Looking at the seasonal differences by location in relation to differences in production patterns, minimizing seasonal differences by extending the growing season of nutrient dense foods may also be a possibility for further improvement.

Study methodology — strengths and limitations As in the major food consumption surveys in rural Bangladesh, the method used for assessing food and macronutrient intakes at the two points in time was one-day food weighing. Recognized determinants of food consumption and nutritional status such as seasonality, regional variation, socioeconomy and their interactions were considered in this study, improving the estimates and tests by making appropriate adjustments. This has not been done before in a developing country. Even the most recent large-scale food consumption surveys from other countries such as the Baltic


593 Republics (Pomerleau et al, 2001) and Italy (Turrini et al, 2001) have not quantified variation in the evaluation in intakes among recognized determinants, although they are to some extent considered by calculating simple averages and=or medians. However, some studies have compared differences in crude mean values with or without standard errors at different points in time, supplemented with estimates from food supply data in order to evaluate trends (Dobson et al, 1997; Harnack et al, 2000; Kim et al, 2000). One of the strengths of the above studies is the large number of households=individuals included and the representativeness. The comparisons done, however, lack proper statistical modelling which utilizes the design of the surveys and quantifies and evaluates variation. The reported decline in rice, energy and carbohydrates found through surveys (Hassan & Ahmad 1984; BBS, 1997; Jahan & Hossain, 1998) and detected trends in food production (Gopalan, 1996) may perhaps be erroneous and this uncertainty could have been avoided if an appropriate statistical model, such as the one used in this study, was employed. The statistical models and analyses used in the present study could have been strengthened if certain considerations were taken into account. By the definition of consumption unit, all individuals were valued equally (FAO, 1967) and the dependent variables in the overall statistical model were adjusted for household size and absent household members. In the comparison of food consumption, energy and nutrient intakes in 1981 – 1982 and 1995 – 1996, the error introduced by use of this definition is assumed to be of minor importance as the household size and composition remained unchanged. The decrease in the average number of consumption units per household between years, however, suggested a change in meal pattern towards an increased number of meals being taken outside the household. Data on meals taken outside the home were not included in this study, but adjusted for by the use of consumption units. An improvement of the method used can be achieved by collecting information on foods eaten outside home and including it in the food consumption data as well as adjusting the consumption unit so that age and gender of household members are taken into account. In order to compare results from different surveys, the same method of adjustment must be used. Such a standard has not yet been developed. In this study, the use of mixed model analyses showed that there was an improved nutritional status, and increased intakes of nutrient dense food groups, fat, iron and calcium, while intakes of cereals and vitamin A remained unchanged between 1981 – 1982 and 1995 – 1996 in two locations representative of rural Bangladesh.

Acknowledgements The contributors wish to thank Dr Jo´ hanna Haraldsdo´ ttir from The Royal Veterinary and Agricultural University, Denmark (RVAU) for fruitful discussions at the final stages of

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