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Agricultural productivity, seasonality and gender bias in rural nutrition: Empirical evidence from South India
Sot. Sci. Med. Vol. 37, No. II, pp. 1313-1319, Printed in Great Britain. All rights reserved
1993
Copyright
f
0277-9536193 $6.00 + 0.00 1993 Pergamon Press Ltd
AGRICULTURAL PRODUCTIVITY, SEASONALITY AND GENDER BIAS IN RURAL NUTRITION: EMPIRICAL EVIDENCE FROM SOUTH INDIA* SURESHCHANDRA BABU,‘~ SUSHEELATHIRUMARAN’and T. C. MOHANAM’ ‘International Food Policy Research
Institute, Washington, DC 20036-3006, ZTamil Nadu Agricultural University, Madurai, India and ‘Madras Institute of Development Studies, Madras, India
U.S.A.,
Abstract-This paper analyzes changes in the nutrients intake, intra-household allocation and gender bias due to changes in agricultural productivity among four groups of rural households over six different seasons. The study utilizes household survey data collected from a village in Tamil Nadu, India. While the results are consistent with earlier findings that seasonality influences variation in the intake of nutrients, it is shown that subsistence agricultural households recover faster from poor crop yields than market oriented agricultural households in terms of nutrient intake. Agricultural labour households consumed lowest quantities of energy and protein in all the seasons with the highest degree of gender bias. The gender bias is more in terms of protein intake compared to energy intake for all the households. The non-agricultural households are least affected due to variability in crop yields and seasonality. While nutritional intake of the rural households is positively correlated with crop yields, the variations in yields worsen the gender bias. It is argued that reducing dependency of rural households on agriculture may reduce malnutrition and the gender bias associated with it. Key ward.s+rop
yields, seasonality,
nutrition
intake,
1. INTRODUCITON
In spite of increased agricultural production in several developing countries due to the green revolution during the past two decades, the problem of malnutrition remains disquieting [I]. While this may be due to poor implementation of proper agricultural, food and nutrition polices, studies have demonstrated that increases in income due to increased agricultural growth do not necessarily mean increased consumption of nutrients [2, 31. Given that rural households are able to produce adequate food due to increased productivity, poor intra-household distribution of food among family members has been suggested as one of the contributing factors for the persistent state of malnutrition [4]. Recently much emphasis has been given to identifying the factors responsible for gender bias against females in the intra-household allocation of nutrition [S]. Attempts have been made to understand the effects of changes in seasonal availability of food on the intra-year fluctuations in nutrient intake and its distribution among family members [6]. Behrman, analyzing the inequality in the intake of nutrients in rural south India, concluded that females are nutritionally most vulnerable when food is scarce [5]. Studying the factors responsible for malnutrition *Paper presented at the Development
tTo
and
International Conference Health, Michigan State
on Women,
University,
East Lansing, 21-23 October, 1988. whom correspondence should be addressed: Suresh Chandra Babu. UNICEF, P.O. Box 30375, Lilongwe 3, Malawi, Central Africa.
intra-household
allocation,
gender
bias
among rural children, Sen and Sengupta found that gender bias in nutrition is a prime cause for malnutrition among female children [6]. There are also studies conducted particularly in south Asia, that suggest intra-household allocation of nutrients favours males over females [7, 81. The extent of promale bias in health and nutrient consumption also depends on socio-cultural factors like asset holding and education of the household head [9-l I]. Seasonal variation in agricultural production has been suggested to be a contributing factor for variations in the availability [ 121 and the allocation of food among household members [ 131. Studies conducted on the impact of seasonal variation in agricultural production on the nutritional status of the rural households also suggest that females are more affected than males [14, IS]. It can be hypothesized at least in the context of south Asia that since male adults and male children are engaged in manual agricultural operations and need more energy, they are the preferred members of the household, and receive more food than female adults and female children [6]. Studies tend to agree that food is allocated more equally among the family members after a season when there is a good harvest than after a poor agricultural season [16]. There is some evidence that small-scale farmers are more influenced in terms of nutrient intake by the seasonality in product and labour markets than are large cultivators [16]. Along these lines, it can be argued that subsistence-farming households are less prone to the seasonality of crop yields than market-
1313
SURESH CHANDRA
1314
oriented farm households and hence may have better nutrition with less inequality in intra-household allocation of nutrition. While the above statement seems to be intuitively plausible there is no empirical evidence to support or negate such an argument. This is partly due to the unavailability of intra-household data on the allocation of nutrients and data on seasonal variations in nutrient intake over several seasons among the same group of households. This paper is an attempt to study the extent of gender bias among agricultural and non-agricultural households and its variation over the seasons. The changes in gender bias due to changes in agricultural productivity in different seasons are compared for four different groups of rural households. Data collected from a village in Tamil Nadu, India, over six seasons (19841986) have been used in the study and are described in the next section of the paper. Methods used to collect and analyze the data are presented in Section 3. Changes in nutrient intake over the seasons among subsistence-farming households, market-oriented farming households, agricultural labour households and non-agricultural households are compared in the fourth section. The intra-household allocation of nutrients among the above households is discussed in Section 5. Changes in gender bias among rural households due to changes in agricultural productivity are analyzed in Section 6. Summary and conclusions form the last section.
2.
STUDY
AREA
The study village, Ayyangarkulam. lies at a distance of about 80 km southwest of Madras, the capital city of the south Indian state, Tamil Nadu. The total population of the village is 2266 with 1094 males and 1I72 females living in 455 households. The total working population of the village is 1929 (85.13%) and of this number, about 66.50% work in the household silk weaving industry, 9.90% are agricultural labourers and 5.29% are cultivators. A brief description of different groups of households studied is given in this section to enable better interpretation of the results. [lion -agricultural
households
The major non-agricultural occupation in the study village is silk-weaving. The non-agricultural households live in both thatched and tiled houses. Silk weaving involves almost all members of the family except very small children, with male heads of the household as the main weavers; these form the highest working population of all occupations in the study village. The information collected on food intake by non-agricultural households shows that members of these households eat high quality grains such as wheat and rice with eggs, fish and milk products.
BABU
e/ al.
Agricultural
labour households
The agricultural labour households live in thatched huts. The village system is such that these agricultural labourers work on the lands of cultivators on a daily wage basis. There arc two agricultural seasons in the village providing opportunity for field work all through the year. The survey on the food items consumed by agricultural labour households showed that rice and finger millet constituted the major share of their food. Meager amounts of milk and non-vcgetarian food items were eaten. Cultivator
households
This group included both subsistence farmers and market-oriented farmers. They owned or rented the agricultural land they tilled and were self-employed or employed agricultural labourers in crop cultivation. Subsistence farmers live in thatched huts while market-oriented farmers live in tiled or terraced houses. The quality of food and clothing in cultivator households is better than that of the other two groups. The food consumed by these households. in general, contained more leafy vegetables and fruits partly due to their access to their own home grown products. The study village receives an average annual rainfall of about 950 mm most of which is received during the months of July to December. There are two myjor crop seasons in a year. The first season crop is sown in July-August and harvested from October to January depending on the duration of the crop variety sown. In the study area. short duration rice varieties are more popular; these mature in YO days. thus harvest in Octoenabling the farmers to ber-November. The second crop is a dry crop sown in December-January and harvested in May. While a third crop is planted in summer (MayySeptcmbcr) in the region. the farmers of the study village keep the land fallow after second crop partly due to the early planting followed in the next season.
3.
METHOD
This paper uses cross-sectional data from the above groups of households collected over a period of 3 years, The base line survey was conducted during January-June 1984 in which all the households in the study village were interviewed [17]. To study the effects of seasonal variations on food and nutrient availability, a sub-set of I20 households was selected. Subsequently, visits were made to these households during November 1984, June 1985. Novcmbcr 1985. June 1986 and November lY86. The information gathered during these interviews includes. family size. the sex, age. education, occupation. number of dependants and monthly income of the family members. The employrnent particulars gathered include the number of persons employed. number of days worked during peak season and lcan season of ern-
Crop yields, seasonality and gender bias in nutrition ployment and total person-days of employment per family. The income aspects covered are: income through employment, crop income, non-farm income and off-farm income. Family consumption expenditure particulars include: expenditure on food, housing, clothing, fuel and lighting, education, medical care, conveyance, recreation, social and religious functions, entertainment and other services. The intake of food items by the sample households was measured for three consecutive days during each round of the survey. The food commodities that were used by the households for preparing each meal were weighed along with the individual intake of cooked food at each meal. The left over food and the food shared with other households were also measured. The data on the quantities of food items were converted into their nutrient values [I81 and individual, per adult equivalent and per household intake measures of these nutrients were calculated. The data on the yields of crops grown by the agricultural households were also collected for the seasons preceding the period of data collection. Table 1 provides descriptive statistics for the study households from the base line survey (January-June 1984). Household size ranged between 4.80-5.68 with highest variation among nonagricultural households. On an average, households had an adult equivalency of 3.4 per household and a male-female ratio of 0.7 1. Non-agricultural households had the highest total expenditures followed by market-oriented farmers, subsistence farmers and agricultural labourers. The share of food in the total expenditure among these households was highest for the agricultural labourers followed by subsistence farmers. market oriented farmers and non-agricultural households. The agricultural labour households consumed the lowest amounts of energy and protein of all the households studied. The data set has also been used in other studies where a more detailed description of additional variables is available [17, 19,201.
Table
I. Descriotive
statistics
Agricultural
4. CHANGES IN NUTRIENT INTAKE AND AGRICULTURAL PRODUCTIVITY
The changes in the intake of energy and protein among four groups of households, namely agricultural subsistence households, agricultural market-oriented households, non-agricultural households, and agricultural labour households were studied in relation to changes in the yields of rice over 6 seasons. Rice is the major crop grown in the study village, constituting the land use for more than 87% of total cultivated area, and rice is also the main staple food and a major component of the diets of the households studied. The quality of rice produced and the quality of rice consumed by the households may generally differ depending on the degree of market participation. At least for the subsistence-farming households and agricultural labour households however, the rice produced and the rice consumed are of the same quality. Most of the market-oriented farmers sold only their surplus production. However, the non-agricultural households did not have the constraint of consuming only the rice grown in their village, a fact which is reflected in the study results. The results of the analysis of changes in intake of energy and protein among the four groups of households and the rice yields during surplus and lean seasons are shown in Table 2. ‘The results based on both per household and per adult equivalent calculations are given. The energy intake per adult equivalent in the surplus season of 1984 ranged from 855 k.cal per day among the agricultural labour households to 1220 k.cal per day among non-agricultural households. The protein intake during the same season ranged from 58 g per day among agricultural labour households to 77 g per day among the nonagricultural households. The lean season of the same year shows a reduction in the intake of nutrients among study households except for energy intake among non-agricultural households. The range of energy intake was reduced to 783 k.cal per day for agricultural labour households but increased to 1248 kcal per day for nonagricultural households.
of variables
used in the analvsis
households
Agricultural Non-agricultural
Variable
Subsistence
Household Adult
size
Total
expenditure
Share
of food
in total Energy
intake
equwalent Protein adult Number ‘Standard
per adult (k.cal/day)
intake
labour households
5.42
4.80
5.68
(3.10)
(3.48)
(2.21)
3.29
3.18
3.12
3.41
(2.13)
(2.42)
(2.46)
(2.84)
0.69
0.71
0.68
0.74
(0.12)
(0.17)
(0.19)
(0. IO)
345.00
372.00
490.00
323.00
(243.12)
(128.14)
(263.41)
(148.42)
expenditure
expenditures
households
5.10
ratio
(Rs/month)
Market-oriented
(2.58) equivalents
Male-female
1315
0.68
0.63
0.60
0.71
(0.10)
(0.12)
(0.23)
(0.18)
II42
1187
1218
(I 70.09)
(285.23)
(268.43)
(568.51)
(Z60)
(%2)
(Yi.28)
(Z.12,
I68
I05
880
per
equivalent
(g/day)
of households deviation.
100
82
1316
S~RESH CHANDRA BAIW et al. Table 2. Chances Agricultural
m nutrition
intake and aericultural ~
Subsistence Year
Market-oriented Protein
Non-aericultural ho&holds __ Energy Protein
Energy”
Proteinh
Energy
HH‘ PAEd
3812 II57
215 65
3942 II98
HH PAE
3641 II07
201 61
3176 II48
HH PAE
3522 1071
I81 55
3642 II07
HH PAE
3125 950
169 51
3246 9x7
HH PAE
3984 1211
211 64
361 I 109x
3892 61 1183 SurpluJ 219 4126 66 I254
HH PAE
3815 II60
196 60
3428 I042
210 64
SGWJ”
oroductivitv
households
Surplu.s 236 4014 72 I220
I984
Agricultural labour households
~~ Energy
Protein
_
Rice’ yields
252 71
2814 855
I91 58
I800
238 12
2517 783
I56 47
1635
242 74
264 I 803
142 43
I040
230 70
2288 695
133 40
948
64 80
3121 949
I98 60
2075
250 76
2734 831
196 60
1980
Leurt
?I6 4105 66 I248 Surplus 210 3914 64 II90
1985
LlWl 202
1986
1.
“Energy intake in k.cal:day. bProtein intake g/day. “Household Intake. dPer adult eauivalent. data corresnondq ‘Yxld in kg/acre (average for the’study
to a” averaee area). -
4109 I249
household
The range of protein intake was reduced to 47 g per day for agricultural labour households and to 72 g per day for non-agricultural households. While a similar interpretation could be given to the intake of nutrients during the surplus and lean seasons of 1985 and 1986, the lowest intake of nutrients was observed during the lean season of 1985 due to the drought experienced in the study region. In general, the study households show higher intakes of nutrients in 1986 compared to the previous years when the rice yields were low. In general, during all the seasons, agricultural labour households consumed the lowest quantities of energy and protein compared to other households, while the non-agricultural households consumed the highest levels of both nutrients. Comparing the subsistence and market-oriented agricultural households, market-oriented households consumed higher quantities of these nutrients. The intake of nutrients is low in the lean seasons compared to the surplus seasons for all households. While the foregoing results could be expected given the nature of the households studied and are in line with results of earlier studies [16], they provide some interesting insights in understanding the effects of seasonality on nutrient intake. Compared to 1984 and 1986, 1985 was a year of poor crop performance in the study region. In general, for all the households. the intake of nutrients is strikingly low in 1985 compared to 1984 and 1986. This result supports earlier findings on the influence of drought on the variations in nutritional intake [l2. 161. It can also be noted that the intake of nutrients among subsistencefarming and agricultural labour households shows a significant increase in 1986, a year of good agricultural production. Market-oriented households, how-
with 2 adults and 3 children
ever. could not attain the same level of intake of both energy and protein in 1986 even though there was an increase in the yields of rice. The reasons underlying this finding are unclear; it may reflect the fact that in the year of poor yields, to support their family expenses, these households could have sold most of the crop output and covered the additional expenses with consumption loans which had to be repaid from the crop revenues in 1986. It is clear, however, that while the intake of nutrients of non-agricultural households also varies with the seasons they are relatively protected from seasonal fluctuations in the crop yields.
5. INTRA-HOUSEHOLD ALLOCATION OF NUTRIENTS AGRICULTURAL PRODUCTIVITY
AND
It has been demonstrated in several studies that there is an increase in the total intake of nutrients of an agricultural household with the increase in the crop yields [12]. However, the information on how these households allocate their increased food availability due to improved agricultural productivity among their family members is limited. Understanding the intrahousehold distribution of food due to the changes in seasonal food availability is essential for designing appropriate food and nutrition policy interventions. The allocation of energy and protein among males and females in the four groups of households over the 6 seasons is presented in Table 3. In general. the discussion presented earlier based on results in Table 2, also holds for the disaggregated data given in Table 3. The energy intake among the males in the surplus season of 1984 ranged from 1627 k.cal per day among agricultural labour households to 2106 k.cal per day
1317
Crop yields, seasonality and gender bias in nutrition
these households were better nourished than those in the other groups of households. Specific details about the gender bias in the intake of nutrients over the seasons are presented in the next section.
among subsistence farming households, while the energy intake of females ranged from 1187 kcal per day among agricultural labour households to 1912 k.cal per day among non-agricultural households. During the lean season of the same year, the energy intake of males ranged from 1543 k.cal per day among agricultural households to 2195 kcal per day among non-agricultural households. The protein intake among males in the surplus (lean) season of 1984 ranged from 119 (100) g per day among agricultural labour households to 139 (135) per day among non-agricultural households, while that of females ranged from 1034 k.cal per day to 1910 k.cal per day for the respective groups of households. The protein intake of females during the surplus (lean) season ranged from 72 (56) g per day to 114 (104) g per day among the same households. Similar interpretations could be given to the data presented in Table 3, for the years 1985 and 1986. The results show that in general assuring adequate food at the household level does not guarantee the nutritional adequacy of every individual of the household, especially women. In all the households, the aggregate intake of nutrients among females is less than that of males. Women in the agricultural labour households consumed the lowest amounts of both energy and protein. Poor crop yields in 1985 seem to have had adverse effect on the intake of nutrients among females in all the households. Comparing subsistence and market-oriented agricultural households during the year 1985, females consumed the same amounts of energy in both households, while the women from subsistence households consumed less protein. The variations in rice yields did not seriously affect the intrahousehold allocation of food in non-agricultural households, although women in Table 3. Intra-household Agricultural
-_.
allocation
BIAS AND AGRICULTURAL
of nutrition
and agricultural Non-agricultural households
Market-oriented
Season
Energy”
Proteinh
Energy
Males’ Fernal&
2106 I706
126 89
2131 1811
M&S Females
2069 1572
120 81
Males Females
1957 1565
Males Females
PRODUCTIVITY
The gender bias in nutrient intake is expressed as the ratio of nutrient intake of females to that of males for a particular household. The gender bias in the household intake of energy and protein along with the yields of rice in various seasons is shown in Table 4. In general, inequality in nutrient intake is more apparent in protein intake than in energy intake. This is due to the fact that the diet in the study region is highly calorie oriented; high quantities of cereals (rice) and low quantities of pulses and legumes are eaten [ 171. This is true for all types of households studied. The bias in nutrition against females is more serious in agricultural labour households than in other households. The non-agricultural households had the least gender bias in nutrition among all groups of households. Among the households dependent upon agriculture, the gender bias is worse during the year 1985, a year of poor crop yields, than in the years 1984 and 1986. The gender bias remained almost constant with the changes in the yields for the non-agricultural households. The variations in crop yields worsen the gender bias more in marketoriented agricultural households than in subsistence households. This may be due to the coping mechanisms that the subsistence farm households follow to meet their food needs. In contrast. the marketoriented farms tend to increase the share of their marketed output when the yields are poor. This leaves little food for their own consumption, thus
households
Subsistence Year
6. GENDER
Protein
Energy
Protein
productivity Agricultural labour households Energy
Protein
Rice’ yields
SWplUS
1984
2102 1912
139 II4
1621 II87
II9 72
I800
2098 1678
132 104 Lean 123 93
2195 1910
I35 104
I543 1034
100 56
1635
107 74
2082 1560
122 88
2028 1886
I31 III
I544 1097
90 52
I040
1982 I308
104 65
1898 I348
II9 83
2038 1854
129 IO1
1338 950
88 45
948
Males Females
2189 I795
121 90
2029 I582
2160 1960
143 121
1794 I327
I21 77
2075
Males Females
2164 1651
II5 81
2017 1412
124 95 LtWl 122 88
2140 I969
I38 II2
1571 II63
124 12
1980
1985
SUph LtWl
1986
dEnergy intake in k.cal/day. bProtein intake g/day. ‘Intake of nutrients among males. %take of nutrients among females. ‘Yield in kg/acre (average for the study area)
SUrplU.7
SURESH CHANDRA BABU et al.
1318 Table 4. Changes
in gender bias in nutrition
Agricultural households ~- - ~~ ~---Market-oriented Subsistence Year
and agricultural
productlwty
Non-agricultural households
Agncultural labour households
Season
Energy”
Proteinb
Energy
Protein
Energy
Protein
Energy
PrOtel”
RIG+ yxlds
Surplus Lea”
0.x I 0.76
0.71 0.67
0.85 0.80
0.79 0.76
0.91 0.87
0 82 I) 77
0.73 0.67
0.61 0.56
I635
Surplus Lean
0.80 0.72
0.69 0.63
0.75 0.71
0.72 0.70
0.93 0.91
0.84 0.78
0.71 0.63
0 57 0.51
I040 94x
Surplus Led”
0.82 0.74
0.74 0.71
0.78 0.70
0.76 0.72
0.91 0.92
0.84 0.81
0.74 0.69
0.63 0.58
2075 1980
I984
Ix00
19x5
19X6
‘Gender bias is expressed as a ratio of intake of nutrients between male and female members equal to I if no gender bias and close to zero if there is a high bias against females “Yields is kg/acre (average for the study area).
forcing them to adjust the available food among the individuals in the family which may result in less food consumption by the females. It is interesting also to note that the subsistence and agricultural labour households do not change the patterns of intrahousehold allocation of food with fluctuations in crop yields, though their gender bias is greater than other two groups of households. This may result from the fact that the market fluctuations associated with yield fluctuations do not influence their household food availability due to their subsistence orientation to farming. In analyzing the gender bias. it should be noted however, that the daily requirement of nutrients is in general lower for women than men. Thus comparing the relative deprivation in nutrient intake between men and women in relation to their needs may provide better estimates of gender bias. In fact, these estimates could be interpreted as gender bias in nutritional poverty between men and women. To verify the difference in results due to this approach, the data were analyzed incorporating the information on the gender specific needs of nutrients. Since the gender bias is expressed, in this case as relative deprivation of nutrients, which is also a ratio, the estimates obtained from the analysis did not change the results discussed above. For example, the gender bias in energy intake for the subsistence agricultural household in the surplus season of 1984 is calculated to be 0.8 I (1706 divided by 2106 from Table 3). The energy requirements for the men and women calculated for the study village based on the nature of work and leisure and pattern of time allocation between these activities were 2200 k. cal and 2000 k. cal respectively [1Y]. The ratio of energy intake between women and men in relation to their requirements is 0.89 [ (1706/2000)/2106/2000)]. This is equivalent to the gender bias calculation shown in Table 4 multiplied by 1.I (220052000). This is the ratio of nutrient requirement between men and women, which is a constant. Thus, the nature of results presented in Table 4 does not change due to the incorporation of information on daily requirement of nutrients in the calculation of gender bias.
7. SUMMARY
of the households
It 19
AND CONCLUSIONS
Four groups of rural households were traced over 6 seasons to study the changes in the intake of energy and protein and the allocation of these nutrients among their members in relation to changes in seasonal yields of crops. Rice, as the major crop and the main constituent of diets in the study area. was used to study the changes over the season. The changes in the gender bias as represented by the ratio of female intake to male intake of nutrients were also cxamined. The results presented in this paper support the relationship between agricultural productivity and nutritional intake among various groups of households. In general, agricultural labour households consumed the lowest amounts of energy and protein. There is remarkable variation in the intake of nutrients with changes in yields of rice among all households except non-agricultural households. Subsistence households adjust faster in terms of nutrient intake compared to market-oriented farm households after a season of low crop yields. For all groups of households, the intake of nutrients is greater 111 surplus seasons than in lean seasons. supporting the results of earlier studies [ 13, 161. The results also shou that adequacy of food at the household level dots not guarantee adequate nutrition for all the mcmbcrs ol the households. Variations in the yield of rice had limited effect on the gender bias of the household5 m general except the market-oriented farm households which showed an increase in the gender bias with lower yields. Gender bias in food distribution ih greater among agricultural households than no11agricultural households. Several implications for food and nutrition mtervention policies can be derived from the results of the study. The results suggest the need for targeting supplementary feeding programs to the subgroups of households identified as vulnerable to seasonal fluctuations in agricultural production. The female mcmbers of these households. whose susceptibility to malnutrition increases with low levels of food production should be identified for food and nutrition related interventions. The importance of diversifying
Crop
and gender bias in nutrition
yields, seasonality
the crops grown by the resource-poor farmers to include drought resistant food crops should be emphasized by the agricultural extension programmes. The results of the study also suggest that in designing of rural development projects, attention should be paid to increasing the non-farm and off-farm activities which may reduce the impact of seasonal variation in agriculture. Nutrition education programmes should focus on issues related to food storage, use of indigenous foods and intra-household allocation. To reduce the effect of seasonal variation in food availability on the food and nutrient intake rural public employment schemes such as ‘food for work’ programme could be designed during the periods of poor harvest
and
targeted
subsistence-farming
to the agricultural households.
While
labour the results
and of
policy directions for the choice of type of interventions and the groups of households that are to be targeted, it is important to identify specific food and nutrition programmes and their appropriate timing of implementation in order to reduce the costs and increase the benefits. The present paper has established the causal relationship between the seasonal variation in food production and the nutrient intake among rural households. It has also shown that the effect of yield variability would be different among various groups of households depending on their resource base, market orientation, and the extent of non-farm activities. However, more detailed analysis is needed to predict changes in intake of nutrients and gender bias based on changes in yields of crops. The discussions of the results in this paper relied on the mean values of the changes of nutrient intake among the four groups of households over different seasons. Studying the mean level differences does not help much in quantifying the influences of seasonal variability in agriculture on nutrient intake. It would be essential to study the distribution of nutrients among the members of rural households due to increased income through crop yield increase. Further, other cultural and social factors should be considered in future studies to predict the changes in gender bias due to increases in income and employment through rural development programmes. Given the importance of intra-household decision making systems in determining the food and nutrient allocation among the members of the household, the need for analyzing and incorporating them in designing food and nutrition interventions cannot be overemphasized. the paper
provide
some
general
REFERENCES
1. Pinstrup-Andersen P. Prevalence of malnutrition and dietary deficiencies as they relate to health and performance problem. World Food Conference, Des Moines, Iowa, 1988.
1319
2. Behnnan J. R. and Deolalikar A. Will developing country nutrition improve with income? A case study for rural south India. J. Polit. Econ. 95,492-507, 1987. dietary 3. Parikh K. and Tims N. Food consumption, status, and chronic hunger: an assessment of its extent and policy options. World Food Conference, Des Moines, Iowa, 1988. 4. Schofield S. Seasonal factors affecting nutrition in different age groups and especially preschool children. J. Dev. Stud. 2, 2240, 1914. allocation of nutrients 5. Behrman J. R. Inter-household in rural India: are boys favoured? Do parents exhibit inequality aversion? Oxford Econ. Papers, March 1988. S. Malnutrition of rural 6. Sen A. K. and Sengupta children and the sex bias. Econ. Polit. Wkly. pp. 8555864, 1983. I. Pitt M. M. and Rosenzweig M. R. Health and nutrient consumption across and within farm households, Rev. Econ. Stat. 67, 212-223, 1985. 8. Chen L. C., Hug E. and D’Souza S. Sex bias in the family allocation of food and health care in rural Bangladesh. Pop. Dev. Rev. 7, 55-70, 1981. 9. Miller B. D. The Endangered Sex: Nenlect of Female Children in Rural North Iidia. Cornell University Press, Ithaca, NY, 1981. of food 10. Carloni A. S. Sex disparities in the distribution within rural households. Food Nut&. Bull. 7, 3-12, 1981. R. Health, agriculture, and rural poverty: II. Chambers why seasons matter. J. Dev. Bud. 18, 217-238, 1982. P. and Jaramillo M. The impact of 12. Pinstrup-Andersen drought and technological change in rice production on intrayear fluctuations in food consumption: the case of North Arcot, India. In Seasonal Variability in Third World Agriculture: The Consequences for Food Security (Edited bv D. E. Sahn). The Johns Hopkins Universitv . Press, Baltimore, MD; 1989. 13. Abdullah M. The effects of seasonality on intra-household food distribution and nutrition in Bangladesh. In Seasonal Variability in Third World Agriculture: The Consequences for Food Security (Edited by D. E. Sahn). The Johns Hopkins University Press, Baltimore, MD, 1989. R. Bad times for rural children: countering 14. Chambers seasonal deprivation. J. Sociefy Int. Dec. 1,4549, 1983. 15. Chambers R., Longhurst R. and Pacey A. (Ed.) Seasonal Dimensions to Rural Poverty. Frances Pinter Publishers, London, 198 1. 16. Behrman J. R. and Deolalikar A. B. Seasonal demands for nutrient intakes and health status in rural south India. In Seasonal Variability in Third World Agriculture: The Consequences for Food Securirjj (Edited by D. E. Sahn). The Johns Hopkins University Press. Baltimore, MD, 1989. 17. Babu S. C. and Hallam J. A. Socio-economic impacts for school feeding programs: empirical evidence from a south Indian village. Food Policy 14. 58-66. 1989. 18. Gopalan C., Sastry B. V. R. and Balasubramanian S. C. Nutritive Value of Indian Foods. National Institute of Nutrition, Hyderabad, 198 I, 19. Babu S. C. Identijjing the Poor-A Development Approach. Iowa State University, Ames, IA 5001 I, Mimeo, 1986. 20. Babu S. C. and Hallam J. A. Nutrition-Education IncomeeNutrition: policy testing of the development cycle. Nineteenth Annual Meeting of the Society for Nutrition Education, Washington, DC 1986.
1993
Copyright
f
0277-9536193 $6.00 + 0.00 1993 Pergamon Press Ltd
AGRICULTURAL PRODUCTIVITY, SEASONALITY AND GENDER BIAS IN RURAL NUTRITION: EMPIRICAL EVIDENCE FROM SOUTH INDIA* SURESHCHANDRA BABU,‘~ SUSHEELATHIRUMARAN’and T. C. MOHANAM’ ‘International Food Policy Research
Institute, Washington, DC 20036-3006, ZTamil Nadu Agricultural University, Madurai, India and ‘Madras Institute of Development Studies, Madras, India
U.S.A.,
Abstract-This paper analyzes changes in the nutrients intake, intra-household allocation and gender bias due to changes in agricultural productivity among four groups of rural households over six different seasons. The study utilizes household survey data collected from a village in Tamil Nadu, India. While the results are consistent with earlier findings that seasonality influences variation in the intake of nutrients, it is shown that subsistence agricultural households recover faster from poor crop yields than market oriented agricultural households in terms of nutrient intake. Agricultural labour households consumed lowest quantities of energy and protein in all the seasons with the highest degree of gender bias. The gender bias is more in terms of protein intake compared to energy intake for all the households. The non-agricultural households are least affected due to variability in crop yields and seasonality. While nutritional intake of the rural households is positively correlated with crop yields, the variations in yields worsen the gender bias. It is argued that reducing dependency of rural households on agriculture may reduce malnutrition and the gender bias associated with it. Key ward.s+rop
yields, seasonality,
nutrition
intake,
1. INTRODUCITON
In spite of increased agricultural production in several developing countries due to the green revolution during the past two decades, the problem of malnutrition remains disquieting [I]. While this may be due to poor implementation of proper agricultural, food and nutrition polices, studies have demonstrated that increases in income due to increased agricultural growth do not necessarily mean increased consumption of nutrients [2, 31. Given that rural households are able to produce adequate food due to increased productivity, poor intra-household distribution of food among family members has been suggested as one of the contributing factors for the persistent state of malnutrition [4]. Recently much emphasis has been given to identifying the factors responsible for gender bias against females in the intra-household allocation of nutrition [S]. Attempts have been made to understand the effects of changes in seasonal availability of food on the intra-year fluctuations in nutrient intake and its distribution among family members [6]. Behrman, analyzing the inequality in the intake of nutrients in rural south India, concluded that females are nutritionally most vulnerable when food is scarce [5]. Studying the factors responsible for malnutrition *Paper presented at the Development
tTo
and
International Conference Health, Michigan State
on Women,
University,
East Lansing, 21-23 October, 1988. whom correspondence should be addressed: Suresh Chandra Babu. UNICEF, P.O. Box 30375, Lilongwe 3, Malawi, Central Africa.
intra-household
allocation,
gender
bias
among rural children, Sen and Sengupta found that gender bias in nutrition is a prime cause for malnutrition among female children [6]. There are also studies conducted particularly in south Asia, that suggest intra-household allocation of nutrients favours males over females [7, 81. The extent of promale bias in health and nutrient consumption also depends on socio-cultural factors like asset holding and education of the household head [9-l I]. Seasonal variation in agricultural production has been suggested to be a contributing factor for variations in the availability [ 121 and the allocation of food among household members [ 131. Studies conducted on the impact of seasonal variation in agricultural production on the nutritional status of the rural households also suggest that females are more affected than males [14, IS]. It can be hypothesized at least in the context of south Asia that since male adults and male children are engaged in manual agricultural operations and need more energy, they are the preferred members of the household, and receive more food than female adults and female children [6]. Studies tend to agree that food is allocated more equally among the family members after a season when there is a good harvest than after a poor agricultural season [16]. There is some evidence that small-scale farmers are more influenced in terms of nutrient intake by the seasonality in product and labour markets than are large cultivators [16]. Along these lines, it can be argued that subsistence-farming households are less prone to the seasonality of crop yields than market-
1313
SURESH CHANDRA
1314
oriented farm households and hence may have better nutrition with less inequality in intra-household allocation of nutrition. While the above statement seems to be intuitively plausible there is no empirical evidence to support or negate such an argument. This is partly due to the unavailability of intra-household data on the allocation of nutrients and data on seasonal variations in nutrient intake over several seasons among the same group of households. This paper is an attempt to study the extent of gender bias among agricultural and non-agricultural households and its variation over the seasons. The changes in gender bias due to changes in agricultural productivity in different seasons are compared for four different groups of rural households. Data collected from a village in Tamil Nadu, India, over six seasons (19841986) have been used in the study and are described in the next section of the paper. Methods used to collect and analyze the data are presented in Section 3. Changes in nutrient intake over the seasons among subsistence-farming households, market-oriented farming households, agricultural labour households and non-agricultural households are compared in the fourth section. The intra-household allocation of nutrients among the above households is discussed in Section 5. Changes in gender bias among rural households due to changes in agricultural productivity are analyzed in Section 6. Summary and conclusions form the last section.
2.
STUDY
AREA
The study village, Ayyangarkulam. lies at a distance of about 80 km southwest of Madras, the capital city of the south Indian state, Tamil Nadu. The total population of the village is 2266 with 1094 males and 1I72 females living in 455 households. The total working population of the village is 1929 (85.13%) and of this number, about 66.50% work in the household silk weaving industry, 9.90% are agricultural labourers and 5.29% are cultivators. A brief description of different groups of households studied is given in this section to enable better interpretation of the results. [lion -agricultural
households
The major non-agricultural occupation in the study village is silk-weaving. The non-agricultural households live in both thatched and tiled houses. Silk weaving involves almost all members of the family except very small children, with male heads of the household as the main weavers; these form the highest working population of all occupations in the study village. The information collected on food intake by non-agricultural households shows that members of these households eat high quality grains such as wheat and rice with eggs, fish and milk products.
BABU
e/ al.
Agricultural
labour households
The agricultural labour households live in thatched huts. The village system is such that these agricultural labourers work on the lands of cultivators on a daily wage basis. There arc two agricultural seasons in the village providing opportunity for field work all through the year. The survey on the food items consumed by agricultural labour households showed that rice and finger millet constituted the major share of their food. Meager amounts of milk and non-vcgetarian food items were eaten. Cultivator
households
This group included both subsistence farmers and market-oriented farmers. They owned or rented the agricultural land they tilled and were self-employed or employed agricultural labourers in crop cultivation. Subsistence farmers live in thatched huts while market-oriented farmers live in tiled or terraced houses. The quality of food and clothing in cultivator households is better than that of the other two groups. The food consumed by these households. in general, contained more leafy vegetables and fruits partly due to their access to their own home grown products. The study village receives an average annual rainfall of about 950 mm most of which is received during the months of July to December. There are two myjor crop seasons in a year. The first season crop is sown in July-August and harvested from October to January depending on the duration of the crop variety sown. In the study area. short duration rice varieties are more popular; these mature in YO days. thus harvest in Octoenabling the farmers to ber-November. The second crop is a dry crop sown in December-January and harvested in May. While a third crop is planted in summer (MayySeptcmbcr) in the region. the farmers of the study village keep the land fallow after second crop partly due to the early planting followed in the next season.
3.
METHOD
This paper uses cross-sectional data from the above groups of households collected over a period of 3 years, The base line survey was conducted during January-June 1984 in which all the households in the study village were interviewed [17]. To study the effects of seasonal variations on food and nutrient availability, a sub-set of I20 households was selected. Subsequently, visits were made to these households during November 1984, June 1985. Novcmbcr 1985. June 1986 and November lY86. The information gathered during these interviews includes. family size. the sex, age. education, occupation. number of dependants and monthly income of the family members. The employrnent particulars gathered include the number of persons employed. number of days worked during peak season and lcan season of ern-
Crop yields, seasonality and gender bias in nutrition ployment and total person-days of employment per family. The income aspects covered are: income through employment, crop income, non-farm income and off-farm income. Family consumption expenditure particulars include: expenditure on food, housing, clothing, fuel and lighting, education, medical care, conveyance, recreation, social and religious functions, entertainment and other services. The intake of food items by the sample households was measured for three consecutive days during each round of the survey. The food commodities that were used by the households for preparing each meal were weighed along with the individual intake of cooked food at each meal. The left over food and the food shared with other households were also measured. The data on the quantities of food items were converted into their nutrient values [I81 and individual, per adult equivalent and per household intake measures of these nutrients were calculated. The data on the yields of crops grown by the agricultural households were also collected for the seasons preceding the period of data collection. Table 1 provides descriptive statistics for the study households from the base line survey (January-June 1984). Household size ranged between 4.80-5.68 with highest variation among nonagricultural households. On an average, households had an adult equivalency of 3.4 per household and a male-female ratio of 0.7 1. Non-agricultural households had the highest total expenditures followed by market-oriented farmers, subsistence farmers and agricultural labourers. The share of food in the total expenditure among these households was highest for the agricultural labourers followed by subsistence farmers. market oriented farmers and non-agricultural households. The agricultural labour households consumed the lowest amounts of energy and protein of all the households studied. The data set has also been used in other studies where a more detailed description of additional variables is available [17, 19,201.
Table
I. Descriotive
statistics
Agricultural
4. CHANGES IN NUTRIENT INTAKE AND AGRICULTURAL PRODUCTIVITY
The changes in the intake of energy and protein among four groups of households, namely agricultural subsistence households, agricultural market-oriented households, non-agricultural households, and agricultural labour households were studied in relation to changes in the yields of rice over 6 seasons. Rice is the major crop grown in the study village, constituting the land use for more than 87% of total cultivated area, and rice is also the main staple food and a major component of the diets of the households studied. The quality of rice produced and the quality of rice consumed by the households may generally differ depending on the degree of market participation. At least for the subsistence-farming households and agricultural labour households however, the rice produced and the rice consumed are of the same quality. Most of the market-oriented farmers sold only their surplus production. However, the non-agricultural households did not have the constraint of consuming only the rice grown in their village, a fact which is reflected in the study results. The results of the analysis of changes in intake of energy and protein among the four groups of households and the rice yields during surplus and lean seasons are shown in Table 2. ‘The results based on both per household and per adult equivalent calculations are given. The energy intake per adult equivalent in the surplus season of 1984 ranged from 855 k.cal per day among the agricultural labour households to 1220 k.cal per day among non-agricultural households. The protein intake during the same season ranged from 58 g per day among agricultural labour households to 77 g per day among the nonagricultural households. The lean season of the same year shows a reduction in the intake of nutrients among study households except for energy intake among non-agricultural households. The range of energy intake was reduced to 783 k.cal per day for agricultural labour households but increased to 1248 kcal per day for nonagricultural households.
of variables
used in the analvsis
households
Agricultural Non-agricultural
Variable
Subsistence
Household Adult
size
Total
expenditure
Share
of food
in total Energy
intake
equwalent Protein adult Number ‘Standard
per adult (k.cal/day)
intake
labour households
5.42
4.80
5.68
(3.10)
(3.48)
(2.21)
3.29
3.18
3.12
3.41
(2.13)
(2.42)
(2.46)
(2.84)
0.69
0.71
0.68
0.74
(0.12)
(0.17)
(0.19)
(0. IO)
345.00
372.00
490.00
323.00
(243.12)
(128.14)
(263.41)
(148.42)
expenditure
expenditures
households
5.10
ratio
(Rs/month)
Market-oriented
(2.58) equivalents
Male-female
1315
0.68
0.63
0.60
0.71
(0.10)
(0.12)
(0.23)
(0.18)
II42
1187
1218
(I 70.09)
(285.23)
(268.43)
(568.51)
(Z60)
(%2)
(Yi.28)
(Z.12,
I68
I05
880
per
equivalent
(g/day)
of households deviation.
100
82
1316
S~RESH CHANDRA BAIW et al. Table 2. Chances Agricultural
m nutrition
intake and aericultural ~
Subsistence Year
Market-oriented Protein
Non-aericultural ho&holds __ Energy Protein
Energy”
Proteinh
Energy
HH‘ PAEd
3812 II57
215 65
3942 II98
HH PAE
3641 II07
201 61
3176 II48
HH PAE
3522 1071
I81 55
3642 II07
HH PAE
3125 950
169 51
3246 9x7
HH PAE
3984 1211
211 64
361 I 109x
3892 61 1183 SurpluJ 219 4126 66 I254
HH PAE
3815 II60
196 60
3428 I042
210 64
SGWJ”
oroductivitv
households
Surplu.s 236 4014 72 I220
I984
Agricultural labour households
~~ Energy
Protein
_
Rice’ yields
252 71
2814 855
I91 58
I800
238 12
2517 783
I56 47
1635
242 74
264 I 803
142 43
I040
230 70
2288 695
133 40
948
64 80
3121 949
I98 60
2075
250 76
2734 831
196 60
1980
Leurt
?I6 4105 66 I248 Surplus 210 3914 64 II90
1985
LlWl 202
1986
1.
“Energy intake in k.cal:day. bProtein intake g/day. “Household Intake. dPer adult eauivalent. data corresnondq ‘Yxld in kg/acre (average for the’study
to a” averaee area). -
4109 I249
household
The range of protein intake was reduced to 47 g per day for agricultural labour households and to 72 g per day for non-agricultural households. While a similar interpretation could be given to the intake of nutrients during the surplus and lean seasons of 1985 and 1986, the lowest intake of nutrients was observed during the lean season of 1985 due to the drought experienced in the study region. In general, the study households show higher intakes of nutrients in 1986 compared to the previous years when the rice yields were low. In general, during all the seasons, agricultural labour households consumed the lowest quantities of energy and protein compared to other households, while the non-agricultural households consumed the highest levels of both nutrients. Comparing the subsistence and market-oriented agricultural households, market-oriented households consumed higher quantities of these nutrients. The intake of nutrients is low in the lean seasons compared to the surplus seasons for all households. While the foregoing results could be expected given the nature of the households studied and are in line with results of earlier studies [16], they provide some interesting insights in understanding the effects of seasonality on nutrient intake. Compared to 1984 and 1986, 1985 was a year of poor crop performance in the study region. In general, for all the households. the intake of nutrients is strikingly low in 1985 compared to 1984 and 1986. This result supports earlier findings on the influence of drought on the variations in nutritional intake [l2. 161. It can also be noted that the intake of nutrients among subsistencefarming and agricultural labour households shows a significant increase in 1986, a year of good agricultural production. Market-oriented households, how-
with 2 adults and 3 children
ever. could not attain the same level of intake of both energy and protein in 1986 even though there was an increase in the yields of rice. The reasons underlying this finding are unclear; it may reflect the fact that in the year of poor yields, to support their family expenses, these households could have sold most of the crop output and covered the additional expenses with consumption loans which had to be repaid from the crop revenues in 1986. It is clear, however, that while the intake of nutrients of non-agricultural households also varies with the seasons they are relatively protected from seasonal fluctuations in the crop yields.
5. INTRA-HOUSEHOLD ALLOCATION OF NUTRIENTS AGRICULTURAL PRODUCTIVITY
AND
It has been demonstrated in several studies that there is an increase in the total intake of nutrients of an agricultural household with the increase in the crop yields [12]. However, the information on how these households allocate their increased food availability due to improved agricultural productivity among their family members is limited. Understanding the intrahousehold distribution of food due to the changes in seasonal food availability is essential for designing appropriate food and nutrition policy interventions. The allocation of energy and protein among males and females in the four groups of households over the 6 seasons is presented in Table 3. In general. the discussion presented earlier based on results in Table 2, also holds for the disaggregated data given in Table 3. The energy intake among the males in the surplus season of 1984 ranged from 1627 k.cal per day among agricultural labour households to 2106 k.cal per day
1317
Crop yields, seasonality and gender bias in nutrition
these households were better nourished than those in the other groups of households. Specific details about the gender bias in the intake of nutrients over the seasons are presented in the next section.
among subsistence farming households, while the energy intake of females ranged from 1187 kcal per day among agricultural labour households to 1912 k.cal per day among non-agricultural households. During the lean season of the same year, the energy intake of males ranged from 1543 k.cal per day among agricultural households to 2195 kcal per day among non-agricultural households. The protein intake among males in the surplus (lean) season of 1984 ranged from 119 (100) g per day among agricultural labour households to 139 (135) per day among non-agricultural households, while that of females ranged from 1034 k.cal per day to 1910 k.cal per day for the respective groups of households. The protein intake of females during the surplus (lean) season ranged from 72 (56) g per day to 114 (104) g per day among the same households. Similar interpretations could be given to the data presented in Table 3, for the years 1985 and 1986. The results show that in general assuring adequate food at the household level does not guarantee the nutritional adequacy of every individual of the household, especially women. In all the households, the aggregate intake of nutrients among females is less than that of males. Women in the agricultural labour households consumed the lowest amounts of both energy and protein. Poor crop yields in 1985 seem to have had adverse effect on the intake of nutrients among females in all the households. Comparing subsistence and market-oriented agricultural households during the year 1985, females consumed the same amounts of energy in both households, while the women from subsistence households consumed less protein. The variations in rice yields did not seriously affect the intrahousehold allocation of food in non-agricultural households, although women in Table 3. Intra-household Agricultural
-_.
allocation
BIAS AND AGRICULTURAL
of nutrition
and agricultural Non-agricultural households
Market-oriented
Season
Energy”
Proteinh
Energy
Males’ Fernal&
2106 I706
126 89
2131 1811
M&S Females
2069 1572
120 81
Males Females
1957 1565
Males Females
PRODUCTIVITY
The gender bias in nutrient intake is expressed as the ratio of nutrient intake of females to that of males for a particular household. The gender bias in the household intake of energy and protein along with the yields of rice in various seasons is shown in Table 4. In general, inequality in nutrient intake is more apparent in protein intake than in energy intake. This is due to the fact that the diet in the study region is highly calorie oriented; high quantities of cereals (rice) and low quantities of pulses and legumes are eaten [ 171. This is true for all types of households studied. The bias in nutrition against females is more serious in agricultural labour households than in other households. The non-agricultural households had the least gender bias in nutrition among all groups of households. Among the households dependent upon agriculture, the gender bias is worse during the year 1985, a year of poor crop yields, than in the years 1984 and 1986. The gender bias remained almost constant with the changes in the yields for the non-agricultural households. The variations in crop yields worsen the gender bias more in marketoriented agricultural households than in subsistence households. This may be due to the coping mechanisms that the subsistence farm households follow to meet their food needs. In contrast. the marketoriented farms tend to increase the share of their marketed output when the yields are poor. This leaves little food for their own consumption, thus
households
Subsistence Year
6. GENDER
Protein
Energy
Protein
productivity Agricultural labour households Energy
Protein
Rice’ yields
SWplUS
1984
2102 1912
139 II4
1621 II87
II9 72
I800
2098 1678
132 104 Lean 123 93
2195 1910
I35 104
I543 1034
100 56
1635
107 74
2082 1560
122 88
2028 1886
I31 III
I544 1097
90 52
I040
1982 I308
104 65
1898 I348
II9 83
2038 1854
129 IO1
1338 950
88 45
948
Males Females
2189 I795
121 90
2029 I582
2160 1960
143 121
1794 I327
I21 77
2075
Males Females
2164 1651
II5 81
2017 1412
124 95 LtWl 122 88
2140 I969
I38 II2
1571 II63
124 12
1980
1985
SUph LtWl
1986
dEnergy intake in k.cal/day. bProtein intake g/day. ‘Intake of nutrients among males. %take of nutrients among females. ‘Yield in kg/acre (average for the study area)
SUrplU.7
SURESH CHANDRA BABU et al.
1318 Table 4. Changes
in gender bias in nutrition
Agricultural households ~- - ~~ ~---Market-oriented Subsistence Year
and agricultural
productlwty
Non-agricultural households
Agncultural labour households
Season
Energy”
Proteinb
Energy
Protein
Energy
Protein
Energy
PrOtel”
RIG+ yxlds
Surplus Lea”
0.x I 0.76
0.71 0.67
0.85 0.80
0.79 0.76
0.91 0.87
0 82 I) 77
0.73 0.67
0.61 0.56
I635
Surplus Lean
0.80 0.72
0.69 0.63
0.75 0.71
0.72 0.70
0.93 0.91
0.84 0.78
0.71 0.63
0 57 0.51
I040 94x
Surplus Led”
0.82 0.74
0.74 0.71
0.78 0.70
0.76 0.72
0.91 0.92
0.84 0.81
0.74 0.69
0.63 0.58
2075 1980
I984
Ix00
19x5
19X6
‘Gender bias is expressed as a ratio of intake of nutrients between male and female members equal to I if no gender bias and close to zero if there is a high bias against females “Yields is kg/acre (average for the study area).
forcing them to adjust the available food among the individuals in the family which may result in less food consumption by the females. It is interesting also to note that the subsistence and agricultural labour households do not change the patterns of intrahousehold allocation of food with fluctuations in crop yields, though their gender bias is greater than other two groups of households. This may result from the fact that the market fluctuations associated with yield fluctuations do not influence their household food availability due to their subsistence orientation to farming. In analyzing the gender bias. it should be noted however, that the daily requirement of nutrients is in general lower for women than men. Thus comparing the relative deprivation in nutrient intake between men and women in relation to their needs may provide better estimates of gender bias. In fact, these estimates could be interpreted as gender bias in nutritional poverty between men and women. To verify the difference in results due to this approach, the data were analyzed incorporating the information on the gender specific needs of nutrients. Since the gender bias is expressed, in this case as relative deprivation of nutrients, which is also a ratio, the estimates obtained from the analysis did not change the results discussed above. For example, the gender bias in energy intake for the subsistence agricultural household in the surplus season of 1984 is calculated to be 0.8 I (1706 divided by 2106 from Table 3). The energy requirements for the men and women calculated for the study village based on the nature of work and leisure and pattern of time allocation between these activities were 2200 k. cal and 2000 k. cal respectively [1Y]. The ratio of energy intake between women and men in relation to their requirements is 0.89 [ (1706/2000)/2106/2000)]. This is equivalent to the gender bias calculation shown in Table 4 multiplied by 1.I (220052000). This is the ratio of nutrient requirement between men and women, which is a constant. Thus, the nature of results presented in Table 4 does not change due to the incorporation of information on daily requirement of nutrients in the calculation of gender bias.
7. SUMMARY
of the households
It 19
AND CONCLUSIONS
Four groups of rural households were traced over 6 seasons to study the changes in the intake of energy and protein and the allocation of these nutrients among their members in relation to changes in seasonal yields of crops. Rice, as the major crop and the main constituent of diets in the study area. was used to study the changes over the season. The changes in the gender bias as represented by the ratio of female intake to male intake of nutrients were also cxamined. The results presented in this paper support the relationship between agricultural productivity and nutritional intake among various groups of households. In general, agricultural labour households consumed the lowest amounts of energy and protein. There is remarkable variation in the intake of nutrients with changes in yields of rice among all households except non-agricultural households. Subsistence households adjust faster in terms of nutrient intake compared to market-oriented farm households after a season of low crop yields. For all groups of households, the intake of nutrients is greater 111 surplus seasons than in lean seasons. supporting the results of earlier studies [ 13, 161. The results also shou that adequacy of food at the household level dots not guarantee adequate nutrition for all the mcmbcrs ol the households. Variations in the yield of rice had limited effect on the gender bias of the household5 m general except the market-oriented farm households which showed an increase in the gender bias with lower yields. Gender bias in food distribution ih greater among agricultural households than no11agricultural households. Several implications for food and nutrition mtervention policies can be derived from the results of the study. The results suggest the need for targeting supplementary feeding programs to the subgroups of households identified as vulnerable to seasonal fluctuations in agricultural production. The female mcmbers of these households. whose susceptibility to malnutrition increases with low levels of food production should be identified for food and nutrition related interventions. The importance of diversifying
Crop
and gender bias in nutrition
yields, seasonality
the crops grown by the resource-poor farmers to include drought resistant food crops should be emphasized by the agricultural extension programmes. The results of the study also suggest that in designing of rural development projects, attention should be paid to increasing the non-farm and off-farm activities which may reduce the impact of seasonal variation in agriculture. Nutrition education programmes should focus on issues related to food storage, use of indigenous foods and intra-household allocation. To reduce the effect of seasonal variation in food availability on the food and nutrient intake rural public employment schemes such as ‘food for work’ programme could be designed during the periods of poor harvest
and
targeted
subsistence-farming
to the agricultural households.
While
labour the results
and of
policy directions for the choice of type of interventions and the groups of households that are to be targeted, it is important to identify specific food and nutrition programmes and their appropriate timing of implementation in order to reduce the costs and increase the benefits. The present paper has established the causal relationship between the seasonal variation in food production and the nutrient intake among rural households. It has also shown that the effect of yield variability would be different among various groups of households depending on their resource base, market orientation, and the extent of non-farm activities. However, more detailed analysis is needed to predict changes in intake of nutrients and gender bias based on changes in yields of crops. The discussions of the results in this paper relied on the mean values of the changes of nutrient intake among the four groups of households over different seasons. Studying the mean level differences does not help much in quantifying the influences of seasonal variability in agriculture on nutrient intake. It would be essential to study the distribution of nutrients among the members of rural households due to increased income through crop yield increase. Further, other cultural and social factors should be considered in future studies to predict the changes in gender bias due to increases in income and employment through rural development programmes. Given the importance of intra-household decision making systems in determining the food and nutrient allocation among the members of the household, the need for analyzing and incorporating them in designing food and nutrition interventions cannot be overemphasized. the paper
provide
some
general
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