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2 MRC Epidemiology Resource Centre, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK and 3 Avon Longitudinal Study of Parents and Children (ALSPAC), Bristol BS8 1TQ, UK
* To whom correspondence should be addressed. E-mail: meb{at}mrc.soton.ac.uk.
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ABSTRACT |
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 TOP ABSTRACT IntroductionMethods and ProceduresResultsDiscussionLITERATURE CITED |
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Introduction |
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TOPABSTRACTIntroductionMethods and ProceduresResultsDiscussionLITERATURE CITED |
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Between 1994 and 1996, a study of women living in villages near Pune city in western India was conducted to examine the relation of maternal nutrition to fetal growth (4–6). The study showed that thinner women had thinner babies, and also that they were significantly thinner than their husbands (7); 65% of women had BMIs below 18.5 kg/m2, an indicator of chronic energy deficiency, compared with 39% of their husbands.
Gender inequalities in health and nutritional status in India are the subject of an extensive literature. Females have higher mortality rates in utero due to sex-selective abortion (8), and a higher mortality in infancy and childhood (9). Girl children are more likely to be undernourished than boys (10) and often have less access to health care (11). There are regional variations in the extent of these inequalities. For example, fewer girls are immunized in rural than urban areas and in the north rather than the south of India (12).
As they pass into adulthood, Indian girls adopt a social role that may limit their access to education, health care, and food (13). Traditionally, they marry young and enter the groom's family at the bottom of the hierarchy. They are given the most menial work and are expected to prove themselves by working hard and bearing a child within a year of marriage, preferably a boy.
Although it seems likely that this role affects women's nutritional status, there is little direct evidence to link the two. Villagers in rural Maharashtra believed their women were thin because of the combined demands of early motherhood and work (7). This article attempts to identify the social and economic correlates of thinness among young women in this population (survey 1), and to explore how women's daily activities might contribute to this phenomenon (survey 2).
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Methods and Procedures |
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TOPABSTRACTIntroductionMethods and ProceduresResultsDiscussionLITERATURE CITED |
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Families were selected, from a survey of all married women in the village (5), to contain a husband and wife pair of child-bearing age with at least 1 son and 1 daughter in the age range of 3 to 8 y (n = 101). A total of 93 men and 98 women took part in the study, producing 90 couples whose nutritional status could be compared in the 2nd half of the analysis.
Families were visited by a researcher (G. Chlorghade), a midwife to make anthropometric measurements, and a community worker who was known to the families. The height and weight of the father and mother in each family were recorded. A questionnaire was completed for each family by a member of the research team (G. Chlorghade), covering social, economic and nutritional factors. Educational status of the target pair was recorded in 5 categories from illiterate to graduate. A record was made of whether they lived in a traditional extended family unit or a nuclear family. Their houses were categorized as a 1-room hut, a "kutcha" (more than 1 room, with mud walls and a thatched roof), "mixed pucca" (stone and cement walls, mud plaster, and a tiled roof), "pucca" (entirely stone or bricks and cement with a tiled roof), or rented house. Distance from Pabal main village was estimated from the jeep's mileometer. Men's and women's occupations were recorded as farm laborer on other's land, farm laborer on their own and other's land, petty employee or artisan, business person or trader, land-owning farmer, worker in service industries, or (for women) housewife.
Participants estimated the acreage of irrigated and nonirrigated land owned by the household. Irrigated land was considered to be 4 times as productive as nonirrigated land. A total productive acreage was created by multiplying irrigated land acreage by 4 and adding the acreage of nonirrigated land. The interviewer recorded whether the household owned the following: an iron, bicycle, tape player or radio, moped, car or jeep, or bullock cart; and these were summed to create a material possessions score. An amenities score was constructed for whether the household had electricity or a well, or both. Men and women were asked if they fasted and, if so, how often. Ownership of milking animals and oil consumption were recorded.
Analysis. A summary and descriptive statistics were produced to enable us to compare the BMIs of men and women in each category of social, economic, and food-related variables. Tests for trends in men's BMIs, women's BMIs, and in the percentage of difference between men's and women's BMIs within households [(men's BMI – women's BMI/ men's BMI) x 100], were carried out using linear regression analysis. To identify patterns of variables and how these related to the BMIs of men and women, we carried out a principal components analysis of the social, economic, and food-related variables. Principal components analysis transforms the original set of variables into fewer summary variables, known as the principal components (15), which are linear combinations of the original variables uncorrelated with each other. The first component accounts for as much of the variation in the data as possible, with each subsequent component explaining less. This analysis was carried out on data from the 90 households where comparisons could be made between the man and the woman. The principal components describing patterns of social, economic, and food-related variables were correlated with the BMIs of men and women separately, and then with the difference between the BMIs of men and women in the same household, using Spearman's ranked correlation.
Women's daily activities: survey 2. From the 101 households, the 45 households that showed the greatest differences between the men and women's BMIs were chosen for detailed interviews. Households were selected from above and below the median BMI. For some, the mother's BMI was higher than the father's, and for others it was lower. All mothers and all but 2 fathers were interviewed (2 men worked away from home). Men and women were interviewed separately.
We administered a structured questionnaire that asked about lifestyle characteristics (identified by the villagers in focus groups) that were responsible for women's thinness (7): the excessive workload of women, limited access to supplementary food sources, and fasting practices. We asked closed questions about the frequency of working on their own or another's farm, or in other jobs; how often they carried out specific household chores; whether they went to bed last in the household and got up first; how often they watched television, spent time with their friends, or had a siesta. Women were asked whether their workload increased, decreased, or remained the same after marriage. Men and women's eating patterns were established by asking how often they missed meals, ate outside the home, ate first or last at meal times, ate nonvegetarian foods, eggs, milk, fruit, and green vegetables. They were asked whether they fasted and why, when they began to fast, how often they fasted, and how many meals they consumed on a fasting day. Respondents were asked about frequency of seeking medical treatment, how much money they spent, and why they needed treatment. We asked men and women about whether they worried, and what they worried about, because worrying had also been mentioned in the focus group discussions as a factor contributing to women's thinness.
Most questions were related to activities during the past month. Questions about medical treatment were related to the past 3 mo. Questions about habitual practices such as fasting referred to the respondent's current lifestyle.
The questionnaire was administered in the local language (Marathi) by 1 member of the GPC research team and piloted in a neighboring village. Interviews were conducted throughout the winter of 1998 and the spring of 1999.
Analysis. A summary and descriptive statistics were produced to compare the workload, eating habits, and fasting practices of men and women. Answers to questions regarding work outside the home, household chores, leisure time, sleep, eating habits, fasting, and worrying were aggregated and recoded where necessary to produce information on frequency per week. We also carried out a principal-components analysis of the relations among these activities using data from the 42 households with complete information from both the man and the woman. Scores on each principal component were compared between men and women using the Wilcoxon Signed Rank Sum test. The principal components were then correlated with BMI for men and women as well as for the difference between men and women in the same household, using Spearman's rank correlation.
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Results |
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TOPABSTRACTIntroductionMethods and ProceduresResultsDiscussionLITERATURE CITED |
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Most women were illiterate (55%), compared with 16% of the men. Most of the men had some secondary schooling compared with only 45% of the women. The majority of households were joint families, and lived in "kutcha" or "mixed pucca" housing. Although 40% lived within 1 km of the main village, 32% were in hamlets >3 km away.
In 63 families, the men considered farming either on their own or another's land their main occupation. The other 30 men were petty employees or artisans, businessmen or traders, or working in local industries. For 79 women, the main occupation was farming. Two women worked as petty employees or artisans, another 2 in local industries, and 1 business-woman traded cloth. Fourteen women called themselves housewives.
Twenty households owned no land. Thirty-six percent of families owned an iron, 64% a bicycle, 55% a bullock, 46% a tape-player or television, 11% a motorcycle or scooter, and 1% a jeep or tractor. Thirty-two percent had a personal well, and 84% had an electricity supply. Forty-seven percent of women and 15% of men reported fasting at least 1/wk. The median consumption of oil (mainly groundnut or mustard) was 0.33 kg/(person · mo).
Living in a joint family, farming family, poorer quality house, or owning a milking animal was associated with lower BMI in both sexes (Table 1). Women in families owning more farmland and living farther from the main village had lower BMIs. Higher educational status on the part of the women was associated with higher BMI in men but not the women themselves. Greater household oil consumption was associated with an increase in men's BMI but not women's. BMI was higher in men relative to women in the same household in families with higher oil consumption.
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The second principal component included variables that defined cash wealth as opposed to land wealth. Higher scores described families living in better housing, consuming more oil, and having more possessions and amenities. This component was positively associated with BMI in men (r = 0.23, P = 0.03) but not women. In households with more cash wealth, men had higher BMIs than women in the same household (correlation with % difference in BMI, r = 0.24, P = 0.02).
Women's daily activities: survey 2. The median (interquartile range) BMI was 18.2 kg/m2 (17.4–21.0 kg/m2) for the 45 women interviewed, and 20.4 kg/m2 (17.8–23.2 kg/m2) for the 43 men.
Work. A third of the women worked full time in farming, mostly on their own family's land, compared with 14% of men (Table 3). Five households owned no land, and the women worked on other's farms as daily laborers. Nine women rarely or never went out to work. Most of the men (n = 25) did work other than farming, such as working in village shops or local industry.
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1/d. The majority of women washed clothes, washed-up, fetched water, and tended to the animals every day. Women were also largely responsible for cleaning the animal shed and collecting firewood. In contrast, men were more likely to run errands, such as buying groceries and going to the main village. Both men and women in the same household often reported going to bed last and waking first, casting doubt on the reliability of this data. Women were more likely to report being the first to wake and the last to bed (n = 28) than men (n = 12). Men watched TV and saw their friends more often than women (Table 3), and more men reported usually relaxing or sleeping after work (8 women, 25 men).
Unequal access to food. The majority of women (n = 27) and nearly half the men (n = 20) said they rarely or never missed meals. More men (n = 17) reported missing 1 meal/d than women (n = 11). However men consumed snacks away from home more often (Table 4). Women were more likely to eat last at meal times. Nonvegetarian foods (meat and fish) were eaten rarely by both men and women. Eggs, milk, and milk products were consumed frequently by both sexes, although men were more likely to drink milk than women. The majority of men and women ate green vegetables >1/wk. However, men were more likely to eat fruit than women.
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Fasting.
The majority of women (n = 24), but fewer men (n = 14), reported fasting 1/wk. On average, women fasted 1/wk, whereas men fasted once every 3 wk. Sixteen women and 15 men rarely or never fasted. When fasting, most men (n = 29) ate 2 meals a day, 1 of which would be fasting snacks such as roasted sweet potato or a sago vada (a deep-fried, savory snack usually made with sago, mashed potato, coriander, peanuts, gram dal, and green chili), whereas only 18 of 45 women ate 2 meals a day.
Most women (n = 25) said they began to fast after marriage, whereas men were more likely to have fasted before they were married. Women said they took up fasting because that is what women in the area do (n = 14), because it was a family tradition (n = 9), and for religious reasons (n = 8). Men fasted for religious reasons (n = 16), to "rest their stomachs" (n = 12), or because of family tradition (n = 10). Respondents recorded >1 response to this question.
Twenty-five women and 15 men said that they had worries. Women and men worried about similar things: the future for their sons (9 women, 4 men) and daughters (13, 5), unpaid debts, and money problems (2, 1). In addition, 7 women worried about unfinished chores.
Principal components analysis. Data from both sexes were combined to derive the variable loadings in the principal components analysis. The first component defined working patterns (Table 5); high scores reflected more farm work, more household chores, less sleep, and fewer snacks. Women had higher scores than men (P < 0.001).
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Neither principal component was correlated with BMI in either men or women or with differences in BMI between spouses.
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Discussion |
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TOPABSTRACTIntroductionMethods and ProceduresResultsDiscussionLITERATURE CITED |
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We conclude that being a part of a farming household is a factor contributing to the thinness of women in this village. Our data suggest this is not simply because farming women are poorer. Women in families with more land were thinner than those who owned less land. Land wealth seems to have a negative rather than positive effect on women's BMIs, but was unrelated to men's BMIs. Though both men and women undoubtedly have hard-working lives, the farming women seemed to have time for little else other than work. Lukmanji (16) describes rural women in developing countries as bearing the burden of a "double day" to fulfill both their working and domestic roles. In another study of women in this part of India, Rao et al. (14) found that farming women had a similar domestic workload to that of nonfarming women. These authors cite a study of female farmers in Burkina Faso, West Africa (17,18), and concluded that time spent farming by women in their study was similar to that spent by the West African women, but that the Indian women spent considerably more time in domestic work. This suggests that even by the standards of poor farmers in other countries, rural Indian women work excessively hard. Previously held focus group discussions (7) suggested that farming women in our population had a particularly hard life, and that parents were prepared to go into debt to provide dowries to ensure their daughters married boys who were not farmers. Recent industrialization in rural Maharashtra may be increasing the burden on women. More women than men in our study listed their occupation as farming, and more women were working full time on the farm. This may be because men were increasingly seeking jobs in the newly opened local factories where they could earn cash and leave their women to tend the family's land.
It is unclear why the differences we observed in the workload and leisure time of men and women did not explain differences in their BMIs. Although work patterns described by the men and women broadly concur with directly observed activity data from this area, our study may have been inadequately powered, given the qualitative nature of some of our data and the small sample size. A study in Ghana showed that farm work had a strong negative effect on women's BMI (19). Alternatively, we may have lacked data on other crucial factors. We did not record the reproductive history of the women, such as parity and breast-feeding, or symptoms of reproductive tract infection. Because of difficulties in obtaining an accurate age in this population, we did not collect data on the age of the men and women, or the age differences between spouses. Skinfold measurements may have been preferable to BMI as assessments of energy status.
Joint families have been associated with worse health outcomes for children and young women (20,21). Young women in joint families are subject to the authority of their mother-in-law, and have little autonomy and decision-making power. We found both men and women in joint families to be thinner than those living in nuclear families. However, the pattern that described farming families with a joint family structure disadvantaged women more than men. This pattern may be identifying traditional family units where young married women are at the bottom of the hierarchy of decision making and access to resources. A study in Zimbabwe found that women who had more say in household decisions had higher BMIs (22). It was notable that women in our focus groups expressed a preference for living in a nuclear family, despite having fewer women with whom to share the farm and household tasks (7).
The second family pattern we identified was "cash wealth." The cash wealthy lived in better housing, had more access to amenities, owned more possessions, and consumed more oil. Why this pattern was associated with men being better nourished, but not women, is not clear. It suggests that household resources are not allocated equally to men and women, even in wealthier households.
Gittelsohn (23) described in detail the distribution of food within households in rural Nepal, and found that adult women ate last, least, and worst. Men received more "high status" foods such as animal products. Our own observations were that men consumed more milk, fruit, and snacks than women, although we found no differences in the consumption of nonvegetarian food. Women in Naved's (24) study in Bangladesh justified their preferential distribution of food to the adult males in the household by saying that men are the main breadwinners and work hardest. This may be a false perception. A study of Indian male and female farmers concluded that although energy intake in women was lower than that of men, they spend more time on economically productive work (25). However, Naved's study might explain some of our findings. This was a qualitative evaluation of the impact of "cottage-industry" schemes to farm vegetables and fish on micronutrient intakes of men and women. Women involved in the fish-farming schemes rarely ate the fish they produced, which were instead given to their guests, men, and children. In contrast, the women vegetable growers ate more of the new varieties of vegetables because other family members did not like them. If the same applies in our study area, women in cash-wealthy households may benefit less from the household's relative wealth because resources are not distributed equally among household members.
Our study demonstrates that women's lack of autonomy, especially limits on their freedom of movement, has a measurable effect on the quality of their diets. They have less access to food prepared outside the home. Unlike men, they rarely go to snack shops and food markets in the main village or even to local shops. The focus group discussions revealed that most women had no access to cash (7). Therefore, women have fewer opportunities to supplement their diet than men. There is epidemiological evidence to suggest that women's freedom of movement is a factor in the health of themselves and their children (9,12). A woman's level of education is also known to be an important factor in the health of her family, although the main focus of research has been on the health of children [for a discussion see (26)]. We found that men had higher BMIs in the households of better-educated women; although, for women, being better-educated was unrelated to their own BMIs. Men's level of education was unrelated to their own or to their wive's BMI. We have been unable to find additional evidence indicating that maternal education improves the nutritional status of husbands. This finding needs to be substantiated in a larger study.
A dietary issue that we explored in some depth is fasting. As far as we know, there is no literature on this topic. In India, fasting is undertaken by both sexes, not only for religious reasons, but also as a social ritual and for the perceived health benefits. However, our data showed that women adhere more strictly to fasting practices than men. Barbara Harriss' (27) explanation of gender differences in fasting is that men fast for their own individual, spiritual purposes, whereas women fast for the benefit of the whole household. Hinduism promotes self-sacrifice in women as a way of pleasing the deities and preventing bad luck. For women, fasting is therefore part of their duty to promote the health and welfare of their household. This sense of responsibility may underlie the fact that women report more worries than men. Unfortunately, fasting may further reduce women's nutritional status.
In a situation where everyone works hard and most people are thin, women in farming families work the hardest and are the thinnest. Villagers in rural Maharashtra know how hard life is for young farming women. Their solution is to provide dowries sufficient to attract grooms working in business or industry to ensure their daughters an "easy lifestyle with enough sleep" (7). The women themselves suggest that if they had regular paid work, much of their anxiety would be alleviated.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Manuscript received 4 May 2006. Initial review completed 7 July 2006. Revision accepted 3 October 2006.
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TOPABSTRACTIntroductionMethods and ProceduresResultsDiscussionLITERATURE CITED |
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