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TABLE 5. Sexual division of labour in India

  Men Boys Women Girls Total hours

recorded

Hours % Hours % Hours % Hours %
Agriculture 2.3 17 0.6 5 1.1 9 0.6 5 222.4
Animal husbandry 1.4 10 2.4 19 1.5 12 3.4 27 297.4
Food processing 0.3 2 0.2 2 1.3 10 0.7 6 113.9
Food preparation 0 0 0.2 2 2.5 20 1.0 8 178.7
Collecting water and firewood 0.1 1 0.6 5 0.6 5 0.3 2 67.1
Eating and 0.5 4 0.5 4 0.5 4 0.4 3 87.3
drinking
Wage labour 4.2 31 0.3 2 0.4 3 1.6 13 290.8
Child care 0.1 1 0.5 4 0.5 4 1.1 9 49.3
Leisure 3.7 28 4.2 34 3.1 24 2.8 22 577.0
Total 13.3 100 12.4 100 12.7 100 12.4 100 2,103.6

Source: Ref. 27, table 4.3.

Total number of days: 39.

Women's economic contributions should include home production of non-marketed goods and services that support the economic participation, health, and well-being of all family members. Where it has been measured, women's portion ranges from 10% to 58% of full household income (table 6). Full income includes cash income, income in kind, and the value of labour devoted to unpaid activities carried on by and for its members which might be replaced by market goods or paid services if circumstances such as income, market conditions, and personal inclinations let the service be delegated to a person outside the household [30].

Sivard [31] estimates that women's household production is worth 25%-40% of the world's gross national product (GNP). Most of this labour and its output is not marketed and so is not counted in standard production estimates like GNP.

Note: Some of the sources from which the information was collected failed to specify the length of the workday, or the type of activities classified as agricultural (for instance. it was sometimes not clear whether threshing and transport to and from the field were included). Where workdays per year were given without specification of their length, the total number of hours worked per year was calculated on the assumption of a six-hour day, and this figure was then divided by 52 to give the average number of hours worked per week. The assumption of a six-hour day may well be on the high side, since shorter hours were recorded in many of the samples, and days of more than six hours were recorded in only a few cases and then in the busiest seasons only. For these reasons, the figures in the table can convey only a broad picture of the input of work in African farming, and it must not be assumed that the table gives a satisfactory picture of differences in work input between the localities mentioned.

As labourers for hire and on the family farm, women play a major role in food production. As heads of household they are increasingly becoming farm managers, especially in food production. Women throughout the world also contribute to the household food supply through kitchen gardens that provide vegetables, tubers, and seasonal dietary supplements. Holmboe-Ottesen et al. [27] comprehensively review women's roles in the overall food system, highlighting how they are an integral part of the food production process.

In all post-harvest activities related to food, women play a major role that includes marketing, processing (in homes or factories), street vending, purchasing, and preparation in the home [33]. Post-harvest grain processing is traditionally in the domain of women. Women thresh, winnow, dry, and parboil grain as part of household production and as employment [34; 35]. As mechanical power replaces human power and increases the returns to labour, the responsibility for post-harvest processing (as well as for many agricultural activities) has devolved to men [26; 34; 35].

Food marketing chains vary tremendously within and between countries. Food systems in most urban areas comprise fragmented, dispersed marketplaces and large numbers of specialized shops and vendors. . . . Marketing and distribution of food stuffs in urban regions of developing countries generate relatively large amounts of income and employment. . .. [They] are heavily dominated by informal sector participants and small enterprises.... Women operate many food-vending and food preparing activities in Third-World cities. These activities are a source of employment. . . and are noticeably dominated by women in Asia and Africa. [33].

At the same time, such activities are often barely viable economically, giving their proprietors a poverty level income, somewhat offset by greater compatibility with child care (flexible hours, potential to bring the child to work, convenience), availability of surplus for home consumption, and social networks [36].

Women are often responsible for purchasing food as well: they decide what kinds of food to buy, in what amounts, and of what quality. Except where women are secluded, they are generally responsible for selecting and transporting food from market to home. In periurban areas, women may have poorer access to food markets and as a result pay higher prices. Musgrove [37] finds no price differential between food retail store prices in various urban poor and non-poor communities in north-east Brazil. Alternatives to household-based food purchasing and preparation - community kitchens, co-operative buying - can lower costs of food and free women's time, but they require scarce organizational skills and management. Women universally play a major role in home food preparation and serving. They also feed children until they are deemed old enough to feed themselves. Mothers' persistence in encouraging children to eat is positively correlated with good nutrition in Mexico [38]. Women play the central role in transmitting eating patterns and many cultural norms related to food.

In recent years, the poor in the heavily indebted developing countries have had to adjust to increased unemployment, reduced social programmes, and rising prices by employing a number of survival

I strategies - eating foods of lower quality, status, and

I price, increasing female employment, and relying on charity [see, e.g., 39]. The poor are already in such a marginal economic and dietary situation, however, that these coping strategies may not be adequate to avert nutritional deterioration [40].

TABLE 6. Women's contribution to full household income

Cameroon, 1974a

58.1

Lebanon, 1984b

10

Pakistan, 1975-76c

17.6

Philippines, 1975d

42

Chile, 1983e with children under 6 employed housewife

24

unemployed housewife

28

no children under 6 employed housewife

15

unemployed housewife

18

Source: Ref. 19.
a. P.87.
b. P. 136, median value.
c. P. 151.
d. P. 154. The data here showed 42% of household income contributed by the mother, 34% by the father, and 23% by the children.
e. P. 179.

 

Reproduction

Over their reproductive life span, third-world women conceive and bear six to eight children, whom they nourish with their own bodies. Because of the high energy and nutrient demands of pregnancy and lactation, women spend a large proportion of their reproductive years under possible nutritional stress .2 Women in low-income countries spend much more time lactating than being pregnant. As a result, the largest variations in the period of potential nutritional stress from reproductive activities are based on differences in the mean length of lactation.

The proportion of time women spend under total nutritional stress during a 35-year reproductive period varies from 22.7% in Costa Rica to 60.8% in Bangladesh. Women in most African and Asian countries fall in the 35%-48% group, while in the Americas most fall in the 23%-33% group. These findings are as expected because of lower incidence and duration of breast-feeding in the Americas [41; 42].

Pregnancy during the adolescent years constitutes an additional risk for mother and child. Teen-age physical growth demands compete with those for foetal growth, resulting in much incidence of low birth weight and high neonatal mortality. Teen-age pregnancy has always been the norm where child marriage is prevalent. In urban areas where the marriage age is higher, however, teen-age pregnancy is increasing, as are out-of-wedlock births. In 28 of 37 developing countries with available data, births to teen-age women account for 10% or more of all births [5].

 

Health care

Women are responsible for a large number of activities related to the production of good health - purchasing, preparing, and serving food; providing a clean and safe environment, water supply, and personal hygiene (e.g., bathing and hand washing); and procuring preventive and curative health services. Women are the crucial link between the family and the traditional and modern health systems. One study of health-seeking behaviour in 16 countries found women most often make the initial decisions about health care (including self-care) except in crisis situations involving substantial sums of money. In the latter case, the male head of household becomes involved [43].

Women are expected to implement the child survival revolution by:

- bringing children to be immunized four times during the first year of life;
- procuring or producing oral rehydration solutions and administering them to the sick child many times over the course of each day of every bout of diarrhoea;
- breast-feeding their babies on demand until the child is six months to two years old, and processing and feeding proper weaning foods in frequent meals to small children;
- bringing children under age five to a weight surveillance programme monthly.

The time costs of these activities, particularly the repetitive ones, may deter effective, sustained participation in health programmes as well as in income generating activities [44] . Few studies have been conducted on the role of time in the use of preventive health services such as immunizations [45; 46]. Research has usually found time costs an important determinant of health-service demand [44; 45]. Women's time constraints have also limited breast feeding [47; 48] and participation in a village-based vitamin-A delivery system [49; 50]. The time costs of prenatal care in the Philippines are the chief deterrent to its use [51].

Women's time costs and constraints appear to be either undervalued or ignored in the design of most primary health care systems. Clinic hours, long waits, and the need to go to a clinic (rather than a community worker) for certain services are factors to be considered.

TABLE 7. Calculation of the percentage of women's reproductive life under the physical and nutritional stress of pregnancy and lactation

  Cumulative fertility (1) Number of months pregnant Mean duration of lactation (months) (5) Total months lactating (6) = (1) x (5) Total months pregnant and lactating (7) = (4) + (6) % of reproductive life in stress (8)
Live births (2)a Miscarriages (3) Total (4)
Africa
Kenya 7.88 69.10 3.61 72.71 15.70 123.72 196.43 46.77
Cameroon 5.18 45.42 2.37 47.79 19.30 99.97 147.76 35.18
North Sudan 6.30 55.24 2.88 58.12 15.90 100.17 158.29 37.68
Lesotho 5.44 47.70 2.49 50.19 19.50 1 06.08 1 56.27 37.21
Senegal 7.20 63.14 3.30 66.44 18.50 133.20 199.64 47.53

Asia and the Near East

lordan 8.60 75.41 3.94 79.35 11.10 95.46 174.81 41.62
Syria 7.80 68. 40 3.57 71.97 11.60 90.48 162.45 38.68
Bangladesh 6.70 58.75 3.07 61.82 28.90 193.60 255.42 60.81
Nepal 5.70 49.98 2.61 52.59 25.20 143.64 196.23 46.72
Pakistan 7.50 65.77 3.43 69.20 19.00 142.50 211.70 50.40
Sri Lanka 5.94 52.09 2.72 54.81 21.00 124.74 179.55 42.75
Fiji 6.50 57.00 2.98 59.98 9.90 64.35 124.33 29.60
Indonesia 5.20 45.60 2.38 47.98 23.60 122.72 170.70 40.64
Korea, Rep. of 5.60 49.11 2.56 51.67 16.30 91.28 142.95 34.04
Malaysia 6.30 55.24 2.88 58.12 5.80 36.54 94.66 22.54
Philippines 7.00 61.38 3.20 64.58 13.00 91.00 155.58 37.04
Thailand 6.80 59.63 3.11 62.74 18.90 128.52 191.26 45.54

The Americas

Columbia 7.30 64.01 3.34 67.35 9.20 67.16 134.51 32.03
Peru 6.99 61.30 3.20 64.50 13.10 91.57 156.07 37.16
Costa Rica 6.70 58.75 3.07 61.82 5.00 33.50 95.32 22.70
Dominican Rep. 6.80 59.63 3.11 62.74 8.60 58.48 121.22 28.86
Mexico 7.10 62.26 3.25 65.51 9.00 63.90 129.41 30.81
Panama 5.90 51.74 2.70 54.44 7 40 43.66 98.10 23.36
Guyana 6.90 60.51 3.16 63.67 7.20 49.68 113.35 26.99
Haiti 6.02 52 79 2 76 55 55 15.50 93.31 148.86 35.44
Jamaica 5.60 49.11 2.56 51.67 8.10 45.36 97.03 23.10
Trinidad

and Tobago

5.90 51.74 2.70 54.44 8.00 47.20 101.64 24.20

Refer to accompanying text for explanation of procedures used and for sources of raw input data.

a. Column 2 values are derived by multiplying column 1 values by 8.769.

Women's nutritional status

Women are often exhausted by the combination of reproductive demands, heavy work load, and inadequate diet 1521. Maternal depletion over the course of numerous or closely spaced pregnancies is an often hypothesized but little measured phenomenon [53; 54].

Careful, systematic analyses of women's diet and nutritional status are rare. Data from small and infrequent studies of women's anthropometry, iron status, and dietary intake suggest that they are at high nutritional risk, but better surveillance of women's nutrition is needed [52]. Assembling data based on various methodologies and sampling procedures leads to problematic interpretations. Moreover, it is very difficult to interpret these data without a clear understanding of standards [55].3

Anaemia

Of particular importance is iron-deficiency anaemia, which reduces work capacity, increases fatigue, and elevates risks of haemorrhage and death in childbirth [56; 57]. A majority of the world's women are anaemic, largely because of iron deficiency resulting from inadequate iron intakes and excessive blood losses from parasites or menstruation and closely spaced births. Nutritional anaemia ranks among the four most prevalent, serious nutritional problems in the world. Anaemia is generally defined as a significant reduction (below a standard level) in haemoglobin concentration and/or red blood cells (haematocrit). It occurs two to three times as frequently in non-pregnant women as in men, and up to 20 times as frequently in pregnant women [84]. Data on women in developing countries indicate that fewer than half the non-pregnant women and nearly two-thirds of the pregnant women have haemoglobin concentrations indicating anaemia. The overall proportion of women and pregnant women with below-standard haemoglobin levels is highest in South Asia and Africa, followed by Oceania. East Asia, and then Latin America (see FIG. 3. Proportions of women with below-standard levels of haemoglobin concentration). Extensive information on anaemia prevalence among women by country is available elsewhere [85; 86].

Dietary intake

An undernourished woman is at increased risk for giving birth to a low-birth-weight baby, who faces greater mortality risks. Poor nutrition also affects her activity level and overall physical performance.

TABLE 8. Summary of studies on dietary intake of women in developing countries

Study Sample characteristicsa Year/season Calories Protein
kcal % RDA Grams % RDA

Recommended daily allowance (RDA)

FAO/WHO/UNU recom-

mendations for women

18-60 years old [58]

55 kg          
NPNL   2,100   41.0  
pregnant   2,385   47.0  
lactating          
1st 6 months   2,600   58.5  
after 6 months   2,600   54.0  

Africa

Ethiopia [59] pregnant, 3rd trimester          
low SES (20)   1,539 64.5 41.2 87.7
high SES (10)   2,963 124.2 81.5 173.4
Gambia [60] pregnantb          
2nd trimester dry season 1.452 60.9    
3rd trimester   1,478 62.0    
2nd trimester wet season 1,459 61.2    
3rd trimester   1,381 57.9    
lactatingb          
0-3 months dry season 1,772 68.2    
3-6 months   1,658 63.8    
6 9 months   1,674 64.4    
9-12 months   1,648 63.4    
0-3 months wet season 1,471 56.6    
3-6 months   1,314 50.5    
6-9 months   1,392 53.5    
9-12months   1,421 54 7    
           
Kenya [61] rural 1977-79        
NPNL (50)   1,765 84.0 59.0 143.9
pregnant          
1st trimester (109)   1,602 67.2 51.0 108.5
2nd trimester (165)   1,623 68.0 50.0 106.4
3rd trimester (92)   1,406 59.0 45.0 95.7
lactating, 10-23          
months (244)   1,978 76.1 63.0 107.7
Upper Volta [62] farmers, non-pregnant

(14)

Dec./Jan. (end

of harvest)

1.515 72.1 0.8c 1.95
    44.8d 109.3

Asia and Oceania

India [63] low SES

pregnant (100)

  1,815 76.1 44.0 93.6
lactating (70)   1,858 71.5 42.7 73.0
same women before

pregnancy (100)

  2,152 102.5 49.8 121.5
India [64] lactating

very poor (54)

  1,439 55.3 39.6 67.7
poor (50)   1,872 72.0 46.1 78.8
middle (57)   1,906 73.3 47.2 80.7
upper middle (49)   2,279 87.7 55.0 94.0
India [65] lactating (39)          
4th week   1.702 65.5 35.0 59.8
16th week   2,090 80.4 42.6 72.8
52nd week   1,711 65.8 35.6 65.9
Korea [66] rural, average SES, winter 1976        
pregnant (93)   2,635 110.5 77.5 164.9
Micronesia [67] women on wealthy, Jan. 1976        
recently Westernized          
Nauru (43)   5,223 248.7 184.0 448.8
New Guinea [68] subsistence farmers          
coastal          
pregnant (9)   1.414 59.3 3.6c  
lactating (13)   1,412 54.3 3.0c  
NPNL (14)   1,402 66.8 3.1c  
highlands          
pregnant (7)   2,001 83.9 10.8c  
lactating (14)   2,133 82.0 9.2c  
NPNL (14)   2,068 98.5 10.4c  
Papua New Guinea [69] adult women (47)e 1975 1,345 64.0 28.5 69.5
non-workers' wives (33)e 1984 1,491 71.0 27.3 66.6
workers' wives (27)e 1984 1,743 83.0 35.9 87.6
Philippines [70] urban household survey          
housewives (94)     81.7f   81.4f
adult offspring (31F)     75.1f   78.2f
Philippines [71] urban 1983-86        
pregnant, 3rd trimester          
(2.555)   1,595 66.9 51.0 108.5
postpartum          
2 months (2.177)   1,675 64.4 53.8 92.0
6 months (2,036)   1,483 57.0 48.5 82.9
14 months (1.971)   1,382 53.2 43.2 80.0
rural          
pregnant, 3rd trimester          
(772)   1,159 48.6 38.3 81.5
postpartum          
2 months (696)   1,242 40.3 40.3 68.9
6 months (669)   1,121 43.1 35.8 61.2
14 months (669)   1,039 40.4 31.6 58.5
Singapore [72] random clinic patients          
pregnant          
1st and 2nd          
trimesters (14)   2,386 100 57.1 121.5
3rd trimester (23)   2,487 104.3 69.0 146.8
non-pregnant (24)   1.927 91.8 53.2 129.8
Taiwan [73] pregnant (112)          
1st trimester   1.211 50.8    
2nd trimester   1,228 51.5    
3rd trimester   1,151 48.3    
lactating (112)          
0-2 months   1,319 50.7    
3-5 months   1.288 49.5    
6-8 months   1,366 52.5    
9-11 months   1,398 53.8    
Thailand [74] urban (15)   1,547 73.7 56.0 136.6
rural (21)   1,292 61.5 46.0 112.2
pregnant (11)   1,980 83.0 39.0 83.0

Latin America

Brazil [75] semi-urban migrant

workers (94)

  1,068 50.9 28.0 68.3
Colombia [76] pregnant, 2nd trimester          
(207)   1,587 61.0 35.6 60.9
Costa Rica [77] rural. pregnant 1979-80        
1st trimester ( 12)   1,472 61.7 42.8 91.1
2nd trimester (46)   1.587 66.5 47.7 101.5
3rd trimester (46)   1,718 72.0 51.2 108.9
Guatemala [78] NPNL (20)   1,418 67.5 39.0 95.1
pregnant          
2nd trimester (57)   1,723 66.3 50 85.5
3rd trimester (57)   1,819 76.3 54.0 114.9
lactating (36)   1,599 61.5 58.0 100
Guatemala [79] NPNL (6)g   1.876 89.3    
lactating (18)g   1,929 74.2 47.6 81.4
Guatemala [80] pregnant, 2nd half (720) 1969-70 1,562 65.5    
lactating          
3 months (520)   1,766 67.9    
6 months (385)   1,764 67.8    
9 months (381 )   1,795 69.0    
1 year (372)   1,708 65.7    
Mexico [81] pregnant (42)   2,020 84.7 53.1 113.0
lactating (12)   2.030 78.1 54.2 92.6
NPNL (54)   1,750 83.3 47.1 114.9

Middle East

Iran [82] outpatients at 2 urban          
hospitals, 3 months          
postpartum          
low SES (15)   1,840 70.8 61.0 104.3
mid SES (28)   2,270 87.3 82.0 140.2
Iran [83] urban. Iow SES. pregnant, autumn 1963        
at MCH clinic          
<5 months (97)   1,815 79.0 57.6 74.0
>5 months (60)   1,996 85.0 57.4 74.0

a. NPNL = non-pregnant, non-lactating. SES = socio-economic status. Figures in parentheses indicate sample size.
b. Total sample, pregnant + lactating, = 156.
c. Animal protein.
d. Vegetable protein.
e. Sample size refers to number of days of intake.
f. Data given as percentage of RDA.
g. Supplemented.

Caloric intake is often low among women (see FIG. 4. Women's calorie intake as percentage of WHO recommended daily allowance (cf. table 8)), although a few populations show adequate intakes (Korea) or excessive ones (Micronesia). Deficiencies in caloric intake are common, regardless of physiologic status. In a few studies, pregnant women consume less than non-pregnant women. In other countries they consume more, but their diets are still deficient in calories. Lactating women generally consume more than their non-pregnant counterparts but still not enough to meet the daily recommendations. Where intakes are reported by income, low-income women appear to consume less than their middle- and high-income counterparts. Women generally meet a smaller percentage of their current recommended daily requirements than men [62; 75; 70].

Protein intakes appear to be more adequate than caloric intakes in most countries. However, the reported figures do not take into consideration that, when calories are deficient, protein will be used for energy. Another problem is that protein quality is not usually reported. Women often consume lower quality vegetable protein, while men receive the larger share of whatever animal protein is available. This situation has been shown in Burkina Faso (then Upper Volta), where women consumed 0.8 grams of animal protein compared with men's consumption of 10.3 grams daily (women also ingested a lower proportion of the gross protein requirement than men). Vitamin and mineral intakes of women show similar inadequacies absolutely and relative to men's diets [52].

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