Indian Pediatrics 1998; 35:975-983

 

M. Srivastava, D.K. Agarwal, A. Agarwal, S. Agarwal and K.N. Agarwal*

From the Maternal and Child Health Unit, Department of Pediatrics, Institute of Medical Sciences, Banaras Hindu University, Varanasi 221 005 and Department of Pediatrics*, University College of Medical Sciences, Delhi-ll0 095, India.

Reprint requests: Prof. K.N. Agarwal, D-115/Sector 36, Noida (U.P.) 201301, India.

Manuscript received: February 2, 1998; Initial review completed: March 18, 1998;
Revision accepted: July 10, 1998

 

Objective: To find out the degree of current under-nutrition in rural reproductive age women. Setting: 49 villages of two adjoining rural blocks of Varanasi. Methods: 6130 non-pregnant and non-lactating rural women in the age group ), 8-45 year were studied for sociodemographic characteristics and anthropometry, i.e., weight, height and midarm circumference. Their percentiles for age and for weight for height were calculated by using cubic spline method. Results: The women in 10th centile weighed <38kg and those in >90th celltile weighed 47-48 kg; 74.2% had weight <45 kg. The 50th centile height ranged between 148-150 cm; 13.5% were <145 cm. For mid arm circumference 50th and 90th centile values were around 22 and 24 cm, respectively. Mid arm circumference and height had significant linear correlation with weight. Conclusion: Around 50% rural UP women in pre-pregnancy state are undernourished. With age these rural women did not change in weight or mid-arm circumference.

Key words: Non-lactating, Non-pregnant, Nutritional status, Rural.

THE average height of Indian women as documented in some studies is 150 cm which is 13.7 cm less than the average height of 163.7 cm of women in USA(1-4). However, it is comparable to average height of women of lower income groups . of Indonesia, Philippines, Guatemala and Chile(5-8). Little can be done about stunted height during pregnancy but these women deviate sharply from their contemporaries in their weight for height which is amenable to improvement.

In a limited survey conducted in Bihar and Uttar Pradesh, 17.4% and 10.8% pregnant women weighed <40 kg, 57.1 % and 60%, weighed <45 kg, respectively, suggesting poor nutritional status(1). In the present study reproductive age rural women (non-pregnant and non-lactating) vvere measured anthropometrically with an objective to find the degree of current under nutrition in pre-pregnancy state. An attempt was also made to prepare percentiles for anthropometric measurements.

Subjects and Methods

The present study data were collected during 1988-1990 in two Blocks of District Varanasi, Uttar Pradesh:

I. Kashi Vidya Peeth block (non-ICDS) is approximately 10 km from Institute of Medical Sciences, Varanasi. It is spread out in 147 sq. km. having 121 villages. According to 1988-1989 census of Varanasi district the total population of the block was 1,28,683 consisting of 69,313 males and 59,370 females. The block has 61 schools, 11 middle schools and 5 intermediate colleges. Of these, 14 schools are only for girls.

II. Harahua block having 148 villages is situated 25 km away from the Institute of Medical Sciences, Varanasi, India. Integrated Child Development Services (ICDS) scheme was launched in this area in 1983. The total population of this block was 1,32,072 (69,390 males and 62,682 females). In all there are 69 schools, of which 54 are primary, 8 junior and 5 high schools and 2 intermediate colleges.

Population selected: In Kashi Vidya Peeth Block (non-ICDS)-21 villages having a population of 32,307 and in Harahua Block (ICDS)-28 Anganwadi centers having a population of 33,770 were selected using random sampling technique (ICMR Statistical Unit). There were a total of 4,582 households in non-ICDS and 4,492 in ICDS area. There were 27.2% family planning acceptors and postmenopausal women in non-ICDS and 24.2% in ICDS area thus leaving the target women of 4,327 in non-ICDS and 4,694 in ICDS areas.

The present study is restricted to the noh-pregnant non-lactating (NPNL) Women of the study area in reproductive age group. Non-lactating women were those who had the youngest child 6f more than one year of age. Women having history of any chronic illness which was likely to affect their current nutritional status were excluded from the study. In all 6130 healthy women were subjected to anthropometric measurements (number of women in ICDS Block=3282, Non-ICDS Block=2848).

A pre-tested semi structured questionnaire was administered to eligible women from each household to elicit information regarding their family, education, occupation, socio-economic status and socio-demographic profile. The socio-economic index was calculated on the basis of patient's education, occupation, caste and per capita income. A linear composite score was obtained by combining the rank order scores of these six variables(9). Anthropometric measurements were taken by using Chattilon weighing scale (USA), anthropometric rod and fibre glass tape by standard techniques(10). Age of women was assessed using age of menarche, marriage, consummation of marriage and age of children by using calendar of important local events. The women were examined at their house by a team of nutritionist and. social . scientists with the help of female village worker.

Percentile for weight, height, midarm circumference for age were calculated using the cubic spline method(11). Weight for height percentile at each cm height were also calculated(12):

Weight of women at that height
----------------------------------------------------------x 100
Weight at 90th centile for that height

The basic method of systematic curve smoothing is spline polynomial smoothing of the observed percentile value. Alternatively, in the present study the system was raised from cubic to quadratic to allow better interrelationship between the percentile lines. It was seen that existing cubic spline technique had strength of placing (fixed or variable) knots. Using the fixed knots alternatively gives some degree of parallelism and interrelationship between the per centile(10). Pregnancy outcome data coresponds to the prospective conceptions followed. As pre-pregnancy weight, height and mid-arm circumference were interrelated the regression equations. were developed using mid-arm circumference and height data for calculation of weight. Mean, standard deviation and error, percentile, Pearson correlation matrix, linear regression, paired 't' tests, chi square test and analysis of variance were also calculated.

Results

The mean age, family size, gravida, parity, mean pregnancy interval and socio-economic index were comparable in the selected women of two blocks (Table I). The socio-economic and environmental characteristics of study women showed that 64.6% of the study women belonged to backward class followed by 24.2% in scheduled caste and only 11.1% belonged to upper class. The average income of these women was found to be Rs. 169.0±1.3 per month. As many as 67.5% were still using well water for domestic use. Only 33% of the households had electrification, remaining used kerosene lamp as a source of light. Illiterate women comprised 87.0% of the total and their main occupation was domestic activities (housewives). The means for height, weight and midarm circumference (MAC) in the ICDS were higher as compared to the non-ICDS by 0.8 cm, 1.1 kg and 0.2 cm, respectively. These differences are significant in view of large sample size. However, the 50th centile values for height and mid arm circumference did not differ >3% and for weight >6% for both the blocks at any point as compared to the corresponding 50th percentile of the pooled data. It was felt that study women in two blocks are not varying much and therefore data were pooled to have a larger sample for calculation of percentiles in pre-pregnancy state(13).

Anthropometric Characteristics

The frequency and percentage distribution of women in the ICDS and non-ICDS blocks for weight and height are given in Table II. The analysis o( combined data showed that 56.0% women were having height less than 150 cm, 13.5% less than 145 cm and 40.5% were between 145-150 cm while 27.1% women had their weight less than 40.0 kg and about 74.2% less than 45 kg.

TABLE I

 Characteristics of Rural Non-pregnant Non-lactating Women (Mean ±SE).

Characteristics	Harahua (ICDS) (n = 3282)	K.V. Peeth (Non-ICDS) (n = 2848)
Age (yr)	26.0±0.10	25.2±0.10
Family size	8.1±0.06	9.2± 0.09
Parity	3.0 ± 0.04	2.9 ± 0.03
Gravida	3.6±0.04	3.5±0.03
Socio-economic index (caste, education- mother and father, per capital income)	10.7±0.04	10.7±0.04
Mean pregnancy interval (months)	21.2±0.29	23.2±0.19
Anthropometry
Height (cm)	149.4±0.07	148.6±0.01
Weight (kg)	42.6 ±0.07	41.5±0.09
Mid-arm circumference (cm)	22.1±0.03	21.9 ± 0.03

Table III shows that the weight and mid arm circumference percentiles with the advancement of age did not show any change. The 90th percentile MAC averaged 24 cm and corresponded to 10th centile value of NCHS for 18-34 yr of age. The averages for.. US women were invariably higher than the 90th centile values of rural women except for height 152-154 cm(4). The 50th centile height values for 18-19 and 34-35 years remained 149 cm, with similar pattern for 5th and 90th centiles, indicating possibly no secular trend.

 

TABLE II

Percentage Distribution of Height and Weight of Non-pregnant and Non-lactating Women

Categories		Block				Pooled
		ICDS		N6n-ICDS
		%	(n)	%	(n)	%	(n)
Weight (kg)	< 35.0	1.6	(52)	5.6	(159)	3.4	(211)
	35.0-39.9	19.0	(620)	29.2	(832)	23.7	(1452)
	40.0-44.9	51.3	(1687)	42.1	(1199)	47.1	(2886)
	45.0-49.9	23.5	(771)	17.3	(492)	20.6	(1263)
	50.0-54.9	3.6	(118)	4.4	(125)	4.0	(243)
	55.0-59.9	0.8	(27)	1.2	(34)	1.0	(61)
	≥60	0.2	(7)	0.2	(7)	0.2	(14)
	Mean±S.E. (n)	42.58±0.07 (3282)		41.47±0.09 (2848)		42.49±0.09 (6130)
Height (cm)	< 140.0	1.5	(48)	3.8	(107)	2.5	(155)
	140.0-144.9	8.5	(279)	13.9	(397)	11.0	(676)
	145.0-149.9	41.8	(1371)	38.9	(1109)	40.5	(2480)
	>150	48.2	(1584)	43.4	(1235)	46.0	(2819)
	Mean±S.E. (n)	149.41±0.07 (3282)		148.60±0.01 (2848)		149.26±0.06 (6130)

The Pearson correlation matrix Was applied to study the impact of socio- demographic variables on weight and midarm circumference. The education of husband and socio-economic index was significantly positively related to weight and midarm circumference in these women. The gravida, parity and pregnancy interval did not show any relationship with weight and MAC (Table IV). As socio- economic index was related to weight and MAC, interrelation between these two parameters was studied to predict weight. The linear equation derived was;

y = 1.75 x + 3.2755 where y = weight (kg) and x = mid arm circumference (cm).
Similarly using height to predict weight
equation was: y = 0.458 x - 26.72 where y = weight (kg)
and x = height (cm).

The reliability of these equations was checked by using paired 't' test and it was found that the difference in the observed and calculated values was non-significant. Calculating weight for height centile charts in case of these rural women presented a problem as 13.5% of the women were shorter than 145 cm, below which average and range for weight as international standards are not available. Thus study women weight for height centiles were calculated (Table V). The 90th centile weight at that height was taken as reference value (possibly optimal attainable). The women having weight for height < 90% of the reference weight for height derived by the manner were 53.2% (undernourished 49.2% and 57.6% in the ICDS and non ICDS), those having weight for height 90-110% considered as normal were 45.2% (49.2% and 40.6% in the ICDS and non ICDS blocks) and> i 10% considered as over-nourished were 1.6%.
 

TABLE III Weight (kg), Height (cm), Mid Arm Circumference (cm) Percentiles for Non-pregnant and Non- lactating Women (Smoothed)
Age	(Yrs)	N	Percentile
			5th	10th	50th	75th	90th
18-19	i	612	35.1	36.4	41.6	44.4	47.0
	ii		141.3	143.0	149.0	151.0	154.8
	iii		20.0	20.0	22.0	23.0	24.0
20-21	i	1010	35.2	36.5	41.7	44.5	47.0
	ii		141.6	143.4	148.2	151.6	154.0
	iii		19.5	20.0	22.0	23.0	24.0
22-23	i	755	35.5	36.6	41.6	44.6	47.3
	ii		142.0	143.8	149.2	151.8	154.3
	iii		19.5	20.0	22.0	23.0	24.0
24-25	i	874	35.9	37.2	41.8	45.0	47.6
	ii		142.3	144.5	149.3	152.0	154.4
	iii		19.5	20.0	22.0	23.0	24.0
26-27	i	588	36.0	37.3	41.8	45.0	48.0
	ii		142.4	144.5	149.5	152.0	154.7
	iii		19.5	20.0	22.0	23.0	24.0
28-29	i	736	35.3	37.1	42.0	45.0	48.3
	ii		142.1	144.2	149.8	152.0	154.7
	iii		19.5	20.0	22.0	23.0	24.0
30-31	i	641	35.0	36.6	41.8	44.8	48.0
	ii		141.6	143.6	149.8	152.0	154.8
	iii		19.1	20.0	22.0	23.0	24.0
32-33	i	240	34.6	36.5	41.7	44.7	47.8
	ii		141.2	143.2	149.8	152.0	154.5
	iii		19.2	20.0	22.0	23.0	24.0
34-35	i	293	35.5	36.7	41.6	44.8	47.2
	ii		141.6	143.5	149.5	151.9	158.1
	iii		19.2	20.0	22.0	23.0	24.0
36-37	i	88	35.6	37.1	42.0	45.3	48.1
	ii		140.4	143.8	149.8	152.1	154.6
	iii		19.0	20.0	22.0	23.0	24.0
38-39	i	99	35.0	37.5	41.6	45.0	4~.7
	ii		138.4	143.7	149.6	151.8	154.8
	iii		19.2	19.5	21.8	23.1	24.0
40-41	i	139	35.0	37.5	41.6	44.7	47.8
	ii		137.0	144.0	149.8	151.7	154.3
	iii		18.2	19.0	22.0	23.2	25.0
42-43	i	35	37.0	38.0	41.5	44.2	46.9
	ii		138.7	144.3	149.8	151.4	153.6
	iii		18.2	19.0	22.0	23.2	25.0
44-45	i	20	37.5	37.0	43.0	45.0	47.5
	II		141.5	146.5	150.5	155.0	156.0
	iii		20.0	20.5	22.5	23.5	24.0
Total		6130

i=weight (kg); ii= height (cm); and iii=mid arm circumference (cm)

 

TABLE IV

Pearsons Correlation Matrix of Socio-demographic Variables of Study Women.

Variables	Weight	Height	Mid arm circumference
Socio-economic index	0.1885**	0.1795**	0.127**
Education of husband	0.1435**	0.151**	0.0965**
Gravida	0.013	0.0265	0.025
Parity	0.031	0.024	0.018
Pregnancy interval	0.0205	0.0305	0.0195

 

 

TABLE IV

 Weight for Height Percentiles of Non-pregnant and Non-lactating Women (Smoothed)
(n = 6130)

Height (cm)	n	Weight percentile (kg)					WHO 1995 (14) average range
		5th	10th	50th	75th	90th
138	104	31.8	32.8	36.6	38.7	43.2
139	51	32.0	32.9	36.8	38.9	43.4
140	92	32.1	33.0	36.9	39.0	43.6
141	98	32.3	33.1	37.8	40.3	43.9
142	129	32.5	33.8	38.8	41.1	44.2
143	164	33.4	34.8	39.4.	42.0	44.3
144	193	33.9	35.5	39.7	42.4	44.5
145	320	34.7	36.2	40.2	42.8	44.8	46.0	42-53
146	366	35.2	36.5	40.3	43.0	45.1
147	471	35.5	37.0	40.5	43.3	45.2
148	692	35.8	37.3	41.0	43.5	45.5	46.5	42-54
149	631	36.0	37.7	41.5	44.2	46.1
150	844	36.2	38.0	42.2	44.7	46.0	47.0	43~55
151	354	36.7	38.2	42.5	45.3	47.7
152	495	37.1	38.6	43.3	45.8	48.5	48.5	44-57
153	265	37.4	39.1	43.6	463	49.0
154	319	37.7	39.2	44.2	46.9	49.5	49.5	4~58
155	129	38.1	39.4	44.5	47.8	50.4
156	121	38.7	39.7	44.8	48.5	50.9	50.4	45-58
157	97	38.1	40.0	45.0	48.0	51.5
158	61	39.4	40.3	45.2	49.0	52.5	51.3	46-59
>159	134	39.4	40.3	45.4	49.2	53.0

The distribution of women according to, BMI [(wt(kg)/height (m²] revealed that 39.5% women (35.5% in ICDS and 42.0% in non-ICDS) were below 18.5 kg/m² (undernourished). These values are lower than 53.2% observed as undernourished having wt/ht   < 90% of the 90th centile value of these rural women.

Discussion

Undernourished women of non-pregnant ,non lactating group are not covered under any national nutrition or health programme. They represent pre-pregnancy status and constitute an important vulnerable group. Normally in, women with the advancement of age, body weight and midarm circumference (MAC) tend to increase. This age related change is ascribed to a combination' of reduced energy requirements, increased sedentary nature of life style and altered hormonal profile. Data available in our country clearly show that this age related weight change is economic status dependent(15). The NCHS data(4) showed increase in mean weight of 7-8 kg in age group 18-54 yr; in the 10th centile the change was only 2 kg while in the 90th centile it was around 12 kg. The MAC increases by about 3.6 cm, with advancement of age. However in the present study, women failed to gain in weight as well as MAC in both the blocks. No difference was observed in height, weight and MAC of the women who were between 18- 19 yr and 38-39 yr even for the 90th centile data (Table III). In these rural areas under 6 yr children were assessed in 1981-83 and 1991-93, but did not show any secular trend in height, affirming that nutrition and health inputs have probably made no significant impact in this region (un- published).

In NNMB data (1975-79 vs 1988-90) after a gap of 12 years, the height increase . was marginal (1.2 cm). The increase for weight and fat fold in the NNMB data of 1975-79,1988-90 and 1994 was 0.7 to 2.0 kg and 1.5 to 2.5 mm, respectively showing some secular trend(2,15-17).

The present study data pertains to rural villages of Varanasi; the means for height and weight were 149.3 cm and 42.5 kg, respectively. These correspond to 11 district rural women data in Bihar and Uttar Pradesh, the mean heigl)ts being 148.4 and 148.7 cm with 50% and 58%, being < 45.0 kg, respectively(1). These data are also similar to the NNMB data for Andhra Pradesh, Gujarat, Orissa and Tamil Nadu(15). In rural women nutritional status data in early pregnancy and lactation from Gujarat and Maharashtra, height ranged between 139 to 161 em and women were underweight(18). These observations on pre-pregnancy rural women of Varanasi and other parts of India highlight the mag- nitude of the problem of low weight and short statured women in reproductive age group.

In populations where the average height of reproductive age female is ≤150 cm (India, Bangladesh, Indonesia and Colombia) and pre-pregnancy weight < 40 kg, poor pregnancy outcome (incidence of low birth weight (LBW) and neonatal mortality rate) is usually documented(18). Garn and Pesick(19) have shown that pre-pregnancy weight was a better predictor of LBW, and birth weight variability than various other height and weight indices. In general, higher the pre-pregnancy weight, the lower is the incidence of prematurity, (≤38 wk gestation) and there is decrease in incidence of very low birth weight « 2300 g). If weight gain in pregnancy is high enough, the effect of lower pre-pregnancy weight can be partially compensated. If, however, the weight gain is also low then pre-pregnancy weight is of primary impotance(14,19). Rural Women in India, often have low pre-pregnancy weight and low weight gain in pregnancy. In them, the former alone will be able to guide for selection of high risk women or those needing special nutrition and health care. In the present study, for evaluating pregnancy outcome including birth weight, and perinatal mortality, women's weight/ height ratio < 90 centile was a good predictor while BMI in the short statured woman was non discriminatory.

In our setting, the weight taken in non- pregnant non-lactating (NPNL) state can safely be considered as pre-pregnancy weight since: (a) the present study rural women showed no change in mean weight with age; (b) 100 rural NPNL women in present study area (7 villages) on monthly weight recording throughout the year did not show any weight variation(20); and (c) these rural women showed delayed weight gain in pregnancy, i.e., in better nourished (weight >45 kg and MAC >23 cm) from 11 week of gestation and in undernourished (wt < 45 kg and MAC < 23 cm) from 16th week of gestation. The weight gain was 8.3±1.1 and 6.5±1.9 kg, respectively in these two groups(20).

In conclusion, in 6130 rural women of Varanasi (non-pregnant and non lactating) in the reproductive age, 13.5% were below 145 cm, 27.1% were below 40 kg; BMI was below 18.5 (thinness) in 40% and weight for height below 90% of 90th centile was documented in 53.2%. The present anthropometric data on rural women of Uttar Pradesh have thus clearly demonstrated that majority of women are not only under-weight but also short statured.'

Acknowledgements

We are indebted to the Indian Council of Medical Research and USAID, New Delhi for the financial support. The Banaras Hindu University, Varanasi provided the infra structural support.