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Determinants of nutrition status of rural preschool children in Andhra Pradesh, India


P. Yasoda Devi and P. Geervani


Abstract


A longitudinal study was conducted in four villages in the Medak district of Andhra Pradesh. One-hundred and ninety-seven children up to four years old were selected from low-income households in the study area. Pre-tested, structured interviews were conducted to collect information on child-related, maternal, paternal, and socio-economic factors from the households. Two child-related factors, number of diarrhoeal episodes and calorie adequacy of diet, showed a highly significant effect on a child's current as well as past nutrition status. The results of this study indicate a strong influence of socio-economic status and parental care on the control of infectious diseases and food intake, which are the two major causes for malnutrition among children in developing countries


Introduction


Malnutrition continues to be a problem of considerable magnitude in most of the developing countries of the world. Children age 0 to 3 years are nutritionally the most vulnerable. More than half of the children in India are unable to grow to their full physical and mental potential owing to malnutrition. Nutritionists are increasingly aware that the condition is multifaceted and is not just a problem of food shortage. Realization is growing that malnutrition is a result of more complex big-social and behavioural determinants that affect child feeding and rearing [1].

In homogeneous poor communities living under fairly uniform socio-economic and environmental conditions, considerable variation is observed in the health and nutrition status of preschool children. At one end of the spectrum, a very small number of children exhibit only minimal growth retardation; at the other end some children suffer from extreme forms of undernutrition such as kwashiorkor and marasmus; and in between are large numbers of children with various degrees of growth retardation.

The factors that underline these differences have not yet been properly elucidated. In a household where socio-economic status is consistently similar over a long period, only one child or some children suffer from the extreme forms of protein-energy malnutrition. The reasons for this are not well understood and established. The present study was an attempt to screen specific factors that are significantly associated with malnutrition in rural preschool children of a similar socio-economic group in Andhra Pradesh, India.


Materials and methods


This was a longitudinal study in four villages in the Medak district of Andhra Pradesh. All low-income families with at least one preschool child were selected from the villages using a suitable socio-economic scale [2] with necessary modifications. The subjects were 197 children of up to four years old from these households.

 

Tools

Pre-tested, structured interviews were conducted to collect information on child-related, maternal, paternal, and socio-economic and environmental factors from the households. Child-related factors were age, birth order, age of starting weaning food, calorie adequacy of diet, immunization coverage, number of diarrhoeal episodes, number of upper respiratory tract infections, other infections, illness prior to the study period, regularity of baths, type of hospital visited during sickness, and primary care-taker when the mother goes out to work.

Maternal factors were education, occupation, health status during pregnancy, health during the study period, help received from parents, help from family members for household activities, and nutritional awareness. Paternal factors were occupation, education level, health during study period, frequent quarrels with wife, expenditure on luxuries and amusements, time spent with the family after work, and whether the father is loving and affectionate with the child.

The socio-economic factors were type of family, caste, family size, per capita income, land availability, income from land, per capita food expenditure, type of roofing, floor space per person, source of drinking water, and number of children in the family attending school or college.

All the factors predicted to influence nutrition were included in the interview. Data were elicited both by interviewing the mother and through home observations during one year of the study period. These independent variables were suitably coded.

Assessment of dietary intake

Diet surveys were conducted in all the families in two seasons of the year, peak and lean, with regard to food consumption. Information about each preschool child's diet was collected from all families using a 24-hour food weighing method. The percentage calorie adequacy of the child's diet was calculated taking the mean calorie intake in the two seasons of the year and comparing it with the recommended daily allowance prescribed by the Indian Council of Medical Research (ICMR) [3].

Morbidity

The morbidity of the children was assessed regularly once a week during the study period. The frequency of various infections and other types of illnesses (diarrhoea, cold, cough, fever, scabies, measles, etc.) during each week preceding the day of collection of information, type of treatment given, and dietary modifications adopted owing to illness were determined by questioning the mothers.

Nutrition status assessment using anthropometry

Data on children's growth status was obtained by measuring weight and height. Weight was measured with minimum clothing and no shoes to the nearest 100 g using a beam balance. Length was measured with an infantometer, following the standardized procedure. The correct age of the child was determined on the basis of a calendar of local events. Height and weight were recorded once every two months during the one-year study.

The weight and height measurements were converted into weight-for-age, height-for-age, and weight-for-height percentage of standard for each child using NCHS standards [4]. The children were grouped into different grades of nutrition status by both Gomez's [5] and Waterlow's classifications [6]. The cut-off points for the two classifications were as follows:

Gomez's

normal: >=90% of standard weight/age,

grade I malnutrition: 89%-75% of standard weight for age,

grade II malnutrition: 74%-60% of standard weight for age,

grade III malnutrition: <60% of standard weight for age;

Waterlow's

weight for height: >=80% = normal, <80% = wasted,

height for age: >=90% = normal, <90% = stunted. Children were assigned to a group of normal, grade I, grade II, and grade III malnutrition using Gomez's method, and normal, stunted, wasted, and both stunted and wasted using Waterlow's system.

 

Data analysis

To identify independent variables that had a significant role in influencing the three dependent variables (weight-for-age, height-for-age, and weight-for-height percentage of standard), stepwise multiple regression analysis was done using SPSS.


Results


Socio-economic status

The villages selected for the study were typical dryland areas. Tables 1-4 summarize the characteristics of the study children and families according to the four groups of factors examined--- child-related, maternal, paternal, and socio-economic. Over 95% of the men and women were illiterate and their main occupation was agricultural labour. A man's daily wage was Rs 15 and a woman's was Rs 10. An average of 75% of the income was spent on food. To meet other expenditures such as clothing, medical aid, and house construction and repair, loans were taken from larger farms at a high rate of interest.

Most families lived in one-room houses with poor ventilation, and cooked in the same room where they lived. None of them had toilet facilities. Household possessions were limited to cooking vessels, serving plates, and earthen pots for storing food grain and water. The people rarely moved out of their villages. The health facilities available to them were limited.

The distribution of children at the end of the study period according to age and sex is shown in table 5.

TABLE 1. Characteristics of study children

Variable Classification %
Age of child (mo) <24 35.1
24-35 30.8
36-47 24.2
48-56 9.9
Birth order of child 1-2 42.2
3-5 49.8
6-11 8.0
Age of starting weaning (mo) 6-12 59.7
13-18 20.0
19-24 14.2
25-30 3.3
31 -36 2.8
Diarrhoeal episodes last year none 54.4
1-2 28.9
3-5 14.8
6-10 1.9
Episodes of none 37.0
upper 1 -3 53.1
respiratory 4-6 9.0
infections 7- 10 0.9
Episodes of other infections none 39.8
1-2 51.7
3-4 6.6
5-6 1.9
Previous severe not ill 84.8
illness severely ill 15.2
Regularity of irregular 64.0
bathing regular 36.0
Calorie adequacy of diet <50% 47.4
50-80% 31.7
81-100% 16.7
> 100% 4.2
Immunization Not immunized 49.3
coverage (DPT 1-2 doses 34.1
and polio) 3 doses 16.6
Type of hospital visited govt/private 17.5
govt 22.8
local private doctor 59.7
Primary

care-taker

of child

5- to 7-year-old child 44.0
8- to 11-year-old child 1.9
>12-year-old girl 3.4
old woman in household 37.4
mother 13.3

Distribution of children at the end of one year according to Gomez's and Waterlow's classifications is presented in tables 6 and 7.

The set of factors that emerged in the final step after eliminating less significant factors in multiple regression analysis (backward elimination method) is shown in tables 8, 9, and 10.

TABLE 2. Characteristics of mothers in study families

Variable Classification %
Occupation agricultural labourer 82.5
  basketweaver 2.8
  housewife 14.7
Health status during generally sick 19.4
pregnancy normal 80.6
Health during study generally sick 13.3
period normal 86.7
Help received by no help 21.3
parents for deliveries only 43.1
  for deliveries, grain,  
  clothes, and  
  financial help 35.6
Help received for not much help 15.1
household only for child care 11.8
activities good amount of help  
  in water and  
  firewood collection 73.1
Nutritional aware- low 84.8
ness score medium 15.2

 

TABLE 3. Characteristics of fathers in study families

Variable Classification %
Education illiterate 87.7
  primary 5.7
  above primary 6.6
Health during study generally sick 10.4
period normal 89.6
Frequent quarrels with no 63.0
wife yes 37.0
Expenditure on luxuries does not spend 88.6
and amusements spends 11.4
Spends time with family no 8.1
after work yes 91.9
Loving and affectionate no 23.4
with child yes 76.6

Table 11 shows the factors that had significant influence on weight for age, height for age, and weight for height, grouped into four categories of child-related, maternal, paternal, and socio-economic factors. The level of significance for each independent variable is indicated.


Discussion


The results of the study confirm earlier reports that the prevalence of moderate and severe forms of malnutrition is high in children age 13 to 36 months (i.e., preschool age). Regression analysis indicated that numerous factors affect child nutrition with a maximum effect on weight for height and lead to wasting, stunting or underweight.

TABLE 4. Socio-economic characteristics of study families

Variable Classification %
Type of family nuclear 63.5
  joint 36.5
Caste Harijans (SC-ST) 46.9
  “Backward caste'' 53.1
Family size 3-6 64.5
  7-10 26.5
  11-14 9.0
Per capita income <750 20.9  
(Rs) 750-1,000 38.3
  1,001 -1,500 30.8
  > 1,500 10.0
Land availability nil 32.2
(acres) < 1 25.6
  1-2 31.3
  >2 10.9
Income from land nil 45.0
  <1,000 25.6
  1,000-2,000 24.7
  2,001-3,000 1.9
  > 3,000 2.8
Per capita monthly < 60 22.3
food expenditure 60-89 46.0
(Rs) 90-120 25.5
  > 120 6.2
Type of roofing thatch 51.7
  tile 46.4
  cement 1.9
Floor space/person < 30 56.8
(sq. ft) 30-49 29.9
  50-69 10.9
  70-90 2.4
Source of drinking tank water 9.0
water deep well 38.4
  bore well 52.6
Number of children in none 69.2
family attending 1 21.3
school/college 2 6.7
  3 0.9
  4 1.9

TABLE 5. Age and sex distribution of study children

Age (mo) Boys Girls Totals
13-24 32 42 74
25-36 38 32 70
37-48 26 27 53
Totals 96 101 197

Tables 8 to 11 show that the set of factors that influence weight for age are different from those that affect height for age and weight for height. This was expected, because each of these three anthropometric measures indicates a different type of nutrition status. Weight for age is an indicator of either current or past nutrition, whereas height for age is an indicator of past nutrition. Weight for height is a sensitive indicator of current nutrition status and of the degree of wasting. It is a useful tool specifically when ages are not known or not certain.

Of the four categories of factors studied (child-related, maternal, paternal, and socioeconomic), two child-related factors, number of diarrhoeal episodes and calorie adequacy of diet, showed a highly significant effect on a child's current as well as past nutrition status. These factors in turn are highly correlated with other socio-economic, maternal, and paternal factors.

In addition to a child's calorie adequacy and number of diarrhoeal episodes, regularity of bathing the child had a significant effect on both height for age and weight for age, as it is indirect evidence of maternal care and personal hygiene. The number of upper respiratory infections and other infections, and late weaning (24-48 mo), had a negative effect on growth status.

The child's age had a significant negative effect on weight for age and height for age, but a positive effect on weight for height of standard. Although immunization (DPT, polio) given to the child did not have a significant association with chronic nutrition, it emerged as a significant factor for current nutrition status. The mother as primary care-taker of the child compared with sibling care had a significant effect on both height for age and weight for age.

Among the maternal factors, good health during pregnancy had a positive significant effect on weight for age and weight for height, but not on height for age. The other two maternal factors that appeared to have an association with stunting and wasting of children, although not a highly significant one, were help received for household activities and help received from her parents in cash and kind.

Health of the father during the study period, and the time he spends with family members after work, also had a positive and significant effect on the child's weight for age but not on height for age. Father's expenditure on luxuries and amusements had a negative effect on weight for height. This could be because the more he spent on luxuries, the less time and money he will have for the family. Frequent quarrels between parents, and the father not being loving and affectionate toward the children, had a negative effect on height for age and weight for age, although not highly significant. These results strongly indicate the role of the father in influencing a child's nutrition.

 

TABLE 6. Nutrition status of children according to Gomez's classification

  Normal and Grade I Grade II Grade III  
Age (mo) No. % No. % No. % Totals
13-24 21 28.4 47 63.5 6 8.1 74
25-36 24 34.2 38 54.3 8 11.4 70
37-48 19 35.8 31 58.5 3 5.6 53
Totals 64 32.5 116 58.9 17 8.6 197

TABLE 7. Nutrition status of children according to Waterlow's classification

Age (mo) Normal Stunted Wasted Stunted and wasted Totals
No. % No. % No. % No. % No.
13-24 40 54.1 16 21.5 6 8.1 12 16.2 74
25-36 35 50.0 22 31.4 1 1.4 12 17.1 70
37-48 25 47.2 26 49.1 0 0.0 2 3.8 53
Totals 100 5.8 64 32.5 7 3.6 26 13.2 197

TABLE 8. Regression coefficient, SE, and t ratio in stepwise regression for dependent variable weight for age

Variable Coefficient SE t ratio Significance
Child-related factors  
number of diarrhoeal episodes —0.862 0.134 -6.429 a
calorie adequacy of diet 0.186 0.019 9.449 a
regularity of bathing 1.722 0.637 2.705 a
number of other infectious episodes —0.800 0.367 —2.181 b
age —0.109 0.046 —2.388 b
immunization coverage 0.734 0.367 2.003 b
primary caretaker 0.568 0.214 2.650 a
Maternal factors  
health status during pregnancy 3.899 1.115 3.497 a
Paternal factors        
health status during study period 2.839 1.398 2.031 b
spends time with family after work 3.368 1.573 2.141 b
not loving and affectionate with child —1.853 1.027 —1.803 c
frequent quarrels with wife —1.543 0.933 —1.654 c
Socio-economic factors  
income from land 0.0009 0.0004 2.670 a
number of children in family attending school/college 1.172 0.510 2.298 b
per capita food expenditure 0.033 0.018 1.868 c

R2 57.62%; adjusted R2 54.11 %; F 16.408.
a. Significant at 1 %.
b. Significant at 5%.
c. Significant at 10%.

TABLE 9. Regression coefficient, SE, and t ratio in stepwise regression for dependent variable height for age

Variable Coefficient Set t ratio Significance
Child-related factors  
number of diarrhoeal episodes - 0.304 0.081 - 3.770 a
age - 0.089 0.028 - 3.200 a
calorie adequacy of diet 0.075 0.114 6.664 a
regularity of bathing 0.865 0.371 2.329 b
primary caretaker 0.384 0.136 2.826 a
Maternal factors  
help received by mother's parents - 0.131 0.077 - 1.697 c
Paternal factors  
not loving and affectionate with child - 1.013 0.567 - 1.784 c
Socio-economic factors  
caste 1.548 0.563 2.747 a
number of children in family attending school/college 0.752 0.311 2.419 b
income from land 0.0005 0.0003 2.036 b
land available 0.510 0.294 1.734 c
per capita food expenditure 0.019 0.011 1.747 c

R2 40 75%; adjusted R2 36.54%; F 9.68.
a. Significant at 1 %.
b. Significant at 5%.
c. Significant at 10%.

TABLE 10. Regression coefficient, SE, and t ratio in stepwise regression for dependent variable weight for height

Variable Coefficient SB t ratio Significance
Child-related factors  
number of diarrhoeal episodes —0.606 0.137 -4.422 a
calorie adequacy of diet 0.050 0.019 2.716 a
age 0.105 0.043 2.430 b
number of upper respiratory infection episodes —0.671 0.262 —2.563 b
age of starting weaning —0.114 0.063 —1.806 c
Maternal factors  
health status during pregnancy 2.834 1.037 2.732 a
help received for household activities 0.464 0.253 1.833 c
Paternal factors expenditures on luxuries and amusements —2.731 1.257 —2.173 b
Socio-economic factors  
income from land 0.0007 0.0003 2.212 b
type of hospital visited 0.910 0.521 1.746 c
per capita income 0.001 0.001 1.671 c
number of children in family attending school/college 0.847 0.489 1.729 c

R2 41.3%; adjusted R2 37 47%; F 10.788.
a. Significant at 1%.
b. Significant at 5%.
c. Significant at 10%.

TABLE 11. Significant factors for the three indicators

Stepwise regression Weight for age Height for age Weight for height
Child-related factors  
number of diarrhoeal episodes a a a
calorie adequacy of diet a a a
primary caretaker a a NS
age b a b
regularity of bathing a b NS
immunization coverage b NS NS
number of upper respiratory infections NS NS b
number of other infections NS NS b
age of starting weaning food NS NS c
Maternal factors  
health status during pregnancy a NS a
help received for household activities NS NS c
help received by mother's parents NS c NS
Paternal factors  
health status during pregnancy b NS NS
spends time with family after work b NS NS
expenditures on luxuries and amusements NS NS b
not loving and affectionate with child c c NS
frequent quarrels with wife NS NS  
Socio-economic factors  
income from land a b b
land available NS c NS
number of children in family attending school/college b b c
caste NS a NS
per capita food expenditure c c NS
per capita income NS NS c
type of hospital visited NS NS c

a. Significant at 1 %.
b. Significant at 5%.
c. Significant at 10%.
NS = not isignificant

Among socio-economic factors, income from land can be used as a good indicator of a child's nutrition. It emerged as a single but significant factor that influenced weight for age, height for age, and weight for height. Families who receive higher incomes from land may have fewer constraints in feeding children. Per capita income and per capita food expenditure emerged as important factors, but were not significant. Caste was not a significant factor for current nutrition status, but was highly significant for past nutrition, indicating that stunting was more prevalent in "Backward caste" children than in Harijans.

From close observation and follow-up during the study period, differences in nutrition status of two preschool children brought up under similar conditions can be traced to two basic causes. First, children who were more vulnerable to infections during early infancy (<24 mo), and had higher morbidity, became malnourished. Second, some young children were unable to eat adequate food, perhaps owing to lack of appetite or because they did not care for the foods given. Such children were also highly prone to diarrhoeal diseases and consequently became malnourished. The effects of chronic calorie deficiency and infection appear to be the basic causes of the poor nutrition status of children below three years of age.

Controlling infection in early infancy and providing access to more easily digestible and palatable foods will promote adequate calorie intake. If preschool children at risk of malnutrition can be identified before they reach their second year of life, if effective primary health care is made available, and if an acceptable food is provided for these children, malnutrition can be averted.

As the determinants of nutrition status vary from culture to culture, similar studies conducted in different geographic regions, perhaps including other variables, can identify the critical family and environmental factors that contribute to the growth and development of children. Relevant intervention strategies can be based on these findings and incorporated into continuing developmental programmes aimed at improving these factors.


References


  1. Chaudry RH. Determinants of dietary intake and dietary adequacy for preschool children in Bangladesh. Food Nutr Bull 1984;6:24-33.
  2. Naarayana R. The socio-economic status rating scale. Ind Soc Sci 1973:206-19.
  3. Indian Council of Medical Research. Recommended dietary intakes of Indians. Delhi: ICMR, 1987.
  4. World Health Organization. Measuring change in nutritional status. Geneva: WHO, 1983.
  5. Gomez F. Galvan R. Frenk S et al. Mortality in second and third degree malnutrition. J Trop Pediatr 1956;2:7783.
  6. Waterlow JC, Buzina R. Kallen W et al. The presentation and use of height and weight data for comparing the nutritional status of groups of children under the age of 10 years. Bull WHO 1977;55:489-98.

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