maternal education & child care: two way anova 1source: babu and sanyal (2009)

1

Maternal Education & Child Care:Two way ANOVA

Source: Babu and Sanyal (2009)

Maternal Education & Child Care 2

Child Malnutrition

• Causes:Inadequate food, health, lack of sanitation facilities,

high fertility rates, ignorance about child-care practices and lack of access to health services.

Poor water, sanitation and hygiene account for 16 per cent of deaths of children under 5 globally WHO (2005).

Understanding the causes and context of malnutrition is important in devising strategies that generate better child health and nutritional outcomes.


Importance of Mother’s Education

• Caldwell (1979): Education of women played an important role in determining child survival even after controlling for other socioeconomic characteristics.

• Mother’s education can enhance child survival : Implementation of health knowledge, an increased capability to interact in the modern world and greater control over health choices for her children.


Issue

• Policy and program formulation: How various determinants of child malnutrition contribute

independently and interact with each other in determining the final outcomes.

Formal education of the mother may increase the care practices through knowledge.

Educated mothers are also time constrained due to their participation in labor markets and illiterate care-givers may have time but may have indigenous (or primitive) child survival practices.

Understanding the interaction of such related variables has been a policy and programmatic challenge since such interactions are usually cultural and context specific.


Method: Two-way ANOVA

• Verify impact of maternal education and child-care on children’s nutritional status as measured by height for age (HAZ) and weight for height (WHZ) Z-scores, using a two-way ANOVA approach.

• Advantage: Permits verification of “interaction effect”, simultaneous assessment of the effects of two (or more) independent variables on a single dependent variable and the possible combined effects of the independent variables on the dependent variable.

• Current Context: Effect of one factor (for example, maternal education) depends on the level of the second factor (child-care).


Conceptual Framework


Conceptual Framework• Better educated women:

Knowledgeable about health care If exposed to new information, assimilate this improved knowledge into

better care practices than women with lesser education; become aware of health services (such as health center facilities and availability of doctors) and generate additional nutritional knowledge (such as immunization of children against diseases, taking appropriate actions on incidence of infant diarrhea, feeding the child during sickness and breastfeeding during early childhood).

Such good care practices can, in turn, improve the nutritional status of children.

Better health care practices are especially relevant for less educated mothers, for mothers with more dependents and for children from households with limited resources, poor housing conditions and lack of access to hygiene and sanitation services.


Conceptual and measurement issues on child-care



• Child survival, nutrition and health = f(household food security, a healthy environment, available health services, care provided to women and children).

• Care = ‘the provision in the household and the community of time, attention and support to meet the physical, mental, and social needs of the growing child and other household members’.



Care (Engle et al., 1999):1. Care for pregnant and lactating women2. Breastfeeding and complementary feeding of

young children3. Food preparation and food storage behaviors4. Hygiene behaviors5. Care for children during illness



Resources for care:1. Education, knowledge, and beliefs2. Health and nutritional status of the care-giver3. Mental health, lack of stress, and self-confidence

of the care-giver4. Control of resources and intrahousehold allocation5. Workload and time constraints6. Social support from family members and the

community.


Measurement issues• Care = time spent (quantity of care) and the nature of the activities undertaken

(quality of care).• ‘time spent on care’ method: Time spent in specific activities with children (such as

bathing, feeding, etc.) along with other activities of the household. Most of the studies do not find any significant association between child-care time and nutritional status; may not be a good indicator of nutritional status.

• ‘quality of care’ approach: Determines how specific practices lead to better nutritional outcomes for children; classified into caregiver and psychosocial care practices – former affects child’s nutrient intake through psychomotor capabilities (such as use of finger foods, spoon handling ability, etc.) and appetite (Engle et al., 1999).

• Additionally, the care-giver’s ability to feed responsively may include encouraging the child to eat, offering additional foods, responding to poor appetite and using a positive style of interaction with the child.

• Some studies in developing countries have also found a strong association between specific feeding behaviors (such as location of feeding, organization of feeding event) with mothers’ educational status (Guldan et al., 1993). Psychosocial care, on the other hand, refers to the provision of affection and warmth, responsiveness to the child and the encouragement of autonomy and exploration (Engle et al., 1999). Culture plays a central role in psychosocial care.


Empirical Analysis

• Interface of maternal education, child care and child • The two-way ANOVA: Determines if there are overall

differences in weight for height Z-scores (ZWH) between different educational levels of the mother, between varying levels of child-care and whether there is an interaction effect of educational level and child-care on improving child nutritional status .

• The interaction effect can be thought of as saying that the effect of one factor (e.g. educational level) depends on the level of the second factor (e.g. child-care). For example, it may be the case that higher educated women provide better child-care than lower educated women.


Analysis

• Educational level effect:• H0: mean weight for height Z-scores do not differ by

educational levels of the mother.• H1: mean weight for height Z-scores differ by

educational levels of the mother.


Analysis

• Care effect:• H0 : mean weight for height Z-scores do not differ by

care levels by the mother.• H01: mean weight for height Z-scores differ by care

levels by the mother.


Analysis

• Interaction effect:• H0 : there is no interaction between educational

levels and care levels.• H1: there is an interaction between educational

levels and care levels.


Data Description

• Dependent variable: weight for height Z-scores, which is a measure of short-term child nutritional status.

• Define a transformation such that: ZWHNEW = 1 if ZWH ≥ -2 (normal Z scores) and = 0

if ZWH < -2 (low Z scores). Value of 1 indicates no wasting, while a value of 0

indicates wasting.


Data Description

• Education of the spouse (EDUCSPOUS): A categorical variable, the value of which ranges from 1 to

7. Measures the education level of the spouse (or mother) in

number of years. (In the case of female-headed households in the two-way ANOVA analysis, we separate out females who are heads of the household and thus are not the spouse of a male-headed household.) For example, the variable attains a value of 5 if the spouse completed secondary education.

Higher values indicate more number of years in schooling.


Data Description

• Child-care index (CARE): F(variables related to child-feeding practices (such as breastfeeding

and feeding the child during sickness) and preventive health seeking behavior (whether the child was immunized).

The index ranged on a continuous scale from -1 to +1, with -1 denoting poor child-care practices and +1 denoting good care practices.

For age groups where a particular practice (such as breastfeeding for children above 24 months of age and compulsory immunization to children below 9 months) is not likely to improve the growth of children, the component was assigned a value of 0 implying a neutral effect. The index was made age specific for each age group.


Table 7.1 Prevalence of stunting by mothers’ educational level

ZHANEW

EDUCSPOUS

Low Normal Total

No education 41 50 91

Adult literacy 1 6 7

Std 1–4 14 19 33

Std 5–8 24 29 53

Total 80 104 184 =n


Prevalence of stunting by mother’s education level

No marked differences in the prevalence of stunting between non-educated and educated women.

For example, for mothers with no education, the prevalence of stunting is 51.3 per cent relative to the presence of normal children of 48.1 per cent.

For some level of educational attainment of the mother (std 5–8) which in this sample is the highest educational attainment, the prevalence of stunting is 30 per cent relative to no prevalence (or normal children) of only 27.9 per cent. The p value is 0.457 and, as the significance level is greater than 0.1, the null hypothesis cannot be rejected at the 10 per cent level. Thus, we can conclude that there is no significant difference in prevalence of stunting between educated and non-educated mothers.


Table 7.2 Prevalence of wasting by mothers’ educational level

ZWHNEW

EDUCSPOUS

Low Normal Total

No education 15 84 99

78.90% 47.50%

Adult literacy 2 5 7

10.50% 2.80%

Std 1–4 0 35 35

0.00% 19.80%

Std 5–8 2 53 55

10.50% 29.90%

Total 19 177 196=n


Prevalence of wasting by mothers’ educational level

Significant differences in the prevalence of wasting between non-educated and educated women. For mothers with no education, the prevalence of wasting is almost 79 per cent compared to non-prevalence (47.5 per cent). Thus, it would appear that short-term nutritional status is significantly influenced by mothers’ educational level.

As educational level increases, there is much less prevalence of wasting. P value from the Pearson chi-square statistic is 0.006 and since it is less than 0.1, the null hypothesis that there is no difference between wasting among uneducated and educated mothers can be rejected.

Educational level matters for short-term nutritional status. In the next section, we investigate the role of mothers’ education and child-care on weight for height Z-scores using a two-way ANOVA approach.


Two-way ANOVA results

• Three different statistical tests:1. Main effect of educational level of the spouse.2. Main effect of care levels by terciles of care.3. Interaction effects between educational level of the

spouse and care levels.


Definition of main effect

• This is the effect of one independent variable on the dependent variable across the levels of the other independent variable.

• Issue: • Verify if there is a difference in the mean weight for height Z-

scores by the educational levels of the mother averaging over the child-care levels. In other words, ignoring the effect of child-care levels, do weight for height Z-scores differ between educated and non-educated mothers?

• Verify if there is a difference in weight for height Z-scores by child-care terciles ignoring the educational levels of the mother. One way to understand the main effect is to examine the marginal means.


Table 7.3 Effect of mothers’ education on ZWHNEW

EDUCSPOUS Mean

No education 0.844

Adult literacy training 0.75

Std 1–4 1

Std 5–8 0.961


Effect of mothers’ education on ZWHNEW

• Mean performance on weight for height Z-scores is greater for mothers with some educational level relative to mothers with no education.

• Do the marginal means differ?


Table 7.4 Effect of child-care on ZWHNEW

NCARE Mean

1 0.842

2 0.974

3 0.884


Effect of child-care on ZWHNEW

Mean weight for height Z-scores is highest for mothers in the medium care tercile (0.974) followed by the upper care tercile.

As care behavior improves (such as breastfeeding children below 2 years of age), nutritional status of children improves after controlling for educational level of the mother.

• Issue: If the marginal means among the various child-care terciles differ

• Ans: Calculate the sum of squares.


Variance partitioning for two-way ANOVA


Between Sum of Squares

• SSB = Squares of mothers’ educational level SS (EDUCSPOUS) + Sum of squares of terciles of child-care SS (NCARE) + Sum of squares of the interaction SS (interaction).


Sum of Square of the Interaction Term


Two-way ANOVA model


Two-way ANOVA model

• The left-hand side of equation (7.5) is the total sum of squares, while the right hand side consists of SSB and SSW.

• The first three terms on the right hand are the sum of squares of factor A, factor B and the interaction term, while the last expression denotes the sum of squares of the error term or the sum of squares within.

• After dividing the relevant expressions by the degrees of freedom, we obtain the mean square expressions.

• The corresponding F ratios are obtained by dividing the mean square of factor A, factor B and the interaction term (A*B) by the mean square error.


Table 7.5 ANOVA table for an a*b factorial experiment

Source SS df MS

Factor A SS(A) (a-1) MS(A) =SS(A)/(a 1)

Factor B SS(B) (b-1) MS(B) = SS(B)/(b 1)

Interaction AB SS(AB) (a-1)(b-1) MS(AB) = SS(AB)/(a -1)(b - 1)

Error SSW (N-ab) SSW/(N -ab)

Total (corrected) TSS (N-1)


ANOVA Results

• Main effect of mothers’ education on weight for height Z-score: F-value = 4.085 (p-value = 0.008)

• Reject null hypothesis that mean weight for height Z-scores do not differ by educational levels of the mother. Thus, education of the mother has a significant influence on weight for height Z-scores.

• Inference: There is a significant difference in the mean weight for height Z-scores between educated and non-educated mothers ignoring the impact of child-care.


ANOVA Results

• Main effect of child-care terciles on weight for height Z-score: F-value = 3.056 (p = 0.049)

• Reject the null hypothesis that the mean weight for height Z-scores do not differ by care levels of the mother and thus child-care levels have a significant impact on weight for height Z-scores after ignoring the impact of mothers’ education.


Table 7.6 Tests of between subject effects: dependent variable ZWHNEW

Source Type III sum of squares df Mean square F P value

SSB 2.187 10 0.218 2.691 0.003

Intercept 64.330 1 64.330 798.914 0.000

EDUCSPOUS 0.987 3 0.329 4.085 0.008

NCARE 0.492 2 0.246 3.056 0.049

EDUCSPOUS*NCARE 0.708 6 0.118 1.468 0.202

SSW 14.971 185 0.081

TSS 17.158 195

R squared = 0.132 (adjusted R squared = 0.085).


Interaction effect and post-hoc tests

• Issue: There are more than two means; which means (if any) are significantly different.

• Four educational levels of the mother and three child-care levels. • Table 7.6: Overall interaction effect (EDUCSPOUS*NCARE) is not

significant.• Still there may be significant differences among the means of

mothers’ educational levels and child-care, i.e., there may be differences among combinations of education levels and child-care terciles.

• Post-hoc tests are used when the researcher is exploring differences among group means, otherwise the likelihood of type 1 errors increases.

• Illustration with reference to educational level of the mother and childcare terciles.


Results• Mothers with more education relative to mothers with no education

practice greater child-care. • The simple post-hoc analysis compares a given pair of means. If they

are significantly different (p < 0.05), different letters are placed next to these means to indicate that they are significantly different.

• For the same level of child-care, higher education among mothers (elementary schooling) improves short-term nutritional status as measured by weight for height Z-scores.

• For a given level of education (no education or some elementary schooling), mothers in the second child-care tercile perform better than ones in the highest care tercile = Impact of positive child-care practices improves short-term nutritional status for households in the lower socioeconomic terciles compared to the upper socioeconomic terciles.


Table 7.7 Multiple comparison test

NCARE

EDUCSPOUS

No education Std 1–4

2 0.929 a 1.00 b

3 0.735 c 1.00 d

maternal education & child care: two way anova 1source: babu and sanyal (2009)

Documents