Under-nutrition of 2–5 years old children and associated factor among employed and unemployed women: Comparative cross-sectional study

Abstract

Background: Many child deaths result from undernutrition globally. More than half of total childhood deaths are attributed to mild and moderate undernutrition in low-income countries. This study intended to assess the undernutrition of pre-school children (2–5 years) and associated factors among employed and unemployed women in three town administrations in the Wolaita zone. Methods: Community-based comparative cross-sectional study design was conducted among randomly selected 317 employed and 317 unemployed women having pre-school children in Wolaita zone town from 22 May to 27 June 2019. Data collection was carried out using structured, pre-tested and interviewer-administered questionnaires. Data were entered into EPI-data version 3.5.2 and exported to SPSS version 21.0 for further analysis. Descriptive statistics such as frequencies, proportions, and cross-tabulation were used to present the data. Also, bivariate logistic regression was done to assess the association between independent and dependent variables. Model fitness was checked by doing the Hosmer and Lemeshow test. Variables that shown association (p-value ≤ 0.25) in the bivariate analysis were included in the final multivariable logistic regression model. Odds ratios for logistic regression along with a 95% confidence interval were estimated. A table having crude and adjusted Odds ratio, as well as 95% confidence intervals, was constructed along with the corresponding p-value. A P-value of less than 0.05 was declared as the level of statistical significance. Result: The magnitude of stunting among children of employed and unemployed women was found to be 18.5% and 26.5%, respectively. Concerning the level of wasting among the study participants, 5(1.7%) and 8(2.6%) of children of the employed and unemployed mother were classified as wasting based on the result of the anthropometric measurement. Similarly, about 4.6% and 8.3% of pre-school children of employed and unemployed mothers were underweight, respectively. In general, the magnitude of stunting, wasting, and underweight is higher among pre-school of an unemployed mother when compared with employed mother. Conclusion and recommendation: The magnitude of stunting and wasting is lower among children of employed mothers compared with unemployed women. Educating and empowering women is one of the areas that needs great intervention by concerned stakeholders for better maternal and child nutritional status.

Keywords:

• employed women
• pre-school children
• stunting
• wasting
• Southern Ethiopia

PUBLIC INTEREST STATEMENT

Undernutrition is global problem that mostly affects developing countries. More than half of total childhood deaths are attributed to mild and moderate undernutrition in low-income countries. In the world today, one child in four is stunted due to malnutrition, and in developing countries, this figure is as high as one in three and specifically in Africa two out of five children will suffered with malnutrition.

However, these studies used only a cross-sectional design and no comparison. Therefore, assessing the role of employment status of women/caregivers on nutritional status of children is crucial for designing intervention to balance the importance of women empowerment and its effect on child nutrition. The magnitude of stunting and wasting is lower in Wolaita town among children of employed mothers compared with unemployed women. Educating and empowering women is one of the areas that needs great intervention by concerned stakeholders for better maternal and child nutritional status.

Competing interests

The authors have declared that no competing interests exist.

1. Background

Malnutrition refers to deficiencies of micronutrients, undernutrition, overweight, and obesity (Black et al., 2013; Shetty, 2003).

Malnutrition is an underlying cause of the death of 2.6 million children each year, and one-third of the global total of children’s (7.6 million children) deaths each year before their fifth birthday through weakening the body’s resistance to illness (Demissie & Worku, 2013). Malnutrition is a silent killer that is under-reported, under-addressed, and, as a result, under prioritized. Every hour and minute of every day, 300 and 5 children die because of malnutrition, respectively (Gudina & Zinabu, 2015). In the world today, one child in four is stunted due to malnutrition, and in developing countries, this figure is as high as one in three, and specifically, in Africa, two out of five children suffered from malnutrition (Vir et al., 2008).

Malnutrition affects people’s physical, mental growth, body immune system, health, and wellbeing. It also increases the risk of noninfectious and transmissible diseases, reducing productivity and other negative social and economic consequences on individuals, households, societies, and nations (Nation, F. A. A. C. O. O. T. U, 2014).

Most of the time inadequate dietary intake and infectious diseases which are highly prevalent in the least developed countries are the cause for malnutrition (Olack et al., 2011). The problem is highly prevalent among children who are synonymous with growth failure. Malnourished children are shorter and lighter in weight than they should be for their age when compared with well-nourished children (Bellamy, 2000).

Undernutrition among children of age less than 5-year old mainly manifests as low height-for-age (stunting) and is a factor in impairment of brain development and growth rate (Ergin et al., 2007). In children, it refers to those that fall below −2 standard deviations from the median height-for-age based on the World Health Organization (WHO) reference standards. On the other hand, underweight is low weight-for-age below −2 standard deviations from the median weight-for-age. Wasting is described as low weight-for-height, a measure below −2 standard deviations from the median weight-for-height standard (de Onis & Session, 2006).

Pre-school children need more attention because it is a rapidly growing period in life. As a result, they are highly vulnerable to malnutrition (Glewwe & King, 2001). Well-nourished children grow well and can survive their future life effectively and become a healthy adult (Hayashi et al., 2017). Under-nutrition in early childhood could result in poor cognitive and behavioral development, as well as school achievement (Mcdonald et al., 2014). So, nutrition plays a vital role as one of the most important environmental factors influencing cognitive performance as it provides the building blocks for the neural formation and brain development. Hence, inadequate nutrient intakes during the developmental stages of the children may adversely affect their cognition (Abdel-Rahman et al., 2017).

The income of employed women is more advanced than unemployed women. This may help women to have good nutrition and health for themselves and their children. In effect women without control over their income and decision-making authority within the household economic power can take action on their babies’ nutritional status (Desai & Johnson, 2005). In another direction, employment status has a negative impact on nutritional status of pre-school children, because it decreases mothers’ time spent for their children’s caring and feeding (Behrman & Hoddinott, 2001).

Women play multiple roles in the family that affect the health and well-being of all family members. There are two contradicting ideas; one indicated that women’s employment status can improve household income and nutritional status of the children and the second idea indicated that women’s employment status affects the time that women give care and effective feeding of their children (Rashad & Sharaf, 2019). However, these ideas were not proofed by conducting comparative study in Wolaita zone. In almost all societies around the world, they are assigned by custom to be the primary caregivers to infants and children. Activities carried out by women such as breastfeeding, preparing food, collecting water and fuel, and seeking preventative and curative medical care is crucial for Childs healthy development. In this modern era, most mothers have become part of the labor force compared to the previous time. Maternal employment influences child feeding practices thus it reflects the child’s nutritional status (Nair et al., 2014). The study indicated that fathers do not increase the time they spend with children to compensate for the reduction in the mothers’ time (Sharaf, 2017).

Yet malnutrition among pre-school is widely prevalent in Africa. As per available data about half of the children in this age group suffer from a different grade of malnutrition (Gilmore et al.). Malnutrition in turn weakens the immune system of the child, thereby contributes to more than 50% of deaths associated with infectious diseases among this age group. Many child deaths result from undernutrition, estimated to be associated with over half of total childhood deaths in developing countries, can be attributed to just mild and moderate undernutrition, varying from 45% for deaths due to measles to 61% for deaths due to diarrhea (Rice et al., 2000). Most studies on child nutritional status have focused on the prevalence of undernutrition among under-five children and socioeconomic, demographic, and cultural factors associated with child undernutrition (Reed et al., 1996).

Malnutrition remains among the most devastating problems currently being faced by the majority of the world’s poor. As of many developing countries, malnutrition is one of the most important health and welfare problems among infants and young children in Ethiopia studies showed that is a result of both inadequate food intake and illness. Undernutrition is one of the leading causes of morbidity and mortality in children under 5 years of age in Ethiopia (Egata et al., 2013; Fikadu et al., 2014; Yisak et al., 2015). The country has the second-highest rate of malnutrition in Sub-Saharan Africa. The common types of undernutrition among children are wasting, stunting, and underweight (Smith & Haddad, 2000). Inadequate food intake is a consequence of insufficient food available at the household level, or improper feeding practices, or both (Hanna Polak, 2006).

As indicated in Figure 1, nationally child Undernutrition is the most important problem in Ethiopia. About 29% were underweight, 44% were stunted and 10% of children were wasted. A study conducted in Southern Ethiopia indicated that 26% are underweight with 7.8% severe underweight, 9.7% of the children are wasted (2.8% severe wasting) and 41.4% of the children are stunted with 18% sever stunting (Agency & Macro, 2012). Thus, assessing the effect of maternal employment and other context-based factors on pre-school children undernutrition plays a vital role for the development of a nutritional intervention for alleviating such public health problem which greatly affects physical and mental development of children that can reduce their productivity in the lifetime (Jayakody1, 2014). However, these studies used only a cross-sectional design and no comparison. Therefore, there is research conducted on the comparative study of pre-school children undernutrition among employed and unemployed women in the study area and this study fills the gap of adequate information of nutritional status difference between the two groups. The objective of this study is to assess the undernutrition of pre-school children and associated factors among employed and unemployed women in Wolaita zone towns administrative.

The research hypothesis that was tested in this study: The magnitude of undernutrition is deferent between pre-school children of employed and unemployed mothers in Wolaita zone towns administrative.

Figure 1. Conceptual framework for assessment of undernutrition and associated factors of pres-chool children.

2. Methods and materials

Community-based comparative cross-sectional study was conducted at Wolaita zone towns administrative in Wolaita zone, southern nation nationalities, and people’s regional state (SNNPRS) from 22 May to 27 June 2019. The capital city of the Wolaita zone is Wolaita Soddo and which is located at 380 KM from Addis Ababa. There are three towns administrations in the Wolaita zone, namely, Areka, Boditi, and Soddo. The zone has a total population of 2,020,384 of which 470,749 are women in the reproductive age group and 315,382 are under-five children. Concerning the health system of the zone, there is one referral hospital, one private general hospital, 68 governmental health centers, and 145 private clinics (Wolaita zone health office, 2019). The common activities in the zone are farming focusing on the production of various cash crop and root-based food items, and rearing of the animal. Study area is shown on figure 2 below.

Figure 2. Map of study setting, taken from Wolaita zone health office Wolaita zone, Ethiopia 2019.

3. Source and study population

All women having 2–5 years old children in the towns of Wolaita zone were taken as source population and all randomly selected women having 2–5 years old children in the towns.

3.1. Inclusion criteria

Women having 2–5 years of children who have lived in the study area at least for 6 months and above, and who have the willingness to participate in the study.

3.2. Exclusion criteria

Women who were unable to respond to the interview due to severe illness or with a mental disability who were not correctly responding for interviews and children with known illness or mental disability were excluded from the study.

3.3. Sample size determination

The sample size required for the first specific objective was determined by using Epi Info statistical software version 7 using two population proportion formulas. The following assumptions were taken into consideration: Confidence level = 95%, Power (1-ß), Design effect = 1.5, Ratio = 1:1, the proportion of stunting among under-five children of unemployed mothers of 39.5% and that of children of employed women 54.3% taken from the study done at Adama town (23). Considering a 10% possible non-response rate, 317 unemployed and 317 employed mothers were included. For estimating the possible number of cases (number of stunted children of employed and unemployed women) who could be included in the research while taking the sample size calculated by using double population formula, multiplying the sample size by proportion taken for calculation of sample size for each group is required; i.e. 317 × 0.543 = 172 and 317 × 0.395 = 125stunted children could be included in the study from employed mothers and unemployed women, respectively, if the sample size calculated by the first specific objective is taken into consideration.

The sample size for the second objective also calculated by using Epi Info version 7 using case–control formula. After searching variables that were found to be significantly associated with stunting among under-five children of employed and unemployed women in a similar study, the educational status of the mother was taken as exposure factor for unemployed mother and marital status was taken for employed mothers for sample size calculation. The process is described as follows:

From the above table, we can see that the number of cases obtained by using education status and marital status for unemployed and employed women, respectively, is smaller than the possible number of cases which will be included in the sample size calculated using two population proportion formula (125 vs 63 for unemployed women) and (172 vs 96 for employed women).

Accordingly, the sample size calculated by using the first specific objective is sufficient to assess factors associated with under-nutrition among pre-school children and taken as a final sample for the study.

3.4. Sampling procedure

As indicated by Figure 3, from a total of 39 kebeles found in three Wolaita zone administrative towns, 13 (33%) of kebeles were selected using a simple random sampling technique. The total number of women having pre-school children in the selected kebeles was identified through conducting a census and sampling frame was prepared for employed and unemployed women having pre-school children separately. The calculated sample size was allocated proportionally to each kebeles based on the number of employed and unemployed women having pre-school children. A simple random sampling technique was used to select study participants. When there are more than one women having pre-school children in a single household, one woman was selected randomly. Similarly, when there are more than one pre-school children in a single household one pre-school child was selected randomly.

Figure 3. Schematic presentation of the sampling procedure for assessment of pre-school children nutritional status and associated factors among employed and unemployed women in Wolaita towns, 2019.

3.5. Dependent variable

Under Nutrition (wasting, stunting and underweight).

3.6. Independent variables

Socio-demographic and economic characteristics, maternal and child health service utilization characteristics, and child characteristics.

3.7. Data collection methods

Socio-demographic variables and other factors were collected by using an interview administered structured questionnaire which was developed and translated to local language through the literature of similar studies. Weight and height measurements were taken from the child immediately following the interview of the mother of the child. Height measurements were conducted in standing position using a portable stadiometer with a precision of 0.1 cm. Measurements of weight and height were taken three times and the average was recorded both interview and anthropometric data were collected by three BSc nurses after taking training on data collection for 2 days.

4. Data analysis

First, the data were cleaned, coded, checked for completeness, and consistency for data entry. Then, data were entered into the computer using EPI-data version 3.1 and exported to SPSS version 21.0 for further analysis. Anthropometric measurements were converted into Height-for-Age Z scores (HAZ) and Weight-for-Height Z score (WHZ) using WHO Anthro (version 1.0.4). Children whose WHZ less than −2SD of the WHO standard was classified as wasted and height for age of Z <-2 SD was considered as stunting. Descriptive statistics such as frequencies, proportions, and cross-tabulation was used to present the data. Also, bivariate logistic regression was done to assess the association between independent and dependent variables. Model fitness was checked by doing a Hosmer and Lemeshow test. Variables that were show association (p-value ≤ 0.25) in the bivariate analysis were included in the final multivariable logistic regression model. Odds ratios for logistic regression along with 95% confidence interval was estimated. A table having crude and adjusted Odds ratio, as well as 95% confidence intervals, was constructed along with the corresponding p-value. A value of less than 0.05 was declared as a level of statistical significance. The research hypothesis that says the magnitude of undernutrition is deferent between pre-school children of employed and unemployed mothers in Wolaita zone towns administrative was tested by two-tailed test analysis.

4.1. Data quality control

The English version questionnaire was translated into Amharic language and back-translated to English to check its consistency by a respective language expert. The data collectors, as well as supervisor, were trained for 2 days on the issue related to the objective of the study, data collection procedure, and ethical principles. Pre-test of the questionnaire was done at kebeles which is not included in the final study and necessary correction was made before the actual data collection. Furthermore, supervision was done by the investigator. The completeness of the questionnaire was checked daily by supervisors and investigators.

4.2. Expected outcome

This study was conducted to determine pre-school children undernutrition among employed and unemployed women and associated factors in Wolaita zone which can be used to design context-based nutritional intervention programs to reduce malnutrition which is the main cause for poor mental and physical development and contribute for the high mortality of children.

4.3. Ethical consideration

Ethical approval was obtained from the ethical review board of the school of public health of Wolaita Sodo University. A letter was also obtained from the Wolaita Zone health office and communicated to each selected woreda and kebeles. Informed verbal and written consent was secured from Women for their participation after the purpose of the study was clearly explained. The right to refuse or discontinue at any point of the data collection process was respected. The information collected from the participants was used for research purposes only and kept confidential as the collected information was stored in a file without a personal identifier of the study participant. For a child found to be undernourished, linking to health institutions and other organizations working on nutritional intervention was done accordingly. Nutrition counseling was given for the mother whose child undernourished.

5. Results

5.1. Socio-demographic characteristics of study participants

In the current study, a total of 604 pre-school children of employed and unemployed women were participated with a response rate of 95.3%. More than half of the respondents (58.7%) were in the age group of 25–34 years. About two-thirds of the respondents (39.40%) were protestant by religion and 46.69% of respondents were attended Primary and secondary school. More than one-third of study participants (39.4%) have a family size greater than five members (Table 1).

Table 1. Sample size determination for the study, 2019

Factors (unemployed mother)	Assumptions	Sample size
Education of mother (9–12 grade)	95% confidence interval level Power = 80% Case–control ratio = 1:1 OR = 3 The proportion of unemployed mother who doesn’t have stunted children and attended 9–12 grades (28.2%)	63 Cases and 63 controls
Factors (employed mother)	Assumptions	Sample size
Marital status(Never married)	95% confidence interval level Power = 80 Case–control ratio = 1:1 OR = 5.5 The proportion of employed mother who doesn’t have stunted children and never married (3.5%)	96Cases and 96 controls

As to maternal and child health service utilization characteristics of study participants, 81.6% of the respondents attended antenatal care for the last pregnancy. The majority (88.7%) of pre-school children have taken fully immunization and about 84.7% of the employed and unemployed women ever got nutritional information (Table 2.)

Table 2. Socio-demographic characteristics of study participants in three town administrations of Wolaita zone, 2019

Variables	Employed		Unemployed		Total
Age of mother 15–24 years 25–34 years 35 and above years	Frequency	%	Frequency	%	Frequency	%
	44	14.5	98	32.5	142	23.51
	217	71.9	138	45.7	355	58.77
	41	13.6	66	21.8	107	17.72
Religion Protestant Orthodox Muslim Others
	219	72.5	202	66.9	421	69.70
	71	23.5	70	23.2	141	23.34
	11	3.6	27	8.9	38	6.29
	1	0.4	3	1	4	0.66
Marital Status Mother Unmarried Married Divorced Wildwood
	2	0.7	1	0.3	3	0.50
	284	94.0	291	96	575	95.20
	12	4	6	2	18	2.98
	4	1.3	4	1.3	8	1.32
Education Status of Mother Read and write Primary and secondary school College and above	6	2	84	27.8	90	14.90
	107	35.4	175	57.9	282	46.69
	189	62.6	43	14.3	232	38.41
Sex of the child Male Female
	181	59.9	166	55	347	57.45
	121	40.1	136	45	257	42.55
Family size ≤Five
	176	58.3	190	62.9	366	60.60
>Five	126	41.7	112	37.1	238	39.40
Variable	Employed		Unemployed		Total
	Frequency	%	Frequency	%	Frequency	%
Number under 5 children
Two and less Greater than two	208	68.9	227	75.2	435	72.02
	94	31.1	75	24.8	169	27.98
Monthly Income <2500 Eth.Birr 2500–5000 Eth.Birr >5000 Eth.Birr
	67	22.2	181	59.9	248	41.06
	57	18.9	77	25.5	134	22.19
	178	58.9	44	14.6	222	36.75
Age of the child 16–32 months Greater than 32 months
	86	28.5	93	30.8	179	29.64
	216	71.5	209	69.2	425	70.36

Source data: field data

Table 2. Maternal and child health service utilization characteristics of study participants in three town administrations of Wolaita zone, 2019

Variables	Employed		Unemployed		Total
	Frequency	%	Frequency	%	Frequency	%
ANC follow-up for the last pregnancy
Yes	246	81.5	247	81.8	493	81.62
No	56	18.5	55	18.2	111	18.38
PNC follow-up for the last pregnancy
Yes	148	49.0	149	49.3	297	49.17
No	154	51.0	153	50.7	307	50.83
Child immunization status
Fully immunized	238	78.8	298	98.7	536	88.74
Not fully immunized	64	21.2	4	1.3	68	11.26
Got nutrition information
Yes	268	88.7	244	80.8	512	84.77
No	34	11.3	58	19.2	92	15.23
Place of delivery
Home	7	2.3	14	4.6	21	3.48
Health institution	295	97.7	288	95.4	583	96.52
Exclusive breastfeeding
Yes	295	97.7	299	99.0	594	98.34
No	7	2.3	3	1.0	10	1.66
Started complementary feeding on time
Yes	286	94.7	235	77.8	521	86.26
No	16	5.3	67	22.2	83	13.74
Continuation of breastfeeding
Yes	271	89.7	275	91.1	546	90.40
No	31	10.3	27	8.9	58	9.60
Dietary diversity score
Greater than four food group	145	48.0	141	46.7	286	47.35
Variable	Employed		Unemployed		Total
	Frequency	%	Frequency	%	Frequency	%
Less than four food group	157	52.0	161	53.3	318	52.65
Knowledge on nutrition
Knowledgeable	295	97.7	279	92.4	574	95.03
Not knowledgeable	7	2.3	23	7.6	30	4.97

Source data: field survey

As shown figure 4, 5 & 6 the current study assessed households’ food security status using household food insecurity access tools. Accordingly, about 58.6% and 79.8% of employed and unemployed women are food-secured status, respectively (Figure 4).

Figure 4. Magnitude of stunting among pre-school children of employed (left side) and unemployed (right side) mothers in three towns administrations of Wolaita zone, 2019.

Figure 5. Magnitude of wasting among pre-school children of employed and unemployed mothers in three towns administrations of Wolaita zone, 2019.

Figure 6. Prevalence of underweight among pre-school children of employed (left side) and Unemployed mother (right side) in three town administrations of Wolaita zone, 2019.

5.2. Factors associated with stunting among pre-school children of employed and unemployed women

This study is intended to assess the level of undernutrition of pre-school children and associated factors among employed and unemployed women in three town administrations in the Wolaita zone. Accordingly, on bivariate logistic regression analysis, ANC follow-up for the last pregnancy, age of women, education status of the mother, Family size, number of under-five children, having home servant, sex of the child and immunization status were incorporated in multiple binary logistic regression analysis based on their p-value (less than 0.25). Based on the regression result of the final model, maternal education status (AOR = 0.35, 95% CI = (0.15, 0.789)) and having home servant (AOR = 2.58, 95% CI = (1.35, 4.91)) were found to have a statistical association with stunting among pre-school children of employed women (Table 3).

Table 3. Factors associated with stunting among pre-school children of employed women in three town administrations of Wolaita zone, 2019

Variables ANC follow-up	Stunting		COR (95%CI)	AOR(95%CI)	P-value
	Yes	No
Yes No	46 10	200 46	0.95 (0.44,2.01) 1	1.1(0.50,2.43) 1	0.8340
Age of mother 18–24 years 25–31 years 32–38 years ≥39 years	10 31 12 3	34 157 50 5	2.04(0.414,10.06) 3.04(0.690,13.38) 2.50(0.53,11.94) 1	2.03(0.32,12.85) 2.86(0.54,15.33) 2.35(0.426,12.98) 1	0.552
Mother education Read and write Primary school Secondary school College and above	3 13 13 27	3 21 60 162	1 0.67(0.032,0.869) 0.27(0.121,0.601) 0.77(0.373,1.588)	1 0.24(0.044,1.273) 0.35(0.150,0.789) 0.91(0.43,1.910)	0.035 0.093 0.012 0.799
No of under-five children ≤2 children >2 children	41 15	167 79	0.77(0.404,1.480) 1	0.78(0.399,1.540)	0.480
Have home servant Yes No	17 39	140 106	1 3.03(1.625,5.649)	1 2.58(1.350,4.910)	0.004
Family size ≤5 >5	34 22	142 104	0.88(0.488,1.598) 1	0.84(0.425,1.676) 1	0.6280
Sex of the child Male Female	32 24	249 97	1.15(0.640,2.074) 1	1.13(0.601,.137) 1	0.6980
Variables ANC follow-up	Stunting		Crude OR (95%CI)	AOR(95%CI)	P-value
	Yes	No
Got nutrition information Yes No	37 19	170 76	1 1.15(0.621,2.126)	1 1.17(0.607,2.267)	0.6340
Immunization status Fully immunized Not fully immunized	40 16	198 48	1 1.65(0.853,3.192)	1 1.55(0.776,3.077)	0.2150

AOR = adjusted odds ratio, COR = crud odds ratio, CI = confidence interval.

As indicated on Table 4 & 5, among unemployed women, ANC follow-up and post-natal service utilization for the last pregnancy, age of women, education status of the mother, family size, number of under-five children, sex of the child and immunization status were exported to multiple binary logistic regression analysis models since their p-value in bivariate binary logistic regression was less than 0.25. Accordingly, sex of the child (AOR = 1.82, 95% CI = (1.05, 3.15)), age of the women (AOR = 0.37, 95% CI = (0.17, 0. 79)), and having nutritional information (P-value = 0.048) were left in the final model as having significant association with stunting among pre-school children of unemployed women (Table 4 & 5.)

Table 4. Factors associated with stunting among pre-school children of unemployed women in three town administrations of Wolaita zone, 2019

Variables	Stunting		Crude OR (95%CI)	AOR(95%CI)	P-value
	Yes	No
Sex of the child Male Female	38 42	128 94	1 0.66 (0.398,1.11)	1 1.82(1.053,3.156)	0.0320*
Age of mother 15–24 years 25–34 years ≥35 years	25 43 12	73 95 54	0.65(0.30,1.406) 0.49(0.239,1.010) 1	0.58(0.255,1.313) 0.37(0.169,0.799) 1	0.1900 0.012*
Mother education Read and write Primary and secondary school College and above	25 47 8	59 128 35	1 0.53(0.219,1.326) 0.62(0.269,1.439)	1 0.60(0.228,1.575) 0.64(0.266,1.554)	0.2990 0.3260
No of under-five children ≤2 children >2 children	59 21	168 54	1 1.11(0.617,1.987)	1 1.19(0.633,2.224)	0.5940
PN service for last delivery Yes No	39 41	110 112	1 1.033(0.619,1.722)	1 1.06(0.597,1.871)	0.8500
Family size ≤5 >5	48 32	142 80	1 1.18(0.700,1.999)	1.45(0.808,2.589)	0.2140
Got nutrition information Yes No	60 20	184 38	1 1.61(0.873,2.985)	1 1.99(1.005,3.934)	0.048*
Immunization status Fully immunized Not fully immunized	79 1	219 3	1 0.92(0.095,9.014)	1 1.40(0.114,17.332)	0.7920

AOR = adjusted odds ratio, COR = crud odds ratio, CI = confidence interval.

Table 5. Factors associated with underweight among pre-school children of employed women in three town administrations of Wolaita zone, 2019

Variables	Underweight		Crude OR (95%CI)	AOR(95%CI)	P-value
	Yes	No
Immunization status Fu lly immunized Not fully immunized	11 3	227 61	1 1.02(0.28,3,75)	1 0.40(0.08,2.11)	.2820
Age of mother 15–24 years 25–34 years ≥35 years	2 8 4	42 209 37	1 2.27(0.39,13.12) 2.82(0.81,9.86)	1 6.89(0.74,64.36) 5.77(1.20,27.89)	0.0900 0.0290
Daitry diversity score ≥four food group Less than four food group	4 10	141 147	1 2.39(0.74,7.82)	1 3.32(0.85,12.96)	0.085
Sex of the child Male Female	5 9	176 112	1 2.83(0.92,8.65)	1 4.04(1.09,14.99)	0.037
Monthly Income <2500 Eth.Birr 2500–5000 Eth.Birr >5000 Eth.Birr	10 2 2	57 55 176	1 0.07(0.014,0.30) 0.31(0.04,2.27)	1 0.05(0.009,0.286) 0.32(0.04,2.64)	0.002 0.001 0.2920
Age of the child 16–32 months Greater than 32 months	6 8	80 208	1 0.51(.17,1.52)	1 0.21(0.05,0.81)	0.024
Postnatal service utilization Yes No	3 11	145 143	1 3.72(1.o2,13.61)	1 3.84(0.90,16.41)	0.069
No of under-five children ≤2 children >2 children	10 4	198 90	1 0.88(0.27,2.88)	1 1.59(0.37,6.81)	0.5290
Family size ≤5 >5	7 7	169 119	1.42(0.49,4.16) 1	0.75(0.20,2.75) 1	0.6630

AOR = adjusted odds ratio, COR = crud odds ratio, CI = confidence interval.

Table 6. Factors associated with underweight among pre-school children of unemployed women in three town administrations of Wolaita zone, 2019

Variables	Underweight		Crude OR (95%CI)	AOR(95%CI)	P-value
	Yes	No
Place of delivery of last-child Home Hospital/health institution	9 16	56 221	1 0.45(0.19,1.07)	1 0.41(0.16,1.06)	0.067
Education status of Mother Read and write Primary and secondary school College and above	5 15 5	79 160 38	2.08(0.57,7.62) 1.40(0.48,4.10) 1	3.18(0.77,13.10) 1.33(0.42,4.22) 1	0.1090 0.6350
ANC follow-up for last preg. Yes No	19 6	228 49	1 1.47(0.56,3.87)	1 0.821(0.33,2.02)	0.6690
Knowledge on nutrition Knowledgeable Not Knowledgeable	21 4	258 19	1 2.59(0.81,8.30)	1 3.84(1.07,13.80)	0.0400
Dietary diversity score Four and above food group Less than four group	11 14	130 147	1.13(0.50,2.57) 1	1.60(0.48,5.37) 1	0.4490
Having own home Yes No	4 21	99 178	1 2.92(0.98,8.75)	1 3.60(1.13,11.51)	0.0310
Family size ≤5 >5	13 12	177 100	1 1.63(0.72,3.72)	1 2.51(1.00,6.29)	0.0490

AOR = adjusted odds ratio, COR = crud odds ratio, CI = confidence interval.

5.3. Factors associated with underweight among pre-school children of employed and unemployed women

We also tried to assess factors associated with underweight among pre-school children of employed and unemployed women in the study area. From explanatory variables selected for multivariate binary logistic regression model among employed women, namely, immunization status, age of the mother, dietary diversity score, sex of the child, number of under-five children in the household, postnatal service utilization, family monthly income and age of the child, only age of the mother (AOR = 5.77, 95% CI = (1.20, 27.89)), family monthly income (AOR = 0.05, 95% CI = (0.009, 0.286)), sex of the child (P-Value = 0.037), and age of the child (AOR = 0.21, 95% CI = (0.05, 0.81)) were found to have a statistical association with pre-school children underweight of employed women. On the other hand, maternal knowledge on nutrition (p-value = 0.0310), family size (p-value = 0.0490), and having own home (p-value = 0.0310) were explanatory variables revealed to have a statistically significant association with underweight of pre-school children of unemployed women.

6. Discussion

6.1. Magnitude of undernutrition in pre-school children of employed and unemployed women

This study aimed to determine the level of stunting, wasting, underweight, and factors associated among children of employed and unemployed in three town administrations in Wolaita zone. The magnitude of stunting among children of employed and unemployed women was found to be 18.5% and 26.5%, respectively. The find is less when compared with the result of the study done among children of employed and unemployed women at Adama town which revealed a prevalence of stunting of 54.3% and 39.5%, respectively (23). It is also lower than the result of a cross-sectional study conducted among pre-school children in Hawassa, Southern Ethiopia revealed that overall prevalence of stunting of 53.1% (Tsedeke Wolde, 2014) as well as the finding of research done among pre-school children in Dembia district, Northwest Ethiopia documented 46% prevalence of stunting (Amare et al., 2016). The possible reason for the above variation could be a time gap between the studies as there is intensive nutritional intervention by the government as well as the non-governmental organization recently which possibly contributed to the reduction of undernutrition in the current study compared to the others. The finding is in line with the study done at Wolaita Sodo Town, Southern Ethiopia which revealed that the prevalence of stunting to be 22.2%, of which 21.8% and 22.6% were in children of employed and unemployed mothers, respectively (Hiwot Eshete1).

With regard to the level of wasting among the study participants, 5(1.7%) and 8(2.6%) of children of the employed and unemployed mother were classified as wasting based on the result of the anthropometric measurement. The level of wasting in the current study is lower when compared with the result of the study done at Wolaita Sodo town revealed the magnitude of wasting of 8.8% and 10.8% for children of employed and unemployed mothers, respectively (Hiwot Eshete1). It is also lower from the finding of research conducted in Bule Hora district, south Ethiopia was 13.4% of the study participants were found to be wasted, respectively (Mandefro Asfaw et al., 2015). The reason could be, accelerated nutritional intervention from different stakeholders is there currently when compared with time at which the above study was done. The current study revealed that about 4.6% and 8.3% of pre-school children of employed and unemployed mothers were underweight, respectively. The finding slightly lower when compared with the finding of a study done at Wolaita Sodo Town, Southern Ethiopia where Low-weight-for age was 10.8% for children of employed mothers and 13.4% for children of unemployed mothers (Hiwot Eshete1). As per the finding of research conducted in Bule Hora district, south Ethiopia 29.2% of the children were found to be underweight (Mandefro Asfaw et al., 2015) which is higher than the finding of the current study. This could be a socio-economic variation of the study participants and time gaps.

In general, the magnitude of stunting, wasting, and underweight is higher among pre-school of the unemployed mother when compared with employed mother. This may be associated with maternal employment which is one of the component of female empowerment where the mother will play a significant role in deciding family issue with knowledge and money they earn from the work particularly on nutrition practice of the family.

6.2. Factors associated with undernutrition of pre-school children among employed and unemployed women

Based on the result of this study, maternal educational status and having home servants were found to have a statistically significant association with stunting among children of the employed mother. Pre-school children whose mothers attended secondary school were about three times less likely to become stunted when compared with mothers whose educational status is read and write (AOR = 0.35, 95% CI = (0.15, 0.789)). The finding is in line with the result of research conducted among pre-school children in Dembia district, Northwest Ethiopia, the odds of stunting were higher among children of the employed mother where higher maternal education levels are associated with lower childhood undernutrition (Hiwot Eshete1). This could be as the educational status of mother increase, the possibility of exposure to maternal and child nutritional information will improve which in turn promote balanced nutritional practice by mothers for the family particularly for children than can improve the nutritional status of their children.

Another variable found to have a statistically significant association with the stunting of children whose mother is employed was having a home servant. The odds of being stunted among children of an employed mother who have no home servant are about three times higher when compared with their counterpart (AOR = 2.58, 95% CI = (1.35, 4.91), P-value = 0.004). The presence of a home servant can handle the issues of child-caring in the absence of a mother that can contribute significantly for better nutritional status for the child as compared to those employed mother not have home servants where they are responsible for caring for the child along with routine governmental duties.

Among unemployed women, from variables included in the final model, sex of the child, age of the mother, and having nutritional information from elsewhere were found to be significant predictors of stunting among pre-school children whose mother were not employed in a governmental institution. The magnitude of stunting among female children of unemployed women is about two times higher as compared to male children(AOR = 1.82, 95% CI = (1.05, 3.15). The result is supported by the study done to assess dietary diversity and meal frequency among infant and young children where male children are less likely to be stunted as compared with their counterparts (Belew et al., 2017; Derso et al., 2017).

The odds of stunting among children of unemployed women who have not got maternal and child nutritional information from elsewhere are nearly two times relative to those children whose mother got maternal and nutritional information (AOR = 1.99, 95% CI = (1.005, 3.934), P-value = 0.048). Health information dissemination which includes nutritional information is one of the essential intervention in bringing behavioral change which fosters healthy feeding practice using locally available food items. Due to the above fact, having information on infant and young child feeding could play a significant role in better nutritional status of children of employed women who have got such information.

The age of the mother was one of the factors found to have an association with stunting. Children whose mothers age is in the range of 25–34 years are nearly three times less likely to stunted when compared with children of others in the age range of greater than 35 years(AOR = 0.37, 95% CI = (0.17, 0. 79). This could be associated with, at an early age, the number of family size particularly children is limited compared with late age which enables the mother to give sufficient time to care from what she has for her children as compared with having a large number of children at a late age.

Concerning to factors associated with underweight, pre-school children of employed mothers whose age is greater than 35 years are nearly six times more likely to be underweight as compared to pre-school children of employed mothers whose age is between 15 and 24 years (AOR = 5.77, 95% CI = (1.20, 27.89)). This associated with the emphasis given for children increases at the early age of the family which may be associated with having limited children may contribute to better nutritional status of such children.

Sex of pre-school children of employed women is another variable found to have an association with underweight. Being female sex increase the risk of underweight by about four times compared with the counterpart (AOR = 4.04, 95% CI = (1.09, 14.99) and (P-Value = 0.037)). A similar finding was reported by the study done elsewhere were female more likely to be underweight as compared to female children (Jayakody1, 2014). Another child characteristic documented to have an association with underweight of pre-school children of employed women is the age of the child. Children whose age was greater than 32 months are about 5 times more likely to be underweight in relative to those in the age group between 16 and 32 months (AOR = 0.21, 95% CI = (0.05, 0.81)). This could be associated with the sharing of child-caring efforts to other children below the age of them as there is a possibility that the family will have additional children. Pertaining to factors associated with underweight among pre-school children of unemployed women, maternal nutritional knowledge was found to be a significant predictor of underweight.

Pre-school children whose mothers have no good knowledge about maternal and child nutrition about four times more likely were underweight compared with their counterparts (AOR = 3.84, 95% CI = (1.07, 13.80)). Having good knowledge of nutrition may foster better infant and young child feeding practice that can benefit the children for having better nutritional status. Odds of underweight among children of unemployed women whose total family size is greater than five is about 2.5 times higher as compared with family having less than five family size (AOR = 2.5, 95% CI = (1.00, 6.29)). As the number of family size increases the possibility of sharing and reducing the quantity of food way exists as one coping mechanism which predisposes children for not having sufficient and balanced food that in turn results in poor nutritional status of children.

6.3. Strength of the study

The study tried to include a large sample size and relatively wider geography of the zone which can be an input for designing and implementation on maternal-child nutrition intervention.

6.4. Limitation of the study

Using a cross-sectional study design might have a chicken-egg dilemma for some variables in the study.

7. Conclusion

The magnitude of stunting, wasting, and underweight is lower when compared with the finding of a different study done in a different area. The prevalence of stunting, wasting, and underweight is lower among children of employed mothers compared with unemployed women.

From different explanatory variable exported to the final model, education status of the mother and having home servant were explanatory variables found to have a statistically significant association with stunting among pre-school children of employed women.

Sex of the child, age of the mother and got maternal and child nutritional information were among the variable left in the final multiple logistic regression model as having a significant association with undernutrition (stunting) among pre-school children of unemployed women.

Age of the mother, family monthly income, sex of the child, and age of the child were found to have a statistical association with pre-school children underweight of employed mother. On the other hand, maternal knowledge on nutrition, family size, and having own home were revealed to have a statistically significant association with underweight of pre-school children of unemployed women.

8. Recommendation

Educating and empowering women is one of the areas that needs great intervention by concerned stakeholders for better maternal and child nutrition. Wolaita zone health office in collaboration with non-governmental organizations working on maternal and child nutrition needs to strengthen the existing activity about improving the awareness of mothers with regards to infant and young child feeding practice.

Author contributions

• Conceptualization: Yoseph Halala and Derartu Zewude

• Data curation: Yoseph Halala and Derartu Zewude

• Formal analysis: Yoseph Halala and Derartu Zewude

• Funding acquisition: Yoseph Halala and Derartu Zewude

• Investigation: Yoseph Halala and Derartu Zewude

• Methodology: Yoseph Halala and Derartu Zewude

• Project administration: Yoseph Halala and Derartu Zewude

• Resources: Yoseph Halala and Derartu Zewude

• Software: Yoseph Halala and Derartu Zewude

• Supervision: Yoseph Halala and Derartu Zewude

• Validation: Yoseph Halala and Derartu Zewude

• Writing ± original draft: Yoseph Halala and Derartu Zewude

• Writing ± review & editing: Yoseph Halala and Derartu Zewude

Acknowledgements

First and for most I would like to acknowledge my almighty God. I would like to extend my heartfelt gratitude to the NORHED PROJECT and Walaita Soddo University School of public health, department of reproductive health, and nutrition for continuous support. My sincere gratitude also goes to the Wolaita Zone health office for providing me with relevant data for the finalization of the research.

Data availability statement

All relevant data are within the paper and its supporting information file.

Additional information

Funding

NORHED PROJECT at Walaita Soddo University School of public health, department of reproductive health and nutrition

Notes on contributors

Derartu Zewdu

Derartu Zewdu is an MSc scholar at Wolaita Sodo University, School of public health, department of nutrition and reproductive health.

Yoseph Halala Handiso

Yoseph Halala Handiso is an Assistant Professor in the school of public health at the department of nutrition and reproductive health, Wolaita Sodo University. His research interests include themes on human nutrition and reproductive health, food and nutrition security, agricultural and nutrition liking.