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Prevalence and associated factors of underweight among children 6–59 months of age in Takusa district, Northwest Ethiopia

International Journal for Equity in Health201817:106

https://doi.org/10.1186/s12939-018-0816-y

  • Received: 6 November 2017
  • Accepted: 6 July 2018
  • Published:

Abstract

Background

Most of the nearly 104 million underweight children in the world lived in South East Asia and sub-Saharan Africa in 2010. According to the 2014 Ethiopian Demographic and Health Survey (EDHS) report, 24 and 7% of children aged 6–59 months were underweight and severely underweight, respectively. Although appropriate child feeding and nutritional interventions reduce child illness and death, malnutrition remains a leading public health problem in Ethiopia. As literature on the issue is scarce in northwest Ethiopia, this study aimed at determining the prevalence of under-weight and associated factors in children 6–59 months of age in Takusa district, northwest Ethiopia.

Methods

A community based cross-sectional study was conducted from January to February, 2017, at Takusa district, northwest Ethiopia. A total of 645 subjects were selected using the multi-stage sampling technique. Anthro software version 2.02 was used to determine the nutritional status of the children. A multivariable logistic regression analysis was used to investigate factors associated with underweight. Adjusted Odds Ratios (AOR) with the corresponding 95% Confidence Interval (CI) were used to show the strength of associations, and variables with P-values of < 0.05 were considered statistically significant.

Results

In this study, the overall prevalence of underweight was 19.5% (95% CI: 16.4–22.8). According to the multivariate analysis, urban residence (AOR = 0.60; 95% CI: 0.38–0.95), no antenatal care (ANC) follow up (AOR = 1.59; 95% CI 1.01–2.52), and mothers age (over 35 years) (AOR = 0.62; 95% CI: 0.38–0.99) were significantly associated with lower odds of underweight.

Conclusion

In the study community, the prevalence of underweight was lower than the findings of different studies in Ethiopia. Advanced maternal age (> 35 years), no antenatal follow up during pregnancy, and rural residence were significantly associated with underweight. Therefore, interventions targeting community management of acute malnutrition might be appropriate to manage the problem of underweight; efforts should also be intensified to reduce under-weight by focusing on identified determinants.

Keywords

  • Underweight
  • 6–59 months children
  • Takusa
  • Northwest
  • Ethiopia

Background

Nutrition adequate for the ages of infants and young children is essential for healthy growth, proper organ formation, and function, as well as for a strong immune system and neurological development [1]. Under-five children are the most susceptible age group for malnutrition, and nutritional status during childhood is a sensitive indicator of community health. Under-nutrition which can make children underweight, stunted, and wasted does not only increase the risk of infections, morbidity, and mortality but can also decrease mental and cognitive development. The effect of child malnutrition is long lasting and goes beyond childhood [1]. Underweight, defined based on weight for-age, is a composite measure of stunting and wasting and is recognized as the indicator for assessing changes in the magnitude of malnutrition over time. Wasting is the result of a recent failure to receive adequate nutrition and may be affected by recent episodes of infections, like diarrhea and other acute illnesses. Wasting indicates current or acute malnutrition, resulting from failure to gain weight or weight loss [2].

Underweight remains one of the most common causes of morbidity and mortality among children throughout the world [3, 4]. Globally, about 104 million children were under-weight in 2010, and the majority of these lived in sub-Saharan Africa and South Asia. Malnutrition is one of the leading causes of morbidity and mortality in children under the age of 5 years in developing countries. Every year, 3.5 million children die of malnutrition-related causes, of which underweight accounts for nearly 1 million [2, 5]. About two in five (38%) children in sub-Saharan Africa are underweight; 10.5% wasted, (2.2% severely), and 46.5% stunted (half of them severely) [4]. In Ethiopia, the prevalence of underweight was 24%, while in Amhara region, where the study was conducted, it was 28.4% [6]. Studies in Ethiopia report that under nutrition remains a public health problem and that its prevalence, in rural Ethiopia in general and Bure district in particular, has been 27 and 14.3%, respectively.

Though childhood malnutrition continues to be the leading public health problem in developing countries, it can occur as a result of a wide range of factors. Lack of dietary diversity and micronutrient-dense food consumption and poor child feeding practices contribute to the high rate of child under nutrition. Various reports also indicate that underweight in children is mainly caused by inadequate food intake [7, 8], repeated infections [911], low parental education [1214], lack of sanitation [15], poor feeding practices [16], no ANC [1719], residence [20], child rearing practices [21], economic [21, 22], social, and cultural factors [23].

In Ethiopia, malnutrition is a leading cause of child illness and death. Having been firmly committed to addressing food insecurity and under-nutrition, the Government established various multi-sectoral groups to coordinate and support efforts to step up rural economic development and food security [2426]. Moreover, efforts to enhance good nutritional practices in rural areas expand health institutions, provide nutrition counseling and food focusing on appropriate child feeding and intervention have been made. However, underweight is still a problem and nearly one-third of the under-weight children are found in the Amhara Region, northwest Ethiopia, where literature is scarce [27]. Thus, this study aimed at determining the prevalence of under-weight and associated factors in Takusa district.

Methods

Study design and setting

A community-based cross-sectional study was conducted from January to February 2017 in Takusa district, northwest Ethiopia. The site is located at 738 km from Addis Ababa, the capital of Ethiopia and has an estimated population of 172,754, living in 25 kebeles (smallest administrative units). It was estimated that about 23,391 under-five children were found in the district. The data were collected from January to February 2017.

Population, sample size, and sampling procedure

All mothers with children aged 6–59 months and lived in the selected kebeles for at least 6 months were included in the study. When households had more than one such child, one of them was selected using the lottery method. Out of the 25 kebeles in the district, five were randomly selected by the simple random sampling technique. For this particular study, the sample size was calculated using Epi-info version 3.7 by considering the following assumptions: the prevalence of underweight as 25.6%, 95% level of confidence, and 5% margin of error. Moreover a 10% non-response rate and a design effect of 2 were also used to yield the final sample size of 645.

Data collection tool and procedures

A pretested, structured and interviewer administered questionnaire was used to collect data. Cronbatch’s alpha was used to check the consistency of the tool which turned out to be 87%. Six data collectors (clinical nurses) and two supervisors (health officers) were recruited for the task. To maintain consistency, the questionnaire was first translated from English to Amharic, the native language of the study area, and re-translated to English by professional translators and public health experts. A two-day intensive training was given to data collectors and supervisors on the objective of the study, confidentiality of information, how to take anthropometric measurements and techniques of conducting interviews. Data were collected at household levels and mother or care givers were the actual respondents. If the care giver or mother was not found, the data collector visited the household at least twice. The response rate was 100%. Initially, anthropometric measurements, like weight and height/length were measured, and age was taken from mothers/caretakers. Child length and height were measured according to child age. Child length was measured with the child lying down (in recumbent) position when they are under the age of 2 years. Thin clothes were used to cover the length board for child comfort. We used a length board (infantometer) and a height board (stadiometer) to measure length and height, respectively. Then, weights for age, weight for height, and height for age were determined using the software Anthro. Weight was measured using the Salter scale. Heavy shoes and clothes were removed during data collection. The height of children was also measured at Frankfurt position (touch occipital, shoulder, buttock, calf, and heel). Length measurement was also used for children less than 2 years of age.

For young children, unable to self-care especially, weight was checked together with their mothers or care givers. Then the mother weighed alone and the child’s weight was found by subtracting the mother’s weight from the total weight. In general, calibration of instruments and standardization techniques were used to avoid discrepancies. Before data collection, training was given on Salter scale with a capacity of 25 kg, and height or length. For children less than 2 years, length was used to check their anthropometric measurement. The tool was piloted on 5% of the total sample out of the study area.

Measurements and study variables

Under weight, the outcome variable of this study, was measured using the anthropometric indicator of weight-for-age (WAZ) in the form of z-score, using the WHO Anthro 2006 software. The z-score depicted the deviation from the median weight of the child according to the World Health Organization (WHO) reference of the median of the growth standard curve. Under-weight was defined as weight-for-age (Z-score < − 2), using child growth standards published by WHO in 2006. Severe underweight was diagnosed if it was below − 3 SD. Variables such as age, sex, maternal and paternal educational status, occupation, family size plus maternal characteristics, like number of children ever born, ANC visits, birth order, health status during pregnancy, as well as morbidity status, like fever, diarrhea, measles and ARI were assessed.

Data processing and analysis

Data were entered into Epi-info version 7 and exported to the Statistical Package for Social Sciences (SPSS) version 20 for analysis. Descriptive statistics, including frequencies and proportions were computed and presented using texts, graphs, and tables. Both bivariable and multivariate logistic regression models were carried out. Variables with a p-value of less than 0.2 in the bi-variable analysis were entered into the multivariable analysis. Both Crude Odds Ratio (COR) and Adjusted Odds Ratio (AOR) with 95% confidence intervals were estimated to show the strength of associations. The technique was a backward stepwise regression method. Finally, a p-value of less than 0.05 in the multivariable logistic regression analysis was used to identify variables significantly associated with underweight. For this study, the Hosmer and Lemeshow goodness of fit test which yielded a p-value greater than 0.05 was considered.

Results

Socio-demographic and economic characteristics

A total of 645 households were included in the study. Nearly half (46.2%) of the mothers were in the age range of 15–29 years. The mean age of mothers was 30.49 (SD 6.24) years. The majority, 629 (97.5%), of the households were Amhara by ethnicity. Three-hundred fifty- three (54.7%) of the mothers and 269 (41.7%) of the fathers were illiterate. Out of the total households, more than two-thirds, 453 (70.2%), lived in rural areas. About 336 (52.1%) of the children were male with a mean age of 21.85 months, and a standard deviation (SD) of 13.2. The majority, 85.9 and 92.6%, respectively) of the mothers were married Orthodox Christians. Almost three-quarters (74.3%) of the mothers were house wives. One-third, (32.6%) of the households had below ETB 500 monthly income. It was revealed that nearly half (47.9%) of the index children were female. About 16.6% of the mothers reported that their children suffered from diarrhea (Table 1).
Table 1

Socio-economic and demographic factors in Takusa district, North West Ethiopia, 2017

Variables

Frequency

Percent

Mother’s age (In years)

 15–29

298

46.2

 30–34

165

25.6

 ≥ 35

182

28.2

Religion

 Orthodox

597

92.5

 Othersa

48

7.5

Marital status

 Not married

91

14.1

 Currently married

554

85.9

Mother’s educational level

 Unable to read and write

353

54.7

 Able to read and write

194

30.1

 Primary and above

98

15.2

Husband’s educational level

 Unable to read and write

269

41.7

 Able to read and write

251

38.9

 Primary and above

125

19.4

Mother’s main occupation

 House wife

479

74.3

 Government employee

62

9.6

 Othersb

104

16

Family monthly income (ETB)

 ≤ 500

210

32.6

 501–1000

233

36.1

 ≥ 1001

202

31.3

Family sizes

 ≤ 4

304

47.1

 5–7

273

42.3

 8–11

68

10.5

Number of Under-five children

 ≤ 2

500

77.5

 > 3

145

22.5

Age of index child (In months)

 6-< 12

179

27.8

 12-< 24

172

26.7

 24-< 36

155

24.0

 36-< 48

90

14.0

 48–59

49

7.5

Sex of index child

 Male

336

52.1

 Female

309

47.9

Household land ownership

 Yes

559

86.7

 No

86

13.3

Child illness

 Diarrhea

107

16.6

 Measles & ARI

39

6.0

 No diseases

499

77.4

aprtotestant and Muslim, bself employed, daily laborer

Health service and environment related characteristics

The majority, 510 (79.1%), of the households had latrines. A large proportions, 266 (60.3%), of the rural households of the district used river water for drinking. About 504 (78.1%) of the households reported that they washed their hands after toilet; 160 (31.7%) of these were urban and 344 (68.3%) rural households. Three-fourths (76.3 and 77.7%, respectively), of the mothers had ANC follow-ups and took extra foods during pregnancy, and the majority (79.2%) had post-natal care visits after pregnancy (Table 2).
Table 2

Health service and environmental related factors in Takusa district, North West Ethiopia, 2017

Variables

Frequency

Percent

ANC follow-up

 Yes

494

76.6

 No

153

23.4

ANC visits

 ≤ 3 times

421

85.5

 > 3Times

73

14.5

PNC visit

 Yes

514

79.7

 No

131

20.3

Source of drinking water

 Piped water

441

69.8

 Protected well and spring

139

22.1

 Others (River and Unprotected well &Spring)

51

8.1

Distance to fetch drinking water

 Less than an hour

472

73.2

 1 h or more

61

9.5

 Water on premises

112

17.3

Have Latrine

 Yes

510

79.1

 No

135

20.9

Hand washing with soap after toilet

 Yes

504

78.1

 No

141

21.9

Prevalence of underweight and feeding practices of children

In this study, the prevalence of underweight, stunting, and wasting were 126 (19.5%), 236 (36.5%), and 52 (8%), respectively. The proportion of severe and moderate underweight children was 53 (8.2%) and 73 (11.3%), respectively. Underweight was higher (76.9%) among rural dwellers than among urban residents (23.1%).

One-fifth, 133(20.6%), of mothers gave food and/or drink to the new-born before the establishment of breast milk in the first 3 days of delivery (prelactal feeds), but about 105 (16.3%) of the children did not get the first milk (the colostrum). The majority, 527 (81.7%), of the children were on exclusive breastfeeding, and about 58.8% started complementary feeding at 6 months. About 501 (77.7%) of mothers had extra food during pregnancy (Table 3).
Table 3

Nutritional status and Feeding practices of childrenin Takusa district, North West Ethiopia, 2017

Variables

Frequency

Percent

Underweight (WAZ)

 Normal (≥ -2SD)

519

80.5

 Moderate (≥ − 3 < -2SD)

73

11.3

 Severe (<-3SD)

53

8.2

 Overall Underweight (<-2SD)

126

19.5

Stunting (HAZ)

236

36.6

Wasting (WHZ)

52

8.1

Complementary feeding started

 < 6 months

73

11.3

 At 6 months

379

58.8

 6–7 months

165

25.6

 > 7 months

28

4.3

Frequency of complementary feeding per day

 < 3 times

96

14.9

 3–4 times

407

63.1

 > 4times

142

22.0

Duration of complementary feeding for child

 < 1 year

25

3.9

 1–2 years

220

34.1

 > 2 years

400

62.0

Types of food given for child

 Cereal based Porridge

72

11.1

 Others (Cereal based Atmit, cow milk and formula milk)

81

12.6

Discard colostrum

 Yes

540

83.7

 No

105

16.3

Time to start breast-fed

 Within 1 h

478

74.1

 2–24 h

142

22.0

 After a day

25

3.9

Exclusive breastfeeding

 Yes

527

81.7

 No

118

18.3

Frequency of breastfeed per day

 < 4 times

43

6.7

 4–7 times

231

35.8

 8–10 times

268

41.6

 > 10 times

103

16.0

Prelactal feeding

 Yes

133

20.6

 No

512

79.4

Extra food during pregnancy

 Yes

501

77.7

 No

144

22.3

Factors associated with underweight among children aged 6–59 months

In the bivariate logistic regression analysis, marital status, mother’s occupation, ANC, age of mother, husband’s education, residence, comprehensive knowledge on IYCF, household income, breast-feeding during crying, child complementary feeding, frequency of breast feeding, and distance of water source were factors associated with underweight at a p-value of less than 0.2. Consequently, these variables were subjected to multivariate logistic regression analysis, and it was noted that residence, age of mother, and ANC follow up were significantly associated with underweight at a p-value of 0.05.

According to the multivariable logistic regression analysis, the odds of underweight children among urban dwellers were 39.6%, less likely to compare with those of rural residents (AOR = 0.604; 95% CI: (0.381–0.958). Similarly, the odds of underweight children among mothers who were above 35 years were 38.5%, unlike that of mothers below 35 years of age (AOR = 0.615; 95%CI: (0.382–0.99). Higher odds of underweight children were observed among mothers who had no antenatal care follow-up (ANC) (AOR = 1.595; 95% CI: (1.010–2.520) (Table 4).
Table 4

Factors associated with underweight among children aged 6–59 months in Takusa district, North West Ethiopia, 2017

Variables

Underweight

COR (95% CI)

AOR (95% CI)

Yes

No

  

Place of residence

 Rural

356(78.6%)

97(21.4%)

1

1

 Urban

163(84.9%)

29(15.1%)

0.65(0.42–1.03)

0.60(0.38–0.95)a

Mother’s age

 15–34 years

366(79%)

97(21%)

1

1

 > 35 years

153(84.1%)

29(15.9%)

0.78(0.48–1.28)

0.62(0.38–0.99)a

Mother’s occupation

 House wife

380(79.3%)

99(20.7%)

1

1

 Others

139(83.7%)

27(16.3%)

0.89(0.52–1.52)

0.63(0.18–2.17)

Distance to fetch water

 < 1 h

372(78.8%)

100(21.2%)

 

1

 1 h or more

51(83.6%)

10(16.4%)

0.73(0.36–1.48)

0.88(0.52–1.51)

Child Complement feeding

 < 6 month

205(77.1%)

61(22.9%)

1.43(0.97–2.13)

0.81(0.53–1.24)

 > 6 month

314(82.8)

65(17.2%)

1

1

Comprehensive Knowledge on IYCF

 Yes

391(81.8%)

87(18.2%)

1

1

 No

128(76.6%)

39(24.4%)

1.36(0.89–2.09)

1.44(0.92–2.27)

ANC follow up

 Yes

402(81.7%)

90(18.3%)

1

1

 No

117(76.5%)

36(23.5%)

1.37(0.88–2.10)

1.59(1.01–2.52)a

Given breast milk during cry

 Yes

213(77.7%)

61(22.3%)

1.35(0.91–1.99)

1.92(0.83–1.92)

 No

316(82.5%)

65(17.5%)

1

1

aVariable significant at p-value less than 0.05

Discussion

In this study, the overall prevalence of underweight was 19.5% with a 95% Cl (16.4–22.8%). The finding was lower than those of Mecha district (34%) [28], Medebay Zana district (Tigray) (45.3%) [29], Haramaya (36.6, 28.2%) [30], in Ethiopia. This might be due to the fact that mothers in food insecure areas were at a high risk of getting underweight babies [7], while participants in this study lived in a food secure area that maximized the frequency of feeding, and making it possible for providing diversified food provision. Similarly, the finding was lower than findings overseas, for example, Bangladesh 43% [31], Yemen 46.2% [17], and Nepal 27.4% [32]. The possible justification for this could be variations among participants in wealth, access to health care, and differences in socio-demographic characteristics [17, 33]. For example, participants in Nepal came from hilly areas where low crop productivity minimized access to balanced nutrition and appropriate health care [32]. In contrast, the magnitude of underweight in our study was higher than 5.74% [34] and 14.9% [35] reported from Tanzania and Kenya, respectively. This difference might be due to the fact that participants from Tanzania and Kenya were urban dwellers and had access to more fruit, vegetables, and dairy products [8]. In addition, variations in study settings, high proportions of educated mothers [28, 32, 36], better wealth index [37], and access to health care [28] might be the other reasons for the variations.

Out of variables which showed significant associations with underweight lower odds of the problem were noted among urban dwellers. It was seen that the odds of underweight among urban children were 39.6%, highly unlikely to compare to rural ones. This finding was consistent with reports from Mozambique [36] and Bangladesh [38]. The notable difference in the rate of underweight among urban and rural children might be differences in living conditions, variations in early screening of mothers at child conception in urban areas compared with rural settings, exposure to poor dietary diversity [7, 8], and greater risks of infections among rural children [10]. Moreover, access to fruit and vegetables, and dairy products among urban dwellers might be the other factors for the differences in underweight rates [8]. In addition, most rural mothers spent their time in fields engaged farming activities and couldn’t offer a 24-h breastfeeding instead they provided only the usual food items which wouldn’t substitute the expected benefits [16, 22].

Like other studies conducted in Haramaya [30], Malawi [18], rural Yemen [17], and Somali Region [3], the odds of underweight in this study were high among mothers who had no antenatal care follow-ups. This might be due to the fact that accesses to health care services, like ANC, are important sources of information for women to access nutritional and health messages [18]. Furthermore, mothers who had ANC follow-ups had knowledge sharing opportunities for optimal infant and young child feeding (IYCF) [28]. As a result, children whose mothers had ANC were less likely to be underweight. In addition, mothers taking ANC were informed about breastfeeding which is of indispensable importance to minimize underweight among children [3]. Furthermore, variations in study settings and designs might be the other possible justifications for the observed differences.

The odds of underweight were low among children whose mothers were over 35 years when compared with those below. The finding was consistent with those of studies conducted in Belesa, and Yemen [39]. This could be due to the fact that young women are, by and large, less experienced in care giving and provide unqualified items [39]. Besides, adolescent mothers demand extra energy and nutrients for completing their growth and development. As a result, pregnancy during adolescence slows down the girl’s growth and may result in an underweight infant [40]. Therefore, this study has tremendous importance for both clinical and public health experts for further reducing burden of underweight. An assessment of a child’s nutritional status is an important routine indicator for monitoring growth and development. It helps to control death and complications relating to malnutrition. Moreover, from the public health perspective, reducing the prevalence of underweight is an important measure for providing supplementation activities to prevent further risks of underweight [2]. Though the study did its best to indicate the magnitude of underweight using a community-based investigation and a large sample, it was not free from limitations. For example, the cross-sectional design might have prevented the work from showing temporal relationships.

Conclusion

In this community, the prevalence of under-weight was lower than the national figure. Advanced maternal age (> 35 years), antenatal care follow-up and urban residence were significantly associated with lower odds of the problem. Therefore, improving health service utilizations, such as ANC follow-up, access to information for rural areas are highly recommended.

Abbreviations

ANC: 

Antenatal care

AOR: 

Adjusted Odds Ratio

CI: 

Confidence Interval

EDHS: 

Ethiopian Demographic Health Survey

EPI: 

Expanded Program on Immunization

MDG: 

Millennium Development Goal

SAM: 

Sever Acute Malnutrition

SUN: 

Scale Up Nutrition

UNICEF: 

United Nations Children Emergency Fund

Declarations

Acknowledgments

The authors are indebted to the University of Gondar for the approval of the ethical clearance, North Gondar Zone Health Departments and respective district health offices for giving us permission to collect data in the selected kebeles. The authors also forward their gratitude to study participants, data collectors, and supervisors who participated in the study.

Ethics approval and consent to participate

Ethical clearance was obtained from the Ethical Review Board of the University of Gondar. A letter of permission was obtained from the North Gondar Zonal Health Department. After the objective of the study was explained, verbal consent was obtained from each participant. Moreover, the privacy and confidentiality of information was strictly guaranteed by all data collectors and investigators. The information retrieved was used only for the study.

Funding

No funding was obtained for this study.

Availability of data and materials

Data will be available upon request from the correspondence author.

Authors’ contributions

GN conceived of the study, coordinate data collection. GN, SA, TYA, and MKY performed statistical analysis and drafted the manuscript. All authors read and approved the final manuscript.

Consent for publication

Not applicable.

Competing interests

Authors declare that they have no conflict of interest.

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Authors’ Affiliations

(1)
Takusa District Health Office, University of Gondar, North-west, Gondar, Ethiopia
(2)
Department of Health Informatics, Institute of Public Health, University of Gondar, Gondar, Ethiopia
(3)
Department of Epidemiology and Biostatistics, Institute of Public Health, University of Gondar, Gondar, Ethiopia

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