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Erschienen in: BMC Nutrition 1/2019

Open Access 01.12.2019 | Research article

Determinants of stunting among children aged 0–59 months in Nepal: findings from Nepal Demographic and health Survey, 2006, 2011, and 2016

verfasst von: Ramesh P. Adhikari, Manisha Laxmi Shrestha, Ajay Acharya, Nawaraj Upadhaya

Erschienen in: BMC Nutrition | Ausgabe 1/2019

Abstract

Background

Stunting is one of the most commonly used indicators of child nutrition and health status. Despite significant efforts by the government and external development partners to improve maternal and child health and nutrition, stunting is consistently high in Nepal. This paper assesses the potential determinants of stunting among children aged 0–59 months using the last three successive Nepal Demographic and Health Surveys (NDHS).

Methods

We used three nationally representative cross-sectional household surveys, known as the NDHS- 2006, 2011 and 2016. Logistic regression was used to identify the potential determinants of stunting. The sub sample for this study includes n = 5083 in 2006, n = 2485 in 2011, and n = 2421 in 2016.

Results

Rates of stunting decreased from nearly 50% in 2006 to about 36% in 2016. The prevalence of stunting was higher among children from larger families (51.0% in 2006, 41.1% in 2011, 38.7% in 2016), poor wealth quintile households (61.2% in 2006, 56.0% in 2011, 49.2% in 2016), and severely food insecure households (49.0% in 2011, 46.5% in 2016). For child stunting, the common determinants in all three surveys included: being from the highest equity quintile (OR: 0.58 in 2006, 0.26 in 2011, 0.28 in 2016), being older (OR: 2.24 in 2006, 2.58 in 2011, 1.58 in 2016), being below average size at time of birth (OR: 1.64 in 2006, 1.55 in 2011, 1.60 in 2016), and being affected by anemia (OR: 1.32 in 2006, 1.59 in 2011, 1.40 in 2016).

Conclusions

This study found that household wealth status, age of child, size of child at time of birth, and child anemia comprised the common determinants of stunting in all three surveys in Nepal. Study findings underscore the need for effective implementation of evidence-based nutrition interventions in health and non-health sectors to reduce the high rates of child stunting in Nepal.
Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s40795-019-0300-0) contains supplementary material, which is available to authorized users.

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Abkürzungen
BMI
Body Mass Index
HFIAS
Household Food Insecurity Scale
MSNP
Multi-Sectoral Nutrition Plan
NDHS
Nepal Demographic and Health Survey
OR
Odds Ratio
PPS
Probability proportion-to- size
SDG
Sustainable Development Goal
STATA
Software for Statistics and Data Science

Background

Child malnutrition remains a major public health problem globally. Malnutrition can take the form of stunting (height-for-age and/or weight-for-height) and underweight (weight-for-age); however, stunting is the primary form of malnutrition seen throughout the world [1, 2]. Stunting in early life is associated with adverse functional consequences, including poor cognition and educational performance, low adult wages, lost productivity, and chronic disease when accompanied by excessive weight gain later in childhood [35]. While the consequences of stunting are clear, its causes are more complex [6]. Direct factors contributing to stunted growth and development include poor maternal health and nutrition, inadequate infant and young child feeding practices, micronutrient deficiencies, and infections [7]. The Sustainable Development Goals (SDG) identified stunting, along with other nutrition indicators, as a target to reduce global malnutrition; meeting this goal demands renewed and concerted efforts focused on disparity [8].
Globally, approximately 155 million children under 5 years suffer from stunting, with an estimated one million associated child deaths annually. Among the regions of the world, Africa and Asia share the highest burden of all forms of malnutrition. In 2017, nearly two out of every five stunted children lived in Southern Asia [9]. Nepal is one of only ten countries in the world where more than half of children under five suffer from some form of malnutrition [10]. According to the 2016 Nepal Demographic Health Survey, 36% of children under five suffered from stunting. Previous studies in Nepal have identified several common determinants of stunting, including child sex, age, birth weight, birth order, number of siblings, wealth index, mother’s education, mother’s body mass index, and access to health care [1113]. The Nepal government identified nutrition as one of the key priority areas for national development. In 2012, the Nepal government developed a multi-sector nutrition plan involving different line ministries to implement an evidence-based nutrition intervention throughout health and non-health sectors. As a result, Nepal has made significant gains in health and nutrition indicators, including stunting, despite being in social, economic and political transition [14], and being one of the poorest countries in South Asia. Nevertheless, decreases in stunting stalled between 2012 and 2017. To meet the global target by 2025, Nepal needs to continue to reduce stunting by 3.9% annually [15].
The purpose of this paper is to determine the prevalence and associated factors of child stunting in the last 15 years in Nepal using nationally representative data from the Nepal Demographic and Health Surveys (NDHS) 1996–2016. While previous studies attempted to explore determinants of stunting, each only reported data from a single year. Currently, there is insufficient evidence on trends and determinants of stunting from nationally representative surveys in Nepal, thus limiting long-term policy formulation and planning. Hence, assessing the trends and factors associated with stunting will provide insights into the effectiveness of the implemented program and will assist policy makers and program developers in designing new and effective programs that target groups most at-risk.

Methods

This paper uses data from the 2006, 2011, and 2016 NDHS, a nationally representative cross-sectional household survey. This dataset includes information on a variety of health topics, as well as socio-economic and demographic information. The risk factors have been classified into demographic factors, maternal nutrition factors, and child nutrition factors. The NDHS surveys used a two stage selection process; initially, enumeration areas (clusters) were selected with probability proportion-to-size (PPS) methodology and next, households were selected with an equal probability systematic selection from each sample cluster. The sampling details for this survey have been documented in the full NDHS report [16]. In 2006, height and weight information for a total of 5295 children was collected from 8707 interviewed households. Similarly, in 2011, 2603 children’s height and weight information was collected from 10,826 interviewed households, and in 2016, a total of 2428 children’s information was collected from 11,040 interviewed households. Some cases were excluded because their height and weight measurements were outliers (n = 212 in 2006, n = 118 in 2011, and n = 7 in 2016). Thus, the final sample sizes for the analyses in this paper were n = 5083 in 2006, n = 2485 in 2011, and n = 2421 in 2016. [16].
Stunting, the single outcome variable, was measured based on height-for-age z-scores <− 2 standard deviation. The NDHS calculated the height-for-age z-scores based on the 2006 World Health Organization (WHO) growth standards. These scores were used for the analysis [17]. Based on the local context and prior studies, household, maternal, and child characteristics were included as potential determinants of stunting in Nepal. Household characteristics included family size, headship of the household, caste/ethnic group (Dalit, Muslim, Janajati, other Terai caste, Brahmin/Chhetri, others), wealth quintile (based on NDHS wealth quintiles), place of residence (urban or rural), ecological zone (mountain, hill, or terai), household food security status (food secure, mildly food secure, moderately food insecure, or severely food insecure), and access to drinking water and a toilet (improved or unimproved). Maternal characteristics included the mother’s age, years of schooling, employment status (currently employed or not), BMI (underweight with a BMI < 18.5, or not), anemia (anemic or not), and number of living children. Likewise, child characteristics included age and sex of the child, birth order, size at time of birth (average or larger or below average), and anemia (anemic or not).
The NDHS used the same questions as the Household Food Insecurity Scale (HFIAS), which was originally developed by the United States Agency for International Development (USAID) Food and Nutrition Technical project to measure household food security status. These questions focused on the severity and frequency of food insecurity in the household units based on the 30 days preceding the survey. Based on responses to these questions, four categories were developed based on the HFIAS measuring guidelines: food secure, mildly food secure, moderately food insecure and severely food insecure [18]. Access to piped drinking water was defined as “improved” water access, while all other sources were defined as “unimproved”. Likewise, access to a toilet was defined as “improved” if the households had flush/pour toilets to piped sewer systems, septic tanks and/or pit latrines, ventilated improved pit latrines with slabs, and/or composting toilets. Access to other types of toilets were considered “unimproved”.
The NDHS collected blood samples to measure mother and child anemia using HemoCue. Children were considered anemic if their hemoglobin levels were < 11.0 g/deciliter. Likewise, mothers were considered anemic if their hemoglobin levels were < 12.0 g/deciliter for non-pregnant mothers and < 11.0 for pregnant mothers. Mothers were included if they had ever been married, were not currently pregnant, and had not given birth in the previous 2 months. Exclusion criteria included outliers in BMI, height, and weight measurements [16]. For the national representation of the sample, the analysis was performed by applying sampling weights. Descriptive, univariate, bivariate, and multivariate analyses was performed. Mean z-scores and standard deviations were calculated for height-for-age. Logistic regression models were used to identify the possible determinants of stunting. All analyses were performed in Stata version 14.

Results

This study included 5083 children from the 2006 NDHS, 2485 children from the 2011 NDHS, and 2421 children from the 2016 NDHS. In all three surveys, more than a quarter of the children were from Janajati caste/ethnic groups, more than half were from the Terai region, and about 60% were between 24 and 59 months. With regard to mothers’ education, more than half of the mothers sampled had no schooling in 2006 and 2011; however, this was down to 36% in 2016 (Table 1).
Table 1
Socio-economic and demographic characteristics of children under 5 years and their mothers
Background characteristics
2006
2011
2016
%
N
%
N
%
N
Caste/ethnicity
 Dalit
15.5
788
17.7
440
14.1
342
 Muslim
5.6
286
5.9
147
6.8
164
Janajati
31.6
1608
32.0
794
27.3
661
 Other Terai caste
14.0
713
9.3
230
19.8
479
 Brahmin/Chhetri
28.4
1444
29.5
734
26.0
629
 Other
4.8
244
5.6
140
6.0
146
Wealth quintile
 Poorest
25.3
1285
25.8
640
20.5
496
 Second poorest
21.4
1086
20.5
510
21.8
528
 Middle
20.3
1032
23.4
582
22.7
549
 Second richest
18.1
921
16.9
421
21.7
526
 Richest
14.9
759
13.4
332
13.3
322
Ecological Zone
 Mountain
8.4
425
7.9
196
7.0
170
 Hill
41.3
2100
39.9
991
36.2
876
Terai
50.3
2558
52.2
1298
56.8
1375
Year of schooling of mother
 No schooling
61.4
3119
50.5
1256
36.0
910
 1–5 years schooling
16.9
858
17.8
442
19.0
449
 6–9 years schooling
15.5
788
18.7
464
23.9
563
 10 and above years of schooling
6.3
318
13.0
323
21.1
499
Age of child
 Less than 6 months
9.1
474
9.2
228
9.0
218
 6–11 months
9.2
484
9.9
247
10.4
251
 12–23 months
18.7
970
19.6
489
21.1
512
 25–49 months
63.1
3155
61.3
1521
59.5
1440
Sex of child
 Boys
51.2
2604
51.2
1273
52.0
1258
 Girls
48.6
2479
48.8
1212
58.0
1163
 Total
100.0
5083
100.0
2485
100.0
2421

Prevalence of stunting

The mean z-scores for stunting (height-for-age) showed slight improvement between 2006 and 2016 (− 1.92 in 2006 and − 1.29 in 2016). Likewise, the proportion of child stunting decreased from 49.3% in 2006 to 35.8% in 2016. The proportion of stunting was higher among larger families, children from the Dalit caste/ethnic group, households from the poorest wealth quintile, children residing in rural and mountain regions, and children from severely food insecure households (Table 2).
Table 2
Prevalence of stunting (<−2SD) among children aged 0–59 months
 
2006
2011
2016
%
N
%
N
%
N
Total (mean z score and SD)
49.3 (−1.93; 1.3)
5083
40.5 (−1.66; 1.4)
2485
35.8 (−1.29; 4.9)
2421
Household characteristics
Family size
 Less than 5
43.2
1247
38.9
693
29.3
727
 5 and above
51.0
3836
41.1
1792
38.7
1694
Headship of the households
 Male
48.7
4052
41.2
1828
36.2
1652
 Female
50.9
1031
38.7
657
35.0
769
Caste/ethnicity
 Dalit
56.5
788
47.0
440
38.7
342
 Muslim
56.6
286
31.0
147
37.2
164
Janajati
44.9
1608
40.4
794
32.2
661
 Other Terai caste
50.3
713
45.9
230
42.3
479
 Brahmin/chhetri
47.8
1444
36.8
734
34.6
629
 Other
48.5
244
41.0
140
28.3
146
Wealth quintile
 Poorest
61.2
1285
56.0
640
49.2
496
 Second poorest
54.4
1086
45.7
510
38.7
528
 Middle
50.6
1032
34.5
582
35.7
549
 Second richest
39.7
921
30.5
421
32.4
526
 Richest
30.5
759
25.8
332
16.5
322
Place of residence
 Urban
35.8
619
26.7
217
32.0
1280
 Rural
51.0
4464
41.8
2268
40.2
1141
Ecological Zone
 Mountain
61.2
425
52.9
196
46.8
170
 Hill
50.2
2100
42.1
991
32.3
876
Terai
46.2
2558
37.4
1298
36.7
1375
Household food security status
 Food secure
NA
 
33.2
1061
29.2
991
 Mildly food insecure
NA
 
41.2
305
35.9
557
 Moderately food insecure
NA
 
45.6
577
42.0
623
 Severely food insecure
NA
 
49.0
542
46.5
250
Access of drinking water
 Unimproved
51.2
1296
48.9
361
43.3
112
 Improved
48.4
3787
39.1
2124
35.5
2309
Access of toilet
 Unimproved
53.9
3659
45.0
1415
48.9
581
 Improved
36.9
1424
34.6
1070
31.7
1840
Maternal characteristics
Age of mother
 15–19
33.6
333
27.9
170
37.4
194
 20–24
45.4
1761
39.8
908
32.5
863
 25–29
49.2
1595
38.7
740
34.8
767
 30 and above
58.6
1394
46.7
667
41.6
597
Years of schooling of mother
 No schooling
57.3
3119
46.9
1256
45.3
910
 1–5 years schooling
45.7
858
41.7
442
36.4
449
 6–9 years schooling
31.9
788
32.1
464
31.7
563
 10 and above years of schooling
20.1
318
25.9
323
22.7
499
Number of living children
 Up to 1 children
34.0
1104
31.9
680
28.0
725
 2 children
46.0
1614
38.5
751
32.0
841
 3 and more children
58.3
2365
47.5
1054
46.2
855
Mother Employment
 No
42.7
1580
37.5
1116
31.7
1240
 Yes
52.0
3503
42.9
1369
40.2
1181
Mother BMI
 less than 18.5/underweight
47.2
3797
38.6
1935
33.6
1901
 18.5 and above
54.7
1284
47.1
469
44.5
452
Mother anemia
 No
48.1
3027
39.8
1476
35.4
1271
 Yes
50.9
2023
41.2
902
35.8
1074
Child characteristics
Age of child
 Less than 6 months
11.5
474
19.4
228
13.5
218
 6–11 months
23.65
484
15.9
247
18.9
251
 12–23 months
47.5
970
34.8
489
37.4
512
 25–49 months
59.2
3155
49.5
1521
41.6
1440
Sex of child
 Boys
48.6
2604
41.4
1273
36.0
1258
 Girls
49.7
2479
39.5
1212
35.7
1163
Birth order
 First
40.6
1378
34.2
781
31.4
791
 Second
44.9
1266
39.2
592
30.1
657
 Third and above
56.1
2439
45.6
1112
43.3
973
Size at the time of birth
 Average or larger
46.9
4109
38.4
2061
34.0
2031
 Below average
59.1
974
50.7
424
45.5
391
Anemia
 No
53.6
2284
41.4
1172
34.7
1022
 Yes
53.9
2191
45.2
1008
40.9
1137
Note: Only % for stunning are reported for each category. So, the total will not be 100% because for each category % of non-stunning are not included in this table, see more on Additional files 1, 2 and 3.
In all three surveys, the proportion of child stunting decreased as the number of years of mothers’ schooling increased. For example, the prevalence of child stunting was 45.3% among children whose mothers had no education, compared with 22.7% among children whose mothers had 10 or more years of schooling in 2016. Furthermore, the increases the number children living in a household also increase the likelihood of stunting. For instance, in 2016, the prevalence of stunting was 28% in single child households compared with 46.2% for the households with 3 or more children. The chances of stunting were also greater among children with anemic mothers. Child characteristics such as age, sex, birth order, birth size, and hemoglobin level were found to be determining factors for stunting in all three surveys. Stunting increased with increases in age and birth order. Likewise, small size at birth, female gender, and low level of blood hemoglobin (anemia) increased the likelihood of stunting in children (Table 2).

Factors associated with stunting

The adjusted odd ratios in Table 3 show that in all three surveys, wealth quintile, age of child, size of child at birth, and anemia were significant determinants of stunting in children. In the adjusted model, we adjusted for household, maternal, and child characteristics including family size, headship of the household, caste/ethnicity, wealth quintile, place of residence, household food security status, access to drinking water and a toilet, mother’s age, mother’s years of education, number of living children, mother’s employment status, mother’s BMI and anemia status, age and sex of child, birth order, size of child at time of birth, and child anemia status. In all three surveys, children in the richer and richest wealth quintile households were less likely to be stunted compared with children from the poorest quintile households. Likewise, in all three surveys, older children were more likely to be stunted than younger children (OR: 2.24 in 2006, 2.58 in 2011, 1.58 in 2016). Children who were below average size at time of birth were 1.6 times more likely to be stunted in all three surveys compared with children who were average size or larger at time of birth (OR: 1.64 in 2006, 1.55 in 2011, 1.60 in 2016). Similarly, children who suffered from anemia were more likely to be stunted in all three surveys (OR: 1.32 in 2006, 1.59 in 2011, 1.40 in 2016) (Table 3).
Table 3
Determinants of stunting in children aged 0–59 months
Background characteristics
Odd ratios of stunting (height for age < −2SD)
2006
2011
2016
Household characteristics
Unadjusted (OR, P/ CI)
Adjusted (OR, P/ CI)
Unadjusted (OR, P/CI)
Adjusted (OR, P/CI)
Unadjusted (OR, P/CI)
Adjusted (OR, P/CI)
 Family size
1.37** [1.16–1.62]
1.15 [0.95–1.38]
1.01 [0.86–1.40]
0.87 [0.62–1.21]
1.52** [1.22–1.90]
1.39* [1.06–1.83]
Headship of the households
 Male (R)
 Female
1.09 [0.91–1.31]
1.01 [0.82–1.24]
0.90 [0.71–1.14]
0.85 [0.64–1.14]
0.95 [0.77–1.17]
1.06 [0.84–1.35]
Caste/ethnicity
 Dalit(R)
 Muslim
1.00 [0.74–1.35]
1.21 [0.82–1.80]
0.50 [0.30–0.85]
0.55 [0.27–1.14]
0.94 [0.60–1.47]
1.04 [0.61–1.78]
Janajati
0.63 [0.48–0.83]
0.73 [0.53–0.99]
0.76 [0.56–1.04]
0.89 [0.61–1.29]
0.75 [0.53–1.08]
1.01 [0.69–1.47]
 Other Terai caste
0.78 [0.59–1.03]
0.96 [0.69–1.33]
0.95 [0.63–1.43]
1.56 [1.04–1.33]
1.16 [0.81–1.66]
1.18 [0.74–1.91]
 Brahmin/chhetri
0.70 [0.57–0.89]
0.94 [0.69–1.26]
0.65 [0.51–0.85]
0.80 [0.58–1.09]
0.84 [0.60–1.17]
1.08 [0.72–1.61]
 Other
0.72 [0.35–1.50]
0.80 [0.36–1.77]
0.78 [0.48–1.29]
0.96 [0.39–2.37]
0.63 [0.37–1.05]
0.60 [0.26–1.36]
Wealth quintile
 Poorest (R)
 Second poorest
0.76** [0.63–0.92]
0.87 [0.65–1.18]
0.66** [0.50–0.88]
0.58** [0.39–0.87]
0.65** [0.49–0.87]
0.60** [0.43–0.85]
 Middle
0.65** [0.51–0.82]
0.84 [0.63–1.13]
0.42** [0.30–0.57]
0.45** [0.29–0.68]
0.57** [0.42–0.77]
0.51** [0.36–0.73]
 Second richest
0.42** [0.32–0.54]
0.59** [0.42–0.83]
0.35** [0.25–0.48]
0.30** [0.17–0.53]
0.49** [0.37–0.66]
0.56** [0.37–0.85]
 Richest
0.28** [0.22–0.35]
0.58* [0.38–0.88]
0.27** [0.19–0.39]
0.26** [0.12–0.54]
0.20** [0.14–0.29]
0.28** [0.16–0.49]
Place of residence
 Urban (R)
 Rural
1.86** [1.51–2.30]
1.06 [0.83–1.35]
1.97** [1.52–2.56]
1.35 [0.94–1.92]
1.42** [1.16–1.77]
1.05 [0.82–1.34]
 Ecological belt
 Mountain (R)
 Hill
0.64** [0.51–0.81]
0.90 [0.70–1.15]
0.65** [0.49–0.85]
0.67* [0.49–0.91]
0.54** [0.37–0.79]
0.80 [0.54–1.18]
Terai
0.54** [0.43–0.69]
0.51** [0.37–0.72]
0.53** [0.40–0.71]
0.67 [0.43–1.03]
0.66* [0.46–0.94]
0.84 [0.53–1.33]
Household food security status
 Food secure (R)
 Mildly food insecure
NA
NA
1.40** [1.02–1.95]
0.86 [0.58–1.29]
1.36** [1.07–1.71]
0.98 [0.75–1.28]
 Moderately food insecure
NA
NA
1.68** [1.28–2.21]
1.07 [0.75–1.53]
1.76** [1.37–2.26]
1.10 [0.82–1.47]
 Severely food insecure
NA
NA
1.93** [1.39–2.67]
1.17 [0.77–1.77]
2.10** [1.43–3.12]
1.32 [0.86–2.01]
Access of drinking water
 Unimproved (R)
 Improved
0.90 [0.76–1.06]
1.19 [0.98–1.44]
0.67 [0.51–0.88]
0.96 [0.68–1.34]
0.72 [0.48–1.07]
0.82 [0.53–1.29]
Access of toilet
 Unimproved (R)
 Improved
0.50** [0.41–0.61]
0.83 [0.59–1.17]
0.65** [0.51–0.81]
1.27 [0.91–1.77]
0.49** [0.38–0.62]
0.64 ** [0.46–0.88]
Maternal characteristics
Age of mother
1.05* [1.03–1.06]
0.97 [0.95–0.99]
1.03* [1.01–1.05]
0.97 [0.94–1.01]
1.02* [1.00–1.03]
0.99 [0.96–1.02]
Years of schooling of mother
0.87** [0.85–0.88]
0.92** [0.89–0.95]
0.92** [0.89–0.94]
1.00 [0.65–1.05]
0.91** [0.89–0.93]
0.98 [0.95–1.01]
Number of living children
1.65** [1.51–1.79]
1.12 [0.96–1.32]
1.39** [1.23–1.58]
1.05 [0.86–1.28]
1.50** [1.33–1.70]
1.17 [0.95–1.44]
Employment
 No (R)
 Yes
1.45** [1.21–1.74]
0.98 [0.80–1.21]
1.25 [0.96–1.62]
0.83 [0.59–1.17]
1.44** [1.20–1.73]
1.27* [1.01–1.60]
Mother BMI
 less than 18.5/underweight (R)
 18.5 and above
1.35** [1.16–1.58]
1.19 [0.98–1.44]
1.42** [1.10–1.83]
1.30 [0.93–1.81]
1.59** [1.23–2.04]
1.23 [0.94–1.60]
Mother anemia
 No (R)
 Yes
1.12 [0.97–1.30]
1.24* [1.04–1.48]
1.06 [0.86–1.30]
0.95 [0.74–1.23]
1.01 [0.84–1.24]
0.90 [0.72–1.14]
Child characteristics
 Age of child
2.11** [1.94–2.29]
2.24** [1.96–2.56]
1.80** [1.59–2.03]
2.58** [2.14–3.11]
1.61** [1.44–1.80]
1.58** [1.32–1.90]
Sex of child
 Boys (R)
 Girls
1.05 [0.91–1.21]
1.00 [0.85–1.17]
0.92 [0.77–1.10]
0.88 [0.71–1.10]
0.98 [0.81–1.20]
0.95 [0.76–1.17]
Birth order
1.17*** [1.13–1.21]
1.11* [1.02–1.20]
1.00 [1.00–1.01]
1.14 [1.03–1.26]
1.15** [1.09–1.21]
0.99 [0.89–1.10]
Size at the time of birth
 Average or larger (R)
 Below average
1.64** [1.37–1.946]
1.64** [1.34–2.00]
1.67** [1.29–2.18]
1.55** [1.19–2.02]
1.64** [1.31–2.05]
1.60** [1.25–2.04]
Anemia
 No (R)
 Yes
1.01 [0.87–1.17]
1.32** [1.12–1.56]
1.17 [0.95–1.43]
1.59** [1.25–2.02]
1.30** [1.06–1.61]
1.40** [1.12–1.75]
* p < 0.05; ** p < 0.01, see more on Additional files 4, 5 and 6

Discussion

This paper outlines the prevalence of stunting and associated risk factors among children under five in Nepal. Study findings suggest that stunting in Nepal has decreased over the last decade (mean decline of − 1.92 in 2006 to − 1.29 in 2016). The Nepal government implemented the Multi-Sectoral Nutrition Plan (MSNP) in 2012 with the key objective of improving nutrition status among adolescent girls, pregnant and lactating women, and all children under 24 months. The MSNP is an evidence-based, cost-effective nutrition intervention that integrates both national and community priorities. The plan outlines the roles of key health, education, and agriculture sectors in implementing policies and strategies. Thus, decreases in stunting may be attributable to the implementation of the MSNP in Nepal [14, 15, 19, 20].
The study analyses identified significant determinants of stunting present across all three surveys; household wealth status, number of years of mother’s schooling, age of child, size of child at time of birth, and child anemia were all associated with stunting. Children from the poorest households were more likely to be stunted than children from middle income, richer, and richest households. This reflects findings from a systematic review conducted in sub-Saharan Africa by Akombi and colleagues [21, 22]. Likewise, a study based on the Bangladesh Demographic and Health Survey 2011 similarly found that wealth index was significantly associated with child stunting [21, 22]. The study findings also indicate that mothers with ten or more years of schooling were 37% less likely to have stunted children than mothers with no education. This reflects results from studies demonstrating less child stunting among mothers with more years of education [2328]. Reduced child stunting among more educated mothers might reflect better feeding and care practices among these mothers [29].
Findings indicate that children aged 24–59 months were at higher risk for stunting than children aged 0–23. This is consistent with findings from similar studies [3032], and may be explained by the protective effect of breastfeeding. While most children in Nepal are breastfed until 24 months, breastfeeding gradually declines with child age [33]. Children who had a low birth weight (less than 2.5 kg) were 1.5 times more likely to be stunted later in life than children of average or greater birth weight. The observed association between stunting and birth weight is consistent with other studies conducted in developing countries [3438]. This link could be explained by the greater likelihood of low birth weight children to contract infections like diarrhea and acute respiratory infection. These infections may make the child more susceptible to later complications associated with stunting.
Child anemia was another determinant for stunting; results suggest that anemic children were 1.3 to 1.6 times more likely to be stunted than non-anemic children. Other studies have similarly found childhood anemia to be a significant determinant for stunting [3942]. The link between anemia and stunting may be caused by anemia’s role in limiting children’s physical growth [43, 44] and iron supplementation could be used to reduce childhood stunting [45].
The findings of this study have policy implications as they provide a clear depiction of the trends and determinants of stunting from 3 nationally representative surveys over a 15 year period. Policy makers and planners can use evidence from this study to formulate feasible and culturally appropriate interventions to reduce stunting in Nepal. Though this paper explores determinants of stunting from the last 15 years of data, it is not free from limitations. The analyses are based on cross-sectional survey data; thus, we were unable to assess the causal relationship between stunting and socio-economic confounders.

Conclusion

The prevalence of stunting in Nepal remains among the highest of developing countries. This study highlights risk factors for stunting, including household wealth quintile, number of years of mother’s schooling, child age, child size at birth, and child anemia. In addition to the policies and programs aimed at improving maternal and child nutrition, equal focus should be given to improving mothers’ education. Findings also suggest the importance of addressing income inequality when implementing nutrition interventions.

Acknowledgements

We would like to thank Emily Satinsky from the University of Maryland College Park, Global Mental Health and Addiction Program, USA for reviewing and revising the final manuscript.
The study involved secondary analysis of publicly available data. Thus, independent ethical approval was not needed. However, the first author received permission from dhsprogram.​com to use the data for analysis.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Metadaten
Titel
Determinants of stunting among children aged 0–59 months in Nepal: findings from Nepal Demographic and health Survey, 2006, 2011, and 2016
verfasst von
Ramesh P. Adhikari
Manisha Laxmi Shrestha
Ajay Acharya
Nawaraj Upadhaya
Publikationsdatum
01.12.2019
Verlag
BioMed Central
Erschienen in
BMC Nutrition / Ausgabe 1/2019
Elektronische ISSN: 2055-0928
DOI
https://doi.org/10.1186/s40795-019-0300-0

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