Literature DB >> 27122480

Factors Associated with Stunting among Pre-school Children in Southern Highlands of Tanzania.

Chiara Altare1, Tefera Darge Delbiso2, George Mutembei Mutwiri3, Regine Kopplow4, Debarati Guha-Sapir2.   

Abstract

BACKGROUND: Stunting is a major public health problem in Africa and is associated with poor child survival and development. We investigate factors associated to child stunting in three Tanzanian regions.
METHODS: A cross-sectional two-stage cluster sampling survey was conducted among children aged 6-59 months. The sample included 1360 children aged 6-23 months and 1904 children aged 24-59 months. Descriptive statistics and binary and multivariate logistic regression analyses were used.
RESULTS: Our main results are: in the younger group, stunting was associated with male sex (adjusted odds ratio [AOR]: 2.17; confidence interval [CI]: 1.52-3.09), maternal absence (AOR: 1.93; CI: 1.21-3.07) and household diet diversity (AOR: 0.61; CI: 0.41-0.92). Among older children, stunting was associated with male sex (AOR: 1.28; CI: 1.00-1.64), age of 4 and 5 (AOR: 0.71; CI: 0.54-0.95; AOR: 0.60; CI: 0.44-0.83), access to improved water source (AOR: 0.70; CI: 0.52-0.93) and to a functioning water station (AOR: 0.63; CI: 0.40-0.98) and mother breastfeeding (AOR: 1.97; CI: 1.18-3.29).
CONCLUSIONS: Interventions that increase household wealth and improve water and sanitation conditions should be implemented to reduce stunting. Family planning activities and programmes supporting mothers during pregnancy and lactation can positively affect both newborns and older siblings.
© The Author [2016]. Published by Oxford University Press.

Entities:  

Keywords:  Tanzania.; child care; diet diversity; growth; maternal support; stunting

Mesh:

Year:  2016        PMID: 27122480      PMCID: PMC5040832          DOI: 10.1093/tropej/fmw024

Source DB:  PubMed          Journal:  J Trop Pediatr        ISSN: 0142-6338            Impact factor:   1.165


INTRODUCTION

Linear growth failure is a major public health problem in Africa, where more than one-third of the children under 5 are too short for their age [1, 2]. Extensive research has shown the health, economic and intergenerational consequences of stunting: higher risk of dying [3]; poorer psychomotor and mental development and school achievement [4, 5]; loss of human capital and economic productivity in adulthood [6, 7]; in creased risk of chronic diseases [8]; and reduced maternal reproductive outcomes [9]. Stunting often begins in utero, as maternal nutrition is the first determinant of the child nutritional status [1, 10], and continues generally during the first two years after birth [11, 12]. Although the pathogenesis of stunting is not yet well-understood, studies have shown that inadequate nutrient intake, infections, unsafe water and poor child care are among its main determinants [13, 14]. Other factors in developing countries include maternal education, socioeconomic status, residence and poor access to health services [15-18]. There is increasing international recognition that efforts to prevent stunting can improve short- and long-term outcomes, at individual, community and country levels [7, 19]. This is reflected in the number of governments joining the Scaling-Up Nutrition (SUN) movement (http://scalingupnutrition.org), and in the inclusion of nutrition-related goals in the World Health Assembly targets, Millennium Development Goals and Sustainable Development Goals. In Tanzania, a SUN member, 35% of the children under 5 were stunted in 2014 [20], down from 42% in 2010 [21]. In central and southern highlands zones, however, the prevalence of chronic malnutrition reaches 50%. Here, the Government of Tanzania, UNICEF and Concern Worldwide, an international non-governmental organization, are implementing the ‘Bringing nutrition actions to scale in Iringa, Njombe and Mbeya regions of Tanzania’ project. It aims to reduce the prevalence of stunting by 10 percentage points over 5 years, through interventions targeting women and children, as well as strengthening capacities of local authorities. At the beginning of the project, baseline information was collected on infant and young child feeding (IYCF) practices, child and maternal nutritional and health status and household socioeconomic situation. By analysing these baseline survey data, this paper investigates factors associated with stunting in regions with high stunting prevalence. Differently from the majority of studies from Tanzania, our analysis does not focus on HIV subjects, but on otherwise healthy children without confirmed co-morbidities.

METHODS

Study area and population

The study was conducted in the regions of Iringa, Njombe and Mbeya, where 4.4 million people live, 72% of whom live in rural areas [22]. Although these regions receive the highest rainfall and are Tanzania’s bread baskets, stunting prevalence was 51.3%, 51.5% and 36.0%, respectively, in 2014 [20]. These are the second and the third highest values in Tanzania, well above the national prevalence (34.7%). The study population includes children under 5 in rural and urban households in the three regions.

Study and sampling design

One cross-sectional survey was conducted in each region in November 2013, using a two-stage cluster sampling design. Sixty-three clusters were selected in each region by probability proportional to the size using ENA delta software [23]. Twenty households were chosen in each cluster by random sampling, using a random number table. A complete list of households with children under 5 in each cluster was prepared before the survey date. Households were visited for verification if necessary. Sample size was calculated to detect a 10 percentage point reduction in stunting among children 24–47 months by the end of the project in each region. Power was set at 80%, level of confidence at 95% (one-tailed test), design effect at 1.5 and non-response at 10%. A sample of 501 children in the age group 24–47 months per region was required. A total of 1253 households with children under 5 were targeted in each region to achieve the required sample size.

Measurements

Data were collected using a standardized questionnaire on a digital data gathering (DDG) device, via face-to-face interview with the main caregiver of the child. The following data were collected for anthropometric measurements of all children under 5: sex, age, weight, height and presence of bilateral pitting oedema. Length was taken for children under 24 months in horizontal position; height was taken standing for older children; both to the nearest 0.1 cm with a standard 130-cm height/length board. Weight was measured with an electronic scale to the nearest 0.1 kg. Stunting was defined as height-for-age z-score (HAZ) below −2 SD from the median height of the WHO reference population. Additional data were collected to reflect selected immediate, underlying and basic causes of undernutrition as illustrated in the UNICEF Conceptual Framework [24]. These were regrouped in child characteristics: IYCF practices, occurrence of diseases, supplementation and treatments received; maternal characteristic: nutritional status, pregnancy and breastfeeding status, workload, habits and supplementation during pregnancy and nutritional information received; and household characteristics: water source, sanitation facilities, use of iodized salt, household dietary diversity and farm diversity. When more than one child aged 6–23 months was present in a sampled household, only data from the youngest child were collected. Definition and measurements of variables used in the analysis are presented in Table 1.
Table 1.

Definitions and measurement of variables used in the analysis

Variable nameDefinition and measurementValues
Child level
 Minimum diet diversity (MDD) [43]Proportion of children aged 6 to 23 months eating from four or more food groups.0 if < 4 groups
1 if ≥ 4 groups
 Minimum meal frequency (MMF) [25]Proportion of children receiving solid, semi-solid or soft food (but also including milk feed for non-breastfed children), the minimum number of times according to their age and breastfeeding status. Minimum is defined as:

two times for breastfed infants aged 6 to 8 months;

three times for breastfed children aged 9 to 23 months;

four times for non-breastfed children aged 6 to 23 months.

0 if MMF not reached;
1 if MMF reached
 Minimum adequate diet (MAD) [25]Proportion of children aged 6 to 23 months who achieve both MMF and MDD. It is calculated separately for breastfed and non-breastfed children. For breastfed children, it corresponds to the children who reach both MDD and MMF. For non-breastfed children, MAD is based on a six-food-group MDD and requires also two separate milk feeds.0 if MAD not reached;
1 if MAD reached
 Occurrence of diseaseThe occurrence of diarrhoea, fever or cough in the two weeks before the survey. Based on caregiver’s recall (children 6 to 23 months of age).0 if no disease episode; 1 if at least one episode of any of the three conditions
 Child vitamin A supplementationProportion of children 6 to 23 months of age who received a Vitamin A dose (capsule) in the 6 months previous to the survey. Based on caregiver’s recall.0 if vitamin A dose not received;
1 if vitamin A dose received
 Child deworming treatmentProportion of children aged 6 to 23 months who received deworming treatment in the 6 months previous to the survey. Based on caregiver’s recall.0 if deworming treatment not received;
1 if deworming treatment received
Maternal level
 Maternal malnutritionUndernutrition defined as mid-upper arm circumference (MUAC) below 210 mm for non PLW; below 230 mm for PLW [26].0 not malnourished;
1 malnourished
 Hand-washing knowledgeDefined as good if three or more occasions when it is important to wash hands were given; satisfactory if two occasions were given; poor if one or none of the options were given.2 good
1 satisfactory
0 poor
 Health-seeking behaviourProportion of caregivers who sought medical care in case of illness (diarrhoea, fever or cough) of the child.0 medical care was not sought;
1 medical care was sought
 Workload during pregnancyPerceived workload during pregnancy compared with the time before the pregnancy. Possible answers: ‘less’, ‘more’ or ‘the same.Less
More
The same
 Food habits during pregnancyChanges in the amount and types of food eaten during pregnancy compared with the time before pregnancy. Based on caregiver’s recall. Possible answers: ‘eaten less’/‘fewer types’; ‘eaten the same amount’/‘the same types’; ‘eaten more’/‘more food types’.Less amount/fewer types;
Same amount/same number of types;
Bigger amount/more types.
 Vitamin A supplementation during pregnancyProportion of mothers who received vitamin A dose (capsule) in the first two months after delivery0 not received;
1 received
 Iron supplementation during pregnancyProportion of mothers who received any iron table or iron syrup during their last pregnancy0 not received;
1 received
 Advice on child and maternal nutritionProportion of caregivers who ever received information on maternal and child nutrition by health workers (hospital or health facility or feeding centre staff, midwives or village health workers), or traditional/religious leaders, or other relatives and friends. Based on the caregiver’s recall.0 never received;
1 received
 Decision-making to feedWho in the family makes the decision regarding what to feed the children.1 mother;
2 others
Household level
 Household dietary diversity score [27]Number of food groups consumed by the household’s member in the 24 h before the survey. Categorization defined by the authors, as no standard thresholds exist.0–4
5–8
9–12
 Farm production diversity scoreNumber of food groups produced by the household in the past 3 months. Categorization defined by the authors, as no standard thresholds exist.0 (no production)
1–2
3–5
6–12
 Source of drinking waterDefined as improved if water coming from piped water, protected well, protected spring and bottled water. Otherwise = unimproved.0 unimproved;
1 improved
 Hand-washing stationDefined as functional if a station was present, or water and soap or ash were available; non-functional if otherwise.0 non-functional;
1 functional
 Use of iodized saltWhether the household used iodized salt or not.0 non-iodized salt;
1 iodized salt
Definitions and measurement of variables used in the analysis two times for breastfed infants aged 6 to 8 months; three times for breastfed children aged 9 to 23 months; four times for non-breastfed children aged 6 to 23 months.

Quality control

The SMART methodology was used to ensure standardized procedures and tools [28]. After a 6-day training, data collectors had to pass a standardization test to assess accuracy and precision of their anthropometric measurements. The questionnaire was piloted and finalized. Team leaders ensured data quality during data collection. Checks, skip functions and acceptable ranges were pre-established in the DDG devices to reduce mistakes. Implausible anthropometric measurements were defined as  ±6 SD, as per WHO criteria [29].

Statistical analysis

The analysis of factors associated with stunting was divided by age groups: 6–23 and 24–59 months, and conducted for the entire sample and broken down by region. Baseline sociodemographic and clinical characteristics of the sample were described with simple frequency distribution. Crude associations between stunting and sociodemographic and clinical variables were investigated using Pearson’s chi-square test. A multivariate logistic regression model was constructed to identify factors associated with stunting. Odds ratios (OR), 95% confidence intervals (CI) and p-values were obtained. P-values  <0.05 were considered significant. Sampling weights were applied to ensure the representativeness of the sample at the regional level. The analysis was conducted in STATA IC/12.1 for Windows and SPSS 20.0. Anthropometric indicators were calculated with ENA software.

Ethical considerations

Concern Worldwide routinely conducts nutrition surveys within its programmes, which are not subject to research ethical scrutiny. The organization subscribes to the ethical principles outlined in the Humanitarian Charter [30]. Furthermore, the project protocol and questionnaire were reviewed and approved by the Government of Tanzania and UNICEF. Oral informed consent was obtained by the interviewees. Consent to conduct anthropometric measurement was obtained from a parent or guardian in the local language.

RESULTS

Data were collected on a total of 3280 children aged 6–59 months. The region or district was missing in 16 records that were excluded, leading to a sample of 3264 children. Descriptive statistics are presented in Table 2. We further excluded 17 records from the inferential analysis due to implausible anthropometric measurements. The final sample includes 3247 children aged 6–59 months, of which 1360 are in the age group of 6–23 months.
Table 2.

Distribution of children aged 6–23 and 24–59 months by demographic, maternal and household characteristics, Iringa, Njombe and Mbeya regions, Tanzania, 2013

Variables6–23 months
24–59 months
n% or * Mean (SD)n% or * Mean (SD)
Nutritional status
 Stunting135242.2189545.7
 Height for age−1.79 (1.31)−1.99 (1.21)
Child’s age (in months)136014.2 (5.2)*190438.4 (10.3)*
 6–1134.5
 12–2365.5
 24–3543.2
 36–4732.4
 48–5924.4
Child’s sex13601904
 Female47.650.3
 Male52.449.7
Child living with1338
 Both parents83.1
 Mother only14.4
 Other guardians2.5
Minimum diet diversity (MAD)1360
 No84.8
 Yes15.2
Minimum meal frequency (MMF)1336
 No73.2
 Yes26.8
Minimum adequate diet (MAD)1337
 No99.2
 Yes0.8
Child’s consumption of animal source food1338
 At least one food32.1
 No67.9
Child’s consumption of vitamin-A-rich food1337
 Yes13.8
 No86.2
Child’s consumption of pulse/legumes/nuts1337
 Yes37.2
 No62.8
Snack between the meals1330
 No snack80.4
 One snack12.0
 Two snacks7.6
Child morbidity1360
 No illness55.7
 One illness23.4
 Two or three illnesses20.9
Health care-seeking behaviour in case of illness550
 Care sought71.6
 Care not sought28.4
Child received deworming treatment1281
 Yes51.1
 No48.9
Child received vitamin A supplementation1285
 Yes80.8
 No19.2
Maternal MUAC (in cm)130927.8 (3.3)*169428.1 (3.4)*
 Malnourished2.10.9
 Non-malnourished97.999.1
Mother currently pregnant13481856
 Yes2.910.2
 No97.189.8
Mother currently breastfeeding13601904
 Yes74.092.3
 No24.07.7
Birth in the past 5 years13571902
 1 child77.385.2
 2+ children22.714.8
Maternal hand-washing knowledge13571902
 Poor16.217.8
 Satisfactory44.151.9
 Good39.730.3
Hours the mother is away from home13601904
 No46.442.6
 1–3 h21.220.5
 4–7 h21.822.4
 8–24 h10.514.6
Husband support during pregnancy1019
 Yes73.1
 No26.9
Amount of food during pregnancy1009
 Less45.1
 The same39.1
 More15.8
Types of food during pregnancy1011
 Fewer37.2
 The same45.2
 More17.6
Mother received iron during pregnancy1004
 Yes62.0
 No38.0
Mother received vitamin A dose after delivery990
 Yes41.8
 No58.2
Advice on child and maternal nutrition1054
 Yes41.9
 No58.1
Decision-making to feed1063
 Mother75.0
 Others25.0
Source of drinking water13571902
 Improved68.470.7
 Not improved31.629.3
Hand-washing station13601904
 Functional5.67.9
 No or not functional94.492.1
Household dietary diversity score13535 (4–6)*,218945 (4–6)*,a
 1–440.736.7
 5–856.559.5
 9–122.83.8
Household farm production diversity score13493 (1–4)*,218863 (2–5)*,a
 No13.711.6
 1–230.324.1
 3–540.842.3
 6–1215.122
Home/kitchen garden13601904
 Yes26.626.6
 No73.473.4
Frequency of buying fresh food13571902
 Daily44.647.9
 2–3 times/week34.730.7
 Once a week10.611.1
 Less often10.110.2
Production of animal source food13601904
 At least one food60.565.6
 No39.534.4
Consumption of animal source food13601904
 At least one food51.048.8
 No49.051.2
Production of vitamin A-rich food13601904
 At least one food38.847.2
 No61.252.8
Consumption of vitamin A-rich food13601904
 At least one food80.283.5
 No19.816.5
Use of iodized salt13321871
 Yes79.379.2
 No20.720.8
Place of residence13601904
 Urban18.720.5
 Rural81.379.5
Region13601904
 Mbeya63.867.4
 Njombe14.813.4
 Iringa21.419.2

aMedian and interquartile range.

Distribution of children aged 6–23 and 24–59 months by demographic, maternal and household characteristics, Iringa, Njombe and Mbeya regions, Tanzania, 2013 aMedian and interquartile range. Mean HAZ was −1.79 among 6–23-month-old children and −1.99 in the older group. Prevalence of stunting was 42.2%, and 45.7%, respectively. Table 3 presents results from the bivariate and multivariate logistic regression for 6–23-month-old children, and Table 4 for the age group 24–59 months. In both groups and after adjusting for confounding factors, children in Njombe and Iringa have higher odds of being stunted than children in Mbeya. Across regions, children in their second and third year of life have higher odds to be stunted than younger or older children. Male children have higher odds than female.
Table 3.

Crude and adjusted odds ratio (95% CI) for stunting among children aged 6 to 23 months, overall and disaggregated by region, according to child, maternal and household characteristics, southern highlands, Tanzania, 2013 (only significant results are shown)

VariablesOverall (N = 929)
Mbeya (N = 374)
Njombe (N = 348)
Iringa (N = 357)
Crude ORAORCrude ORAORCrude ORAORCrude ORAOR
Male sex2.15***2.17***2.35***2.90***1.67***2.13***2.04***2.45***
(1.65–2.81)(1.52–3.09)(1.57–3.50)(1.76–4.80)(1.15–2.42)(1.27–3.60)(1.41–2.95)(1.44–4.16)
Child age
 6–1111111111
 12–242.70***3.91***2.730***4.63***2.92***3.04***2.63***4.74***
(2.02–3.62)(2.49–6.12)(1.751–4.256)(2.47–8.67)(1.97–4.34)(1.68–5.50)(1.75–3.95)(2.40–9.37)
Receiving deworming treatment0.64**0.53**1.89***
(0.41–0.99)(0.30–0.93)(1.28–2.79)
Mother hours away from home
 0 h1111
 1–3 h0.851.000.790.96
(0.59–1.21)(0.64–1.59)(0.48–1.32)(0.53–1.76)
 4–7 h1.64***1.93***1.90**2.25**
(1.17–2.30)(1.21–3.07)(1.14–3.14)(1.20–4.19)
 8–24 h0.831.070.791.00
(0.53–1.29)(0.58–1.98)(0.39–1.60)(0.42–2.39)
Mother currently pregnant2.98**4.26**6.64**
(1.05–8.51)(1.08–16.87)(1.23–35.66)
Food types during last pregnancy
 Fewer1
 The same1.79**
(1.13–2.84)
 More1.10
(0.64–1.88)
Receiving husband support during pregnancy0.61**
(0.38–0.99)
Births in the past 5 years
 One1
 Two or more2.02**
(1.11–3.66)
Household dietary diversity score
 0–411111
 5–80.66***0.61**0.66**0.630.61***
(0.50–0.86)(0.41–0.92)(0.44–0.98)(0.36–1.09)(0.42–0.89)
 9–120.25***0.15***0.20**0.14**0.10**
(0.09–0.66)(0.04–0.53)(0.04–0.95)(0.02–0.96)(0.01–0.82)
Owning a home garden0.58**
(0.38–0.89)
Production of animal-based food0.67**0.50**
(0.46–0.98)(0.26–0.95)
Production of vitamin A-rich fruits and vegetables1.43***1.71**1.59**
(1.09–1.87)(1.06–2.76)(1.09–2.32)
Frequency of buying fresh food
 Daily11
 2–3 times per week1.202.19**
(0.78–1.85)(1.14–4.23)
 Once a week1.151.47
(0.66–2.00)(0.53–4.05)
 Less often2.28**1.11
(1.19–4.39)(0.41–2.99)
Using iodized salt0.72**0.54***0.41***
(0.53–0.97)(0.34–0.84)(0.21–0.79)
Knowledge of hand-washing practices
 Poor1
 Satisfactory3.10***
(1.33–7.24)
 Good1.13
(0.47–2.71)
Improved water source0.48***
(0.30–0.76)
Urban residence0.68**0.50***
(0.49–0.95)(0.30–0.81)
Region
 Mbeya11
 Njombe1.34**1.77**
(1.03–1.76)(1.11–2.80)
 Iringa1.191.59**
(0.91–1.55)(1.06–2.40)

Level of significance:. ***p  <  0.01,**p  <  0.05; OR =  Odds ratio.

Table 4.

Crude and adjusted odds ratio (95% CI) for stunting among children aged 24 to 59 months, overall and disaggregated by region, according to child, maternal and household characteristics, southern highlands, Tanzania, 2013 (only significant results are shown)

VariablesOverall (N = 1618)
Mbeya (N = 561)
Njombe (N = 517)
Iringa (N = 535)
Crude ORAORCrude ORAORCrude ORAORCrude ORAOR
Child age
 24–35111111
 36-470.73**0.71**0.70**0.69*0.68**0.68*
(0.57–0.94)(0.54–0.95)(0.49–1.00)(0.45–1.05)(0.47–0.99)(0.44–1.06)
 48-590.59***0.60***0.52***0.53***0.64**0.61**
(0.44–0.78)(0.44–0.83)(0.35–0.77)(0.33–0.85)(0.43–0.97)(0.37–0.98)
Male sex1.30**1.28**
(1.04–1.61)(1.00–1.64)
Mother currently breastfeeding1.79***1.97***2.82**
(1.20–2.68)(1.18–3.29)(1.23–6.47)
Mother currently pregnant2.28**2.81**
(1.05–4.93)(1.20–6.60)
Mother hours away from home
 0 h1111
 1–3 h0.58**0.981.201.32
(0.36–0.94)(0.63–1.53)(0.72–2.00)(0.86–2.01)
 4–7 h0.811.64**1.66**1.63**
(0.50–1.30)(1.07–2.52)(1.01–2.73)(1.09–2.44)
 8–24 h0.971.53*1.95**1.31
(0.55–1.71)(0.97–2.39)(1.15–3.31)(0.76–2.27)
Improved water source0.70**0.58***1.56**0.63**
(0.52–0.93)(0.39–0.87)(1.06–2.29)(0.40–0.99)
Functional hand-washing station0.63**0.43**
(0.40–0.98)(0.18–0.99)
Knowledge of hand-washing practices
 Poor11
 Satisfactory0.810.80
(0.51–1.28)(0.47–1.36)
 Good0.55**0.47**
(0.34–0.90)(0.26–0.85)
Household dietary diversity score
 0–411
 5–80.66***0.65**
(0.53–0.83)(0.47–0.91)
 9–120.961.25
(0.52–1.80)(0.59–2.66)
Household consuming animal-based food0.67***0.63***0.63**
(0.54–0.84)(0.46–0.86)(0.42–0.94)
Farm production diversity score
 No production11
 1–2 food groups0.901.79**
(0.67–1.20)(1.01–3.14)
 3-5 food groups1.56**2.33***
(1.04–2.33)(1.38–3.93)
 6–12 food groups1.343.16***
(0.92–1.94)(1.72–5.78)
Household production of animal-based food0.72**1.45**
(0.52–0.99)(1.04–2.02)
Production of vitamin A-rich fruits and vegetables2.25***
(1.63–3.10)
Owning a home garden1.99***
(1.44–2.75)
Frequency of buying fresh food
 Daily1
 2–3 times per week1.46**
(1.00–2.11)
 Once a week1.64*
(0.99–2.72)
 Less often1.30
(0.80–2.13)
Urban residence1.74***2.02***0.61**0.47***
(1.18 – 2.57)(1.21 – 3.39)(0.39 – 0.95)(0.31 – 0.72)
Region
 Mbeya
 Njombe1.83***1.77***
(1.47–2.29)(1.33–2.35)
 Iringa1.27**1.37**
(1.02–1.59)(1.04–1.79)

Note. OR =  Odds ratio.

Level of significance:

***p  <  0.01,

**p  <  0.05.

Crude and adjusted odds ratio (95% CI) for stunting among children aged 6 to 23 months, overall and disaggregated by region, according to child, maternal and household characteristics, southern highlands, Tanzania, 2013 (only significant results are shown) Level of significance:. ***p  <  0.01,**p  <  0.05; OR =  Odds ratio. Crude and adjusted odds ratio (95% CI) for stunting among children aged 24 to 59 months, overall and disaggregated by region, according to child, maternal and household characteristics, southern highlands, Tanzania, 2013 (only significant results are shown) Note. OR =  Odds ratio. Level of significance: ***p  <  0.01, **p  <  0.05. In the entire sample, children aged 6–23 months had lower odds of stunting if they received deworming treatment or came from a household consuming five or more food groups or that has a home garden. In Njombe, children from households producing animal-based food have lower odds of stunting. In Iringa, using iodized salt was also found to be protective. Risk factors in the same age group are maternal absence for 4–7 h and production of vitamin-A-rich food. In Njombe and Iringa, children whose mother is currently pregnant have higher odds of stunting. In Iringa, two or more births in the past 5 years, reduced frequency of buying fresh vegetables and improved knowledge of hand-washing practices were other risk factors. Overall, children aged 24–59 months from households with access to improved water source or with a functioning water station had lower odds of stunting. Knowledge of hand-washing practices protects against stunting in Iringa, while in Mbeya, children from households consuming animal-based food have lower odds. In the entire sample, children whose mother was currently breastfeeding have higher odds of stunting. Short maternal absence (1–3 h) was a protective factor in Mbeya, while longer absence (4–7 h) was a risk factor in Njombe. Urban residence was a protective factor in Njombe and a risk factor in Mbeya.

DISCUSSION

This study investigates factors associated to the nutritional status of pre-school children in Tanzanian southern highlands. The likelihood of stunting is higher among children in the regions of Njombe and Iringa, compared with Mbeya. As the regions have similar socioeconomic profiles, further effort is needed to investigate possible explanatory factors to better define interventions. For example, diet habits, cultural practices and HIV prevalence could play a role. Children under 2 years of age consume more dairy products in Mbeya than in the other regions (results not shown), which is associated with improved linear growth [31]. The higher HIV/AIDS prevalence in Njombe (15%) compared with Iringa and Mbeya (9%) [32] can also have implications on the households’ economic status and indirectly on the child nutritional status [33]: reduced labour productivity, increased expenditure in illness and funerals and reduced food security. Njombe registers, for example, the lowest mean household dietary diversity score (HDDS), followed by Iringa and Mbeya (difference among regions is significant). Within Mbeya though, urban children seem to be more disadvantaged than their rural counterparts, possibly due to the fast urbanization that was not followed by an equitable development of and access to health, sanitation and educational services [34]. With regard to child characteristics, our analysis confirms that children in their second and third year of life are more likely to be stunted than both younger and older children. This is well-recognized in the literature. Studies have shown that children accumulate growth delay during the first 2 years of life, with stunting peaking around 2 and 3 years, after which they stabilize [12, 35]. Furthermore, boys are at higher risk than girls, which also confirms results from sub-Saharan African and Asian countries [36]. The nutritional status of a child is directly related to maternal presence and her reproductive status. Maternal time allocation affects both the child nutritional status (through the time spent caring for the child) and income generation (through labour force) [37]. The net effect may vary by household and by child age. Our study shows that small children are particularly affected by maternal absence, while the results are mixed among older children. Furthermore, in Njombe and Iringa, children of pregnant women and of women with recent short birth intervals are more likely to be stunted. Among the older children, those whose mother is breastfeeding have higher odds. These results point in the same direction: older children may suffer from the presence of younger siblings. Programmes supporting mothers during pregnancy and lactation can have positive effects not only on the newborn, but also on older siblings. Cost–benefit studies of such interventions should also take this into account. Various activities could contribute towards reducing the workload on women: conservation agriculture, shortening distance to drinking water sources and engaging with other family members. Reproductive health programmes involving men and boys represent an important channel to emphasize men’s shared responsibility in pregnancy and childcare [38]. A better understanding of cultural norms defining women’s and men’s reproductive role in the Tanzanian southern highlands is necessary to design successful programmes. Finally, our study supports the evidence on promoting child spacing and family planning, which can reduce maternal burden and has been shown to contribute to a reduction of stunting [39]. It is widely accepted that economic welfare boosts nutritional status. Studies from resource-limited settings show that children from families with greater income and resources tend to have better diets, improved nutritional status and an overall growth-conducive environment [16, 40]. Our study contributes to this evidence by showing that higher HDDS is associated with lower odds for stunting among 6–23-month-old children. The number of food groups consumed in a household is commonly used as a proxy for the socioeconomic level, as it reflects the economic access to a variety of foods [27]. The interpretation of the relation between HDDS and stunting is complicated by the fact that richer families usually have better access to health care and improved environmental health, therefore pointing to a broader relation between poverty and stunting. Cultural food practices may have a strong mediating influence on a child nutrition status regardless of the family economic conditions. Further operational research to unravel the pathways should be undertaken. Access to improved water source and to a functioning hand-washing station protects against stunting, particularly among older children. These two public health interventions are likely to reduce the transmission of diarrhoeal diseases and the risk of tropical enteropathy [41], which are both associated with reduced linear growth. As 43% of the Tanzania households still do not have access to improved water source [21], strengthening strategies to increase the provision of water and sanitation interventions is crucial for the health of preschool children. Surprisingly, the production of vitamin-A-rich food was found to increase the odds of stunting, instead of reducing it. It should be investigated further whether producing vitamin-A-rich food substitutes the production (and consumption) of animal-based food, which may have a greater impact on child growth. None of the IYCF indicators was associated with linear growth, despite evidence from multi-country studies that indicate that diverse [42, 43] and adequate diet, as well as solid food consumption [44], reduce the risk of stunting. In the same studies, no association is found between meal frequency and linear growth, as in our analysis. Very few children (<1%) in our study met the definition of adequate diet, unlike the National Nutrition Survey, where 7.3%, 5.3% and 23.9% of the children in Iringa, Mbeya and Njombe, respectively, received minimum adequate diet (MAD). The results are not comparable unfortunately, as the calculation of MAD in the National Nutrition Survey did not consider milk feeds for non-breastfed children as recommended by the WHO. The present study has some limitations. First, the cross-sectional design does not allow to investigate causation, but only association. Second, information on maternal education was not collected, despite the importance recognized to it in the literature. The SMART questionnaire should include it in the future. Third, it was not possible to investigate the extent to which HIV/AIDS influences stunting in this population. Given the complexity and sensitivity around HIV status, data on HIV prevalence were not collected. In conclusion, our analysis confirms that stunting remains a public health problem in the southern highlands region in Tanzania. Interventions aiming to improve household wealth and sanitation conditions to reduce the high level of stunting should be put in place. Furthermore, family planning activities as well as supporting programmes for mothers during pregnancy and lactation can have positive effects not only on the newborn, but also on older siblings.
  29 in total

Review 1.  Maternal and child undernutrition and overweight in low-income and middle-income countries.

Authors:  Robert E Black; Cesar G Victora; Susan P Walker; Zulfiqar A Bhutta; Parul Christian; Mercedes de Onis; Majid Ezzati; Sally Grantham-McGregor; Joanne Katz; Reynaldo Martorell; Ricardo Uauy
Journal:  Lancet       Date:  2013-06-06       Impact factor: 79.321

2.  Feeding practices and factors contributing to wasting, stunting, and iron-deficiency anaemia among 3-23-month old children in Kilosa district, rural Tanzania.

Authors:  Peter S Mamiro; Patrick Kolsteren; Dominique Roberfroid; Simon Tatala; Ann S Opsomer; John H Van Camp
Journal:  J Health Popul Nutr       Date:  2005-09       Impact factor: 2.000

3.  World Health Organization (WHO) infant and young child feeding indicators: associations with growth measures in 14 low-income countries.

Authors:  Bernadette P Marriott; Alan White; Louise Hadden; Jayne C Davies; John C Wallingford
Journal:  Matern Child Nutr       Date:  2011-12-16       Impact factor: 3.092

4.  Stunting and wasting are associated with poorer psychomotor and mental development in HIV-exposed Tanzanian infants.

Authors:  Christine M McDonald; Karim P Manji; Roland Kupka; David C Bellinger; Donna Spiegelman; Rodrick Kisenge; Gernard Msamanga; Wafaie W Fawzi; Christopher P Duggan
Journal:  J Nutr       Date:  2012-12-19       Impact factor: 4.798

5.  The effect of multiple anthropometric deficits on child mortality: meta-analysis of individual data in 10 prospective studies from developing countries.

Authors:  Christine M McDonald; Ibironke Olofin; Seth Flaxman; Wafaie W Fawzi; Donna Spiegelman; Laura E Caulfield; Robert E Black; Majid Ezzati; Goodarz Danaei
Journal:  Am J Clin Nutr       Date:  2013-02-20       Impact factor: 7.045

6.  Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys.

Authors:  Mary Arimond; Marie T Ruel
Journal:  J Nutr       Date:  2004-10       Impact factor: 4.798

7.  The contribution of preterm birth and intrauterine growth restriction to childhood undernutrition in Tanzania.

Authors:  Ayesha Sania; Donna Spiegelman; Janet Rich-Edwards; Ellen Hertzmark; Ramadhani S Mwiru; Rodrick Kisenge; Wafaie W Fawzi
Journal:  Matern Child Nutr       Date:  2014-04-10       Impact factor: 3.092

8.  Complementary feeding and attained linear growth among 6-23-month-old children.

Authors:  Adelheid W Onyango; Elaine Borghi; Mercedes de Onis; Ma del Carmen Casanovas; Cutberto Garza
Journal:  Public Health Nutr       Date:  2013-09-19       Impact factor: 4.022

Review 9.  Boys are more stunted than girls in sub-Saharan Africa: a meta-analysis of 16 demographic and health surveys.

Authors:  Henry Wamani; Anne Nordrehaug Astrøm; Stefan Peterson; James K Tumwine; Thorkild Tylleskär
Journal:  BMC Pediatr       Date:  2007-04-10       Impact factor: 2.125

10.  A matching decomposition of the rural-urban difference in malnutrition in Malawi.

Authors:  Richard Mussa
Journal:  Health Econ Rev       Date:  2014-09-03
View more
  9 in total

1.  Risk Factors for Undernutrition and Diarrhea Prevalence in an Urban Slum in Indonesia: Focus on Water, Sanitation, and Hygiene.

Authors:  Yumiko Otsuka; Lina Agestika; Neni Sintawardani; Taro Yamauchi
Journal:  Am J Trop Med Hyg       Date:  2019-03       Impact factor: 2.345

2.  The importance of public health, poverty reduction programs and women's empowerment in the reduction of child stunting in rural areas of Moramanga and Morondava, Madagascar.

Authors:  Chitale Rabaoarisoa Remonja; Rado Rakotoarison; Nivo Heritiana Rakotonirainy; Reziky Tiandraza Mangahasimbola; Alain Berthin Randrianarisoa; Ronan Jambou; Inès Vigan-Womas; Patrice Piola; Rindra Vatosoa Randremanana
Journal:  PLoS One       Date:  2017-10-18       Impact factor: 3.240

3.  Trends and Determinants of Child Growth Indicators in Malawi and Implications for the Sustainable Development Goals.

Authors:  Henry V Doctor; Sangwani Nkhana-Salimu
Journal:  AIMS Public Health       Date:  2017-11-30

4.  Level of Undernutrition and Its Determinants Among Children Aged 12-59 Months in Wolaita District, Ethiopia.

Authors:  Shimelash Bitew Workie; Tesfa Mekonen; Wubalem Fekadu; Tefera Chane Mekonen
Journal:  Pediatric Health Med Ther       Date:  2020-03-24

5.  Regional Disparities in the Decline of Anemia and Remaining Challenges among Children in Tanzania: Analyses of the Tanzania Demographic and Health Survey 2004-2015.

Authors:  Bruno F Sunguya; Si Zhu; Linda Simon Paulo; Bupe Ntoga; Fatma Abdallah; Vincent Assey; Rose Mpembeni; Jiayan Huang
Journal:  Int J Environ Res Public Health       Date:  2020-05-17       Impact factor: 3.390

6.  Dietary diversity among school age children in Merawi town, Amhara region, Ethiopia, 2018: a community based cross-sectional study.

Authors:  Tilahun Tewabe; Amare Belachew; Yihun Miskir; Getnet Mekuria
Journal:  Arch Public Health       Date:  2020-01-06

7.  Prevalence of stunting and associated factors among public primary school pupils of Bahir Dar city, Ethiopia: School-based cross-sectional study.

Authors:  Getasew Mulat Bantie; Amare Alamirew Aynie; Kidist Hailu Akenew; Mahlet Tilahun Belete; Eyerusalem Teshome Tena; Genet Gebreselasie Gebretsadik; Aynalem Nebebe Tsegaw; Tigist Birru Woldemariam; Ashenafi Abate Woya; Amare Alemu Melese; Agumas Fentahun Ayalew; Getenet Dessie
Journal:  PLoS One       Date:  2021-04-12       Impact factor: 3.240

8.  Boys are more likely to be undernourished than girls: a systematic review and meta-analysis of sex differences in undernutrition.

Authors:  Susan Thurstans; Charles Opondo; Andrew Seal; Jonathan Wells; Tanya Khara; Carmel Dolan; André Briend; Mark Myatt; Michel Garenne; Rebecca Sear; Marko Kerac
Journal:  BMJ Glob Health       Date:  2020-12

9.  Stunting in the Context of Plenty: Unprecedented Magnitudes Among Children of Peasant's Households in Bukombe, Tanzania.

Authors:  Lucas L Shilugu; Bruno F Sunguya
Journal:  Front Nutr       Date:  2019-11-07
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.