Background
According to WHO Adolescents ranged from 10–19 years and they account about 18 % of the global population. They are under physiological, cognitive, and psychosocial changes but remain neglected from many health and nutrition services [1, 2].
The burden of energy, protein and micronutrient deficiencies is high in adolescents of developing courtiers. The subsequent social, economic, health, and development impact of under nutrition in adolescents is expected to be high in this countries [2, 3].
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Malnutrition is one of the major public health issue affecting many women in Ethiopia. Twenty seven percent of women had chronic energy deficiency (BMI < 18.5), 17 % of women were anemic, and 6 % of rural women were experiencing night-blindness in their most recent pregnancy [3]. Undernutrition throughout the human life cycle usually starts in uterus and spans generation [4]. Malnutrition that occurs during childhood, adolescence, and pregnancy has an additive negative impact on the birth outcome of the newborn and it will have intergenerational effect. Malnourished adolescents tend to be ultimately malnourished adults and give birth to small babies [3, 5‐7]. Moreover Infants with low birth weight are more vulnerable to adult-onset chronic diseases than children born at normal weight [7].
Malnutrition in adolescents may be genetically inherited, however, the vast majority of cases are linked with food insecurity, poor care and poor socioeconomic status [3]. Prematurity, short maternal stature, infections, cigarette smoking, alcohol and drug use, very young maternal age, indoor air pollution, domestic violence, closely spaced pregnancies, hypertension, stress, and malaria are all important predictors for the intergenerational effect of undernutrition [8].
The adolescent growth spurt offers a chance to compensate for earlier growth failure, although such potential is very limited [3]. Adolescence is a pivotal stage of the life cycle, and in turn, provides a unique opportunity to foster a healthy transition from childhood to adulthood and halting generational effect of malnutrition [5].
Large-scale community-based health and nutrition interventions showed promising results in improving nutritional status of adolescents in different countries [9]. In Ethiopia there are community based interventions mainly to prevent malnutrition in women and children, however there is limited effort to address malnutrition in adolescents. The current study aimed to assess the prevalence and associated factors of undernutrition in adolescent girls in Amhara region, Ethiopia. The study will be a base line for other future studies and will guide policy makers to design proper nutrition interventions for adolescents.
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Methods
Study design and period
Quantitative cross sectional study was employed in December 2013.
Study area
The study was conducted at Amhara National Regional State which is located in the northwestern part of Ethiopia between 9° 20′ and 14° 20′ North latitude and 36° 20′ and 40° 20′ East longitude. Its land area is about 170,000 square kilometers [10]. The region is divided into 11 zones and 140 Weredas. There are about 3429 Kebeles (the smallest administrative units) in the region. During the study period, the community based nutrition(CBN) program was implemented in 10 Zones and 47 Woredas in Amhara region. The study was conducted in 5 major CBN implementing woredas namely Wogera, Ebnat, Wadla, Chilga and Dembecha [11].
Source and study population
All adolescent girls in all CBN sites in Amhara Region were the sources population. All adolescent girls in selected CBN sites in Amhara region were the study population. Those adolescent girls who were seriously ill at time of data collection were excluded in this study.
Sample size
The sample size of the Study was calculated using single population proportion formula by considering the following assumptions: Proportion of adolescents with stunting as 50 %, margin of error as 4 %, confidence level at 95 %, non response rate of 10 % and design effect of 2. The final sample size for this study was 1320.
Sampling procedure
Multistage cluster sampling was employed to select adolescent girls. There were 11 zones in the region and we have selected 4 zones by simple random sampling, then we have selected 5 woredas where CBN service implemented in 4 different phases. We have selected 15 kebeles by simple random sampling technique, three kebele in each woreda. All adolescents from selected kebeles have been incorporated in the study.
Variables of the study
Stunting and thinness in adolescent girls were considered as dependent variables in this study. Adolescent girls with height-for-age Z-score < −2 from the median value of WHO’s 2006 reference data were considered as stunted and those with BMI-for-age Z-score < −2 were considered as thin. Those adolescent girls with height-for-age or BMI-for-age Z-score < −3 from the median value of 2006 WHO’s reference data were considered as severely stunted or severely thin respectively [12]. Socio demographic variables, economic status, nutrition and health related characteristics were considered as independent variables.
Data collection instruments and procedure
A cross-sectional quantitative study design was employed. Structured questionnaire was used for data collection. The questionnaire was prepared in English first and then translated to Amharic and back to English by language experts to check for consistency. Twenty Nurse data collectors and 7 health officer supervisors were trained for data collection and supervision.
Weight of adolescent girls was measured using beam balance with light closing, and was measured to the nearest 0.1 kg, and height of adolescent girls was measured to the nearest 0.1 cm on standing position without shoes. Checking accuracy of the scale and frequent calibrating of the scale was done.
The categories for dietary diversity were determined by first asking if the adolescent girl had eaten a particular type of food in the previous 24 h prior to date of data collection. These were then combined in to different food groups. Dietary diversity score(DDS) of adolescents was assessed and scored as “poor” for 0–3 food group, as “medium” for 4–5 food group and as “high” for greater than 6 food group.
Food security was assessed using 6-item module and the sum of affirmative responses to the six questions in the module was taken. The food security status of households with raw score 0–1 was described as food secure and the two categories “low food security” and “very low food security” in combination were referred to as food insecure [13].
Data quality control
Data quality was controlled via conducting a pre-test on 5 % of the samples and through supervision during data collection. The completeness of the questionnaire was also checked before data entry. Anthropometric measurements of subjects were done by trained data collectors using standard procedures.
Data processing and analysis
First code was given to the completed questionnaire and then data were entered and analyzed using SPSS version 20 statistical package. Data cleaning was performed to check for accuracy, consistencies and missed values. Any error identified has been corrected. Frequencies, proportion and summary statistics was used to describe the study population in relation to relevant variables. Anthropometric measurements were converted to height-for- age z-scores and BMI-for-age z-scores using WHO Anthroplus software [14]. The levels of undernutrition (thinness and stunting) were regressed against the demographic, socio-economic, health and nutrition related factors. Binary logistic regression model was fitted to identify factors associated with thinness and stunting. The two outcome variables were coded as “1” for having thinness and stunting where as “0” for not having thinness and stunting. Bivariate analysis was performed and variables with p-value < 0.2 in the bivariate analysis were exported to multivariate logistic regression analysis in order to screen strong predictors of undernutrition. Significance was obtained at 95 % CI and p < 0.05.
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Ethical considerations
Ethical approval has been obtained from the University of Gondar and permission letter was obtained from Amhara Regional Health Bureau and from zonal and woreda health offices. The questions from the questionnaire has proved not to affect the moral and personality of study subjects. Informed consent was obtained from each study subject after explanation of why they take part in research. They were also informed participation is volunteer based. Confidentiality has been ensured from all the data collectors, supervisors and investigators side using code numbers than names and keeping questionnaires locked.
Result
Socio demographic and economic characteristics of study subjects
A total of 1281 adolescent girls aged 10–19 years included in the final analysis among 1320 which make a response rate 97.2 %. Among this 499(39 %) were early adolescents, 425(33 %) were middle adolescents. while 357(27 %) of them were late adolescents. Majority of adolescents (83.8 %) were single in marital status. Around 65 % of them attended primary education and 1013(79.1 %) of them were students (Table 1).
Table 1
Socio demographic characteristics of adolescent girls, Amhara region, Northwest Ethiopia, December, 2013 (N = 1281)
Variables | Frequency | Percent (%) |
|---|---|---|
Age | ||
10 to 14 | 499 | 39.0 |
15 to 17 | 425 | 33.2 |
18 to 19 | 357 | 27.9 |
Woreda | ||
Dabat | 256 | 20.0 |
Aykel | 256 | 20.0 |
Ebnat | 258 | 20.1 |
Wadila | 253 | 19.8 |
Dembecha | 258 | 20.1 |
Marital status | ||
Single | 1073 | 83.8 |
Married | 193 | 15.1 |
Divorced | 12 | 0.9 |
Separated | 3 | 0.2 |
Newlywed | 126 | 9.8 |
Religion | ||
Orthodox Christian | 1261 | 98.4 |
Muslim | 20 | 1.6 |
Ethnic group | ||
Amhara | 1134 | 88.5 |
Othera | 147 | 11.5 |
Educational status | ||
Can’t read/write | 71 | 5.5 |
Can read/write | 32 | 2.5 |
Primary (1 to 8) | 831 | 64.9 |
Secondary (9 to 12) | 315 | 24.6 |
College/university | 32 | 2.5 |
Occupation | ||
Housewife | 145 | 11.3 |
Farmer | 27 | 2.1 |
Daily laborer | 6 | 0.5 |
Private/government employee | 2 | 0.2 |
Student | 1013 | 79.1 |
Jobless (unemployed) | 67 | 5.2 |
Otherb | 21 | 1.6 |
Family size | ||
< or equal to 5 | 587 | 45.8 |
Greater than 5 | 694 | 54.2 |
Staple cereal | ||
Teff | 484 | 37.8 |
Wheat | 398 | 31.1 |
Maize | 184 | 14.4 |
Sorghum | 123 | 9.6 |
Othersc | 82 | 7.1 |
Nutrition and health related characteristics of adolescent girls
Around 20 % of all adolescents were consuming less than three meals per day. The mean Dietary Diversity Score(DDS) was 5.6 (SD 2.04). Among all study subjects, 664(53 %) were practiced bellow the mean score of dietary diversity. About 33 % of adolescent girls had consumed 3 or less food groups (poor dietary diversity) in the previous day, 45 % had consumed 4 to 5 different food groups and 21.8 % consumed 6 or more food groups. Food insecurity status was determined at household level. The research revealed that 556(44.4 %) of adolescents lived in food insecure households. Adolescents were asked to list any sickness a month prior to the survey and 241(19.2 %) of adolescents reported sickness. Based on current physiologic state of adolescents, 27 were pregnant, 58 were lactating and the rest 91.6 % were non- pregnant and non-lactating (Table 2).
Table 2
Nutrition and health related characteristics of adolescent girls in Amhara region, Northwest Ethiopia, December, 2013 (N = 1281)
Variable | Frequency | Percent |
|---|---|---|
Physiological state | ||
Not pregnant/lactating | 1174 | 91.6 |
Pregnant | 27 | 2.1 |
Lactating | 58 | 4.5 |
Pregnant and lactating | 2 | .2 |
Don’t know | 20 | 1.6 |
Dietary Diversity Score | ||
Poor(0–3 food group) | 417 | 32.6 |
Medium(4–5 food group) | 585 | 45.7 |
High(6+ food group) | 279 | 21.8 |
Meal frequency total | ||
Less than 3 meal | 266 | 20.8 |
3 plus meal | 1015 | 79.2 |
Meal frequency (non pregnant) (N = 1252) | ||
Once | 11 | 0.9 |
Twice | 247 | 19.7 |
Three and more times | 994 | 79.4 |
Food security | ||
Food insecure | 556 | 44.4 |
Food secure | 696 | 55.6 |
Knowledge on vitamin A rich foods | ||
Green vegetable and other vegetable, fruits egg, meat, milk | 163 | 12.7 |
I don’t know | 1118 | 87.3 |
Knowledge on iron rich foods | ||
Teff, meat | 286 | 22.3 |
I don’t know | 995 | 77.7 |
Availability of home garden | ||
Yes | 785 | 61.3 |
No | 496 | 38.7 |
Disease reported in last one month(N = 1252) | ||
Yes | 241 | 19.2 |
No | 1011 | 80.8 |
Access to health and nutrition information from health extension workers | ||
No information | 478 | 37.3 |
Growth monitoring | 97 | 7.6 |
Adolescent girls nutrition | 88 | 6.9 |
Maternal nutrition | 75 | 5.9 |
Exclusive breast feeding | 82 | 6.4 |
Complementary feeding | 85 | 6.6 |
Family planning | 93 | 7.3 |
Child care | 53 | 4.1 |
Nutrition during pregnancy | 67 | 5.2 |
Nutrition during lactation | 163 | 12.7 |
Prevalence and associated factors of malnutrition in adolescent girls
Prevalence of malnutrition in adolescent girls
Overall the prevalence of girls with a low body mass index-for-age Z score less than < −2SD were 13.6 % while 4 % were with less than −3 SD. The overall prevalence of height-for-age Z-score less than −2 SD were 31.5 % while 14.7 % were with less than −3 SD.
Factors affecting low BMI-for-Age in adolescent girls
Those adolescents aged 10–14 years were 5.8 times more likely to be thin than those aged 18–19 years [AOR = 5.83, 95 % CI: 3.26, 10.44] where as those aged 15–17 were 2 times more likely to be thin than those aged 18–19 years [AOR = 2.06, 95 % CI: 1.09, 3.89]. Adolescents with poor dietary diversity score were 2.5 times more likely to develop thinness than those having high dietary diversity score [AOR = 2.48, 95 % CI: 1.60, 3.84]. CBN service utilization was also other contributory factor for good nutritional status. Those who utilized CBN service were 33 % less likely to be thin than those not utilizing CBN service [AOR = 0.67, 95 % CI: 0.47, 0.95] (Table 3).
Table 3
Both bivariate and multivariate result of factors affecting body mass index-for-age of adolescent girls, Amhara region, Northwest Ethiopia, 2013
Low body mass index -for -age | OR(95 % CI) | |||
|---|---|---|---|---|
Variable | Yes | No | Crude OR(95 % CI) | Adjusted OR(95 % CI) |
Age | ||||
10 to 14 | 118 | 381 | 7.08(3.99, 12.56) | 5.83 (3.26, 10.44) |
15 to 17 | 38 | 381 | 2.28(1.21, 4.28) | 2.06 (1.09, 3.89) |
18 to 19 | 14 | 320 | 1 | 1 |
DDS | ||||
Low | 53 | 134 | 3.48(2.30,5.27) | 2.48(1.60, 3.84) |
Medium | 57 | 420 | 1.19(0.81, 1.75) | 0.96 (0.64, 1.44) |
High | 60 | 528 | 1 | 1 |
Community based nutrition service utilization | ||||
Yes | 65 | 595 | 0.51(0.36, 0.71) | 0.67(0.47,0.95) |
No | 105 | 487 | 1 | 1 |
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Factors affecting low height-for-age in adolescent girls
Those adolescents aged 10–14 years were 6 times more likely to be stunted than those aged 18–19 years [AOR = 6.07, 95 % CI: 4.00,9.22] where as those aged 15–17 were 1.4 times more likely to be thin than those aged 18–19 years [AOR = 1.40,, 95 % CI: 1.93, 2.09]. In this study adolescents who had nutrition and health information were 2 times more likely to be stunted than those who had no information [AOR = 1.94, 95 % CI: 1.46, 2.57]. Adolescents living in food secured households were 35 % times less likely to be stunted than those living in food in secured household. (AOR:0.65, 95 % CI: 0.50, 0.84] (Table 4).
Table 4
Both bivariate and multivariate result of factors affecting low height-for-age in adolescent girls, Amhara region, Northwest Ethiopia, 2013
Low height for age | OR | |||
|---|---|---|---|---|
Variable | Yes | No | Crude OR(95 % CI) | Adjusted OR(95 % CI) |
Age | ||||
10 to 14 | 262 | 237 | 6.34(4.51, 8.91) | 6.07(4.00,9.22) |
15 to 17 | 89 | 336 | 1.52(1.05, 2.21) | 1.39(1.93,2.09) |
18 to 19 | 53 | 304 | 1 | 1 |
Nutrition and health information | ||||
No information | 122 | 356 | 1.58(1.23,2.03) | 1.94(1.46, 2.57) |
Had information | 282 | 521 | 1 | 1 |
Food insecurity | ||||
Yes | 153 | 467 | 0.54(0.42,0 .68) | 0.65(0.50, 0.84) |
No | 251 | 410 | 1 | 1 |
Home gardening | ||||
Yes | 241 | 544 | 1 | 1 |
No | 163 | 333 | 1.11(0.87, 1.41) | 1.27(0.96, 1.67) |
Discussion
This cross sectional nutritional survey was conducted at five CBN implementing woredas of Amhara region. The study determined prevalence and associated factors of undernutrition in adolescent girls. Despite the fact that community based nutrition program will improve the nutritional status of women and children, prevalence of low BMI-for-age and Low height-for-age in adolescent girls were found to be high in the study setting which were 13.6 % and 31.5 % respectively.
The prevalence of low BMI-for-age is comparable with the national nutrition baseline survey report for the NNP of Ethiopia which was14% [15] and lower than a study done in northern part of Ethiopia (58.3 %) [16] and Varanasi rural India (26.6 %) [17]. However, the prevalence is higher than a study in Addis Abeba Ethiopia (6.2 %) [18]. The variation in prevalence could be explained in socioeconomic and urban–rural difference between the study subjects and settings. Low prevalence as compared to the study in northern Ethiopia may be due to the current study was conducted after the introduction of community based program in Ethiopia.
The prevalence of low Height-for-age is higher than the national base line survey which was 23 % [15], northern part of Ethiopia [16] and Addis Abeba town [18]. The reason could be our survey is done in Amhara region in which adolescents may have a different feeding habit. High levels of stunting in the study setting may be due to early marriage and early pregnancy which is high in the region. The other possible reason could be the others were conducted in the age group of 13–19 in which the most vulnerable groups were not included.
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In this survey, variation in development of thinness was observed across different age groups. Young adolescent girls were more likely to be thin than older adolescent girls in this study (Table 3). The findings of this study was in line with a study in Northern Ethiopia and Ambo town [16, 19]. This may be due to the fact that age 10–14 is the time of adolescent growth spurt in which there is an increased demand of essential nutrients. Hence, if the requirement for achieving the their maximum need is not fulfilled they will be prone to malnutrition.
The DDS is one of best indicators of both macronutrient and micronutrient intake. The current study revealed that adolescent girls with higher DDS were more likely to have normal BMI-for- age Z scores as compared to those having low DDS (Table 3). This is because when the DDS is high, adolescents will get adequate energy, and other important nutrients having role in growth and development.
Age of adolescent girls was also important predictor of stunting in adolescent girls in which early adolescents aged 10–14 years were more likely to be stunted as compared with those 18–19 years old (Table 4). This finding is consistent with the baseline national nutrition survey and a study in northern Ethiopia [15, 16]. Those early adolescents are at the greatest gain in height as compared to late adolescents. Hence, Failing to achieve their nutrient needs for this period will make early adolescents more susceptible for developing chronic malnutrition.
Adolescents living in food secure households were 35 % times less likely to be stunted than those living in food insecure household (Table 4). This finding is consistent with a study in Jimma Zone, southwest Ethiopia [20]. This is because food security is one of the important determinant of chronic nutritional insult in adolescent girls.
In this study adolescents who had no nutrition and health information were 2 times more likely to be stunted than those who had information (Table 4). This is because adolescents getting nutrition information will change their dietary habit which can improve their nutritional status.
Even though the study is conducted in wider coverage it may not address cause and effect relationship between variables since it is a cross sectional study. There may be recall and social desirability bias in listing food items eaten in the past 24 h. More over DDS did not measure quantity of food eaten by this adolescents.
Conclusion
Prevalence of adolescents with low BMI for age and Height for age Z score less than < −2SD were high. Age, dietary diversity score and CBN service utilization were factors affecting low BMI for Age in adolescent girls. Age, food insecurity and access to Nutrition and health information were factors affecting low height for age in adolescent girls. Considering adolescents as one of major target groups for CBN and give training to health extension workers and Women development army about nutrition services to be delivered to adolescents is recommended.
Acknowledgment
The authors are grateful for Ethiopian Public Health Institute and University of Gondar for their support for the accomplishment of this study. The authors are also thankful for officials of Amhara National Regional State Health Bureau, Zonal and Woreda Administrative Health offices for delivering necessary information for this study. We would also like to thank supervisors and data collectors for taking their precious time to collect the data. This survey will not be true without the financial support from the Global Fund. Last but not least, we are glad to thank the adolescent girls who participated in this study and took their time to provide information.
Funding
Global Fund financialy support this study.
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Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
The authors’ responsibilities were as follows-MM, AA, ME, GD, TM and AB: designed and supervised the study and ensured quality of the data and made a substantial contribution to the local implementation of the study. MM did the analysis and interpretation of the data. MM, the corresponding author wrote the manuscript and had the final responsibility to submit it for publication. All authors read and approved the final manuscript.
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