Objective: To assess determinants of under nutrition among adolescents at Lemo district, south Ethiopia

Design: Community based unmatched case-control study design was conducted. Cases comprised undernourished adolescents aged 10-19 years and controls were well-nourished adolescents.

Study setting: The study was conducted at Lemo district of Hadiya zone after eligible group identified at household from March 10 up to May 25, 2015.

Participants: One hundred eighty two (91 cases and 91 controls) study subjects were selected with probability proportional to size from six kebeles by using simple random sampling technique.

Main outcome measures: Weight was measured in kilogram using digital bath room weighing scale to nearest 0.1 kg and height was measured in centimeter using a portable measuring board to the nearest 0.1 cm, Body Mass Index<18.5 kg/m² cut-off point for malnutrition

Results: Age, sex and type of latrine were found to be independent predictors of adolescent under nutrition. Adolescents in age group 10-12 years were more likely to develop under nutrition as compared to adolescents in age group 13-15 years (AOR=8.7 (95% CI=2.51-30.10)), adolescents in age group 13-15 years were more likely to develop under nutrition as compared to adolescents in age group 16-19 years (AOR=7.9 (95% CI=2.67-23.82)), male adolescents were more likely to develop under nutrition as compared to female adolescents (AOR=4.3 (95% CI=1.87-10.04)), adolescents who used open field defecation were more likely to develop under nutrition as compared to adolescents who had ventilated pit latrine (AOR=8.7 (95% CI=1.27-60.03)) and adolescents who had pit latrine were more likely to develop under nutrition as compared to adolescents who had ventilated pit latrine (AOR=6.8 (95% CI=1.18, 39.94)).  

Conclusion: Age, sex and type of latrine were independently associated with adolescent under nutrition. Therefore, developing and implementing health programs to tackle adolescent malnutrition should be taken into account.

Keywords:  Malnutrition, Adolescent, Predictors, Lemo

Malnutrition is the condition that results from taking an unbalanced diet in which certain nutrients are lacking, in excess, or in the wrong proportions [1].

The World Health Organization cites malnutrition as the gravest single threat to the world's public health. Improving nutrition is widely regarded as the most effective form of aid. FAO reported that there were 925 million malnourished people in the world in 2010 [2].

Malnutrition is the most serious human health and social problems that affect vast population of the world where, the effect in terms of increased mortality, morbidity, reduction in productivity and reproductive capacity is considerable particularly in the developing countries [1].

About one-quarter of the Sub-Saharan African population is unable to secure adequate food to meet their nutritional requirements.   The   large   and   increasing   incidence   of malnutrition in Sub-Saharan Africa impedes the social and economic progress of the continent. In Ethiopia there is a high level of chronic food insecurity and vulnerability to acute food insecurity, due to drought, environmental degradation, as well as poor access to and availability of food. Between 2004 and 2006, 44% of the people in the country were estimated to be undernourished [3].

World Health Organization, in 1986 defines adolescent as person age 10 to 19 years old. Adolescents are the future generation of any country and their nutritional needs are critical for the wellbeing of society. Growth during adolescence is faster than at any other time in an individual’s life except the first year. 20% of adult height, 50% of adult weight and 50% of adult skeletal mass is attained during adolescence; as a result, nutritional requirements peak in adolescence [4].

Good nutrition during adolescence is critical to cover the deficits suffered during childhood and should include nutrients required to meet the demands of physical and cognitive growth and development. Adolescent represent around 20% of the global world's population and around 84% of them are found in developing countries [1].

Adolescents from developing countries are more vulnerable to nutritional deficiencies due to early childhood nutritional problems, which include underweight, stunting and low dietary intakes. In developing countries where a large segment of the population is involved in low income jobs with large family sizes can’t afford to buy good quality food and their diets are mostly restricted to cereals and legumes [5].

Adolescent in Ethiopia accounted for 25.2% of the total population according to Demographic and Health Survey, 2005 [6].

Adolescents haven't received much attention with respect to their nutritional needs and wellbeing so there is limited information on the determinants of adolescent under nutrition and the precise mechanisms by which it is linked to other health and social outcomes [7].

The Federal Government of Ethiopia has been working to reduce under nutrition significantly through public education and providing nutritional supplements and financial support to vulnerable families. However, the risk factors of under nutrition are diverse and could potentially change in space and time. Thus, there is a need to determine the current nutritional status to review the pitfalls and design effective intervention strategies.

To the best of my knowledge, there was no study done on nutritional status of adolescent in the area. Therefore, this study was carried out to assess determinants of under nutrition among adolescents and to fill information gaps and recommend possible intervention in Lemo district, South Ethiopia.

METHODS AND MATERIALS

Design 

Community based unmatched case-control study design was conducted in Lemo district, Hadiya zone, South Ethiopia from March 10 to May 25, 2015. Cases comprised undernourished adolescents aged 10-19 years and controls were well-nourished adolescents. Sample size was determined using statistical formula for two population proportions. Assumption was based on considering sex (OR=2.5), boys had greater chance to be underweight as compared to girls, prevalence of under nutrition among controls was 58.3% with 95% CI and 80% power and case to control ratio 1:1 [8,9].

The study subjects were selected with probability proportional to size from six kebeles From 2 urban kebeles, 77 households were included and from 4 rural kebeles, 105 households were included in the study using simple random sampling technique data until sample size was fulfilled. If there were more than one eligible adolescent in household, one adolescent was selected using lottery method. Finally 182 sample sizes were enrolled. 

Data collection was conducted using a structured questionnaire developed in English and addressed all important variables and translated in to local language which is Hadiysa. Six data collectors and two supervisors who were recruited based on previous data collection and work experience. In each kebele one data collector was assigned. Data collectors were trained for two days on purpose, scope of the study, and overall procedure of data collection instrument and supervision.

The information was obtained both from parents and study subjects. Weight was measured in kilogram using a portable bath room digital weighing scale with the adolescents in light clothing and without shoes to nearest 0.1 kg. Weighing scale was recalibrated before taking the weight of each study subject. The height was measured in centimeter using portable measuring board  standardized by WHO and used by CSA and EHNRI at national level in standing position without shoes to  nearest 0.1 cm.

Supervision was conducted by supervisors and principal investigator during data collection and data was edited each day and feedback was given for data collectors.

Pre-test was done in 18 subjects in other district  with similar socio-demographic background and consistency was ensured and appropriate modifications was made after discussing with  supervisors and data collectors such as skipping patterns and some other corrections two days before starting the actual data collection process.

STATISTICAL ANALYSIS

Male adolescents were more likely to develop under nutrition as compared to female adolescents (COR=2.5; 95% CI: 1.38-4.66). Adolescents with first birth order were more likely to develop under nutrition as compared to adolescents with 2-6 birth order (COR=2.0; 95% CI: 1.09, 3.83). Adolescents with less than 24 months birth interval were more likely to develop under nutrition as compared to adolescents with 48+ months birth interval (COR=3.8; 95% CI: 1.22, 12.35) (Table 1).

Majority 69 (66.3%) of cases and 35 (33.7%) of controls were educated to level of primary. Adolescents educated to level of primary were more likely to develop under nutrition as compared to adolescents educated to level of senior secondary/tertiary (COR=8.5; 95% CI: 3.21, 22.68). Adolescents whose mothers age group 25-29 years were more likely to develop under nutrition compared to adolescents whose mothers age greater than or equal to forty years (COR=4.7; 95% CI: 1.39, 15.4) (Table 1).   

Adolescents who used open field waste disposal were more likely to develop under nutrition as compared to adolescents who had private waste disposal container (COR=2.5; 95% CI: 1.22, 5.21). Adolescents who used communal waste disposal container were more likely to develop under nutrition as compared to adolescents who had private waste disposal container (COR=3.5; 95% CI: 1.47, 8.48). Only source drinking water was not significantly associated with adolescent under nutrition (Table 3).   

The final model was constructed using backward binary logistic regression method. All variables which had shown statistically significant association during chi-square analysis such as age, sex, birth order, birth interval, educational status of study subjects, practicing regular physical exercise, frequency of physical exercise, current mother’s age, mothers educational status, ethnicity, type of latrine and availability of waste disposal container were included. However, on multivariate backward binary logistic regression analysis, out of these twelve independent variables only age, sex and type of latrine were found to be independent predictors for the occurrence of adolescent under nutrition.

Male adolescents were more likely to develop under nutrition as compared to female adolescents (AOR=4.3; 95% CI: 1.87, 10.04) (Table 4).

Adolescents who used open field defecation were more likely to develop under nutrition as compared to adolescents who had ventilated pit latrine (AOR=8.7; 95% CI: 1.27, 60.03). Adolescents who had pit latrine were more likely to develop under nutrition compared to adolescents who had ventilated pit latrine (AOR=6.8; 95% CI: 1.18, 39.94) (Table 4).

DISCUSSION 

This study investigated determinants of under nutrition among adolescents in Lemo district.

Recently many unindustrialized countries have entered a nutrition transition in which rapid changes in food availability and physical activity patterns have led to an upward shift in BMI [10]. This changeover has also been observed in countries in Latin America, Asia and Africa. Ethiopia is undertaking many changes, including demographic, life style and food habits, and socio-economic changes.

Despite lack of historical data, the nutrition transition in Ethiopia has been explained by changes in lifestyle borrowed from Western countries of diets high in refined carbohydrates, saturated fats and sugars [11]. Recently, Ethiopia has seen an upsurge in the food availability and little is known on whether it benefitted all sections of the society to improve the nutritional level.

Adolescence is an important stage of growth and development that requires increased nutrition. But it has often failed to get increased attention as observed in childhood with regards to health related uses and interpretation of anthropometry.

In this study, many variables (age, being male, birth order, birth interval, adolescent education, current mother age, regular physical exercise, frequency of exercise, type of latrine and waste disposal) were significantly associated with under nutrition in bivariate logistics association, but later most of the variables lost their significance in multivariate logistics analysis.

Factors such as age, sex and type of latrine were significantly associated with an increased risk of under nutrition.

Under nutrition was common in adolescent who were 10 to 12 years old and 13-15 years old. This is in agreement with the studies in different African countries, including Ethiopia [12-18]. Feeding practices, care and exposure to infection, which primarily determine the nutritional status of adolescent, vary with age [19,20]. Children of age 10 to 15 years are more active and lose more amount of energy. Excess energy loss, together with lack of nutritious food, could make them undernourished. Indeed, it was the underweight adolescent (compared to those that were overweight) who demonstrated a high level of physical activity [21]. This may have important public health implications to countries like Ethiopia which require a strategy to keep the energy balance.

The risk of under nutrition was high among males than females. Male adolescents were 4.3 times higher at risk of developing under nutrition compared to female adolescents. This was in line with Turkey, Ramallah, Nigeria, Tanzanian and South Africa study that documented significantly more boys underweight than girls [7,8,22-24]. This can be explained as male did more physical exercise than females and hence can demand more energy replacement. Also biological factors, inequalities in resource allocation within households and socio-cultural norms prevailing in the community could be responsible for the variation in the risk of under nutrition between males and females.

Adolescents who used open filed defecation were 8.7 times higher at risk of developing under nutrition compared to respondents who used ventilated pit latrine. Also adolescents who used pit latrine were 6.8 times higher at risk of developing under nutrition compared to adolescents who used ventilated pit latrine. This finding is consistent with reports from a study conducted on nutritional status of rural adolescent girls in Tigray in 2009 that showed lack of latrine the predictors of malnutrition [9].

Adolescents with less than 24 months birth interval were 3.8 times more likely to develop under nutrition compared to adolescents with 48+ month’s birth interval. This can be attributed to inadequate child spacing and early starting of weaning diet which can lead to childhood infection that can affect growth and development in adolescence.

Substance use and illness were not significantly associated with adolescent malnutrition. This study was similar with a survey conducted in India in 2009 which showed addiction was not significantly associated with nutritional status of study subjects at the time of survey and also illness or frequency of illness was found not significantly associated with malnutrition [25,26].

When we look at predictors of adolescent under nutrition age group 10-12 years were 8.7 times higher at risk of developing under nutrition compared to age group 13-15 years and age group 13-15 years were 7.9 times higher at risk of developing under nutrition compared to age group 16-19 years. This finding is consistent with reports from a study conducted on nutritional status of rural adolescent girls in Tigray in 2009 that showed age the predictors of malnutrition [9].

CONCLUSION

It was found that adolescents in age group of 10-15 years old, being male, open field defecation and pit latrine was found to be independent predictors for the occurrence of adolescent under nutrition in study area.

The results of this study give a clue on the factors contributing to malnutrition and provide a base line data for other investigators and policy makers. Addressing the nutritional needs of adolescents could be an important step towards breaking the vicious cycle of intergenerational malnutrition. Special attention should be sought to early and middle adolescents and male sex in particular in nutrition. Prevention of communicable diseases through improving environmental hygiene and sanitation especially increasing latrine coverage.

Therefore, developing and implementing health programs to tackle malnutrition among adolescents should take into account such differences that are consequence of socio-demographic, health and environment related factors.

ACKNOWLEDGEMENT

We would like to thank the Wachemo University and South Ethiopia People Development Agency (SEPDA) for its material support and providing us all the necessary facilities needed during the study period. We also acknowledge Hadiya zone health department, Lemo District health department, study participants and data Collectors for their valuable contribution in the realization of this study.

COMPETING INTERESTS

1.       Dasgupta A, Butt A, Saha TK, Basu G, Chattopadhyay A, et al. (2010) Assessment of malnutrition among adolescents: Can BMI be replaced by MUAC. Indian J Community Med 35: 276.

2.       Kurz KM, Galloway R (1999) Improving adolescent iron status before childbearing. Presented at the Experimental Biology 1999 meeting Washington DC.

3.       Iliescu C, Beghin L, Maes L, De Bourdeaudhuij I, Libersa C, et al. (2008) Socioeconomic questionnaire and clinical assessment in the HELENA cross-sectional study: Methodology. Int J Obes 32: S19.

4.       Choudhary S, Mishra CP, Shukla KP (2009) Correlates of nutritional status of adolescent girls in the rural area of Varanasi. Internet J Nutr Wellness 7: 18.

5.       Müller O, Krawinkel M (2005) Malnutrition and health in developing countries. CMAJ 173: 279-286.

6.       Demographic E (2011) Health survey: Addis Ababa. Ethiopia and Calverton, Maryland, USA: Central statistics agency and ORC Macro.

7.       Martins IS, Fischer FM, Oliveira DC, Teixeira LR, Costa LA, et al. (2002) Growth and work among elementary and high school students in São Paulo, Brazil. Revista de Saude Publica 36: 19-25.

8.       Bonnard P (2001) Improving the nutrition impacts of agriculture interventions: strategy and policy brief. Food and Nutrition Technical Assistance Project (FANTA) and Academy for Education Development (AED), Washington DC.

9.       Who EC (2004) Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 363: 157.

10.    Letamo G (2011) The prevalence of and factors associated with, overweight and obesity in Botswana. J Biosoc Sci 43: 75-84.

11.    World Bank (2011) Botswana - Nutrition at a glance; Botswana. Washington DC. World Bank.

12.    UNICEF (2010) Levels and trends in child mortality: Report 2010: Estimates developed by the UN Inter-Agency Group for Child Mortality Estimation. United Nations Children's Fund.

13.    Degarege A, Erko B (2013) Association between intestinal helminth infections and underweight among school children in Tikur Wuha Elementary School, north-western Ethiopia. J Infect Public Health 6: 125-133.

14.    Parraga IM, Assis AM, Prado MS, Barreto ML, Reis MG, et al. (1996) Gender differences in growth of school-aged children with schistosomiasis and geohelminth infection. Am J Trop Med Hyg 55: 150-156.

15.    Lwanga F, Kirunda BE, Orach CG (2012) Intestinal helminth infections and nutritional status of children attending primary schools in Wakiso district, Central Uganda. Int J Environ Res Public Health 9: 2910-2921.

16.    Genebo T, Girma W, Haider J, Demissie T (1999) The association of children's nutritional status to maternal education in Zigbaboto, Guragie Zone, Ethiopia. Ethiop J Health Dev 13: 55-61.

17.    Yimer G (2000) Malnutrition among children in southern Ethiopia: Levels and risk factors. Ethiop J Health Dev 14.

18.    Asfaw ST, Giotom L (2000) Malnutrition and enteric parasitoses among under-five children in Aynalem village, Tigray. Ethiop J Health Dev 14: 67-75.

19.    Katona P, Katona-Apte J (2008) The interaction between nutrition and infection. Clin Infect Dis 46: 1582-1588.

20.    Gandhi SJ, Godara N, Modi A, Kantharia SL (2014) Impact of feeding practices on nutritional status of children in rural area of Navsari district. Religion 20: 84-90.

21.    Dennison BA, Erb TA, Jenkins PL (2002) Television viewing and television in bedroom associated with overweight risk among low-income preschool children. Pediatrics 109: 1028-1035.

22.    Funke OM (2008) Prevalence of underweight: A matter of concern among adolescents in Osun State, Nigeria. Pak J Nutr 7: 503-508.

23.    Lwambo NJ, Brooker S, Siza JE, Bundy DA, Guyatt H (2000) Age patterns in stunting and anaemia in African school children: A cross-sectional study in Tanzania. Eur J Clin Nutr 54: 36.

24.    Kruger R, Kruger HS, Macintyre UE (2006) The determinants of overweight and obesity among 10-15 year old school children in the north west province, South Africa - The THUSA BANA (Transition and Health during Urbanisation of South Africans; BANA, children) study. Public Health Nutr 9: 351-358.

25.    Önera N, Vatansevera Ü, Saria A, Ekuklub G, Güzela A, et al. (2004) Prevalence of underweight, overweight and obesity in Turkish adolescents. Order 8: 10.

26.    Mikki N, Abdul-Rahim HF, Awartani F, Holmboe-Ottesen G (2009) Prevalence and socio-demographic correlates of stunting, underweight and overweight among Palestinian school adolescents (13-15 years) in two major governorates in the West Bank. BMC Public Health 9: 485.