Effects of preventive nutrition interventions among adolescents on health and nutritional status in low‐ and middle‐income countries: A systematic review

Abstract Background Malnutrition is one of the most common causes of morbidity and mortality among children and adolescents and is now considered to be one of the largest risk factors responsible for the global burden of diseases along with poor diet. Objectives The objective of this review was to assess the impact of preventive nutrition interventions (including nutrition education and counselling; micronutrient supplementation/fortification and macronutrient supplementation) to improve the health and nutritional status of adolescents aged 10–19 years in low‐ and middle‐income countries (LMICs). The secondary objective of the review was to assess various contextual factors based on the World Health Organisation (WHO) health system building blocks framework that might potentially impact the effectiveness of these interventions for this age group. Search Methods The search was conducted on Cochrane Controlled Trials Register (CENTRAL), MEDLINE, EMBASE, CINAHL, PsycINFO, the WHO nutrition databases, CAB Global Health, Social Science Citation Index, Scopus, WHO Global Health Index, ADOLEC and EPPI until February 5, 2019. We searched Google Scholar along with key nutrition agencies database such as Nutrition International, the Global Alliance for Improved Nutrition, the World Food Programme and HarvestPlus to search for nonindexed, grey literature to locate relevant programme evaluations and any additional trials. All searches were performed without any restrictions on publication date, language or publication status. Selection Criteria We included randomised controlled trials, quasiexperimental studies, controlled before‐after studies and interrupted time series evaluating the effectiveness of preventive nutrition interventions among adolescents between 10 and 19 years of age from LMICs. Data Collection and Analysis Two review authors independently assessed trials for inclusion, assessed risk of bias and extracted data from included studies. Meta‐analysis was conducted separately for each outcome and intervention. For dichotomous data, we reported risk ratios (RR) with 95% confidence intervals (CI). For continuous data, we reported the mean difference (MD) or standard mean difference (SMD) with 95% CI. Main Results This review summarises findings from a total of 10 studies from 15 papers including 10,802 participants. All the studies included in this review assessed the impact of micronutrient supplementation/fortification on health and nutritional status among adolescents in LMIC. We did not find any study assessing the impact of nutrition education and counselling or on macronutrient supplementation among adolescents. Micronutrient supplementation/fortification interventions included calcium/vitamin D supplementation/fortification, iron supplementation with or without folic acid, zinc supplementation and multiple micronutrient (MMN) fortification. The majority of the studies (eight out of 10 studies) included adolescent girls aged between 10 and 19 years of age. We did not find any large scale preventive nutrition intervention programmes targeting adolescents in LMICs. We are uncertain of the effect of iron supplementation with or without folic acid on anaemia (daily supplementation; RR: 1.04, 95% CI 0.88, 1.24; one study; 1,160 participants; low quality evidence. Weekly supplementation; RR: 1.07, 95% CI: 0.91, 1.26; one study; 1,247 participants; low quality evidence). We are uncertain of the effect of various micronutrient supplementation/fortification on body mass index (calcium/vitamin D supplementation; (MD: −0.01 kg/m2; 95% CI: −1.20, 1.17; two studies; 730 participants; I 2 94%; very low quality evidence, iron supplementation with or without folic acid; MD: 0.29 kg/m2; 95% CI: −0.25, 0.83; two studies; 652 participants; I 2 69%; very low quality evidence, zinc supplementation; MD: 0.35 kg/m2; 95% CI: −0.15, 0.85; one study; 382 participants; very low quality evidence) and MMN fortification; MD: 0.23 kg/m2, 95% CI: −0.11, 0.57; two studies; 943 participants; I 2 22%; very low quality evidence). None of the included studies reported any other primary outcomes including morbidity or adverse effects. Iron supplementation with or without folic acid may improve haemoglobin concentrations (MD: 0.42 g/dL, 95% CI: 0.13, 0.71; four studies; 1,020 participants; I 2 89%; low quality evidence). Calcium/vitamin D supplementation may improve serum 25(OH) D levels (standardised mean difference [SMD]: 2.85, 95% CI: 0.89, 4.82; two studies; 395 participants; I 2 99%; low quality evidence). We are uncertain of the effect of calcium only supplementation (MD: 0.02 g/cm2, 95% CI: −0.00, 0.04; one study; 233 participants; low quality outcome) and calcium + vitamin D supplementation (MD: 0.02 g/cm2, 95% CI: −0.00, 0.04; one study; 235 participants; low quality evidence) on total bone mineral density (BMD). We are uncertain of the effect of MMN fortification on haemoglobin concentrations (MD: −0.10 g/dL, 95% CI: −0.88, 0.68; two studies; 1102 participants; I 2 100%; very low quality evidence); calcium supplementation on total body bone mineral content (BMC); (MD: 30.20 g, 95% CI: −40.56, 100.96; one study; 233 participants; low quality evidence), calcium + vitamin D supplementation on total body BMC (MD: 21.60 g, 95% CI: −45.32, 88.52; one study; 235 participants; low quality evidence) and zinc supplementation on serum zinc levels (SMD: 6.94, 95% CI: −4.84, 18.71; two studies; 494 participants; very low quality evidence). One study reported the impact of iron supplementation with or without folic acid on cognition of adolescent girls suggesting improved cognition in most of the tests with daily or twice weekly supplementation compared to once weekly or no supplementation. None of the other secondary outcomes were reported including any other development outcomes and all‐cause mortality. These findings warrant caution while interpreting due to very few studies and high heterogeneity. Authors' Conclusions There is limited evidence of micronutrient supplementation/fortification among adolescents on health and nutritional status in LMICs, with lack of evidence on nutrition education and counselling and macronutrient supplementation. The findings are generaliseable for adolescent girls since all studies (except one) targeted female adolescents.

Data Collection and Analysis: Two review authors independently assessed trials for inclusion, assessed risk of bias and extracted data from included studies. Metaanalysis was conducted separately for each outcome and intervention. For dichotomous data, we reported risk ratios (RR) with 95% confidence intervals (CI). For continuous data, we reported the mean difference (MD) or standard mean difference (SMD) with 95% CI.
Main Results: This review summarises findings from a total of 10 studies from 15 papers including 10,802 participants. All the studies included in this review assessed the impact of micronutrient supplementation/fortification on health and nutritional status among adolescents in LMIC. We did not find any study assessing the impact of nutrition education and counselling or on macronutrient supplementation among adolescents. Micronutrient supplementation/fortification interventions included calcium/vitamin D supplementation/fortification, iron supplementation with or without folic acid, zinc supplementation and multiple micronutrient (MMN) fortification. The majority of the studies (eight out of 10 studies) included adolescent girls aged between 10 and 19 years of age. We did not find any large scale preventive nutrition intervention programmes targeting adolescents in LMICs. We are uncertain of the effect of iron supplementation with or without folic acid on anaemia (daily supplementation; RR: 1.04, 95% CI 0.88, 1.24; one study; 1,160 participants; low quality evidence. Weekly supplementation; RR: 1.07, 95% CI: 0.91, 1.26; one study; 1,247 participants; low quality evidence). We are uncertain of the effect of various micronutrient supplementation/fortification on body mass index (calcium/ vitamin D supplementation; (MD: −0.01 kg/m 2 ; 95% CI: −1.20, 1.17; two studies; 730 participants; I 2 94%; very low quality evidence, iron supplementation with or without folic acid; MD: 0.29 kg/m 2 ; 95% CI: −0.25, 0.83; two studies; 652 participants; I 2 69%; very low quality evidence, zinc supplementation; MD: 0.35 kg/m 2 ; 95% CI: −0.15, 0.85; one study; 382 participants; very low quality evidence) and MMN fortification; MD: 0.23 kg/m 2 , 95% CI: −0.11, 0.57; two studies; 943 participants; I 2 22%; very low quality evidence). None of the included studies reported any other primary outcomes including morbidity or adverse effects. Iron supplementation with or without folic acid may improve haemoglobin concentrations (MD: 0.42 g/dL, 95% CI: 0.13, 0.71; four studies; 1,020 participants; I 2 89%; low quality evidence). Calcium/vitamin D supplementation may improve serum 25(OH) D levels (standardised mean difference [SMD]: 2.85, 95% CI: 0.89, 4.82; two studies; 395 participants; I 2 99%; low quality evidence). We are uncertain of the effect of calcium only supplementation (MD: 0.02 g/cm 2 , 95% CI: −0.00, 0.04; one study; 233 participants; low quality outcome) and calcium + vitamin D supplementation (MD: 0.02 g/cm 2 , 95% CI: −0.00, 0.04; one study; 235 participants; low quality evidence) on total bone mineral density (BMD). We are uncertain of the effect of MMN fortification on haemoglobin concentrations (MD: −0.10 g/dL, 95% CI: −0.88, 0.68; two studies; 1102 participants; I 2 100%; very low quality evidence); calcium supplementation on total body bone mineral content (BMC); (MD: 30.20 g, 95% CI: −40.56, 100.96; one study; 233 participants; low quality evidence), calcium + vitamin D supplementation on total body BMC (MD: 21.60 g, 95% CI: −45.32, 88.52; one study; 235 participants; low quality evidence) and zinc supplementation on serum zinc levels (SMD: 6.94, 95% CI: −4.84, 18.71; two studies; 494 participants; very low quality evidence). One study reported the impact of iron supplementation with or without folic acid on cognition of adolescent girls suggesting improved cognition in most of the tests with daily or twice weekly supplementation compared to once weekly or no supplementation. None of the other secondary outcomes were reported including any other development outcomes and all-cause mortality. These findings warrant caution while interpreting due to very few studies and high heterogeneity. There are no studies of other preventive measures, that is, macronutrient supplementation or nutrition education and counselling.

| What is this review about?
Malnutrition is one of the most common causes of morbidity and mortality among adolescents and is now considered to be one of the largest risk factors responsible for the global burden of disease, along with poor diet. This review assesses the impact of preventive nutrition interventions (including nutrition education and counselling; micronutrient supplementation/fortification and macronutrient supplementation) to improve the health and nutritional status of adolescents aged 10-19 years in LMICs.

| What is the aim of this review?
This Campbell systematic review summarises findings from 10 studies on preventive nutrition interventions among adolescents in LMICs.

| What studies are included?
To be eligible for inclusion, studies had to be randomised controlled trials (RCTs), quasiexperimental studies, controlled before-after (CBA) studies or interrupted time series (ITS) studies evaluating the effectiveness of preventive nutrition interventions among adolescents between 10 and 19 years of age, from LMICs.
The review summarises evidence from 10 studies from 15 papers, which included 10,802 participants. All the included studies are RCTs assessing micronutrient supplementation and fortification.
Adolescents girls were the intervention groups for all but one of the included studies.
No studies evaluating macronutrient supplementation or nutrition education and counselling were found.
1.1.4 | Do micronutrient supplementation and fortification improve health and nutritional outcomes? 1.1.5 | What do the findings of this review mean?
The evidence on preventive nutrition interventions among adolescents from LMICs is too scarce for any conclusive implications for practice. The existing evidence is limited to micronutrient supplementation/fortification only. There is no evidence on nutrition education and counselling and macronutrient supplementation among adolescents.
Future studies assessing preventive nutrition interventions among adolescents in LMICs should focus on nutrition education and macronutrient supplementation. Future studies should be designed with longer follow-up periods and also assess any adverse effects.
There is a need for large-scale nutrition intervention programme evaluations from LMIC settings. Programmes targeting adolescents in LMICs should also report on contextual factors in planning, implementation and evaluation in light of the WHO health system building blocks. Future studies should target adolescent boys and girls.
1.1.6 | How up-to-date is this review?
The review authors searched for studies published up to February 2019.

| Description of the condition
Malnutrition is one of the most common causes of morbidity and mortality among children and adolescents (UNICEF, 2005) and along with poor diet, it is now considered to be the largest risk factor responsible for the global burden of diseases (Forouzanfar Mohammad et al., 2015). A survey conducted among adolescents aged 12-15 years from 57 LMICs between 2003 and 2013 suggested that the prevalence of stunting was 10.2% while thinness was 5.5% (Caleyachetty et al., 2018). Micronutrient deficiencies account for a substantial global burden of diseases, with iron and vitamin A deficiency being among the 15 leading causes of global morbidity and mortality (WHO 2002). More than 2 billion people, including both children and adolescents, suffer from micronutrient deficiencies in the developing world (Stanger et al., 2009). In 2014, iron deficiency anaemia was one of the three most common causes of disability-adjusted life years (DALYs) lost among adolescents along with other micronutrient deficiencies accounting for over 2,500 DALYs per 100,000 adolescents (Akseer, Al-Gashm, Mehta, Mokdad, & Bhutta, 2017;WHO, 2014).
Adolescence is a critical age group with key changes in health and its determinants later in life. Adequate nutrition is vital for transition from adolescence to healthy adults as the consequences of malnutrition among children and adolescents include delayed growth, impaired cognitive maturation, lower intellectual quotient, behavioural problems and increased risk of contracting communicable diseases (Mengistu, Alemu, & Destaw, 2013;Onyango, 2013). There are many underlying determinants of undernutrition including poverty, food insecurity, poor sexual and reproductive health, violence, and many infectious and noninfectious diseases (Patton George et al., 2016). The quality of available diets in LMICs is also a challenge as diet is fairly restricted and comprises largely of cereals or legumes with few animal products and a limited access to a variety of fruits and vegetables (Ladipo Oladapo, 2000). Poverty in these settings also leads to limited ability to purchase and consume sufficient amounts of key nutrients. Food insecurity in these settings has also been linked to poor diet quality and uncertainty in the food environment related to inability to access adequate food sources for the sustainability of healthy and active living (Akseer et al. 2017). Food choices and preferences are also determinants of malnutrition since in some settings, despite adequate food access, dietary choices lead to nutritional deficiencies. Adolescents globally are consuming less than adequate amounts of fruits and vegetables and alarmingly high levels of sodium and sugar (Akseer et al. 2017). These poor dietary habits and eating choices pose further threat to the growing bodies.
The burden of malnutrition is further complicated for women and girls in LMIC settings owing to the their status and power in society compared to their male counterparts (Jayachandran, 2015).
Micronutrient deficiency is often referred to as hidden hunger and has a global health impact on adolescents because its manifestations are less visible and usually begins to show when the condition is severe and has already led to serious health consequences. A number of nutrition-specific interventions to address malnutrition have been advocated and these include nutrition education and counselling, micronutrient supplementation, food fortification and macronutrient supplementation.

| Description of the intervention
The following interventions (alone or in combination) have been advocated to prevent nutrition deficiencies: • Nutrition education and counselling • Micronutrient supplementation and fortification • Macronutrient supplementation

| Nutrition education and counselling
Dietary habits of adolescents are influenced by various factors including food environments, food advertisements, mass media messages, peers and social eating culture (Riebl Shaun et al., 2015;Stang Jamie and Stotmeister, 2017). Nutritional concerns among adolescents include poor dietary habits; low intake of fruits, vegetables, fibre and calcium-rich foods; high intake of foods high in fat and sugar; unhealthy dieting; and erratic eating behaviours, such as meal skipping (Stang Jamie & Stotmeister, 2017).
Nutrition education and counselling is a widely used strategy to improve nutritional status and change nutrition related behaviours (Story, Lytle Leslie, Birnbaum Amanda, & Perry Cheryl, 2002). The strategy focuses primarily on promoting a healthy diet by increasing the diversity and amount of foods consumed. Nutrition education can help young people attain the knowledge and skills they need to make healthful food choices and develop lifelong healthy eating patterns.
Food fortification is the process in which micronutrients are added to processed foods. In many stances, this approach has lead to ameliorating micronutrient deficiencies in the population with reasonable cost making it a very efficient public health intervention.
Fortification could be mass fortification (that is adding micronutrients to foods that are commonly consumed such as flour, salt, sugar and cooking oil) or point-of-use fortification (that involves adding single-dose packets of vitamins and minerals in powder form that can be sprinkled onto any ready to eat food consumed at home, school, nurseries, refugee camps or any other place where possible) (WHO, 2014;Zlotkin Stanley et al., 2005).

| Macronutrient supplementation
Macronutrient interventions include supplementary feeding, balanced energy and protein supplementation and lipid based nutrition supplementation (LNS). Supplementary feeding is the provision of extra food to children or families beyond the normal ration of their home diets, and can take place in homes, feeding centres, healthcare centres and schools (Sguassero, de Onis, Bonotti Ana, & Carroli, 2012). Energy protein supplements are used to increase the total daily protein and calorie intake in order to aid nutrition and it involves supplements in which protein provides <25% of the total energy content. These are available in both oral and parenteral form. Oral supplements could be in the form of whole protein milk and beverages. These supplements also contain a wide range of micronutrients which may benefit the consumer. LNS are a family of products in which majority of the energy is from lipids; they also include protein and essential fatty acids and a range of micronutrients (Dewey Kathryn, & Arimond, 2012).
2.3 | How the intervention might work 2.3.1 | Nutrition education and counselling Nutritional concerns among the adolescent age group make them vulnerable to environmental influences and consequent unhealthy eating behaviours (Riebl Shaun et al., 2015;Stang Jamie & Stotmeister, 2017). Therefore, promotion of healthy nutrition during adolescence is vital to inculcate sustainable healthy dietary habits.
Nutrition education and counselling at this stage can create knowledge through active, fun and interactive processes and promote behaviour changes in food attitudes and practices (Baldasso, Galante Andrea, & De Piano Ganen, 2016). Such programmes can increase adolescents' ability to understand proper food practices and encourage them to actively adopt healthy food habits. It is important to note that nutrition education and counselling alone have higher chances of success if there are no other serious constraining factors in terms of access to foods and the intervention is appropriately designed for the target population group (Harrison, 2010). There is some evidence that in relatively advantaged populations, targeted educational approaches can work well (Contento et al., 1995;Harrison, 2010). If provided under ideal circumstances, nutrition education and counselling have the potential to address multiple nutrient deficiencies without the risks of toxicity and interactions.

| Micronutrient supplementation and fortification
Direct supplementation of vulnerable subpopulations with micronutrients, usually through a primary healthcare system or healthcare delivery system such as an immunisation programme, has been shown to be effective and cost-effective. A direct supplementation approach through a healthcare delivery system has the advantage of directly reaching portions of the population most at risk while not putting other segments of the population at risk of over consumption or adverse interactions (Harrison, 2010). The long-term disadvantages, however, relate primarily to sustainability, coverage and compliance. Supplementation depends upon a viable delivery system with built-in quality control, as well as wide coverage and high uptake rates among vulnerable individuals and families. Supplementation only works if the supplements are available and accessible and the intended individuals actually take them. The risks of using dietary supplements might include organ damage from inherent toxicity, interactions or product contamination (Harrison, 2010). SALAM ET AL.

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The advantage of food fortification, provided that safe and effective levels of the relevant nutrients can be delivered through an appropriate food vehicle, is that no or minimal behaviour change is required on the part of the population. This provides a tremendous advantage in terms of coverage and efficiency. Food fortification adopts an integrated approach and provides support to improve micronutrients malnutrition when other existing food supplies fail to do so (Allen, De Benoist, Dary, Hurrell, & World Health Organization, 2006).

| Macronutrient supplementation
Supplementary feeding, balanced energy and protein supplementation and LNS are designed to increase the total daily protein and calorie intake in order to aid nutrition (Sguassero et al., 2012). Supplementary feeding can improve the quality and quantity of the daily nutritional intake by providing additional calories, minerals and vitamins consequently leading to better nutritional status, however there are issues of compliance, improving coverage and sustainability. Although food supplementation can aid in improving current nutritional situation, it is not a solution to the primary health and nutritional problems faced by families living in poverty. Macronutrient interventions have many of the same problems as micronutrient interventions including sustainability, coverage and compliance.
We aim to assess the impact of these interventions alone or in combination on adolescent health and nutrition status in LMIC. There is an increasing evidence that health initiatives require health systems that can deliver services equitably and efficiently; and thus, many global health initiatives now involve health systems strengthening measures into their programmes (WHO, 2010). Therefore, we also aim to assess various health system components using the World Health Organisation (WHO) health system building blocks framework (WHO, 2010). This will aid the understanding of how these areas are utilised in planning and delivering equitable and contextually appropriate nutrition interventions for adolescents.

| Why it is important to do this review
Malnutrition is one of the most common causes of morbidity and mortality among children and adolescent population worldwide (UNICEF, 2005); half of the global child mortality is attributable to malnutrition (IGME, 2017). With about one quarter of the total world population (1.8 billion people) comprising adolescents and young adults (Ameratunga, 2017;UNPFA, 2014); it has become even more important to identify effective interventions targeting adolescents to improve their health and nutrition status to ensure sustainable healthy behaviours along with healthy growth and development (Sawyer Susan et al., 2012).
Globally, there is an increased focus on adolescents and youth as reflected by the sustainable development goals. Existing systematic reviews assessing the impact of nutrition interventions among adolescents are either not comprehensive (assessing a single intervention or a specific micronutrient); have overlapping age groups (includes children and youth along with adolescents); or are focused on female adolescents only (Lassi Zohra, Anoosh, Das Jai, Salam Rehana, & Bhutta Zulfiqar, 2017;Salam Rehana et al., 2016). The majority of the existing systematic reviews have restricted their included studies to randomised trials without focusing on various contextual factors that might potentially impact the effect of nutrition interventions in this age group. Moreover, the impact of nutrition education and counselling in this age group has not been systematically reviewed. Table 1 describes the existing systematic reviews.
This review aims to comprehensively evaluate the effectiveness of all the above mentioned preventive nutrition interventions in combination or alone. We aim to include large-scale programme evaluations that are implemented in multiple communities targeting adolescents with the above mentioned nutrition interventions. We also aim to assess various contextual factors that might potentially influence the effectiveness of these nutrition interventions in this age group. This contextual information will be based on the WHO health system building blocks framework describing health systems in terms of six core components: service delivery, health workforce, health information systems, access to essential medicines/supplies, financing and leadership/governance (WHO, 2010). Findings from this review will assist the policy makers in designing contextually appropriate nutrition intervention initiatives targeting this important age group.

| OBJECTIVES
The objective of this review is to assess the impact of preventive nutrition interventions (including nutrition education and counselling, micronutrient supplementation/fortification and macronutrient supplementation) to improve the health and nutritional status of adolescents aged 10-19 years of age in LMICs.
The secondary objective of the this review is to assess the various contextual factors based on the WHO health system building blocks framework that might potentially impact the effectiveness of these interventions in this age group. We included primary studies, including large-scale programme evaluations, using experimental and quasiexperimental study designs.
The following study designs were eligible for inclusion: • Randomised controlled trials including both cluster and individual level randomisation • Quasiexperimental studies with nonrandom assignment to intervention and comparison groups • Controlled before-after studies in which observations are made before and after the implementation of an intervention, both in a group that receives the intervention and in a control group that does not.
• Interrupted time series studies that uses observations taken at least three time points before and after an intervention to detect whether the intervention has had an effect significantly greater than any underlying trend over time.
We intended to include quasiexperimental study designs, such as CBA and ITS, along with RCTs since we intended to assess the effectiveness of large scale programme evaluations that might not have been conducted in a randomised design. Moreover, we also intended to assess various contextual factors based on the WHO health system building blocks as they could potentially impact the uptake and effectiveness of these interventions.

| Types of participants
The target population was adolescents between 10 and 19 years of age from LMICs. We classified LMIC according to the World Bank criteria (World Bank). We excluded studies conducted specifically among hospitalised adolescents and adolescents with any preexisting health conditions. Studies including only a subset of eligible participants were included only if the results provided information for the relevant subgroup separately.

| Types of interventions
The following interventions alone or in any combination were reviewed: • Nutrition education and counselling (provision of general information related to health with or without nutrition assessment, identification of individual nutrition needs and goals and discussing ways to meet those goals provided in any setting) • Micronutrient supplementation and fortification (any micronutrient alone or in combination)

• Macronutrients supplementation
We analysed different individual interventions separately and studies assessing a combination of interventions were also analysed separately. Eligible comparisons were no intervention or placebo (whatever was applicable in the setting where study was conducted).

| Types of outcome measures
We included all of the studies that met our inclusion criteria, but only those studies that had the outcomes defined below were included in the meta-analysis.

Primary outcomes
• Anaemia (haemoglobin concentrations <12 g/dL) • Body mass index (defined as weight in kg divided by height in metres squared) • Morbidity (any morbidity as reported by the study authors for, e.g., infectious diseases, night blindness, etc.) • Adverse effects (as reported by study authors)

Secondary outcomes
• Haemoglobin concentration (measured in any units) • Micronutrient status (measured in any units) • Body composition (measured in any units) • Development outcomes (as reported by authors; could include cognitive development, interpersonal development and social development) • All-cause mortality

Duration of follow-up
We included studies with any duration of follow-up.

Type of settings
We included studies conducted in community, facility or school settings in LMICs. The trials registry Clinicaltrials.gov was searched for ongoing trials. We searched Google Scholar along with key nutrition agencies database such as Nutrition International (https://www.nutritionintl. org/), the Global Alliance for Improved Nutrition (https://www. gainhealth.org/homepage), the World Food Programme (https:// www.wfp.org/) and HarvestPlus (https://www.harvestplus.org/) to search for nonindexed, grey literature to locate relevant programme evaluations and any additional trials. We did not apply any restrictions based on publication date, language or publication status.

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Search strategies for MEDLINE, CENTRAL and CINAHL is added as Appendix 1; we used the same search strategy for other search engines.

| Searching other resources
We made every effort to contact relevant organisations and experts in the field to identify unpublished or ongoing studies. We also searched Eldis.org to find organisations with an interest in nutrition.
References of included articles, relevant reviews and annotated bibliographies were scanned for eligible studies. We conducted forward citation searching of included studies in Google Scholar to identify any recent studies missed from the database searches.

| Selection of studies
Two reviewers (O. I. and W. A.) independently screened titles and abstracts in duplicate. We pilot-tested the screening criteria at both title and abstract screening stage and full text stage. We used the PRISMA flow diagram to report eligibility of studies. We retrieved the full text of all studies which passed this first level screening. The full text review were also done in duplicate by two reviewers, and agreement was reached by consensus.
Disagreements were resolved by consultation with a third reviewer (S. S.). We collated multiple reports of the same study, so that each study rather than each report was the unit of interest in the review. We examined any relevant retraction statements and errata for information.

| Details of study coding categories
Two review authors (R. A. S. and O. I.) extracted data independently and a third review author (J. K. D.) checked for reliability and resolved any conflict. We extracted the primary data for the study characteristics including details of the populations, setting, sociodemographic characteristics, interventions, comparators, outcomes and study design in duplicate. Disagreements were resolved by discussion or consultation with a third reviewer.
The following information was extracted for each included study: • Background: time period when study took place, type of publication (e.g., full-text journal article, abstract, conference paper, thesis), study country or countries • Population and setting: population age and setting • Methods: Study design, description of study arms, unit of allocation, sample or cluster size per study arm (for individually or cluster randomised trials respectively), start and end date, follow up • Participants: total number randomised/allocated, sample representativeness, baseline characteristics, number of withdrawals, sociodemographic data • Intervention group details: number randomised/allocated to group, description of intervention, duration and follow-up, timing, delivery of intervention, providers and their training. We described all the study intervention arms in the tables of included studies, however, we only reported the intervention arms that met review inclusion criteria.
• Comparison group details: number randomised to group, description of comparison, duration and follow-up, timing, providers and their training • Outcomes: measurement tool, validation of the tool, total number in intervention and comparison groups, change indicated at each time point • Other information: study start date, study end date, funding sources and conflict of interest.
In addition to the above mentioned details, we also collected details related to the programme related contextual factors. This information was based on the WHO health system building blocks framework describing health systems in terms of six core components (WHO, 2010): • Service delivery: The availability of health services including all services dealing with the delivery of nutrition interventions.
• Health workforce: The availability of sufficient and capable staff to deliver nutrition interventions.
• Health information systems: The availability of the production, analysis, dissemination and use of reliable and timely information on health and nutrition related determinants and status.
• Access to essential medicines/supplies: The availability of nutrition intervention related commodities and supplies in adequate amounts, in the appropriate dosages and at an affordable price.
• Financing: The sources of funds available for the delivery of nutrition interventions.
• Leadership/governance: The roles and responsibilities of various sectors including public, private and voluntary sectors in implementing the nutrition interventions.

| Assessment of risk of bias in included studies
For RCTs we used the Cochrane risk of bias tool (Higgins & Green, 2011) which assesses selection bias, performance bias, detection bias, attrition bias and reporting bias. We rated each component as "high", "low" or "unclear" for each risk of bias component. For nonrandomised studies, we used the Cochrane Effective Practice and Organisation of Care (EPOC) risk of bias criteria (based on additional criteria including similar baseline outcome measurements, similar baseline characteristics, knowledge of the allocated interventions adequately prevented during the study, protection against contamination, intervention independent of other changes, shape of intervention effect prespecified and intervention unlikely to affect data collection) and rated the studies as low risk, high risk or unclear risk (EPOC, 2017). We provided supporting evidence for the risk of bias judgements.Two independent reviewers performed quality appraisal for each study and disagreements were resolved by discussion or consultation with a third reviewer. We summarised the quality of evidence according to the outcomes as per the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria (Walker, Fischer-Walker, Bryce, Bahl, & Cousens, 2010). A grade of "high", "moderate", "low" and "very low" was used for grading the overall evidence indicating the strength of an effect on specific health outcome based on methodological flaws within the component studies, consistency of results across different studies, generalisability of research results to the wider patient base and how effective the treatments have shown to be (Balshem et al., 2011). For nonrandomised studies, the evidence quality was upgraded based on large magnitude of effect, dose-response relationship and effect of all plausible confounding factors would be to reduce the effect (where an effect is observed) or suggest a spurious effect (when no effect is observed). Two reviewers discussed ratings and reached consensus, and disagreements were resolved by consulting a third reviewer. We developed a summary of findings table to show the effects for the primary outcomes.

| Synthesis procedures and statistical analysis
The following synthesis procedures and analysis methods were used:
For dichotomous data, we used odds ratios (OR), and risk ratios (RR) with 95% confidence intervals (CI). For continuous data, we used the mean difference (MD) with 95% CI, if outcomes were measured in the same way between trials. We used the standardised mean difference (SMD) with 95% CI to combine trials that measured the same outcome but used different methods of measurement.

| Unit of analysis issues
Before initiating the synthesis, we ensured that all articles reporting on the same study were appropriately linked. To ensure independence and appropriate combination of outcome constructs, we synthesised the data according to the type of interventions specified above. If multiarm studies were included, we combined intervention groups or separated into different forest plots, and ensured that there was no double counting of participants. If an outcome was reported in several different metrics, we performed unit conversions in order to pool the data. We anticipated differences in the types of literature and ensured that any analysis take possible sources of dependency into account by grouping papers into studies and ensuring that no double counting of evidence took place when synthesising across studies.
Two trials (Agarwal, Gomber, Bisht, & Som, 2003;Zhu et al., 2005) reported the outcomes of interest at multiple time points, we coded the data for outcomes from all reported time points and then reported the the outcomes from the time point closest to other studies. Where trials used clustered randomisation, we anticipated that study investigators would have presented their results after appropriately controlling for clustering effects (e.g., variance inflated standard errors, hierarchical linear models). If it was unclear whether a cluster-RCT had appropriately accounted for clustering, we planned to contact the study investigators for further information. Where appropriate controls for clustering were not used, we requested an estimate of the intra-class correlation coefficient. We used the "inflated standard error" approach to calculate the correct estimates by multiplying the standard error with the square root of the design effect (Higgins, Altman, & Sterne, 2011a).

| Dealing with missing data
If the outcome of interest did not include data on all participants, we first contacted the study authors via email to inquire about data for the missing cases. Missing data, if found, were reincluded in the analysis. If we were unable to find the missing data, we analysed data for only those participants whose results were available, and addressed the impact of the missing data in the assessment of risk of bias. Only one study ) had high attrition (29% loss to follow-up) and we analysed data for only those participants whose results were available.

| Assessment of heterogeneity
We assessed heterogeneity among studies in two ways. Firstly, we assessed heterogeneity at face value: heterogeneity in population, interventions, or outcomes. We used I 2 , Q and τ 2 statistics as a guide to assess heterogeneity along with a visual inspection of forest plots.

| Assessment of reporting biases
There were only nine studies included in this review; therefore we could not assess for the reporting bias. For future updates funnel plots would be used if there are 10 or more studies in meta analysis for one outcome and investigation will be conducted for reporting biases, for example, publication bias.

| Data synthesis
A meta-analysis was conducted separately for each outcome and intervention. Furthermore, for each outcome, we separately metaanalysed different study designs (RCT, ITS and CBA). We pooled data from studies we judged to be clinically homogeneous, if more than one study provided usable data in any single comparison, we performed a meta-analysis. We standardised all the reported effect sizes as RRs for the dichotomous outcome and MDs or SMDs for the continuous outcomes. We attempted to standardise the outcomes as a common metric and synthesised together, where possible. We carried out statistical analysis using the Review Manager software (Revman, 2014). We used random-effects meta-analysis for combining data to produce an overall summary, since we expected reasonable clinical heterogeneity in interventions, comparisons, outcomes and settings within the studies included. The randomeffects summary was treated as the average of the range of possible treatment effects and we discussed the clinical implications of treatment effects differing between trials. We reported statistical heterogeneity as I 2 , Q and τ 2 statistics for all random-effects metaanalyses. We narratively synthesised and reported the findings on the contextual factors based on the WHO health system building blocks framework for each intervention.

| Subgroup analysis and investigation of heterogeneity
Based on the availability of the data, we had planned to conduct subgroup analysis for following subgroups: • Duration or intensity of intervention (e.g., short vs. long term, oneoff vs. multiple sessions).
• Individual context versus group context (for nutrition education and counselling only, that is, children receiving the intervention individually vs. those in groups) • Study setting: school, community, clinic, and so forth.
• Sex: Male and females.
• Population (e.g., urban population vs. rural population; resource poor vs. resource rich population) • We also attempted to conduct subgroup analysis based on the WHO health system building blocks factors (where data was available).
However, since very few studies were included in each comparison within the review, we could not conduct any of the afore mentioned subgroup analysis. We did, however, subgrouped the outcomes according to the specific micronutrients being supplement under the comparison of "Micronutrient Supplementation/Fortification" for clarity. For future updates, we plan to assess difference in subgroups based on the methodology described in the Cochrane Handbook (Higgins & Green, 2011) by using a simple approach for a significance test to investigate differences between two or more subgroups. We will undertake a standard test for heterogeneity across subgroup results using χ 2 test or moderator analysis rather than across individual study results.

| Sensitivity analysis
We had planned to conduct sensitivity analyses to consider the impact of the following: • Allocation concealment (adequate vs. inadequate and/or unclear).
However, since very few studies were included in the review, we could not conduct any sensitivity analysis.

| Treatment of qualitative research
We did not include qualitative studies.

| Description of studies
See Characteristics of included studies; Characteristics of excluded studies; Characteristics of studies awaiting classification.

| Results of the search
We identified a total of 665 potentially relevant titles from the search. After removing duplicates, we screened 650 records for eligibility and excluded 597 articles on the basis of titles and abstracts. We obtained the full-text reports of the remaining 53 records, and of these, excluded 38 and included 15 papers (10 studies) in the review. Figure 1 depicts the search flow diagram.

Participants
The majority of the studies (eight out of 10 studies) included adolescent girls aged between 10 and 19 years of age. Hettiarachchi et al. (2008) included both female and male adolescents from 12 to 16 years of age. Soekarjo et al. (2004) included both adolescent girls and boys aged 12-15 years. Zhu et al. (2005) was conducted among girls aged 10-12 years of age; Khadilkar et al. (2010) included girls 14 to 15 years of age; Sen (2009) included girls 9-13 years of age; Agarwal et al. (2003) included girls 10-17 years of age; Chiplonkar and Kawade (2012) and Goyle (2012) included girls 10-16 years of age. Two studies mentioned that the participants were adolescent girls but did not specify the age group; the mean age of adolescent girls in Hyder et al. (2007) was 12 years; while Februhartanty et al. (2002) included postmenarchal female adolescent girls with mean age 14.6 years.
Three of the studies had multiple intervention arms:  Contextual factors based on the WHO health system building blocks framework All the included studies were RCT and we did not find any large scale nutrition intervention programmes targeting adolescents from LMICs. We have narratively synthesised the findings from the six health system building blocks based on WHO health system building blocks framework (Table 2) (2012) and Zhu et al. (2005) did not clearly specify the workforce utilised for the nutrition intervention delivery; however from the description it appeared that the intervention was probably delivered through school teachers.
Health information system. None of the included studies specified the details pertaining to health information systems.
Access to essential medicines/supplies. In all of the included studies, the nutrition supplement was provided by the researcher.

| Excluded studies
Out of these 38 studies, participants in four studies (Manger et al., 2008;Prentice et al. 2012;Rerksuppaphol & Rerksuppaphol, 2016;Sarma et al., 2006) included both children and adolescents. We wrote emails to these four authors to obtain data for the adolescent subgroup. We received response from Manger et al. 2008 stating that the number of adolescents was too small while three (Prentice et al. 2012;Rerksuppaphol & Rerksuppaphol, 2016;Sarma et al., 2006) of the other authors did not respond to the emails and hence these studies were excluded from the review.
The major reasons for exclusion were that the study design was not appropriate; the intervention was therapeutic and/or that the studies were conducted in countries other than LMIC. Please see Characteristics of excluded studies.

| Risk of bias in included studies
Overall the included studies were judged to be at unclear risk of bias due to insufficient information regarding sequence generation and allocation concealment. The majority of the studies lacked blinding and were judged to be at high risk or unclear risk for blinding. The majority of the studies were at low risk of bias for incomplete outcome data, selective reporting and other biases. The summary of the risk of bias across the included studies is shown in

| Allocation (selection bias)
Only one study (Hyder et al., 2007) was judged to be at low risk of bias for sequence generation and allocation concealment. All other studies (Agarwal et al., 2003;Chiplonkar & Kawade, 2012;Februhartanty et al., 2002;Goyle, 2012;Hettiarachchi et al., 2008;Khadilkar et al., 2010;Soekarjo et al., 2004;Zhu et al., 2005) were judged to be at unclear risk of bis due to insufficient information regarding the methods for sequence generation and allocation concealment.

| Blinding (performance bias and detection bias)
For the blinding of participants and personnel, five studies (Februhartanty et al., 2002;Hettiarachchi et al., 2008;Hyder et al., 2007;Khadilkar et al., 2010;Zhu et al., 2005) were judged to be at low risk of bias for blinding of participants and personnel; while five studies (Agarwal et al., 2003;Chiplonkar & Kawade, 2012;Goyle, 2012;Soekarjo et al., 2004) were rated to be at high risk due to lack of blinding of participants and personnel.
For blinding of outcome assessors, three studies (Hyder et al., 2007;Khadilkar et al., 2010;Zhu et al., 2005) were judged to be at low risk of bias, three studies (Agarwal et al., 2003;Chiplonkar & Kawade, 2012;Hettiarachchi et al., 2008) were rated to have unclear risk of bias, while four studies (Februhartanty et al., 2002;Goyle, 2012;Soekarjo et al., 2004) were rated to be at high risk of bias due to absence of blinding of the outcome assessors.

| Incomplete outcome data (attrition bias)
All studies except one ) were judged to be at a low risk of attrition bias.  had about 30% overall loss to followup rate.

| Selective reporting (reporting bias)
None of the included studies mentioned information regarding trial registration and we did not find any prior published protocol for any of the included studies. The studies were judged to be at low risk of selective reporting since the outcomes specified in the methodology section have been reported in the results section.

| Comparison 1: Nutrition education and counselling
We did not find any study assessing the impact of nutritional education and counselling on health and nutritional status among adolescents in LMICs.

| Comparison 2: Micronutrient supplementation and fortification (any micronutrient alone or in combination)
A total of 15 papers from 10 studies including 10,802 participants assessed the impact of micronutrient supplementation/fortification. Two studies (Khadilkar et al., 2010;Zhu et al., 2005) assessed calcium/vitamin D supplementation/fortification; four studies (Agarwal et al., 2003;Februhartanty et al., 2002;Hettiarachchi et al., 2008;) assessed iron supplementation with or without folic acid; two studies (Chiplonkar & Kawade, 2012;Hettiarachchi et al., 2008) assessed zinc supplementation; while three studies assessed MMN fortification (Chiplonkar & Kawade, 2012;Goyle, 2012;Hyder et al., 2007). Two of the studies had multiple intervention arms and were included in multiple comparison groups. Chiplonkar and Kawade (2012) provided MMN fortified snack in one group and zinc supplement in the other group while Hettiarachchi et al. (2008) provided iron supplement in one group while zinc supplement in the other group.

Primary outcomes
Among the primary outcomes, included studies reported anaemia and BMI. None of the included studies reported on any other primary outcome, including morbidity or adverse effects.
Development outcomes: Single study result. One study  reported the impact of iron supplementation with or without folic acid on cognition of adolescent girls suggesting improved digit span scores, clerical task scores, visual memory test scores and maze test scores in daily or twice weekly supplementation compared to once weekly or no supplementation (Analysis 1.8; Figure 7).

| Comparison 3: Macronutrients supplementation
We did not find any study assessing the impact of macronutrient supplementation on health and nutritional status among adolescents in LMICs. These findings warrant caution in interpretation due to the fact that there were very few studies and most had high heterogeneity and since they quality of the outcomes were either low or very low these can only be seen as preliminary findings. Moreover, we could The findings are generaliseable mainly for adolescent girls since all studies (except two) targeted female adolescents.
Since we did not find any large scale programmes assessing preventive nutrition interventions for adolescents in LMIC, we could not conduct an in-depth analysis of the contextual factors that might potentially impact the effect of nutrition interventions in this age group in the light of the WHO building blocks. Almost all the included studies reported "service delivery", "health workforce", "access to essential medicines/supplies", "financing" and "leadership/governance" while none of the included studies reported on "health information systems". Findings from the included studies suggest that in LMICs, school based delivery of nutrition interventions remains the most utilised platform to target adolescents since the service delivery platform in all the included studies was school while the "health workforce" included school teachers and class monitors in majority of the included studies. The leadership and governance in almost all the studies remained under the researchers while financing was provided by various not-for-profit organisations. None of the included studies reported any information regarding "health information system"; since the data control ad monitoring was limited to the study period and were as per protocol and planned by the

| Quality of the evidence
Overall, the included studies were judged to be at unclear risk of bias due to insufficient information regarding sequence generation and allocation concealment. Majority of the included studies lacked blinding and were judged to be at high risk or unclear risk for blinding. Majority of the studies were at low risk of bias for incomplete outcome data, selective reporting and other biases.
The quality of the evidence was rated to be low to very low. The outcome quality was downgraded due to study limitations, including unclear sequence generation and allocation concealment methods and lack of blinding; high heterogeneity and imprecision.

| Potential biases in the review process
The potential biases in the review process were that this type of review requires to make a number of subjective judgements and others may have reached different decisions regarding assessments of eligibility and risk of bias. We have tried to minimise these in two ways: (a) eligibility for inclusion and data extraction were assessed independently by two review authors and (b) assessments of risk of bias and data entry were also assessed independently by two review authors. We would encourage readers to examine the Characteristics of included studies tables to assist in the interpretation of results.

| Agreements and disagreements with other studies or reviews
Two systematic reviews by Salam Rehana et al. (2016) andLassi Zohra et al. (2017) assessed the effects of micronutrient supplementation. Both the reviews concluded that iron-folic acid supplementation reduces anaemia; while our review findings are uncertain regarding any impact on anaemia with iron-folic acid supplementation. The difference between these reviews and our review is that these reviews included youth (15-24 years of age) along with the adolescents while our review was restricted to the adolescent age group only. Many of the studies included in these reviews were excluded from our review due to the age cut-offs.
Therefore, the number of eligible studies in these reviews was greater than our review and our findings for anaemia is based on a single study. Futhermore, these reviews included studies from upper middle income and high income countries along with LMIC while our review only included studies conducted in LMICs.
The review by Das et al. (2013) assessed the impact of micronutrient fortification. This review concluded that MMN fortification significantly improved anaemia and haemoglobin concentrations; however this review also included overlapping age groups of children and adolescents and studies from upper middle income and high income countries.
There were very few studies in each comparison in our review and that could be the reason that we could not find any definite evidence on the outcomes.

| Implications for practice
The evidence on preventive nutrition interventions among adolescents from LMICs is too scarce for any conclusive implications for practice. The existing evidence is limited to micronutrient supplementation/fortification only while there is no evidence on nutrition education and counselling and macronutrient supplementation among adolescents.

CONFLICT OF INTERESTS
The authors declare that there are no conflict of interests.

DIFFERENCES BETWEEN PROTOCOL AND REVIEW
We could not conduct any of the prespecified subgroup analysis and sensitivity analysis due to very few studies included in the each comparison in the review. Control group did not receive any tablets during the intervention period and haemoglobin was estimated at 115 ± 5 days. They were thereafter given 100 tablets with advice to take 1 tablet daily for 100 days (N = 691) Inclusion criteria: Apaarently healthy adolescent girls Exclusion criteria: Girls who were ill or had in the recent past any illness such as fever, respiratory or gastrointestinal infection, or those undergoing medical treatment, or taking multivitamin mineral supplements were identified and excluded from the study

Interventions
Intervention (sample size): Intervention group 1 (N = 60) Supplement was provided in the form of six different snacks to each girl with one snack (average amount 100 g/serving) per day for 6 school days in a week. The average zinc content of the food supplements was 2.2 ± 0.4 mg/serving Intervention group 2 (N = 59) The ayurvedic zinc tablet containing 20 mg of jasad bhasma, equivalent to 16.6 mg of elemental zinc, was given to each girl every day for 6 school days/week under the guidance of an ayurvedic doctor The intervention was provided for a duration of 10 weeks Control (sample size): Control group (N = 53) No supplements given to control

Outcomes
Primary outcomes: Dietry intake, haemoglobin levels, plasma zinc, plasma beta-carotene, plasma retinol, plasma vitamin C Secondary outcomes: Not specified Timing of outcome assessment: After 10 weeks of intervention The iron tablet used in this study contained 60 mg elemental iron and 0.25 mg folic acid in the form of 200 mg ferrous sulphate Group 1: Weekly iron tablets (N = 50) Group 2: Iron tablet for four consecutive days during their menstruation cycle (N = 50) Control (sample size): Placebo tablet (N = 50) The supplementation was conducted over 16 weeks under the supervision of teachers appointed from the participating schools and the first author. To control parasitic infestation, all subjects were given a single dose of 500 mg mebendazole three days before supplementation   Unclear risk Quote: "Adolescents from 15 schools (four U-MTs, seven U-SMP and four R-SMP) (n = 2990) were randomly selected to receive weekly supplements, while adolescents in the other nine schools (three U-MTs, two U-SMP and four R-SMP) served as controls (n = 1750)." Comment: Insufficient information to permit judgement.

Allocation concealment (selection bias)
Unclear risk Quote: "In each of the schools receiving supplements, each of the three grades was randomly allocated to receive one of the three supplementation regimes." Comment: Insufficient information to permit judgement.
Blinding of participants and personnel (performance bias) High risk Quote: "All pupils were aware of which supplement they were taking and they were told that the supplements would improve their health and prevent/cure anaemia" Comment: Not done Blinding of outcome assessment (detection bias) High risk Quote: "All pupils were aware of which supplement they were taking and they were told that the supplements would improve their health and prevent/cure anaemia" Comment: Not done Abbreviations: BMI, body mass index; CI, confidence interval; MD, mean difference; MMN, multiple micronutrient; RR, risk ratio. *The basis for the assumed risk (e.g., the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI).