research about malnutrition in the philippines

Undernutrition in the Philippines: Scale, Scope, and Opportunities for Nutrition Policy and Programming

January 30, 2021--Filipino children stand next to each other at a slum area in Quezon City, Metro Manila, Philippines.

Ezra Acayan/World Bank

Key Findings

• For nearly thirty years, there have been almost no improvements in the prevalence of undernutrition in the Philippines. One in three children (29%) younger than five years old suffered from stunting (2019), being small in size for their age.
• The country is ranked fifth among countries in the East Asia and Pacific region with the highest prevalence of stunting and is among the 10 countries in the world with the highest number of stunted children.
• There are regions with levels of stunting that exceed 40% of the population. In Bangsamoro Autonomous Region in Muslim Mindanao 45% of children below five are stunted, in Southwestern Tagalog Region (MIMAROPA) 41%, Bicol Region it is 40%, Western Visayas 40%, and in the south-central Mindanao Region (SOCCKSARGEN) 40%
• Micronutrient undernutrition is also highly prevalent in the Philippines: 38% among infants six to 11 months old; 26% among children 12–23 months; and 20% of pregnant women are anemic. Nearly 17% of children aged 6–59 months suffered from vitamin A deficiency (2018), of which children aged 12–24 months had the highest prevalence (22%) followed by children aged six to 12 months (18%).
• The persistence of very high levels of childhood undernutrition, despite decades of economic growth and poverty reduction, could lead to a staggering loss of the country’s human and economic potential. A Filipino child with optimal nutrition will have greater cognitive development, stay in school longer, learn more in school, and have a brighter future as an adult, while undernutrition robs other children of their chance to succeed.
• The burden on the Philippine economy brought by childhood undernutrition was estimated at US$4.4 billion, or 1.5% of the country’s GDP, in 2015.
• The country’s Human Capital Index (HCI) of 0.52 indicates that the future productivity of a child born today will be half of what could have been achieved with complete education and full health.
• In 2013, it was estimated the benefit cost ratio for nutrition investments in the Philippines at 44 (Figure 3.2). In other words, every dollar invested in nutrition has the potential of yielding a $44 return. A lower estimate projecting the benefits accruing from a nutrition intervention scenario (NIS) at the national level through key nutrition-specific interventions rolled out over ten years at full coverage reaches US $12.8 billion over a 10-year period with a corresponding cost of $1,062 million, yielding a benefit cost ratio of 12:1.
• Hunger in the Philippines rose sharply following the start of the pandemic. Social Weather Stations (SWS) surveys show that in September 2020, after seven months of community quarantine, 31% of families reported experiencing hunger in the past 30 days, and 9% were suffering severe hunger—in both cases, the highest levels recorded in more than 20 years.
• The key determinants of undernutrition are multisectoral. At the immediate level, a child becomes undernourished because of inadequate or inappropriate food, health, and care.
• At the basic level, poverty is one of the most important causes of undernutrition: 42.4% of children from households in the poorest income quintile are stunted. Governance structures also pose significant challenges for the country’s efforts to combat undernutrition. 

Policy and programmatic actions to address the challenge of reducing childhood undernutrition:

• Strengthen the National Nutrition Council to provide the supervisory and oversight capacities needed for programs to run effectively and efficiently and be enabled to respond to gaps in program implementation
• High priority and strong support to nutrition should be the agenda of both the executive and legislative bodies in the municipalities
• “More Money for Nutrition and More Nutrition for the Money”: Secure domestic funding for nutrition-related programs
• Adopting an evidence-based package of nutrition-specific interventions that can be made available to each household in all priority LGUs
• Formulating a comprehensive, social behavior change communications strategy targeted at policy makers, health workers and households
• Maternal and child health programs provide the best opportunities for both nutrition-specific and nutrition-sensitive components.
• Implement nutrition sensitive programs aimed at improving dietary quality, access to clean water and sanitation, ensuring that PF serves the most vulnerable populations
• Establish geographic convergence by key sectors down to the household level and that focus on delivering a basic nutrition package of nutrition-specific and nutrition-sensitive programs to pregnant and lactating women and children younger than 2 years old.
• Ensure availability of subnational, ethnicity-disaggregated nutrition and nutrition-related data for targeted policy advice and interventions
• [FULL REPORT] Undernutrition in the Philippines: Scale, Scope, and Opportunities for Nutrition Policy and Programming
• Report Executive Summary
• [EVENT] Undernutrition and Stunting: From Crisis to Action
• [VIDEO] Addressing undernutrition in the Philippines, investing in the health of Filipino children
• Video in Filipino
• [PRESS RELEASE] Investing in Nutrition Can Eradicate the “Silent Pandemic” Affecting Millions of Poor Families in the Philippines – World Bank

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Diet Diversity and Micronutrient Adequacy among Filipino School-Age Children

Tsz-ning mak, imelda angeles-agdeppa, yvonne m lenighan, mario v capanzana, ivan montoliu.

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Correspondence: [email protected]

Received 2019 Jun 30; Accepted 2019 Sep 9; Collection date 2019 Sep.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/ ).

Previous studies have shown that the dietary diversity of young Filipino children to be limited and that the prevalence of nutrient inadequacies is high. This study extends the current knowledge to examine the relationship between diet diversity and the probability of adequacy of micronutrients among Filipino schoolchildren (aged 6 to 12 years), by the wealth status and dwelling location. The dietary intake data were collected using a single 24-h recall from 6460 children in the Filipino National Nutrition Survey 2013. The diet diversity score (DDS) and the probability of adequacies (PA) of 11 micronutrients were calculated, and further stratified by socio-economic status (SES) and dwelling location. The diet diversity was generally low (mean DDS = 4 out of 9). Children from the lowest SES, and living in rural areas, tended to have a lower DDS. Children with a DDS of 1 were likely to be inadequate in all 11 micronutrients. The higher DDS (≥6) was associated with higher PAs for the B vitamins but not for calcium, folate, iron, vitamin A and to large extent, vitamin C. This suggests that it was difficult for this population to achieve adequacy in these 5 micronutrients. More rigorous research on the topic is needed. Better access to nutrient-rich or fortified staple foods, in tandem with increased education on the importance of dietary diversity, are potential strategies to support children in achieving adequate micronutrient intakes.

Keywords: diet diversity, micronutrient adequacy, micronutrient fortification, Filipino schoolchildren

1. Introduction

Malnutrition, including underweight and stunting, is still a major public health concern in the Philippines. The prevalence of underweight Filipino children aged 5 to 10 years is 31.2%, stunting 31.1%, and wasting/thinness 8.4%. However, overweight children also exist in this age group (8.6% nationally), with a higher prevalence in urban than rural areas (13.0% versus 5.1%) [ 1 ]. Malnutrition is partially attributable to poor dietary quality, with 2 out of 3 Filipino households experiencing food insecurity [ 2 ]. The results of the latest Filipino National Nutrition Survey (2013) demonstrates inadequate nutrient intakes in schoolchildren, particularly with respect to poor intakes of calcium, iron, phosphorus, vitamin A, vitamin C and some B vitamins [ 3 ]. These nutrients are vital for growth and development in this young, vulnerable population [ 4 ]. Moreover, higher nutrient inadequacies were observed in Filipino schoolchildren from a rural dwelling location or from a poorer wealth status, which may be due to the limited access to affordable, fresh food [ 3 ]. On the other hand, it has also been reported that a small proportion (between 3–16%) of schoolchildren 6 to 12 years have excessive fat, protein and carbohydrate intakes in the Philippines, particularly those from the higher socioeconomic groups [ 3 ]. While little is known about nutrition transition among Filipino children, a previous study on the double burden of malnutrition in the Philippines between 1978 to 2003 has shown that although the mean food intake per capita in Filipino households did not change overtime, the mean energy intake per capita increased from 1804 kcal/day to 1905 kcal/day over the 25 year period. Furthermore, the consumption of meat, meat products and poultry; sugars and syrups; fats and oils increased while fruit and vegetable consumption reduced over this period. Rice remained as the country’s top staple food and source of energy [ 5 ].

While there has been progress in addressing undernutrition in the Philippines, it is still a problem of far greater magnitude than overnutrition is among children [ 5 ]. Limited dietary diversity can contribute to inadequate micronutrient intakes. Dietary diversity scores (DDS) have been implemented in a number of developing countries to evaluate dietary diversity and micronutrient adequacy in children and adults [ 6 , 7 , 8 , 9 ]. Higher dietary diversity has been associated with reduced stunting. Rah et al. identified that children (aged < 5years) in the higher diet diversity group were 30% less likely to be stunted compared to children from the lower diet diversity group [ 6 ]. A higher DDS has also been associated with increased micronutrient intakes [ 9 , 10 ]. A DDS score was applied to 9 food groups in a cross-sectional survey of children and women in rural Bangladesh. The prevalence of micronutrient inadequacy was 43% in children and 26% in women, which was primarily explained by diets low in energy and little diversity of foods [ 10 ]. Furthermore, a study in Ghanian children demonstrated significant improvement of nutrient intakes with an increasing DDS score. Moreover, the DDS was associated with impaired growth, wherein children with a lower DDS presented lower weight- and height-for-age and weight-for-length scores [ 9 ].

Kennedy et al. demonstrated the use of DDS, based on 10 food groups, to predict the probability of micronutrient adequacy in 2–5 year old Filipino children [ 7 ]. This group of young children consumed a relatively limited diet of four or five of food groups per day, with the mean probability of adequacy (MPA) of 11 micronutrients being 33% [ 7 ].

While the nutrient intakes of Filipino schoolchildren have been previously described [ 3 ], the dietary diversity, based on food group consumption of Filipino schoolchildren and its relationship with the probability of adequacy of key micronutrients, is unknown. Furthermore, the impact of socio-economic status (SES) and dwelling location on dietary diversity in a Filipino population has not been explored. Therefore, the aim of this study was to characterise dietary diversity among school age children (6–12y), and examine its relationship with the probability of adequacy of 11 micronutrients by SES and dwelling location (urban versus rural). The results of this study could inform further research and provide policy makers evidence on the potential association between dietary diversity and micronutrient intakes in Filipino schoolchildren.

2. Materials and Methods

2.1. study population.

The dietary intake data from 6460 children, aged 6 to 12 years, who participated in the 2013 National Nutrition Survey (NNS) were used in the current analyses. The details of the NNS have been previously outlined [ 1 ]. In brief, the 2013 NNS was a cross-sectional, population-based survey that collected information on the health and nutritional status of the Filipino population. Filipino households ( n = 35,825) were sampled with a response rate of 91%. The Ethics Committee of Food Nutrition Research Institute (FNRI) approved the survey protocol and data collection instruments. All surveyed households provided informed consent prior to participation.

2.2. Data Collection

Trained, registered dietitians, conducted face-to-face 24-h dietary recalls with a parent or caregiver of each child during household visits, wherein the dietician recorded all food and beverages that the child consumed the previous day. A first 24-h recall was performed for all children and a second 24-h recall was repeated in 50% of randomly selected households, typically 2 days after the first recall. Only the first 24-h recall was used in the current analysis. The amount of each food item or beverage was estimated using common household measures such as cups, tablespoons, by size or the number of pieces. The information was then converted to grams using a portion-to-weight list for common foods compiled by the FNRI or through weighing of the food samples. The nutrient composition of the data was cleaned, quality controlled and processed by the FNRI prior to analysis. This included reviewing all foods and drinks reported at the individual level to ensure that all the codes and quantities were entered correctly. The food and beverages consumed were converted to energy and nutrient intakes using the Filipino Food Composition Tables. Eleven micronutrients, as validated by Kennedy et al. [ 7 ] comprising calcium, thiamine, riboflavin, niacin, iron, vitamins A, C, B6, B12, folate and zinc were retained for the current analysis. The outliers were defined as intakes above the 99th percentile, as per Lopez-Olmedo et al. [ 11 ] and were replaced by the median value of the corresponding variable.

The 979 unique food items reported were categorised into 9 major food groups and further subgroups. The food grouping system was adapted from What We Eat in America Food Categories [ 12 ] and the US Feeding Infants and Toddlers Study (FITS) adjusted for the Philippines local food culture [ 13 ].

2.3. Diet Diversity Score (DDS)

In the current analysis, the aforementioned food categories were further assigned to 10 DDS food groups (cereals and tubers; meat, poultry and fish; dairy; eggs; pulses and nuts; vitamin A-rich fruits and vegetables; other fruit; other vegetables; oils and fats; and other). This DDS food grouping system was defined based the outcome of a Food and Agriculture Organization (FAO) workshop on the validation methods for dietary diversity [ 14 ]. Kennedy et al. examined and validated the use of these 10 food groups to reflect diet diversity in Filipino children, aged between 2 and 5 years old [ 7 ]. In the current study, if a child consumed a minimum of 10 g of at least one food item belonging to a DDS food group, excluding oils and fats, he/she would receive a maximum score of 1 for that particular DDS group. Previous validation studies have demonstrated that applying a minimum food group consumption of 10 g provided a better representation of nutrient adequacy in children [ 7 , 15 ]. The DDS for each child was determined based on the sum of the number of individual DDS food groups consumed in their 24-h recall. The DDS ranged from a minimum score of 0 to a maximum of 9.

2.4. Probability of Adequacy (PA) of Micronutrients

An existing algorithm developed by Foote et al. (2004) was used to estimate a child’s probability of adequacy (PA) of a given micronutrient [ 16 ]. The PA is defined as the probability that a child’s nutrient intake is adequate on a single day [ 15 ]. The dietary requirement of the nutrient is assumed to follow a normal distribution, with an age and gender specific cut-off for the estimated average requirement (EAR) and standard deviation (SD). The PA is calculated based on the probability of the cumulative distribution function (CDF) multiplied by the difference of the estimated child intake and EAR, divided by the SD. For iron, as its distribution of requirement is skewed and therefore this equation was not applicable, its PA was derived from Tables 1–5 within the IOM manual for iron [ 17 ] as recommended by Kennedy and Nantel [ 14 ].

The PA of each nutrient was calculated for the total population, and further stratified by the socioeconomic status and dwelling location. The mean of the 11 PAs (MPA) was calculated to provide an estimate of the overall probability of adequacy of the key micronutrients of the sample population. All nutrient intakes were converted to milligrams per day (mg/d) prior to the analysis.

2.5. Statistical Analysis

The DDS, PA and MPA were calculated as described above. The cross-tabulations and χ2 statistics were applied to determine the associations between the gender, wealth status and dwelling locations. The associations between the PA for each nutrient, DDS, dwelling locations and SES were examined using regression models.

To identify if certain micronutrients were driving the MPA, a set of gradient boosting regressor models (GBMs) were applied, as predictors of probability of inadequacy (defined as 1-MPA) based in the micronutrient intake. The GBMs were preferred due to the skewness of the nutrient intake data. The model parameter optimization was performed by a grid search and internal cross validation (11 segments). To ensure the validity of the models, a random subsample was selected and the same model was applied to check for congruency.

All calculations were performed in an Anaconda Python 3.6.7 environment running on a HP Z440 workstation in Windows 10. To perform model optimization and validation, the modules from Sklearn v.0.20.1 library were applied [ 18 ]. The data handling and manipulation was done using Pandas 0.24.1. For statistical analyses, the Scipy v.1.1.0 library was used [ 19 ].

3.1. Descriptive Statistics

A description of the sample population is shown in Table 1 . The mean age was 9.61 years (SD: ±2. Half of the sample came from the poor and poorest socio-economic classes, and living in rural dwellings. The mean DDS was 4, with the majority of children consuming three to five food groups per day. The contingency table analysis showed significant relationships between the socio-economic status, dwelling location ( Supplementary Figure S1 ) and DDS, independent of gender (data not shown). The socio-economic status was strongly associated with DDS; whereby those from the highest socio-economic group had the highest diet diversity ( Figure 1 ), and those with lower DDS were predominantly from lower socio-economic groups. No children from the poorest SES group reached a DDS of nine. A similar trend was observed by dwelling locations, with a greater proportion of children from a rural location presenting a lower DDS ( Figure 2 ).

Descriptive statistics of the sample population ( n = 6460).

Percentage of children in each diet diversity score (DDS) group by socio-economic status.

Percentage of children in each diet diversity score (DDS) group by dwelling locations (urban and rural).

Figure 3 illustrates the non-linear relationship between the DDS and MPA. The result showed that a DDS of 4 (the mean score of this population), the mean probability of adequacy across the 11 micronutrients was approximately 35%. Even at the highest DDS of 9, the mean probability of adequacy across the 11 micronutrients was only approximately 60%.

Mean probability of adequacy as the average of probability of adequacies (PA) of 11 micronutrients, presented by the diet diversity score (DDS) level.

3.2. DDS and PA

The relationships between DDS and the probability of adequacy of each individual nutrient are summarized in Table 2 . A PA score of 1 indicates the probability of adequacy of a nutrient was 100%, while 0 indicates the probability of being adequate was 0%. Children with a DDS of 1 were likely to be inadequate in all 11 micronutrients. The probability of adequacy of nutrients improved with increasing DDS. Even with relatively low DDS (e.g., DDS ≤ 4, the mean score of this population), children were likely to be adequate in vitamin B12, thiamine and vitamin B6. Children with a DDS of 9 had the highest number of nutrients with PA = 1 (100% probability of adequacy), however, for calcium, folate, vitamin A and vitamin C, the PA remained at 0.

Distribution of probability of adequacy (PA) values of 11 micronutrients according to the diet diversity score (DDS).

Probability of adequacy (PA) is the probability that a child’s nutrient intake is adequate on a single day. PA = 0 indicates the probability of being adequate of a particular nutrient is 0%; PA = 1 (shaded) indicates the probability of being adequate of a particular nutrient is 100%. The diet diversity score (DDS) refers to the number of food groups (out of 9) a child has consumed on a single day.

3.3. DDS, PA, and Dwelling Locations

Table 3 illustrates the PA scores stratified by urban and rural areas. While the overall patterns of PA were similar between the two populations, some differences were observed. Children from urban areas were likely to reach 100% adequacy in riboflavin, thiamine and zinc with lower DDS scores compared to children from rural areas. For example, children from urban areas could reach 100% adequacy in zinc at a DDS of 7 while children from rural areas would need a DDS of 8 or 9 to reach full adequacy.

Distribution of probability of adequacy (PA) values of 11 micronutrients according to the diet diversity score (DDS), stratified by rural and urban areas.

Probability of adequacy (PA) is the probability that a child’s nutrient intake is adequate on a single day. PA = 0 indicates the probability of being adequate of a particular nutrient is 0%; PA = 1 (shaded) indicates the probability of being adequate of a particular nutrient is 100%. Diet diversity score (DDS) refers to the number of food groups (out of 9) a child has consumed on a single day.

3.4. DDS, PA, and SES

The patterns of PA by DDS and SES are comparable to those by dwelling locations, although the differences between the poorest and the richest are more prominent. As shown in Table 4 , at the highest DDS among the children from the poorest households, they were only adequate in 5 out of 11 micronutrients. Children from the richest households on the other hand, at a DDS of 9, were adequate in 7 of the 11 micronutrients. The majority of children from the poorest group had a DDS between 1 and 4, suggesting that these children were likely to be adequate in only 2 (Vitamin B12 and B6) out of 11 micronutrients. Furthermore, zinc intakes were related to SES, wherein 100% adequacy was achieved at a DDS of 6 in the richest children, but not in the poorest children.

Distribution of Probability of Adequacy values of 11 micronutrients according to the diet diversity score (DDS), stratified by socio-economic status (poorest and richest groups shown).

4. Discussion

4.1. diet diversity among filipino children.

The current study examined the relationship between diet diversity of Filipino school age children (6–12y) and their probability of adequacy of 11 micronutrients. The diet diversity was low with an average of four out of nine food groups per day. A previous study in younger Filipino children found similar findings on DDS [ 7 ], wherein diets were composed of limited foods, namely a large amount of refined rice and non-nutritious foods [ 13 ]. The current study demonstrates that older Filipino children also consume a relatively monotonous diet that lacks variety, and nutrient inadequacy is prevalent. Furthermore, this study confirms that characterising children by SES and dwelling locations are important when examining the relationships between DDS and PA, which has not been previously demonstrated.

4.2. Socio-Economic Status and Urban versus Rural Children

This study showed that nutrient adequacy was greater in those from higher socio-economic groups and urban areas than their lower SES and rural counterparts. Those from higher SES or urban areas met B-vitamin adequacy with relatively fewer food groups than rural or children from the lower SES. These results are in accordance with the recent study by Angeles-Agdeppa et al. [ 3 ] which found that micronutrient inadequacy was greater (thiamine, riboflavin, niacin, vitamin B6, phosphorus, zinc, and iron) in Filipino schoolchildren and adolescents from poorer families and living in rural areas. Interestingly, they found a higher prevalence of inadequacy for vitamin C (10–12 years), vitamin A (6–9 years) and folate (6–9 years) among urban children. However, no difference in the probability of adequacy of vitamin A and folate according to DDS groups by dwelling location was observed in the current study. Previous studies have suggested that children from lower SES/rural areas have greater consumption of vegetables and fruit (including fortified fruit juices) than urban children [ 3 , 20 ]. This may explain the higher iron and vitamin C intakes among rural children. The association between zinc and the PA gradient was greater for individuals in the urban areas. This suggests that it is more achievable for this subgroup of the population to reach zinc adequacy, and by consuming a lower number of food groups.

4.3. Calcium, Folate, Iron, Vitamin A and Vitamin C Adequacies are Difficult to Meet

The literature suggests that Filipino children are most at risk of calcium, iron, vitamin C, folate, vitamin A, riboflavin, thiamine and phosphorus inadequacies [ 3 ]. This study suggests that it is difficult for Filipino schoolchildren to be adequate in all 11 micronutrients, a finding that has not been previously demonstrated in this population. Although increasing the number of food groups in the diet can improve nutrient adequacy to some extent [ 9 ], this study has shown that even with a diverse diet (e.g., DDS ≥ 7), the probability of adequacies for calcium, folate, vitamin A and vitamin C remained as zero. The simple view that increasing diversity of a diet can reduce inadequacy of nutrient intakes does not appear to hold true for all micronutrients. This is likely because the commonly consumed food sources are not rich enough in these nutrients, or the consumption of foods rich in calcium, folate, vitamin A and vitamin C is too low, or both. The potential solutions include significantly increasing the quantity of foods that are rich in these nutrients in the diet, to fortify or increase the level of fortification of commonly consumed foods from the different food groups. Indeed, for calcium for example, increased milk consumption would help close this nutrient gap. However, the previous National Nutrition Survey in the Philippines indicated that less than a third of school-age children consume any milk [ 21 ]. Therefore, the low intake of calcium may be attributed to the availability and affordability of milk, dairy products, or other food sources of calcium, such as fish, for those who are lactose intolerant [ 3 , 13 ]. Thus, an increased consumption of calcium-rich foods may help close this nutrient gap.

Increasing nutrient rich foods in the diet could increase the cost of diet, which may not be ideal for low-income families. A national food fortification programme could, therefore, be a more cost-effective and viable solution to address micronutrient inadequacy among poorer or rural households. A mandatory food fortification law of staple foods such as wheat flour, rice, cooking oil and sugar has existed since 2004 in the Philippines. However, a number of challenges have been reported to hinder its success [ 22 ]. Better access to fortified foods and a more enhanced, a widespread fortification programme to target staples as well as popular foodstuffs for children may remove some of these challenges. Indeed, a RCT conducted in the Philippines has demonstrated that a non-carbonated fortified juice drink with iron and zinc was effective in reducing the prevalence of anemia and improved the zinc status of children [ 23 ]. Similarly, a study demonstrated that fortified milk can improve the nutritional status of school children. This RCT identified a micronutrient fortified milk-based drink as effective in improving the micronutrient status of vitamin B2, vitamin B12 and red cell folate and in preventing a decline in hemoglobin levels, compared to an unfortified milk-based drink among South Indian children. [ 24 ]. A further study demonstrated the benefits of regular milk and fortified milk consumption among children in rural Vietnam. Both the weight-for-age and height-for-age significantly improved during 6 months of intervention among milk drinkers and fortified milk drinkers, and underweight and stunting dropped by 10% in these groups compared to the controlled group. Fortified milk consumption also showed improvements in physical and mental performance [ 25 ]. Nonetheless, an extensive fortification strategy with increased accessibility to nutrient-rich foods, combined with personalised nutrition education to children and their caregivers, are some of the potential strategies to improve the adequacy of multiple micronutrients among children in the Philippines.

4.4. Strengths and Limitations

This study has demonstrated that a diverse diet does not guarantee the adequacy of key micronutrients in Filipino children. Moreover, the patterns of micronutrient probability of adequacy can vary by dwelling locations and SES, even if children are eating the same number of food groups, which has not been previously described in this Filipino school-aged population. The large sample of children (n = 6460) from a nationally representative survey of the Philippines covering the age group 6 to 12 years is a strength of this study.

There are however, limitations to be highlighted. Only one day of the 24-h recall was used in the estimation of DDS and PAs and therefore cannot represent habitual food consumption or nutrient intakes. Consequently, self-reported bias such as under- or over-reporting is plausible among the sample. A further limitation is that most children had DDS scores between 3 and 5, and the number of children with DDS < 2 or DDS > 6 was low. There were more children in the high DDS groups from urban areas or higher SES than rural or poorer families. Therefore, readers should take caution when interpreting results on PAs for these higher DDS groups.

While previous studies have shown the strengths of using DDS as an indicator of diet diversity in developing countries, given the Philippines are going through a nutrition transition where the double burden of undernutrition and overweight exists, caution should be taken when categorising nutrient-dense and energy-dense foods into DDS groups. While the authors followed the DDS food groups suggested by the literature on younger Filipino children, an improvement for the future could be to increase the sensitivity of DDS groups to different types of nutrient-rich or fortified foods versus foods high in energy and low in micronutrients. Further research on nutrition transition in the Philippines as well as the relationship between diet diversity and nutrient intakes and overweight/obesity are needed, to support policymakers in addressing this emerging type of food insecurity.

5. Conclusions

This study provides novel insights into the dietary diversity of Filipino schoolchildren, and the associations between socioeconomic status, dwelling location and dietary diversity. The lack of dietary diversity is one of the reasons for the low probability of adequate intakes of micronutrients, particularly those from poorer households. The strategies such as wide-spread fortification, improved accessibility to fortified products, as well as tools to help increase a caregivers’ awareness and understanding on diet diversity and nutrient-rich foods may help to improve micronutrient intakes in the children population.

Acknowledgments

We would like to thank Laurence Donato-Capel for overseeing the project, Emma F. Jacquier and Lolita Bazarova for their guidance of the manuscript. We would like to thank FNRI for granting access to the data.

Supplementary Materials

The following are available online at https://www.mdpi.com/2072-6643/11/9/2197/s1 , Figure S1: Distribution of percentage of children per wealth status group according to dwelling locations.

Author Contributions

T.-N.M. conceptualized and designed the study, interpreted the data, and drafted the manuscript. I.M. conducted the data analysis, interpreted the data, and drafted the manuscript. Y.M.L. contributed to the interpretation of data, and drafted the manuscript. I.A.-A. and M.V.C. critically reviewed the draft of the manuscript. All authors proofread and approved the final manuscript.

This research and the APC were funded by Nestlé Research.

Conflicts of Interest

The authors declare no conflicts of interest. T.-N.M, I.M., Y.M.L are employees of Nestlé Research, Vers-chez-les-Blanc, Lausanne, Switzerland. This research was funded by Nestlé Research, Lausanne, Switzerland.

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Research Article

Exploring the double burden of malnutrition at the household level in the Philippines: Analysis of National Nutrition Survey data

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada

Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing

Affiliation School of Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada

Roles Conceptualization, Supervision, Writing – review & editing

Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing

Affiliation School of Public Health and Social Policy, University of Victoria, Victoria, British Colombia, Canada

• Josephine Gaupholm, 
• Warren Dodd, 
• Andrew Papadopoulos, 
• Matthew Little

• Published: July 17, 2023
• https://doi.org/10.1371/journal.pone.0288402
• Reader Comments

In the Philippines, the rising prevalence of obesity and related chronic diseases alongside persistent undernutrition presents a complex public health challenge. Understanding the patterns and dynamics of this ‘double burden of malnutrition’ (DBM) is crucial for developing effective intervention strategies. However, evidence of the occurrence of undernutrition and overnutrition within the same household is currently lacking.

Using cross-sectional data from the 2013 Philippines National Nutrition Survey this study examined the prevalence of different typologies of household-level DBM from an analytical sample of 5,837 households and 25,417 individuals. Multivariable logistic regression was performed to identify factors associated with overall occurrence of intrahousehold DBM.

The overall prevalence of double burden households was 56% based on a comprehensive definition. The most common typology of intrahousehold DBM characterized in this study (% of all households) comprised households with at least one adult with overnutrition and at least one separate adult with undernutrition. Household size, wealth quintile, food insecurity, and household dietary diversity were all associated with household-level DBM. Double burden households were also influenced by head of household characteristics, including sex, level of education, employment status, and age.

Conclusions

The findings from this study reveal that the coexistence of overnutrition and undernutrition at the household level is a major public health concern in the Philippines. Further comprehensive assessments of household-level manifestations of the DBM are needed to improve our understanding of the trends and drivers of this phenomenon in order to develop better targeted interventions.

Citation: Gaupholm J, Dodd W, Papadopoulos A, Little M (2023) Exploring the double burden of malnutrition at the household level in the Philippines: Analysis of National Nutrition Survey data. PLoS ONE 18(7): e0288402. https://doi.org/10.1371/journal.pone.0288402

Editor: Emmanuel Oladeji Alamu, International Institute of Tropical Agriculture (IITA), ZAMBIA

Received: November 14, 2022; Accepted: June 26, 2023; Published: July 17, 2023

Copyright: © 2023 Gaupholm et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The datasets used in this study are publicly available online from the Philippines’ Food and Nutrition Research Institute of the Department of Science and Technology’s website ( http://enutrition.fnri.dost.gov.ph/site/home.php ).

Funding: This research was funded by the Social Sciences and Humanities Research Council of Canada ( https://www.sshrc-crsh.gc.ca/home-accueil-eng.aspx ) grant number 430-2019-00150 was awarded to ML and WD. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The Philippines, like many low- and middle-income countries, is currently facing multiple burdens of malnutrition [ 1 , 2 ]. Despite rapid economic growth, the Philippines continues to experience high levels of undernutrition (e.g., stunting, wasting, underweight) in addition to a rapid rise in the prevalence of overnutrition (e.g. overweight, obesity, and diet-related non-communicable diseases) [ 2 – 4 ]. Indeed, according to the 2022 Global Nutrition Report the prevalence of stunting among children under five is 28.8% in the Philippines, which is higher than the Asian regional average of 21.8% [ 2 ]. Meanwhile, approximately one third of adults are overweight or obese [ 2 ]. Micronutrient deficiencies also persist, with an estimated 70 to 80% of adults not meeting the recommended nutrient intakes for many vital micronutrients, including iron, calcium, and vitamin A [ 5 ]. This coexistence of both over- and undernutrition is known as the double burden of malnutrition (DBM) and can occur at the population, household, and/or individual level [ 6 ]. Understanding the patterns and dynamics of malnutrition is crucial for developing effective intervention strategies [ 7 ]. Studies of the DBM most frequently report on the coexistence of undernutrition and overnutrition at the population level [ 8 ]. DBM research in the Philippines is similarly population-level focused, with some recent work assessing individual-level DBM [ 9 , 10 ]. However, household-level manifestations of the DBM have not been widely studied in the Philippines.

DBM at the household level is broadly characterized as the coexistence of undernutrition and overnutrition within the same household, however, no definitive operational definition or indicators of double burden households exist [ 8 , 11 ]. While the majority of DBM research at the household level focuses solely on maternal-child relationships, where the presence of an overweight mother and a stunted child has largely become the archetypal characterization of a double burden household, numerous other typologies can, and do, exist [ 12 – 16 ]. In most studies, anthropometric measurements are used as indicators of undernutrition and overnutrition, however, exact indicators and cut-off points differ across studies [ 15 ]. As a result of such heterogeneity in DBM definitions and indicators, prevalence estimates of double burden households can vary widely between studies [ 8 , 15 , 16 ].

The cooccurrence of under- and overnutrition at the household level is often considered paradoxical, as historically these two forms of malnutrition were understood to arise from two different sets of determinants and behaviours [ 12 , 17 ]. However, intrahousehold DBM requires that both under- and overnutrition arise among people who share similar food environments and household characteristics. As such, there is an increasing recognition that under- and overnutrition should not be considered distinct conditions at opposite ends of the nutrition spectrum, as both are indicative of malnutrition, including diets high in calories but low in micronutrients [ 6 , 18 ]. Previous research has found associations between double burden households and socio-demographic factors, such as maternal age, educational level, and occupation, as well as household wealth and family size [ 11 , 12 , 14 ]. Suggested mechanisms driving intrahousehold DBM often relate to the nutrition transition and related changes in household dietary and lifestyle patterns [ 12 ]. Dietary behaviour and patterns are strongly influenced by social and familial dynamics. However, empirical evidence examining associations between intrahousehold DBM and dietary indicators, such as diet diversity, food security, and diet quality, is lacking [ 12 , 19 – 21 ].

Understanding the various types and correlates of malnutrition at the household level provides an opportunity to identify shared drivers of malnutrition, which is critical for effectively designing and targeting interventions. However, in the Philippines, the extent and determinants of intrahousehold DBM are relatively unknown because of scarce information. To our knowledge, the only published research investigating household-level DBM in the Philippines reported that among a study sample of 376 child-mother pairs living in Metro Manila, 59% were experiencing dual forms of malnutrition [ 22 ]. However, since this localized study conducted two decades ago, no further examinations of household-level DBM have been done. To begin addressing this knowledge gap, the current study aims to explore this phenomenon using nationally representative data and gain a high-level understanding of factors associated with intrahousehold DBM. Specifically, the objectives of this study are: 1) to determine the prevalence of different typologies of the DBM at the household level in the Philippines; and 2) to examine the broad factors associated with the DBM at the household level.

Data source and study population

This study used publicly available data from the 2013 National Nutrition Survey (NNS) in the Philippines. The NNS, conducted by the Philippines Food and Nutrition Research Institute, is a cross-sectional, nationally representative survey that reports on the health, nutrition, and dietary composition of the Filipino population [ 23 ]. The 2013 NNS employed a three-stage stratified sampling design. Primary Sampling Units (PSUs) were defined first as a barangay (i.e., the smallest administrative unit in the Philippines) or contiguous barangay with at least 500 households. PSUs were then used to identify enumeration areas (EAs) of 150–200 households. A random selection of households within each EA made up the final sampling unit. Overall, 35,825 households and 172,323 individuals were sampled across 80 provinces (the province of Batanes was not surveyed due to logistic reasons). The complete methodology for the 2013 NNS survey has been detailed elsewhere [ 23 , 24 ].

This study included multi-person households with complete data from seven survey components, including anthropometric, biochemical, clinical, food security, socioeconomic (household and individual), and dietary data. Data from pregnant women were excluded from the analysis because pregnancy affects the accuracy of anthropometric measurements [ 25 ]. A total of 5,837 households and 25,417 individuals were eligible for analysis ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0288402.g001

Outcome variables

Assessment of overnutrition and undernutrition at the individual level..

Table 1 provides an overview of each of the indicators used to classify under- and overnutrition in adults and children and the clinical cut-offs. For adults, we used a combination of anthropometric, biochemical, and clinical indicators to classify malnutrition. Body mass index (BMI) was classified based on the World Health Organization (WHO) standard cut-offs [ 26 ]. Under- and overnutrition among children/adolescents were identified using height-for-age Z-scores (HAZ), weight-for-height Z-scores (WHZ), weight-for-age Z-scores (WAZ), and body-mass-index- for-age Z-scores (BAZ) [ 27 ]. Z-score calculations were performed using the Anthro and AnthroPlus macro packages for Stata developed by the WHO and United Nations Children’s Fund (UNICEF) which apply the WHO Child Growth Standards as reference data [ 28 , 29 ]. Adults were classified as having overnutrition if they had any of the following conditions: (1) overweight/obesity or abdominal obesity; (2) hypertension; (3) hyperglycemia, or; (4) dyslipidemia. Adults were classified as having undernutrition if they had any of the following conditions: (1) underweight; (2) anemia; (3) vitamin A deficiency; or, (4) iodine deficiency. A child was considered under-nourished if they were stunted, wasted, and/or underweight. A child was considered over-nourished if they were overweight. Micronutrient deficiencies were not assessed for children and adolescents due to a limited number of complete micronutrient data from children and adolescents in our sample.

https://doi.org/10.1371/journal.pone.0288402.t001

Anthropometric, biochemical, and clinical data collection.

Height and weight measurements were obtained for all eligible household members using an electronic calibrated portable stadiometer (SECA 217, Hamburg, Germany) and a digital double window weighing scale (SECA 874, Hamburg, Germany). The recumbent length of children under 2 years-old was measured using an infantometer or a wooden length board. Waist circumference was measured among participants aged 10 and older using a calibrated tape measure. Blood pressure measurements were taken by trained nurses using a non-mercurial sphygmomanometer (A&D Um-101TM) and stethoscope. Registered medical technologists collected blood samples which were used to measure biomarkers of cardio-metabolic risk factors (CMRF), namely fasting blood glucose and blood lipids. Following collection, they were analyzed using the enzymatic colorimetric method with Roche COBAS Integra and Hitachi 912. Registered medical technologists also collected blood and urine samples to assess micronutrient deficiencies. The cyanmethemoglobin method was used to evaluate hemoglobin levels. Serum retinol was examined using High-Performance Liquid Chromatography. Urinary iodine excretion levels were determined using the acid digestion/colorimetric method.

Assessment of the double burden of malnutrition at the household level.

To comprehensively evaluate the prevalence of double burden households in the Philippines, we considered all possible typologies, or combinations, of under- and overnutrition among household members. A household was considered a double burden household if they had any combination of undernutrition and overnutrition in two or more household members ( Table 2 ). We also explored the prevalence of several specific household DBM subtypes relevant to the literature, including the co-occurrence of child undernutrition and maternal overnutrition (represented by women of reproductive age 18–49 years).

https://doi.org/10.1371/journal.pone.0288402.t002

Independent variables

Covariates were identified from previous literature and included both household factors and individual-level characteristics of the head of household [ 11 – 14 ]. These include the age, sex, educational attainment, and occupation of the head of household. Household factors included the number of people living in the household (household size), wealth quintile, food security, and diet diversity.

The head of household was reported by participants during the survey. The sex of the head of household was classified as either male or female, while the age variable was categorized as 18–29, 30–39, 40–49, 50–64, and ≥65. Educational attainment was classified as either having a post-secondary education or not. Household size was categorized into four groups: 2–3, 4–6, 7–10, and ≥11. Wealth status was derived from principal component analysis scores based on household assets such as possession of vehicles, appliances, housing construction materials, and sanitation facilities [ 23 ]. These scores were used to define wealth quintiles.

The Household Food Insecurity Access Scale (HFIAS) was used to assess household food security. The nine-question HFIAS measures the occurrence and frequency of various conditions related to food insecurity over a one-month (30 day) period. Participants are first asked an occurrence question—i.e., whether a condition occurred at all in the past 30 days (yes or no). If they respond yes, they are then asked the frequency-of-occurrence, that is, if the condition happened rarely (once or twice), sometimes (three to ten times) or often (more than ten times) in the past four weeks. Using the scoring system developed by USAID’s Food and Nutrition Technical Assistance Project [ 37 ], households were categorized as either “food secure”, “mildly food insecure”, “moderately food insecure”, or “severely food insecure”.

Household diet diversity scores (HDDS) were calculated based on data collected through one-day food records, which including weighing foods consumed inside the home. Trained registered nutritionist-dietitians used a digital dietetic scale to weigh (before cooking or serving) all food items prepared and served in the home for an entire day. Unconsumed or leftover food was deducted from the total in order to obtain the final amount of food and beverages consumed by the household. Foods consumed outside the house were recalled by household members and added to the household food record. Dietary data were aggregated into 12 food groups based on Food and Agriculture Organization guidelines [ 38 ]. HDDS were computed by summing up the total number of food groups consumed by members of the household. Scores were then categorized into three groups representing low diet diversity (score of 1 to 4), moderate diet diversity (5 to 7), and high diet diversity (≥8).

Statistical analysis

We generated descriptive statistics for the socio-demographic and individual over- and undernutrition characteristics of the study sample using weighted means and percentages. Survey sample weights were computed and adjusted for non-response, then post-stratified based on the projected population obtained from the Philippines Statistics Authority. We calculated the prevalence of all possible combinations of overnutrition and undernutrition within households, with overall presence being categorized as a binary outcome (0 = not a double burden household, 1 = a double burden household). The rationale for this approach was based on the desire to gain a high-level understanding of factors associated with the phenomenon of intrahousehold DBM in general across the Philippines, as this has not yet been explored in the literature. Additionally, following preliminary explorations of the data, we found that assessing all possible typologies of household DBM separately increased the risk of misclassification bias and diminished the statistical power of the analyses. It was also for this reason that micronutrient deficiencies were not assessed separately from underweight.

Logistic regression analyses were used to examine factors associated with double burden households of any type. First, bivariate regression models were constructed to examine the unconditional association between each of the independent variables and our dependent variable (i.e., household-level DBM). As we had identified our variables of interest a priori based on previous research, all covariates, regardless of significance in the unconditional analysis, were included in the multivariable logistic regression model. Prior to fitting our main model, we examined all pairwise correlations among predictor variables to test for possible collinearity using Spearman’s rho. However, we found no evidence of multicollinearity between independent variables as all correlation coefficients were less than |0.80|. As such, a model containing all variables of interest was constructed. This model also included dummy variables for the 17 administrative regions in the Philippines to control for geographic differences. Subsequently, we tested for all plausible two-way interactions among the covariates included in our main model, however, none were found to be significant. Goodness of fit was assessed using the Hosmer-Lemeshow goodness of fit test for binary data. All statistical analyses were performed using the Stata statistical software package version 16.1 (2022; StataCorp). The level of significance was set at p<0.05.

Individual nutrition status among study participants

We analysed the individual nutrition status of 13,843 adults (≥18 y) and 11,574 children/adolescents (≤17 y). The mean BMI of adults in the sample was 23.06 kg/m 2 (SD = 4.18), with 31.2% of women and 26.2% of men being either overweight or obese ( Table 3 ). Dyslipidemia was the most prevalent CMRF, affecting nearly one in three adults within the study sample. The prevalence of abdominal obesity was notably 6.8 times higher in women than in men (20.5% compared to 3%). Overall, 55% of adults had one or more indicator of overnutrition. Conversely, undernutrition affected 41.7% of adults. Approximately 11% of adults were underweight (BMI <18.5 kg/m 2 ), while over one in three adults had some form of micronutrient deficiency.

https://doi.org/10.1371/journal.pone.0288402.t003

Table 4 presents the prevalence of malnutrition among children and adolescents. Overall, over one in three children and adolescents were classified as having some form of undernutrition, while only 3.3% were considered overweight. Stunting was the most prevalent form of undernutrition, affecting nearly 30% of all children/adolescents.

https://doi.org/10.1371/journal.pone.0288402.t004

Household-level double burden

The overall prevalence of double burden households was 56% when we included all possible combinations of over- and undernutrition among household members ( Table 5 ). The majority of these double burden households (83.3%) had at least one adult with overnutrition and at least one adult with undernutrition. The proportion of households with DBM type 1, i.e., at least one adult with overnutrition and at least one child/adolescent with undernutrition, was 26.8%. When we restricted DBM type 1 to only include the co-existence of overnutrition among women of reproductive age (18–49 y) and undernutrition among children/adolescents, the prevalence of DBM fell to 12%. Further, if we define child undernutrition using only stunting and wasting metrics among children under five, household-level DBM prevalence was 4.3%.

https://doi.org/10.1371/journal.pone.0288402.t005

Socio-demographic characteristics

Table 6 describes the sociodemographic characteristics of the study population overall and by household DBM type. Overall, households had on average five members, with the majority having a male head of household. Households were relatively evenly distributed across each of the wealth quintiles, however, close to 60% of households were classified as either moderately or severely food insecure. Household heads were mainly employed as farmers, laborers, or unskilled workers, with only 15.7% having attended postsecondary school.

https://doi.org/10.1371/journal.pone.0288402.t006

Factors associated with household-level double burden

Table 7 presents the results from both our bivariate and multivariable logistic regression models, reporting the unadjusted odds ratios (uOR) and adjusted odds ratios (aOR), respectively. The remainder of the results section focuses on the results of the multivariable analysis. Female-headed households had significantly lower odds of household-level DBM compared to male-headed households (95% confidence interval (CI): 0.63–0.86). Similarly, the odds of being a double burden household were lower when the head of household attended post-secondary school (95% CI: 0.63–0.89). The age of the head of the household was positively associated with the household experiencing a DBM. For example, intrahousehold DBM was 2.22 times more likely in households with a head of household aged 65 or older, compared to households with a head of household between the ages of 18 to 29 (95% CI: 1.51–3.14). We found no significant differences in household-level DBM between head of households employed as farmers, laborers, or in unskilled work and other occupation categories. However, households with an unemployed head of household were found to have 1.24 times higher odds of household-level DBM compared to household heads employed in farming, labour, or unskilled work (95% CI: 1.03–1.49).

https://doi.org/10.1371/journal.pone.0288402.t007

Larger household size was associated with higher odds of household-level DBM. Additionally, households experiencing food insecurity had higher odds of intrahousehold DBM compared to food-secure households. Household wealth quintile was also associated with household DBM, with households in the 5 th (or wealthiest) quintile having 1.26 times the odds of household-level DBM when compared to the 1 st (or lowest) quintile (95% CI: 1.00–1.59). Lastly, higher household diet diversity scores were associated with increased odds of household-level DBM. For instance, households with high household diet diversity (i.e., a HDDS of 8 or above) had 1.46 times the odds of household DBM when compared to households with low diet diversity (i.e., a HDDS of 4 or below) (95% CI: 1.14–1.87).

The current study sought to evaluate the prevalence, typologies, and correlates of the household-level DBM in the Philippines. Using data from a large nationally representative survey, we adopted a comprehensive definition of household-level DBM to examine this complex phenomenon. Results indicate that various types of household-level DBM exist in the Philippines, with over half of all households experiencing some form of intrahousehold DBM. This reflects both the high prevalence of individual-level indicators of over- and undernutrition among the Filipino population, but also the number and type of individual-level indicators we measured which included anthropometric measurements, micronutrient deficiencies, and CMRF. The growing concern of overweight and associated CMRF in the Philippines was emphasized in this study, as over one in two adults were affected by some form of overnutrition. On the other hand, undernutrition remains a serious public health concern in the Philippines, with 41.7% of adults and 33.5% of children and adolescents exhibiting at least one indicator of undernutrition. At the household-level, these forms of malnutrition manifested in a myriad of ways. The prevalence of households containing a woman of reproductive age (18–49 years) with overnutrition and a child with undernutrition, which is the most frequently assessed household-level DBM type in the literature, was 12%. While this figure is comparable to the global average prevalence, there is large variation between studies, regions, and countries [ 6 , 11 ]. A recent systematic review by Kosaka and Umezaki found that household prevalence of mother overweight–child underweight pairs ranged from <3% (e.g., in Bangladesh, Cambodia, and Nepal) to >10% (e.g., in Bolivia, Egypt, and Guatemala) [ 11 ]. Of the household-level DBM typologies characterized in this study, the most common (46.4% of all households) comprised households with at least one adult with overnutrition and at least one different adult with undernutrition. Of these pairings, 54.2% (or 25% of all households) consisted of a man (≥18 years) with overnutrition and a woman (≥18 years) with undernutrition. The high prevalence of this pairing is notable, as there is a substantial lack of research exploring such adult-adult DBM parings in the literature [ 8 ]. Previous studies on DBM may have overlooked this important manifestation of household-level DBM. This typology of DBM may be indicative of inequitable allocation of resources (e.g., food, financial resources, and decision-making power) among adults at the household level, which bears further investigation.

Our analysis identified a number of socio-economic and demographic factors associated with intrahousehold DBM. Consistent with previous research, we found positive associations with both the age of the head of household and household size [ 11 ]. Household wealth was also associated with household-level DBM, with households in the 3 rd and 5 th wealth quintiles having significantly higher odds of household-level DBM compared to households in the 1 st (or lowest) wealth quintile. This indicates that middle- and high-income households may be at higher risk for intrahousehold DBM in the Philippines, which supports findings from similar research [ 14 , 39 ].

Our results showed female-headed households had lower odds of DBM compared to male-headed households. Correspondingly, a similar study using nationally-representative survey data from Indonesia found that female-headed households were less likely to experience the DBM, defined as households with at least one overweight and one underweight member [ 40 ]. This association underscores the importance of gender dynamics and decision-making power in household nutrition. Evidence suggests that women’s empowerment in the household, including decision-making power and autonomy, is associated with improved child nutrition in Asia [ 41 ], Africa [ 42 ], and other regions [ 43 ]. It has been hypothesized that when women have greater control and access to household resources, they tend to prioritize health and food spending, therefore leading to improved diets and nutrition [ 40 ]. However, such relationships are complicated by the reality that female-headed households are at increased risk of food insecurity and poverty [ 44 ] due to numerous economic and societal disadvantages, including unequal access to assets (e.g., land and livestock), markets, and services [ 45 , 46 ]. Indeed, contrary to our findings, Sansón-Rosas et al. found that female-headed households in rural Colombia had higher odds of intrahousehold DBM [ 47 ], while results from a pooled analysis of 23 African countries found no association with the sex of the head of household [ 14 ]. Conflicting results across studies and contexts could be influenced by the variation in sample populations, study design, and/or measures of household DBM.

It has been previously reported that the Philippines has one of the highest burdens of food insecurity in southeast Asia [ 48 ]. Food insecurity is strongly associated with a number of nutritional and cardio-metabolic health outcomes, including indicators of both under- and overnutrition [ 49 ]. In our analysis, food insecurity was associated with increased odds of household-level DBM, indicating that food insecurity may reduce household dietary quality and increases risk of multiple forms of malnutrition. Households experiencing food insecurity often modify their diets by decreasing the overall amount of food consumed and increasing consumption of cheaper, energy-dense, highly processed foods, thus creating a nutrition environment in which multiple forms of malnutrition can develop [ 48 ]. Studies from Brazil, Indonesia, and Colombia also found food insecurity was associated with the DBM at the household level [ 47 , 50 , 51 ]. Further research is needed to examine the precise mechanisms for this association, including how food insecurity interacts with environmental (e.g., food environment) and household (e.g., intrahousehold allocation of resources) factors to modify dietary consumption and influence risk of nutritional health outcomes [ 52 ].

We also found that household dietary diversity scores were associated with increased odds of intrahousehold DBM. This finding is contrary to our expectations, as the HDDS is often viewed as an indicator of a household’s economic ability to access food [ 38 ] and diversity is often seen as a key component of healthy diets [ 53 ]. While the HDDS is not intended as a proxy for dietary quality [ 38 ], studies elsewhere have established a positive association between household diet diversity and healthy diets [ 54 ], food security [ 55 ], and nutrition outcomes [ 56 ]. One might therefore expect that households with higher HDDS would have lower odds of DBM; however, we observed the inverse association in our analysis. This association was consistent across bivariate analyses and when controlling for household food security, wealth status, and occupation in the multivariable model. This finding may indicate that in the Philippines, households with greater dietary diversity consume larger quantities of non-nutrient-dense foods and/or live more sedentary lifestyles. Another possibility is the presence of intrahousehold disparities in resource allocation, leading to nutritional inequalities that are not identified by the household-level HDDS. However, such explanations remain purely conjecture given the limited information provided by HDDS. These findings may raise questions about the HDDS as an accurate indicator of food access and dietary quality. Researchers have previously criticized dietary diversity scores for their limited cross-cultural validity and misuse/misinterpretation in nutrition literature [ 57 – 59 ]. Other authors have critiqued the reliability and usefulness of the HDDS [ 57 , 60 ] as a research tool and promote tools (e.g., the World Food Programme’s Food Consumption Score) that assign higher weights to foods deemed most important for nutritional purposes [ 61 ]. Further research is therefore required to ensure validity and reliability of the HDDS across multiple global contexts [ 60 ], particularly since improved dietary diversity is often measured in DBM research [ 14 ] and is a stated goal of nutrition interventions. Future studies examining dietary determinants of intrahousehold DBM should also focus on measuring household dietary intake and quality, not just diversity.

This research provides important and novel insights into the household-level double burden of malnutrition in the Philippines. However, our study has several limitations. First, although we use data from a large, nationally representative sample, we were limited to the information and variables collected by the NNS. For instance, it was not possible to establish familial relations within each household (for example, in households with children and multiple women of reproductive age, we could not definitively identify mother-child pairs), which may limit the comparability of results with research on household-level DBM elsewhere. Second, while this the most recent NNS with publicly available data, the situation in the Philippines today has likely changed since 2013. Similar analysis of future NNS data should be done to get a more accurate picture of the intrahousehold DBM in the Philippines. Third, due to our use of a comprehensive definition of household-level DBM rather than focusing on the more common mother-child DBM pairs, the comparability of our study to other research on household-level DBM is limited. Further, although we did include some indicators of micronutrient deficiencies among adults, this paper did not assess the presence of these conditions as separate from underweight, or what is known as the triple burden of malnutrition. Due to limitations of the data set, which lacked an adequate number of complete micronutrient data from children and adolescents in our sample, assessing triple burden and double burden typologies separately increased the risk of misclassification bias and diminished the statistical power of the analyses.

In conclusion, we found a very high prevalence of intrahousehold DBM when considering all possible typologies of under- and overnutrition among household members in the Philippines, indicating that this form of the double burden of malnutrition is a major public health concern. This study highlights important gaps in the current understanding of household-level manifestations of the DBM, particularly those between adult-adult DBM parings. While further research is needed to investigate each of these specific typologies in greater detail, these findings support the need for more comprehensive surveillance of the DBM at the individual, household, and national levels in order to monitor progress and develop better targeted interventions. We identified a number of socio-economic and demographic factors associated with overall intrahousehold DBM, including household size, wealth quintile, food insecurity, and diet diversity. Double burden households were also influenced by head of household characteristics including sex, level of education, employment status, and age. These results suggest that key policy actions for reducing the DBM should center on supporting education and employment opportunities, gender equality, and social safety nets. Overall, this evidence provides important high-level insight into factors influencing household-level DBM in the Philippines and may help inform future research designs and directions.

Acknowledgments

We thank the Food and Nutrition Research Institute of the Department of Science and Technology, Philippines for providing access to the 2013 National Nutrition Survey data.

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• Open access
• Published: 16 April 2018

Nutritional status of children ages 0–5 and 5–10 years old in households headed by fisherfolks in the Philippines

• Mario V. Capanzana 1 ,
• Divorah V. Aguila 1 ,
• Glen Melvin P. Gironella 1 &
• Kristine V. Montecillo 1  

Archives of Public Health volume  76 , Article number:  24 ( 2018 ) Cite this article

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The study aimed to analyze the nutritional status of Filipino children ages 0–60 months (0–5.0 years old) and 61–120 months (5.08–10.0 years old) in households headed by fisherfolks.

The 8th National Nutrition Survey (NNS) data collected by the Food and Nutrition Research Institute, Department of Science and Technology (FNRI-DOST) was used in the study. There were 13,423 young children and 16,398 schoolchildren participants for anthropometry component. The World Health Organization Child Growth Standards (WHO-CGS) was used to assess the nutritional status of the young children while the WHO Growth Reference 2007 was used for schoolchildren. Occupational groups were categorized based on the 1992 Philippine Standard Occupational Classification (PSOC). Descriptive statistics were used for the profiling of the different variables while bivariate analysis, logistic regression and odds ratios were used to correlate the different variables to the nutrition status of the children. Data were analyzed using Stata 12.0.

Results showed that households headed by fisherfolks (HHF) were one of the occupational groups with highest malnutrition among young and school-aged children. The HHF had higher prevalence of malnutrition among young children compared to the overall prevalence of malnutrition among young children in the Philippines, except for overweight. This is also true for schoolchildren, except for wasting. Age of child, sex, household size, age, fishermen and farmer as household head and type of toilet (water-sealed) were correlated to stunting, underweight, overweight and obesity among children.

Conclusions

The high prevalence of stunting, underweight and wasting among young and schoolchildren in this occupational group poses immediate and serious nutrition intervention strategies such as health and nutrition information, health care, sanitation and hygiene, and physical activities. A national policy on the health, nutrition and welfare of households headed by fisherfolks and their children is highly recommended.

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Fisherfolks consistently top as the poorest sector in the Philippines from 2003 to 2012 based on the report of Philippine Statistics Authority (PSA) on Poverty Incidence of Basic Sectors [ 1 ]. Aside from the uncertainty of income among fishing communities, factors such as land ownership, debt, access to health, education and financial capital, as well as political and geographical marginalization also contribute to why poverty thrives in this sector [ 2 ]. Moreover, fisherfolks often live in places that have particularly high risk of extreme events; flooding, cyclones and tsunamis often visit coastal and floodplain fisheries, while inland fisheries can be significantly affected by droughts and floods. These disasters leave severe damages on infrastructures as well as productive assets such as boat, landing sites, post-harvesting facilities and road among fishing-dependent people. These consequently decrease their harvesting capacity and access to markets, affecting both local livelihood and the overall economy [ 3 ].

These kinds of disasters had also brought severe asset damages among fishing communities in the Philippines. In 2013, Typhoon Yolanda/Haiyan, one of the strongest typhoons that visited the country, affected Eastern Samar, Samar and Leyte. The National Disaster Risk Reduction and Management Council (NDRRMC) estimated that 16 million people were affected and 1.1 million houses were damaged. The livelihood of fisherfolks was also affected in the areas. There were nearly 30,000 small-scale fishing boats damaged while more than 100,000 were lost or destroyed [ 4 ]. Additionally, about 600,000 ha of agricultural land, 33 million coconut trees and 305 km farm-to-market road were damaged, whereas more than 400 health facilities and 1200 provincial, city and municipal and barangay halls and public markets were destroyed in the area [ 5 ].

Disasters, such as typhoon Yolanda/Haiyan, can have serious consequences for food security, nutrition and health. Damaged infrastructures due to extreme events or flooding can cut access to local markets, and consequently reduce the availability of food products and increase the food prices, resulting in higher incidences of malnutrition in communities [ 3 ].

These disturbances in nutrition as a result of inadequacy in food intake, health problems, or a combination of both, invariably affect the growth of children [ 6 ]. Hence, assessments on the nutritional status of children based on their anthropometric indicators of growth has been used not only in generating information on their nutritional and health status, but also in providing an indirect measurement of the quality of life of their community, and thereby as an indicator of the nutritional status and food intake adequacy of all members in that community [ 7 , 8 ].

Thus, this study aimed to focus and analyze the condition of households headed by fisherfolks (HHF) with respect to the nutritional situation by assessing the nutritional status of children ages 0–60 months (0–5.0 years old) and 61–120 months (5.08–10.0 years old), using the 8th National Nutrition Survey data. Factors affecting the nutritional status of the children in HHF were also analyzed to better understand the nutrition situation in the fishing communities in the Philippines.

The study was initiated to estimate the prevalence of malnutrition among young and school-aged children among fishing community as basis in planning and developing nutrition programs that will improve the nutritional situation of this occupational group. It is hoped that this study will provide significant information that can serve as basis for policy makers and program planners in the nutrition and fishery sectors among private or public organizations in drawing future strategies for improving the nutritional situation of the fisherfolks in the Philippines.

Conceptual framework

Malnutrition in children is the result of complex interaction of numerous and multifaceted factors. Thus, in the analysis of this study, the UNICEF’s conceptual framework for the causes of malnutrition was considered (Fig.  1 ). It was expected that factors such as age, gender, household size, occupation, and sanitation facilities were associated with the malnutrition among children in HHF.

UNICEF conceptual framework for the causes of malnutrition (Adapted from Mason, 2003)

The study used the data from 8th National Nutrition Survey (NNS) conducted by the Food and Nutrition Research Institute, Department of Science and Technology (FNRI-DOST) in 2013. The NNS was conducted in 79 provinces, 45,047 households and 172,323 individuals, adopting the 2003 master sample developed by Philippine Statistics Authority (PSA) [ 9 ]. A stratified multi-stage sampling design for household-based surveys covering all the 17 regions, including the National Capital Region was used.

The 2013 NNS used the four subsample or replicates of the master sample for its anthropometry component. There were 13,423 young children ages 0–60 months (0–5.0 years old) and 16,398 schoolchildren ages 61–120 months (5.08–10.0 years old) participated in the survey. The World Health Organization-Child Growth Standards (WHO-CGS) [ 10 ] was used to assess the nutritional status of young children, while WHO Growth Reference 2007 [ 11 ] was used for schoolchildren.

A written informed consent was obtained from all the participants of this study through the mother or guardian. Ethical clearance was provided by the FNRI Institutional Ethics Review Committee (FIERC).

To analyze the nutrition situation of the fisherfolks in the Philippines, the households were categorized into occupational groups based on the 1992 Philippine Standard Occupational Classification (PSOC) of PSA [ 12 ]. Descriptive statistics was employed to summarize data on the prevalence of malnutrition among young children and schoolchildren in different occupational groups including the fisherfolks. Logistic regression and multinomial logistic regression analyses were used to determine the association of variables to underweight, stunting, and overweight or obesity among children 0–5 years and 6–10 years children. Statistical analysis was conducted using Stata version 12.0.

The prevalence of malnutrition among Filipino children ages 0–60 months (0–5.0 years old) by occupational group in the Philippines is summarized in Table  1 . Results showed that stunting (30.3%) was the most prevalent malnutrition among children of this age group in the country, followed by underweight (19.9%). The prevalence of stunting and underweight in this age group are considered high based on the 1995 WHO cut-off for public health significance [ 13 ]. On the other hand, the prevalence of wasting among this age group was 7.9%. The prevalence of overweight was 5.0%.

The young children in household headed by fisherfolks (HHF) had higher prevalence of malnutrition compared to the overall prevalence of malnutrition among young children in the Philippines, except for overweight. The magnitude of underweight (26.4%), stunting (37.7%) and wasting (11.2%) were all alarmingly high and pose as serious public health concerns. The HHF had lower prevalence of overweight (3.2%) compared to the overall prevalence of overweight among young children in the Philippines.

Among the occupational groups, young children in HHF had the highest prevalence of underweight, stunting and wasting next to children belonging to household headed by forestry and related worker. They also had the lowest prevalence of overweight among all occupational groups.

The prevalence of malnutrition among Filipino children ages 61–120 months (5.08–10.0 years old) by occupational group in the Philippines is summarized in Table  2 . Findings showed that stunting (29.9%) is the foremost form of malnutrition that is prevalent among schoolchildren in the Philippines followed by underweight (29.1%). However, unlike the observation on the young children, the prevalence of overweight (9.1%) among schoolchildren was higher compared to the prevalence of wasting (8.6%).

Among HHF, underweight (39.9%) and stunting (39.9%) were the primary forms of malnutrition among schoolchildren. Compared to other occupational groups, schoolchildren in the fishing communities had the highest prevalence of underweight. Furthermore, the prevalence of underweight among fisherfolks was even higher compared to the prevalence of underweight among all schoolchildren in the Philippines (29.1%).

The prevalence of stunting among HHF was also higher compared to the prevalence of stunting among all schoolchildren in the Philippines (29.9%). However, compared to other occupational groups, schoolchildren in HHF had the highest prevalence of stunting next to forestry and related workers (43.3%) and farmers and other plant growers (40.1%).

Moreover, there was the same magnitude of wasting among all schoolchildren in the Philippines (8.6%) and those in fishing communities (8.6%). The magnitude of wasting among schoolchildren in fishing communities was also relatively high compared to the prevalence of wasting in other occupational groups.

Fisherfolks had lower prevalence of overweight among schoolchildren (4.0%) compared to the prevalence of overweight among all schoolchildren in the Philippines (9.1%). They even had the lowest prevalence of overweight among other occupational groups, next to forestry and related workers (2.6%).

With the other variables were held constant, logistic regression indicated that both stunting and underweight were influenced by the same variables. Older children (OR = 1.03; OR = 1.11), male gender (OR = 1.15; OR = 1.08), larger household (HH) size (OR = 1.08; OR = 1.07), and the occupation of the HH head, specifically fishermen (OR = 1.36; OR = 1.44) and farmers (OR = 1.51; OR = 1.32), increases the risk for stunting and underweight respectively. While older age of the HH head (OR = 0.99; OR = 0.99) and the use of water sealed toilet (OR = 0.57; OR = 0.59) manifested a protective effect on the nutrition status. Wasting or thinness was also correlated to gender of child but was not correlated to households headed by fishermen and farmer. For overweight and obesity, older children (OR = 0.93), household size (OR = 0.96), and the occupation of the household head, fishermen (OR = 0.71) and farmer (OR = 0.77) were found to decrease its risk while the use-of water-sealed toilet (OR = 1.29), gender (OR = 1.08) and age of household head increases it. Details were shown in Table 3 .

The present study showed that malnutrition is highly prevalent among children in HHF. Colds and cough, diarrhea, skin infections and asthma, sore eyes and various intestinal parasites are the common illness among children livisdng in coastal rural areas [ 14 , 15 ]. These kinds of illnesses affect the growth and nutritional status of children [ 16 ]. Perhaps, the nutritional status of children in HHF was compromised due to their poor health caused by their living environment.

Another factor that affects the nutritional status of children living in the coastal areas is the high risk of extreme events, such as typhoons and tsunamis [ 3 ]. In the Philippines, many families lost their livelihood, especially the famers and fishers, when typhoon Yolanda/Haiyan visited the country. The typhoon also damaged the means of transportation (i.e. boats) of people living in far flung areas. Because of this, they experienced difficulties going to city proper or mainland where most of the evacuation areas are located and relief goods are distributed making them to go on up to four days without food. As a result, malnutrition among children increased because of difficulties in accessing nutritious foods. It has been reported that 1.5 million children were identified as at risk of acute malnutrition [ 17 , 18 ].

Household socioeconomic status remains to be crucial determinant of nutritional status of children. Children in the poorest quintile had worse nutritional status than the ones from the richest group [ 19 ]. Thus, with HHF being the poorest sector in the country, the prevalence of undernutrition among fisherfolks may be due to their low economic capacity that limits their access to food and nutrition.

However, while poverty is a strong determinant of undernutrition among young children, it may not be true for schoolchildren. A study suggests that poverty is predictive factor to the poor nutrition among young children but not to the nutritional outcomes among schoolchildren [ 20 ]. On the other hand, factors such as household food insecurity, low maternal education and poor health are stronger predictor for the undernutrition of schoolchildren [ 21 ].

Furthermore, women in fishing communities often engage in economic activities to complement men’s decreasing income. In some areas, this results to substantial reduction in breast-feeding when mothers resumed their economic activities soon after delivery. Consequently, the quality of nutrition provided to the young children is compromised [ 22 ]. Moreover, various factors were also observed that are contributing to the nutritional status of schoolchildren. Quality of food intake, food availability, household size, literacy of person in charge of food preparation and household head are some of the factors associated to the nutritional status of schoolchildren. Food availability and nutrition education on balanced diet, food production and consumption are necessary, although not sufficient, to improve the nutritional status of schoolchildren [ 23 ].

Perhaps, in the case of fisherfolk communities in the Philippines, the living condition of this occupational group coupled with poor health, high risk to extreme events, poverty and poor quality of diet may have contributed to the occurrence of various forms of undernutrition among young and school-aged children.

On the other hand, along with high prevalence of undernutrition, overnutrition was also observed among young children in fishing community in the Philippines. Generally, overweight among young children is usually attributed to excessive calorie consumption and low calorie expenditure. The increased consumption of more energy-dense, nutrient-poor foods with high levels of sugar and saturated fats, together with reduced physical activity, have led to obesity rates that have increased three-fold or more since 1980 [ 24 ]. However, these reasons may be unlikely in poor households. A study suggests that overweight among young children in food insecure households may be due to other potential factors linked to obesity, like low activity levels and excessive television watching [ 25 ].

Moreover, overweight among children observed in coastal areas may be due to geographical disparities in terms of income. One study observed that those in coastal area with high economic status exhibited increase in the prevalence of overweight and obesity than those in other areas with less economic development [ 26 ]. Perhaps, in the present study, the overweight children in HHF may be located in coastal areas with high economic status.

Looking into the prevalence of malnutrition among children in HHF, it can be observed that there is a low prevalence of overweight and high prevalence of underweight, stunting and wasting children. This scenario can be attributed to limited access of children to high-calorie snacks and fast food which are hardly affordable. Thus, there are only few who are identified to overweight. Another plausible explanation given is that the children may have been engaged in a more physically demanding activities compared to their contemporaries [ 27 ].

Based on the results of the present study, there is a need for immediate action to intervene in the magnitude of undernutrition among this occupational group with priority on the needs of children. Young children are more prone to poor nutrition and health conditions than adults. Poor nutrition among children of this age could not only contribute to increased likelihood of contracting serious illnesses but may also have a permanent effect on their health and development [ 28 ].

In addition, aside from the direct welfare and financial costs of illness due to poor nutrition, schoolchildren with poor health can also grow up as an adult with poor lower health status with less education which in turn could result to intergenerational transmission of poverty [ 29 ]. Childhood undernutrition exposure has permanent socioeconomic and health consequences. These consequences may include metabolic and cardiovascular diseases, reduced learning ability, lowered years of schooling and intellectual performance in adulthood, reduced working ability, productivity and income, poor quality of life and overall poverty that could be transferred to the future generations [ 22 ].

Thus, investing in the nutritional status of young children and schoolchildren in HHF could break the cycle of poverty in this occupational group. Alleviating the poverty has been a challenge for the longest time now and starting from the poorest of the poor sectors in the country should be a good start.

Findings showed that young children in HHF had higher prevalence of malnutrition compared to the overall prevalence of malnutrition among young children in the Philippines, except for overweight. This is also true for schoolchildren in HHF, except for wasting. It also identified that fisherfolks were one of the occupational groups with highest malnutrition among young and school-aged children. The high magnitude of public health concern in terms of underweight, stunting and wasting among these age groups pose an immediate and serious need for action, prioritizing the nutritional needs of this occupational group.

Various factors could affect the nutritional status of children in fishing communities. Food security, socio-economic capacity, availability of health services, environmental sanitation and geographical disparity in terms of economic development are some of the factors that should be considered in formulating and prioritizing in nutrition programs for children in this occupational group. Possible interventions should include health and nutrition education program that advocates the promotion of children’s nutrition at home, physical activity, capacity building, sanitation and hygiene in the community. A national focus on the health, nutrition and welfare of fisherfolks is highly recommended.

Furthermore, forestry and related workers is another occupational group that exhibited alarmingly high prevalence of malnutrition among young and school-aged children. Perhaps, for future studies, it would be an interesting topic to explore and understand the determining factors of malnutrition in this occupation group.

Abbreviations

Annual Poverty Indicators Survey

FNRI Institutional Ethics Review Committee

Food and Nutrition Research Institute, Department of Science and Technology

households headed by fisherfolks

National Disaster Risk Reduction and Management Council

National Nutrition Survey

Philippine Statistics Authority

Philippine Standard Occupational Classification

World Health Organization-Child Growth Standards

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Acknowledgements

The authors would like to express their sincere gratitude to the children and their parents/guardians for being part of the study. The authors would also like to thank the WorldFish Philippines for funding this study.

This study was funded by the WorldFish Philippines. The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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MVC DVA MPG contributed to the design and acquisition of data and data analysis, MVC DVA KVM contributed to the data analysis and drafting of the manuscript. All authors read and approved the final manuscript.

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Capanzana, M.V., Aguila, D.V., Gironella, G.M.P. et al. Nutritional status of children ages 0–5 and 5–10 years old in households headed by fisherfolks in the Philippines. Arch Public Health 76 , 24 (2018). https://doi.org/10.1186/s13690-018-0267-3

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Received : 02 November 2016

Accepted : 14 March 2018

Published : 16 April 2018

DOI : https://doi.org/10.1186/s13690-018-0267-3

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Executive Summary Undernutrition in the Philippines June 2021

Executive Summary. For nearly 30 years, the rates of both wasting and stunting in the Philippines have been nearly flat. For 2019, the rate of stunting among children under five years of age (28.8 percent) was only slightly lower than in 2008 (32 percent)—the prevalence of underweight in 2019 was 19 percent and that of wasting was 6 percent. Based on the World Health Organization’s classification of undernutrition rates, the stunting prevalence of children in the Philippines is of “very high” public health significance. The Philippines’ 29 percent stunting rate places it fifth among countries in the East Asia and Pacific region, and among the top 10 countries globally. The Philippines’ high levels of childhood undernutrition can lead to a staggering loss of the country’s human and economic potential. The burden on the Philippines’ economy brought by childhood undernutrition was estimated at US$4.4 billion, or 1.5 percent of the country’s GDP, in 2015. Undernutrition robs Filipino children of their chance at a bright future. When viewed through the lens of the World Bank’s Human Capital Index (HCI), the country’s 2020 HCI score of 0.52 predicts that the future productivity of children born today will be 48 percent below what they might achieve if they were to enjoy complete education and full health. Undernutrition in the Philippines: Scale, Scope, and Opportunities for Nutrition Policy and Programming presents a comprehensive, analytical work on this topic. It provides evidence of why it is critical that the government of the Philippines prioritize tackling this persistent challenge. The report assesses the determinants and causes of childhood undernutrition and reviews current policies and programs directed at addressing this problem. Based on these analyses, the report provides recommendations of how national policies and programs can be strengthened to reduce the high rates of undernutrition in the country. It sets out to inform the debate on the causes and potential solutions of undernutrition while identifying high-priority policies and policy commitments for action.

6/14/2021 08:57:00 AM

6/15/2021 09:00:00 AM

Gabriel Demombynes,Nkosinathi Vusizihlobo Mbuya,Sharon Faye Piza

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PH-Undernutrition-Report-Executive-Summary-2021.pdf

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