Convergence and Divergence in Statistical and Programmatic Approaches to Address Child Stunting and Wasting

Convergence and Divergence in Statistical and Programmatic Approaches to Address Child Stunting... Undernutrition underlies almost half of all child deaths and has far-reaching educational, economic, and health impacts (1). Stunting and wasting are the major forms of child undernutrition and are perceived to be caused by disease and poor diet. However, stunting and wasting are not explained by these 2 factors alone, and although these conditions often coexist, stunting and wasting are largely treated as separate phenomena in research, policy, and programming. Bergeron and Castleman (2) highlighted 2 primary reasons for this specialization: perceived differences in the causes and in the solutions. Acute malnutrition often results from an immediate problem such as acute illness, and chronic malnutrition often is more closely associated with latent causes such as poverty, food insecurity, poor feeding practices, and health problems. Programmatically, the approach to acute malnutrition is treatment to avert child mortality and the approach to chronic malnutrition is prevention (3, 4). Recently, there has been debate about the relative convergence and divergence in research and programmatic approaches to addressing stunting and wasting. In 2016, Angood et al. (5) identified research priorities on the relation between stunting and wasting with the use of the Child Health and Nutrition Research Initiative methodology. The top 3 identified research priorities were “Can interventions outside of the 1000 days lead to catchup in height and other developmental markers?”, “What timely interventions work to mitigate seasonal peaks in both stunting and wasting?”, and “What is the optimal formula of ready-to-use foods to promote optimal ponderal growth and also support linear growth during and after recovery from severe acute malnutrition?” Richard et al. (6) highlighted the need for longitudinal studies to determine whether early signs of growth faltering manifest in subsequent stunting and wasting. In this issue of the Journal, Stobaugh et al. (7) report an association between linear growth and relapse to acute malnutrition in high-risk Malawian children during the year after recovery from moderate acute malnutrition (MAM). This research challenges the notion that stunting and wasting are separate phenomena and highlights the potential concept that linear growth faltering may put children at increased risk of MAM relapse. However, the interpretation of these findings relies on 2 methodologic assumptions that deserve debate and discussion: 1) directionality of findings, because of timing of longitudinal measurements, and 2) changes in height-for-age z scores (HAZs) being representative of growth faltering or catch-up growth. Although Stobaugh et al. (7) do briefly discuss the potential bidirectionality of the relation between stunting and wasting, their analysis and even their title posit that linear growth faltering itself is a risk factor for acute malnutrition. The majority of recent debate about the relation between stunting and wasting has focused on 2 other potential explanations for an association: 1) repeated bouts of acute malnutrition may cause linear growth faltering because the body preserves ponderal growth over linear growth (8–10) and 2) inflammation, immunodeficiency, poor feeding behaviors, and illness are underlying and interacting causes and consequences of both stunting and wasting (11, 12). As stated previously, longitudinal population studies are necessary for understanding the relation between ponderal and linear growth faltering. In the referenced cohort, all of the children entered the longitudinal cohort upon recovery from MAM and more than half of the children were stunted before enrollment (7). In addition, the children may or may not have had previous episodes or treatment for MAM. The length of recovery from MAM was highly varied, with the mean recovery of 32 ± 21 d (mean ± SD) indicating a significant amount of heterogeneity in the severity of malnourishment and ability to respond to treatment. Although the longitudinal follow-up of this cohort is a major strength, the study enrolled children in the middle of a “growth journey,” and resulting growth trajectories are likely heavily influenced by previous ponderal and linear growth faltering and underlying subclinical inflammation. The second assumption underlying the authors’ interpretation is that changes in HAZ scores are representative of growth faltering or catch-up growth. HAZ is a standardized measure that adjusts each child's height for the median expected height for a child's age and sex and is useful for comparing linear growth across populations. The utility of HAZ for assessing growth across time is questionable: the denominator of HAZ is the SD at a given age and the SD is cross-sectional and reflects the dispersion of heights at a given age. As children age, the SD increases, limiting the interpretability of using changes in HAZ to identify growth faltering or growth catch-up. For example, a child could have the same height at time 1 and time 2, but a larger denominator at time 2. This would appear as a positive difference in HAZ, but with no actual change in height. This phenomenon has been reported in several studies in which HAZ scores increased despite increasing height deficits (13, 14). In the current article, the authors state that age was associated with odds of relapse, with younger children being more likely to relapse. HAZ at a younger age would also have a smaller SD than the SD for older children, so younger children would be more likely mathematically to have a negative change in HAZ and be characterized as experiencing growth faltering. The authors conclude that negative changes in HAZ are predictive of subsequent relapse to MAM or severe acute malnutrition in children who have recovered from MAM. This conclusion is valid within the constructs of the study and offers additional insight about potential risk factors for relapse in this high-risk population. As discussed above, this conclusion is based on 2 assumptions about directionality of effect and the definition of growth faltering, which may or may not be valid. Nevertheless, this research shows a relation between stunting and wasting that should not be ignored. Although there is no “gold standard” to characterize growth faltering longitudinally, future studies could avoid analytical issues related to z scores by using more appropriate methods of quantifying growth trajectories across time. Leroy et al. (15) recommend using an absolute height-for-age difference [difference in height (centimeters) between 2 time points – the median difference for a child of that age (centimeters)]. Divergent analytical approaches may be necessary to accurately characterize the relation between stunting and wasting and motivate convergence in program design to address child undernutrition more globally. Acknowledgments The sole author had responsibility for all parts of the manuscript. Notes The author reported no funding received for this commentary. Author disclosures: LES, no conflicts of interest. References 1. Black RE , Victora CG , Walker SP , Bhutta ZA , Christian P , de Onis M , Ezzati M , Grantham-McGregor S , Katz J , Martorell R . Maternal and child undernutrition and overweight in low-income and middle-income countries . Lancet 2013 ; 382 : 427 – 51 . Google Scholar CrossRef Search ADS PubMed 2. Bergeron G , Castleman T . Program responses to acute and chronic malnutrition: divergences and convergences . Adv Nutr 2012 ; 3 : 242 – 9 . Google Scholar CrossRef Search ADS PubMed 3. WHO. Updates on the management of severe acute malnutrition in infants and children . Geneva (Switzerland) : WHO ; 2013 . 4. WHO. Global nutrition targets 2025: stunting policy brief . Geneva (Switzerland) : WHO : 2014 . 5. Angood C , Khara T , Dolan C , Berkley JA . Research priorities on the relationship between wasting and stunting . PLoS One 2016 ; 11 : e0153221 . Google Scholar CrossRef Search ADS PubMed 6. Richard SA , Black RE , Checkley W . Revisiting the relationship of weight and height in early childhood . Adv Nutr 2012 ; 3 : 250 – 4 . Google Scholar CrossRef Search ADS PubMed 7. Stobaugh HC , Rogers BL , Rosenberg IH , Webb P , Maleta K , Manary MJ , Trehan I . Children with poor linear growth are at risk for repeated relapse to wasting after recovery from moderate acute malnutrition . J Nutr 2018 ; 148 : 974 – 979 . 8. Dewey KG , Hawck MG , Brown KH , Lartey A , Cohen RJ , Peerson JM . Infant weight-for-length is positively associated with subsequent linear growth across four different populations . Matern Child Nutr 2005 ; 1 : 11 – 20 . Google Scholar CrossRef Search ADS PubMed 9. Walker SP , Grantham-McGregor SM , Himes JH , Powell CA . Relationships between wasting and linear growth in stunted children . Acta Paediatr 1996 ; 85 : 666 – 9 . Google Scholar CrossRef Search ADS PubMed 10. Costello AM . Growth velocity and stunting in rural Nepal . Arch Dis Child 1989 ; 64 : 1478 – 82 . Google Scholar CrossRef Search ADS PubMed 11. Bourke CD , Berkley JA , Prendergast AJ . Immune dysfunction as a cause and consequence of malnutrition . Trends Immunol 2016 ; 37 : 386 – 98 . Google Scholar CrossRef Search ADS PubMed 12. Petrou S , Kupek E . Poverty and childhood undernutrition in developing countries: a multi-national cohort study . Soc Sci Med 2010 ; 71 : 1366 – 73 . Google Scholar CrossRef Search ADS PubMed 13. Leroy JL , Ruel M , Habicht JP , Frongillo EA . Linear growth deficit continues to accumulate beyond the first 1000 days in low- and middle-income countries: global evidence from 51 national surveys . J Nutr 2014 ; 144 : 1460 – 6 . Google Scholar CrossRef Search ADS PubMed 14. Lundeen EA , Stein AD , Adair LS , Behrman JR , Bhargava SK , Dearden KA , Gigante D , Norris SA , Richter LM , Fall CH et al. Height-for-age z scores increase despite increasing height deficits among children in 5 developing countries . Am J Clin Nutr 2014 ; 100 : 821 – 5 . Google Scholar CrossRef Search ADS PubMed 15. Leroy JL , Ruel M , Habicht JP , Frongillo EA . Using height-for-age differences (HAD) instead of height-for-age z-scores (HAZ) for the meaningful measurement of population-level catch-up in linear growth in children less than 5 years of age . BMC Pediatr 2015 ; 15 : 145 . Google Scholar CrossRef Search ADS PubMed © 2018 American Society for Nutrition. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Nutrition Oxford University Press

Convergence and Divergence in Statistical and Programmatic Approaches to Address Child Stunting and Wasting

Journal of Nutrition , Volume Advance Article (6) – Jun 7, 2018

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Publisher
Oxford University Press
Copyright
© 2018 American Society for Nutrition.
ISSN
0022-3166
eISSN
1541-6100
D.O.I.
10.1093/jn/nxy098
Publisher site
See Article on Publisher Site

Abstract

Undernutrition underlies almost half of all child deaths and has far-reaching educational, economic, and health impacts (1). Stunting and wasting are the major forms of child undernutrition and are perceived to be caused by disease and poor diet. However, stunting and wasting are not explained by these 2 factors alone, and although these conditions often coexist, stunting and wasting are largely treated as separate phenomena in research, policy, and programming. Bergeron and Castleman (2) highlighted 2 primary reasons for this specialization: perceived differences in the causes and in the solutions. Acute malnutrition often results from an immediate problem such as acute illness, and chronic malnutrition often is more closely associated with latent causes such as poverty, food insecurity, poor feeding practices, and health problems. Programmatically, the approach to acute malnutrition is treatment to avert child mortality and the approach to chronic malnutrition is prevention (3, 4). Recently, there has been debate about the relative convergence and divergence in research and programmatic approaches to addressing stunting and wasting. In 2016, Angood et al. (5) identified research priorities on the relation between stunting and wasting with the use of the Child Health and Nutrition Research Initiative methodology. The top 3 identified research priorities were “Can interventions outside of the 1000 days lead to catchup in height and other developmental markers?”, “What timely interventions work to mitigate seasonal peaks in both stunting and wasting?”, and “What is the optimal formula of ready-to-use foods to promote optimal ponderal growth and also support linear growth during and after recovery from severe acute malnutrition?” Richard et al. (6) highlighted the need for longitudinal studies to determine whether early signs of growth faltering manifest in subsequent stunting and wasting. In this issue of the Journal, Stobaugh et al. (7) report an association between linear growth and relapse to acute malnutrition in high-risk Malawian children during the year after recovery from moderate acute malnutrition (MAM). This research challenges the notion that stunting and wasting are separate phenomena and highlights the potential concept that linear growth faltering may put children at increased risk of MAM relapse. However, the interpretation of these findings relies on 2 methodologic assumptions that deserve debate and discussion: 1) directionality of findings, because of timing of longitudinal measurements, and 2) changes in height-for-age z scores (HAZs) being representative of growth faltering or catch-up growth. Although Stobaugh et al. (7) do briefly discuss the potential bidirectionality of the relation between stunting and wasting, their analysis and even their title posit that linear growth faltering itself is a risk factor for acute malnutrition. The majority of recent debate about the relation between stunting and wasting has focused on 2 other potential explanations for an association: 1) repeated bouts of acute malnutrition may cause linear growth faltering because the body preserves ponderal growth over linear growth (8–10) and 2) inflammation, immunodeficiency, poor feeding behaviors, and illness are underlying and interacting causes and consequences of both stunting and wasting (11, 12). As stated previously, longitudinal population studies are necessary for understanding the relation between ponderal and linear growth faltering. In the referenced cohort, all of the children entered the longitudinal cohort upon recovery from MAM and more than half of the children were stunted before enrollment (7). In addition, the children may or may not have had previous episodes or treatment for MAM. The length of recovery from MAM was highly varied, with the mean recovery of 32 ± 21 d (mean ± SD) indicating a significant amount of heterogeneity in the severity of malnourishment and ability to respond to treatment. Although the longitudinal follow-up of this cohort is a major strength, the study enrolled children in the middle of a “growth journey,” and resulting growth trajectories are likely heavily influenced by previous ponderal and linear growth faltering and underlying subclinical inflammation. The second assumption underlying the authors’ interpretation is that changes in HAZ scores are representative of growth faltering or catch-up growth. HAZ is a standardized measure that adjusts each child's height for the median expected height for a child's age and sex and is useful for comparing linear growth across populations. The utility of HAZ for assessing growth across time is questionable: the denominator of HAZ is the SD at a given age and the SD is cross-sectional and reflects the dispersion of heights at a given age. As children age, the SD increases, limiting the interpretability of using changes in HAZ to identify growth faltering or growth catch-up. For example, a child could have the same height at time 1 and time 2, but a larger denominator at time 2. This would appear as a positive difference in HAZ, but with no actual change in height. This phenomenon has been reported in several studies in which HAZ scores increased despite increasing height deficits (13, 14). In the current article, the authors state that age was associated with odds of relapse, with younger children being more likely to relapse. HAZ at a younger age would also have a smaller SD than the SD for older children, so younger children would be more likely mathematically to have a negative change in HAZ and be characterized as experiencing growth faltering. The authors conclude that negative changes in HAZ are predictive of subsequent relapse to MAM or severe acute malnutrition in children who have recovered from MAM. This conclusion is valid within the constructs of the study and offers additional insight about potential risk factors for relapse in this high-risk population. As discussed above, this conclusion is based on 2 assumptions about directionality of effect and the definition of growth faltering, which may or may not be valid. Nevertheless, this research shows a relation between stunting and wasting that should not be ignored. Although there is no “gold standard” to characterize growth faltering longitudinally, future studies could avoid analytical issues related to z scores by using more appropriate methods of quantifying growth trajectories across time. Leroy et al. (15) recommend using an absolute height-for-age difference [difference in height (centimeters) between 2 time points – the median difference for a child of that age (centimeters)]. Divergent analytical approaches may be necessary to accurately characterize the relation between stunting and wasting and motivate convergence in program design to address child undernutrition more globally. Acknowledgments The sole author had responsibility for all parts of the manuscript. Notes The author reported no funding received for this commentary. Author disclosures: LES, no conflicts of interest. References 1. Black RE , Victora CG , Walker SP , Bhutta ZA , Christian P , de Onis M , Ezzati M , Grantham-McGregor S , Katz J , Martorell R . Maternal and child undernutrition and overweight in low-income and middle-income countries . Lancet 2013 ; 382 : 427 – 51 . Google Scholar CrossRef Search ADS PubMed 2. Bergeron G , Castleman T . Program responses to acute and chronic malnutrition: divergences and convergences . Adv Nutr 2012 ; 3 : 242 – 9 . Google Scholar CrossRef Search ADS PubMed 3. WHO. Updates on the management of severe acute malnutrition in infants and children . Geneva (Switzerland) : WHO ; 2013 . 4. WHO. Global nutrition targets 2025: stunting policy brief . Geneva (Switzerland) : WHO : 2014 . 5. Angood C , Khara T , Dolan C , Berkley JA . Research priorities on the relationship between wasting and stunting . PLoS One 2016 ; 11 : e0153221 . Google Scholar CrossRef Search ADS PubMed 6. Richard SA , Black RE , Checkley W . Revisiting the relationship of weight and height in early childhood . Adv Nutr 2012 ; 3 : 250 – 4 . Google Scholar CrossRef Search ADS PubMed 7. Stobaugh HC , Rogers BL , Rosenberg IH , Webb P , Maleta K , Manary MJ , Trehan I . Children with poor linear growth are at risk for repeated relapse to wasting after recovery from moderate acute malnutrition . J Nutr 2018 ; 148 : 974 – 979 . 8. Dewey KG , Hawck MG , Brown KH , Lartey A , Cohen RJ , Peerson JM . Infant weight-for-length is positively associated with subsequent linear growth across four different populations . Matern Child Nutr 2005 ; 1 : 11 – 20 . Google Scholar CrossRef Search ADS PubMed 9. Walker SP , Grantham-McGregor SM , Himes JH , Powell CA . Relationships between wasting and linear growth in stunted children . Acta Paediatr 1996 ; 85 : 666 – 9 . Google Scholar CrossRef Search ADS PubMed 10. Costello AM . Growth velocity and stunting in rural Nepal . Arch Dis Child 1989 ; 64 : 1478 – 82 . Google Scholar CrossRef Search ADS PubMed 11. Bourke CD , Berkley JA , Prendergast AJ . Immune dysfunction as a cause and consequence of malnutrition . Trends Immunol 2016 ; 37 : 386 – 98 . Google Scholar CrossRef Search ADS PubMed 12. Petrou S , Kupek E . Poverty and childhood undernutrition in developing countries: a multi-national cohort study . Soc Sci Med 2010 ; 71 : 1366 – 73 . Google Scholar CrossRef Search ADS PubMed 13. Leroy JL , Ruel M , Habicht JP , Frongillo EA . Linear growth deficit continues to accumulate beyond the first 1000 days in low- and middle-income countries: global evidence from 51 national surveys . J Nutr 2014 ; 144 : 1460 – 6 . Google Scholar CrossRef Search ADS PubMed 14. Lundeen EA , Stein AD , Adair LS , Behrman JR , Bhargava SK , Dearden KA , Gigante D , Norris SA , Richter LM , Fall CH et al. Height-for-age z scores increase despite increasing height deficits among children in 5 developing countries . Am J Clin Nutr 2014 ; 100 : 821 – 5 . Google Scholar CrossRef Search ADS PubMed 15. Leroy JL , Ruel M , Habicht JP , Frongillo EA . Using height-for-age differences (HAD) instead of height-for-age z-scores (HAZ) for the meaningful measurement of population-level catch-up in linear growth in children less than 5 years of age . BMC Pediatr 2015 ; 15 : 145 . Google Scholar CrossRef Search ADS PubMed © 2018 American Society for Nutrition. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

Journal of NutritionOxford University Press

Published: Jun 7, 2018

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