SLIDE 1 XXVIII IUSSP International Population Conference
Full paper submission Title: Trends of Inequalities in Child Malnutrition in Nepal: Does they Swimming against Tide?
Authors
Harchand Ram (Corresponding and presenting Author) Doctoral Student Centre for the Study of Regional Development (CSRD) School of Social Sciences (SSS) Jawaharlal Nehru University (JNU) Phone No: +91 7506541092 Email: hm8460@gmail.com; harcha28_ssf@jnu.ac.in Mohammad Zahid Siddiqui Doctoral Student Centre for the Study of Regional Development (CSRD) School of Social Sciences (SSS) Jawaharlal Nehru University (JNU)
Assistant Professor Centre for the Study of Regional Development (CSRD) School of Social Sciences (SSS) Jawaharlal Nehru University (JNU) Abstract: This study examines the trends and patterns of averages vis-a-vis inequalities in child malnutrition by wealth status of population across regions and place of residence of Nepal. Data from the two rounds of Nepal Demographic and Health Survey (NDHS) 2006 and 2011 were
- analysed. The proportion of children Underweight, Stunting and Wasting (moderate and severe)
have been used as a dependent variable and wealth index as a proxy for economic status of the
- population. Bivariate analysis, Poorest-Richest (P-Rt) ratio, Poorer-Richer (P-Rr) ratio and
concentration indices were used to examine the trends in averages vis-a-vis economic inequalities in children nutritional status. Results indicated that, in spite of a substantial improvement in average nutritional status from 2006 to 2001 (Underweight declined by 10 percentage points), but the corresponding improvement was not observed in inequality in nutritional status (P-Rt ratio rose by 1.5 times and concentration indices rose by -0.59). The
SLIDE 2
similar finding was observed in Wasting and Stunting. Further, the findings suggest that the inequalities in child malnutrition in Nepal are swimming against its progress in averages. This implies that the benefits of improvements in child nutritional status by passed the children of poorest wealth quintiles while it disproportionately benefiting children of richer and richest wealth quintiles. Therefore, Policies and programmes that are targeting to improve nutritional status need to focus on both efficiency and equity. Introduction: ‘Social inequalities are killing people on a grand scale’ this statement of the World Health Organization (WHO) report on health inequality has rejuvenated the earlier debates on social inequalities in health (WHO 2008). Even now a majority of the people doesn’t enjoy the good health that is biologically and naturally possible. A burgeoning volume of research before and after this report have documented that the toxic combination of exclusive socioeconomic and public health policies, and the politics are accountable for this (Wagstaff & Wanatable, 2000; Wagstaff et al., 2003; Marmot, 2005; Deaton, 2013). Monitoring socioeconomic inequalities and formulating policy in order to try to combat them had a long tradition in the developed world since the first half of the nineteenth century. The evidence suggests that for long run there is an increasing gap in mortality at all ages between poor and well off section of society in most industrialized countries. These gaps have frequently claimed to be unjust and policies were made to reduce them (Drever and Whiteland 1997, Acheson 1998) whereas in developing countries, the issues of socioeconomic inequalities in health have been started to receive attention recently. Prior to this, the main focus is on improving the health averages. The health progress in any country is measured based on the progress in health averages (Wagstaff and van Doorslaer, 1991; Kakwani et al., 1997; Gwatkin 2000; Goli and Arokiasamy, 2013; Hosseinpoor et al., 2006). Nepal is small, food deficit, landlocked and less developed country in South Asia (Goli et al., 2015). The country has never documented any economic miracle or debacle. According to United Nations Development Programme (UNDP) report on human development, Nepal ranks 145th out of 187 countries in terms of Human Development Index (UNDP, 2013). Among the numerous health challenges faces by Nepal, the reduction of the child malnutrition needs instantaneous attention of program and policy maker (Martorell et al., 1984; Joshi, 2012; Niraula, 2013). Adequate nutrition is most important for the development of the country as well as well-being of the individuals. Generally poor nutritional status affects the entire population and especially it affects the women and children more because of their unique physiological
SLIDE 3 needs and greater vulnerability to socioeconomic deprivation (Walkins and Marmot, 2003). The Nepal nutrition report card documented that: approximately 1.7 million children, i.e. nearly half
- f all the children five years old in the country are stunted or suffer from under nutrition. About
47 percent of children below age five are underweight (less weight as per the height); 54 percent
- f them are stunted (less height as per the age), and 7 percent being wasted (thinner for height)
(Nepal micronutrient status survey, 1998). The reduction of absolute poverty from 46 in 1996 to 31 in 2004 is a significant improvement in economic condition of Nepal. Per capita income has also increased and improvements in public health indicators occurred due to advances in medicines, openness of economy, agricultural advancement and remittance. The last 15 years in Nepal witnessed a substantial reduction of child mortality; by large the most contributing factor is reduced in nutritional deficiency. Programs and policies targeted towards reduction of malnutrition are the fruits of surveys that start long back and lighten the intensity of problem. Government of Nepal is prioritizing their motive to the improvements of nutritional status of children and mothers, including food security scrutinizing and early caution. But the improvements in health status or fruits of economic growth are not uniformly distributed and the better off sections are achieving highest level of health whereas poor and downtrodden sections of people are receiving negligible health improvements. This period also witnessed the widening inequality in income, health of mother and child, consumption and in assets. Similarly, the scenario of poverty and malnutrition reduction was not uniform among the caste and ethnic groups and even in all regions of the country (NLSS I, 1996 and NLSS II, 2004 and NDHS 4, 2011, Central bureau of statistics, Nepal government). In this context, an important question arises is “Does improvements in average of child malnutrition leading to greater uniformity in health distribution or health inequalities are swimming against the averages”. The several health inequality studies referred above either excluded Nepal or did not analyze the relationship between “averages of children nutrition versus inequalities in child nutrition”. Moreover, understanding the relationship between “averages of children nutrition versus inequalities in child nutrition” is critical in monitoring and evaluation of existing socioeconomic, health and nutrition policies, especially to know how inclusive are they? Literature suggests that from early 2000, Nepal is at the peak of nutritional transition, but, whether the economically poor and other disadvantaged children are part of such transition or not, is need to be examined. Examining the inequalities in nutritional status during transition help us to understand the question, whether the benefits are uniformly distributed or
SLIDE 4 fruits of transition are unequally distributing among children of different socioeconomic background? Theoretical Framework and Evidence Gap The connection between health inequality and per capita income is probably due to technological change going hand-in-hand with economic development, paired with a propensity for the more well-off to take up new technology and innovation ahead of the poor. In other words, it is just that richer people absorb new health technology and purchasing power faster than poorer ones (Wagstaff, 2002). Often, the efforts to achieve health targets may increase inequalities with the better-off in a society benefiting disproportionately, in consequence lead to increase in health inequality with increasing in health averages (Contoyannis & Forster, 1999b; Victoria et al., 2000;Wagstaff, 2002; Moser et al., 2005; Goli & Arokiasamy, 2014). Because not all societies are equally prepared to innovate or draw the benefits of the innovation from outside, this phenomenon leads to increase in inequality followed by decreasing of inequalities when late entering population become able to catch up pioneering until the new technologies discovered or new advances happened (Vallin & Mesle, 2004). However, very few studies attempted to explain the question: how does rising health averages pushing up the health inequalities? Panayotov (2008) developed a framework showing the relationship between ‘AHS and HI’ (Figure 1). He said “improvement in average health status can mask widening of health inequalities. This is a situation where health gain and health equity are not interdependent as it complies with Kaldor-Hicks criterion for efficiency”1. He explained the association between AHS and HI in time as the outcomes of different combinations of distribution of the benefit among the population. The concrete curve for specific population is not something fixed or static. It is something dynamic, which is constantly impacted by the distribution of the benefit from implementing policies, programs and interventions in the population. In other words, the concrete situation constantly changes depending on who-gets-what and how-much from implemented policies, programs and interventions in their interaction. Theoretically, there are eight possible combinations between
A Kaldor–Hicks improvement, named for Nicholas Kaldor and John Hicks, also known as the Kaldor– Hicks criterion, is a way of judging economic re-allocations of resources among people that captures some of the intuitive appeal of Pareto improvements, but has less stringent criteria and is hence applicable to more circumstances. A re-allocation is a Kaldor–Hicks improvement if those that are made better off could hypothetically compensate those that are made worse off and lead to a Pareto-improving
- utcome. The compensation does not actually have to occur (there is no presumption in favor of status-
quo) and thus, a Kaldor–Hicks improvement can in fact leave some people worse off (Kaldo and Hicks, 1939).
SLIDE 5
AHS and HI and one when there is no change in both variables. Of these eight, four combinations (“major”) have change in both variables – AHS and HI, and four (“minor”) have change in any one variable while the other remains the same. Major combinations are represented in the following cases: 1) AHS increases and HI increase (red line) 2) AHS increases and HI decrease (green line) 3) AHS decreases and HI increase (black line, left and up) 4) AHS decreases and HI decrease (dashed black line, left and down) Figure 1. Panayotov’s framework showing the relationship between average health status and health inequalities The explanation of Panayotov’s framework is also similar to that of the relationship between income growth and health inequalities. As said above, the rising inequalities will be more likely if new health technology is dispersed through the population unequally with the higher income groups adopting it ahead of the lower income groups. However, there is a dearth of empirical evidence on the relationship between “health average and health inequalities”. Until recently in both developing and developed countries, the literature on health subject is focused on either averages or inequalities independently (Kakwani et al., 1997; Gwatkin, 2000; Kawachi et al., 2002; Subramanyam and Subramanyam, 2011; Tonoyan and Lusine, 2012). There are few studies which documented the relationship between health average and health inequalities (Contoyannis & Forster, 1999b; Victoria et al., 2000; Wagstaff, 2002). With reference to Nepal, there is hardly any study which the relationship between “health average and health inequalities”. Thus, this study for the first time aims to examine the association between “health
SLIDE 6 average and health inequalities” by using the information on nutritional status of children in the context of Nepal. Methods: Data: This study used the data from two consecutive surveys round of Nepal Demographic and Health Survey (NDHS-2006 and NDHS-2011). NDHS is homogenous to Demographic and Health Survey conducted in over 90 countries. The DHS conducted in many countries with similar
- questions. It collects the information on socioeconomic, demographic, fertility, mortality, child
& maternal health and health care utilization. In addition, it also collects the bio-anthropometric measure of child and maternal nutritional status. Information on anthropometric indicators for children under age five years has been used uniformly to investigate the economic inequalities in nutritional status in both the rounds of NDHS. It provides information about weight-for-age (Underweight), weight-for-height (Wasting), and height-for-age (Stunting) in both the rounds (Nepal Demographic and Health Survey 2006, 2011). A Child (below five years of age) whose weight-for-age is below minus two standard deviations from WHO reference population (WHO Multicentre Growth reference study group, 2006) is classified as “moderate underweight”. While “Severe Underweight” defined as children whose “weight-for-age” is below minus three standard deviations from WHO reference population (WHO Multicentre Growth reference study group, 2006). Similar classification has been used for deriving the stunting and wasting estimates. In the absence of direct data on income or expenditure we used wealth status as a proxy for assessing the economic status of the
- household. Wealth quintiles were based on 33 assets and housing characteristics; each
household asset was assigned a weight (factor score) generated through principal component analysis, and the resulting asset scores standardized in relation to a normal distribution with mean of zero and standard deviation of one (Rustein and Johnson, 2004)). Sampling: The multi-stage stratified cluster sampling has used in NDHS 2006 and 2011. Administratively Nepal is divided into 75 districts, which are further divided into smaller units known as village development committees (VDCs) in rural areas and the municipalities in urban areas. The VDCs are further divided into two wards: larger wards and sub-wards. An Enumeration Area
SLIDE 7 (EA) has a ward in the rural areas and sub-wards in the urban areas. The sampling design
- btains 13 domains by cross classifying the three ecological regions and five developmental
regions (stratum). The sampling weights have used in NDHS: at first stage probability proportionate to size for selection of EAs, to obtain the target size of each domain. In the second stage 35 households from urban and 40 households from rural areas selected randomly (NDHS- 4). For more detail on sampling see ICF International and PDMDP (2011). Statistical Methods: Bi-variate analysis was carried out to investigate the trends in children nutritional status across the different socio-demographic characteristics and different geographic regions of Nepal for both the survey years. Pearson chi-square was performed to check whether the difference in child malnutrition by wealth and region of residence were significant in the bi-variate analysis. The framework given by Mackenbach and Kunst (1997) for measuring the magnitude of socioeconomic inequality in health, which was developed by the World Health Organization (WHO) European region to monitor changes over time, has been used for the analysis. They suggest Poor-Rich ratio for the measurement of socioeconomic inequality in health. We measured both Poorest-Richest (P-Rt) ratio and Poorer-Richer (P-Pr) ratio in child nutritional
- indicators. If the Poorest-Richest (P-Rt) ratio has a value of 1, it indicates that the poorest and
richest experiences the malnutrition equally; and if the Poorest-Richest (P-Rt) ratio is greater than 1, the poorest are more likely to suffer from the malnutrition than the richest, and if it is below 1, the richest are more likely to suffer than the poorest. Concentration Index (CIs) To assess the socioeconomic inequality in health, we used concentration index proposed by Wagstaff et al. (1991). The concentration index is computed as twice the (weighted) covariance
- f the health variables, and a person’s relative rank in terms of economic status, divided by the
variable mean according to the equation: 𝐷 = 2 µ covw(Yi, Ri) Where Yi and Ri are, respectively, the nutritional status of the ith individual and the fractional rank of the ith individual (for weighted data) in terms of the index of household economic status, µ is the (weighted) mean of the nutrition variable of the sample and covw denotes the weighted
- covariance. The value of the concentration index can vary between –1 and +1. Its negative
SLIDE 8 values imply that a variable is concentrated among disadvantaged people, while the opposite is true for its positive values. When there is no inequality, the concentration index will be zero. Results: Trends, patterns and differentials in child malnutrition by economic status The estimates of trends in averages and inequalities of child malnutrition by economic status and geographical regions in Nepal from 2006 to 2011 revealed that, though there is consistent decline in the prevalence of child malnutrition over the period, the children from the poorest wealth quintiles fared worse than their richest counterparts. The differences in the prevalence of child malnutrition across different economic and geographical regions of residence were highly
- significant. For instance, in 2006 nearly 47 percent of the children among the poorest quintile
were underweight (moderate) whereas only 19 percent of children from the richest quintile were underweight (moderate). Similarly, 14 percent of children from the poorest quintiles household as compared to just 3 percent of children from the richest quintiles household were severely
- underweight. The prevalence of child malnutrition in 2011 also revealed more or less same
- patterns. In specific, nearly 40 percent of children among poorest quintiles were underweight
(moderate) while the prevalence of underweight (moderate) among the richest quintile was even below 10 percent. The prevalence of stunting (moderate) among the children of poorest quintile was 61 percent as compared to 30 percent of children among the richest counties in 2006. Whereas in 2011 these trends were not changed much, but reduced marginally to 56 percent in the poorest and 24 percent in the richest quintiles households. Wasting of children also depicts the same patterns of inequalities by wealth quintiles. The overall results indicate that levels of child malnutrition were much higher among children from the poorest quintile compared to those in the richest quintile for moderate and severe child malnutrition status (Table 1, 2 and 3). Therefore, the decline in child malnutrition during 2006-2011 was much lower among the poorest quintiles as compare to richest quintiles. Decline in underweight among the children of poorest quintiles were 6 percent (from 46.5 to 40.3), whereas among the richest quintile halves the prevalence of underweight (from 18.6 to 9.9). This slower decline in child malnutrition among the poor as compare to better-off during 2006-2011 indicative of the rising inequality that was disadvantageous to the poor. The growing inequality trends can be observed from the increasing poorest richest ratio and poorer richer ration as well as declining concentration index
- value. The increasing trends of richest-poorest ratio observed from the table 2, which shows that
SLIDE 9 it increased from the 2.50 in 2006 to 4.07 in 2011 while measuring the underweight (moderate), whereas poorer richer ratio was 1.60 in 2006 to 2.24 in 2011, while measuring the prevalence of severe underweight. Declined value of concentration also demonstrated the increasing inequalities, which were -0.125 in 2006 as compared to -0.184 in 2011 while measuring the children underweight (moderate). While the indicator of severe underweight had alarmingly decreasing value of concentration index and observed at -0.178 in 2006 and -0.238 in 2011. Similar patterns of economic inequality observed by richest-poorest ratio, richer-poorer ratio and concentration index while measuring the children wasting and stunting. Results suggested that richest-poorest ratio increased (from 2.02 to 2.25) and a richer, poorer ratio increased (from 1.36 to 1.51) for measuring stunting (moderate) while, these values were 1.70 to 1.64 and 1.15 to 1.42 accordingly for measuring children wasting (moderate) during the period of 2006-2011. Furthermore, the children with severe stunting and severe wasting also depicts the similar patterns, for instance, poorest richest ratio and poorer richer ratio were increased from 2.99 to 4.91, 1.57 to 2.58, while measuring severe stunting and for severe wasting, it was 2.48 to 1.03 and 1.17 to 1.24 during the period of 2006-2011. The levels of child malnutrition were falling economic inequalities with respect to increase in child malnutrition, thereby being disadvantageous to the poor (Table 1, 2 and 3). Inequality examination by different economic status and region of residence Earlier evidence shows that a mere examination of overall inequality trends at the national level might delude our understanding in a country with diverse geographical regions (Goli et al., 2015). Economic inequality with respect to child malnutrition varied considerably across the different place of residence and geographic regions in Nepal. Economic inequalities in child malnutrition by place of residence revealed that in rural areas, the poorest-richest ratio was increased from 2.18 in 2006 to 4.24 in 2011 for the children being underweight (moderate) and concentration index value for the rural areas decreased (from -0.195 to -0.253) during the period
- f 2006-2011 (Table 4). In case of severe underweight, poorest and richest ratio declined from
6.54 in 2006 to 4.76 in 2011, but concentration index rose from -0.128 in 2006 to 2011. The children who were stunted and wasted also depict the similar patterns. In particular, the results
- f concentration index revealed that economic inequalities among the rural children in terms of
malnutrition have increased over the period in a majority of the indicators considered in the
- study. Nepal is predominately a rural country. Urbanization is less than ten percent that has
been reflected in our sample. The urban samples in NDHS are not sufficient to estimate the inequalities in child nutritional status.
SLIDE 10 On the other hand, economic inequalities in child malnutrition varied considerably across different regions of Nepal. For instance the poorest richest ratio and concentration index value
- f children underweight (moderate) were increased from P-Rt=2.76 & CI=-0.311 to P-Rt=5.85
& CI -0.354 during 2006-2011 in Hill regions in a similar direction but different volume of inequality was found in Tarai regions P-Rt=2.49 & CI =0.083 to P-Rt=4.05 & CI=0.109 during the same period, 2006-2011, while measuring the children underweight. Results of stunting and wasting also decipher the similar results over the period of 2006-2011 (Table 5). Although, the volume of economic inequalities in child malnutrition status varies by development regions, but the direction of inequality trends was same across the majority of
- regions. For instance, in the Eastern region P-Rt with 2.74 in 2006 was increased to 2.90 in
- 2011. Similarly, in case of economic inequalities in Stunting among far western and mid-
western region, both P-Rt (1.84 in Far western, 1.6 in mid-western) and CI (-0.343 in Far western & -0.3185 in mid-western) in 2011 have increased in comparison with P-Rt (1.28 in Far western, 1.15 in mid-western) and CI (-0.323 in Far western & -0.259 in mid-western) in 2006. During the same period (2006-2011), in a majority of the regions inequalities in Underweight
- increased. For example, in the eastern region, P-Rt in children underweight with 2.85 in 2006
was increased to 8.52 in 2011. Similarly, in case of economic inequalities in far-western and mid-western region, both P-R (1.50 in Far western, 1.1.98 in mid-western) and CI (-0.353 in Far western & -0.327 in mid-western) in 2011 have increased in comparison with P-Rt (1.30 in Far western, 1.23 in mid-western) and CI (-0.257 in Far western & -0.329 in mid-western) in 2006. Overall, in a majority of the selected indicators by both the inequality measures the results reveals that the economic inequalities in nutritional status over the period have increased during 2006 to 2011, irrespective of the religion and place of residence in Nepal. Discussion and conclusion During the last one decade, Nepal has undergone a major political transition. Abolition of monarchy, the establishment of the Federal Democratic Republic, and the election of Constituent Assembly in 2008 (and re-election in 2014) are the landmarks in the political history of Nepal. It is making significant efforts to move out of an extended political transition and is aiming to become a developed country by 2022 (World Bank 2014; UN Nepal, 2014). Furthermore, the population as a whole has experienced the significant improvements in key economic, health and population outcomes over the years and these outcomes have been monitored and the country is getting closer to meet some of the MDGs.
SLIDE 11 But there are still 2.6 percent of children under five years of age had severe acute malnutrition, which account for approx 60 percent of child deaths in Nepal (UNICEF 2011). Poverty and widespread lack of opportunity in rural Nepal are believed to have served as both the spark and fuel for the Maoist insurgency against the growing inequality among the population (Central Bureau of Statistics 2006). Economic growth and foreign aid have mitigated to some extent the adverse impacts that are associated with political violence and instability, and likely the drivers of recent improvements in national economic and health indicators, including the nutritional status of children. However, such improvements at the national level may mask the increasing inequality in health and population outcome. This leads to miss-judge the actual condition of economic and health parameters prevailing in the country (UNICEF 2011). The large number of studies corroborates the evidence by analysing the data on trends in health inequalities, which have tended to be rising in both the developing and developed worlds; Nepal is no exception of this phenomenon. This study takes a closer look at economic distribution of selected child nutrition indicators just after the political unrest of 2006. This will provide an empirical basis for the advocacy of typically pro-poor programmatic and policy
- intervention. The findings clearly suggest that economic inequalities in child nutritional
indicators (stunting, wasting and underweight) were more in 2011 than 2006 from both measures (poor-rich ratio and concentration index) used in this study. However, the average in child nutritional indicators continued to improve. Thus, the findings suggest the inequalities in child nutritional status in Nepal is swimming against the progress in averages of child nutritional status. Our findings are in tune with earlier studies in global or developing countries in context that examined the relationship between “averages of health status and health inequalities” (Contoyannis & Forster, 1999b; Victoria et al., 2000;Wagstaff, 2002; Moser et al., 2005; Goli & Arokiasamy, 2014). However, presence and growing of inequality cannot be seen in nature historically except in human, so an inference may be drawn that inequality is man-made and man-maintained. Central issue such as unequal access to food and health care, basic services, employment opportunities and the perceived inability of poor, women and marginalized groups are still remaining unaddressed in Nepal. Thus, this study not only lighten the most important aspect of distributive health or health inequalities, but also assist to policy makers that not to focus only on averages rather than equity with efficiency to register the more holistic approach towards improvements in health. In order to tackle the economic inequalities in child nutritional indicators, Nepal need
SLIDE 12 to adopt the inclusive approach in its social, economic and public health policies. The deprived socioeconomic groups needs more support than their counterparts. References Adam Wagstaff. (2002) Inequalities in Health in Developing Countries: Swimming Against the Tide? World Bank 2002. Alleyne, G. A. O, et. al. (2000). Equality, equity: why bother?. Bulletin of the World Health Organization, 78 (1): 76 –77. Archeson, D. (1998) Independent Inquiry into inequalities in health. London: the stationery
Arnold N. et. al. (2004) Indicators of Nutrition for Women and Children Current Status and
- Recommendations. EPW, Vol. 39, Issue No.07, pp: 664-670.
Contoyannis, P., Forster, P., (1999b) “The distribution of health: a theoretical framework. Journal of Health Economics 18 (5), 605–622. Dipty N. et. al. (2013) Inequalities in utilization of maternal health care services in Nepal. Ethnicity and Inequalities in Health and Social Care 2013; Vol. 6 Iss: 1, pp.3–15. Drever F, et. al. (1997) Health inequalities: decennial supplement. London, The Stationary Office (DS Series No.15). Goli, S. et. al. (2013) Pathways of economic inequalities in maternal and child health in urban India, A decomposition analysis. PloS one, 8.3 (2013): e58573. Goli, S. et. al. (2014) Trends in health and health inequalities among major states of India: assessing progress through convergence models. Health Economics, Policy and Law: Volume 9 / Issue 02 / April 2014, pp 143 – 168. Government of Nepal. 2012. Central Bureau of Statistics, National Planning Commission
- Secretariat. Available at http//: www. Central Bureau of Statistics.gov.np.
Gwatkin, D.R. (2000), “Health inequalities and the health of the poor: what do we know? What can we do?” Bulletin of the World Health Organization, Vol. 78 No. 1, pp. 3-17. Gwatkin, et. al. (2000) Socioeconomic Differences in Health, Nutrition and Population. Health, Nutrition & Population Discussion Paper, World Bank, Washington, DC. Hicks, John (1939). "The Foundations of Welfare Economics". Economic Journal (The Economic Journal, Vol. 49, No. 196) 49 (196): 696–712. doi:10.2307/2225023. JSTOR 2225023. Hosseinpoor, et. al. (2006) Decomposing socioeconomic inequality in infant mortality in Iran. International Journal of Epidemiology, 35: 1211–9. Joshi, P.C. 2012. Malnutrition in Children: A Serious Public Health Issue in Nepal. Health Prospect; 11:61-62. Kakwani, et. al. (1997) Socioeconomic inequalities in health: Measurement, complication and statistical inference. Journal of Econometrics, (forthcoming). Kakwani, N.C., Wagstaff, A. and Van Doorslaer, E. (1997), “Socioeconomic inequalities in health: measurement, computation and statistical inference”, Journal of Econometrics, Vol. 77, pp. 87-104.
SLIDE 13 Kaldor, Nicholas (1939). "Welfare Propositions in Economics and Interpersonal Comparisons
- f Utility". Economic Journal (The Economic Journal, Vol. 49, No. 195) 49 (195):
549–552. doi:10.2307/2224835. JSTOR 2224835. Kawachi, I., Subramanian, S. and Filho, N.A. (2002), “A glossary for health inequality”, Journal of Epidemiology and Community Health, Vol. 56, pp. 647-52, doi10.1136/jech.56.9.647. Mackenbach and Kunst (1997) Measuring the magnitude of socio-economic inequalities in health: an overview of available measures illustrated with two examples from
- Europe. Social science & medicine, 44.6 (1997): 757-771.
Martorell R, Leslie J, Moock P. R. 1984. Characteristics and determinants of child nutritional status in Nepal. The American Journal of Clinical Nutrition 39: 74-86. Moser, et. al., (2005) How does progress towards the child mortality millennium development goal affect inequalities between the poorest and least poor? Analysis of DHS Data. BMJ 331.7526 (2005): 1180-1182. Niraula SR, Barnawal SP, Poudel S, Mishra S, Dahal S, Das S, Pradhan S, Ghimire S, Khanal S, Sharma S, Rajput S, Bhattarai S, Jha N. 2013. Prevalence and associated risk factors with malnutrition among under-five Nepalese children of Borbote village, Ilam. Health Renaissance; 11 (2); 111-118. Panayotov, Jordan. (2008) Evidence in Public Health and Health Impact Assessment. Science and Medicine, 33, 545-557. Sharma, Shiva. (2009) Poverty Growth and Economic Inclusion in Nepal. Conference Paper. Expert Group Meeting on Practical Strategies to Promote Social Integration: Lessons learned from existing policies and practices. Retrieved March, Vol. 20. Subramanyam, M.A. and Subramanian, S.V. (2011), “Research on social inequalities in health in India”, Indian Journal of Medical Research, Vol. 133 No. 5, pp. 461-3. Tarozzi, A. et. al. (2007). Child nutrition in India in the nineties. Economic Development and Cultural Change, 55(3), 441–86. Tonoyan, T. and Lusine, M. (2012), “Health inequalities in Armenia – analysis of survey results”, International Journal for Equity in Health, Vol. 11, p. 32. UNICEF, ROSA, 2011. Annual Report 2011 for Nepal. UNITED NATIONS 2007. Annual Report of Nepal, 2007. Vallin, J. et. al. (2005) Convergences and divergences: an analytical framework of national and sub-national trends in life expectancy. Genus (2005): 83-124. Wagstaff, A. and van Doorslaer, (1991) On the measurement of inequalities in health. Social Wagstaff, A. et. al. (2003) On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam. Journal of econometrics, 112: 1207-223. Wagstaff, et. al. (2000) Socioeconomic inequalities in child mortality: comparisons across nine developing countries. Bulletin of the WHO, 78 (1), 19–29. Wagstaff, et. al. (2004) Overall versus socioeconomic health inequality: a measurement framework and two empirical illustrations. Health economics, 13.3 (2004): 297- 301. Walker, et. al., (2007) People, Places, and Processes: Reducing health inequalities through balanced health approach. Victorian Health Promotion Foundation, 15-31.
SLIDE 14
World Development Report (2006). Equity and Development, pp5-15. World Health Organization (2008) Inequities Are Killing People on Grand Scale Geneva. Report of WHO.
SLIDE 15 Table 1- Percent distribution of children, who were moderately Wasted, Stunted, and Underweight by economic status of their households in Nepal, 2006-2011 Economic Status Moderate ((<-2SD) Wasting Stunting Underweight 2006 2011 2006- 2011 2006 2011 2006- 2011 2006 2011 2006- 2011 % ±CI % ±CI % ±CI % ±CI % ±CI % ±CI Poorest 11.66 ±3.72 12.34 ±5.67 0.29 61.30 ±5.87 56.18 ±8.66 5.12 46.52 ±5.88 40.38 ±8.5 6.14 Poorer 15.17 ±5.18 11.51 ±6.42 4.28 54.48 ±7.24 45.27 ±10.8 9.21 45.44 ±7.22 31.10 ±10.11 14.34 Middle 15.13 ±5.93 13.00 ±7.88 3.1 50.73 ±7.74 34.10 ±10.55 16.63 41.99 ±7.67 28.44 ±10.25 13.55 Richer 13.20 ±5.12 8.13 ±6.44 5.73 40.05 ±7.76 29.96 ±11.61 10.09 31.45 ±6.97 21.91 ±10.37 9.54 Richest 6.86 ±4.04 7.55 ±7.23 0.91 30.28 ±8.4 24.95 ±11.39 5.33 18.64 ±6.87 9.92 ±7.64 8.72 Poorest/Richest Ratio 1.70 1.64 2.02 2.25 2.50 4.07 Poorer/Richer Ratio 1.15 1.42 1.36 1.51 1.45 1.46 Chi-square Value and Significance level 36.10*** 10.74*** 224.759*** 125.3*** 204.710*** 204*** CI a Value and Standard Error
- 0.029(0.005)
- 0.082(0.008)
- 0.121(0.005)
- 0.157(0.008)
- 0.125(0.005)
- 0.184(0.008)
Note: - Significance level- p<0.05**, p<0.01***, CIa (Concentration Index and Standard Error), # CI (Confidence Interval) Table 2- Percent distribution of children, who were severly Wasted, Stunted, and Underweight by economic status of their households in Nepal, 2006-2011 Economic Status Severe ((<-3SD) Wasting Stunting Underweight 2006 2011 2006- 2011 2006 2011 2006- 2011 2006 2011 2006- 2011 % ±CI % ±CI % ±CI % ±CI % ±CI % ±CI Poorest 3.07 ±1.96 2.39 ±2.24 0.68 29.11 ±5.26 25.56 ±6.42 3.55 14.29 ±4.05 11.80 ±4.74 2.49 Poorer 3.09 ±2.69 3.14 ±3.13
21.60 ±5.62 20.29 ±7.22 1.31 12.63 ±4.66 10.04 ±5.4 2.59 Middle 2.64 ±2.25 2.48 ±2.91 016 20.28 ±6.07 11.96 ±6.05 8.32 12.63 ±5.37 6.77 ±4.69 5.86 Richer 2.64 ±2.37 2.53 ±3.27 0.11 13.77 ±5.21 7.86 ±5.61 5.91 7.91 ±4.03 4.50 ±4.31 3.41 Richest 1.24 ±1.72 2.31 ±3.17
9.73 ±5.33 5.20 ±4.69 4.53 2.39 ±2.04 2.02 ±2.97 0.37 Poorest/Richest Ratio 2.48 1.03 2.99 4.91 5.98 5.83 Poorer/Richer Ratio 1.17 1.24 1.57 2.580 1.60 2.24 Chi-square Value and Significance level 7.61 1.30 139.389*** 83.15*** 86.844*** 23.8*** CI a Value and Standard Error
- 0.115(0.005)
- 0.002(0.008)
- 0.188(0.005)
- 0.260(0.008)
- 0.178(0.005)
- 0.238(0.008)
Note: - Significance level- p<0.05**, p<0.01***, CIa (Concentration Index and Standard Error), # CI (Confidence Interval)
SLIDE 16 Table 4- Poorest-richest ratio, poorer-richer ratio and concentration index depicting trends in economic inequalities with respect to Stunting, Wasting, Underweight (<-2S.D for moderate and <-3S.D for severe) by place of residence, Nepal, 2006-2011. Place of Residence Moderate (<-2SD) Severe (<-3SD) Stunting Wasting Underweight Stunting Wasting Underweight 2006 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 2011 Rural Poorest/Richest Ratio
1.92 2.12 1.48 1.49 2.18 4.24 3.69 3.58 1.63 1.33 6.54 4.76
Poorer/Richer Ratio
1.36 1.48 1.15 1.46 1.43 1.43 1.50 1.99 1.28 0.84 1.6 1.55
CI a Value and Standard Error
(0.006)
(0.009)
(0.006)
(0.009)
(0.006)
(0.009)
(0.006)
(0.009)
(0.006)
(0.009)
(0.006)
(0.009)
Urban Poorest/Richest Ratio
........ ...... ....... ....... ....... ........ ........ 4.26 ........ 0.76 ........ 10.15
Poorer/Richer Ratio
1.41 ...... 0.69 ....... 1.38 ....... 2.07 1.76 0.47 2.37 1.28 2.11
CI a Value and Standard Error
0.273 (0.011) 0.323 (0.018) 0.352 (0.011) 0.323 (0.018) 0.225 (0.011) 0.248 (0.018) 0.203 (0.011) 0.218 (0.018) 0.304 (0.011) 0.513 (0.018) 0.203 (0.011) 0.059 (0.018)
Note: - CI a (Concentration index and standard error in parenthesis) Table 5- Poorest-richest ratio, poorer-richer ratio and concentration index depicting trends in economic inequalities with respect to Stunting, Wasting, Underweight (<-2S.D for moderate and <-3S.D for severe) across ecological regions, Nepal, 2006-2011. Ecological Zone Moderate (<-2SD) Severe (<-3SD) Stunting Wasting Underweight Stunting Wasting Underweight
2006 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 2011
Mountain Poorest/Richest Ratio
....... ...... ........ ........ ...... ........ ....... ........ ...... ........ ...... ........
Poorer/Richer Ratio
1.22 ....... 4 ........ 1.37 ....... 1.36 ....... ........ 1.75 .........
CI a Value and Standard Error
(0.014)
(0.018)
(0.014)
(0.018)
(0.014)
(0.018)
(0.014)
(0.018)
(0.014)
(0.018)
(0.014)
(0.018)
SLIDE 17 Note: - CI a (Concentration index and standard error in parenthesis) Table 6- Poorest-richest ratio, poorer-richer ratio and concentration index depicting trends in economic inequalities with respect to Stunting, Wasting, Underweight (<-2S.D for moderate and <-3S.D for severe) across development regions, Nepal, 2006-2011. Developmenta l Region Moderate (<-2SD) Severe (<-3SD) Stunting Wasting Underweight Stunting Wasting Underweight 2006 2011 2006 2011 2006 2011 2006 2011 2006 2011 2006 2011 Eastern Poorest/Richest Ratio
2.74 2.90 4.42 1.41 2.85 8.52 3.98 6.04 2 1.38
Poor/Rich Ratio
1.36 1.39 0.87 1.9 1.38 1.17 3.01 1.48 0.28 1.38 2.19 1.16
CI a Value and Standard Error
(0.011)
(0.017)
(0.011) 0.032 (0.017)
(0.011)
(0.017)
(0.011)
(0.017)
(0.011) 0.349 (0.017)
(0.011)
(0.017)
Central Poorest/Richest Ratio
2.06 1.93 2.92 2.3 3.54 3.44 3.50 4.2 2.75 1.89 8.2 3.42
Poor/Rich Ratio
1.48 1.81 1.53 1 1.78 2.2 1.91 2.18 0.96 0.53 2.24 1.89
Hill Poorest/Richest Ratio
1.96 1.99 2.40 2.12 2.76 5.85 2.43 6.1 2.63 1.25 11 4.54
Poorer/Richer Ratio
1.44 1.33 0.97 1.39 1.71 1.06 1.49 1.35 0.39 2.75 0.93 1.79
CI a Value and Standard Error
(0.008)
(0.012)
(0.008)
(0.012)
(0.008)
(0.012)
(0.008)
(0.012)
(0.008)
(0.012)
(0.008)
(0.012)
Tarai Poorest/Richest Ratio
1.96 2.67 1.78 1.14 2.49 4.05 4.05 3.68 3.33 0.72 4.55 3.95
Poorer/Richer Ratio
1.32 1.56 1.17 1.46 1.36 1.69 1.59 2.5 1.28 0.62 1.89 1.61
CI a Value and Standard Error
0.106 (0.008) 0.132 (0.013) 0.125 (0.008) 0.110 (0.013) 0.083 (0.008) 0.109 (0.013) 0.030 (0.008) 0.066 (0.013) 0.042 (0.008) 0.269 (0.013) 0.037 (0.008) 0.096 (0.013)
SLIDE 18 CI a Value and Standard Error
(0.011) 0.007 (0.018) 0.021 (0.011) 0.037 (0.018)
(0.011)
(0.018)
(0.011)
(0.018) 0.044 (0.011) 0.054 (0.018)
(0.011)
(0.018)
Western Poorest/Richest Ratio
1.86 1.86 0.84 1.33 1.51 2.71 2.31 3.43 1.73 0.95 4.05 1.88
Poor/Rich Ratio
1.25 1.36 0.79 0.93 1.21 0.64 1.15 1.57 0.14 0.20 0.72 0.84
CI a Value and Standard Error
0.111 (0.013) 0.126 (0.021) 0.238 (0.013) 0.197 (0.021) 0.134 (0.013) 0.167 (0.021) 0.088 (0.013) 0.017 (0.021) 0.284 (0.013) 0.350 (0.021) 0.104 (0.013) 0.182 (0.021)
Mid-Western Poorest/Richest Ratio
2.27 ........ 0.55 ...... 3.10 2.6 3.18 3.5
Poor/Rich Ratio
1.15 1.6 1.28 1.82 1.30 1.5 1.07 6.6 1.21
CI a Value and Standard Error
(0.013)
(0.017)
(0.013)
(0.017)
(0.013)
(0.017)
(0.013)
(0.017)
(0.013)
(0.017)
(0.013)
(0.017)
Far-Western Poorest/Richest Ratio
1.61 ...... 0.95 1.69 1.95 4.24 1.19 2.42
Poor/Rich Ratio
1.28 1.84 1.02 4.76 1.23 1.98 0.90 1.25 1.59 3.15
CI a Value and Standard Error
(0.013)
(0.019)
(0.013)
(0.019)
(0.013)
(0.019)
(0.013)
(0.019)
(0.013)
(0.019)
(0.013)
(0.019)
Note: - CI a (Concentration index and standard error in parenthesis)
Figure 1: Concentration Curves DHS-Nepal 2006-2011 (Stunting, Wasting, Underweight)
SLIDE 19
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators Cummulative Proportaion of Children based on wealth index
Moderate (<-2SD)
Moderate Wasting (2006) Moderate Underweight (2006) Line of Equity Moderate Stunting (2011) Moderate Underweight (2011) Moderate Wasting (2011) Moderate Stunting (2006)
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators Cummulative Proportaion of Children based on wealth index
Severe (<-3SD)
Severe Stunting (2006) Severe Underweight (2006) Severe wasting (2006) Severe Stunting (2011) Severe Underweight (2011) Severe Wasting (2011) Line of Equity
SLIDE 20
Appendix: 1
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Rural Children
Moderate (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate wasting (2011) Moderate Underweight (2011) Linear (Line of Equity)
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Urban Children
Moderate (<-2SD)
Moderate Stunting (2006) Modearte Underweight (2006) Moderate Wasting (2006) Modearte Stunting (2011) Moderate Wasting Moderate Underweight (2006) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Commulative Proportion of Rural Children
Severe (<-3SD)
Severe Stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe wasting (2011) Severe Underweight (2011) Linear (Line of Equity)
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Urban Children
Severe (<-3SD)
Severe Stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Linear (Line of Equity)
SLIDE 21
Appendix: 2
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Mountain Region Children
Moderate (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Mountain Region Children
severe(<-3SD)
Severe stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Hill Region Children
Moderate (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Hill Region Children
Severe (<-3SD)
Severe Stunting (2006) Severe wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
SLIDE 22
Appendix:3
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Tarai Children
Moderate (<-2SD)
Moderate Stunting (2006) Moderate wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate Wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Eastern Region Children
Severe (<-3SD)
Severe Stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummalative Proportion of Eastern Region Children
Moderate (<-2SD)
Moderate Stunting (2006) Modearte Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate Wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selcted Nutrional Indicator
Cummulative Proportion of Eastern Region Children
Severe (<-3SD)
Severe Stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
SLIDE 23
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proportion of Central Region
Moderate (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Modearte Underweight (2006) Moderate Stunting (2011) Moderate Wasting (2011)
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proportion of Central Region Children
Severe (<-3SD)
Severe Stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proporion of Western Reigin Children
Modeare (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate Wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proportion of Western Reigion Children
Severe (<-3SD)
Severe Stunting (2006) Severe wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
SLIDE 24
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proportion of Mid-Western Region Child
Moderate (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate Wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proportion of Mid-Western Children
Severe (<-3SD)
Severe Stunting (2006) Severe Wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe wasting (2011) Severe Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummalative Proportion of Far-Western Children
Modearte (<-2SD)
Moderate Stunting (2006) Moderate Wasting (2006) Moderate Underweight (2006) Moderate Stunting (2011) Moderate Wasting (2011) Moderate Underweight (2011) Line of Equity
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Selected Nutrional Indicators
Cummulative Proportion of Far-Western Children
Severe (<-3SD)
Severe Stunting (2006) Severe wasting (2006) Severe Underweight (2006) Severe Stunting (2011) Severe Wasting (2011) Severe Underweight (2011) Line of Equity
