Feeding the African Child Socioeconomic Variables and Child

Feeding the African Child: Socioeconomic Variables and Child Nutritional Status in Nigeria Emmanuel Nwosu (Ph. D) Anthony Orji (Ph. D) Department of Economics, University of Nigeria Nsukka AEC Conference 5 th-7 th Dec, 2016 Abuja, Nigeria.

Motivations q q This study analyses variations in child nutritional status with social economic status and other factors in Nigeria’s geopolitical zones in a multivariate context. The maternal and child health situation is one of the indicators of a society’s level of development, as well as an indicator of the performance of the health care delivery system.

Motivations q q According to Nigeria Health Review (2006) Report, Nigeria is one of the countries lagging behind in most of the Millennium Development Goals (MDGs), which 191 countries, including Nigeria, signed in 2001. In 2000, the World Health Organization (WHO) ranked Nigeria’s overall health system performance 187 th among its 191 member states.

Motivations q q The Nigerian health indicators and variations across the six geopolitical zones have deteriorated significantly over the past years to the extent that Nigeria has continued to rank high in poor population health. The country is remarkably diverse in social and economic development especially across the six geopolitical zones. The coverage of the national health system is limited and health education and enlightenment is weak, partly due to high level

Motivations q q Available statistics also indicate that the rates of malnutrition are high with 43% of children under-five being stunted (chronically malnourished) and 27% being underweight. At birth, 17% of children are underweight (WHO, 2006). The patterns of health status in Nigeria mirror many other Sub-Saharan African nations but are worse than would be expected given Nigeria’s GDP per capita.

Motivations q q For example after 2003 Demographic and Health Survey (DHS), infant mortality rate (IMR) was estimated at 115 out of 1000, under-5 mortality rate was estimated at 205 out of 1000, and the maternal mortality ratio (MMR) was estimated at 948 out of 100, 000 (NHR, 2006; Gustafsson-Wright, and Gaag, 2008). Despite astounding numbers that show poor child health/nutritional status in Nigeria, very little is known about its variations with socioeconomic and other factors especially in Nigeria’s geopolitical

Motivations q Poor Child Health and its variation in Nigeria is huge. Yet, very little is known empirically about the socioeconomic determinants. Previous health-related studies in Nigeria known to us were focused on issues such as: inequality in the provision of healthcare (Ibiwoye and Adeleke, 2008) the distributive effect of healthcare financing (Ichoku and Fonta, 2006; Ichoku and Fonta, 2009) the demand for healthcare (Onwujekwe and Uzochukwu, 2005; Amaghionyeodiwe, 2008) studies did not adequately address the links between socioeconomic status and health especially at individual level. Studies relied on individually collected data on a small portion of a State and some on macroeconomic data. DHS data more reliable and likely to produce reliable results but have been ignored

Research Questions q This study therefore makes contributions to literature on socioeconomic health inequality in Nigeria by addressing the following research questions: 1. 2. What are the socioeconomic determinants of child health in Nigeria? Does zonal disparity in socioeconomic endowment account for much of the variation in child health across the zones?

Policy Relevance q This study has a lot of potential implications for policy in Nigeria in the following areas: Estimating the causal relationship between health outcome and socioeconomic status would be informative in predicting how inequality will change if policymakers are to change certain SES variables. Understanding if health inequality across geopolitical regions is due to differences in their SES is important in designing effective policy interventions that address specific health needs of those regions. Understanding if certain SES indicators explain health outcome inequality more than others is important in knowing priority areas policy should be designed to target. The outcome of this study will shape policies that aim at realizing the SDGs goals.

Model Specification q Let the health outcome H be dichotomous. That is, a child may have poor nutritional status or not. Hence we specify a multivariate probit model of child nutritional status. In the probit model, the binary dependent variable yi is replaced by a latent continuous dependent variable such that then yi=1 and then yi=0.

Model Specification q q In order to interpret the regressor’s impact on the probability of an event occurring, we need to compute marginal effects if the regressor is a continuous variable or impact effects if the regressor is a binary variable. Instead of using the matrix expression of the index, we use the following simple expression: where the index contains a constant term, a continuous regressor and a dummy variable.

q. The Data q q Nigeria Demographic and Health Surveys (NDHS) for 2003 and 2008 provided the secondary data source used in the study. The data were collected to provide estimates of health, social and population indicators for Nigeria. The data covered rural and urban areas, and the six geo-political zones as well as the whole country.

Distribution of Prevalence of Malnutrition (Stunting) Using Negative of Height-for-Age Z-score for Children<10 Years, by Groups and Year Groups Zones North Central Year and Heath Indicator Mean SD -1. 238 2. 3158 North East -1. 739 North West -2. 4814 South East -1. 0741 South West -0. 8694 South -1. 0045 Weath Quintile Poorest -2. 081 Poorer -2. 021 Middle -1. 86 Richer -1. 304 Richest -0. 839 Education level of Mother No -2. 175 Education Primary -1. 507 Secondary -0. 887 Higher -0. 61 Locality/Sector Urban -1. 293 2003 % below 2 SD 2008 % below 2 SD % below Mean -3 SD SD % below 3 SD 34. 33 15. 61 -2. 2156 3. 7319 48. 58 32. 7 2. 3937 3. 2529 2. 771 2. 7342 2. 7447 47. 01 61. 16 26. 98 26. 76 31. 03 26. 77 43. 32 16. 55 11. 34 12. 9 -2. 0499 -2. 4019 -1. 0518 -1. 8085 -1. 3051 3. 2829 3. 8233 3. 6867 3. 8572 3. 1289 50. 76 56. 83 29. 02 38. 18 35. 17 35. 07 40. 7 16. 63 23. 83 18. 74 2. 777 2. 67 2. 563 3. 169 2. 759 53. 7 51. 6 47. 9 35. 2 26 34. 5 33 28. 9 19. 1 11 -2. 372 -2. 265 -1. 921 -1. 638 -1. 208 3. 639 3. 599 3. 471 3. 581 3. 758 55. 5 53. 2 46. 4 38. 7 30. 1 40. 5 36 29. 6 23. 5 18. 2 2. 596 54. 5 35. 8 -2. 325 3. 747 54. 6 38. 6 2. 699 3. 242 2. 329 41. 1 28. 3 14. 4 22. 1 12. 5 5. 3 -1. 896 -1. 489 -1. 969 3. 269 3. 605 3. 627 45. 1 36 46. 7 28. 3 21. 8 31. 2 2. 826 35. 3 18. 8 -1. 532 3. 64 37. 9 23. 5

q. Distribution of Prevalence of Malnutrition q q The results show that 26. 8 percent and 43. 3 percent of children in the North East and North West region were respectively exposed extensively to malnutrition; while 47 percent and 61 percent of children under 10 years were moderately malnourished in the same regions respectively. On the other hand, 15. 6 percent of children under 10 years in the North Central were severely malnourished while 34. 3 percent of children under the same category in the same zone were moderately

q. Distribution of Prevalence of Malnutrition q q Essentially, in both 2003 and 2008, there were high cases of both moderate and severe malnutrition in all the zones but it was worst in the Northern regions than in the South. However, the results show that in the North and South the degree of malnutrition of children began to worsen in 2008.

q. Results of Correlates of Nutritional Status Mrginal Effects of Stunting by Geopolitical Zones– Table 2 Vitamin A occupation bednet_type safe water safe toilet electricity sex of child age in months agesq head-female age of head primary secondary higher rural asset index 2 time dummy Observations Pseudo R 2 chi 2 (1) Overall -0. 0486*** (0. 000) -0. 00396** (0. 027) -0. 0139 (0. 278) -0. 0111 (0. 265) 0. 00716 (0. 460) 0. 000257 (0. 982) -0. 0697*** (0. 000) 0. 0220*** (0. 000) -0. 0345*** (0. 000) -0. 0399*** (0. 010) -0. 0011*** (0. 001) -0. 0816*** (0. 000) -0. 139*** (0. 000) -0. 221*** (0. 000) 0. 0415*** (0. 000) -0. 0147** (0. 017) 0. 00541* (0. 097) 16571 0. 061 991. 7 (2) NC -0. 0664*** (0. 003) -0. 0140*** (0. 002) -0. 0311 (0. 308) -0. 0416 (0. 117) -0. 0603** (0. 011) 0. 0298 (0. 343) -0. 0981*** (0. 000) 0. 0187*** (0. 000) -0. 0268*** (0. 000) -0. 0333 (0. 321) -0. 00119 (0. 130) -0. 00285 (0. 904) -0. 0625** (0. 019) -0. 135*** (0. 003) -0. 0143 (0. 612) -0. 0338** (0. 039) 0. 0331*** (0. 000) 3168 0. 060 230. 7 (3) NE -0. 0603** (0. 025) 0. 00173 (0. 629) -0. 0586** (0. 028) 0. 0368* (0. 098) 0. 0485** (0. 023) -0. 00253 (0. 924) -0. 0399** (0. 030) 0. 0339*** (0. 000) -0. 0510*** (0. 000) -0. 0489 (0. 253) 0. 000337 (0. 676) -0. 0356 (0. 147) -0. 0609* (0. 060) -0. 0905 (0. 183) 0. 0657*** (0. 010) -0. 0232* (0. 093) 0. 0200*** (0. 003) 3725 0. 086 346. 4 (4) NW 0. 00792 (0. 801) -0. 00298 (0. 315) 0. 00236 (0. 918) -0. 0287 (0. 119) -0. 0121 (0. 475) 0. 0120 (0. 569) -0. 0747*** (0. 000) 0. 0293*** (0. 000) -0. 0455*** (0. 000) -0. 101*** (0. 006) -0. 0022*** (0. 001) -0. 0388 (0. 128) -0. 102*** (0. 004) -0. 220*** (0. 001) 0. 0792*** (0. 002) -0. 00183 (0. 826) -0. 0187*** (0. 003) 4379 0. 068 343. 8 (5) SE -0. 0271 (0. 364) 0. 00668 (0. 263) -0. 0799** (0. 028) -0. 00921 (0. 744) -0. 00691 (0. 825) -0. 00188 (0. 956) -0. 0266 (0. 328) 0. 0137*** (0. 000) -0. 0250*** (0. 000) 0. 0582* (0. 095) -0. 000904 (0. 363) -0. 0993** (0. 013) -0. 103** (0. 024) -0. 135*** (0. 006) 0. 0255 (0. 392) -0. 0378* (0. 052) -0. 00434 (0. 708) 1316 0. 041 54. 19 (6) SW 0. 0105 (0. 691) 0. 000716 (0. 903) 0. 0258 (0. 462) -0. 0320 (0. 276) 0. 0120 (0. 708) 0. 00249 (0. 932) -0. 0652*** (0. 009) 0. 0148*** (0. 000) -0. 0275*** (0. 000) -0. 00834 (0. 796) 0. 00197* (0. 056) -0. 0319 (0. 513) -0. 101** (0. 039) -0. 198*** (0. 000) -0. 000664 (0. 984) 0. 00374 (0. 802) 0. 0271** (0. 011) 1827 0. 033 61. 98 (7) SS -0. 0239 (0. 300) -0. 00171 (0. 739) 0. 0201 (0. 631) 0. 0200 (0. 411) -0. 0214 (0. 428) -0. 0110 (0. 745) -0. 0834*** (0. 000) 0. 00888*** (0. 001) -0. 0139*** (0. 004) 0. 00225 (0. 948) -0. 00160* (0. 084) -0. 0163 (0. 640) -0. 0530 (0. 139) -0. 121*** (0. 005) 0. 0319 (0. 262) -0. 0196 (0. 228) 0. 00626 (0. 433) 2156 0. 028 61. 02

q. Results of Correlates of Nutritional Status Mrginal Effects of Underweight by Geopolitical Zones--Table 3 Vitamin A occupation bednet_type safe water safe toilet electricity sex of child age months agesq head is female age of head primary secondary higher rural asset index 2 time dummy Observations Pseudo R 2 chi 2 aic bic ll (1) Overall -0. 0443*** (0. 000) -0. 00192 (0. 223) -0. 00242 (0. 825) 0. 0103 (0. 246) 0. 0198** (0. 019) -0. 0323*** (0. 002) -0. 0524*** (0. 000) 0. 0143*** (0. 000) -0. 0234*** (0. 000) -0. 0391*** (0. 005) -0. 0015*** (0. 000) -0. 128*** (0. 000) -0. 177*** (0. 000) -0. 200*** (0. 000) 0. 0304*** (0. 004) -0. 0114* (0. 061) 0. 00128 (0. 654) 16571 0. 082 1137. 3 17984. 5 18123. 3 -8974. 2 (2) NC 0. 0165 (0. 377) -0. 00606 (0. 117) -0. 0489** (0. 036) 0. 0314 (0. 175) -0. 0408** (0. 026) -0. 0317 (0. 173) -0. 0399** (0. 010) 0. 00481*** (0. 007) -0. 00703** (0. 034) -0. 0359 (0. 210) -0. 0017*** (0. 008) -0. 110*** (0. 000) -0. 144*** (0. 000) -0. 161*** (0. 000) 0. 00336 (0. 887) -0. 0124 (0. 280) 0. 0112* (0. 055) 3168 0. 059 160. 6 3247. 0 3356. 0 -1605. 5 (3) NE -0. 0394 (0. 131) -0. 00263 (0. 443) -0. 00238 (0. 927) -0. 0293 (0. 164) 0. 0157 (0. 446) 0. 00378 (0. 883) -0. 0819*** (0. 000) 0. 0327*** (0. 000) -0. 0508*** (0. 000) -0. 0424 (0. 326) -0. 0022*** (0. 006) -0. 0774*** (0. 001) -0. 116*** (0. 000) -0. 172*** (0. 001) -0. 000199 (0. 993) -0. 0382** (0. 012) 0. 0239*** (0. 000) 3725 0. 096 374. 1 4477. 7 4589. 7 -2220. 9 (4) NW -0. 00434 (0. 891) 0. 00573** (0. 050) 0. 0250 (0. 272) 0. 0378** (0. 037) -0. 00772 (0. 644) -0. 0618*** (0. 002) -0. 0801*** (0. 000) 0. 0230*** (0. 000) -0. 0383*** (0. 000) 0. 0402 (0. 275) -0. 00090 (0. 168) -0. 0583** (0. 017) -0. 0747** (0. 025) -0. 229*** (0. 000) 0. 0785*** (0. 002) -0. 00226 (0. 805) -0. 00515 (0. 396) 4379 0. 050 263. 5 5698. 9 5813. 8 -2831. 4 (5) SE -0. 0462** (0. 022) -0. 00216 (0. 614) -0. 0351 (0. 146) 0. 0381** (0. 050) -0. 0177 (0. 419) -0. 0586** (0. 029) -0. 0120 (0. 515) 0. 00019 (0. 929) -0. 00268 (0. 512) -0. 0041 (0. 863) -0. 0013* (0. 087) -0. 0165 (0. 554) -0. 0279 (0. 357) -0. 0265 (0. 508) -0. 00161 (0. 940) -0. 00453 (0. 806) 0. 00551 (0. 388) 1316 0. 039 34. 81 993. 6 1086. 9 -478. 8 (6) SW 0. 0239 (0. 228) -0. 00813* (0. 061) -0. 0298 (0. 192) -0. 0699*** (0. 001) -0. 0153 (0. 502) 0. 00352 (0. 868) -0. 0360** (0. 049) 0. 0036 (0. 106) -0. 00548 (0. 154) -0. 0126 (0. 584) 0. 00029 (0. 696) -0. 00896 (0. 784) -0. 0701** (0. 035) -0. 0822** (0. 012) 0. 0321 (0. 193) 0. 0143 (0. 178) -0. 0113* (0. 095) 1827 0. 045 53. 56 1538. 9 1638. 1 -751. 5 (7) SS -0. 0136 (0. 410) -0. 00250 (0. 497) 0. 00215 (0. 943) -0. 0141 (0. 425) 0. 0219 (0. 267) -0. 00772 (0. 766) -0. 0291* (0. 062) 0. 0038** (0. 032) -0. 00547* (0. 096) -0. 0183 (0. 434) -0. 00106 (0. 116) -0. 0278 (0. 221) -0. 0458* (0. 058) -0. 0842*** (0. 000) 0. 00815 (0. 698) -0. 0264** (0. 026) -0. 00868* (0. 088) 2156 0. 030 46. 41 1750. 2 1852. 4 -857. 1

q. Discussion of Results Tables 2 and 3 report the corresponding marginal effects for correlates of stunting and underweight respectively. q Overall the marginal effects of the correlates of stunting in table 4 show that having access to health infrastructure (for example, giving a child vitamin A at least two months after delivery) is significantly associated with lower probability that the child will be stunted. q

q. Discussion of Results q Specifically, giving a child vitamin A at least two months after delivery significantly reduces the likelihood of stunting by about 4. 86 percent. But looking at geopolitical zone specifics, giving a child vitamin A reduces the probability of stunting by 6. 64 percent in North Central and 6. 03 percent in the North East, while this is not significantly correlated with prevalence of stunting in the other geopolitical zones.

q. Discussion of Results q The results in table 2 also show that the use of sanitary toilet facilities lead to significant reduction in the prevalence of stunting by 6. 03 percent in the North Central while it increases it by 4. 85 percent the North East Zone. This is not significant in other zones.

q. Discussion of Results q As shown in table 2 and 3, the sex of child significantly correlated with lower probability that the child will be stunted or underweight. Specifically, being a female child is significantly associated with 6. 97 per cent and 5. 24 per cent lower probability of being stunted and underweight respectively. This finding is similar across all the geopolitical zones except in the South East (SE).

q. Discussion of Results q Furthermore, the result shows that the probability of prevalence of stunting and underweight increases with child’s age by 2. 2 per cent and 1. 4 per cent respectively across the Zones, while the age square indicates that after a certain age the overall probability of being stunted and underweight decreases by 3. 45 per cent and 2. 34 per cent respectively across the Zones.

q. Discussion of Results q Overall, children born to female-headed households are about 3. 99 per cent less likely to be stunted and 3. 91 per cent less likely to be born underweight. q This is consistent across almost all the geographical zone though only statistically significant in the North West (NW).

q. Discussion of Results q The results also show that the likelihood of malnutrition is significantly negatively associated with increasing age of the head of household. q This means that as the household head grows old, he or she acquires more experience on better approaches to health issues which may lead to improvement in child health.

q. Discussion of Results q Across the six geopolitical zones education of mother, both secondary and higher levels of education, is statistically negatively correlated with the probability of being stunted and underweight and the degree of correlation varies across geopolitical zones with higher negative association in the SW, SE and NW. q It also follows from theory that healthier children are more likely to be borne by mothers with higher levels of education since they understand the dynamics of health better than less educated ones and are also able to bring up their children with better knowledge of health issues (Grossman, 1972).

q. Discussion of Results q q The findings also show that living in rural area increases the likelihood of malnutrition but the effect is significant only in NE and NW. Overall, the results in tables 2 and 3 indicate that the higher the household income (proxied by wealth index), the lower the probability that a child born to the household will be malnourished. q Thus, increases in income are clearly important for reducing child malnutrition (Alderman et al, 2001).

q. Discussion of Results q Year dummy was added in the regression in order to ascertain if malnutrition has changed over time between 2003 and 2008. q Overall, the results indicate that child malnutrition significantly increased over time in the NC, NE and SW but declined significantly in the NW and SS.

Policy Recommendations Special intervention needed to improve the welfare of the disadvantaged groups most of them found in the North. Providing basic education for women and making it affordable Women education vital for effective utilisation of health information in health production function Women education could reduce health inequality across groups and also improve mean health.

Policy Recommendations Income-generating activities in both private and public sectors should be pursued by the government at all levels Supporting the private sector with soft loans Provision of basic infrastructure, e. g. , electricity Pursuance of inclusive growth to improve mean health and reduce disparity Provision of basic amenities that directly affect health (e. g. safe drinking water, good sewage, etc) and campaign for utilisation Gender disparity at early childhood should be reduced by giving special attention to the fragility of male child

Policy Recommendations Women should be encouraged to complete all the necessary immunization of the child at the early childhood to make him resistant to frequent outbreak of diseases.

Thank you for Listening q. Thank Listening you for

Health Inequality and Determinants

Decomposition of Concentration Index for Height-for. Age Z-scores of Children<10 Years, Nigeria, 2003 and 2008 2003 2008 Variable Elasticities Concindex Contrib %Contrib Child age Agesq Male Child Asset Index Vitamin A 0. 858 -. 3291 -. 0315 -. 0562 -. 0271. 0185 0. 373 -. 255 . 3857 -. 223 . 025. 043 . 01 -. 231 -. 1366 . 0013 -. 0002 . 0024 -0. 275 . 002 -. 001 . 012 -. 0305 . 6108 -. 0186 . 257 -. 0228 . 594 -. 0136 . 328 -. 0133 . 1783 -. 0024 . 0326 -. 0086 . 197 -. 0017 . 0413 male HH Head -. 1256 -. 0060 . 0008 -. 0104 . 0274 -. 023 -. 0006 . 0153 Age HHH Urban Residence Electricity Safe water toilet Education Zones Residual Total . 0460 -. 0227 -. 001 . 0144 -. 005 -. 013 . 0001 -0. 002 . 262 -. 094 -. 0247 . 3400 . 0189 -. 087 -. 0016 . 0395 -. 1833. 0053. 0029. 1999 . 2785. 2620. 1108. 0125 -. 0511. 0014. 0003. 0025. 0445 -. 0155 -. 0726 . 704 -. 019 -. 005 -. 035 -. 6133. 2135 . 0294 -. 0062 -. 0238. 0175 . 273. 227. 284. 005 . 0080 -. 0014 -. 0068. 0001 -. 0129 -. 0105 -. 0414 -. 1941. 0342. 1631 -. 002. 3113. 2536