Burden of micronutrient deficiencies by socio-economic strata in children aged 6 months to 5 years in the Philippines

Abstract

Background: Micronutrient deficiencies (MNDs) are a chronic lack of vitamins and minerals and constitute a huge public health problem. MNDs have severe health consequences and are particularly harmful during early childhood due to their impact on the physical and cognitive development. We estimate the costs of illness due to iron deficiency (IDA), vitamin A deficiency (VAD) and zinc deficiency (ZnD) in 2 age groups (6-23 and 24-59 months) of Filipino children by socio-economic strata in 2008.

Methods: We build a health economic model simulating the consequences of MNDs in childhood over the entire lifetime. The model is based on a health survey and a nutrition survey carried out in 2008. The sample populations are first structured into 10 socio-economic strata (SES) and 2 age groups. Health consequences of MNDs are modelled based on information extracted from literature. Direct medical costs, production losses and intangible costs are computed and long term costs are discounted to present value.

Results: Total lifetime costs of IDA, VAD and ZnD amounted to direct medical costs of 30 million dollars, production losses of 618 million dollars and intangible costs of 122,138 disability adjusted life years (DALYs). These costs can be interpreted as the lifetime costs of a 1-year cohort affected by MNDs between the age of 6-59 months. Direct medical costs are dominated by costs due to ZnD (89% of total), production losses by losses in future lifetime (90% of total) and intangible costs by premature death (47% of total DALY losses) and losses in future lifetime (43%). Costs of MNDs differ considerably between SES as costs in the poorest third of the households are 5 times higher than in the wealthiest third.

Conclusions: MNDs lead to substantial costs in 6-59-month-old children in the Philippines. Costs are highly concentrated in the lower SES and in children 6-23 months old. These results may have important implications for the design, evaluation and choice of the most effective and cost-effective policies aimed at the reduction of MNDs.

Figure 1

General structure of study. The DHS and NNS sample populations are first structured into 10 socio-economic strata (SES) and 2 age groups of children per SES (6–23 months and 24-59 months). In a second step the MNDs of children are assessed in each of these groups. In a third step the lifetime health consequences of these MNDs are modelled based on information extracted from literature. In a final step the direct medical costs, production losses and intangible costs caused by these health consequences are computed and long-term costs are discounted to present value.

Figure 2

Simplified representation of relevant time periods for future costs. Future losses occurring in the 1-year model cohort are discounted to present value taking account of the time frames in which the losses occur.

Figure 3

Prevalence of MNDs by SES and age group. Source: [36], own calculation. No severe IDA in the 24–59 months age group.

Figure 4

Health and cost consequences of IDA. Numbers refer to source of information of effect size or DALY weight in Tables 6, 7 and 8 (first number identifies table). Dotted lines represent long term consequences.

Figure 5

Health and cost consequences of VAD. Numbers refer to source of information of effect size or DALY weight in Tables 6, 7 and 8 (first number identifies table). Dotted lines represent long term consequences.

Figure 6

Health and cost consequences of ZnD. Numbers refer to source of information of effect size or DALY weight in Tables 6, 7 and 8 (first number identifies table). Dotted lines represent long term consequences.

Figure 7

Factors with strongest influence on intangible costs and future production losses. Grey bars indicate the consequence of an increase of the parameter by 20%; black bars the effect of a decrease of 20%.

Figure 8

Results of probabilistic SA for future production losses and intangible costs. The curves indicate the cumulative distribution of future production losses and intangible costs. The solid vertical line represents the main results of the model while the dotted vertical lines delimit the 80% confidence interval of the results of the probabilistic SA.