Identifying Nutritional Need for Multiple Micronutrient Interventions1,2
+ Author Affiliations
- ↵*To whom correspondence should be addressed. E-mail: lneufeld@micronutrient.org.
Abstract
Micronutrient deficiency remains a major
public health problem in many countries worldwide with important
consequences for
the health of the population and child growth and
development. The objective of this article is to review information that
should be taken into consideration in identifying
the need for and in designing micronutrient programs. We review
information
that could be used to identify nutritional need,
including the prevalence of deficiency and evidence of inadequate
dietary
intake as well as potential data sources and some
strengths and weakness of such data for program decision-making. We also
review factors that might modify the potential
impact of programs and that should therefore be taken into consideration
in
their design. For example, such factors may include
access to formal and informal health systems, quality of health
provider
training, and behavior change communication and
complementary or overlapping interventions. Nationally representative
data
on micronutrient deficiencies and dietary intake
are most useful for identifying unmet needs. Although the burden of
micronutrient
deficiencies lies in low-income countries, few have
detailed information on specific deficiencies beyond anemia, and
nationally
representative dietary intake data are scarce.
Nationally representative data may still mask considerable
within-country variability
by geographic, economic, or ethnic group. Some
efforts designed to promote coordination in nutrition programming within
countries
utilizing information on prevalence, intake, and
program coverage and utilization are also reviewed. Improving the
quality
of such data and ensuring continual updates are
vital to guide decision making and to ensure that programs can
appropriately
respond to needs.
Introduction
Micronutrient deficiency remains a major public health concern in many developed and developing countries around the world.
It is estimated that up to 2 billion people worldwide are anemic (1). Similarly, millions are affected by iodine deficiency and deficiency of other nutrients such as vitamin A and zinc and
likely others (2). Infants and young children are particularly vulnerable to micronutrient malnutrition due to rapid growth in the first 2
y of life and the use of complementary foods with low micronutrient content and/or poor bioavailability.
The impact of a number of interventions to ensure adequate intake and improve micronutrient status on pregnancy outcome (3, 4), child growth and development (5–7), and morbidity and survival (8, 9)
has been documented. Based on this evidence, recommendations exist for
many interventions, including dietary diversification
and food fortification to increase regular
consumption of a number of nutrients in populations, vitamin A
supplementation
to reduce child mortality, iron folic acid
supplementation during pregnancy to improve maternal outcomes and fetal
growth,
and zinc as adjunct to oral rehydration solution
for the treatment of diarrhea. Deficiency data and programs currently
tend
to focus on iron, iodine, and vitamin A and, to a
slightly lesser extent, zinc and folic acid (2, 10).
This was motivated by evidence that deficiency of these nutrients is
high and associated with important functional outcomes.
Current evidence suggests, however, that intake of
other nutrients may also be inadequate among many populations and
interventions
to ameliorate negative health impacts may be
needed, including, e.g., vitamin D (11, 12) and vitamin B-12 (13).
At this time, few countries have considered interventions for
micronutrients beyond vitamin A, iron, zinc, iodine, and
folic acid; as additional interventions are
developed, indicators that permit monitoring these should be included.
Despite the documented efficacy of many micronutrient interventions (impact under controlled conditions), evidence of their
impact under programmatic conditions (effectiveness) remains undocumented for most interventions (14).
Likewise, evidence is lacking to explain what factors might modify the
effect of an intervention, whether implemented as
a controlled research study or program. The
potential of a micronutrient intervention to improve micronutrient
status and
functional outcomes is likely dependent on the
severity of the micronutrient deficit and the extent to which the
intervention
addresses the specific causes of deficiency in the
population. When implemented under programmatic settings, a number of
additional
factors could also modify the effect, including the
quality and accessibility of health services, training and behavior
change
communication strategies, and the existence of
complementary or overlapping interventions (15).
The objective of this paper is to review
information that should be taken into consideration in identifying the
need for and
in designing micronutrient programs. We will review
information that could be used to identify nutritional need for
micronutrient
interventions, including the prevalence of
deficiency and evidence of inadequate dietary intake and potential data
sources
for such information. We will also review factors
that might modify the potential impact of programs and should thus be
taken
into consideration in their design.
Identifying Nutritional Need for Micronutrient Interventions
Micronutrient deficiency.
The prevalence of deficiency can be
identified using clinical signs and/or biomarkers. Relying solely on
prevalence of deficiency
identifies only those who have reached a
state of insufficiency so as to alter biochemical or biological
processes. Most biomarkers
identify deficiency and cannot be used to
assess whether intakes are optimized or whether there is a risk of
excess intake.
For some (e.g., serum zinc), this is due to
tight homeostatic control (16).
For others, biomarkers are not specific to the nutrient of interest and
we require additional information to adequately
interpret values. For example, serum ferritin
is elevated as a response to infection or inflammation (16);
without markers of inflammation, ferritin values cannot be adequately
interpreted. Biomarkers of optimal micronutrient
status and not just reduced risk of
deficiency would be ideal, but much research would be required to
develop them.
Anemia is diagnosed as hemoglobin concentration below a cutoff point and reflects insufficiency in the mass of circulating
RBC (1). It is commonly estimated that 50% of cases of anemia are due to iron deficiency (17, 18).
Given the variability in the prevalence of causes of anemia such as
deficiency of other micronutrients, malaria and other
parasitic infection, hemoglobinopathies,
state of chronic disease or pregnancy, and possibly obesity among and
within countries,
it is likely that the figure of 50% of anemia
due to iron deficiency is not accurate in all contexts (19–21). Thus, without complementary information it is difficult to determine what type of intervention is most appropriate to reduce
anemia in any specific context.
Urinary iodine is one of the few
commonly used biomarkers that can indicate low, adequate, and excessive
dietary intake of
iodine. Risk of high intake of iodine using
urinary iodine as a biomarker has been identified in some populations (22). Current surveillance systems require strengthening before this indicator can routinely be used to assess risk of excess
intake as part of routine monitoring (27).
Dietary intake.
Micronutrient deficiency occurs when needs and losses exceed dietary intake. A number of factors contribute to needs, including
normal metabolism, growth and development, pregnancy and lactation, and disease state (16). Loss of nutrients can also be part of normal physiological processes (e.g., menstruation) and can be highly accelerated
during disease and with parasitic infections (16).
Nutrient intake can be quantified from consumption of foods with
naturally occurring or fortified micronutrients and supplemental
sources, but actual uptake of nutrients will
depend on multiple factors, including the bioavailability of nutrients
in foods
and supplements and presence of facilitators
and inhibitors of absorption in the diet, among others. For example, the
bioavailability
of iron from nutritional supplements and
fortified foods may depend on the type of iron used (23); for iron and zinc, absorption will depend on the phytate content of the diet (24).
In populations, nutrient intake can
be quantified from various types of dietary data, ideally from
representative population
groups. Most countries recommend a range of
age- and sex-specific nutrient intake values associated with minimum
risk of insufficient
intake and without risk of adverse effects
for the majority of the population. To avoid confusion related to
differences in
terminology across countries, three values
have been identified (25).
The Average Nutrient Requirement is the average or mean nutrient
requirement for a specific age and sex group. The Individual
Nutrient Intake Level represents the
recommended intake for all healthy individuals in an age- and
sex-specific population
group, and the Upper Nutrient Level
represents the highest intake that is likely to pose no risk of adverse
effects for the
given group (25). These reference values provide a framework to estimate the range of safe intakes, focusing on minimizing risk of insufficient
and excess intakes.
Data Sources for Identifying Deficiency, Inadequate Nutrient Intake, and Other Causes of Deficiency
Data sources on the prevalence of deficiency.
The WHO maintains a repository of information on micronutrient status from its member countries (2). Previously, the VMNIS3
included only iodine status, vitamin A deficiency, and anemia and
relied mainly on multi-nation surveys such as the DHS,
UNICEF MICS, and other national surveys. The
VMNIS system recently received a considerable upgrade with the objective
of improving
its functionality for decision making in
countries (2).
Information sources on micronutrient status will be systematically and
regularly updated, including a number of sources
not previously considered. The new system
will also include additional indicators of micronutrient status,
including hemoglobin,
serum ferritin, serum transferrin receptor,
serum or plasma retinol, serum or plasma retinol binding protein,
urinary iodine
excretion, serum or plasma zinc, serum or
plasma folate, RBC folate, as well as clinical indicators of vitamin A
and iodine
deficiencies (i.e., night blindness and
goiter, respectively) (2).
Although the systematization of
this information will be extremely useful, the extent to which it
improves accessibility to
information on micronutrient status for
decision making in countries depends on the availability and quality of
information
included. At this time, national and
within-country representative data for micronutrients beyond vitamin A
and iodine and
anemia remain scarce for most countries.
Nationally representative data will mask considerable variability by
geographic region,
economic status, and ethnic group within
countries. For zinc deficiency, we continue to rely on the prevalence of
stunting,
an indicator not specific to zinc deficiency (26).
Furthermore, the limitations of the existing data for vitamin A,
iodine, and anemia to represent the true risk of micronutrient
deficiency in populations are clearly
recognized. For example, pregnant women and their fetuses are the most
vulnerable to
the effects of iodine deficiency, yet
information on their status is scarce and insufficient to estimate the
global burden
of deficiency in this group (27).
At this time, logistic concerns
related to transportation of biological samples and the cost of
analyzing micronutrient biomarkers
remain an important barrier to their
inclusion in large surveys. The development of noninvasive methods for
assessing micronutrient
status and laboratory methods that can be
used on very small biological samples could do much to improve this. For
example,
the use of dried serum spots for ferritin
obtained from capillary samples holds much promise for assessing iron
status in
population surveys, though standardization is
required and many laboratories in lower resource settings lack the
equipment
and expertise to analyze this less invasive
method (28). There have also been efforts to develop noninvasive tests for quantifying hemoglobin concentration (29), but methods still require validation.
Dietary intake data.
National level data on food
availability such as food balance sheets have been used to assess the
adequacy of energy available
to meet population needs and have recently
also been used to assess adequacy of the supply of vitamin A (30) and zinc (31)
at a national level. Although the above-mentioned strategies are useful
for planning some national untargeted strategies
such as agricultural policies and food
fortification, targeted programs such as supplementation require
information on nutritional
needs of specific age groups or other
vulnerable groups. This requires nationally and preferably regionally
representative
survey data for those groups (16). Few countries have nationally representative dietary intake data from individuals from the past 10 y (Fig. 1) (32–49).
Data are particularly scarce for regions of the world with the highest
vulnerability to micronutrient deficiency; notably,
published data were found for only five
countries in Africa, four in South and Central America, and four in
South East Asia.
Most countries collect information with some regularity on household income and expenditure (50).
Such information distinguishes consumers from nonconsumers (at the
household level) and those foods that are purchased
from those that are home produced or gifted, a
strength distinguishing this data source from food balance sheets. The
method
permits a proxy estimation of individual
consumption based on assumptions of intra-household distribution
(adult-equivalent
method) (50).
The extent to which this is appropriate for consumption among specific
vulnerable groups (e.g., pregnant women or children)
is currently being evaluated using data from a
number of countries in Africa and Asia (Jack Fiedler, personal
communication).
Additional Factors That Should Be Taken into Consideration in Program Design
Beyond the prevalence of deficiency and
quantification of dietary intake, additional information about
population characteristics
may support the design of context-appropriate
interventions to improve micronutrient status. For older children and
adults,
we may assume that access is a key limiting factor
for micronutrient intake. For infants and young children and possibly
for
pregnant women, traditions related to
breast-feeding and complementary feeding and food taboos may also be
important causes
of inadequate micronutrient intake. Such factors
should be taken into consideration in the design of interventions to
address
deficiency. Some of the same data sets used to
document deficiency prevalence, such as the DHS and MICS surveys,
usually contain
some information related to feeding practices.
Strengths and weaknesses of some data sources can be found in Table 1 (2, 51).
For many, particularly the multi-nation surveys such as DHS, attempts
have been made to standardize methodologies across
sites. Although appropriate to ensure
comparability, this may limit flexibility to adapt the surveys to
country-specific potential
causes of micronutrient deficiency, e.g.,
traditions related to dietary intake during pregnancy. Some countries
such as Mexico
have invested in large, national surveys with
regional, state-wide, and urban-rural level representative samples,
including
dietary data and biological indicators of
micronutrient status (52). This information, coupled with the wealth of information from program evaluations that exist in Mexico, allows for detailed
assessments of need among different groups in the population (53).
This has permitted the implementation of specific targeted strategies
and the refinement of program targeting criteria
to the most vulnerable. Many countries would not be
in a position to make such a large investment. At a minimum,
information
should be available for the administrative level at
which programs will likely be implemented. For example, if a country
considers
targeting a program to the most vulnerable
provinces, then information should be available by province to
prioritize their
inclusion in the program.
View this table:
TABLE 1
Data sources used to estimate need for micronutrient interventions and some strengths and weaknesses of each
One aspect of need that is often
inadequately documented is the availability and utilization of existing
programs and strategies
to improve micronutrient status. Coordinated
program delivery may or may not be effective among governmental and
nongovernmental
organizations operating within a single region and
even across different government sectors within a country. A number of
initiatives exist to support this process,
including the REACH and WHO Core health indicators (54, 55).
The REACH Initiative serves as a knowledge broker for east African
health programs, and the Core health indicators report
world health statistics from the WHO database.
Although promising, the REACH Initiative is still in its infancy and the
Core
health indicators, though exhaustive, lack
information about specific indicators of micronutrient status. In
addition to nutrition-specific
interventions, programs that may complement
strategies should be considered in the design of micronutrient
interventions.
For example, social protection programs may be
complementary to efforts to reduce micronutrient deficiency by
facilitating
access to the population in which micronutrient
deficiency is high. An excellent example of such complementarity is
conditional
cash transfer programs that have been shown to
increase the use of health services among the poor in a number of
countries
(56).
At this time, only the program in Mexico has been used as a delivery
platform for a micronutrient intervention, specifically
the free distribution of a micronutrient-fortified
food for pregnant and lactating women and complementary food for
children
6–24 mo of age (57).
A number of factors might limit or
facilitate the successful implementation of interventions, including
utilization of formal
and informal health services in the population,
quality and regularity of training of health personnel, and coverage of
other
vital health services such as immunization and
growth monitoring. Such factors have been shown to be important
modifying factors
in the success of implementation of the Integrated
Management of Childhood Illness program, including the success of
vitamin
A supplementation (58).
The WHO’s Nutrition Landscape Information System (59)
provides access to country profile information on the nutrition
situation in the country, existing programs, infrastructure,
and a number of measures of country commitment,
capacity, and other factors vital for understanding the need for further
interventions.
Like the VMNIS and other compiled data sets, the
utility of this information system will depend on the quality of the
information
included and the frequency with which it is updated
to ensure that it reflects the current situation.
Summary and Conclusions
Micronutrient interventions should be
implemented in response to a demonstrated need, whether that is the
prevalence of deficiency
or evidence of insufficient dietary intake to meet
the needs of the majority of the population and a lack of existing
programs
to address that need. Up-to-date information on the
prevalence of deficiency beyond vitamin A and iodine is scarce for most
countries in the world and particularly for many of
those with the highest risk of deficiency. Even when available,
national-level
data may be insufficient to identify vulnerable
groups due to variation in dietary intake and deficiency prevalence by
region,
economic status, or other factors. The need for
information to guide policy and program development in nutrition has
been
recognized (59) and some advances to the systematization of data collection and dissemination have been made.
Most recommendations and guidelines are
intervention specific and do not provide clear indications or
contraindications on
the simultaneous implementation of multiple
interventions. This limits our ability to predict risk of excess
consumption in
contexts where multiple interventions exist or
where changes to dietary patterns have improved usual intake of
micronutrients.
For example, guidelines for the management of
severe acute malnutrition should clearly specify whether other
interventions
likely to be implemented in the country, such as
vitamin A supplementation, zinc with oral rehydration solution for
treatment
of diarrhea, and home fortification (micronutrient
powders and/or lipid-based nutrient supplements) should be suspended
during
treatment and when these should resume. Although
this may not yet be a problem in most countries with a high burden of
micronutrient
deficiency, monitoring and evaluation systems
should be in place that would permit such reflections over time.
In addition to clear guidance, programs
should assure accurate monitoring and evaluation and include indicators
beyond simple
measures of program coverage to ensure that trends
on coverage and utilization of programs can be tracked over time. For
some
interventions such as vitamin A supplementation,
coverage might be an acceptable proxy for utilization as the
intervention
is delivered directly by trained personnel. For
such interventions, data from large surveys have been used to identify
characteristics
of those not receiving the program (60)
and provide contextual factors that might help improve program
implementation and estimate potential impact. Adding a module
to such surveys on receipt and utilization of other
programs that might affect vitamin A intake and status would be useful
for assessing overlap and complementarities. For
other programs, e.g., iron-folic acid for pregnant women and
micronutrient
powders or lipid-based supplements for children,
coverage estimates do not reflect the extent to which the supplements
were
consumed or the regularity, duration, or mode of
use. Consistent collection, analysis, and reporting of such information
would
complement deficiency and dietary intake data and
allow for the accurate mapping of nutritional shortfalls and help
determine
whether existing interventions are likely to meet
that need.
Acknowledgments
L.M.N. wrote the paper and had primary responsibility for final content; B.M.C. assisted with preparation of the presentation
with background work for the manuscript. Both authors read and approved the final manuscript.
Footnotes
-
↵1 Published in a supplement to The Journal of Nutrition. Presented at the workshop “Multiple Micronutrient Nutrition: Evidence from History to Science to Effective Programs,” held at the 2nd World Congress of Public Health Nutrition in Porto, Portugal, September 23–25, 2010. The supplement coordinators were Klaus Kraemer, Sight and Life, Basel, Switzerland and Richard D. Semba, Johns Hopkins University School of Medicine, Baltimore, Maryland. Supplement coordinator disclosures: Klaus Kraemer is employed by Sight and Life, a humanitarian initiative of DSM Nutritional Products Ltd., Basel, Switzerland. Richard D. Semba has no conflicts of interest. The Acting Editor-in-Chief for this supplement was Jesse Gregory. Acting Editor-in-Chief disclosure: Jesse Gregory has no conflicts of interest. The supplement is the responsibility of the Guest Editor to whom the Editor of The Journal of Nutrition has delegated supervision of both technical conformity to the published regulations of The Journal of Nutrition and general oversight of the scientific merit of each article. The Guest Editor for the supplement was Marian Neuhouser. Guest Editor disclosure: Marian Neuhouser has no conflicts of interest. The workshop was supported by a grant from Sight and Life, Basel, Switzerland. The contents are solely the responsibility of the authors and do not necessarily represent the official views of the organization of which the organizers are affiliated. Publication costs for this supplement were defrayed in part by the payment of page charges. This publication must hereby be marked “advertisement” in accordance with 18 USC section 1734 solely to indicate this fact. The opinions expressed in this publication are those of the authors and are not attributable to the sponsors or the publisher, Editor, or Editorial Board of The Journal of Nutrition.
-
↵2 Author disclosures: L. M. Neufeld and B. M. Cameron, no conflicts of interest.
-
↵3 Abbreviations used: DHS, Demographic and Health Survey; MICS, Multiple Indicator Cluster Survey; REACH, Regional East African Community Health Initiative; VMNIS, Vitamin and Mineral Nutrition Information System.
- Manuscript received: January 19, 2011.
- Initial review completed: May 21, 2011.
- Revision accepted: July 16, 2011.
