The Gerald J. and Dorothy R. Friedman School of Nutrition Science and PolicyFOOD POLICY AND APPLIED NUTRITION PROGRAM

DISCUSSION PAPER NO. 4

Intrahousehold Dimensions of Micronutrient Deficiencies:A Review of the Evidence

Patrick Webb

March 2002

Corresponding Author: Patrick.Webb@Tufts.edu

Discussion papers provide a means for researchers, students and professionals to sharethoughts and findings on a wide range of topics relating to food, hunger, agriculture andnutrition. They contain preliminary material and are circulated prior to a formal peer reviewin order to stimulate discussion and critical comment. Some working papers will eventuallybe published and their content may be revised based on feed-back received.

The views presented in these papers do not represent official views of the School. Thediscussion paper series is available on line at nutrition.tufts.edu/publications/fpan. Please submitdrafts for consideration as FPAN Discussion Papers to Patrick.Webb@Tufts.edu.

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Acknowledgements

The author would like to thank the following people who generously shared data and/orinsights:

Chidzuru Nishida and Ian Darnton-Hill (WHO Geneva), Beatrice Rogers, James Levinson,Gary Gleason, Robert Russell, Willie Lockeretz, Guangwen Tang and Judy Ribaya-Mercado(Friedman School of Nutrition Science and Policy, Tufts University), Chipo Mwela (NationalFood and Nutrition Commission, Zambia), Howarth Bouis (International Food PolicyResearch Institute), Noel Solomons (Center for Studies of Sensory Impairment, Aging andMetabolism, Guatemala), Keith West, Joel Gittlesohn and Rebecca Stotzfus (Johns HopkinsUniversity), Margaret Bentley (University of North Carolina—Chapel Hill), Martin Frigg(Task Force Sight and Life, Geneva), Nina Schlossmann (Global Food and Nutrition), MartinBloem (Helen Keller International, Jakarta), Klaus Becker, Peter Fuerst and Konrad Biesalski(Hohenheim University, Stuttgart), Pieter Dykhuisen (World Food Programme), EllenMesser (Brown University), Victor Barbiero and Timothy Quick (USAID), and Rainer Gross(GTZ, Jakarta).

All errors in data or interpretation are those of the author alone. The use of English (ratherthan US) spelling relates to the commissioning of this report and its use by a UN agency.

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Summary

Although micronutrient deficiency is a global problem, it is not a universal one; the burden isnot evenly shared within countries or households. Empirical evidence from 69 studiescompiled for this review indicates that there are important non-linearities in relationshipsamong food intakes, sharing and caring behaviour, and micronutrient status that lead to adiversity of outcomes not always predictable by age or gender. Mothers and girls display ahigher prevalence of some deficiencies than men or boys, but the situation is confounded orreversed in other contexts. No single age cohort, gender or location is invariably worse offthan every other, all of the time. The manifestation of deficiencies is determined bysynergies among nutrients, diseases and biological functions, on the one hand, andinteracting social, economic and environmental processes, on the other.

The unmasking of age and gender diversity in risks and outcomes is important for betterestablishing the global prevalence of micronutrient problems and for improving the focus ofpublic action. The tools used in assessing deficiencies need to be re-examined in light ofmultiple interactions among micronutrients, on the one hand, and among health andbehavioural confounders, on the other. Understanding local dietary practices, health carepreferences, activity patterns and tradeoffs in resource access is as crucial as specifyingphysiological benchmarks. Clinical rigour needs to be combined with rigourous contextualinsight. The conventional narrow focus on one deficiency, for one priority group at a timeneeds to be questioned. Progress in tackling single micronutrient problems for single targetgroups may not mean that everyone is, or remains, better off. Sustainable gains for wholepopulations are likely to require combinations of actions at various levels to influence theincentive and behaviour structures operating down to the intrahousehold level.

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Introduction

As recently as 1994, the World Bank was concerned that “policymakers in many countriesstill need to be convinced of the imperative to attack micronutrient malnutrition.” Todaythings appear to have improved. “Great strides” have been made in tackling iodinedeficiencies according to the ACC/SCN (1997), with 73 countries having enacted legislationto support universal salt iodisation. The number of countries likely to meet vitamin A goalsset by the World Summit on Children rose from 17 in 1995 to 30 in 1997 (OMNI 1997).And although nutritional anemia is proving to be more of a challenge, “progress is beingmade” (UNICEF 1998a), and “success is at hand” (West and Hautvast 1997).

These developments are encouraging. But a certain caution is required in interpreting suchoptimism. For example, one of the main criteria for assessing whether a country can meetvitamin A goals set for the end of 2000 is whether 50 percent of its children are covered bysupplementation programmes (VAGI 1997). By implication, if 50 percent of children in all78 countries in which vitamin A deficiency is a public health concern receive supplements,the target will be met. While acknowledging the political constraints involved in achievingconsensus on international nutrition agendas, such a criterion begs two important questions.First, what of the other 50 percent of children—when will their needs be met? Second, whatof all the non-children? Similar questions apply to the goal of reducing iron deficiencyanemia by one third among women of reproductive age (ACC/SCN 1997). What of thewomen who are not of reproductive age? What of men? The assumption seems to be thatprogress in tackling deficiencies for mothers and infants will inevitably benefit all otherpopulation groups. Are such assumptions valid? Is the micronutrient status of one group agood proxy for the status of others?

Based on a review of 69 empirical studies, this paper explores the issue of variability inmicronutrient deficiencies by age and gender in diverse developing country contexts. Thefocus is on vitamin A, iron and iodine, but other minerals and trace elements are includedwhere relevant. Numerous scientific and field experts were consulted, some offering accessto latest findings as well as older archived materials. An effort was made to achieve broadgeographic (and non-English language) coverage, as well as representation from differentdisciplines and methodologies. Thus, around two-thirds of the studies presented here are‘clinical’ studies based on laboratory assessment of deficiencies and evaluation of publicinterventions; the rest are secondary analyses of national surveys, anthropologicalinvestigations, and a few household economic surveys. This is by no means an exhaustivecompilation. The 69 studies represent the tip of an iceberg. Dozens more studies were notincluded because they did not disaggregate their analysis although the base data would haveallowed it. Tracing such datasets for a meta analysis of combined data (following Beaton et.al. 1993) is feasible. This paper is therefore only a first step towards an urgently neededbroader assessment of the intrahousehold context of deficiency outcomes.

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Entering the Household

It is something of a paradox that while nutrition science offers increasingly sophisticatedage-, and sex- specific dietary recommendations for micronutrients (WHO 1996; Berdanier1998), much nutrition policy and practice continues to be formulated in the absence ofinformation drawn at a comparable level of disaggregation. Our knowledge of who is mostaffected by what deficiencies (either singly or in combination), when and where, isrudimentary at best. Although statistics on the global prevalence of various deficiencies arewidely circulated, most represent extrapolations based on shaky foundations. For example,“many countries do not have up-to-date national-level assessments of the prevalence ofvitamin A deficiency, and are unlikely to have them in the near future.” (VAGI 1997)Similarly, estimates of global iron deficiencies “are not accurate” based as they are on smallstudies “in limited geographic areas.”(IDRC 1998)

This is not to detract from the careful statistical interpolation carried out by many individualsand agencies in the absence of better data (Clugston et. al. 1987; WHO 1995; Sethuraman et.al. 1997; UNICEF 1998b). Considerable effort has gone into aggregating small surveys up tonational level so that a sample of 423 children aged 0 to 60 months in Zambia can becompared with, say, 22,335 children 4 to 72 months old in Bangladesh. However, much lesseffort has been directed towards disaggregating survey data by age and gender with a view toclarifying interactions among nutrients for different individuals in diverse environments.

This is somewhat surprising given the long tradition of intrahousehold research on other foodand nutrition issues. There is a large literature on gender, age and status biases in developingcountry households that owes much to the anthropological and ethnographic work of the earlytwentieth century (Mead 1928; Hailey 1938). Although diverse, this (still-growing) body ofresearch generally agrees that households rarely represent unitary enterprises that maximizewelfare for all members. As Agarwal (1997) puts it, “households comprise multiple actors,with varying (often conflicting) preferences and interests, and differential abilities to pursueand realize those interests. They are arenas of…consumption, production and investmentwithin which both labor and resource allocation decisions are made.” As a result, the successof public policy or interventions can in part depend on predicting tradeoffs in resource accessamong different individuals.

This applies to micronutrients as much as it does to macronutrients, income or productiveassets. A micronutrient deficiency is more than a biological symptom requiring ‘treatment’through targeted supplements or fortified foods—it reflects a development problem withinherent intrahousehold dimensions. According to Nelson (1986), “interpretation of dietaryadequacy in household food surveys should take into account the distribution of nutrientintakes within the household, as the distribution may be substantially different from thatrecommended.” Similarly, Gittelsohn et. al. (1998) argue that “examining intrahouseholdbehaviour is critical for understanding the causes of [micronutrient] deficiency.” Yet, theempirical basis for gaining such an understanding is constrained by a lack of information at theintrahousehold level. Few sample-based studies or national surveys of deficiency distributionsconsider all members of included households, or multiple age and sex categories of largercross-household samples. Some studies do look at mother-child pairs (WHO/CHD 1997), atboth parents of a ‘focus’ child (Schultink et. al. 1996), or at one or more siblings of a ‘focus’child (Katz et. al 1993). But only a handful of studies have sought to include all individuals

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from at least several hundred households. Less than half a dozen such studies are included inthis review.

Equally important is the contextual basis for interpreting deficiency outcomes. Someanthropological or ethnographic studies have examined evidence of dietary discrimination,culturally-prescribed activity patterns and differentials in care behaviour in relation tomicronutrient intakes or deficiency measures, but again these are limited to a handful of cases(including Leonard 1991a; Backstrand et. al. 1997; Gittelsohn et. al. 1998). Why so few?

Aside from the obvious cost and difficulty involved in pursuing large, multiple categorysurveys, the lack of age/gender disaggregation seems to derive in part from the biochemicalor clinical nature of most micronutrient studies. The majority of micronutrient studies arebased on case-control samples aimed at exploring specific nutrient-disease or intervention-outcome responses. Clinical trials are crucial to understanding biological mechanisms andpotential public responses. Some offer invaluable insights into age, gender, socioeconomicor geographic differentials; but most do not. Typically, the prevalence of a singlemicronutrient deficiency is reported and populations are aggregated into case and controlgroups. Some studies go so far as to specify the age and sex stratification used in samplingand in defining groups, but they still report findings in aggregate terms (such as MeeksGardner (1988) and Kapil et. al. (1996)).

Of course the masking of heterogeneity in sampled populations also occurs in someanthropological and food policy-oriented studies. A few important studies in India(Pushpamma et. al. 1982), Indonesia (Schultink et. al. 1996), Peru (Leonard 1991a), Nepal(Gittelsohn et. al. 1997; Shankar et al. 1998), and the Philippines (Bouis et. al. 1998), exploremultiple age, gender and status differences in nutrient access or status, but most focusnarrowly on young childhood and/or maternal outcomes. For example, of over 500 studieson anemia reviewed by Kurz (1996) only 39 included adolescents, and a mere handfulconsidered the status of male adults or school-aged children. In the current review almosttwo-thirds of the studies are principally, if not exclusively, concerned with the condition ofinfants and mothers alone.

This focus derives from an understanding of the special physiological demands facingpregnant and lactating mothers, and of the dual dangers to infants of early mortality or ‘earlytrauma-later deficit’ (Waterland and Garza 1999; Pollitt 1999; Hurtado et. al. 1999). Buteven these categories sometimes obscure more than they reveal. Depending on the nutrientsconcerned (and prevailing policies of international agencies), young children can bespecified as “children under five years of age” (Kapil et. al. 1996; WHO 1998), “childrenfrom 6 to 36 months of age” (WHO/UNICEF 1998), or “children 6-24 months of age”(Nestel 1995; Thu et. al. 1999). The focus on “mothers” is similarly diverse in that it canrefer specifically to lactating mothers (VAGI 1997), or to adult women with offspring of anyage (Schultink et. al. 1996).

The paucity of data disaggregated beyond young children and mothers makes it difficult to assessrelative states of sufficiency among whole populations and can even deflect attention fromunderlying causes. For example, measuring nutritional anemia among mothers in isolation fromproblems of other household members carries two important risks: first, the danger of missingimportant deficiencies affecting adolescents, the elderly, school-aged boys, and working men;

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second, the likelihood of incorrectly interpreting a deficiency—that is, mistakenly attributing amother’s deficiency to gender bias or low status of women when it in fact the problem relates toall household members. Thus, deficiencies of mothers and infants need to be addressed in tandemwith those of other household members if a net gain is to be sustainable.

With this in mind, the following sections explore empirical findings on the heterogeneousnature of micronutrient problems presented at varying levels of disaggregation. The firstsection deals with vitamin A, and also addresses issues of age and life cycle. The secondsection focuses on iron deficiency set in the context of discussion of socioeconomicconfounders. The third section examines iodine deficiencies alongside consideration of thegeographic/agroecological dimensions of nutrient problems. A final section addresses thequestion of age and gender discrimination within the household.

Who suffers what deficiencies, when?

Three broad generalizations with clear intrahousehold dimensions are repeated as if de rigeurin the micronutrient literature. The first is that “boys are frequently at greater risk ofxerophthalmia (night blindness and Bitot’s spot) than are girls.” (Sommer 1995; McLaren andFrigg 1997) The second is that females, especially women of reproductive age, suffer a higherprevalence of iron deficiency than men do (Kurz 1996; ACC/SCN 1997). The third, relatingto iodine, is that “girls have a higher prevalence than boys”, especially from adolescenceonwards (WHO 1993, 1996; Cobra et. al. 1997). These generalizations are based on decadesof accumulated field experience, backed up by national surveys from the 1970s and 1980s,and by laboratory experiments. They have served as a vital platform during the 1990s forinforming policy targets and programming decisions. But, to what extent do they matchempirical findings at an intrahousehold level?

Are boys more deficient in vitamin A than girls? If so, which ‘boys’?

McLaren and Frigg (1997) report that vitamin A deficiency is “almost uniformly reported” to beup to 10 times more common in males than females. Yet, the studies used to illustrate this pointdate from 1960 to 1982. Only 3 of the studies reviewed here are that old, and more recentempirical support for such a generalization is not strong. Of 49 studies compiled here that dealwith vitamin A only 15 (less than one third) report that boys have a lower vitamin A status thangirls (see Table 1 for a summary of findings, Appendices 1 and 2 for detailed information).

This seems to hold for all parts of the world; no region has a majority of studies showing boysto be significantly more vitamin A deficient than girls. For example, although one study inIndonesia shows that boys have a higher prevalence of Bitot’s spot and night-blindness thangirls (Muhilal et. al. 1994), another from the same country (included in the meta analysis byKatz et. al. 1993) finds no significant difference in the risk of xerophthalmia by gender.Similarly, Tafesse et. al. (1996) report that boys from one of Ethiopia’s provinces displaysignificantly lower retinol levels than girls, but Wolde Gebriel (1992) found no difference inmean serum retinol levels by gender for Ethiopian children in a national sample. And while

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Table 1—Overview of studies included in the review and summary of findings

Geographic Number Confirming Confirming Confirming ConfirmingRegion of studies1 boys more females more girls more girls more

vitamin A iron deficient iodine deficient deficient indeficient 2 other elements3

Asia/Pacific 29 8/27 8/14 1/1 7/12

Sub-Saharan 15 5/13 1/3 2/2 1/2Africa

W.Asia/N. Africa 08 2/5 1/1 1/2 -/-

Latin America/ 11 0/3 2/5 1/2 3/3Caribean

Industrialized 03 0/1 1/1 -/- 2/2

Total 69 15/49 13/23 5/7 13/23

1 Since many of the 69 studies included in this review dealt with more than one micronutrient column

and row totals do not match.2 For example, only 8 of 27 studies from the Asia/Pacific region showed that boys were significantly

more deficiency in vitamin A than girls.3 Other elements included here are vitamins B6, B12, C, and E zinc, manganese, calcium, niacin and

thiamine.

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Badenhorst et. al. (1993) show that 6-10 year-old boys in South Africa (in primary schools)have a serum retinol level below recommended level, Willumsen et. al. (1997) find nosignificant difference in retinol levels by gender for a sample taken from South Africanhospitals. Such apparently contradictory findings are available for many other countries,challenging ideas about the universal nature of male deficiencies.

That said, it cannot be assumed that girls are more at risk than boys are. Of the 34 studies inwhich boys do not have more deficiencies than girls, only 10 find greater signs of deficiencyamong females than males; the other 24 (71 percent) find no significant difference betweengenders. For example, while Pushpamma et. al. (1982), Upadhay et. al. (1985), Bloem et. al(1989) and Katz et. al. (1993), all report a higher relative risk or prevalence of vitamin Adeficiency for one gender over the other (in India, Nepal, Thailand, Indonesia, Malawi andZambia), in no case was the difference statistically significant. The significance level ofreported differences between boys and girls must be as carefully interpreted as the absolutebenchmarks used.

This raises two issues of survey design and analysis. On the one hand, there are difficulties incomparing assessment methods. Of the 15 studies in which vitamin A deficiency is shown to bea greater problem among boys than girls, only 4 are based on biochemical analysis of serum; therest are based on food intake and/or clinical examination for ocular signs. This is not to suggestthat the latter approaches are less valid than laboratory-based measures, rather to highlight theissue of comparability among techniques. One study finds that male neonates have significantlylower cord plasma levels of vitamin A than girls (Tolba et. al. 1998), another sees higher ratesof night-blindness among girls aged 3 to 4 years than boys (Shankar et.al. 1998), while a thirdfinds that adult women have a lower intake of green leafy vegetables, in a 24 hour-recall foodsurvey, than men (Gittelsohn et. al. 1997). Are these three findings indicative of the same typeor degree of deficiency problem? What confounders might apply to one context or methodmore than to another? Such were the difficulties facing WHO (1995) in its assessment of theglobal prevalence of vitamin A deficiencies; namely, to derive global generalizations based on“disparate classifications…in many of the rates presented for total xerophthalmia.” Care isneeded in interpreting micronutrient findings based on widely differing approaches and moresensitivity analysis and cross-validation of techniques are urgently required (McLaren and Frigg1997; Stotzfus et. al. 1997; Mock 1999; Olson 1999).

On the other hand, there is the issue of age categories included in the sample frame andstatistical benchmarks. For a sample of Thai children aged 1 to 8 years, Bloem (1989) showedthat there was no difference between boys and girls in vitamin A status if one considered onlymean values. That is, the mean retinol level for boys (all ages) was 0.72 umol/l compared with0.76 for girls, and the difference was not statistically significant. Mean levels of retinol-bindingprotein and serum iron were also comparable by gender. Yet, a highly significant difference didapply to standard deviations around the mean, not only for retinol values but also for ferritin.Indeed deviation from the mean was not only higher for girls than boys (showing greatervitamin A deficiency among certain girls), but it occurred in some age cohorts and in somelocations more than it did in others. That is, rural boys and girls aged 3 to 6 years both hadsignificantly lower serum retinol levels than urban children—rural children of others ages didnot show such a difference. What is more, boys aged 3 to 6 years in rural areas had asignificantly lower retinol level than girls of the same age in rural areas, but other age groupsshowed no difference.

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In other words, combining all ages and demographic groups obscures specific outcomes. Weneed to ask what terms like ‘boy’ or ‘girl’ actually mean. Of the studies that consider the statusor food intakes of children (separate from those of adults), more than half report no significantdifference between boys and girls. Yet, some studies consider boys aged 0 to 60 months andothers include girls aged 1 to 18 years. A lack of statistical significance may be due to amasking of differences that exist among different age cohorts or either gender. Wolde-Gebrielet. al. (1991) found that while beta-carotene levels were within normal range for both boys andgirls aged 60 to 72 months, they were significantly lower for all children aged less than 23months (especially so for boys). In South Africa, Badenhorst et. al. (1993) found that 11 to14year-old boys consumed more dietary retinol equivalents than boys aged 6 to 10. Both casesillustrate that an averaged statistic for all ‘boys’ would obscure age differentiation.

The latter examples lend support to the generalization that deficiencies relate to agedifferences; namely, that “as children grow older…vitamin A status improve[s], and the riskof blinding xerophthalmia and other consequences of deficiency declines.”(Sommer 1995)Indeed, Lindblad et. al. (1998) and Tolba et. al. (1998) have shown that serum retinol levelsamong newborns can be extremely deficient in United Arab Emirates and Saudi Arabia(especially for boys), which may lead to high risks early in life.

However, a different view has also been put forward. The four-country meta analysis byKatz et. al. (1993) found that “age was strongly associated with xerophthalmia in each study.The risk increased 3-5% for each additional month of age. This translated to an increasedrisk of 36-60% for each year of life.” Sommer and West (1996) indicate that mildxerophthalmia peaks between ages 3 and 6 in India, Zambia and Nepal, and earlier whereincidence is more severe. These findings are supported in Nepal by Shankar et. al. (1996).They found that the prevalence of ocular measures of vitamin A deficiency (night blindness,Bitot’s spot, corneal xerosis) increased with age, such that 10 percent of the sample showedsigns of deficiency in the 1 to 2 year age group, 37 percent had problems in the 3 to 4 yearcategory, and the remaining 53 percent were concentrated in the 5 to 6 year group.

Other studies have found less linear relationships. For example, a national survey in Nigerconducted in 1986 found more evidence of night blindness among boys than girls aged 0 to 6years, but higher prevalence among girls than boys in the 6 to 10 year age cohort (see WHO1995). What is more, although there appeared to be no difference in prevalence of Bitot’sspot by gender in the 0 to 6 years cohort, Bitot’s spot prevalence was significantly higher forboys in the 6 to 10 cohort. Indeed, it is interesting that where studies focus on children up tosix years of age, the vitamin A deficiency problem is commonly concentrated in the laterages of such samples: 4 to 6 years in the Philippines (Klemm et. al 1993), 6 years versus 3years in Bangladesh (Stanton et. al. 1986), 3 to 5 years in Malawi (Tielsch et. al. 1986), 4 to5 years in Yemen (Rosen et. al. 1996). This may be related to periods of rapid growth,associated in turn with increased protein metabolism which can impair vitamin A status.

Studies that include children older than 6 years are not common, but the few that do suggestthat vitamin A deficiencies can increase with age during school years rather than decrease.For example, Ismail (1989) showed that males aged 13 to 19 years in Malaysia had anaverage daily intake of dietary vitamin A considerably higher than males aged 20 to 59 years(the same trend applying to women). Bouis and Novenario-Reese (1997) found that

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adequacy of vitamin A intake in Bangladesh fluctuates considerably by age and gender--falling from a level of 51 percent adequacy for boys aged 0 to 6 years to only 41 percent inthe 7 to 12 age group, then climbing again to 63 percent among 13 to 18 year-olds.Adequacy for girls was more stable lying between 46 and 49 percent of adequacy from infantto adulthood.

It can be concluded here that the aggregation of age and gender towards undifferentiatedsample means obscures the dynamics of a problem that affects females as well as males, andolder children, adolescents and adults as well as infants. This has implications for estimatesof the global prevalence of deficiency problems. For example, WHO (1995) generatedvaluable estimates of ‘population at risk’ of vitamin A deficiency problems. Representativenational surveys were available for some countries, although ‘representative’ in this casemeans geographic coverage rather than age and gender coverage (most national surveysfocus on pre-school age children and present data as an aggregate for both genders). On theone hand, since many of the studies in this review show that severe deficiencies can occur inthe school-age and adolescent periods there is a danger of large-scale underestimation of thescale of deficiencies. On the other hand, where national surveys were not availablemultiplication factors were derived from sub-national surveys and applied to the childpopulation (0 to 4 years) of each country. However, if there are clear gender differentials insome countries (making one gender much more at risk than the other) then there is the dangerof overestimating the scale of the problem in numeric terms since only half the childpopulation may be involved.

These are simply theoretical illustrations to point out the need for greater sensitivity to life-cycle dimensions of vitamin A deficiencies for males and females of all ages, and to thecultural dimensions of care behaviour, physical activity and resource discrimination whichmediate food intakes and deficiency outcomes. The specifics of the individual matter, as dothe specifics of the individual’s environment.

Are richer women more iron deficient than poor men?

Iron deficiency also has complex life-cycle dynamics. According to West and Hautvast(1997), nutritional anemia has been “more difficult” to control than other micronutrientdeficiencies. On the one hand, the search continues for simple, functional measures of ironstatus that allow consideration of the interactions among iron, other micronutrients, anddiseases for different age and gender categories (Beutler 1997). On the other hand, debatecontinues regarding appropriate interventions (ACC/SCN 1997; Viteri 1999).

It is well documented that there is a higher risk of anemia to women of reproductive agedue to menstruation (Brabin and Brabin 1992; Kurz 1996). And it is widely argued that“pregnant women and children under 5 years old are at greatest risk of being iron deficientwhen anemia is used as the major clinical manifestation.”(Nestel 1995)

Nevertheless, evidence is accumulating that deficiencies are also to be found among men andalso children between 5 and 18 years of age. For example, although Badenhorst et. al. (1993)found little difference in iron intake between 6 to 10 year old boys and girls (intake for girls wasslightly higher), 46 percent of boys had low serum levels compared with 33 percent for girls.

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Also 36 percent of boys had a transferritin saturation level below 16 percent, compared withonly 17 percent of the girls. When considering 11 to 14 year olds there was no statisticaldifference in dietary iron intake, but more boys were anemic. As the authors note, “wide age-ranges (3-14 years) and different cut-off criteria used in defining anemia causes problems indiagnosing anemia properly.” (Badenhorst et. al. 1993)

The use of different measures and age groups does indeed bring about different combinationsof outcomes. In Thailand, for instance, Bloem et. al. (1989) found no significant differencebetween boys and girls (aged 1 to 8 years) in terms of hemoglobin, hematocrit, serum iron,transferritin or transferritin saturation levels—only ferritin was statistically different (higheramong girls than boys). Similarly, Nicklas et. al. (1998) found that in urban Haiti boys aged2 to 5 years had a higher prevalence of anemia (42 percent) than girls (36 percent), althoughthere was no statistical difference by gender in terms of ferritin or transferritin levels. Bycontrast, Schultink et. al. (1996) found no difference in anemia by gender for under 5s inurban Indonesia, although they did see a higher prevalence among schoolboys (9 percent)than schoolgirls (4.5 percent). In the latter case there was a reversal of differentiation duringadolescence such that women showed 10 times more prevalence of anemia than males. Awidening of the gap between males and females during adolescence and adulthood has alsobeen reported for Malaysia (Ismail 1989), India (Pushpamma et. al. 1982), Bangladesh(Bouis and Novenario-Reese 1997), and Nepal (Gittelsohn et. al. 1997).

By contrast, a large-scale survey by Tian et. al. (1996) of 15-64 year olds in Tianjin provinceof China showed no significant difference among adults by gender, and it has been arguedthat iron deficiency is not only a problem for women since it also has “a serious impact on…working men.” (IDRC 1998) Of course, information allowing comparison among adultmen, or between men and adult women, is scarce. However, Schultink et. al. (1996) did findthat the rate of anemia among elderly males in Jakarta was as high as among male schoolchildren (at 9 percent), compared with 13 percent for elderly women. In Nepal, Gittelsohnet. al. (1997) showed that even among adults consuming sufficient calories, 4 percent ofwomen and 2 percent of men were deficient in their consumption of iron. And in thePhilippines, Bouis et al. (1998) found that while all adult men (‘fathers’) exceededrecommended daily allowances for iron consumption, women (‘mothers’) did not.

But are ‘fathers’ and ‘mothers’ alike in all households? An important distinction amongadults relates to poverty. Fleming (1995) found a strong correlation between high serumferritin and hemoglobin levels and place of habitation; that is, adults in (wealthy)Johannesburg were much less likely to be iron deficient than those living in (poor) Soweto.The author suggests that anemia in Soweto may be linked more to diseases and otherenvironmental and socioeconomic deficiencies than to deficiency in iron intake. Similarly,Kirkwood et. al. (1996) found a lack of ponderal growth among malnourished childrenreceiving vitamin A supplements in Ghana. Thus, while child mortality rates may belowered by targeted supplementation, growth rates may not be affected if confounders (suchas poverty) are not simultaneously addressed.

Findings from many other countries also suggest the need for closer attention to the contextof iron (and other) deficiencies. For example, in Jakarta Schultink et. al. (1996) showed thatthe difference between iron intakes of mothers and fathers was smaller (although in favour ofmothers) than the difference between intakes of both parents in richer versus poor

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households. Indeed, the consumption of vitamin A and other micronutrients was lower foreveryone in poorest households than for everyone in wealthier households.

Elsewhere, Fawzi et. al. (1997) showed that children (boys or girls) in poorest households inSudan were twice as likely to consume low levels of carotenoid or preformed vitamin A thanchildren in wealthier households. And, in Indonesia de Pee et. al. (1999) found that womenand children with extremely low serum retinol concentrations did not seem to benefit fromincreased consumption of green leafy vegetables. That is, while the distribution curve forserum retinol shifted to the right for most women with a plant-derived intake of vitamin Aabove the median, this did not happen among the absolute poor. Following Fleming (1995)and Kirkwood et. al. (1996), de Pee et. al. (1999) suggest that poverty (linked to low hygieneand higher disease and parasitic loads), may be compromising carotene bioavailability.

Feedback loops among deficiencies and infections have been widely explored since Beaton et.al. (1993) and Tonascia (1993) documented the role of vitamin A deficiency in explaininginfant mortality. For example, significant links have been documented between vitamin Adeficiency and malnutrition in Cote d’Ivoire, India and Kiribati (Gopaldas et. al. 1993; WHO1995; Schaumberg et. al. 1996). Vitamin A deficiency increases the risk and impact of illness(affecting the severity of diarrhea, if not its prevalence), but certain infections such as malariaand measles can in turn impair vitamin A status (De Sole et. al. 1987; Barreto et. al. 1994;Bhandari et. al. 1994; West et. al. 1997; Hautvast et. al. 1998). Thus, infants with a history ofmalaria in the Congo were much more likely to have low levels of serum retinol comparedwith children less affected by malaria (Samba et. al. 1990). And in Turkey children withmeasles were more than twice as likely to have low serum retinol levels than those sick but notwith measles, and 10 times more than a healthy control group (WHO 1995).

Where iron is concerned, nutritional anemia is often linked to parasitic infestations. Forexample, in Tanzania the combination of ascariasis and iron deficiency was found to be linkedto low weight gain among children, while schistosomiasis was correlated with low heightgains (Stoltzfus et. al. 1997). Similar links have been found between malnutrition and lowserum magnesium levels (Singla et. al. 1998), imbalances between n-6 and n-3 fatty acids(Tichelaar et. al. 1994), vitamin E-related neurologic deficits (Kalra et. al. 1998), cataractdevelopment (Caufield et. al 1999), and low levels of bioavailable zinc (Sandstead 1991).

While the causal nature of such relationships is often uncertain, it is clear that macronutrientstatus, illness, and micronutrient deficiencies are inter-related and that the nature and severityof household poverty can determine the precise outcome. Furthermore, there is a special linkbetween poverty and local agroecological conditions where micronutrients are concerned.That is, the soils and water of some regions of developing countries are sometimes deficientin minerals and trace elements and that results in human deficiencies not easily remediedthrough public intervention because of low population densities, distance, and imperfectmarkets. Iodine provides a good example of this problem.

Girls are often more deficient in iodine than boys. But in all agroecologies?

According to Calloway (1995), iodine deficiency disorders have “different characteristics indifferent places, depending on the environmental iodine level.” That is, regions far from the

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sea (especially arid environments and mountain zones) tend to have low levels of iodine inthe soil, bedrock and groundwater that translate into human deficiencies if left untreated. Forexample, the total goiter rate in the lowlands of Lesotho was found to be 5.7 compared with28.0 in the mountains (Todd and Hoeane 1991).

Yet even in such regions it is believed that “females from adolescence onwards generallyhave a higher prevalence of goitre than males.” (WHO 1993) A number of studies supportthis generalization. For example, El-Sayed et. al. (1998) found that school-aged girls (aged 8to 18 years) in Upper Egypt were significantly more likely to develop goiter than boys,although living in a household with access to farmland of low iodine content represented ahigh risk factor that affected either gender and all ages. Similarly, the findings on 10 to 19year olds in Papua New Guinea by Simon et. al. (1987), Lemaire’s (1993) data on adults inLiberia, and Wolde-Gebriel’s (1992) analysis of Ethiopian data for 6 to 12 year olds allconfirm that females exhibit more iodine deficiencies than males.

Adolescent and adult women also appear to be more at risk of contracting Keshan disease (aselenium deficiency that may be associated with a lack of iodine), and Kashin-Beck disease(a combination of iodine and other deficiencies) (Ge and Yang 1993). These diseases havebeen mostly found in land-locked interior regions of China and other parts of Asia, although“the precise etiology of the gender bias is unknown.” (NEJM 1998) It has been shown thatthe biological retention rate of manganese can be significantly lower in adult women than inmen (Finley et. al. 1994), and that certain illnesses suppress the synthesis of thyroidhormones (with an impact on iodine status), and thyroid metabolism (linked to seleniumstatus) (Das et. al. 1996; Tanumihardjo et. al. 1996; Thurnham 1997). If women in suchregions are more prone to certain diseases than men, this may lead to a micronutrientdeficiency that triggers one of these little-studied medical problems. Too few studies havebeen carried out in different country contexts to examine whether Keshan and Kashin-Beckdiseases are limited to conditions mainly found in central Asia or whether women moregenerally carry a propensity towards thyroid-associated conditions.

There are some studies that suggest otherwise. De Hernandez (1994) found no significantdifference in iodine status by age or gender among Venezuelan children 6 months to 17years. A UNICEF (1992) survey in North Korea found a higher total goiter rate amongwomen than among men but the difference was insignificant. And although Oldham et. al.(1998) found a slightly higher urine-content iodine deficiency among pre-school girls inMorocco the difference was not significant. Nor was there any significant difference bygender in terms of goiter palpation. As a result Oldham et. al. (1998) conclude that“intrahousehold food distribution does not seem serious with respect to dietary iodineintake.” This does not mean that there is no problem; rather that iodine deficiency in thissample population was not associated with one gender or age group.

Interestingly, although universal coverage of iodized salt might help explain the last threefindings Venezuela, North Korea and Morocco do not have particularly high levels of iodizedsalt usage (UNICEF 1998a). What they do have, however, are long coast-lines and dietsheavy in fish and fish products (high in iodine), which is not true of Ethiopia, the desertregions of Upper Egypt, nor the interior of Papua New Guinea. In other words, agroecologyis a strong, but not perfect, predictor of iodine deficiency outcomes.

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This applies to micronutrients beyond iodine. For example, Nestel et. al. (1993) and Fawsiet. al (1997) found that individuals of either sex (but especially boys) living in semi-aridregions of Sudan were more at risk of vitamin A deficiency than people living near the Nileor in more humid locations, especially during the dry season. The reason is that intake ofmany micronutrients can fluctuate greatly between sufficiency and deficiency for the samepopulation. Swings in intake and bioconversion depend partly on the season (fewer fruitsand vegetables are available during dry seasons and many diseases have seasonal peaks,including malaria, gastro-enteritis and respiratory infections); and partly on the year--droughts and other supply or price shocks having a direct impact on consumption patterns(Santos et. al. 1983; Bloem et. al. 1989; Desai et. al. 1992). For example, Hardenbergh(1997) found that pre-school girls in Madagascar consume too little vitamin A in the dryseason but meet minimum requirements in the wet season. In north-east Brazil signs ofxerophthalmia absent during most of the year make a regular appearance during the inter-harvest “sertao” period (Santos et. al. 1983). Similarly, Foster et al. (1986) showed thatwhile surveillance data for Tabora region of Tanzania found no evidence of Bitot’s Spotamong 0 to 4 year-old girls in the Spring of 1985, a considerable problem had emerged thereby the Spring of 1986. In other words, micronutrient outcomes can be highly sensitive to thetiming of assessments.

Unfortunately, studies that explicitly deal with different micronutrient outcomes for differentage and gender categories in different agroecological contexts are few and far between.Much remains to be clarified regarding differential impacts of micronutrient interventions indifferent environmental settings. According to Kuhnlein (1992) insufficient attention hasbeen paid to the “ecological, economic, and cultural factors that influence the intake ofnatural food sources of [micronutrients].” And Gonzalez et al. (1994) and Musaiger (1996)argue that the agroecology of different regions is so different that researchers need to be“more sensitive to resultant variability in food customs among zones (as well as povertyamong zones) in order to understand variability in micronutrient outcomes.”

The term ‘food customs’ refers not only to local variation in dietary patterns but also tocultural and other biases that can affect deficiency outcomes along age, gender and statuslines. Which brings us to the issue of intrahousehold food distribution.

Discrimination

Discrimination is a common term in the intrahousehold literature referring to discriminatorybehaviour--negative biases in the ways in which food, income, health care and productiveassets are distributed within the household. Studies of the sharing of macronutrients, culturaltaboos and dietary belief systems have long confirmed that some individuals may consumefoods in quantity or quality that puts them at a disadvantage with respect to other householdmembers, or to global minimum standards (Carloni 1981; Rogers and Schlossman 1990).

However, patterns are complex. The world hosts great diversity in beliefs and rulesregarding food classifications (such as ‘hot’ versus ‘cold’), models of illness causation(resulting in age/sex taboos), and perceptions of the social and economic value of differenthousehold members (Dettwyler 1989; Gittelsohn et. al. 1997). In Guatemala, for instance,male household heads may consume adequate protein leaving other members with

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inadequate protein intake, while female heads of households may consume more caloriesthan other members (Engle and Nieves 1993). In Bangladesh, although female adults mayconsume poorer quality foods than men, girl children in those households may not suffer anysuch discrimination (Abdullah and Wheeler 1985). And in The Gambia children of juniorwives (most recently married) can be more malnourished than children of senior wives in thesame household (Webb 1989). In each case social status, conceptions of personal value, andlocal dietary practices can reflect favouritism or discrimination against selected groups ofpeople that produce nutritional side-effects.

There is also diversity in patterns of ‘culturally’ prescribed physical activity that influencenutrient requirements. For example Backstrand et. al. (1997) argue that although school girlsin Mexico consume significantly fewer calories and micronutrients than boys, their activitylevels are so much lower, due to “culturally patterned sex roles” that calculation of theirrequirements need to be adjusted downwards. This appears to be true of traditional Moslemcultures in which adolescent girls are secluded from the public after a certain age, while boysare still at liberty to roam and forage for snacks and other meal supplements (Musaiger1996). Other forms of ‘cultural’ patterns are important, such as the traditional ‘fostering’ outof young children in West Africa to extended family members, a practice which increases therisk of malnutrition among fostered children, especially girls, due to discrimination againstthe newcomer in terms of access to food and health care (Bledsoe et. al. 1988).

However, while protein, fats and calories have received considerable attention in theintrahousehold literature over the years, that does not hold for micronutrient aspects of fooddiscrimination. This is arguably because micronutrient consumption and deficiencies go“unnoticed for the most part” by most consumers (Bouis and Novenario-Reese 1997), andbecause until recently most food-based surveys focused on the macro energy content of foodssince this was the basis for international comparisons of malnutrition (Pinstrup-Andersen et.al. 1995).

As a result, biases have to be identified indirectly by considering how ‘preferred foods’,health care or supplementation goods are shared or withheld by those with authority in thehousheold. Even this is complicated: first, because the distribution of nutrients may be moreequal than the distribution of foods; second, because although the distribution of nutrientsmay be equitable (in terms of access to an equal share of food available), it may not meetphysiological requirements of each individual; and third, because of the diversity ofoutcomes across communities as a result of behavioural counfounders.

The last point remains important because the intrahousehold literature continues to drawheavily on early findings from South Asia that suggested widespread discrimination againstfemales of all ages. For example, India is widely cited as a country in which intra-familydistribution of food is “least fair” for girls and older women (Harriss 1986). Das Gupta(1995) has argued that women “over much of Asia…are nutritionally deprived over most oftheir lives.” And Messer (1997) comments that “even where females [in Asia] apparently aremeeting or exceeding minimal recommended intakes for energy, they may be at risk formicronutrient malnutrition, as apparently adequate intakes of staple foods may maskrestricted access to relatively more expensive animal foods, fruits and treats of highernutrient density.”

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However, recent re-evaluations of older data (combined with new empirical studies) suggestthat although maternal and female child mortality rates are indeed too high across much ofthe region there are huge variations in patterns of discrimination that make generalizationsuntenable, even for India (Filmer, King, and Pritchett 1998). For example, Walker’s (1987)analysis of longitudinal panel data from central India showed “no significant differencebetween boys and girls in the intake of 10 nutrients.” Subbarao (1989) noted that “systematicevidence on gender discrimination in food and nutrient intake [in India] is hard to come by.While there is some evidence of sex bias in intrafamily distribution of food, the evidence isby no means conclusive.” And Basu’s (1993) work showed that ”we have no reason tobelieve that girls…invariably get an unfair deal in the matter of nutrition, even in those areaswhere sex differentials in child mortality are the most acute.” In a single region of IndiaBasu (1986) found that one group of people (the Lepchas) apparently favoured of females;another (the Sherpas) showed mixed tendencies; a third (the Oraons) displayed nodiscrimination by gender at all; while the ‘high status’ Mahishyas seemed to discriminateagainst women, and lower status Mahishyas showed no consistent bias either way.

Similar findings were reported by Levinson (1974) from the Punjab of India. Althoughnoting that “the greater premium placed on sons than on daughters clearly results in majordifferentials in their care and upbringing,” serious male-female differentials in nutritionaloutcomes only occurred at the lower end of the income spectrum. Where resource and timeconstraints are less serious girls are adequately fed (in terms of intake), although male-femaledifferences in the quality of care remain.

Evidence from outside of India tells a similar story. In Peru, both Leonard (1991) andGraham (1997) report no discrimination in energy intake or growth among infants andpreschoolers in southern regions, but Larme (1997) in northern Peru sees “a pattern ofdiscrimination against females and younger children, especially infants under age one.”A review of intrahousehold food allocation also found little evidence of consistent,generalized discrimination against young children of either sex . Similarly, multi-countryreviews of studies from the 1980s by Millman and deRose (1997) and Miller (1997) found nouniversal patterns of bias. Indeed, according to Millman and deRose (1997), “femalechildren do not consistently have poorer growth than male children even in India. Adultwomen actually have better diets than adult men, except when lactating or pregnant.”

This is not to suggest that nutrient-based discrimination does not negatively impact the livesof millions of individuals. Certain culturally proscribed taboos can have perverse effects,such as the prohibition in parts of Africa against the consumption by pregnant women ofchicken or eggs (O’Laughlin 1974; Johns et. al. 1992). For example, the pattern of platesharing in Nepal (which children and adults share food together) is significantly correlatedwith vitamin A deficiency (Shankar et. al. 1998). Similarly in Orissa (India), the ‘deposedchild’ phenomenon (abruptly weaning when a subsequent pregnancy is recognized) has longbeen linked to subsequent xerophthalmia (McLaren and Frigg 1997).

However, the converse can be true where pro-male bias results in a positive outcome forfemales. For example, Bouis and Novenario-Reese (1997) found that there was favoritismtowards pre-school boys and adult men in Bangladesh in the distribution of preferred foods,such as meat, and eggs. However, rice, fish and potatoes were found to be more or lessequally distributed in the household (although adolescent girls were favoured with pulses and

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milk). The only food consumed more by adult women than men were green, leafyvegetables—a low-status food that nevertheless allowed women to meet much of their dailyiron intake needs in a context where other iron sources were very expensive.

In other words, poverty and the social ‘status’ of households may be a key determinant of so-called ‘cultural’ bias. Which raises the question of what public action can or cannot beexpected to achieve in addressing micronutrient deficiencies associated with apparentlybiased resource allocation in the household. As Bouis et. al. (1998) put it, “supplementationmay be the best short-term solution to [low iron intake] in that rich sources of iron in the dietare expensive, and nutrition education cannot solve the problem if women cannot afford tobuy the iron-rich food recommended.” But, can we be sure that targeted supplements orfortified foods are accessible to all those who most need assistance? And can we be sure thatconfounding factors will not cancel out potential benefits for those individuals?

Implications for Public Action

It could be argued that detailed attention to the complexities of intrahousehold nutrientdistribution sets too high a standard for public intervention. Many policymakers andpoliticians are already wary of ‘intruding’ into the realm of household decision-making(Agarwal 1997). Analysts lack agreement on the feasibility of modeling (and theninfluencing) the dynamic interactions that characterize intrahousehold relations (Fafchamps1998). And many field professionals doubt the feasibility of effectively targeting only achosen few individuals within otherwise commonly poor households (Haddad et. al. 1997;Jaspars and Shoham 1999).

Yet, there are two important aspects of the micronutrient problem which suggest thatattention to intrahousehold dimensions is no luxury. The first, already raised in the contextof iodine deficiencies, is that the prevalence of certain diseases and individual responses topublic action can be differentiated by gender. For example, Cobra et. al. (1997) found thatiodine supplementation had a greater effect on reducing male infant mortality in West Javathan for mortality among girls. A study by Sazawal et. al. (1997) in India found that zincsupplementation reduced the prevalence of diarrhea among pre-school boys by 35 percentcompared with a fall of only 19 percent among girls. Although Ninh et. al. (1996) found nogender difference in growth responses to zinc supplementation in Vietnam where deficiencywas severe, the authors did note that where the deficiency was mild “increases in growthhave usually been greater in boys than in girls.” Layrisse et. al. (1996) studied the effects ofiron fortification on anemia among children and adolescents in Venezuela and found asignificantly lower positive response among 15 year-old girls compared with boys of thesame age, and compared with younger girls. And the vitamin A supplementation trials inIndonesia examined by West et. al. (1988) found significant growth responses in treatmentvillages (versus control villages), but only for non-infant males.

Once again such male-female differentials cannot be generalized. No significant differencewas found between boys and girls in response to zinc supplementation, for instance (Bentleyet al. 1997). No gender difference in growth response was found in response to vitamin Asupplementation in countries as diverse as Brazil, South Africa, Indonesia and Ghana(Marinho et. al. 1991; Willamsen et. al. 1997; West et. al. 1988; Kirkwood et al. 1996).

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What is more, in their meta-analysis of vitamin A trials on mortality Beaton et. al. (1993)showed that, “gender did not affect the relative effectiveness of vitamin A administration.That is, the relative effect of vitamin A supplementation in reducing childhood mortality isvirtually the same in girls and boys.”

Thus, while there is evidence to suggest that responses to programme interventions maydiffer by gender, and possibly age, the empirical basis for defining and predicting suchresponse differentials is lacking. Most studies that do show girl-boy variability in outcomesderive from Asia, and most are tied to studies of supplementation trials. More needs to beknown about age/gender responses, a) to other forms of intervention (including access tofortified foods, home-grown vegetables, nutrition education), b) in countries outside of Asia,and c) in association with contextual information allowing for better interpretation of clinicalfindings. The last requires attention to social, cultural and behavioural dimensions of foodaccess, distribution and consumption, as well as non-food parameters linked to health anddevelopmental care. Which raises the problem of behavioural change--the second publicintervention issue with intrahousehold dimensions.

It has long been documented that while targeted public action can be successful in reducingnutritional deficiencies to a given level, it is more difficult to maintain that level withoutappropriate adjustments in local knowledge, perceptions and behaviour (Ghassemi 1992;Engle et. al. 1996; Rogers et. al. 1999). That is, incentive systems typically need to bestructurally modified. For example, in Nepal it was found that despite the regular supply of afull food ration to long-term camp-based refugees, beriberi (thiamin deficiency) emerged as awidespread problem in the mid-1990s (Upadhyay 1998). Elderly patients responded tothiamin injections, but the incidence did not fall dramatically until there was a relaxation onthe sale of ration goods (for preferred food items in local markets), and nutrition educationsuccessfully encouraged the consumption of parboiled rice (thiamin rich) instead of polishedrice (thiamin poor). “Now, most of the refugees consume parboiled rice…and there havebeen no reported cases since then.”(Upadhyay 1998)

The work of Chevalier et. al. (1998) is also relevant in this regard. A study of the immunestatus of malnourished children in Bolivia (based on weekly ultrasonography of the thymus)showed that it took at least two months for previously malnourished children to reach fullimmunologic recovery. That requires adequate recovery of micronutrient status and allphysiological functions. Yet, most children were discharged from nutrition rehabilitationcentres after only one month at which time they had reached 90 percent of median referenceweight-for-height but their immunologic systems were still depressed. The lack of change intheir home context in the meantime meant that recovered children returned to the samedisease, care and food allocation environment that they inhabited previously. According toChevalier et. al. (1998), “frequent relapses” among such children are due to the incompleteimmunologic recovery, which goes beyond meeting minimum anthropometric standards. Asnoted above, micronutrient and health status together play an important role in determiningrecovery and growth. According to Dimitrov et. al. (1998), “intra- and interindividualvariations in bioavailability of micronutrients should be considered when human studiesare…evaluated. The interaction of endogenously circulating micronutrient withsupplemental micronutrients must be part of the clinical evaluation of bioavailability.”

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Such examples imply that public action needs to be better informed by studies that addressthe complexity of nutrition-health-poverty interactions. More micronutrient studies need toconsider the synergies among nutrients, diseases and other confounders that operate at theintrahousehold level. Success in addressing only one (clinical) aspect of the problem may inthe longer run mean that benefits are not sustainable. For example, Rice et. al. (1999)considered the effects of maternal postpartum vitamin A or ß-carotene supplementation onserum retinol concentrations among on mothers and their infants in Bangladesh. Comparedwith a control group, the mothers receiving supplements did have higher concentrations ofvitamin A in their breast milk at 3 months, but the improvements were not sustained. Theauthors conclude that while both interventions were beneficial in the short-term, neither wassufficient to correct underlying subclinical vitamin A deficiency among the mothers nor tobring their infants into adequate vitamin A status. The most likely reason was that despitetargeted supplements, regular intake of dietary vitamin A-rich foods remained unchanged at avery low level. The conclusion for Rice et. al. (1999) is that “supplementation programsalone cannot solve the problem of vitamin A deficiency.”

Similarly, Rosado’s (1999) study in Mexico showed that 82 percent of sampled children weredeficient in at least 2 out of 5 micronutrients under consideration. Yet, despite 12 months ofsupplementation of one or more micronutrients there was little difference in growth betweentreatment and control groups. This suggests that “in populations with multiple micronutrientdeficiencies, the effect on linear growth of supplementation with single nutrients will not besignificant.” The same was reported by Thu et. al. (1999) from their study in Vietnam;namely that daily and weekly supplementation did improve benchmark levels of hemoglobinzinc and retinol, but limited effect was found in terms of height growth rate among stuntedchildren. More recent findings are also mixed. Multiple micronutrient supplements havecaused some growth improvement among infants (<12 months) in Mexico, but no impactwas shown on growth in Peru (Penny et. al. 1997) or Guatemala (Brown et. al. 2000).According to Allen and Gillespie (2001), additional trials are needed “to confirm whethermultiple micronutrients improve child nutritional status, health and development more thansingle micronutrients.”

Conclusions

Three main conclusions stand out from this review. First, important differences do exist inprevalence rates for various micronutrient deficiencies by age and gender, but these cannotbe generalized. The undifferentiated aggregation of people into broad categories of‘children’ or ‘fathers’ obscures wide variation in conditions as individuals proceed throughthe life cycle in different socioeconomic, cultural, agroecological contexts. Studies ofchildren aged 6 months to 4 years may draw misleading conclusions where deficiencies aregreater among 6 to 10 year-olds. Research that aggregates data for males and females aremore likely than not to miss important gender-specific differentials in risk factors anddeficiency manifestations. And, a narrow focus on infants and pregnant/lactating womenrisks ignoring considerable problems among school-aged girls, adolescents, non-pregnantwomen and the elderly. Infants and mothers are sometimes most at risk, but not only themand not always them.

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These findings do not suggest that widely-held generalizations are completely wrong; ratherthat they cannot be held as universally true. Whether considering vitamin A, iron or otherdeficiencies one age or gender may face more deficiencies than others in some places andtimes but not in others. More attention to the context-specific nature of deficiencies is calledfor as a first step towards more reliable prevalence estimations and a more rational basis fortargeting public action. This implies a need for greater efforts toward linking quantitativeinformation with qualitative insights about the dynamics of social and economic interactionthat affect clinical outcomes.

Second, to achieve greater reliability in problem analyses requires more attention toassessment methods and analytical approaches. This implies rigourous comparative studiesand sensitivity analysis of alternative deficiency identification techniques. A critique isneeded of the co-linearity, substitutability or exclusivity of the many clinical, biochemical,anthropological and food recall indicators now in use. Future meta analyses of large datasetsrequire such understanding to be able to scale up the relevance of their findings. What ismore, research protocols need to pay more attention to the multiple interaction amongnumerous micronutrients, diseases, health history and life cycle context that affect thebiochemical markers of a single micronutrient deficiency. That is, while research on a singlenutrient problem adds some depth to our knowledge, the operational utility of such findingsis often compromised by a lack of understanding of relationships to other (often directlyrelated) deficiencies or health concerns.

Third, if multiple deficiencies are inter-related so too must be the solutions. Operationalagencies are often noted for their expertise in tackling one specific micronutrient problem oranother. This engenders a one-at-a-time approach that may achieve definable results in theshort-term but leave much to be desired in the longer run. If micronutrient interventions areto benefit all individuals at risk (not just those most at risk during one period of the lifecycle), deficiencies must be addressed as a mainstream development problem rather than aspecialist niche within the nutrition community. The effectiveness of any interventiondepends on more than a simple interaction between a deficiency and a supplement.Combinations of actions are often required at various levels to achieve a net benefit.

Similar conclusions have long been drawn in relation to many macronutrient interventions,including targeted food aid, coupon programmes and supplementary feeding (Pinstrup-Andersen et. al. 1995; Rogers et. al. 1999; Levinson and McLachlan 1999). One targetedfood, income or information transfer may be ineffective without additional complementaryinputs. Micronutrient deficiencies are not a different order of problem. The sustainability ofactions aimed at resolving and preventing micronutrient problems typically depends on themodification of contextual factors by the stakeholders themselves. If discrimination inaccess to certain foods or health benefits lies at the root of a given micronutrient deficiency,universal fortification of selected food items will have a limited impact on the problem.Thus, removing economic constraints, enhancing local capacities for responding toincentives, and encouraging enhanced care behaviour for all individuals are longer-lastinggoals. Enabling such changes requires a greater understanding among policymakers andproject designers of the daily tradeoffs that are made in access to food, income, care andother resources, including micronutrients, at the intrahousehold level.

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Appendix 1(a)—Studies that do report intrahousehold variability in micronutrient deficiencies Geographic SurveyLocation Study Sample size/type Methods 1 Findings2

Asia

Nepal Shankar 162 households with FFQs (weekly), More xerophtalmia in girls 3-4y(rural) et. al. (1996); 1-6-year child; village Clinical than boys, but not for other age

and (1998) case-control study cohorts (1996) —stat. sig. not reported. Child(either sex) eating with manmore risk of VADD.

Nepal Gittelsohn 767 adults and children WF, FFQ, Adult women more deficient in(rural) (1991) in 115 households (in 6 Qualitative. carotene intake and vit. C. No sig.

villages) diff. by child gender.

Nepal Gittelsohn 105 households, adults 24HR, FFQ Male sex and age best predictors(rural) et. al. (1997) and children. Village- Qualitative of carotene, vit. C and iron intake.

based case-control Adult women most deficicient butage bias differs by nutrient.

Nepal Ohno et. al. 245 people 10-72y 24HR, Overall females all ages sig,. lower(rural) (1998) in two villages. Biochemical serum iron than males. In one village

Stratified random. Women also sig. lower niacin, in theother women lower calcium.

Indonesia Schultink et. 1 child (2-5y) plus 24HR, 3DR, Poor women and men inadequate(urban) al. (1996) parents in 40 WF intake vit. A and iron compared with

households. richer adults. Adolescent girls 10 timeshigher prevalence anemia than boys.

Indonesia Muhilal et. 18,508 children <6y Clinical Bitot’s spot sig. more in boys(rural) al. (1994) in 15 provinces (twice the prevalence as girls).

Same for night-blindness.

India Kapil et. 1,277 adults 24HR Zinc intake 70% of RDA for men(rural) al (1998) and only 50% of RDA for

women (non preg./non-lac.). But,iron intake much lower for women.

India Levinson 496 children 6-24m 24HR Girls lower intake vit A than boys(rural) (1974) regardless of caste, but higher caste

girls better iron intake than othergirls, or high caste boys.

India MHRD Varying state-level Clinical Prevalence Bitot’s spot varies by(rural/urban) (1996a, 1996b) sample sizes (for 10 states) gender and state. But corneal xerosis

all ages combined mostly hjgher in boys in all states.

India Pushpamma 1,435 members of WF, ANT Adolescent and adult women sig.(rural) et. al. (1982) 280 households lower intake iron. No sig. diff by

age/sex for vit.A, vit.C. or calcium.

1 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.2 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.

33

Appendix 1(b)—Studies that report intrahousehold variability in micronutrient deficiencies Geographic SurveyLocation Study Sample size/type Methods 4 Findings5

Asia (continued)

Thailand Bloem et. al. 1,772 children 1-8y, ANT, clinical. Girls (1-8y) sig. better retinol,(rural, urban) (1989a) of which 863 full biochemical retinol-binding protein and

biochemical data. ferritin than boys of same age.

China Tian et. al. 3,652 adults 15-64y, 3DR, WF Rural women lower intake of 14(rural, urban) (1996) representative, 24HR micronutrients than men, and

stratified random lower than urban women.

Philippines Klemm et. al. 11,378 children, ANT, clinical, Mild xerophthalmia highest(rural) (1993) 6-83m, random. FFQ. among boys in 4-6y cohort.

Philippines Chula et. al. Children 3-6y in WF Boys above RDA most nutrients,(rural) (1980) 58 households no sig. diff. in sibling order.

Kiribati Schaumberg 1,428 0-6y children Clinical, FFQ Boys, post-weaning, sig.(national) et. al. (1996) (case-control) higher rates of xerophthalmia.

Kiribati Danks et. al. 150 0-7y children Clinical Boys sig. higher Bitot’s spot(rural) (1992) from 3 villages and night-blindness.

Bangladesh Bouis et. al. Children and adults WF, 24HR Male adequacy of iron, vit. A(rural) (1997) from 590 households and vit C higher than women.

Boys/ girls 13-18y least adequacy.

Bangladesh Hussain and 248 children 2-15y, Clinincal, FFQ Serum retinol sig. lower for girls.(urban, rural) Kvale (1996) case-control biochemical Ages 4-6y worst for both sexes.

Bangladesh Stanton et. al. Children 0-14y in FFQ, clinical Boys, of older cohorts (6y(urban) (1986) case-control study versus 3y) sig. more xerophtalmia.

Pakistan Lindblad et. Infants 0-6m and Clinical, Women (pregnt. and non-(urban) al. (1998) adults biochemical prentg.) sig. lower serum retinol

than men. No sig. diff. for infants.

Malaysia Ismail (1989) Children 4-13y and 3DR, weighed Women (20-59y) lower vit.A(rural, urban) adults 14-59y food intake than men, few sig. diffs

13-19y by sex for iron, calcium.

Vietnam Giay et. al. 23,782 children 0-59m Clinical Boys generally, sometimes sig.,(national) (1988) worse than girls in night

blindness, Bitot’s spot, total rate.

Papua New Simon et. al. Adolescents aged 10-19y Clinical Female prevalence goiter (totalGuinea (rural) (1990) Sample size no specified rate) double that of men.

4 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.5 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.

34

Appendix 1(c)—Studies that do report intrahousehold variability in micronutrient deficiencies Geographic SurveyLocation Study Sample size/type Methods 1 Findings2

Asia (continued)

Micronesia Lloyd-Puryear 448 children 3-7y Clinical Boys twice rate Bitot’s spot, and(national) et. al. (1991) higher night-blindness, versus girls.

West Asia/North AfricaSaudi Arabia Tolba et. al. 105 neonates randomly Biochemical Boys neonates sig. lower cord(urban) (1998) selected in hospital plasma levels of vit. A than girls.

Yemen Rosen et. al. 2438 children 12-60m, Boys sig. more nightblindness and(rural) (1996) stratified cluster sample Clinical Bitot’s spot than girls. All children 4-

5y sig. more at risk than <4y.

Egypt El-Sayed et. 6,750 children 8-18y, Clinical, Girls sig. more goitre (iodine(rural) al. (1998) 2-stage cluster sample biochemical deficiency) than boys).

Morocco MSP (1995) 1,094 adults over 18y. Biochemical Pregnant women >4 times more(national) (National sample survey) likely to be anemic than adult men

Sub-Saharan AfricaSouth Africa Badenhorst 296 children, 6-14y. 24HR, ANT, Girls 6-10y higher intake than boys(rural) et. al. (1993) Random sample in Clinical, vitamin A, C, Ca, K and sugar.

Elementary schools. Biochemical. No diff. in iron. But, girls 11-14ylower intake vit. A, B12, and C. SDsoften greater for younger cohorts.

South Africa Tichelaar et. 296 children, 6-14y. Biochemical Diet imbalance of n-3/n-6 fatty(rural) al. (1994) Random from clinics acids seems linked to malnutrition.

Boys 7-12y higher imbalance.

Madagascar Hardenbergh 619 children 0-17y ANT, 24HR, Girls aged 6y lower vit A. in dry(rural) (1997) plus adults, random. WF season (but not iron or girls 7-9y)

In wet season girls also lower butintake meets RDA. Girls and boys10-17y all deficient in iron.

Ethiopia Tafesse et. 147 children 6-72m, Clinical, Serum retinol deficiency and Bitot’s(rural) al. (1996) Arssi province biochemical spot sig. higher for boys than girls

Ethiopia Wolde-Gebriel 6,636 children aged Clinical, ANT, No sig. diff. by age or sex in serum(rural) et. al. (1991) 6-72m, stratified biochemical retinol values, but boys >12m sig.

sample by agroecology higher Bitot’s spot and xerosis.

Ethiopia Wolde-Gebriel 35, 635 national Clinical Girls/women higher iodine deficiency.(national) et. al. (1992) survey from 1980/81 Diff. increases with age from 6y on.

1 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.2 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.

35

Appendix 1 (d)—Studies that do report intrahousehold variability in micronutrient deficiencies Geographic SurveyLocation Study Sample size/type Methods1 Findings2

Sub-Saharan Africa (continued)Ethiopia De Sole et. al. 2,647 children 6-72m, Clinical, Bitot’s spot sig. higher in boys(urban/rural) (1987) cluster, case-control biochemical than in girls (p=0.03).

Tanzania Tanner and All inhabitants of 32 FFQ, 24HR, Iron sig. low among infants of(rural) Lukmanji (1987) households. WF both sexes, but girls 10-16y and

women sig. less than boys/men.

Sudan Nestel et. al. 29,615 children 6-72m Clinical, ANT Risk of xerophthalmia sig. higher(rural) (1993) in 5 districts of Khartoum FFQ for boys than girls, and increased

and Gezira provinces with age and poverty.

Liberia Lemaire (1993) 1,707 adults (more than Clinical Females three times higher goiter(rural) half women) prevalence than men (all greades)

Latin AmericaVenezuela Layrisse et. al. >1,200 (in 3 rounds) Biochemical Girls aged 11y sig. more iron(national) (1996) Random samples from deficient than boys. Girls >15y

schools, clinics, homes. generally more deficient.

Mexico Backstrand 91 school children ANT, 24HR, School-age girls sig. lower(urban) et. al. (1997) (in CRSP study) weighing intake of vitamins E, B6 and

iron, zinc, thiamine, niacin.

Chile Ruz et. al. 98 children in day-care Biochemical Boys in zinc supplmtn. group sig.(urban) (1997) centres, 27-50m old. higher growth than placebo group,

Double-blind supplmtn. but no effect for girls in either group.

Chile Muzzo 1,015 children 6-18y in Clinical Girls twice the rate of iodine(rural/urban) (1986) Santiago-Temuco deficiency than boys.

Peru Imai et. al. 91 adults aged >19y 7DR, Women 25-50 sig. higher risk of (rural) (1997) and 100 children biochemical selenium deficiency in terms of

%RDA by bodyweight. Only girls7-10 closer to RDA than boys.

Industrialised CountriesCanada Wolever et. 700 people >9y from 24HR, WF Women sig. lower iron, niacin, and(urban) al. (1997) Ojibwa-Cree tribe Biochemical folate intake than men.

UK Nelson (1986) 343 people all ages in 79 7 DR, WF Women >18y sig. lower calcium, retinol(urban) households in Cambridge carotene and vit.C. versus male head

of household. No sig. diff iron.

USA Finley et. al. 40 adult men/women, Biochemical Absoprtion manganese sig. higher(urban) (1994) case study in women, but half-life longer for men.

1 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.2 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.

36

Appendix 2 (a)—Studies not showing significant intrahousehold variability in micronutrient deficiencies Geographic SurveyLocation Study Sample size/type Methods 1 Findings2

Meta-analysisNepal, Zambia Katz et. al. 30,000 children 0-6y Clinical Boys higher risk ofMalawi, (1993) from 4 independent xerophthalmia than girlsIndonesia studies overall, but not sig. diff.

AsiaChina Zhang et. al. 6,500 adults 35-64y Biochemical No diff. by sex for zinc(rural, urban) (1996) in 65 communes status.

Philippines Bouis, et. al.c. 4,000 children and 24HR, ANT, No sig. diff in intake of(rural) (1998) adults qualitative micronutrients/minerals by age or

sex (not controlling for requirements)

India Behrman 800 children 0-15y 24HR No sig. diff. (boys/girls) in intake(rural) (1988) from VLS studies carotene, vit. C, calcium, riboflavin

even adjusting for requirements.

Nepal Upadhay et. National random Clinical Higher prevalence of Bitot’s spot(rural) al. (1981/85) sample, children 0-14y. for boys, but not statistically sig.

Pakistan NIH (1988) 10,406 children under Clinical No difference in prevalence of(national) 5y. Bitot’s spot by gender of child.

Thailand Bloem et. al. 127 children 1-3y in Biochemical No sig. diff. in mean level or SD.(rural,urban) (1989b) Sakon Nakhon province for serum retinol, (except for ages 3 to

6 when boys had lower level).

West Asia/ North AfricaMorocco Oldham et. al. 197 children from 110 Biochemical, No sig. diff by sex of(rural) (1998) hhs in 19 villages clinical child for urinary iodine status.

(random sample)

Morocco GoM (1998) 1,453 children 6-72m, ANT, clinical No sig. diff. in clinical(rural/urban) stratified random biochemical, or serum retinol levels

FFQ by sex of child.

Oman GoO (1995) 759 children 0-6m Clinical No diff. in mean levels of serum(national) retinol by gender, or in SDs.

Djibouti Resnikoff 114 children 4-10y Biochemical No diff. in serum retinol level (<0.70(rural/urban) (1988) umol/l) by gender in urban areas

(but higher prev. for rural girls than boys )

1 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.2 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.

37

Appendix 2 (b)—Studies not showing significant intrahousehold variability in micronutrient deficiencies

Geographic SurveyLocation Study Sample size/type Methods 1 Findings2

Sub-Saharan Africa

South Africa Willumsen et. 57 children Biochemical No sig. diff. vit. A by gender (rural) al. (1997) (hospitalized due to kerosene poisoning)

Cameroon Wilson et. 5,352 children 0-5y Clinical, No sig. diff. by age or sex in(rural) al. (1996) multi-stage cluster FFQ vit.A status, but all worst in

sample remote mountain ecology.

Malawi Tielsch et. al. 5,436 children <6y. Clinical Bitot’s spot higher for boys(rural) (1986) Lower Shire Valley. than girls but not stat. sig.

Malawi GoMi (1986) 5,436 children <6y. Clinical No sig. diff. by gender for(rural) Lower Shire Valley night-blindness or corneal scars.

Ethiopia Wolde-Gebriel 739 children 6-72m Biochemical No difference in mean serum(national) (1992) (national survey from retinol levels by gender for

1981/82) overall sample.

Zambia Luo and Mwela 900 mothers and 900 Biochemical No significant difference in(national) (1999) children (<5 year) serum retinol values by age or

attending polio clinics gender of children

Latin America

Venezuela de Hernandez 814 children 6m to Biochemical No sig. Diff. in serum retinol or(national) (1994) 17 years old (from iodine by gender or age cohorts

1981/82 national survey)

Guatemala Ribaya-Mercado 26 elderly (>60y) Clinical, No sig. gender diff. in(peri-urban) et. al. (1999) Biochemical body, liver or rerum retinol.

Peru Leonard 101 adults and children ANT, FFQ, No sex diff. in child(rural) (1991a,b) from 26 households. WF micronutrient intakes.

Chile Castillo-Druan. 32 infants 0-24m Biochemical No sig. diff. by sex in(urban) et. al. (1987) response to zinc supplmtn.

Brazil Sichieri et. 142 children 6-12y, 24HR, Iron and vit.C status low(rural) al. (1996) random in poor schools biochemical for both sexes but at sample

median no dig. diff. by gender.

Haiti Nicklas et.. 305 children 2-5y, Biochemical 40% of children low(urban) al. (1998) of low income groups low serum ferritin level,

but no sig. diff. by sex.

1 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.2 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.

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Appendix 3—Selected studies that could be re-analyzed through age and gender disaggregation Geographic SurveyLocation Study Sample size/type Methods 1 Findings2

Meta-analysis

WHO/CHD 9,424 mother-infant Bichemical, Impact of vit A. dosing with(1997) pairs from Ghana, ANT immunization. focus on age and

India and Peru. gender cohorts outcomes possible.Asia

India Kalra et. al. 100 case children Biochemical, Compared serum alpha-tocopherol (urban) (1998) 3-8 years (from health levels and neurological signs with

centers), and 50 matched PEM. Vitamin E-PEM interactioncontrols from clinics) by gender possible.

Pakistan Northrop-Clewes 191 breast-fed infants. Biochemical Iron and carotene data for iron

(rural) et. al. (1996) Case-control supplemented/ placebo groups.

Sri Lanka Cox et. al. 182 pre-schoolers, WF Vit. A, zinc, niacin, calcium.(urban) (1993) in nursery schools

Thailand Egger et. al. 108 children 3-8y 24HR Calcium, iron vitamin A,(rural/urban) (1991) riboflavin, thiamin, niacin.

Sub-Saharan AfricaZambia Hautvast 210 children 6-20m ANT, 24HR Serum retinol data available(rural) et. al. (1998) at MCH clinics biochemical

Kenya Kennedy et. 1,677 children 0-72m, FFQ, 3DR, Vitamin A consumption by(rural) al. (1993) stratified random 24HR, gender of child and of

qualitative household head possible.

Nigeria Erinoso et. 30 children, selected Food weighing Intakes of iron, vit.C, calcium(rural) al. (1991) method niacin possible by sex.

Gran Canaria Gonzalez et. 264 children 2-8, FFQ iron, calcium, vitamins possible(urban) al. (1999) from primary care centres.

Latin AmericaBrazil Santos et. al. 10,922 children, 0-12 y, Clinical Finds large geographic variation (rural) (1983) from 6 localities in VAD (semi-arid regions worst)

but no analysis by sex.

Mexico Allen at al. 197 pre-school and ANT, FFQ zinc, calcium, iron, serum retinol(urban) (1992) school children biochemical all low by aggregated by “child”

Jamaica Gardner et. 85 children 6-24m, ANT, clinical Age-sex stratification of zinc(urban) al. (1988) selected from clinics, outcomes possible.

Guatemala King et. al. 164 elderly men and ANT, Blood serum retinol levels by sex(rural) (1997) women biochemical possible.

1 FFQ = Food frequency questionnaire. 3DR = Three-day dietary recall questionnaire. 24HR = 24-hour recall of foodsconsumed. WF = Weighed Foods Methods. ANT= Anthropometry. Biochemical = laboratory analyses (blood, serum,etc.). Qualitative = direct observation and other qualitative techniques.2 Abbreviations: ‘Diff.’ = difference; ‘Stat.’ = statistical’; ‘sig.’ = significant; ‘SD’ = Standard Deviation.