ORIGINAL PAPER

Relating dietary diversity and food variety scores to vegetableproduction and socio-economic status of womenin rural Tanzania

Gudrun B. Keding & John M. Msuya &

Brigitte L. Maass & Michael B. Krawinkel

Received: 3 May 2011 /Accepted: 25 December 2011# Springer Science+Business Media B.V. & International Society for Plant Pathology 2012

Abstract The objective of the present study was to measurediversity in nutrition with dietary scores, and to assess theirrelationship to vegetable production and the socio-economicstatus of women in rural Tanzania. A dietary diversity score(DDS) and a food variety score (FVS) were created from datagathered with three semi-quantitative 24-h recalls performedduring three non-consecutive seasons during 2006/2007. Dataon vegetable production, selling and buying and socio-economic data was gathered with a semi-quantitative ques-tionnaire. A total of 252 randomly selected women from threedistricts of north-eastern and central Tanzania participated.The median DDS of 6 and the mean FVS of 8.3 were low,suggesting an overall poor dietary quality, with about onethird of participants having an alarmingly low DDS of onlytwo to four food groups per day. These women consumed avery basic diet consisting mainly of cereals and vegetables.Differences among districts were pronounced while thoseamong seasons were less distinct. The DDS and FVS wereboth significantly associated with ethnicity, occupation and

status within the household of participants. As a more varieddiet is not necessarily healthier, integration of both quantityand quality in the scores is proposed for future studies. Thiscan be achieved, for example, by weighing food types accord-ing to their importance in the diet. As both scores are linked tothe production, selling and buying of vegetables, the promo-tion of homestead food production may be a good way toimprove dietary diversity.

Keywords Dietary diversity score . Food variety score .

Rural Tanzania . Traditional vegetables

Introduction

Nutrition security addresses not only the availability of andaccess to food but also its utilisation. Therefore, one importantunderlying factor of nutritional security is a certain degree ofdiversity in the available food with its macro- and micronu-trients (Bouis and Hunt 1999; Hoddinott and Yohannes 2002;Steyn et al. 2006). While the causes of malnutrition arecomplex, a leading cause is suggested to be a general simpli-fication of diets and its associated low nutrient intake; in short,reduced diversity may lead to a decline in nutrition quality.

Homestead food production, e.g. in home gardens, willhave a direct and positive impact on dietary diversity and,consequently, the dietary quality of the homestead occu-pants (Olney et al. 2009). This has been shown, for example,by the homestead food production program introduced byHelen Keller International in Bangladesh about two decadesago in which the increase in production and consumption ofdiverse micronutrient rich foods played a major role (Iannottiet al. 2009). Besides this, little effort has been made to useagricultural programs to improve human nutrition. Only re-cently a first international conference has highlighted the

G. B. Keding (*) :M. B. KrawinkelJustus-Liebig-Universität Giessen,Institute of Nutritional Sciences – International Nutrition,Wilhelmstrasse 20,35392 Giessen, Germanye-mail: gudrun.keding@ernaehrung.uni-giessen.de

G. B. Kedinge-mail: g.keding@cgiar.org

J. M. MsuyaDepartment of Food Science & Technology,Sokoine University of Agriculture (SUA),P.O.Box 3006, Morogoro, Tanzania

B. L. MaassInternational Center for Tropical Agriculture (CIAT),P.O. Box 30677-00100, Nairobi, Kenya

Food Sec.DOI 10.1007/s12571-011-0163-y

importance of leveraging agriculture for improving nu-trition and health, suggesting that so far there is littleconcrete evidence on how agriculture-nutrition linkageswork (IFPRI 2011). Consequently, the present studyinvestigates associations between human nutrition andvegetable production, in which the term ‘production’includes both vegetable cultivation in gardens/fieldsand vegetable collection from the wild.

Dietary diversity and food variety consumed by womenin rural areas of Tanzania were assessed in order to investi-gate the nutritional quality of their diets. The last can beimproved with consumption of a large number of foodgroups and food items. Dietary diversity is, therefore, animportant component of nutritional quality (Hatloy et al.1998; Torheim et al. 2004).

The main objective of this study was to test whether highvegetable diversity, available through cultivation in fields/gardens and collection from the wild, resulted in high die-tary diversity in different districts of rural Tanzania. Further-more, the question of whether dietary diversity was linked tothe socio-economic status of participants was alsoinvestigated.

This study was integrated into the project ‘Promotion ofNeglected Indigenous Leafy and Legume Vegetable Cropsfor Nutritional Health in Eastern and Southern Africa’ (Pro-NIVA) led by the World Vegetable Centre, Regional Centrefor Africa (AVRDC-RCA).

Methods

Research location, time and participants

For this repeated cross-sectional study, three surveys cov-ered different seasons within a whole year, namely the dryseason during June/July 2006 (DS), the short rainy seasonduring November/December 2006 (SR) and the end of thedry and beginning of the long rainy season during March/April 2007 (LR). Data were surveyed during the threeseasons within a single year, as food consumption dependson seasonal food availability, especially in rural areas and infarming communities (Keding 2010). The chosen seasonswere those with the largest differences between each other(rainy, dry, in-between).

The districts and villages for this study were some ofthose already visited within a baseline survey of a precedingproject (Keller et al. 2005; Weinberger and Msuya 2004),namely six villages, each in three different districts(Kongwa, Muheza and Singida) of north-eastern and centralTanzania. Districts were chosen in order to have significantdifferences in a variety of factors such as climate, altitude,ethnic groups and distance to urban centres. Selection ofvillages and households was based on the snowball

approach (Weinberger and Swai 2006). Participants werewomen randomly selected in each of the 18 villages by theresponsible village extension officer and on the basis ofhousehold lists. Selection criteria included reproductiveage (i.e. age between 15 and 45 years) and cultivation ofvegetables. The study focused on women only as theyare usually responsible for vegetable cropping and foodpreparation and they are also a vulnerable group in termsof nutritional health (Lyimo et al. 2003; Price 2003;Keding et al. 2007). At the start of the project, 360participants (120 per district) were included. This samplesize was calculated according to feasibility while the aimof the study was not to estimate representative prevalen-ces but to gain insight into problems of nutritional andagricultural linkages. Only 252 women attended all threemeetings and consequently formed the study cohort. Themost common reasons for dropping out were illness,travel, relocation or workload.

Data collection

Each survey comprised an individual interview, which in-cluded a semi-quantitative 24-h recall of food consumption(single food items and quantities) and questions on thesocio-economic status of participants (during the first surveyonly) and on vegetable production during the time of inter-view. The 24-h recall was chosen as the quantity of foodsconsumed are usually recalled more precisely than a foodfrequency questionnaire and because the method had al-ready been successfully applied to DDS calculation in anAfrican study (Savy et al. 2007). Questions concerningsocio-economic status included ethnic origin of participantsand occupation and status within the household amongothers (Keding 2010) and those concerning vegetable pro-duction included the number and types of vegetables culti-vated by women and if (yes or no) they bought and soldvegetables (which types; quantity was not measured), thusdifferentiating between vegetables cultivated in own gar-dens or fields and vegetables collected from the wild. Allvegetables mentioned by women were identified with apicture book containing pictures and descriptions of mosttraditional vegetables of Tanzania (Vegetable Picture Folderby Patrick Maundu, Bioversity International, unpublished).The questionnaire was developed in English, translated intoKiswahili, in which the interviews were conducted, andtranslated back into English to cross-check that the correctmeanings were maintained. It was pre-tested with eightTanzanian women from the Arumeru district. Ethical clear-ance for this study was granted by the Faculty of Medicineat Justus-Liebig-University, Giessen, Germany. Permissionfor the research was given by Sokoine University of Agri-culture, Morogoro, Tanzania. Oral consent was sought fromeach participant during recruitment.

G.B. Keding et al.

Data analysis

The dietary diversity score (DDS) and food variety score(FVS) are supposed to be qualitative measures that can serveas proxies for the nutrient adequacy of the diet of individualsand can also reflect household access to a diversity of foods(FAO 2007). In fact, it has already been observed that theDDS represents the overall dietary quality of women in apoor rural African setting very well and can also be linked totheir nutritional status (Savy et al. 2005).

Dietary diversity scores (DDS) were calculated by sum-ming the number of different food groups consumed by anindividual over the 24-h recall period. However, currentlyno international consensus exists on which food groups toinclude in the scores (FAO 2007). Therefore, 14 differentfood groups were chosen for this study (Table 1) accordingto food items found during the survey and in line withliterature concerning local food habits (West et al. 1988;FAO 1970). The Food Variety Score (FVS) was calculated,whereby all single foods consumed on a single day weresummed (Table 1). Some food items such as different leafyvegetable species were grouped as one food type. Whencomparing the different seasons, scores calculated from onlyone 24-h recall were applied. When comparing the differentdistricts, scores were averaged over the three 24-h recallsfrom the three seasons.

The DDS and FVS were grouped into terciles to distin-guish between diets of low, medium and high diversity andvariety as in other studies (Savy et al. 2007; Savy et al.2005). Tercile cut-offs were chosen in the first season withthe aim of having well balanced groups, and the same cut-offs were applied for the other two seasons. Women withinthe low DDS group consumed only two to four differentfood groups per day, participants with medium DDS con-sumed five or six, while those with a high DDS consumedseven to 11 food groups per day. Regarding FVS, partici-pants were assigned to low (2–6 different foods), medium(7–9) or high (10–16) FVS groups.

Vegetable production was assessed by asking which andhow many different vegetable types a woman cultivated (inown garden/field), collected from the wild, sold and pur-chased. As there is no literature on different levels of diver-sity of vegetable production, low or high vegetable diversitywas determined by comparing own data of the differentdistricts or during different seasons.

Statistical analysis

DDS and FVS scores were checked for differences betweenseasons (non-parametric Friedman test) and districts (t-testor non-parametric Kruskal-Wallis test). Associations of thescores with socio-economic status, vegetable production and

Table 1 List of 76 different dietary items within 14 different food groups according to West et al. (1988) and FAO (1970) and adaptedto food items found during the survey 2006/2007 in Tanzania

No Food group Foods within this group

Plant origin

1 Cereals and grain products Maize, millet, rice (incl. vitumbua), sorghum, wheat (incl. chapati, andazi, scones etc.)

2 Starchy roots, tubersand fruits

Cassava, plantain, potato, sweet potato, taro/cocoyam, yam

3 Grain legumes and legumeproducts

Bambara groundnut, bean, chickpea, cowpea, mungbean, green pea (dried), pigeon pea, soybean

4 Nuts and seeds Cashew nut, coconut (and products, e.g., milk), groundnut, melon seeds, pumpkin seeds, sunflower seeds

5 Vegetables andvegetable products

Bulbs (onion, leek, garlic), cabbages, cucumber (wild or exotic), eggplant (African, brinjal), leafyvegetables (dark green), legumes/unripe pulses (e.g., fresh peas), mushrooms, root vegetables (carrot),okra, pumpkin fruit, tomato

6 Fruits Avocado, baobab, banana, carambola, jackfruit, lemon, mango, melon, orange, papaya, pear, pineapple,tangerine, watermelon, wild fruits (e.g., lade, matogo)

Animal origin

7 Meat Beef, goat, mutton, pork, offal

8 Poultry Chicken, duck, offal of poultry

9 Eggs Eggs (from chicken)

10 Fish and fish products Cod-type fish (saltwater/sea), salmon-type fish (freshwater/lake), anchovy-type (dried) fish (dagaa)

11 Milk and milk products Milk (cow, goat), sour milk

Others

12 Sugars and syrups Sugar/sugar cane, honey

13 Oils and fats Ghee/clarified butter, lard/animal fat, (red) palm oil (korie), vegetable oil (sunflower)

14 Beverages Carbonated soft drink, non-alcoholic hot drink (tea, coffee)

Dietary scores of women in Tanzania

food consumption variables were tested both through bivar-iate correlations and multiple regression models. However,no additional insights were gained through the latter soonly results from the bivariate relationships are shownand discussed. Relationships between categorical varia-bles were assessed with the chi-square (χ2) test; rela-tionships between continuous variables were determinedwith Spearman’s rank-order coefficient, rho (ρ). Allstatistical analyses were carried out with the StatisticalPackage for the Social Sciences (SPSS) version 16.0(SPSS Inc., Chicago, IL, USA).

Results

Characteristics of participating women

Mean age of the women was 33 years and most of thembelonged to one of five different ethnic groups (Table 2).Three-quarters of the women were wives of the head ofhousehold and 89% had completed primary school. Only aminority (12%) earned additional cash income through abusiness or service, the majority (77%) being crop andlivestock farmers. The number of different vegetable typescultivated or collected per woman was especially high dur-ing the long rainy season (March/April) and in Muhezadistrict (Table 2). Furthermore, the number of additionallypurchased vegetables was highest in Kongwa during theshort rains (November/December) and women in Muhezasold their vegetables more regularly (Table 3).

Dietary diversity score

Overall, participants consumed between two and 11 differ-ent food groups on a single day, but between two and tenwhen averaged over 3 days (mean of three surveys). Distri-bution was skewed and, therefore, the median instead of themean DDS had to be considered, which was about six for allseasons and districts taken together. Median DDS both forKongwa and Singida were considerably lower than the onefor Muheza (Table 4).

The proportions of women having low, medium or highDDS were significantly different between the districts(Fig. 1); the DDS in Kongwa were evenly distributed overthe different numbers of food groups. Conversely, the DDSwere mainly medium or high for participants in Muhezadistrict and either low or medium for women in Singidadistrict (Fig. 1). Seasonal differences, though significant(p<0.001), were less distinctive (Fig. 2). DDS and FVSwere lowest during the short rains (Nov/Dec) when fewerwomen consumed a high number of food groups or fooditems. By contrast, DDS and FVS were highest during thedry season (Jun/Jul) and especially the long rains (Mar/Apr).

The main food groups consumed by participants witheither low, medium or high DDS differed. While cerealsand vegetables were consumed by everyone and, to a greatextent oils/fats, the other 11 food groups were not consumedby all participants (Fig. 3). Only 54% of women with a lowDDS consumed grain legumes, besides the three main foodgroups. Women with a medium DDS consumed additionallynuts and fish to a great extent. In the high DDS group,cereals, vegetables, oils/fats, grain legumes and nuts wereconsumed by everyone. About 90% of participants alsoconsumed fish and beverages (meaning black tea only),while 83% consumed milk. Only 20% or fewer participantsconsumed fruits, meat, poultry or eggs (Fig. 3).

Table 2 Characteristics of women (n0252) from three districts ofTanzania participating in the 2006/2007 survey

Mean ± SD Proportion(%)

Median(range)

Age (years) 33.3±6.9

Ethnic group

Bondei 7.5

Gogo 14.3

Kaguru 9.5

Nyaturu 41.3

Shambaa 9.5

Other 17.9

Status within hh

Head of hh 8.7

Wife of head of hh 74.6

Mother of head of hh 8.7

Daughter of head of hh 7.9

Education

No or few years in formaleducation

7.9

Primary school completed 89.3

Higher education (postprimary school)

2.8

Occupation

Crop farmer 10.7

Crop and livestock farmer 77.0

Farmer + business/service 12.3

Vegetable cultivation/collectiona

Jun/Jul (DS) 6 (0–22)

Nov/Dec (SR) 6 (0–19)

Mar/Apr (LR) 9 (0–19)

Kongwab 7 (2–11)

Muhezab 8 (3–18)

Singidab 7 (1–14)

hh householda Number of vegetable types cultivated and collected per womanbmean across all three seasons

DS dry season; SR short rains; LR long rains

G.B. Keding et al.

Food variety score

The FVS ranged between two and 16 foods consumed perday, and between three and 14 when averaged over threedays (mean of three surveys). It was normally distributedwith an overall mean FVS of eight foods per day. BothKongwa and Singida had a mean FVS of 7.1 but this wassignificantly different from Muheza with an FVS of 10.6(Fig. 4). In Kongwa a greater proportion of women con-sumed a low or medium number of foods, while in Muhezathe majority of women (about 72%) had a high FVS. Bycontrast, in Singida district, nearly 50% of participants had amedium FVS. Differences between seasons were also sig-nificant, with slightly higher values during Mar/Apr (LR)than during the other two seasons (Fig. 5).

Associations between food scores and vegetable production

DDS and FVS values were significantly associated with thenumber of vegetables that women cultivated/collected, andif they bought or sold vegetables. Women with a high DDS/FVS cultivated/collected a similar number of vegetablesyear round, while participants with medium and, especially,

with a low DDS/FVS had more fluctuations in their vege-table cultivating/collecting diversity (Table 5).

Vegetable diversity was positively correlated with DDSduring Jun/Jul (DS) and Nov/Dec (SR), whereas it wasnegatively correlated to both scores during Mar/Apr (LR)(Table 6). While there were no significant correlations be-tween the two scores and vegetable buying or selling duringJun/Jul (DS), more women who sold their vegetables had ahigh DDS (58%) or high FVS (50%) during Nov/Dec (SR).There was also a trend that women who bought vegetablesin addition to those that they produced themselves had ahigh DDS, while those who did not buy additional vegetablesmore often had a low DDS (Keding 2010).

Associations between food scores, socio-economic variablesand food group intake

Both food scores were associated with the ethnic group ofparticipants (p<0.001). For example, nearly 100% ofBondei and Shambaa, living mainly in Muheza district,had a high DDS and FVS (Table 4). Other ethnic groupswere rather evenly distributed among the categories of foodscores, yet, with a focus on low and medium values.

The occupation of participants was also related to both DDS(p00.004) and FVS (p<0.001). Women who were crop farm-ers had a low ormediumDDS, while those having a business orservice besides farming tended to have a high DDS and FVS.Mixed crop-livestock farmers were equally present in each ofthe three scoring categories. Also, the status within the house-hold was strongly associated with DDS (p<0.001) and FVS(p00.001). Women being the head of household, the mother ordaughter of the head of household had high DDS and FVS,whereas women being the wife of the head of household hadeither a low DDS or a medium FVS.

Table 3 Vegetable production, collection (from wild), purchase and sale by women during different seasons and in three different districts ofTanzania

Cultivationa Collectiona Purchaseb Sales duringc

Nov/Dec (SR) (n0150)

Mar/Apr (LR) (n0109)

Noseason

1season

2seasons

Allseasons

Kongwa 3 (1–6) 3 (1–8) 3.3 1.6 76.4 18.1 4.2 1.4

Muheza 4 (1–9) 4 (1–9) 2.7 3.0 60.5 21.1 10.5 7.9

Singida 4 (0–9) 3 (0–6) 2.2 2.1 63.5 26.9 7.7 1.9

Jun/Jul (DS) 4 (0–12) 2 (0–10)

Nov/Dec(SR)

3 (0–10) 3 (0–11)

Mar/Apr(LR)

5 (0–12) 5 (0–10)

a Number (median and range) of vegetable types per woman (n0252)bMean number of vegetable types per womenc Share of women (%) that sold vegetables

Table 4 Dietary diversity score (DDS) and food variety score (FVS)across three seasons of women in three districts of Tanzania

District Main ethnicgroups

n DDS Median(range)

FVS Mean(± SD)

All 252 6 (2–10) 8.2 (±2.4)

Kongwa Gogo, Kaguru 72 5 (3–8) 7.1 (±2.1)

Muheza Bondei, Shambaa 76 8 (5–10) 10.6 (±1.4)

Singida Nyaturu 104 4 (2–8) 7.1 (±1.7)

Dietary scores of women in Tanzania

The actual intake (in g/day) of all food groups except foranimal products was significantly correlated (p<0.001) to bothfood scores while the intake of cereals was only correlatedwithDDS. All correlations were positive except for those of

vegetables (DDS: rho0−0.433, p<0.001; FVS: rho0−0.338,p<0.001) and cereals (DDS: rho0−0.140, p00.027), implyingthat the higher the DDS/FVS the lower was the quantity ofvegetables and cereals consumed and vice versa.

0

10

20

30

40

2 3 4 5 6 7 8 9 10

low medium high

Pro

po

rtio

n o

f p

arti

cip

ants

(%

)

Number of food groups consumed on a single day

Kongwa Muheza Singida

Fig. 1 Proportion ofparticipants (%) with a certaindietary diversity score (DDS) inthree districts of Tanzania;mean values across threeseasons (n0252); p00.01 fordifferences between districts(Keding 2010)

0

5

10

15

20

2 3 4 5 6 7 8 9 10 11

low medium high

Pro

po

rtio

n o

f p

arti

cip

ants

(%

)

Number of food groups consumed on a single day

Jun/Jul (DS) Nov/Dec (SR) Mar/Apr (LR)

Fig. 2 Proportion ofparticipants (%) with a certaindietary diversity score (DDS)during three different seasonsacross three districts ofTanzania (n0252); p<0.001 fordifferences between seasons(Keding 2010)

G.B. Keding et al.

0 10 20 30 40 50 60 70 80 90 100

Eggs

Meat

Poultry

Fruits

Starchy plants

Milk

Sugars

Beverages

Fish

Nuts

Grain legumes

Oils/fats

Vegetables

Cereals

Share of participants

Fo

od

gro

up

s

High DDS (7-11 fg) Medium DDS (5-6 fg) Low DDS (2-4 fg)

Fig. 3 Proportion of participants (%) consuming each food group as a function of dietary diversity score (DDS) categories; n0252 women from threedistricts in Tanzania interviewed during three different seasons; fg0food groups (Keding 2010)

0

5

10

15

20

25

30

3 4 5 6 7 8 9 10 11 12 13 14

highmediumlow

Sh

are

of

par

tici

pan

ts (

%)

Number of foods consumed on a single day

Kongwa Muheza Singida

Fig. 4 Proportion ofparticipants (%) with a certainfood variety score (FVS) inthree districts of Tanzania(n0252); mean values acrossthree seasons; p00.01 fordifferences between districts(Keding 2010)

Dietary scores of women in Tanzania

Discussion

The median DDS of 6 and the mean FVS of 8.3 of the studypopulation were low, suggesting an overall poor dietaryquality. Yet, the scores were similar to those of other studiesin the Middle East and West Africa (Azadbakht et al. 2005;Savy et al. 2005). In a study from Kenya a DDS of 6 wasconsidered as medium, however, only 12 instead of 14 foodgroups were assessed (ACF 2009) and, therefore, it is diffi-cult to compare the two studies. When comparing dietaryscores from different studies, how food items and foodgroups are defined also has to be considered, e.g. weredifferent cereal or vegetable varieties counted as one orindividually, and if foods were grouped according to theirorigin or nutritional value (e.g. Vitamin A rich foods).

In general, about one third of participants had amonotonousdiet with an alarmingly low DDS of only two to four foodgroups per day. These women consumed a very basic dietconsisting of cereals, vegetables and usually oil or fat (generalfor all three seasons and districts). Such individuals rarelyconsumed foods from animal sources, and also fruit consump-tion was fairly low. This is in accordance with findings fromrural Burkina Faso, where womenwith a lowDDS of only twoor three food groups consumed mainly cereals, green leafyvegetables and condiments (Savy et al. 2005). By contrast,between 90% and 100% of women in the present study with ahigh DDS also consumed grain legumes, nuts, fish and bev-erages, usually black tea. These additional food groups weregenerally more expensive. However, other food groups such asfruits were less consumed, most likely due to lack of

0

5

10

15

20

2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6

low medium high

Sh

are

of

par

tici

pan

ts (

%)

Number of foods consumed on a single day

Jun/Jul (DS) Nov/Dec (SR) Mar/Apr (LR)

Fig. 5 Proportion ofparticipants (%) with a certainfood variety score (FVS) duringthree different seasons acrossthree districts of Tanzania(n0252); p<0.001 fordifferences between seasons(Keding 2010)

Table 5 Overall number of vegetable types cultivated/collected per woman (median and range) with either low, medium or high dietary diversityscore (DDS) or food variety score (FVS) during three different seasons across three districts in Tanzania (n0252)

Season Low Medium High

DDS FVS DDS FVS DDS FVS

Jun/Jul (DS) 4 (0–12) 4 (0–12) 6 (0–16) 6 (0–22) 8 (0–22) 9 (0–18)

Nov/Dec (SR) 6 (0–13) 6 (0–13) 6 (0–15) 6 (0–15) 8 (0–19) 9 (0–19)

Mar/Apr (LR) 10 (3–19) 9 (3–19) 11 (1–19) 10 (1–19) 7 (0–17) 7 (0–17)

G.B. Keding et al.

availability owing to seasonality and nutritional knowledge,while starchy roots were presumably not consumed by everywoman because of certain dietary habits or customs.

The high consumption of oils/fats and sugar, measurednot only through food scores but also as quantity by Keding(2010), is remarkable, especially in such a rural Africancontext; this suggests that excessive caloric intake mightvery soon become a problem. Additionally, the differencesobserved between low and high dietary diversity typicallyrefer to dietary changes that happen during the process of anutrition transition (Popkin 2002), and of which the earlystage is suggested to have taken place already in ruralTanzania (Keding 2010). Still, vegetables were among thosefood groups forming the basic diet and being consumed bynearly every participant year round; here, the vegetable quan-tity consumed ought to be taken further into account. The factthat the amount of vegetables consumed decreases with in-creasing diversity in the diet is of concern. Obviously, lesshealthy and valuable food groups such as beverages and sugaraccounted for a high dietary diversity and replaced the amountconsumed of more healthy food groups such as vegetables.

District and seasonal differences

DDS and FVS differed both among the three districts andamong the three seasons, although differences among thelatter were less pronounced. Obviously, each district, withits particular ethnicities, culture, agro-ecology and (chang-ing) nutritional habits, had a stronger influence on dietarydiversity and food variety than season.

The high vegetable diversity was expected in Muheza dis-trict, as it is situated in the Eastern Usambara Mountains that

form part of the Eastern Afromontane hotspot, one of 34biodiversity hotspots in the world (Conservation_International2007). Although wild plants are not necessarily consumed, itwas expected that conditions were also favourable for foodproduction in this district. By contrast, Kongwa and Singida,are situated in Central Tanzania which has a semi-arid climateand supports lower diversity of vegetation, including vegeta-bles (Keller et al. 2005).

This study confirmed that women fromMuheza district hadthe highest DDS and FVS. However, a high dietary diversityresults not only from a great diversity of locally available andproduced products. The various ethnic groups in Muhezapossess different dietary customs (Weinberger and Msuya2004; Keller et al. 2005) and therefore, they are likely tocontribute to the high dietary diversity of participants. Addi-tionally, coastal trade affects food availability and usage thatcan be traced back to the 5th to 7th century, when the IndianOcean trade was already linked to a regional commerce (Iliffe1995). On the other hand, reasons for low diversity diets inKongwa and Singida districts can be due to the general lowagricultural diversity in these districts and also because onlyone or two ethnic groupswith similar food habits dominate thedistricts (Weinberger and Msuya 2004; Keller et al. 2005).

DDS and FVS seemed to be little dependent on seasonalchanges. This applies especially to food items that are not orare seldom home-produced, but can be bought all yearround, such as tea, sugar, bread/cakes, oil/fat and alsostarchy staples. Additionally, as the food scores do notaccount for food quantity it is possible that seasonal changesoccur for amounts of foods consumed, while the food typesin general remain essentially similar.

Dietary diversity and vegetable production

Participants with a high DDS/FVS cultivated/collected moreor less the same number of different vegetables year round. Bycontrast, the women with low or mediumDDS/FVS had morefluctuation in their vegetable cultivating/collecting diversity,which may be an indicator of more weather-dependent culti-vation/collection. It is generally acknowledged that seasonalmalnutrition in rural areas of Africa is widespread (SCN 1988)and is caused, to a great extent, by seasonal fluctuations infood availability and the ability to acquire food (Teokul et al.1986). Not only those women who cultivated/collected vege-tables more consistently, but also those who sold their prod-ucts, had higher DDS and FVS. Consequently, not only theavailability of agricultural diversity was associated with die-tary diversity, but also the possibility of marketing diversifiedagricultural products played a certain role.

The purchase of additional vegetables can be regarded asan indicator that women in general were able to buy food inaddition to what they produced on their own. Self-producedvegetable/food diversity did not alone influence dietary

Table 6 Correlations between cultivation/collection of vegetables andfood scores (dietary diversity score, DDS and food variety score, FVS)of women from three districts during three seasons in Tanzania

No. of vegetables cultivated No. of vegetables collected

Correl. coeff. rho p Correl. coeff. rho p

All year

DDS 0.313 <0.001 n.a. n.s.

FVS 0.247 <0.001 n.a. n.s.

Jun/Jul (DS)

DDS 0.307 <0.001 0.434 <0.001

FVS 0.367 <0.001 0.392 <0.001

Nov/Dec (SR)

DDS 0.328 <0.001 0.135 0.032

FVS 0.347 <0.001 n.a. n.s.

Mar/Apr (LR)

DDS −0.237 <0.001 −0.381 <0.001

FVS −0.187 0.003 −0.321 <0.001

n.a. not applicable; n.s. not significant

Dietary scores of women in Tanzania

diversity, but the purchase of foods and all related factors,such as income and supply of foods, had great impacts onthe diversity of foods consumed, even in rural environ-ments. Women-controlled income often has greater imme-diate benefits for the nutrition and well-being of allhousehold members, especially children, than when incomeis controlled by men (FAO 1997). Moreover, the nearerwomen live to a town or economic centre, the more theywill participate in the cash economy, such as the sale ofgarden produce (Fratkin and Smith 1995), and both factorscan contribute to an increase in diversity of family nutrition.

Dietary diversity and socio-economic status

Ethnicity of participants was strongly associated with bothDDS and FVS. The influence is likely to be in terms of differ-ences in dietary habits such as the preference for different foodgroups. This is an important factor to consider, especially whenproposing a high variety of foods for improving nutrition inareas inhabited by many different ethnic groups. It was alsofound in studies with migrants that ethnicity may be an impor-tant factor influencing eating habits (IFAVA 2008).

Women with an additional income from non-farmingactivities were able to eat a greater variety of foods, espe-cially those that needed to be bought. The present findingsconcur with those from Burkina Faso, where a higher pro-portion (about 50%) of women with commercial incomeshad high FVS and DDS (Savy et al. 2005).

Being “only” the wife of the head of household was asso-ciated with less food variety, while women being the head ofhousehold consumed higher dietary diversity. Women-headedhouseholds are usually poorer than households headed bymen(UNDP 1995), yet, equating a poor household with lowdietary diversity is not supported by the present findings.The present results rather suggest that, besides wealth, it isalso important to consider how much decision making powerthe person responsible for family nutrition in the householdhas. Local traditions often dictate that higher-status foodshould be given to husbands and sons (Walker 1997) but thismay not necessarily translate into higher dietary diversity beingprovided for male household members.

Advantages and drawbacks of using DDS and FVS

In the present study, the analysis of FVS had no clear addedvalue when compared to DDS analysis. The FVS was ap-plied to investigate the diversity within single food groups,which should be of concern when studying agro-biodiversityand its link to nutrition. Yet, calculating FVS is not necessarywhen focusing only on general dietary diversity of people andrelated factors.

A study by Savy et al. (2007) suggests that a DDScalculated from a 1-day recall was sufficient to describe

women’s nutritional status and this was applied also in thepresent study. Yet, the time period of data collection couldbe reconsidered as in other studies e.g. differentiation be-tween 1-day recalls for individuals and 7-day recalls for thehousehold (Hoddinott and Yohannes 2002). While a singleday’s intake of an individual can be unusually high or low,respondents are more likely to remember accurately foodintake of the past 24 h than that of the past 7 days.

In general, while diversity should not be confused withquality, it has been shown that diversity scores clearly reflectoverall dietary quality (Hatloy et al. 1998; Torheim et al.2004). While the food scores account only for diversity offoods, the quantity of foods consumed definitely needs to betaken into account if addressing the health status of people,e.g., the body mass index (BMI) (Keding 2010). Furthermore,different forms of an increase in dietary diversity and foodvariety must be distinguished. A simple increase, for instance,in FVS could result from either consumption of more differentfruits and vegetables, or consumption of more different con-venience and fast foods of animal origin; it could also resultfrom establishing and using a homegarden or from moving totown and being exposed to another type of nutrition. Conse-quently, while a high nutritional diversity is usually desirablefor a balanced diet (Burgess and Glasauer 2004), it may notnecessarily result in better health. Likewise, a certain degree ofdiversity does not mean that the dietary quality will matchpeople’s particular needs (Brown et al. 2002). Therefore,dietary diversity scores should be enhanced with a measureof dietary quality. This could be achieved through weighingsingle food groups according to their importance for a healthydiet, e.g. following the food pyramid.

Conclusions

Major regional and minor seasonal differences of dietaryhabits of the study population in Tanzania were shown bymeans of DDS and FVS. Women with either low, mediumor high scores could be characterised by further variablessuch as vegetable production and socio-economic status. Infact, many bivariate associations with the food scores werefound and the rather easy and quickly measured diversityscores were successfully applied to describe the dietarysituation of the present study population. Yet, less healthyand less valuable food groups account for high dietarydiversity in this study and replaced the amount consumedof more healthy food groups, such as vegetables. Therefore,it is emphasised that explicitly different forms of increase indietary diversity and food variety must be distinguished, aswell as quantity and quality of diversity.

In the present study, vegetable cultivation functioned, to acertain extent, as an indicator of wealth. A high wealth statuswas related to high DDS and FVS scores and, thus, to a more

G.B. Keding et al.

varied, yet not necessarily healthier diet. Still, as both scoreswere linked to the production, selling and buying of vegetables,the promotion of homestead food production may be a goodway to improve dietary diversity. It is proposed that a study onnutrition or nutritional health always needs to integrate aspectsof food production. Contrariwise, nutritional concerns shouldalways be integrated into agricultural research. Understandingthe linkages between the diversity of foods in the field and onthe plate is one step towards the necessary but often neglectedintegration of nutrition and agriculture.

Acknowledgements The authors would like to acknowledge theunreserved cooperation and contributions of all participating women;the horticultural extension workers in the different districts; AVRDC-RCA and HORTI Tengeru staff; and students and staff from SokoineUniversity of Agriculture, Morogoro. Financial support by the GermanFederal Ministry for Economic Cooperation and Development/DeutscheGesellschaft für Technische Zusammenarbeit (BMZ/GTZ), the GermanAcademic Exchange Service DAAD and the Eiselen Foundation Ulm,Germany is gratefully acknowledged.

Conflict of interest The authors declare no conflict of interest.

References

ACF. (2009). Mathare sentinel surveillance report. Nairobi, Kenya:ACF (Action Against Hunger) Kenya Mission.

Azadbakht, L., Mirmiran, P., & Azizi, F. (2005). Dietary diversityscore is favorably associated with the metabolic syndrome inTehranian adults. Int J Obes (Lond), 29(11), 1361–1367.

Bouis, H., & Hunt, J. (1999). Linking food and nutrition security: pastlessons and future opportunities. Asian Development Review, 17(1,2), 168–213.

Brown, K. H., Peerson, J. M., Kimmons, J. E., & Hotz, C. (2002).Options for achieving adequate intake from home-prepared comple-mentary foods in low income countries. In R. E. Black & M. K.Fleischer (Eds.), Public health issues in infant and child nutrition(Vol. 48, Nestle’ Nutrition Workshop Series, Pediatric Program).Vevey/Lipincott: Nestec, Williams and Wilkins.

Burgess, A., & Glasauer, P. (2004). Family nutrition guide. Rome: FAO.Conservation_International. (2007). Biodiversity Hotspots: Eastern

Afromontane. http://www.biodiversityhotspots.org/xp/Hotspots/afromontane/Pages/default.aspx. Accessed 13 September 2009.

FAO. (1970). Food composition tables for use in Africa. Rome: FAO.FAO. (1997). Agriculture, food and nutrition for Africa. A resource book

for teachers of agriculture. Rome: Food and Nutrition Division, FAO.FAO. (2007). Guidelines for measuring household and individual

dietary diversity. Version 2. Rome, Italy.Fratkin, E., & Smith, K. (1995). Women’s changing economic roles

and pastoral sedentarization: varying strategies in altervativeRendille communities. Hum Ecol, 23(4), 433–454.

Hatloy, A., Torheim, L. E., & Oshaug, A. (1998). Food variety—a goodindicator of nutritional adequacy of the diet? A case study from anurban area in Mali, West Africa. Eur J Clin Nutr, 52(12), 891–898.

Hoddinott, J., & Yohannes, Y. (2002). Dietary diversity as a foodsecurity indicator. In F. C. a. N. D. International Food PolicyResearch Institute (Ed.), (Vol. Discussion Paper No. 136). Wash-ington, USA: International Food Policy Research Institute, FoodConsumption and Nutrition Division.

Iannotti, L., Cunningham, K., & Ruel, M. T. (2009). Improving dietquality and micronutrient nutrition. Homestead food productionin Bangladesh. Washington DC: IFPRI.

IFAVA. (2008). Fruit and vegetable consumption among migrants. TheIFAVA Scientific Newsletter No.29. Ottawa: International Fruitand Vegetable Alliance.

IFPRI. (2011). Leveraging agriculture for improving nutrition andhealth. Highlights from an international conference. New Delhi,India, 10 –12 February 2011

Iliffe, J. (1995). Africans. The history of a continent. Camebridge:Camebridge University Press.

Keding, G. B. (2010). Linking nutrition security and agrobiodviersity: theimportance of traditional vegetables for nutritional health of womenin rural Tanzania (PhD thesis, Institute of Nutritional Sciences, Justus-Liebig-University Giessen). Göttingen, Germany: Cuvillier Verlag.

Keding, G. B., Weinberger, K., Swai, I., & Mndiga, H. (2007). Diversity,traits and use of traditional vegetables in Tanzania (TechnicalBulletin No.40). Shanhua: AVRDC - The World Vegetable Center.

Keller, G. B., Mndiga, H., & Maass, B. L. (2005). Diversity andgenetic erosion of traditional vegetables in Tanzania from thefarmer’s point of view. Plant Genetic Resources, 3(03), 400–413.

Lyimo, M., Temu, R. P. C., & Mugula, J. K. (2003). Identification andnutrient composition of indigenous vegetables of Tanzania. PlantFoods for Human Nutrition (Formerly Qualitas Plantarum), 58(1), 85–92. doi:10.1023/a:1024044831196.

Olney, D. K., Talukder, A., Iannotti, L. L., Ruel, M. T., & Quinn, V.(2009). Assessing impact and impact pathways of a homesteadfood production program on household and child nutrition inCambodia. Food Nutr Bull, 30(4), 355–369.

Popkin, B. M. (2002). An overview on the nutrition transition and its healthimplications: the Bellagiomeeting. Public Health Nutr, 5(1A), 93–103.

Price, L. L. (2003). Farm women’s rights and roles in wild plant foodgathering and management in North-East Thailand. In P. L.Howard (Ed.), Women and plants. London: Zed Books Ltd.

Savy, M., Martin-Prevel, Y., Sawadogo, P., Kameli, Y., & Delpeuch, F.(2005). Use of variety/diversity scores for diet quality measure-ment: relation with nutritional status of women in a rural area inBurkina Faso. Eur J Clin Nutr, 59(5), 703–716.

Savy, M., Martin-Prevel, Y., Traissac, P., & Delpeuch, F. (2007). Mea-suring dietary diversity in rural Burkina Faso: comparison of a 1-dayand a 3-day dietary recall. Public Health Nutr, 10(1), 71–78. doi:S1368980007219627[pii]10.1017/S1368980007219627.

SCN. (1988). First report on the world nutrition situation. SCN NewsNo. 2. Geneva: United Nations Standing Committee on Nutrition.

Steyn, N. P., Nel, J. H., Nantel, G., Kennedy, G., & Labadarios, D. (2006).Food variety and dietary diversity scores in children: are they goodindicators of dietary adequacy? Public Health Nutr, 9(5), 644–650.

Teokul, W., Payne, P., & Dugdale, A. (1986). Seasonal variations innutritional status in rural areas of developing countries: a reviewof the literature. Food and Nutrition Bulletin, 8(4), 8–10.

Torheim, L. E., Ouattara, F., Diarra, M. M., Thiam, F. D., Barikmo, I.,Hatloy, A., et al. (2004). Nutrient adequacy and dietary diversityin rural Mali: association and determinants. Eur J Clin Nutr, 58(4), 594–604.

UNDP. (1995). Human development report: HDR. New York: UnitedNations Development Programme. Oxford University Press.

Walker, S. P. (1997). Nutritional issues for women in developingcountries. [Review]. Proc Nutr Soc, 56(1B), 345–356.

Weinberger, K., & Msuya, J. M. (2004). Indigenous vegetables inTanzania: Significance and Prospects (Technical Bulletin No.31). Shanhua: AVRDC - The World Vegetable Center.

Weinberger, K., & Swai, I. (2006). Consumption of traditional vegetablesin Central and Northeastern Tanzania. Ecol Food Nutr 45, 87–103.

West, C. E., Pepping, F., & Temalilwa, C. R. (1988). The compositionof foods commonly eaten in East Africa. Wageningen: WageningenAgricultural University.

Dietary scores of women in Tanzania

Gudrun B. Keding studied agri-cultural sciences at Georg-August-Universität Göttingen,Germany and University ofReading, UK. In 2002 she car-ried out field work in Namibiafor her BSc on intercroppingand further fieldwork in 2003for her MSc on productionand consumption of traditionalvegetables within a project ledby the World Vegetable Center(AVRDC) – Regional Centerfor Africa (RCA) in Arusha,Tanzania. From April 2005 to

March 2009 she worked as a research fellow at the Institute ofNutritional Sciences – International Nutrition, Justus-Liebig-Universität Giessen, Germany. In 2006/2007 she did further fieldwork, again within an AVRDC-RCA project which resulted in athesis with the title “Linking nutrition security and agrobiodiver-sity: the importance of traditional vegetables for nutritional healthof women in rural Tanzania”, for which she received her PhD.She is currently a postdoctoral research fellow with BioversityInternational in Nairobi, Kenya.

John Msuya is an Associate Pro-fessor at Sokoine University of Ag-riculture in Tanzania. He is aversatile researcher-cum-educatorand consultant having spent consid-erable time of his 2 decade career inresearch and university teaching.With a first degree in agriculture, aMasters in Human Nutrition and aDoctorate in Food Economics, JohnMsuya combines academic and de-velopment expertise with a focus onfighting malnutrition and relatedconsequences. More recently, hehas taken an interest in the subject

of HIV/AIDS and its linkage with Food Security. John has field experiencein Tanzania, Uganda, Kenya and Zimbabwe.

Dr. Brigitte L. Maass is currentlybased in Nairobi, Kenya, whereshe leads the development, adapta-tion and dissemination of tropicalforages in Eastern and CentralAfrica for the International Centerof Tropical Agriculture (CIAT).Prior to this, she was an AssociateProfessor for Agrobiodiversity andPlant Genetic Resources in theTrop i c s a t Geo rg -Augus t -Universität Göttingen, Germany(1999–2008). Before she joinedthe university, she was a principlescientist at the International Live-

stock Research Institute (ILRI) in Ethiopia (1997 to 1999) and at CIAT inColombia and Peru (1989 to 1997), where she led the characterization,evaluation, and conservation of tropical forage genetic resources. Sheobtained her PhD (Dr. sc. agr.) at the University of Göttingen in 1988,prior to which she conducted her field research at CIAT in Colombia(1984–1986). She initiated her overseas’ career in a GTZ (German Societyfor Technical Cooperation) grassland development project in Peru (1981–1983) after conducting studies in agriculture at the University of Hohen-heim, Stuttgart, Germany (1973–1978), where she obtained her MSc. Shehas published over 30 papers in scientific journals and more than 100 inother forms; she has supervised over 30 MSc and 9 PhD students.

Michael Krawinkel is Professorof Human Nutrition with a focuson International Nutrition atJustus-Liebig-University in Gies-sen, Germany. He is by training amedical doctor and paediatrician,and has worked since 1999 inhuman nutrition and nutrition se-cur i ty. Academic teachingextends to the Universities ofGiessen, Germany and of Vienna,Austria, as well as the HebrewUniversity of Jerusalem.His research focus is on dietarymeans of meeting micronutrient

needs of human populations in resource-poor countries and on man-agement of chronic non-communicable diseases through consumptionof specific vegetables, especially bitter gourd.

G.B. Keding et al.