Money Can’t Buy Me Love, but It Can Buy Apples: An Analysis of Fruit and Vegetable Demand in Uzbekistan

Abstract

Hidden hunger affects far more people than hunger. Being rich in vitamins, fruit and vegetables are wonderful ways to reduce micronutrient deficiency. In Uzbekistan, although per capita national supply exceeds the recommended amounts, individual-level intakes remain inadequate. This study sheds light on the factors affecting poor fruit and vegetable consumption. The research area included five districts in Tashkent province, where almost 1000 people were visited in summer and winter. A fixed effects regression model has shown high income elasticity of demand across all population groups. In adults, food and nutritionknowledge was positively associated with increased intake. Prices were found to have an inverse impact on intake in infants and adult females. Nutrition education may be therefore just as important as lowering the price.

Introduction

Since 1991, horticultural production has been expanding in Uzbekistan in terms of area and quantities (FAOSTAT, 2015). As a result, per capita national supply of fruit and vegetables—as derived from the Food Balance Sheets of the Food and Agriculture Organization of the United Nations (FAO)—exceeds the recommended amount of 400 grams by more than two times.

It is, however, misleading to conclude a saturation of fruit and vegetables in actual consumption, which might be lower than the quantities shown, as food availability may vary because of the magnitude of food losses along the marketing chain, food wastage within the household, cooking and storage losses (Nichols et al., 2012). In fact, individual-level intakes—as derived from the survey conducted for this study—remain inadequate with a strong seasonal pattern (Table 11.1).

Table 11.1 Per capita supply and intake of fruit and vegetables in Uzbekistan, grams per day

Micronutrient deficiency is a global problem and hidden hunger affects far more people than hunger (WHO, 2006). In Uzbekistan, the nutritional profile shows high rates of stunting in children and overweight in all population (NLiS, 2015). Figures from the Global Burden of Disease Study 2017 showed that within the European Region of the World Health Organization (WHO), unhealthy eating is deadliest in Uzbekistan: 394 diet-related deaths per 100,000 people (Meier et al., 2019). Such elements as a ‘diet low in fruit’ and a ‘diet low in vegetables’ lead the group of dietary risk factors attributable to the disease burden in Uzbekistan, as expressed in per cent of a total number of years of life lost (IHME, 2018).

Meanwhile, fruit and vegetables provide an easily available source of micronutrients (WCRF & AICR, 2007) and are linked with reduced risk of chronic diseases (Lock, Pomerleau, Causer, Altmann, & McKee, 2005), obesity and type 2 diabetes (Ball et al., 2003). Given the importance of a healthy diet and especially fruit and vegetables, this paper therefore quantitatively identifies the determinants of fruit and vegetable consumption among the Uzbek population.

Conceptual Framework

The conceptual framework on Fig. 11.1 succinctly summarises the key assumptions and hypotheses of the interactions between fruit and vegetable supply and demand and their effect on nutrition and health. For the sake of the current analysis, the focus lies on the demand side of the equation. For instance, seasonality in supply influences decisions on consumption via prices and other factors. It is noteworthy that interaction between supply and demand goes both ways, as the horticultural industry is attempting to react efficiently to changes in consumer demand, while supply shortages/surpluses are the signals for consumers’ behaviour. According to a theory of reciprocal determinism, consumption of fruit and vegetables (being a person’s behaviour) both influences and is influenced by personal factors, such as knowledge and wealth, and social environment (Bere & Klepp, 2005; Cullen et al., 2003; Granner et al., 2004).

Fig. 11.1

(Source Adapted from Bouis, Raney, and McDermott [2013], Gillespie, Harris, and Kadiyala [2012], Masset, Haddad, Cornelius, and Isaza-Castro [2011], Ruel [2002]. Note Interactions between the shadowed boxes are analysed explicitly while outlining the white box linkages in the Supply-Demand-Diet-Nutrition-Health nexus)

Conceptual framework

The limited fruit and vegetable intake, therefore, affects individual’s diet quality and it is assumed that there is a positive association between dietary diversity and nutritional outcomes in children, which might also lead to better health. In sum, improving fruit and vegetable supply, in order to match the population demand, should improve diets and reduce micronutrient deficiencies and stunting that, in turn, will result in better health outcomes.

Data

Data availability remains a constraining factor in analysing agricultural economics in Uzbekistan, as authorities have a reluctant attitude in sharing the data and making them publicly available. Other data sources rarely exist in the country.

Therefore, all analyses are largely based on the primary data, which were purposely collected in the research area among various target groups. This study’s focus lies in Tashkent province, which is located in the northeast of Uzbekistan. The choice of the research area was based on the fact that the province is a leading region in terms of horticultural production. Being a case study analysis, this paper does not serve as a country- or region-representative research.

Food Consumption Survey

The foodconsumption survey was performed in the form of structured face-to-face interviewing, including 24-hour food recall and physical measurements. The target sample size for this survey was calculated as 200 households or 1040 people. A multi-stage cluster sampling procedure was chosen as a sampling design.

In the first stage, the population was split into five strata, each representing a selected district of Tashkent province (Fig. 11.2). Each stratum was allocated 40 households that are a disproportional allocation of a total number of 200 households among five districts.

Fig. 11.2

(Source Author’s compilation)

Research area: food consumption survey, Tashkent province, Uzbekistan

In the second stage, the target population was divided into two domains—urban and rural—in each stratum, resulting in ten final strata. The sample allocation of households in these strata was done proportionally to the distribution of the urban/rural population. As a result, 94 households were selected in urban areas, whereas 106 households in rural areas.

During the third stage, the primary sampling units (PSU) were chosen with probability proportional to their size (PPS) from the list of small territorial units within the strata. In this survey, administrative units were regarded as the PSUs: in urban areas—towns and urban settlements, and in rural areas—village assemblies of citizens. Due to budget and time restrictions, it was decided to select 10 PSUs in each district with equal probabilities: four PSUs in urban areas and six PSUs in rural areas. As a result, a total of 50 PSUs were selected.

In Uzbekistan, the mahalla (local neighbourhood community) serves as a territorial unit of households and plays a great role in organising the social life of its inhabitants. Therefore, for this survey, it was decided to take advantage of the availability of the mahalla level of disaggregation and use it as a secondary sampling unit (SSU) for the fourth stage of sampling.

Finally, in the fifth stage, in each SSU the required households were selected at random. Prior to actual interviews, the updated lists of households were obtained from the village assemblies of citizens and/or local mahalla committees. Such updated lists were used as the frames for the fifth stage of sampling. For that, the households were sequentially numbered from one to n (the total number of households in each enumeration area).

The actual survey was conducted in two waves: first in August–September 2014 and second in February–March 2015. During both waves 200 households were interviewed, 193 of which were the same, the remaining seven were not available during the winter period, as they moved out. As a result, the information on food consumption and other variables both in summer 2014 and winter 2014/2015 is available for 931 people in 193 households.

During the survey, the person mainly responsible for food preparation and distribution was interviewed for most of the questions. In answering questions related to individual-level diet, the main respondent was consulting with each available family member.

The survey questionnaire was designed using the WHO’s STEPS methodology (WHO, 2008) and based on the 2006 Uzbekistan Multiple Indicator Cluster Survey and other sample questionnaires (in particular, FEHD 2010). The questionnaire was translated into Uzbek and Russian languages and pre-tested in one urban area of Tashkent city (Mirabad district) and one rural area of Kibray district of Tashkent province before fieldwork.

Fruit and Vegetable Market Survey

For the market price analysis, the data come from 2014 & 2015 Fruit and vegetable market survey, which was implemented by the author in three big markets of Tashkent province (Chirchik, Kuylik and Parkent). The choice of these markets was explained by their equidistant proximity to the SSU and sample households, as shown on Geographic Information System map in Fig. 11.3.

Fig. 11.3

(Source Author’s compilation)

Research area: fruit & vegetable market survey, Tashkent province, Uzbekistan

Qualitative and quantitative data were obtained from structured face-to-face interviews conducted with randomly selected horticultural retailers and wholesalers as well as key resource experts such as market staff members. As a result, collected information includes quarterly data on fruit and vegetable retail and wholesale prices for 2013 and 2014. For each traded product, an average price was taken based on at least three bids, representing a general price trend in the respective market.

Field visits took place in April 2014 and March 2015. Necessary permissions were obtained from local governments and market directorates. Challenges included lack of recorded information on sales, the reluctant attitude of some traders and inconvenient working time of wholesalers.

Methods

The empirical estimation involves three steps. The food consumption data allow calculating individual-level intakes of fruit and vegetables, which would then lay a basis for dependent variable in the econometric model of fruit and vegetable intake. The second step involves quantification of the independent variables. Special attention is given to such variables as income, market prices and foodknowledge. Finally, an econometric model is constructed and analysed to investigate the role of each factor on fruit and vegetable consumption.

Fruit and Vegetable Intake Level

In the current study, the definitions of fruit and vegetables relate to their nutritional qualities, and therefore are defined as ‘low-energy-dense foods relatively rich in vitamins, minerals and other bioactive compounds as well as being good sources of fibre’ (Agudo, 2005).

‘Vegetables’ include fruited vegetables, leafy vegetables, onions and roots, but exclude legumes, pulses, potatoes and other starchy tubers. Fruit jams, nuts, seeds and cereals are classified as differing from the fruit category, while pome fruit, stone fruit, berries, currants, citrus fruit, grapes and tropical fruit, as well as 100% derived fruit juices, are classified as ‘fruit’ (SAFEFOOD, 2013).

Based on the survey results, it was possible to estimate individual fruit and vegetable intake in both summer and winter seasons. The questionnaire was structured by meals in chronological order, starting from the first breakfast and ending with the last dinner. The actual intake of each food item was expressed in grams, following a calculation procedure given the daily frequency and portion size, as outlined in Fig. 11.4.

Fig. 11.4

(Adapted from Martin-Prevel et al. [2015], Herrador et al. [2015], WHO [2008])

Procedure of calculation of fruit and vegetable intake

Household Income Level

Being partly food security research, this study tries to capture the role of affordability in healthy eating. The piloting phase of the fieldwork showed that the respondents were reluctant to share the information regarding their income status in absolute terms. Keeping in mind this attitude, there was a five income categories’ breakdown provided in the questionnaire. Given the fact that there is no official statistics on the income level either at the individual or household level in Uzbekistan, the threshold values for each category were calculated based on previous research and official statistics. Below there is an explanation of how these five categories were chosen: lowest income, low-to-middle, middle, middle-to-high and highest income (Table 11.2).

Table 11.2 Calculation of threshold values for household income groups

Following household expenditure statistics among various income groups by Musaev, Yakshilikov, and Yusupov (2010) (who, in turn, used the data from the World Bank’s Uzbekistan Regional Panel Survey 2006), total expenditures per capita for middle-income group—25,251 Uzbek soums (UZS)—was taken as a reference for calculating the relative ratios of total expenditures per capita for other income groups. Assuming that the real income pattern follows the pattern of total expenditures linearly, the values of real income per capita for all income groups were calculated given that an official aggregate real income per capita for 2011 (UZS 1,992,400 per annum, or UZS 166,033 per month) was assumed to be associated with the middle-income group. Household-level data were calculated as a product of household size and real income per capita of each respective income group. Then, the values of 2011 data were expressed in 2014 prices using Consumer Price Indices. Finally, the values of real income per household were rounded up to serve threshold values for identification of each income group.

Fruit and Vegetable Price Index

During the study period, clear seasonal price variations of some fruit crops (apples, grapes, apricots, cherries, plums) and vegetables (tomatoes, cucumbers, radish) were observed across quarters as substantiated in peaking prices during the winter season.

Based on the interviews with fruit and vegetable market retailers, there were two main sources of supply: home-grown products and those purchased from farmers or wholesalers for further reselling. Wholesalers normally buy fresh foodstuffs from farmers via pickup from the fields. All retailers sell the products to individual consumers at the same market at retail prices, whereas wholesalers sell to retailers at the same market at wholesale prices, and occasionally they sell to individual consumers at retail prices. Prices, in general, can be bargained.

For the current analysis an aggregate index was generated, equalling to an average price for a basket of fruit and vegetables typically available in the area such as apples, grapes, tomatoes and cucumbers. The dynamics of this index in three sample markets is depicted in Fig. 11.5.

Fig. 11.5

(Source Author’s representation based on the Fruit and vegetable market survey)

Dynamics of fruit and vegetable retail price index in 2013–2014, UZS per kilo

It was assumed that these four basic foodstuffs would represent the price dynamics of the general fruit and vegetable category. This assumption was confirmed by exploration of the food consumption survey data, which showed the dominant role of these four crops in domestic consumption in both seasons.

Unfortunately, the absence of primary data on prices for food groups other than fruit and vegetables did not allow controlling for food substitution effects. Seasonal movements and price differences were examined using tabular analyses and t-tests, conducted in Microsoft Excel.

Food Knowledge Index

In order to capture the individual’s knowledge of healthy eating habits, a self-designed index was constructed based on the answers of the person responsible for food preparation and distribution. While developing this index, previous international studies were considered. For example, Parmenter and Wardle (1999) constructed and validated a nutrition questionnaire tool, which was tested among British adults and included four sections, two of which were adopted for constructing the current food knowledge index: awareness of dietary recommendations, and awareness of diet-disease associations. These two components were also found in a three-dimensional health and nutrition knowledge index used by Mancino and Kinsey (2010) in the United States, which also captured the knowledge of how many servings should be consumed.

The data for the food knowledge index used in this study come from the answers to the five questions, covering such modules as food variety, fruit and vegetables, oils and fats and diet-disease associations (Table 11.3). Since the index covers only a limited area of diet awareness and lacks important information on, for example, sources of nutrients, it therefore cannot be appropriate for use in measuring the overall nutritionknowledge.

Table 11.3 Structure of the food knowledge index

Fruit and Vegetable Intake Model

Intuitively, economic factors are very important when making decisions regarding fruit and vegetable consumption. Naturally, more income and lower prices should lead to higher intake. Although this relates to all socio-economic groups, it tends to be more of a concern among those with smaller incomes (Azagba & Sharaf, 2011; Dibsdall, Lambert, Bobbin, & Frewer, 2003).

Sociodemographic factors have been observed to influence fruit and vegetable consumption in various studies. For example, being married might predispose an individual to better access to fruit and vegetables (Franchini, Poínhos, Klepp, & Vaz de Almeida, 2013), while being employed would lead to better knowledge about their benefits for human health (Thompson, Margetts, Speller, & McVey, 1999).

It is rather interesting that intake decreases with age for children (Rasmussen et al., 2006), while it increases for adults (Oliveira, Maia, & Lopes, 2014).

Foodknowledge has been positively associated with intake of fruit and vegetables, as found elsewhere (Beydoun & Wang, 2008; Brug, Tak, te Velde, Bere, & De Bourdeaudhuij, 2008; Lin, Yang, Hang, & Pan, 2007; Yeh et al., 2008).

Thus, based on the quantified variables, representing summer and winter seasons, it was possible to use them for multiple linear regression analysis, by means of ordinary least squares to examine the determinants of fruit and vegetable intake. Similar estimations have been conducted elsewhere (Agudo & Pera, 1999; Ahlstrom, 2009; Amo-Adjei & Kumi-Kyreme, 2014).

The functional form of the model can be expressed as follows:

$$\ln Y_{it} = \beta_{0i} + \beta_{1} W_{it} + \beta_{2} \ln P_{it} + \beta_{2} E_{it} + \beta_{4} Z_{it} + \beta_{5} Season_{it} + \varepsilon_{it},$$

${\text{Y}}_{it}$ :

Intake of fruit and vegetables, log transformed

$W_{it}$ :

Household income level (Base: Lowest income)

$P_{it}$ :

Fruit and vegetable price index, log transformed

$E_{it}$ :

Food and nutrition knowledge index

$Z_{it}$ :

Confounding factors: household size, age, marital status, occupation (Base: Unemployed)

$Season$ :

Data collection season (Base: Summer 2014)

$\varepsilon_{it}$ :

Error term.

In order to control the heterogeneity of different age groups, three focal groups were identified and treated separately: infants aged six months or older and below four years, children aged four years or older and below 15 years and adolescents and adults aged 15 years or older.

Given the panel nature of the sample data and time-invariant personal characteristics such as sex and residence, fixed effects model was employed. All analyses were conducted with STATA statistical software (version 13), using a statistical significance level of 0.05 or less for all tests.

Results and Discussion

There was a significant difference in the total fruit and vegetable intakes between summer 2014 (M = 345, SD = 11.6) and winter 2014/2015 (M = 133, SD = 5.5); t(1860) = 16.48, p = 0.0000. There was a statistical variance in summer intake between urban (M = 372, SD = 16.6) and rural (M = 307, SD = 15.3) residents: t(929) = −2.81, p = 0.0051. This difference, however, vanished in winter.

The found significant seasonal difference is in line with most studies conducted in similar settings. For example, one study found drastic seasonal fluctuations in daily per capita intake of fruit (from 263 grams in summer to 143 grams in winter) and vegetables (221 grams versus 145, respectively) among Iranian households (Toorang, HoushiarRad, Abdollahi, Esmaili, & Koujan, 2013).

Figure 11.6 shows a comparison between recommended and actual levels of fruit and vegetable intakes across different population groups. While average intake in summer 2014 was slightly higher than the mean recommended level, in winter 2014/2015 this indicator was much lower. In the summer period, adult males consumed slightly lower than recommended amounts, whereas children’s consumption was above recommended thresholds. In winter, however, consumption was significantly lower than it should be in all age categories.

Fig. 11.6

(Source Author’s illustration based on the food consumption survey and the recommendations from WHO [2003])

Actual and recommended intakes of fruit and vegetables, grams/day/person

There was no significant gender difference in the total fruit and vegetable intakes between males (M = 236, SD = 10.5) and females (M = 241, SD = 9.0); t(1860) = 0.3609, p = 0.7182. However, straightforward analysis of mean intakes shows that in both seasons, girls consume larger amounts than do boys of the same age, as well as do female adolescents and adults in winter season compared to their male counterparts. The observed gender difference is similar to what has been found in Sweden, the UK and Norway (Rasmussen et al., 2006).

Descriptive statistics of the regression variables are presented in Table 11.4. Overall summary statistics are complemented by the seasonally grouped data.

Table 11.4 Summary statistics of the model variables

The socio-economic profile of households remains the same across two seasons, and the sample data show a predominance of households below the middle-income group, with very few rich families. The foodknowledge index does not vary across seasons and exhibits a rather adequate level of 4.3 out of 6. On the contrary, the fruit and vegetable price index shows a five-fold increase in winter compared to summer, which might partially explain the observed high seasonality pattern in fruit and vegetable intakes.

Whereas half of the adult population was married, one third was unemployed. Average household size of 6.4 is rather large, suggesting possible issues with intra-household food distribution. The average age of the sample is 31 years, reflecting the prevalence of a young population in the national age distribution.

As shown in Table 11.5, the fixed effects model indicates that the fruit and vegetable consumption is quite sensitive to economic factors’ change, which is consistent with classical demand theory, especially for adult females and infants. Being in the ‘highest income’ category compared to the ‘lowest income’ category leads to a tremendous 350% increase in intake of fruit and vegetables in children. This income elasticity is even more striking for infants: a five times increase in intake is associated with being raised in a rich family, all other factors being constant. A similar association (4.6) is found in female adolescents and adults. For this category, any improvement in income leads to higher probability of consuming more fruit and vegetables.

Table 11.5 Parameter estimates of the fruit and vegetable intake regression model

The present study reveals the strong role of socio-economic status in foodconsumption within Uzbekistan. In their analysis of the results of the World Bank’s 2005 Uzbekistan Regional Panel Survey, Musaev et al. (2010) argued that the diet of the poorest households was mostly comprised of cereals (an inexpensive source of nutrients) and much less consumption of fruit.

The found socio-economic gradient in fruit and vegetable consumption pattern is also in line with the results of studies conducted in countries with similar fruit and vegetable intake: in the United Kingdom (Dibsdall et al., 2003), Norway (Bere & Klepp, 2004), Finland (Roos, Hirvonen, Mikkilä, Karvonen, & Rimpelä, 2011) and Sweden (Höglund, Samuelson, & Mark, 1998).

As expected, fruit and vegetable prices serve as another important economic factor in consumption. For instance, for adult females, a 1% increase in fruit and vegetable price index is associated with a 6% decrease in intake of fruit and vegetables, other variables being equal. Similar to income variable, prices affect consumption even greater if it comes to children under four: a more than 17% reduction in intake results from increasing price index by 1 at 5% significance level, ceteris paribus.

Being a nutrient-dense diet, fruit and vegetables are far more costly than energy-dense foods (Darmon & Drewnowski, 2008). In fact, due to cold winters in Uzbekistan, the costs for horticultural growing are extremely high in the off-season, resulting in drastic seasonality of supply (Ali et al., 2006). Strong state control systems over the horticultural volumes and prices limits the flexibility of farmers and, as noted by Bobojonov and Lamers (2008), the lack of information on prices results in poor decision-making activities, given a shortage of knowledge regarding their comparative advantages.

The food knowledge index is statistically significant and positively associated with fruit and vegetable consumption: one unit increase in food knowledge index leads to a 23% (for females) and 30% (for males) increase in intake, with other variables being constant.

The strong correlation observed between knowledge and intake highlights the importance of food and nutrition knowledge, found in other studies too. For example, the study by De Bourdeaudhuij et al. (2008) showed a strong effect of knowledge (awareness of national recommendations) on children’s fruit and vegetable intake in nine European countries.

A straightforward bivariate correlation test showed that household income level narrowly correlates with food knowledge: r(193) = −0.05 in summer 2014 and r(193) = 0.16 in winter 2015, suggesting that even richer families might have a low level of awareness about a healthy diet.

The size of the family positively affects consumption in adults: an additional family member is associated with more than 70% (for females) and almost 95% (for males) increase in intake, ceteris paribus. This positive association possibly reflects the greater wealth often associated with household size and economies of scale because of less waste and the possibility to purchase in bulk associated with larger family size, as found by Robin (1985) in France. While understanding that it is not the household size per se but the dependency ratio within a household that plays an important role in determining the intake levels, in this analysis, however, the dependency ratio was not included in the model due to the complexity of its measurement.

In adolescents and adults, age has a strong negative influence on decisions regarding fruit and vegetable consumption, especially for females. This can be related to the inter-household distribution of healthy food, such as fruit and vegetables, from elder to younger family members. Given the limited sources, adults would care more about the children’s health, limiting their own diet. This finding should be taken with caution, as the age-consumption link is not this straightforward and needs more detailed disaggregation. Obviously, the more age/sex specification, the more precise would be the conclusion. For example, one study by Oliveira et al. (2014) showed that inadequate fruit and vegetable consumption was more frequently found in younger women and men (<40 years) compared to older people (>=65 years).

Seasonality had a surprisingly strong positive effect on intake of infants and women, meaning a significant increase in winter season compared to summer. It can be due to changes in the composition of total fruit and vegetable intakes between seasons as a result of substitution effect. In fact, the survey data showed that such winter fruit as persimmon and quince, as well as such vegetable products as pickles increased considerably in winter. It might be true that the winter season does increase consumption of fruit and vegetables in women and infants in relative terms, because in most cases being better aware of health benefits of fruit and vegetables, women are responsible for health and diet in the family, and therefore they try to increase the winter intake in order to smoothen a year-long consumption. This hypothesis is supported by the survey data showing that female adults are indeed consuming larger amount of fruit and vegetables in winter compared to men. The positive association between winter season and intake can also be related to possible flaws with the use of the generic price index. In particular, any association between season and intake disappears after separating price effects into grapes and cucumber prices.

For adults, the effects of being married and employed on fruit and vegetable intake are not statistically significant, while age, foodknowledge and household size are statistically non-significant for infants and children.

Conclusion

For this analysis, a food consumption survey was conducted for the first time in the last 30 years, filling an important geographic gap in the dietary analysis, as Uzbekistan remains one of the countries where determinants of fruit and vegetable consumption have been understudied.

It is hoped that the results from this evidence-based study will lay the ground for future research on fooddemand in the Central Asian region. Being in line with the work by Mirzabaev (2013), who found that the Uzbekistan households’ food consumption is quite sensitive to agricultural income changes, this paper underlines the strong role of economic factors in people’s diet.

This conclusion should give rise to a more balanced and harmonious policy approach to tackle nutrition and well-being issues in Uzbekistan. An expected negative effect of market prices on individual-level intake demonstrates a high price elasticity of nutrient-dense diet, which would give a greater emphasis on the importance of measures on improving a year-long fruit and vegetable supply, including protected cultivation and post-harvest handling technologies.

The fact that income and price elasticities were found the strongest in infants compared to older children and adults, should gain a particular attention for policy-making, given the crucial significance of healthy diet at this age for further physical development.

The positive association between foodknowledge and intake of fruit and vegetables, found in adults, highlights the importance of raising awareness about a healthy diet. This should eventually result in encouraging healthier eating habits among children.

In order to increase demand for fruit and vegetables, the state policies should consider providing subsidies and other incentives to help low-income families purchase more fruit and vegetables, with particular focus on children’s diet. According to DiSogra (2014), such strategies include free fruit and vegetable snacks and vouchers for students from low-income families.

Although the study showed the overall good knowledge about a healthy diet, the awareness of some aspects requires improvement. In addition, there is a lack of basic education and training in food hygiene and safety at technical and educational institutions, as well as inadequate information services and a lack of resources for programmes studying nutrition.

In this regard, educational programmes, which would aim at building capacity in dietary recommendations and implications for human health, will be useful in reaching appropriate dietary change. There is a need for public campaigns that give advice on improving variety, increasing healthy foods (such as fruit and vegetables) and cutting down unhealthy meals.