1. Introduction
Food systems in developing countries have been evolving rapidly in the last few decades, with a growing role played by modern retailers such as supermarkets, hypermarkets, convenience stores, and fast-food restaurants [
1,
2,
3,
4]. The modernization of food systems is largely driven by consumer preference changes resulting from urbanization, income growth, and globalization [
5,
6,
7,
8,
9]. However, at the same time consumer preferences and demand may also be shaped by changing food environments [
10,
11,
12]. For example, a shift from traditional markets to modern supermarkets and hypermarkets has effects on the types of food offered, as well as on food variety, food prices, and shopping atmosphere, all of which may influence consumer choices [
3,
13,
14,
15]. Understanding the links between changing food environments and food consumption patterns is important to promote food security and healthy diets. This is especially true in Africa, where poverty and undernutrition are still widespread, but where being overweight and obesity are also on the rise [
16,
17,
18]
Available research suggests that the modernization of food retailing may make calories more affordable for urban consumers but—at the same time—may foster the nutrition transition towards more highly processed foods that are rich in fat, sugar, and salt, but contain low amounts of micronutrients and other ingredients for healthy nutrition [
1,
12,
19,
20]. Recent studies with data from different countries in Africa, Asia, and Latin America suggest that the growth of supermarkets may contribute to increased consumption of processed foods and a higher body mass index (BMI), after also controlling for household income [
13,
18,
21,
22,
23,
24]. However, especially in Africa, relatively little is known about what type of consumers actually use modern supermarkets and to what extent. Moreover, focusing only on supermarkets may be misleading, as most consumers obtain their food from various modern and traditional retailers [
8,
25,
26,
27].
Here, we add to the existing literature by analyzing more explicitly the associations between household socioeconomic status, the use of different types of retailers, and dietary patterns in urban Africa. In particular, we use household survey data from urban Zambia to analyze what type of socioeconomic characteristics are associated with the choice of modern and traditional food retailers, and to what extent the use of different retailers is associated with the consumption of processed and unprocessed foods, and products belonging to different healthy and unhealthy food groups. To our knowledge, this is the first study that looks into these issues with detailed data from Africa.
Zambia is an interesting empirical setting for this analysis, because it has recently experienced rapid growth of supermarkets, hypermarkets, and other modern retailers [
5]. Moreover, Zambia is experiencing a triple burden of malnutrition, where undernutrition and micronutrient malnutrition coexist with rising overweight and obesity [
17,
28]. Hence, our results may help to project how diets evolve with further changes in retail environments and what type of policy responses might be useful. We expect that the insights from Zambia can be useful also for other countries in Africa, where the modernization of the food retail sector is still in its earlier stages.
The rest of this paper is organized as follows.
Section 2 provides an overview of the most important types of modern and traditional food retailers in Zambia.
Section 3 explains materials and methods, including a description of the household survey, the measurement of key variables, and the econometric models used.
Section 4 presents and discusses the results, while
Section 5 provides the conclusions.
2. Modern and Traditional Food Retailers in Zambia
Food retail environments in many African countries have been changing rapidly during the last 20 years, with a considerable growth of modern retailers such as supermarkets and hypermarkets [
5,
29]. Zambia is one of the countries in the Southern African region with particularly high growth rates of modern retailers [
29,
30]. For instance, our own review of internet sources supplemented by key informant interviews in the local context revealed that the number of large shopping malls in Lusaka City increased from one in 1995 to 25 in 2018 (
Table S1 in the Supplementary material). These shopping malls with a big variety of shops are also the main locations of supermarkets, hypermarkets, and fast-food restaurants. Most of these modern retailers are almost homogenous in product offerings across countries in Africa. For instance, supermarket retail giant like Shoprite; Africa’s largest food retailer is operating more than 2738 outlets in 15 African countries (Angola, Botswana, Democratic Republic of Congo, eSwatini, Ghana, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Nigeria, South Africa, Uganda and Zambia) [
31]. Smaller supermarkets and convenience stores are also found in other locations. In the following, we characterize the main types of modern food retailers that we also use in the empirical analysis below. We characterize the most important types of traditional food retailers as well. An overview of the key characteristics of each type of retailer is shown in
Table 1. The classification builds on criteria similar to those used in previous studies [
22,
24,
25], partly adjusted to the local context based on key informant interviews.
The largest modern retailers are hypermarkets with a floor space of more than 200 m2. The main hypermarket chains in Lusaka are Game Stores, Cheers, and Choppies. Supermarkets are similar to hypermarkets, but are smaller with 100–200 m2 of floor space. Major supermarket chains in Lusaka include Shoprite and PicknPay, among others. Both hypermarkets and supermarkets are self-service stores with a wide range of fresh and processed products, including chilled and frozen foods. Convenience stores also belong to the category of modern retailers. They are also self-service in nature but are smaller (<100 m2) and offer a more limited range of food products.
Finally, we include fast-food restaurants—such as Hungry Lion, Debonairs Pizza, and KFC—in the group of modern retailers (
Table 1).
Traditional food retailers include grocery stores, traditional markets, roadside markets, and neighborhood kiosks (
Table 1). None of the traditional retailers have self-service options, all providing over-the-counter services. Traditional retailers are mostly owner-operated and do not belong to larger chains. Customers can negotiate prices to some extent and can usually also buy foods on credit. The range of products and brands offered by traditional retailers is smaller than that offered by modern retailers. Packaging sizes are also smaller. Sometimes traditional retailers repackage foods such as sugar, flour, or cooking oil, into very small packets, which are particularly demanded by poor customers. Traditional retailers rarely sell frozen and chilled foods, mostly due to lack of refrigeration facilities.
3. Materials and Methods
3.1. Household Survey
The data used in this study were collected through a household survey in Lusaka, the capital city of Zambia, between April and July 2018. We surveyed a total of 475 households using a two-stage random sampling procedure. At the first stage, we purposively selected 14 compounds within Lusaka urban. These compounds were selected based on the locations of major shopping malls as well as information provided by the City Council on mean income levels in the different compounds. Based on population distributions, we selected four compounds with high mean income levels (Avondole, Chalala, Kabulonga, Woodlands), four compounds with medium income levels (Chelston, Chilenje, Kabwata, PHI), and six compounds with low income levels (Chawama, Chazanga, Gardens, Kalingalinga, Kaunda Square, Ng’ombe). At the second stage, depending on compound size, we randomly sampled around 34 households from each compound for study participation. The spatial distribution of selected compounds and households is shown in
Figure S1 in the Supplementary material. The sample should be fairly representative of households in the urban parts of Lusaka.
In each of the sample households, we carried out a face-to-face interview with the household head or another adult responsible for food purchase decisions. The computer-aided structured interviews were conducted in the local language by a small team of interviewers that we recruited, trained, and supervised. The questionnaire that we had developed for this purpose captured general economic and socio-demographic information of the household and its members. Food consumption data were collected through a 7-day household-level recall, using a detailed list of food items typically consumed in the local setting. In addition to food quantities and expenditures, we also collected data on the processing level and the source of each food item, focusing particularly on the different modern and traditional retailers. These data were used to construct various key variables, as discussed below.
3.2. Measurement of Key Variables
We are interested in analyzing the relationship between socioeconomic characteristics and use of different retailers. Socioeconomic characteristics of interest include household income levels, education, gender, and age of the household head, household size and structure, ethnicity, religion, car ownership, among others. Previous research showed that these characteristics can influence the decision of which retailers to use [
13,
15,
22,
23,
24,
32]. The use of different retailers is measured through a set of dummy variables capturing whether or not the household purchased any food from a particular type of retailer during the 7-day recall period. In addition to the retailer dummies, we also examine the share of the total household food budget spent in different retail outlets.
We are also interested in analyzing associations between the use of different retailers and dietary patterns. One way of looking at dietary patterns is through classifying all food items consumed by their level of processing. We differentiate between unprocessed foods, primary processed foods, and ultra-processed foods [
24]. For these three processing levels, we calculate household expenditures and food expenditure shares. Unprocessed foods include wholegrain cereals and pulses, fresh fruits and vegetables, eggs and fresh milk, among others. Primary processed foods include milled cereals and fresh meat and fish. Ultra-processed foods include bread, pasta, dairy products, sausages and meat products, soft drinks, sweets, and other ready-made dishes and snacks (
Table S2 in the Supplementary material). Ultra-processed foods are generally considered less healthy than unprocessed foods, because they often have high sugar, fat, and salt contents, and low fiber and micronutrient contents. Research has shown that high consumption of ultra-processed foods is associated with obesity and increased risks of chronic diseases such as coronary heart diseases, stroke, and diabetes [
17,
28,
33,
34]. Separate indicators of dietary patterns that we use are the quantities of different food groups consumed by the households during the 7-day recall period. We use the following food groups: cereals and tubers, legumes, fruits, vegetables, meat and fish, dairy products, eggs, oils and fats, and sugar and sugar-sweetened beverages. While the last two food groups are considered as rather unhealthy, the others contain important nutrients and can therefore contribute to healthy nutrition.
3.3. Statistical Analysis
We start the analysis by calculating descriptive statistics for the use of modern retailers and dietary patterns and comparing between households of different socioeconomic status. For this purpose, we subdivide the sample into three groups of almost equal size, namely the lower, middle, and upper income terciles. In addition, we use regression models to analyze the associations of interest more formally.
To analyze the socioeconomic factors that influence the use of different types of retailers, we estimate models of the following type:
where
is a vector of the types of food retailers that household
i used during the 7-day recall period,
is a vector of socioeconomic variables, and
is a random error term.
is measured through a set of dummy variables, one for each of the modern and traditional retailers considered, so that we use a probit specification to estimate Equation (1). Households can use more than one type of retailer, and the decisions for different retailers are likely correlated. We use a multivariate probit model to account for possible error correlation between the equations for different retailers [
35].
Next, we analyze how far the use of particular retailers is associated with more or less healthy dietary patterns by estimating regression models of the following type:
where
characterizes the observed dietary pattern of household
, and
is the random error term.
is a vector of variables representing the food expenditure shares of each of the retailers, and
is a vector of socioeconomic characteristics. In one set of regressions,
will characterize expenditures for foods with different processing levels, while in another set of regressions
will characterize the consumption of different healthy and unhealthy food groups.
For the processing level equations, we use an ordinary least squares (OLS) estimator. As error term correlation between the different equations is possible, we also use a seemingly unrelated regression (SUR) estimator to compare the results. Furthermore, in addition to estimates with the full sample, we estimate separate models for households below and above the poverty line, as the role of modern retailers may potentially differ by socioeconomic status. For the food group equations, we use a Tobit estimator, because the consumption quantities are left-censored at zero. To account for the heterogeneity among the sampled households, for all models, standard errors are clustered at the level of city compounds.
We start estimating the models in Equation (2) by only considering one food retailer in
, namely supermarkets. This is similar to previous studies that have analyzed the effects of supermarkets on diets and nutrition [
13,
22,
23,
24,
32]. However, conclusions based on such models that only consider the use of supermarkets may be incomplete, as households typically use various types of retailers. To demonstrate this, we re-estimate the same models with all types of retailers included. We note that the use of food retailers (vector
) is endogenous, so the estimated
δ coefficients from Equation (2) should not be interpreted as causal effects. Using instruments to deal with possible endogeneity bias would be possible in principle, but is difficult in our case, with a total of eight endogenous variables. We were unable to identify eight valid instruments, which is why we interpret the estimated coefficients only in terms of associations.
5. Conclusions
Many countries in Africa are experiencing a rapid modernization of their food retail sector, with supermarkets, hypermarkets, modern convenience stores, and fast-food restaurants gaining in importance. These changing food environments, especially in urban areas, may influence consumers’ food choices, dietary patterns, and nutrition. Previous research has suggested that the spread of modern retailers may contribute to less healthy diets, higher consumption of ultra-processed foods, and rising rates of overweight and obesity. However, previous studies did not pay much attention to the question as to which socioeconomic groups use what type of retailers. Furthermore, the existing research on diet and nutrition effects focused primarily on the role of supermarkets, without accounting for the fact that most consumers obtain their foods from various types of retailers. We have added to this research direction by more explicitly analyzing the associations between household socioeconomic status, the use of different types of modern and traditional retailers, and dietary patterns. We have collected and used data from households in Lusaka City in Zambia, one of the places in Southern Africa where food environments have changed dramatically in recent years.
Our results show that almost all households use different types of retailers on a regular basis. Two-thirds of the households use modern and traditional retailers simultaneously. Among the modern retailers, supermarkets account for the largest share of the food purchases, followed by modern convenience stores and hypermarkets. Overall, in Lusaka City, modern retailers account for 42% of the household food expenditures on average, although with notable differences between poor and rich households. Modern retailers account for 20% and 63% of total food expenditures in the lowest and highest income tercile, respectively. Income is also an important predictor of the use of modern retailers after controlling for other socioeconomic variables. Other variables that increase the likelihood of using modern retailers are education, car ownership, having an office job, and female household heads. Supermarkets and hypermarkets, in particular, offer a large variety of products, which consumers perceive as safe and of high quality. Supermarkets and hypermarkets also have longer and more reliable opening hours than most traditional retailers. All of these factors make supermarkets and hypermarkets attractive shopping places especially for better-off households with high opportunity costs of time.
The regression analysis also shows that using supermarkets is associated with a higher consumption of ultra-processed foods and a lower consumption of unprocessed foods, also after controlling for income and other socioeconomic variables. This is in line with earlier research on the dietary effects of supermarkets [
19,
21,
22,
24,
32]. From a nutrition and health perspective, these dietary trends are undesirable, as high consumption of ultra-processed foods is associated with increased risks of obesity and chronic diseases [
10,
28,
33,
34]. However, unlike earlier studies, we also analyzed the role of other retailers and found that especially the use of traditional grocery stores and neighborhood kiosks is also associated with higher consumption of ultra-processed foods. These results suggest that there is a general shift towards the consumption of ultra-processed foods that cannot be attributed to modern retailers alone.
We also analyzed the consumption of different food groups and found that the use of modern retailers is associated with higher consumption of certain unhealthy food groups (sugar, sweets, oils, fats), but also with higher consumption of certain healthy food groups (meat, fish, dairy products). At the same time, the use of some of the traditional retailers—such as grocery stores, traditional markets, and kiosks—is also associated with higher consumption of unhealthy food groups.
Many countries in Africa are experiencing a nutrition transition with both positive and negative implications. On the positive side, the consumption of some nutritious foods is increasing. On the negative side, the consumption of sugar, fat, and salt is increasing as well. Changing food environments seem to influence and support these dietary trends and should, therefore, also be seen as potential entry points for public regulations and policies to support more healthy diets. Policy options to consider are regulations related to the advertisement and promotion of healthy and unhealthy foods and their strategic placement within shops. For instance, in studies referring to industrialized countries, the authors of [
46,
47] showed that changes in the placement of fruits and vegetables can positively influence consumer choices. Related regulations could also be relevant for countries in Africa. In urban Zambia, the consumption of fresh fruits is particularly low; policies to increase fruit consumption levels would be useful. Beyond advertisement, awareness campaigns, and nudges, taxes and subsidies could also be options to promote healthy diets. A detailed discussion of policy approaches is beyond the scope of this article. In any case, our results emphasize that modern retailers are not the only drivers of dietary transitions, so that a focus on regulating modern retailers alone would be insufficient to promote healthy eating.
In closing, three limitations of our research should briefly be discussed. First, we used processing level categories, which could not sufficiently classify the degree of healthfulness of a specific food. Moreover, the three categories (ultra-processed, primary processed and unprocessed foods) could not properly account for the overlap in nutritional attributes for some food products. Second, we used observational data and could not control for the endogeneity of households’ decisions about which retailers to use. Therefore, our results are interpreted only in terms of associations, not as causal effects. Proper identification is difficult with observational data, but longer-term studies with panel data may possibly help. Third, results from Lusaka City in Zambia are not necessarily representative for other parts of Africa. Follow-up research in different geographical contexts would be interesting to further broaden the knowledge base.