Consumer’s Awareness and Willingness to Pay for Aflatoxin-Free Sunflower Oil from Four Selected Regions in Tanzania

Abstract

This study aimed to answer two objectives: assessing consumer awareness of aflatoxin contamination in food and their willingness to pay (WTP) for aflatoxin-free sunflower oil, and investigating the factors influencing consumers’ WTP a premium price for aflatoxin-free sunflower oil. A total of 480 consumers were randomly selected from four towns, and the towns were selected based on the level of aflatoxin contamination incidences: Dodoma (low awareness) and Iringa (high awareness) (towns with high contamination), and Dar es Salaam (low awareness) and Morogoro (high awareness) (towns with low incidence). To elicit consumers’ willingness to pay for aflatoxin-free food, we used the multiple price list technique (MPL) to assess WTP for sunflower oil which is aflatoxin-free and sunflower oil which has not been tested to be aflatoxin-free. Furthermore, an interval regression model was used to estimate WTP and factors influencing WTP a premium price for aflatoxin-free sunflower oil. We found that consumers were willing to pay a premium price for aflatoxin-free sunflower oil. Consumers had a WTP for a premium of up to 1043 TZS for 1 L of aflatoxin-free sunflower oil. However, the premium varies in the different regions. Consumers from towns with a high incidence of aflatoxin contamination have a WTP of up to 357 TZS, while those from towns with a low incidence of aflatoxin contamination but high awareness have a WTP of up to 1043 TZS. Furthermore, the study finds that education, age, gender, and consumer awareness of aflatoxin contamination have a significant influence on the WTP for sunflower oil free of aflatoxin contamination. This study sheds light to stakeholders involved in the production, marketing, and monitoring of food safety and standards. For the public sector, to maximize consumer welfare, policies to ensure the delivery of safe and healthy food are important, while for the private sector, there is an opportunity to tap into the gap for supplying food with private food safety standards.

1. Introduction

Food safety has become an increasingly important concern for consumers worldwide, particularly as the global food supply chain becomes more interconnected and complex. Aflatoxins are among such food safety concerns that have garnered significant attention due to their adverse effects on human health. Aflatoxin contamination is particularly relevant to the production and consumption of sunflower oil in Tanzania, where this product is a key staple in the local diet. Aflatoxin is a secondary metabolite produced by mold, mostly by Aspergillus flavus and Aspergillus parasiticus [1]. They are commonly found in cereals and nuts such as maize and ground nuts, where they appear in four main forms: aflatoxin B1 (AFB1), B2 (AFB2), G1 (AFG1), and G2 (AFG2). AFB1 is among the most potent carcinogenic compounds found in human and animal foods [2]. Consumption of foods containing aflatoxins has been associated with liver cancer, weakened immune systems, impaired child growth, and death [3,4]. Health outcomes such as liver cancer and immune suppression can be exacerbated when such foods are deficient in essential nutrients as is the case in developing countries where most people depend on cereal-based diets [5]. Acute toxicity of aflatoxin is exemplified by the aflatoxicosis which occurred in Kenya in 2004. In that year, 317 people including children became ill and 125 of them died after consuming aflatoxin-contaminated cereals [6,7,8]. Aflatoxin contamination in crops is possible along the food chain, throughout plant growth, maturation, harvesting, storage, and processing [9]. Fungi infection can be induced when maturing crops are under drought conditions and during prolonged periods of hot weather [9,10]. Contamination during storage of the crop can occur if moisture and relative humidity, oxygen availability, temperature, time, and damaged or broken grain kernels are allowed to go to critical levels [7,11]. A flavus comes in contact with crops before harvest; it however remains associated with the crop through harvest and storage [12,13]. Thus, seed grains become contaminated with aflatoxins both before and after harvest [2]. The contamination is, however, more likely to occur in the post-harvest stage if the produce is not handled properly to minimize the thriving of the fungal species [14]. Poor harvesting practices, inappropriate storage, and less-than-optimal situations during transport and marketing can also contribute to fungal development and increase the risk of aflatoxin production [15].

Therefore, due to the deviations in the food system that bring about an increase in the consumption of processed food in Tanzania, especially in urban areas as reported by [16], the likelihood of aflatoxin contamination of food products is increasing. Ref. [17] explained that consumers are the last stakeholders in the food value chain; therefore, they have less control over what is going on in the food value chain, as the risk of aflatoxin contamination and pervasiveness variations as foodstuffs pass along the value chain. Thus, it is of great importance that they are provided with a way to distinguish between safe food and contaminated food [18]. Sunflower oil is widely consumed in Tanzania, as it is a rich source of essential fatty acids and is used extensively for cooking and frying [19]. The potential contamination of sunflower oil with aflatoxins poses a significant public health concern, and understanding consumer awareness and WTP for aflatoxin-free sunflower oil can provide crucial information for the development of effective food safety policies and strategies.

1.1. Consumer Preference and WTP for Food Safety

Studies on consumer preferences suggests that safety, nutrition, and taste are among the most important product attributes to a consumer in developed [20,21] and developing countries such as Tanzania [22,23,24]. These studies report that food safety and the attitude towards healthy eating are especially important when there are health concerns and the introduction of unfamiliar technology [21]. However, WTP for food safety depends on various factors, including food values, knowledge (awareness) [22,25,26,27], and social, economic, and demographic characteristics [27,28]. For example, Ref. [26] found very poor awareness of food safety problems among consumers in Sub-Saharan Africa, attributing this to producer behavior towards food safety. On the other hand, Ref. [29] found trust and perceived risks were the main determinants of WTP for safer green vegetables, with wealth playing a minor effect, while [26,28] found that gender and income have a significant impact on WTP for food safety. They found that even though female consumers are paying less for tomatoes, they are WTP significantly more for organic and inspected tomatoes. Other studies found age, knowledge, education, and income to have a significant influence on consumer WTP for organic and healthier products [6,27,30]. For example, Ref. [6] discovered that education and income had a substantial impact on consumer WTP for the safety of street food in Nigeria, while [27] found that gender, access to food safety information, acquaintance with organic products, monthly income, and nutritional knowledge of the food planner to have a significant impact on the WTP for organic beans among consumers in Southwest Nigeria. Ref. [27] found that being a woman, older, and with high income positively influence WTP for organic beans. Although several studies have been carried out on consumer WTP for food safety in Africa [31,32], little is known about African consumer awareness and WTP for aflatoxin-free products. Hence, this study will contribute to the understanding of consumer awareness of aflatoxin contamination and their WTP for products that are free from aflatoxin contamination. This study will shed light on this issue to stakeholders involved in the production, marketing, and monitoring of food safety and standards. This study can be used by both the private and public sector in bringing about a more sustainable food system.

Consumers must first be aware of aflatoxin contamination to protect themselves against it, since a lack of knowledge about it increases the likelihood that they may sustain harm [33]. Researchers have conducted several studies on consumer awareness and willingness to pay for food safety, and results show that awareness can be interpreted in various ways. For example, a study carried out by [34] specified that, in rural areas most affected by aflatoxins, consumers are aware of them, but few are knowledgeable of the possible health risks posed by aflatoxins. That is why this study went ahead and required consumers to state what exactly they know about aflatoxins to make sure that consumers that claim to know about aflatoxins have correct information about what they are. In other studies, education played an important role in influencing the awareness of consumers, such as the study by [13]. Aflatoxin contamination is one of the risks associated with food safety that people who have higher education are more aware of than those who do not have higher education. According to [35], consumers are exposed to aflatoxins through the consumption of low-quality food due to inadequate knowledge of aflatoxins and their impacts on health. To determine the awareness of the health threat of consuming aflatoxins in food, the International Institute of Tropical Agriculture (IITA) conducted an aflatoxin information campaign in some Tanzanian regions in 2012. The study concluded that there is poor baseline information on aflatoxins among consumers.

1.2. Factors Influencing WTP

Various factors can influence individuals’ willingness to pay, including their social, economic, and demographic circumstances [11,32]. Ref. [11]’s research revealed that trust and perceived risks were the primary determinants of willingness to pay for safer green vegetables, while wealth had a lesser impact. In predicting the likelihood that smallholder farmers in Kenya will use Aflasafe, Ref. [36] discovered that formal education, family income, and county of residency had the greatest effects on the WTP. Other studies found that respondents’ age and household size influence consumers’ WTP higher prices for healthier products [33], while [28] found that consumers’ willingness to spend more for organic food depended on their age, nationality, education, household size, and income. When evaluating the WTP for the safety of street food in Nigeria, ref. [6] discovered that education and income had a substantial impact on WTP. When analyzing farmers’ perceptions of and willingness to pay for Aflasafe KE01 in Kenya, another study found that income, gender, and age positively affected WTP among farmers whereas household size and distance to the market adversely influenced WTP [37].

There are few reports in the literature indicating that A. flavus and A. parasiticus can infect sunflowers and cause aflatoxin accumulation in seeds and cakes [37]. Ref. [38], in their study on aflatoxin levels in sunflower seeds and cakes collected from micro- and small-scale sunflower oil processors in Tanzania, found that there was a high number of aflatoxins in the sunflower sample collected; this implies that aflatoxins can also be found in sunflower oil even after being processed. That is why sunflower oil was used as the case product for this study.

This study required consumers to state their knowledge about aflatoxins to ensure that those who claim to know them have accurate information about them. Not only that, but consumers were also required to state their willingness to pay for sunflower oil that is free from aflatoxins contamination in the urban areas of Dar es Salaam, Dodoma, Morogoro, and Iringa. Since the literature shows that most, if not all, studies about aflatoxins and aflatoxin interventions in Tanzania were conducted in rural areas and primarily with farmers [38,39,40,41,42,43,44,45,46,47]. Two research questions helped to know if specific objectives were assessed: what is the level of consumers’ awareness of aflatoxins in sunflower oil?, and what are consumers’ WTP and factors influencing WTP for aflatoxin-free sunflower oil? It is essential to note that the study intends to shed more light on the awareness of consumers towards aflatoxins and how willing they are to pay for sunflower oil that has been tested and certified as safe for human consumption. It will also enable all stakeholders involved in the production, marketing, and monitoring of food safety to know the measures to take to ensure consumer safety. Additionally, the information generated from this study on the awareness and willingness to pay for aflatoxin-free sunflower oil will be vital for its commercialization. If the consumers’ willingness to pay for the product is positive, the outscaling, upscaling, and commercial capability of the products will be justified.

2. Methodology

2.1. Theoretical Framework

This research used a consumer behavior theory, which explains that consumers decide to balance the marginal health utility and marginal price of one unit of quality-improved food. The marginal health utility lies in the awareness and perception of risks, which are determined by the consumer’s socio-economic characteristics, learning ability, and exposure levels to food-borne hazards [48], and because safety is a food “attribute”. Then, by considering Lancaster’s consumer theory [49], goods are considered a bundle of attributes, and consumers’ preferences will be stated over those attributes.

The basic equation of Lancaster’s consumer theory is:

U = f (x1, x2, …, xn)

(1)

where:

U is the consumer’s utility or satisfaction;

x1, x2, …, xn are the different characteristics or attributes of the goods or services being consumed;

f is a function that maps the combination of characteristics to utility.

2.2. Research Design and Sampling Procedure

The research was conducted in four regions: Morogoro, Dodoma, Iringa, and Dar es Salaam, specifically targeting urban districts. The purpose of selecting these regions was to capture a diverse range of consumers, particularly those who consume processed foods such as sunflower oil. The selection of these regions was based on their unique characteristics, as indicated by previous studies on aflatoxin contamination levels and awareness in those areas [2,15,38,39,40,41,43,44,45,46,50]. Dodoma was chosen due to its history of aflatoxin outbreaks and low awareness. For instance, in 2016, there were 68 cases and 20 deaths attributed to aflatoxin poisoning, primarily affecting the central part of Tanzania, particularly Dodoma [2,15,41].

Dar es Salaam was selected for its low awareness of aflatoxins in food, high number of processed food consumers, and diverse consumer base, as reported by [40]. Iringa, on the other hand, was included because of the high incidence of aflatoxin cases and presumed high level of awareness regarding aflatoxins in food, as indicated by [38]. Morogoro was selected because of the low level of aflatoxin contaminations that have been reported in multiple studies performed on different crops, for instance, the study by [38,51]. All these studies were performed in Morogoro and found a low level of aflatoxin contamination of foodstuff in Morogoro.

To collect the required data, a cross-sectional design was employed, given its suitability for gathering data from a specific population sample at a single point in time. The study areas were purposively selected based on their unique characteristics. The target respondents for this study were consumers above 18 years old who could provide economic information on behalf of the household head. The sample size comprised 480 consumers from the four districts, with each district consisting of 120 consumers. Furthermore, each district was divided into two groups: 60 consumers from the high-end market and another 60 from the low-end market. This distribution allowed for the inclusion of both high-income and low-income consumers by selecting markets from different socioeconomic segments within each municipality.

2.3. Demographic Factors

The information was gathered by a standardized questionnaire, and information coded before analysis. The first specific objective was analyzed by gathering descriptive statistics such as frequency tables, percentages, and means, to analyze respondents’ level of awareness about aflatoxins in food using STATA 15 software.

2.4. Introduction to Multiple Price List and Experimental Design

The study used multiple price list method to obtain data on WTP of consumers for safe sunflower oil in the study areas. Multiple price list (MPL) is an extension of the real dichotomous choice (RDC) used by [52] in their MPL experiment; each participant was given a list with the following statement: “At a price of X, I will buy______; I will not buy______”, with values ranging from $0.25 to $8.75. For each value, the participant was asked to check either “I will buy” or “I will not buy”. At the end, the monitor selected one row from the list at random and the participant’s choice for that row was implemented [53].

To capture information on consumers’ willingness to pay, we provided respondents with a card without giving them any more information. The card contained two different pictures of 1 L of sunflower oil. One picture showed the unlabeled oil to indicate that we did not know its status (status quo), while the other 1 L oil was labeled “tested and certified free from aflatoxin”. The exercise asked respondents to consider that the current sunflower oil needed replacement and invited them to think about oil that is tested and certified as safe and free from aflatoxin contamination. The description of the choice made clear that the new sunflower oil was going to prevent them from eating food that is contaminated by aflatoxins and prevent them from contracting the diseases that were likely to be caused by eating food that has aflatoxins.

In the MPL format, under the pictures of sunflower oil, participants were given an array of ordered prices in a table, one per row, starting from the smallest price of 2500 TZS to 8000 TZS and asked to indicate whether they are willing to buy a product at each price level. They were supposed to put a tick for all the prices in a row that they think they will be able to pay for the product until the maximum amount that they think they cannot exceed. This was carried out for both status quo and aflatoxin-free oil cards presented to them. The study used the intreg command to run the interval regression analysis, with the lower limit being the maximum price the consumer selected and the upper limit being the minimum price the consumer did not select.

2.5. WTP and Factors Influencing WTP

The second specific objective was analyzed using an interval regression model. Interval regression models are used in statistical analysis to model variables that are measured on an interval or ratio scale but are subject to censoring or truncation [54]. Censoring occurs when the true value of the variable is unknown, but we know that it falls within a certain range. Truncation occurs when we only observe values above or below a certain threshold [54]. Interval regression models can provide more accurate estimates of the parameters of the underlying distribution than other methods. This is because they consider the fact that some observations are censored or truncated, which can bias the estimates if ignored.

To motivate this model, the respondent’s true valuation or WTP is assumed to follow a linear function as given in the following equation:

Y_i* = β₀ + β₁X_i + ε_i

(2)

where:

Y_i* is the latent dependent variable representing willingness to pay for the i^th observation, which is not directly observable;

β₀ is the intercept, representing the expected willingness to pay when all the independent variables are equal to zero;

β₁ is the slope coefficient for the independent variable X_i, representing the expected change in willingness to pay for a one-unit increase in X_i, holding all other variables constant;

X_i is an independent variable that is believed to influence willingness to pay;

ε_i is the error term, representing the deviation of the observed willingness to pay (Y_i) from the expected willingness to pay (Y_i*).

Because willingness to pay was subject to censoring, we modeled it using an interval regression approach, by letting L_i and U_i denote the lower and upper bounds of the censoring interval, respectively, for the i^th observation. Then, the observed willingness to pay Y_i was:

Y_i = L_i + (U_i − L_i) × Z_i + Y_i*

(3)

where:

Z_i was an indicator variable that took the value 0 if Y_i is observed (not censored) or 1 if Y_i is censored;

Y_i* was the latent dependent variable representing willingness to pay, which is normally distributed with mean E(Y_i*) and variance σ²;

L_i and U_i were the lower and upper censoring points, respectively, for the i^th observation. The lower limit used was the maximum price the consumer selected and the upper limit being the minimum price the consumer did not select.

3. Results and Discussion

3.1. Social Economic Characteristics

Table 1. Social economic characteristics.

	POOLED	DODOMA	MOROGORO	IRINGA	DAR ES SALAM
Gender	Frequency (%)	Frequency (%)	Frequency (%)	Frequency (%)	Frequency (%)
Female	275 (57.3)	72 (60)	73 (60.8)	74 (59.2)	67 (56)
Male	205 (42.7)	48 (40)	47 (38.2)	51 (40.8)	53 (44)
Education
0–7	157 (32.7)	47 (39.2)	28 (23.3)	48 (38.4)	38 (31.9)
8–11	119 (24.8)	38 (31.7)	27 (22.5)	27 (21.6)	32 (26.1)
12–15	85 (17.7)	18 (15.6)	55 (45.8)	25 (20)	25 (21)
16 and above	119 (24.7)	17 (14.2)	10 (8.3)	25 (20)	25 (21)
Age
20–30	214 (44.6)	67 (55.8)	58 (48.3)	36 (28.8)	49 (41.2)
31–40	139 (28.9)	40 (33.3)	52 (43.3)	41 (32.8)	32 (26.9)
41–50	74 (15.4)	8 (6.7)	10 (8.3)	20 (16)	27 (22.7)
51 and above	53 (11.1)	5 (4.2)	9 (7.1)	27 (21)	12 (9.3)
Household size
1–3	230 (47.9)	55 (45.8)	56 (46.6)	71 (56.8)	53 (44.5)
4–6	214 (44.7)	60 (50)	51 (42.5)	50 (40)	56 (44.)
7 years and above	35 (7.4)	5 (4.2)	13 (10.9)	4 (3.2)	11 (9.5)
Monthly income
15,000–100,000	13 (2.7)	0 (0)	3 (2.5)	8 (6.4)	3 (1.8)
110,000–500,000	240 (50)	74 (61.7)	39 (32.5)	68 (54.4)	67 (57.2)
510,000 and more	225 (46.9)	46 (38.3)	78 (65)	49 (39.2)	48 (40)

Note: Numbers in parenthesis are percentage.

reports the social-demographic characteristics of our sample. Out of the 480 consumers interviewed, 42.7% were male and 57.3% female. In a developing country such as Tanzania, female consumers are more involved in food decision making and grocery shopping [28,55]. Furthermore, because the study only included food decision makers, 44.6% of the consumers were between 31 to 40 years old, hence not nationally representative, where 50% of the population in Tanzania is 18 years old [19]. In the study, the level of education of respondents differed between regions with the majority having at least attained primary education for most of the regions except for Morogoro, where most respondents were found to have at least a first degree. Among the respondents, 68% are families with children and the remaining are either married without children or single. The study also found that most of the consumers’ income ranged between 110,000 TZS and 500,000 TZS per month for all regions surveyed except for Morogoro where 65% of all consumers interviewed earned above 510,000 TZS per month. Morogoro represents a higher income and education category; the rest of the sample represents a typical Tanzania population [56].

3.2. Consumers’ Awareness of Aflatoxin

Consumers’ awareness of aflatoxins in food is important in enabling their buying decisions and theresults show that, out of all respondents interviewed, 55.83% are confirmed to have never heard about aflatoxin contamination in food. Iringa and Morogoro have nearly the same levels of awareness, with only 43.20% and 44.54% levels of awareness, respectively. In line with [41], the high number of unaware consumers (71.6%) were found in the Dodoma region where there are more incidences of aflatoxin contamination in food, followed by Dar es Salaam with 63.03%. This might be because most of the research and intervention programs carried out on aflatoxin contamination in Tanzania are conducted in rural areas to farmers, as in those of [42,44,47]. For this reason, the study found the majority of urban consumers to be unaware of aflatoxins and aflatoxin contaminations in food, its health impacts, and strategies to minimize contamination. The study also found that government extension officers (40.57%), social media (26.89%), and society in general (26.42%) were their main source of information. The study later went ahead and inquired consumers who declared awareness on what exactly they knew about aflatoxins to make sure they have all the knowledge. Of these, 82% stated that aflatoxins are a form of mold and can be easily seen if present in food, hence indicating that there is still a need for an education campaign to raise awareness of aflatoxin contamination and its associated health risks.

The findings of this study are consistent with the research conducted by [34], which also indicated that many consumers in the most affected areas are aware of aflatoxins but have limited knowledge regarding the potential health risks associated with them. The results further highlight that the dissemination of awareness regarding aflatoxins remains insufficient in Tanzania. This finding aligns with the study conducted by [57] which identified low awareness among the general public and stakeholders within the food chain as significant factors influencing the behavior of food value chain stakeholders and their understanding of aflatoxins and their health impacts in Tanzania.

Table 2. Consumer awareness of aflatoxin contamination.

Variable (n = 480)	Frequency	Percent
Awareness (grouped)	Pooled (n = 480)
Not aware	268	55.83
Aware	212	44.17
Dodoma (n = 120)
Aware	34	28.33
Not aware	86	71.67
Morogoro (n = 120)
Aware	66	55
Not aware	54	45
Iringa (n = 120)
Aware	69	57.50
Not aware	51	43.50
Dar es Salaam (n = 120)
Aware	44	36.67
Not aware	76	63.33

shows the distribution of consumers’ awareness of aflatoxin contamination in sunflower oil.

3.3. Consumer’s Willingness to Pay

Despite the overall low awareness of aflatoxins and aflatoxin contamination among consumers, survey data indicate that, on average, consumers are willing to pay an additional 419 TZS for one liter of sunflower oil that is tested and certified as free from aflatoxins. This willingness to pay is consistent among both high-income and low-income consumers. Among the regions surveyed, consumers from Morogoro exhibited the highest willingness to pay, with a premium of 771TZS, followed by Dar es Salaam with 488 TZS, Dodoma with 341 TZS, and Iringa with the lowest at 208 TZS (

Table 3. Consumer mean WTP.

Region	Product	WTP	SD	Minimum	Maximum
Pooled	Aflatoxin-free	5831.10	661.02	3000	8000
	Status quo	5411.66	664.59	2800	7400
Morogoro	Aflatoxin-free	6027.12	668.16	4000	8000
	Status quo	5255.93	632.39	4000	7400
Dodoma	Aflatoxin-free	5790.76	492.14	4100	7000
	Status quo	5450	539.69	4000	6000
Iringa	Aflatoxin-free	5583.05	679.78	4000	6600
	Status quo	5374.58	903.29	3600	10000
Dar es Salaam	Aflatoxin-free	5862.71	508.19	4000	7000
	Status quo	5374.58	903.29	3600	10,000

and Figure 1). The higher willingness to pay among consumers in Morogoro can be attributed to their higher level of consumer awareness, education, and income, as supported by previous studies [38,58].

Contrary to expectations, despite the level of awareness of aflatoxins and aflatoxin contamination among consumers in Iringa, they reported the lowest willingness to pay for foods free from aflatoxin contamination (208 TZS). This finding contradicts the existing literature, such as the study by [59] which suggests that increased awareness and knowledge about aflatoxins can lead to a reduction in aflatoxin and other mycotoxin contamination in food. The low willingness to pay among consumers in Iringa can be attributed to the fact that most of the interviewed consumers in Iringa were net producers who processed their own oil from the sunflower seeds they grew. It could also be because they preferred purchasing sunflower oil from local milling machines due to lower prices, hence their preference and willingness to pay were poorly reflected in their responses.

Apart from Iringa, the willingness to pay results from consumers in the other surveyed regions align well with the existing literature on aflatoxin cases and awareness. Consumers with higher levels of awareness demonstrated a higher willingness to pay, with Morogoro having the highest premium, followed by Dar es Salaam and Dodoma. However, surprisingly, consumers from regions with the highest reported cases of aflatoxin contamination exhibited the lowest willingness to pay. In the case of Dodoma, this can be attributed to low awareness levels, as seen in the study conducted by [41] where, despite the highest number of recorded cases in Dodoma, awareness of aflatoxin and its contamination of food products remained low due to the belief among locals that all the cases were caused by a regular food poisoning. Overall, the willingness to pay results are in alignment with the literature, and the characteristics of the surveyed regions in terms of aflatoxin cases and awareness, as explained in the research design section and supported by studies conducted by [2,42,44,46,47]. Due to the low level of awareness, consumers from Iringa and Dodoma were willing to pay, but not to the same extent as regions such as Morogoro, where the literature indicates a higher level of awareness compared to other regions.

Table 4. WTP between aflatoxin-free sunflower oil and status quo sunflower oil.

Variables	Pooled	Dodoma	Iringa	Morogoro	Dar es Salaam
	Coefficient (S.e)	Coefficient (S.e)	Coefficient (S.e)	Coefficient (S.e)	Coefficient (S.e)
1 = aflatoxin-free; 0 = otherwise	266.23 ** (107.44)	828.77 *** (222.30)	357.35 ** (164.65)	1043.16 *** (277.13)	846.15 *** (198.36)
Constant	6.88 *** (0.03)	6.96 *** (0.07)	6.73 ** (0.07)	6.82 *** (0.08)	7.02 *** (0.09)

Note: Wald chi²(5) = 1882.59; Prob > chi² = 0.0000; and significant results ** p < 0.05; and *** p < 0.001; SE in parenthesis.

presents the results of the interval regression analysis, showing the coefficients (with standard errors in parentheses) for the variables in the model. The dependent variable is the willingness to pay (WTP) for sunflower oil that is free from aflatoxin contamination compared to the status quo sunflower oil.

The coefficient for the variable “aflatoxin-free” represents the difference in WTP between the two types of sunflower oil. In line with the mean WTP presented in Table 3 and Figure 1, the coefficient is positive and statistically significant in all regions, indicating that consumers are willing to pay more for sunflower oil that is certified as aflatoxin-free. The magnitude of the coefficient varies across regions, with the highest premium found in Morogoro (1043.16 TZS), followed by Dar es Salaam (828.77 TZS), Dodoma (846.15 TZS), and Iringa (357.35 TZS). The pooled coefficient (266.23 TZS) represents the overall average increase in WTP for aflatoxin-free sunflower oil across all regions.

The constant term represents the WTP for the status quo sunflower oil (not certified as aflatoxin-free). The coefficients for the constant term are statistically significant in all regions, indicating that consumers have a positive baseline WTP for sunflower oil.

The given t-test results in

Table 5. Two-sample t test comparing WTP between the for status quo and aflatoxin-free sunflower oil.

	Variable	Observation	Mean	Standard Error	Standard Deviation
Pooled	Status quo	308	5500	34.45	604.54
	Aflatoxin-free	308	5881.169	35.19	617.68
	Combines	616	5690.584	25.78	639.75
	Diff	−381.17	49.25	49.25
Morogoro	Status quo	120	5574.79	51.72	564.22
	Aflatoxin-free	120	6021.85	48.38	527.73
	Combines	240	5798.32	38.20	589.35
	Diff	−447.05	56.82	619.84
Dodoma	Status quo	120	5106.67	55.90	612.44
	Aflatoxin-free	120	5426.67	56.11	614.63
	Combines	240	5266.67	40.85	632.89
	Diff	−447	70.82
Iringa	Status quo	120	5419.36	92.91	517.31
	Aflatoxin-free	120	5825.80	94.01	523.42
	Combines	240	5622.58	70.53	555.27
	Diff		−406.45	132.17
Dar es Salaam	Status quo	120	5217.14	90.77	630.12

Note: diff = mean (status quo 1 litre) − mean (aflatoxin-free 1 litre); t = −7.73; degrees of freedom = 614; t = −7.86 Morogoro; t = −4.04 Dodoma; t = −3.07 Iringa; and t = −5.61 Dar es Salaam. (Pr(|T| > |t|) = 0.0000).

, compare the mean willingness to pay (WTP) for the status quo and aflatoxin-free oil across the surveyed regions. The t-test results intended to prove our claim that consumer WTP for aflatoxin-free sunflower oil is higher than for status quo sunflower oil. The p-value (Pr(|T| > |t|)) is reported as 0.0000, which is less than the significance level of 0.05. This indicates that there is a statistically significant difference between the mean of the 1 litre bottles for status quo sunflower oil and aflatoxin-free sunflower oil.

The t-value of −7.7398 suggests a substantial difference between the means of the two groups, aflatoxin-free sunflower oil and status quo sunflower oil. The negative sign indicates that the mean of status quo 1 litre is significantly lower than the mean of aflatoxin-free 1 litre. In all regions, the t-values indicate a significant difference in mean WTP between the status quo and aflatoxin-free oil groups. The negative differences (diff) suggest that, on average, consumers are willing to pay more for aflatoxin-free oil compared to the status quo. In line with the results from the interval regression model, the coefficients and their significance levels differ slightly across regions, suggesting some regional variations in the magnitude of the influence.

3.4. Factors Influencing Willingness to Pay

Results from the interval regression model reveal that several factors significantly influence consumers’ willingness to pay for sunflower oil that is free from aflatoxin contamination. These factors include age, gender, awareness, food status, income, and education (years).

The age variable was found to be important in determining consumers’ willingness to pay. The results indicate that older consumers were willing to pay more for aflatoxin-free food compared to younger consumers. This may be because, as people age and become more conscious of the diseases associated with aging, they prioritize their health more. Therefore, as their age increases, their willingness to pay for healthier food also increases. In this study, younger consumers were found to spend more money on food consumed away from home, and many of them did not prepare their own meals. On the other hand, older consumers were more inclined to pay more because they paid greater attention to the food, they ate due to health reasons, and preferred homemade meals. Similar findings were reported by [60] in their study on the willingness to pay for organic food products and by [61] when assessing farmers’ perception and willingness to pay for Aflasafe KE01, a product used to reduce aflatoxin contamination in crops.

The level of education was found to be an important factor in explaining customers’ willingness to pay. The study revealed that educated individuals were more aware of the risks associated with aflatoxin, and this awareness significantly influenced their willingness to pay. Morogoro, which had a higher proportion of educated individuals and higher awareness of aflatoxins and their contamination, showed the highest willingness to pay for sunflower oil compared to other regions. These findings align with those of [62] who studied awareness and perceptions of groundnut aflatoxin among Ghanaians and found that education level positively affected awareness and willingness to pay.

The awareness of aflatoxin-free products positively influenced consumers in the amount they were willing to pay for safe sunflower oil. This suggests that as people’s knowledge about aflatoxins increases, their willingness to pay also improves. This may be because people become less afraid to switch to new, high-quality foods as they become more aware of toxins in their diets and their potential health effects. Therefore, they are ready to pay more for such products. These results are consistent with those found by [59] who also reported that increasing awareness and knowledge about aflatoxins can reduce aflatoxin and other mycotoxin contamination in cereal grains.

The study also found the variable gender (female) to be significant in explaining the willingness to pay. The mean WTP amount was less for male consumers compared to females. This could be because in developing countries such as Tanzania, female consumers are more involved in food decision making and grocery shopping [28,55]. However, these results were not the same for all regions, whereby the variable gender did not have any significant influence on WTP in Morogoro, as it was significant in Dar es Salaam. These results are consistent with those found by [34] in their study of rural consumers’ willingness to pay for quality labels using experimental auctions for the case of aflatoxin-free maize in Kenya, that also found that gender and education affect WTP and that women exhibited a slightly higher overall WTP than men.

The results in

Table 6. Distribution of factors influencing WTP.

Variables	Pooled	Morogoro	Dodoma	Iringa	Dar es Salaam
	Coefficient (S.e)	Coefficient (S.e)	Coefficient (S.e)	Coefficient (S.e)	Coefficient (S.e)
Education (number of years)	164.25 *** (8.99)	224.37 *** (16.60)	147.13 *** (16.75)	195.57 *** (19.11)	148.72 *** (28.65)
Age (Years)	60.49 *** (3.81)	67.60 *** (9.69)	97.86 *** (9.62)	54.02 *** (5.13)	97.77 *** (11.34)
Hhsz (Number of people)	47.09 (27.15)	34.84 (53.82)	108.77 (58.83)	150.13 (55.62)	−87.97 (72.59)
Income (TZS)	27.02 ** (0.018)	19.01 *** (0.0084)	8.41 ** (0.0403)	6.48 *** (0.0023)	8.48 *** (0.029)
Gender (1 = female 0 = otherwise)	592.44 *** (101.54)	298.48 (213.42)	341.21 ** (162.12)	686.83 *** (194.66)	1024.19 *** (239.15)
Awareness (1 = yes 0 = otherwise)	270.66 *** (107.00)	614.64 *** (229.98)	1068.54 *** (173.51)	740.16 *** (223.62)	1025.53 *** (254.23)
Food status 1 = aflatoxin-free 0 = otherwise	266.23 ** (107.44)	828.77 *** (222.30)	357.35 ** (164.65)	1043.16 *** (277.13)	846.15 *** (198.36)
Constant	6.88 *** (0.03)	6.96 *** (0.07)	6.73 ** (0.07)	6.82 *** (0.08)	7.02 *** (0.09)

Note: significant results ** p < 0.05; and *** p < 0.001; SE in parenthesis. Household size was not statistically significant at the 1, 5, and 10 percent level.

show that product status has a significant influence on consumer WTP in this study. Knowing the status of the food product helped consumers to make a decision that will be of benefit to their health and families. Consumers were WTP more after finding out that one of the products presented to them was tested and found to be safe from aflatoxin contamination. These results are the same as those found by [31] in an experiment performed in the US where the WTP for growth-hormone-free milk and organic milk labels was higher compared to conventional milk [31]. Ref. [63], in the experiment performed in France, also found the WTP for conventional food products decreased when the certified products were introduced because consumers were willing to pay more for the safe products.

Hence in totality, these findings agree with what was reported by [30,64]. Ref. [30] when assessing the adoption of the improved genotype in the food crop and in dry land regions, found that the factors influencing adoption may differ between regions, countries, and products. Overall, consumers were willing to pay more for the sunflower oil that is tested and certified as free from aflatoxin for all regions.

3.5. Conclusion and Recommendations

Based on the findings and observations made in the study area, and since sunflower oil is among the major food items consumed by most Tanzanians, the study found that there is a demand for aflatoxin-free sunflower oil in Tanzania, and that consumers are willing to pay a premium price for it. This provides an opportunity for farmers and food producers to invest in technologies and practices that can reduce aflatoxin contamination and increase the availability of safe, high-quality sunflower oil for consumers. Not only that, but the study also suggests that deliberate decisions should be taken by all food value chain stakeholders, to provide education and awareness on what to watch out for in food to avoid the risk of aflatoxicosis.