Intention of consumers dwelling in urban areas of Ethiopia to consume Spirulina-fortified bread

Figures & data

Figure 1. Conceptual framework explaining attitude, subjective norm, perceived behavioral control, eating intention, and individual characteristics.

Table 1. Description of individual characteristics.

Variable	Description	Codes
Gender	Gender of the respondent	1 = Male
		2 = Female
Age	Age of the respondent	1 = $\le$ 30 years
		2 = 31–40
		3 = 41–50
Education	maximum education level of the respondent	1 =$\le$ Diploma
		2 = Degree
		3 = MSc. And above
Income	Monthly disposable income of the respondent	1 = < =3000 ETB (USD55.55*)
		2 = 3001–5000 ETB (USD 55.6–92.59)
		3 = 5001–8000 ETB (USD 92.6–148)
		4 = >8000 ETB (>USD 148)
Prior information	Whether the respondent has prior information on Spirulina as a food supplement	1 = Yes
		0 = No
Regular Physical activity	Whether the respondent is engaged in regular physical exercise	1 = Yes
		0 = No
Residence city	City of residence of the respondents	1 = Addis Ababa city
		0 = Other regional cities

* The April 2023 average exchange rate was used to convert the ETB to USD.

Table 2. Basic information presented to the participants about the benefits of Spirulina: adapted from Lucas et al. (2023) with little modification.

Category of information	Description of the information
Sustainability aspect	-Spirulina uses solar energy efficiently to accumulate nutrients in its biomass. -It does not require arable land for its cultivation, and -Less water is required to produce Spirulina compared to other foods, such as meat.
Health benefits	-Spirulina can be consumed to maintain an adequate protein intake while eating less meat. -Spirulina has a high protein content (∼60%) and contains all essential amino acids. -This seaweed also contains polyunsaturated fatty acids that are good for your health, and studies have shown the benefits of consuming Spirulina to treat malnutrition. -Studies showed that Spirulina supplementation improves performance in physical exercise and reduces pain.
Sensory properties (related to consumption)	-Research shows that the taste of Spirulina is considered acceptable by consumers when this microalga is added to different foods. -Adding Spirulina to foods includes a fun component because most products turn green after its addition due to its green pigment. -Currently, our project provides Spirulina-fortified bread to primary school children around Bahir Dar, Ethiopia, as a feeding program to improve the nutrition status of children.

Table 3. Description of TPB constructs and items.

Constructs (Codes)	Items	Codes
Attitude towards eating Spirulina-fortified bread (ATT)	I have a favorable attitude and would prefer Spirulina-fortified bread over regular bread	ATT1
	I have a favorable attitude that Spirulina-fortified bread as a nutritious food choice	ATT2
	I believe that eating Spirulina-fortified bread is good for my overall health	ATT3
	I have a positive attitude that Spirulina-fortified bread would be pleasant to eat	ATT4
	I have a positive attitude towards including healthy foods like Spirulina-fortified bread in my diet	ATT5
	I have a positive attitude towards choosing Spirulina-fortified bread due to its potential positive impact on the environment	ATT6
Subjective norms (SUN)	People who are important to me believe I should consume this bread	SUN1
	I will eat if my family members think I should eat Spirulina-fortified bread	SUN2
	I will eat if my close friend thinks I should eat Spirulina-fortified bread	SUN3
	I will eat if celebrities and health influencers promote the consumption of this bread	SUN4
	I will eat if my coworkers think I should eat Spirulina-fortified bread	SUN5
Perceived behavioral control (PBC)	I can consume the bread fortified with Spirulina	PBC1
	Consuming this new bread is entirely under my control	PBC2
	I am confident that I could take this Spirulina-fortified bread	PBC3
	I am pretty sure that I will consume this Spirulina-fortified bread in the future	PBC4
	I consider Spirulina-fortified bread to be reasonably priced and within my budget	PBC5
Consumption intention (COI)	I believe that this bread has much more health advantages	COI1
	I Intend to purchase this bread in the near future	COI2
	I am willing to try Spirulina-fortified bread to see if I like it	COI3
	I intend to include Spirulina-fortified bread in my meals regularly	COI4
	I would recommend Spirulina-fortified bread to my friends and family	COI5

Table 4. Percentage distribution of respondents’ characteristics.

Respondents’ characteristics	Category	Percentage
Gender	Male	70%
	Female	30%
Age	$\le$30 years	66%
	31–40	19%
	41–50	15%
Maximum education level	$\le$ Diploma	16%
	Degree	54%
	MSc. And above	30%
Monthly disposable income	< =3000 ETB (USD55.55*)	47%
	3001–5000 ETB (USD 55.6–92.59)	5%
	5001–8000 ETB (USD 92.6–148)	12%
	>8000 ETB (>USD 148)	36%
Prior information	Yes	71%
	No	29%
Regular physical activity	Yes	51%
	No	49%
Residence city	Addis Ababa	38%
Weekly bread consumption frequency	Other regional cities	62%
	>three times a week	58%
	Three times a week	18%
	$\le$ two times a week	24%

Table 5. Mean and standard deviation of the behavioral factor constructs and items.

Dependent variables	Item Mean	Std. Dev.	Construct Mean
Attitude towards eating Spirulina-fortified bread (ATT)			3.68
ATT1	3.65	1.09
ATT2	3.75	1.00
ATT3	3.68	1.00
ATT4	3.72	1.00
ATT5	3.65	0.99
ATT6	3.62	0.96
Subjective norms (SUN)			3.56
SUN2	3.70	0.97
SUN3	3.55	0.97
SUN4	3.56	0.97
SUN5	3.44	1.03
Perceived behavioral control (PBC)			3.49
PBC1	3.57	0.96
PBC3	3.48	0.99
PBC4	3.64	0.91
PBC5	3.28	1.03
Consumption intention (COI)			3.46
COI1	3.61	0.93
COI2	3.61	0.97
COI3	3.27	1.06
COI4	3.37	1.06
COI5	3.43	1.04

Table 6. Standardized loadings, reliability, and validity of the CFA model.

Constructs and items	Factor loadings	Std. error	Sig	COR	AVE	VIF
Attitude towards eating Spirulina-fortified bread (ATT)				0.89	0.58	2.31
ATT1	0.62	0.03	p < 0.01
ATT2	0.80	0.03	p < 0.01
ATT3	0.78	0.02	p < 0.01
ATT4	0.81	0.03	p < 0.01
ATT5	0.79	0.03	p < 0.01
ATT6	0.75	0.04	p < 0.01
Subjective norms (SUN)				0.88	0.64	2.28
SUN2	0.79	0.02	p < 0.01
SUN3	0.85	0.02	p < 0.01
SUN4	0.85	0.02	p < 0.01
SUN5	0.70	0.03	p < 0.01
Perceived behavioral control (PBC)				0.81	0.53	1.78
PBC1	0.77	0.03	p < 0.01
PBC3	0.79	0.02	p < 0.01
PBC4	0.81	0.02	p < 0.01
PBC5	0.52	0.04	p < 0.01
Consumption intention (COI)				0.88	0.55	2.20
COI1	0.73	0.03	p < 0.01
COI2	0.81	0.02	p < 0.01
COI3	0.68	0.03	p < 0.01
COI4	0.76	0.03	p < 0.01
COI5	0.71	0.03	p < 0.01

Note: COR = Composite reliability; AVE = Average variance explained; VIF = variable inflation factor.

Table 7. Pearson’s correlation coefficient and discriminant validity.

Construct	COI	ATT	SUN	PBC
COI	0.748
ATT	0.617*	0.761
SUN	0.558*	0.6084*	0.802
PBC	0.707*	0.6265*	0.5931*	0.728

Note: Pearson’s correlation coefficient is significantly different from 0 at the 1% level of significance (p < 0.01). The bold values represent the square root of AVE.

Table 8. Overall goodness of fit of the measurement model.

Fit indices	Values	Threshold	Assessment
RMSEA	0.049	<0.05	Close fit
CFI	0.954	>0.95	Very good fit
TLI	0.943	>0.90	Acceptable fit
SRMR	0.049	<0.05	Clos-fit

Table 9. Structural relationship between the TPB constructs and hypotheses status.

Relationship	Direct		Indirect		Total		Hypothesis status
	$\widehat{\beta }$	p-value	$\widehat{\beta }$	p-value	$\widehat{\beta }$	p-value
ATT→COI	0.14	0.030**	0.33	<0.001***	0.47	<0.001***	$H_1$: Accepted
ATT→PBC	0.44	<0.001***	–	–	0.44	<0.001***	$H_2$: Accepted
SUN→ATT	0.69	<0.001***	–	–	0.69	<0.001***	$H_3$: Accepted
SUN→PBC	0.32	<0.001***	0.30	<0.001***	0.63	<0.001***	$H_4$: Accepted
SUN→COI	−0.02	0.652	0.57	<0.001***	0.54	<0.001***	$H_5$: Rejected
PBC→COI	0.75	<0.001***	–	–	0.75	<0.001***	$H_7$: Accepted

Note: *** and ** represent significance at the 1% and 5% level, respectively; $\widehat{\beta }$‘s are standardized path coefficient estimates.

Table 10. Structural relationship between individual characteristics and constructs of the TPB.

Relationship	Direct		Indirect		Total		Hypothesis status
	$\widehat{\beta }$	p-value	$\widehat{\beta }$	p-value	$\widehat{\beta }$	p-value
Age ($\le$30 years = 1) → ATT	0.14	0.060*	–	–	0.14	0.060*	$H_8$: Accepted
Education (≤Diploma =1) →ATT	−0.18	0.135	–	–	−0.18	0.135	$H_{11}$: Rejected
Physical activity (Yes = 1) → ATT	0.14	0.041**	–	–	0.14	0.041	$H_{16}$: Accepted
Prior information (Yes = 1) → ATT	0.14	0.076*	–	–	0.14	0.076*	$H_{19}$: Accepted
Age (≤30 years = 1) → PBC	0.03	0.652	0.06	0.069*	0.09	0.218	$H_9$: Rejected
Education (≤Diploma =1) → PBC	−0.02	0.049**	−0.08	0.144	−0.29	0.013**	$H_{12}$: Accepted
Income (≤USD55.5 = 1) → PBC	−0.03	0.603	–	–	−0.03	0.603	$H_{14}$: Rejected
Physical activity (Yes = 1) → PBC	0.16	0.006***	0.06	0.050*	0.23	0.001***	$H_{17}$: Accepted
Prior information (Yes = 1) → PBC	0.11	0.075*	0.06	0.084*	0.18	0.014**	$H_{20}$: Accepted
Age (≤30 years = 1) → COI	−0.06	0.266	0.08	0.152	0.02	0.730	$H_{10}$: Rejected
Education (≤Diploma =1) → COI	0.08	0.343	−0.25	0.013**	−0.16	0.159	$H_{13}$: Rejected
Income (≤USD55.5 = 1) → COI	−0.03	0.518	−0.02	0.604	−0.06	0.343	$H_{15}$: Rejected
Physical activity (yes, = 1) → COI	0.05	0.334	0.19	0.001***	0.24	<0.001***	$H_{18}$: Rejected
Prior information (Yes = 1) → COI	0.05	0.332	0.15	0.012**	0.21	0.004***	$H_{21}$: Rejected

Note: ***, **, and * represent significance at the 1%, 5%, and 10% level, respectively; $\widehat{\beta }\prime s$ are standardized regression coefficient estimates.

Table 11. Mediation effects.

Relationship	$\widehat{\beta }$	Z-value	RIT	RID	Mediation	Hypothesis decision
SUN→ATT→COI	0.09	2.136**	1.36	3.77	COMPLETE	$H_6$: Accepted
ATT→PBC→COI	0.33	5.117***	0.71	2.44	PARTIAL	$H_{7a}$: Accepted
SUN→PBC→COI	0.24	4.203***	1.11	9.76	COMPLETE	$H_{7b}$: Accepted
Age→ATT→COI	0.02	1.423	0.43	0.29	NO	$H_{10a}$: Rejected
Age→ATT→PBC	0.06	1.809	0.66	1.95	NO	$H_{10b}$: Rejected
Age→PBC→COI	0.02	0.450	0.59	0.37	NO	$H_{10c}$: Rejected
Education→ATT→COI	−0.03	−1.233	0.43	0.30	NO	$H_{13a}:$ Rejected
Education→ATT→PBC	−0.08	−1.459	0.28	0.39	NO	$H_{13b}:$ Rejected
Education→PBC→COI	−0.16	−1.912*	2.12	1.89	PARTIAL	$H_{13c}:$ Accepted
Income→PBC→COI	−0.03	−0.519	0.43	0.74	NO	$H_{15a}$: Rejected
Physical activity→ATT→COI	0.02	1.491*	0.28	0.39	PARTIAL	$H_{18a}:$ Accepted
Physical activity→ATT→PBC	0.06	1.954*	0.28	0.38	PARTIAL	$H_{18c}:$ Accepted
Physical activity→PBC→COI	0.12	2.598***	0.71	2.54	COMPLETE	$H_{18b}$: Accepted
Prior information→ATT→COI	0.02	1.374	0.26	0.35	NO	$H_{21a}$: Rejected
Prior information→ATT→PBC	0.06	1.710	0.34	0.51	NO	$H_{21b}:$ Rejected
Prior information→PBC→COI	0.08	1.742	0.63	1.66	NO	$H_{21c}$: Rejected

Note: The test of mediation was based on the Baron and Kenny approach; ***, **, and * represent significance at the 1%, 5%, and 10% levels, respectively; RIT =  indirect effect / total effect; RID =  indirect effect / Direct effect.

Lucas, B. F., Costa, J. A. V., & Brunner, T. A. (2023). Attitudes of consumers toward Spirulina and aça and their use as food ingredients. LWT, 178, 114600. https://doi.org/10.1016/j.lwt.2023.114600

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Data availability statement

The data will be made available upon request from the corresponding author.