Perceived severity of diseases and meat consumption among university students

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Perceived severity of diseases and meat consumption among university students

https://doi.org/10.21203/rs.3.rs-3572447/v1

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Many societies consider meat to be their favorite food choice. However, meat consumption is also associated with possible health complications. To minimize health complications, one may alter their meat consumption. A university student’s perceived severity of diseases may influence their meat consumption. However, few studies seem to have addressed this issue. Thus, this study aimed to investigate the relationship between the perceived severity of diseases and meat consumption among university students in Uganda. This study used a correlational survey that was mainly quantitative in nature. The study population comprised 59,998 university students in 2022. We selected a total sample of 403 students using proportionate stratified random sampling. We collected data through face-to-face interviews using a questionnaire. We analyzed the data using SPSS (V23) and AMOS (V23) software for correlational and Confirmatory factor tests. The results revealed that perceived severity had no significant influence on the meat consumption of university students.

Health Policy

Perceived Severity

Uganda

Health

Meat Consumption

Many societies consider animal products as consumption staple with meat being one of the preferred meal choices (Bereżnicka & Pawlonka, 2018; Valli et al., 2019). The world’s meat consumption is estimated at 337 million tones (FAO, 2021), with Africa’s projected consumption growth at 2.8% per year second to only South Asia (Pica-Ciamarra et al., 2014). Uganda, in particular, consumed 315 metric tons in 2019 (UBOS, 2020). However, mass meat consumption has been associated with a number of human health problems that include cancer, diabetes, Kidney complications, and eyesight defects (Farvid et al., 2021; Godfray et al., 2018; Grosso et al., 2022; Huang et al., 2021; Mayega et al., 2014).

Among the health complications associated with meat consumption are heart diseases (Papier et al., 2021). According to WHO (2022), heart diseases are the global leading annual cause of death accounting for 17.9 million fatalities in 2019. Three quarters of those deaths occur in low and middle-income countries (WHO, 2021). These diseases are a major concern for many governments world wide as they are a major budget cost at both household and national level (Kazibwe et al., 2021) hence the need for devising policies to curb the problem (Temple, 2020).

Governments have introduced programs like educational campaigns, food donations, medical care (Nguyen et al., 2021) and taxation policies to combat the associated health problems (Katare et al., 2020) with seemingly little progress. Relatedly, in Wilde et al. (2019) study on how to combat meat related health problems, they found it more probable for the US government to implement policies like public service announcements and product label warnings so as to influence individual views regarding meat consumption.

To understand how individual views may alter one’s meat consumption, Nguyen et al. (2021) suggests the use of the Health Belief Model (HBM). This model asserts that individual health beliefs influence one’s health behavior (Rosenstock, 1974). These health beliefs include perceived severity described as an individual’s apparent conviction of the weight of the health problem once contracted (Rosenstock et al., 1988). The stronger one’s belief is in the negative result of diseases is the more one will act to avoid those diseases (Carpenter, 2010). For instance, according to Naghashpour et al. (2014)‘s study, female student’s understanding of the possible harshness of hypertension to their bodies was the likely reason behind their increased consumption of calcium rich foods. Similarly, Bastami et al. (2019) reported that high school students’ fear of illness was the reason they did not consume snacks at school. Adejoh (2014) also reported that the more severe people thought diabetes would be the more likely they consumed healthy foods. Additionally, Amiot et al. (2018) suggests that one’s fear of diseases may lead to reduction in his/her meat intake. Zur & Klöckner (2014) also states that the higher the health risks individuals associate with meat intake the less they are likely to consume it. In the same vein, Malek et al., (2019) study of Australian adults revealed an association between one’s health concern and the their reduction in meat intake. However, Deneke et al. (2022) results indicated that knowledge of the perceived severity of zoonotic disease positively associated with raw meat consumption. Tooby et al., (2021) echoed this when they reported that Canadians continued to consume meat despite their beliefs of the severity of the diseases resulting from its consumption. This study therefore hypothesizes that there is a negative relationship between diseases’ perceived severity and meat consumption among university students in Uganda.

Despite the number of empirical studies applying the Health Belief Model constructs to preventive health behaviors (Fekadu et al., 2018), few seem to have focused on the relationship between perceived disease severity and meat intake (Hyvönen, 2019; Kothe et al., 2019). The available studies seem to apply perceived disease severity on intention or attitude to reduce meat consumption (Kwasny et al., 2022; Palomo-Vélez et al., 2018); and omega 3 supplement intake (Jalili et al., 2019). Additionally, these studies mainly focus on children and elderly with seemingly few studies within Africa’s sub-populations (Moreira et al., 2022; Quah, 1985) that focus on university students. The available studies, also, portray a seemingly inconclusive stand on the relationship between diseases’ perceived severity and meat consumption. To fill this gap, this study investigates the relationship between perceived severity and meat consumption among university students in Uganda.

We conducted a correlational survey approach to test the hypotheses developed in this study and to determine the relationship between disease perceived severity and meat consumption of university students. The population of this study consisted of 59,998 students of Makerere University and Kyambogo University located in Uganda in December 2022 (School Guide Uganda Limited, 2020; UniRank, 2021). Uganda in located in East Africa, North of Tanzania and west of Kenya. Uganda has one of the youngest populations in the world.

Basing on Yamane (1967) formulae, we selected a sample of 403 students using a proportionate stratified random sampling method. We based the strata on university student population. We selected students based on their willingness to participate in the study. We obtained an ethical clearance from the Faculty of Graduate Studies and research of Makerere University Business School prior to data collection. We issued 550 questionnaires and received 432 questionnaires and then discarded 29 unusable ones since according to Hair et al. (2014), they had at least 30% unfilled. We thus got a response rate (Kviz, 1977) of 73.3%.

We collected data using adapted questionnaire items, which we tested for both reliability and validity prior to the starting the study. Specifically, subject experts evaluated questionnaire interpretation, length, easiness, and clarity. Next, in order to assess the reliability of the questionnaire, we conducted a pilot study using 40 questionnaires at the Islamic University in Uganda (located approximately 2 kilometers (1 mile) north of Mbale's central business district in the Eastern Region of Uganda, on the Mbale-Soroti road). We then calculated the Cronbach’s alpha coefficient. All instrument scales produced coefficients above 0.7.

The final research instrument was a fixed-response questionnaire consisting of two main parts. The first part contained demographic items; including age, religion, gender, education, residential status; partner lived with, student nationality and region of origin. The second part contained two constructs – perceived severity and meat consumption – operationalized as follows:

Perceived Severity corresponds to what an individual thinks will be the seriousness of a food related complication if he/she were to contract it (Rosenstock et al., 1988). The study adapted items from Hanson & Benedict, (2002) and Tong et al., (2020). They were modified as follows; Diabetes would be a major issue if I suffered from it, High blood pressure would be a severe burden if it occurred to me, Kidney disease would be a crucial problem if I suffered from it, and Eyesight problems would be a serious concern if I experienced them. We anchored the items on a six-point likert-scale that ranged from ‘1 – strongly disagree’ to ‘6 – strongly agree’. Meat Consumption corresponds to the act of taking meat through the mouth to the body (Rutishauser, 2005). We adapted the Food Frequency Questionnaire (FFQ) from Subar et al. (1995) and included meat items; beef, liver, and goat meat that are largely consumed in Uganda. We required respondents to indicate their frequency of meat consumption within the preceding year using scale anchors that ranged from ‘Never or less than once a month’ to ‘more than 6 times a day’.

We used SPSS (version 23) to produce descriptive statistics and AMOS (version 23) for Confirmatory Factor Analysis (CFA). Under CFA we analyzed a structural equation model to determine whether perceived severity predicted meat consumption of university students in Uganda. Below are the results.

The study population comprised students at Makerere and Kyambogo University in Uganda as at December 2022. Table 1 provides the demographic attributes of the respondents.

Table 1

Respondent characteristics
Variable	Frequency	Percentage (%)
Gender
Male	197	48.9
Female	206	51.1
Total	403	100
Age Bracket
17 years – 19 years	13	3.2
20 years – 22 years	193	47.9
23 years – 25 years	169	41.9
26 years – 28 years	18	4.5
29 years and above	10	2.5
Total	403	100
Region of Origin
Northern	21	5.2
North East	7	1.7
West Nile	19	4.7
Western	128	31.8
South West	13	3.2
Central	146	36.2
Eastern	60	14.9
Foreign Resident	9	2.2
Total	403	100
University attended
Makerere University	301	74.7
Kyambogo University	102	25.3
Total	403	100
Educational level
Certificate	12	3.0
Diploma	20	5.0
Bachelors	362	89.8
Post graduate diploma	1	0.2
Masters	6	1.5
Doctorate	2	0.5
Total	403	100

Table 1 shows that, the study sample included 197 males (48.9%) and 206 females (51.1%). The mean age of respondents was 21 years implying they were majorly youth, and 89.8% of the respondents were pursuing a bachelor degree implying that they were literate. Most respondents (36.2%) hailed from the central region of Uganda. Makerere University had the largest portion of students (74.7%).

We carried out CFA to examine whether or not the construct measures were consistent with the construct nature (Hair et al., 2014). Table 2 shows several commonly-used fit indices we employed to assess the overall model fit (Hu & Bentler, 1999). The comprehensive goodness-of-fit indices produced a Chi square of 19.561, and Chi-Square/DF = 1.505 (Wheaton et al., 1977).

We considered the comparative fit index (CFI) value of 0.995, incremental fit index (IFI) value of 0.995 and Tucker-Lewis index (TLI) value of 0.993, as very good fits to the model based on Hu and Bentler, (1999), assertion that for these indices a value of 0.7 and above is satisfactory, 0.8 and above is good, and 0.9 and above is very good. The root mean square error of approximation (RMSEA) value was 0.035 indicating a close fit (Browne & Cudeck, 1992). Thus, the results in the measurement model (see Fig. 1) indicate an acceptable fit.

Table 2

Confirmatory Factor Analysis
Item Code	Label	Standardized Regression estimates	CR (t)
	Perceived Severity
PSV6	High blood pressure would be a severe burden if it occurred to me	.929
PSV4	Eyesight problems would be a serious concern if I experienced them	.841	24.190
PSV3	Diabetes would be a major issue if I suffered from it	.819	22.912
PSV7	Kidney disease would be a crucial problem if I suffered from it	.855	25.038
	Meat Consumption
MF1	How often did you eat beef last year?	.691
MF14	How often did you eat liver last year?	.738	8.997
MF8	How often did you eat goat’s meat last year?	.623	9.059
	RMSEA CMIN (X²) IFI TLI CFI CMIN/DF
	0.035 19.561 0.995 0.993 0.995 1.505

All standardized factor loadings should be at least 0.5 and statistically significant to indicate that observed indicators are strongly related to their associated constructs (Hair et al., 2014). In the model, all standardized factor loadings were above 0.5 and significant (see Fig. 1). These findings indicate that there was a satisfactory fit between the proposed model and the data. We also tested for convergent and discriminant validity of the constructs. The test for convergent validity revealed (see Table 3), that the composite reliability for all constructs met the threshold of 0.7. In addition, the Average Variance Extracted (AVE) for all constructs met the threshold of 0.5 (Hair et al., 2014). We calculated discriminant validity based on Hair et al.'s, suggestion (2014) that when the correlation values among the latent variables are less than the square root of AVE, it indicates discriminant validity. Table 4 shows that there was discriminant validity between the constructs. Finally, the values of Skewness and Kurtosis did not identify any serious violations of normality, as all the coefficients were below ^±2 (see Table 5).

Table 3

Summary of Reliability statistics (Composite Reliability)
Variable	Composite Reliability (CR)
Meat Consumption Behavior	.934
Perceived Severity	.984

Table 4

Discriminant Validity
Study variables	AVE	1	2
Perceived Severity (1)	.7	.862
Meat Consumption Behavior (2)	.5	− .007	.686

Table 5

Skewness and Kurtosis Test
		Perceived Severity	Meat Consumption Behavior
N	Valid	403	403
	Missing	0	0
Standard deviation		1.26877	1.02798
Variance		1.610	1.057
Skewness		-1.299	.837
Std. Error of Skewness		.122	.122
Kurtosis		.463	.478
Std. Error of Kurtosis		.243	.243

In order to explore the association between meat consumption and perceived severity, we estimated Pearson correlation coefficients (see Table 6). There was a significant and positive correlation between perceived severity and meat consumption.

Table 6

Correlation analysis between variables together with their manifest variables
	1	2	3	4	5	6	7	8	9
High blood pressure would be a severe burden if it occurred to me (1)	1	.770^**	.760^**	.804^**	.927^**	.053	− .030	.040	.030
Eyesight problems would be a serious concern if I experienced them (2)	.770^**	1	.719^**	.717^**	.895^**	.007	− .069	− .004	− .023
Diabetes would be a major issue if I suffered from it (3)	.760^**	.719^**	1	.674^**	.882^**	.027	− .051	− .002	− .006
Kidney disease would be a crucial problem if I suffered from it (4)	.804^**	.717^**	.674^**	1	.886^**	.024	− .084^*	.025	− .009
Perceived Severity (5)	.927^**	.895^**	.882^**	.886^**	1	.031	− .065	.016	− .002
Beef (6)	.053	.007	.027	.024	.031	1	.510^**	.431^**	.842^**
Liver (7)	− .030	− .069	− .051	− .084^*	− .065	.510^**	1	.460^**	.792^**
Goat (8)	.040	− .004	− .002	.025	.016	.431^**	.460^**	1	.770^**
Meat Consumption (9)	.030	− .023	− .006	− .009	− .002	.842^**	.792^**	.770^**	1
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).

We carried out Structural Equation Modeling (SEM) to evaluate how well perceived severity predicted meat consumption. We used SEM as it provides for the control of the measurement error.

Table 7

**SEM** Results on Direct hypothesized Paths
	Standardized Coefficients	Unstandardized Coefficients
β		B	S.E.	t-Value	P	SMC (R²)	Decision
− 0.122		− .006	.049	− .118	.906	.000	Not supported

Table 7 indicates that the relationship between perceived severity and meat Consumption behavior among university students in Uganda is not significant (β = − 0.122, t-value = − 0.118, p-value = 0.906). The squared Multiple Correlation is 0.000. This means perceived severity, approximately, explains 0 percent of the variance in Meat Consumption. In other words, the error variance of meats is approximately 100 percent of the variance of meat consumption itself

Meat consumption is associated with a number of health complications. Literature suggests that perceived disease severity, as a health belief, likely influences meat consumption. We, therefore, conducted this study to investigate the relationship between diseases’ perceived severity and meat consumption among university students in Uganda. The results of this study revealed that diseases’ perceived severity has no significant influence on the consumption of meat among university students. This means that a university student’s understanding on how much of a problem on their lives it would be if they acquired (meat consumption related ailments) diseases like hypertension, diabetes, kidney ailments and eyesight defects seemed not to influence their own consumption of meat – beef, liver and goat meat. The student’s knowledge on the potential negative health consequences of meat consumption does not seem to affect their subsequent consumption of meat. The students probably did not see a connection between meat consumption and the acquisition of hypertension, diabetes, kidney ailments and eyesight defects. This result concurs with Tooby et al. (2021) study that reported a no significant relationship between Canadians’ perceived severity and their subsequent meat consumption. The current study findings however contradicts those of McCarthy et al. (2003), study of Irish consumers, which found that the perceived severity of diseases may predict an individual’s meat consumption.

4.1 Implications

This study has both academic and managerial implications. From an academic standpoint, there is no significant relationship between perceived severity of diseases and meat consumption. Further research should explain the potential associations of other health beliefs – perceived susceptibility, perceived benefits, and perceived barriers have with meat consumption. These findings also have important policy implications. The results show a much more need for consumer education regarding health threats of meat consumption.

4.2 Limitation and future research

The present study is not without limitations, but in turn offers opportunity for future studies. The results of this study are an outcome of a case study of university student’s in Uganda. There is need for further extension of these studies to other countries and populations before making generalizations. The results of this study opened a way for assessing meat consumption in Uganda. Further, it would be of value when future research considers the effect of other health beliefs on the meat consumption, such as “perceived susceptibility, perceived benefits, and perceived barriers”. Consumers demographics might also have a different effect on their meat consumption, which should be investigated in the future studies.

We conducted this study to investigate the relationship between diseases’ perceived severity and meat consumption among university students in Uganda. The results of this study lead to the conclusion that a university student’s belief in the severity of diseases may not necessarily influence the consequent meat consumption. In other words, the fear of diseases like diabetes, high blood pressure and kidney complications may not influence a university student’s consumption of meats that is beef, liver, and goat meat. This study provides preliminary evidence for the association of one of the health beliefs and meat consumption, specifically among university students in Uganda. However future research should focus on the effect other health beliefs have on meat consumption.

Acknowledgement

We would like to thank the community of practice from which the lead author learnt a lot.

Author contribution

The Corresponding author of this manuscript is Musa Kiggwe and contribution of the authors as mentioned below with their responsibility in the research.

	Author full name	Email ID	Contribution of author	Complete address
1	Musa Kiggwe*	[email protected]; [email protected]	Conceptualization and article writing	Makerere University Business School. Plot 21A Port bell Road, Nakawa, P.O. Box 1337, Kampala Uganda
2	Prof. Joseph Ntayi (PhD)	[email protected]	Literature review and methodology	Makerere University Business School. Plot 21A Port bell Road, Nakawa, P.O. Box 1337, Kampala Uganda
3	Dr. Annet K. Nabatanzi-Muyimba	[email protected]	Literature review	Makerere University Business School. Plot 21A Port bell Road, Nakawa, P.O. Box 1337, Kampala Uganda
4	Assoc. Prof. Jotham Byarugaba (Ph.D.)	[email protected]	Literature review	Makerere University Business School. Plot 21A Port bell Road, Nakawa, P.O. Box 1337, Kampala Uganda
5	Dr. Timothy Esemu	[email protected]	Literature review	Makerere University Business School. Plot 21A Port bell Road, Nakawa, P.O. Box 1337, Kampala Uganda
6	Prof. John C. Munene (Ph.D.)	[email protected]	Literature review and Methodology	Makerere University Business School. Plot 21A Port bell Road, Nakawa, P.O. Box 1337, Kampala Uganda

Ethical declaration

This study followed the APA Ethical Guidelines for Research with Human Subjects; the researcher fully informed all participants about the general scope of the study, the researcher obtained informed consent from the participants, and provided no compensation for participation. Prior to data collection, we obtained ethical clearance from Makerere University Business School’s ethics committee. The survey began with questions about meat consumption behavior and in the second part of the survey, we asked participants about their beliefs, followed by general demographic questions.

Funding acknowledgement

The research was sponsored by Makerere University Business School. The funder did not have a role in study design; in the collection, analysis and interpretation of data, in the writing of the report and decision to submit the article for publication.

Declaration of interest:

none

Data availability:

Data will be provided on request

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Perceived severity of diseases and meat consumption among university students

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1.0 Introduction

2.0 Methods

3.0 Results

4.0 Discussion

4.1 Implications

4.2 Limitation and future research

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