Journal of Food, Agriculture and Environment

Factor influencing risk perception of food additives 

Author(s):

Latifah Amin ^{1, 3}*, Md. Abul Kalam Azad ^{1, 2}, Abdul Latif Samian ³

Recieved Date: 2013-01-22, Accepted Date: 2013-04-20

Abstract:

Food additives are intentionally added to foods in order to improve their quality and stability. However, their presence in food has become a concern for consumers and the food industry and perception of food hazards has been shown to be influenced by many factors. The purpose of this paper was to identify the relevant factors influencing public perception of risks related to food additives using structural equation modelling. A survey was carried out on the general public (550 respondents) in the Klang Valley region, stratified according to their occupations classification by Malaysian Standard Classification of Occupations 1998. Risk perception was measured using self-developed questionnaires with seven point Likert scales. Structural equation  modelling  (SEM)  was  carried  out  using  AMOS  version  5.0  with maximum likehood estimation. The acceptability of risks related to food additives was highly influenced by perception of benefits and risk associated with them. Perceived benefit is the most important direct predictor for the acceptability of risks related to food additives and the encouragement of the use of food additives. Conversely, perceived  risk  was found to be negatively associated with perceived benefits, risk acceptance and encouragement, while risk acceptance was positively associated with encouragement. Other factors such as familiarity, food safety concerns, confidence in key actors, attitudes towards the impact of science and technology,  and  risk  taking  attitudes  contributed  either  directly  or  indirectly  to  the acceptability of risk and encouragement of use  the food additives. These factors could be considered  when  devising  measures  to  improve  public  health  policy  and  food  safety regulation. 

Keywords:

Structural equation model, risk perception, food additives

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Journal: Journal of Food, Agriculture and Environment
Year: 2013
Volume: 11
Issue: 2
Category: Food and Health
Pages: 66-72

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