مقایسه تحلیلی عوامل مؤثر بر مصرف ماهی در شهرهای ساری و مشهد

نوع مقاله : مقالات پژوهشی

نویسندگان

• افسانه نیکوکار ¹
• مسعود حسین‌ زاده ²
• زهرا نعمت الهی ³

¹ دانشگاه پیام‌نور، تهران

² دانشگاه آزاد اسلامی، واحد زابل

³ دانشگاه کشاورزی و منابع طبیعی ساری

https://doi.org/10.22067/jead2.v31i4.65025

چکیده

با توجه به نقش و اهمیت مصرف آبزیان در سلامت جامعه، در این مطالعه عوامل مؤثر بر مصرف ماهی در دو شهر ساری و مشهد بررسی شده است. به این منظور، از طریق مصاحبه حضوری و تکمیل پرسش‌نامه از 180 خانوار مشهدی و 120 خانوار ساروی در سال 1394 و با استفاده از الگوی لاجیت ترتیبی، مهمترین عوامل مؤثر بر مصرف ماهی در این دو شهر شناسایی شده است. بر اساس نتایج به دست آمده، متغیرهای تعداد افراد زیر 10 سال و منطقه مسکونی بر مصرف ماهی در خانوارهای مشهدی تأثیر مثبت و معنی‌دار داشته و عوامل مرتبط با سلیقه، تهیه و طبخ آبزیان و سلامت و بهداشت آبزیان بر مصرف ماهی در خانوارهای مشهدی تأثیر منفی و معنی‌دار داشته است. در خانوارهای ساروی، متغیرهای تعداد افراد زیر ده سال، تعداد افراد با بیماری خاص، تعداد سالمندان و سطح درآمد، بر مصرف ماهی تأثیر مثبت و معنی‌دار داشته و سن بر مصرف ماهی تأثیر منفی و معنی‌دار داشته است. مقایسه عوامل مؤثر بر مصرف آبزیان در شهرهای مشهد و ساری نشان می‌دهد، هیچ یک از متغیرهای نامطلوب مرتبط با آبزیان بر مصرف آبزیان خانوارهای ساروی مؤثر نبوده‌اند. از آنجا که خانوارهای ساروی (ساحلی) به آبزیان تازه و با قیمت پایین‌تری نسبت به خانوارهای مشهدی (غیرساحلی) دسترسی دارند؛ این امر در سطح مصرف ماهی این خانوارها تأثیرگذار بوده است. لذا بر اساس نتایج به‌دست آمده، برگزاری کلاس‌های آموزشی طبخ آبزیان برای علاقه‌مندان و ایجاد بازارچه‌های آبزیان جهت عرضه انواع آبزیان پیشنهاد می‌گردد.

کلیدواژه‌ها

• الگوی لاجیت ترتیبی
• ساری
• مشهد
• مصرف ماهی

20.1001.1.20084722.1396.31.4.3.1

عنوان مقاله [English]

Analytical Comparison of Factors Affecting Fish Consumption in the Cities of Sari and Mashhad

نویسندگان [English]

• A. Nikoukar ¹
• M. Hosseinzadeh ²
• Z. Nematollahi ³

¹ Payame Noor University, Tehran

² Zabol Branch, Islamic Azad University

³ Sari

چکیده [English]

Introduction: The first step in any planning is recognition of the actual condition and the main tool to know the present situation and move towards to the ideal conditions is the access to data and information. This study, tried to study fish consumption status and identify the factors affecting it in Sari and Mashhad Cities.
Materials and Methods: Data was collected through interviews and questionnaire and were analyzed using ordered Logit model. Often dependent variables are ordinal, but are not continuous in the sense that the metric used to code the variables is substantively meaningful. A widely used approach to estimating models of this type is an ordered response model, which almost allows employing the Logistic link function. This model is thus often referred to as the "ordered Logit" model. The central idea is that there is a latent continuous metric underlying the ordinal responses observed by the analyst. Thresholds divides the real line into a series of regions corresponding to the various ordinal categories. The latent continuous variable, y* is a linear combination of some predictors, x, plus a disturbance term that has a standard Logistic distribution. Similar to the models for binary data, we are concerned with how changes in the predictors translate into the probability of observing a particular ordinal outcome. In this model, the dependent variable is divided to different classes. Coefficients cannot be interpreted directly; so for evaluating the effect of independent variables on the dependent variable, marginal effect or marginal probability is calculated. independent variables are: Family size, Age, Price of fish, Price of meat, Price of chicken, Education, The number of people under 10 years, The number of people with specific diseases, The number of elderly, Income level, Job, Factor related to taste, Factors related to the access and ease of preparation of fish, Factors related to preparation and cook and Factors related to aquatic health.
Results and Discussion: Households, based on the frequency of buying aquatic (fish, shrimp and canned), are divided into four groups: households with no annual, monthly and weekly consumption of aquatic. So we ran order Logit model for these groups. Pseudo R2 Shows that the order Logit model has a high level of goodness of fit, and the independent variables used in the models explain 12% and 14% variations in the probability of Mashhadian and Saravian households at different levels of consumption. The value of the χ2 statistic in Wald test also indicates the significance of the whole regression. The estimated results of ordered Logit model showed that variables of the number of children under 10 years, the number of people with specific diseases, the number of elderly and income level have the positive impact on fish consumption in Sari. Variables of residential area and the number of children under 10 years have a positive impact on fish consumption in Mashhad. In other words, increasing these variables, increases the probability of fish consumption in these cities. Age has the negative impact on fish consumption in Sari. Also, factors associated with taste, factors related to lack of knowledge of preparation and cooking aquatic and factors related to the health of aquatics have a negative impact on fish consumption in Mashhad. This means that increasing these variables, puts households at lower levels of fish consumption. In such a way, the habitat of coastal towns towards non-coastal cities, reduces the probability of households to be in the low-level of aquatic consumption. This is due to the lower price of fish in coastal cities and access to fresh fish in these cities. The likelihood of Mashhadian households in the low-levels (no use) of aquatic consumption was reduced by 0.308 and increases the probability of households in annual, monthly and weekly of aquatic consumption, with increase in the residential area level by 0.091, 0.192 and 0.025 respectively. The likelihood of Sarian households in high- level of aquatic consumption (weekly and monthly) was increase by 0.120 and 0.395, with increase in the number of people with specific diseases, respectively. Increasing the income level of households also reduces the probability of Sarian households in the low-level (no use) of aquatic consumption group by about 0.0000006.
Conclusions: This study aimed to identify the factors affecting fish consumption in Sari and Mashhad Cities. For this purpose, data was collected through interviews and questionnaire and were analyzed using ordered Logit model. The estimated results of ordered Logit model showed that variables of the number of children under 10 years, the number of people with specific diseases, the number of elderly and income level have a positive impact on fish consumption in Sari. However, variables of residential area and the number of children under 10 years have a positive impact on fish consumption in Mashhad. In other words, increasing these variables, increases the probability of fish consumption in these cities. But factors associated with taste, factors related to lack of knowledge of preparation and cooking aquatic and factors related to the health of aquatics have the negative impact on fish consumption in Mashhad. Based on the results, holding the training classes of fish cooking for enthusiasts and creation of aquatics Markets to supply of aquatic have been proposed.

کلیدواژه‌ها [English]

• Fish consumption
• Mashhad
• Ordered Logit Model
• Sari

مراجع

1- Ahmed A.F., Mohammad Z., and Ismail M.M. 2011. Determinants of fresh fish purchasing behavior among Malaysian consumer, Current Research Journal of Social Sciences, 3 (2): 129- 131.

2- Akinbode S.O., and Dipeolu A.O. 2012. Double-Hurdle Model of Fresh Fish Consumption among Urban Households in South-West Nigeria, Current Research Journal of Social Sciences 4 (6): 431-439.

3- Baghyani Moghadam M. H., and Eivazi S. 2011. Investigation of Factors Related to Lack of Using Fish at The Recommended Amount by WHO in Families of Javanrood (western Iran) According to Model Goal- directed Behavior, Journal of Ilam University of medical sciences, 19, (1): 1-9. (In Persian)

4- Bruns K., Verbeke W., Olsen S.O., and Jeppesen L.F. 2009. Motives, barriers and quality evaluation in fish consumption situations: exploring and comparing heavy and light users in Spain and Belgium, British Food Journal, 111(7): 699-716.

5- Dadgar n., Salehi H., Haji Mir Rahimi S. D., and Teymoori M. 2015. Measuring of per capita fish consumption and assessing barriers and development strategies for consumption in Markazi Province, Iranian Scientific Fisheries Journal, 23 (4): 17-29. (In Persian)

6- Dadgar S., Salehi H., Hajimirrahimi S. D., and Teimoori M. 2015. Measuring of per capita fish consumption and assessing barriers and development strategies for consumption in Markazi Province, Iranian Scientific Fisheries Journal, 23: 17-28 (In Persian).

7- Dourandish A., Hosseinzadeh M., and Nematollahi Z. 2105. Assessment the effective component of seafood consumption in Mashhad (Comparison of Double-Hurdle model and Heckman two-stage method), Agricultural Economics, 9 (4): 197-219. (In Persian)

8- FAO Yearbook of Fishery Statistics Summary tables. 2013.

9- Ghorbani M., Kucheki A.R., Rajab Zadeh M., and Mansouri H. 2014, Investigating the farmers tendency to produce organic cucumber in Khorasan Razavi province, Journal of Agricultural Economics and Development, 28 (2): 149- 156 (In Persian).

10- Gojarati D. 2013. Applied Econometrics, Translation: Nader Mehrgan and Lotfali Agheli, Noor Elm Publication, Hamadan.

11- Greene W.H. 2005. Econometric Analysis, Macmillan. New York.

12- Hosseini S.M., Adeli A., and Vahedi M. 2016. Evaluation of factors and barriers affecting per capita consumption of fish in Sari, Fisheries, Iranian Natural Resources Journal, 69 (3): 341-350 (In Persian).

13- Howard A., and Berry W. 2008. The soil and heath: A study of organic agriculture. The university Press of Kentucky.

14- Kessuvan A., Parthanadee P., and Buddhakulsomsiri J. 2015. The study of consumption behaviors and factors affecting decision to purchase fishery products of consumers in the North and Northeast of Thailand, International Food Research Journal 22(6): 2670-2678.

15- Khoshbavar Rostami H.A. 2017. Director General of Fisheries Department in Mazandaran Province.

16- Kiziloğlu R., and Kizilaslan H. 2016. Analysis of Factors Affecting Households’ Fish Consumption in Erzurum, Turkey, International Journal of Social Sciences and Education Research 2 (2): 527-537.

17- Liao T.F. 1994. Interpreting Probability Models: Logit, Probit and other Generalized Linear Models, In: Sage University Paper Series on Quantitative Applications in the Social Sciences, Vol. 07-101. Thousand Oaks, CA, Sage, California.

18- Mehdizadeh M.R. 2017. Fisheries and Aquaculture Director of Khorasan Razavi Agriculture Jihad Organization.

19- Mousavi H. 2006. Principles of feeding fish (warm water, cold water, shrimp, caviar, decoration). Negar Noo Publication, Tehran. (In Persian)

20- Nosrati Sh., Hayati B.A., Pishbahar A., and Mohammadrezaei R. 2013. Analysis of Factors Affecting Fish Consumption behavior of households in the Tabriz Counties, Journal of Agricultural Economics and Development, 27 (3): 230- 241. (In Persian)

21- Pai C.W., and Saleh W. 2008. Modeling motorcyclist injury severity by various crash types at T-junctions in the UK, Safety Science, 46 (8):1234–1247.

22- Rahimi A.A. 1998. Examine the factors affecting fish consumption in the city of Shiraz, Shiraz: Fisheries Department of Fars province. (In Persian)

23- Rahmawaty S., Charlton K., Lyons-Wall P., and Meyer B. J. 2013. Factors that influence consumption of fish and omega-3 enriched foods: a survey of Australian families with young children, Nutrition and Dietetics, 70 (4): 286-293.

24- Rostami M.R. 2001. Assessment the effect of the marketing mix factors on consumer’s behavior mechanisms of fishery products in Tehran, a master's thesis, Tarbiat Modarres University. (In Persian)

25- Shahnoushi N., Firooz Zare A., Zhaleh Rajabi M., Daneshvar M., and Dehghanian S. 2011. Application of ordered Logit model to investigation of factors affecting Bread waste (Case Study: Mashhad city), Journal of Economic Research, 96: 111-132. (In Persian)

26- Statistical Center of Iran. 2011.

27- Statistical Yearbook of the Iranian Fisheries Organization. 2013-2014. Office of Management and Budget, Page 44.

28- Yousefi A., and Shariati M.T. 2009. Sociological analysis of fish consumption behavior in Mashhad city, Iran Social studies, 3, (3): 5-37. (In Persian)

29- Zahedian Tajanky R., Mojaverian S.M., and Shahpoori A.R. 2015. Investigation of factors affecting on damage groups in agricultural crops insurance "case study: Low-yielding units of beekeeping in Iran", Agricultural Economics, 9 (3): 1-13. (In Persian).

30- Zhang X., House L., Sureshwaran S., and Hanson T. 2004. At-home and away-from-home consumption of seafood in the United States, selected paper prepared for presentation at the southern Agricultural Economics Association Annual Tulsa, Oklahoma, February 18.