مصرف مواد مغذی، تنوع و امنیت غذایی در دهک‌های درآمدی استان تهران

نوع مقاله : مقالات پژوهشی

نویسندگان

• محسن رفعتی
• مهدی شعبان زاده
• ابراهیم جاودان

مؤسسه پژوهش‌های برنامه‌ریزی، اقتصاد کشاورزی و توسعه روستایی، تهران، ایران

https://doi.org/10.22067/jead.2021.69156.1019

چکیده

شتاب بالای تورم در یک دهه گذشته، هزینه‌ی زندگی را در کلان‌شهر تهران با افزایش مواجه ساخته است. گزارش برنامه جهانی غذا (WFP) نشان می­دهد استان تهران در مقایسه با سایر استان‌های ایران بالاترین میزان نابرابری رفاه را دارد و بخش قابل‌توجهی از جمعیت استان تنها سیری شکمی دارند. این مسئله سبب شده تا ابتلا به کوتاهی قد، بیماری‌های قلبی عروقـی، سرطان‌ها، چـاقی، دیابـت، پوسیدگی دندان و بیماری‌های گوارشی در میان خانوارهای تهرانی افزایش یابد. در این راستا اگر چه با تصمیم کارگروه سلامت و امنیت غذایی و مشارکت دستگاه‌های مختلف برنامه‌هایی به منظور ارتقاء سطح سلامت و تغذیه ساکنان استان انجام گرفته است، اما شیوع نارسایی­ها و بیماری­های مختلف ممکن است در نتیجه کمبود مواد مغذی در سبد غذایی و در نتیجه ناامنی غذایی باشد. از آن جا که تأمین سلامت و امنیت غذایی از اهداف راهبردی سند چشم‌انداز بیست ساله کشور است، در این مطالعه ابتدا بر اساس طبقه‌بندی گروه کالایی مرکز آمار ایران و با استفاده از ماتریس عملکرد تغذیه­ای، سطح دریافت مواد مغذی در دهک‏های مختلف درآمدی استان تهران در سال 1397 بررسی شده است. سپس با استفاده از روش جورسازی مصرف مواد مغذی، تنوع و امنیت غذایی دهک­های درآمدی استان تحلیل شده است. نتایج نشان داد که وضعیت دریافت کلسیم، آهن و ویتامین C در میان خانوارهای دهک پائین درآمدی استان تهران بسیار ناگوار است و یک فرد بالغ در سه دهک پائین درآمدی روزانه تنها حدود 14، 487 و 75 میلی‌گرم از این سه ماده مغذی را دریافت نموده است. در مورد سایر مواد مغذی نیز یک فرد بالغ در سه دهک پائین درآمدی پروتئین و ویتامین A را به ترتیب معادل 72 میلی­گرم و 551 میکروگرم دریافت نموده که در سطح حداقل مورد نیاز روزانه است و تنها کربوهیدرات و ویتامین B1 به ترتیب به میزان 339 گرم و 1/5 میلی­گرم دریافت شده که بالاتر از حداقل نیاز روزانه می­باشد. شایان ذکر است که در همه دهک­های درآمدی سطح دریافت کربوهیدرات بیش از سه برایر آستانه مورد نیاز روزانه فرد بالغ است (130 گرم). نهایت آن که بر اساس نتایج خانوارها در سه دهک پائین درآمدی نسبت به سایر دهک­ها تنوع و امنیت غذایی پایین‌تری دارند.

کلیدواژه‌ها

• امنیت غذایی
• تنوع غذایی
• دهک‌های درآمدی
• روش جورسازی
• مصرف مواد مغذی

20.1001.1.20084722.1400.35.2.4.6

موضوعات

• اقتصاد کشاورزی

عنوان مقاله [English]

Nutrient Consumption, Diversity and Food Security of the Income deciles of Tehran Province

نویسندگان [English]

• M. Rafaati
• M. Shabanzadeh
• E. Javdan

Institute of Planning Research, Agricultural Economics and Rural Development, Tehran, Iran

چکیده [English]

Introduction: The rapid acceleration of inflation over the past decade has increased the cost of living in the metropolitan area of Tehran. The World Food Program (WFP) report shows that Tehran province has the highest rate of welfare inequality compared to other provinces in Iran, and a significant portion of the province's population has only abdominal satiety. This has led to an increase in short stature, cardiovascular disease, cancer, obesity, diabetes, tooth decay and gastrointestinal diseases among Tehran families. In this regard, although with the decision of the Working Group on Health and Food Security and the participation of various agencies, programs have been carried out to improve the level of health and nutrition of the residents of the province, but the prevalence of various deficiencies and diseases may be due to lack of nutrients in the food basket and as a result of food insecurity.
Materials and Methods: Since ensuring health and food security is one of the strategic goals of the 20-year vision document of the country, in the present study, households living in Tehran province were first divided into three lower income deciles, four middle deciles and three upper income deciles according to the raw data of the income expenditure of the Statistics Center of Iran. Then based on the classification of the commodity group of the Statistics Center of Iran and using the nutritional performance matrix, the level of nutrient intake in different income deciles of Tehran province in 2018 has been investigated. Then, using the Matching method, nutrient consumption, the diversity and food security of the province's income deciles have been analyzed.
Results and Discussion: The results showed that the level of calcium, iron and vitamin C intake among households in the lower three deciles of Tehran province is very low and an adult received only about 14, 487 and 75 mg of these three nutrients per day. As for other nutrients, an adult in the lower three deciles of income received protein and vitamin A 72 mg and 551 micrograms, respectively which is at the minimum daily requirement and only carbohydrates and vitamin B1 has been received 339 g and 1.5 mg, respectively which is above the minimum daily requirement. It should be noted that in all income deciles, the level of carbohydrate intake is more than triple the daily threshold required by an adult (130 g). Finally, according to the results, the lower three deciles of income have lower diversity and food security than the other deciles.
Conclusion: Considering the current situation of receiving micronutrients in Tehran province, the culture and nutritional literacy of households has a great importance and role that responsible organizations can play an important role in promoting it through culture as well as specialized and general education. At the same time, the stability of food prices along with the provision of cash grants and targeted food packages can increase the consumption and food diversity of households and significantly increase food security in poor households, especially women and children. In this regard, considering that a significant part of the country's resources is wasted annually in the form of hidden and non-targeted subsidies, Iran ranks first in the world in the payment of non-targeted food and fuel subsidies, therefore, targeting subsidies and paying cash and non-cash subsidies with proper identification of the target community, in accordance with the conditions of the country is an important issue that should be considered by policy makers.

کلیدواژه‌ها [English]

• Income deciles
• Nutrient intake
• Food diversity
• Food security
• Matching methods

مراجع

1. Abdi F., Atardi Kashani Z., Mirmiran P., and Estaki T. 2016. Examining and comparison of food consumption pattern in Iran and the world: a review article. Journal of Fasa University of Medical Sciences 5(2): 159-167. (In Persian)
2. Arndt C., Davies R., Gabriel S., Harris L., Makrelov K., Robinson S., and Anderson L. 2020. Covid-19 lockdowns, income distribution, and food security: An analysis for South Africa. Global Food Security 26: 100410.
3. Aslan Nasab A. 2021. Analyzing the effect of income distribution inequality on food security in Iran. 3^th International Conference on Interdisciplinary Studies in Iranian Food Industry and Nutrition Sciences, Tehran. (In Persian)
4. Bandarianzadeh D., Faridshaygan N., and Hoshyarrad A. 2013. Evaluation of nutritional adequacy based on food cost index in households living in Tehran. Iranian Journal of Nutrition Sciences and Food Industry 7(5): 243-252. (In Persian)
5. Callus N. 2020. Generalized optimal matching methods for causal inference. Journal of Machine Learning Research 21(62): 1-54.‏
6. Candel J.J. 2018. Diagnosing integrated food security strategies, NJAS. Wageningen Journal of Life Sciences 84: 103-113.
7. Carletto C., Zezza A., and Banerjee R. 2013. Towards better measurement of household food security: Harmonizing indicators and the role of household surveys. Global Food Security 2(1): 30-40.‏
8. Cenzer I., Boscardin W.J., and Berger K. 2020. Performance of matching methods in studies of rare diseases: a simulation study. Intractable & Rare Diseases Research.‏
9. Colen L., Melo P.C., Abdul-Salam Y., Roberts D., Mary S., and Paloma S.G.Y. 2018. Income elasticities for food, calories and nutrients across Africa: A meta-analysis. Food Policy 77: 116-132.‏
10. Coleman-Jensen A., Rabbitt M.P., Gregory C.A., and Singh A. 2018. Household Food Security in the United States in 2017. USDA-ERS Economic Research Report.
11. Dehejia R.H., and Wahba S. 1998. Matching Methods for Estimating Causal Effects in Non-experimental Studies.‏
12. Dercon S., and Krishnan P. 1998. Changes in poverty in rural Ethiopia 1989-1995: Measurement, robustness tests and decomposition. Centre for the Study of African Economies, Institute of Economics and Statistics, University of Oxford.‏
13. Donzé L., De Pérolles B., and Lai P. 2011. Propensity Score Matching and Genetic Matching: Monte Carlo Results.
14. Esfarjani F., Rustaei R., Mohammadi Nasrabadi F., Abdollahi M., Hoshyar Rad A., and Esmailzadeh A. 2011. Investigating the relationship between dominant dietary patterns and short stature in Tehranian children: a case-control study. Iranian Journal of Nutrition Sciences and Food Industry 6(4): 92-83. (In Persian)
15. 2017. How close are we to zero hunger?, the state of food security and nutrition in the world.
16. Hojabr Kiani K., and Wardi S.S. 2013. Determining the optimal food basket of different urban and rural deciles in Iran. Applied Economics 4(12): 46-37. (In Persian)
17. Hooper L., Telke S., Larson N., Mason S.M., and Neumark-Sztainer D. 2020. Household food insecurity: associations with disordered eating behaviours and overweight in a population-based sample of adolescents. Public Health Nutrition 23(17): 3126-3135.‏
18. Hosseini S.S., Pakravan Charodeh M.R., and Salami H. The impact of subsidy targeting policy on food security in Iran. Iranian Journal of Economic Research 21(67): 53-82. (In Persian)
19. Jovanovic M. 2016. Empirical analysis of income changes impact on food consumption expenditure. Poljoprivreda i Sumarstvo 62(3): 49.‏
20. Kai L., and Prabhala N.R. 2007. Self-selection models in corporate finance.Handbook of empirical corporate finance 37-86.‏
21. Lahouti M., Zavoshi R., Nowruzi M., Rashidkhani B., and Rostami, R. 2015. Relationship between dominant dietary patterns and depressive symptoms in adult women living in Tehran in 2013. Scientific Journal of Qazvin University of Medical Sciences 19(4): 41-32. (In Persian)
22. Lee C.Y., Zhao X., Reesor-Oyer L., Cepni A.B., and Hernandez D.C. 2021. Bidirectional relationship between food insecurity and housing instability. Journal of the Academy of Nutrition and Dietetics 121(1): 84-91.‏
23. Lim H.S., Park Y.H., Lee H.H., Kim T.H., and Kim S.K. 2015. Comparison of calcium intake status by region and socioeconomic status in Korea: The 2011-2013 Korea National Health and Nutrition Examination Survey. Journal of Bone Metabolism 22(3): 119.‏
24. Meade B., and Thome K. 2017. International Food Security Assessment, 2017-2027, Amber Waves, 1-14.
25. Moltedo A., Troubat N., Lokshin M., and Sajaia Z. 2014. Analyzing food security using household survey data: streamlined analysis with ADePT software. The World Bank.
26. Mousavi Nasab E., and Rahmani R. Food security status in different income groups (Case study: Boyerahmad city). Journal of Agricultural Economics and Development 23(92): 217-245. (In Persian)
27. Narmaki A., Shirasb F., Ghorbani M., and Sotoudeh G. 2016. Investigating the relationship between food safety and anthropometric measures, body composition and blood pressure in women referring to sports clubs in West Tehran Municipality. Iranian Journal of Diabetes and Metabolism (Iranian Journal of Diabetes and Lipids) 6(2): 110-103. (In Persian)
28. Oyenubi A., and Wittenberg M. 2020. Does the choice of balance-measure matter under genetic matching?. Empirical Economics 1-14.
29. Ren Y., Li H., and Wang X. 2019. Family income and nutrition-related health: Evidence from food consumption in China. Social Science & Medicine 232: 58-76.‏
30. Rezazadeh A., Rashidkhani B., and Omidvar N. 2009. Examining the dominant dietary patterns and general obesity and abdominal obesity in adult women in the north of Tehran in 2007. Research in Medicine (Medical Journal Research Journal) 33(4): 257-246. (In Persian)
31. Sekhon J.S. 2011. Multivariate and propensity score matching software with automated balance optimization: the matching package for R.Journal of Statistical Software, Forthcoming.‏
32. Sekhon J.S., and Grieve R. 2008. A new non-parametric matching method for bias adjustment with applications to economic evaluations. In iHEA 2007 6th World Congress: Explorations in Health Economics Paper.‏
33. Shabanzadeh-Khoshrody M., Azadi H., Khajooeipour A., and Nabavi-Pelesaraei A. 2016. Analytical investigation of the effects of dam construction on the productivity and efficiency of farmers.Journal of Cleaner Production 135: 549-557.‏
34. Tanhaei M., Zare E., Shirani Bidabadi F., and Julaei R. 2016. Examining the status of food security using food diversity index case study: the rural areas of Marvdasht city, Fars province. Village and Development 18(4): 17-35. (In Persian)
35. Trudell J.P., Burnet M.L., Ziegler B.R., and Luginaah I. 2021. The Impact of Food Insecurity on Mental Health in Africa: A Systematic Review. Social Science & Medicine, 113953.‏
36. 2016. Food and Nutrition Security in Iran, A Summary report WFP Iran country office.
37. Wight V., Kaushal N., Waldfogel J., and Garfinkel I. 2014. Understanding the link between poverty and food insecurity among children: Does the definition of poverty matter?. Journal of Children and Poverty 20(1): 1-20.‏