Socioeconomic Factors Boosting Female Obesity in Turkey and Its Income Related Inequality

Yıl 2020, , 350 - 366, 25.04.2020

Banu Beyaz Sipahi

https://doi.org/10.21547/jss.623857

Cited By: 1

Öz

 This study analyses inequality in
obesity for adult females using TurkStat “2008 Health Survey Data” since
obesity prevalence among adult females observed higher than male counterparts at
different socioeconomic dimensions such as income, education and occupation. This
study is specifically aimed to find which socio demographic variables cause
inequality among adult female obese in Turkey. In order to asses the relationship
between socioeconomic variables and 
female obesity in Turkey, a probit model is estimated including
explanatory variables age, education, income, location, marital status and
occupation. Based on Probit model result, various concentration indexes are
computed to evaluate income related distribution of female obesity between poor
and rich. The total concentration index of obesity is found as 0.2186 which
means income related inequality in obesity is concentrated among poor. According
to the concentration index measure age groups (positive), education status
(negative), marital status (negative) and occupation status (negative) are the
most important contributing socioeconomic variables to inequality in adult
female obesity in the country. 

Anahtar Kelimeler

Income Related Inequality in Female Obesity, Female Obesity in Turkey, , inequality in obesity, Concentration Index, Factors Influencing Obesity in Female

Türkiye’de Kadınlarda Obezite Üzerine Sosyoekonomik Faktörlerin Etkisi ve Gelir Eşitsizliği

Öz

Bu çalışma, TÜİK “2008 Sağlık Anketi
Verileri” kullanılarak kadınlarda obezite eşitsizliğini analiz etmektedir.  Çünkü yetişkin kadınlarda gelir, eğitim ve
meslek gibi farklı sosyoekonomik boyutlarda obezite yaygınlığı erkeklerden daha
yüksek gözlenmiştir. Çalışmanın amacı Türkiye’de obez kadınlar arasında
eşitsizliğe neden olan sosyo demografik değişkenleri bulmaktır. Türkiye'de
sosyoekonomik değişkenlerle kadın obezite arasındaki ilişkiyi değerlendirmek
için, probit model yaş, eğitim, gelir, yerleşim yeri, medeni durum, ve meslek
gibi açıklayıcı değişkenler kullanılarak tahmin edilmiştir. Probit model
sonuçlarına bağlı olarak, zenginlerle fakirler arasında kadın obezitesinin
gelirle ilişkisini değerlendirmek için çeşitli yoğunlaşma indeksleri
hesaplanmıştır. Obezitenin toplam yoğunlaşma indeksi 0.2186 bulunmuştur. Bu obezitede gelirle ilgili
eşitsizliğin fakirler arasında yoğunlaştığını gösterir. Yoğunlaşma indeksi
ölçümüne göre, yaş grupları (pozitif), eğitim durumu (negatif), medeni durum
(negatif) ve meslek durumu (negatif), sosyoekonomik değişkenlerin kadın
obezitesindeki eşitsizliğe katkıda bulunan en önemli faktörlerdir.

Anahtar Kelimeler

Kadınlarda Obezitede Gelir Eşitsizliği, Türkiye’de Kadınlarda Obezite, Obezitede Eşitsizlik, Yoğunlaşma İndeksi, Kadında Obeziteyi Etkileyen Faktörler

Kaynakça

• Bilger, M., Kruger, E.J., Finkelstein, E.A. (2017). Measuring socieconomic inequality in obesity:looking beyond the obesity threshold. Health Economics, 26, 1052-1066.
• Buyukgebiz, A. (2005 internet report). 60 Trillion was spent on obesity. Access Date: 21.01.2013, bwww.diyetform.com.
• Caballero, B. (2007). The global epidemic of obesity: An Overview. Epidemiologic Reviews, 29, 1-5.
• Candaş, A. & Buğra, A. (2010). Inequality in Turkey: An overview of permanent inequalities. the Boğaziçi University social policy forum, open society foundation, Working Paper (In Turkish entitled “Türkiye’de Eşitsizlikler: Kalıcı Eşitsizliklere Genel Bir Bakış”, Boğaziçi Üniversitesi Sosyal Politika Formu, Açık Toplum Vakfı); 1-133 (www.spf.boun.edu.tr)
• Cawley, J. (2004). The impact of obesity on wages. The Journal of Human Resources, 39(2); 451-474.
• Chen, Z. & Roy, K.(2009). Calculating concentration index with repetitive values of indicators of economic welfare. Journal of Health Economics, 28, 169-175.
• Clarke, P, O’Malley, P. M., Johnston, L. D., Schulenberg, E. (2009). Social disparities in BMI trajectories across adulthood by gender, race/ethnicity and lifetime socio-economic position: 1986-2004. International Journal of Epidemiology, 38, 499-509.
• Clarke, P. & Van Ourti, T. (2010). Calculating the concentration index when income is grouped. Journal of Health Economics, 29(1), 151-157.
• Costa-Font, J. &, Gil, J. (2008). What lies behind socio-economic inequalities in obesity in Spain? A decomposition approach. Food Policy, 33, 61-73.
• Erreygers, G. (2009).Correcting the concentration index. Journal of Health Economics, 28, 504-515.
• Hwang, J., Lee, E., Lee C. (2019). Measuring socioeconomic inequalities in obesity among Korean adults, 1998-2015. International Journal of Environmental Research and Pubic Health, 16(1617), 2-14.
• Kakwani, N.C., Wagstaff, A., van Doorslaer, E. (1997). Socio-economic inequalities in health: measurement, computation and statistical inference. Journal of Econometrics, 77(1), 87-104.
• Ljungvall, A., Gerdtham, U. G. (2010). More equal but heavier: a longitudinal analysis of income-related obesity inequalities in an adult Swedish cohort. Social Science&Medicine, 70, 221-231.
• Mackenbach, J. P., Stirbu, I., Roskam, A. J. R. (2008). European Union Working Group: Socioeconomic inequality in health in 22 European Countries. The New England Journal of Medicine, 358(23), 2468-2481.
• Madden, D.(2010). The socioeconomic gradient of obesity in Ireland. Health Econometrics and Data Group (HEDG), The University of York, 10(24), 1-19.
• Najafi, F., Pasdar, Y.,Hamzeh, B. (2018). Measuring and decomposing socioeconomic inequality in adult oesity in west Iran. J Prev Med Public Health, 51, 299-297.
• Nikolaou, A. & Nikolaou, D. (2008). Income related inequality in the distribution of obesity among Europeans. Journal Public Health, 16, 403-411.
• Rmling, C. & Qaim, M. (2011). Direct and indirect determinants of obesity: The case of Indonesia. RTG 1666 global food, transformation of global agri-food systems: trends, driving forces and implications for developing countries. Georg- August University of Göttingen, (4), 1-29.
• Schmeiser, M. (2008). Expanding wallets and waistlines: The impact of family income on the BMI of women and men eligible for the earned income tax credit. Institute for Research on Poverty Discussion Paper, (1339-08), 1-35.
• Sobal, J. (1991). Obesity and socioeconomic status: a framework for examining relationships between physical and social variables. Medical Anthropology, 13, 231-247.
• TurkStat, (2011). Turkey, Health Interview Survey, Press Release, No. 8620 (2010).
• TurkStat, (2012a). Labour Force Status of Female, Employment Statistics. Access Date: 29.06.2018, http://www.turkstat.gov.tr/Start.do
• TurkStat, (2012b). Labour Force Status of Female by Education Level, Employment Statistics. Access Date: 29.06.2018, http://www.turkstat.gov.tr
• TurkStat, (2018). Statistic of female, no: 30707. Access Date: 23.09.2019, http://www.turkstat.gov.tr
• Vallejo-Torres, L., Morris, S. (2010). The contribution of smoking and obesity to income-related inequalities in health in England. Social Science & Medicine, 71, 1189-1198.
• Van Doorslaer, E., Koolman, X. (2004). Explaining the differences in income-related health inequalities across European Countries. Health Economics, 13, 609-628.
• Van Doorslaer, E., Masseria, E.C, Koolman, X. (2006). The OECD health research group,: inequalities in access to medical care by ncome in developed countries. Canadian Medical Association Journal, 174, 177-183.
• Van Oort, F.V., Van Lenthe, F.J., Mackenbach, J.P. (2005). Material psychosocial and behavioural factors in the explanation of educational inequalities in mortality in The Netherlands. Journal Epidemiology and Community Health, 59, 214-220.
• Zhang, Q., Wang, Y. (2004). Socioeconomic inequality of obesity in the United States: do gender, age and ethnicity matter?. Social Science& Medicine, 58, 1171-1180.
• Zhang, Q., Wang, Y. (2007). Using concentration index to study changes in socio-economic inequality of overweight among US adolescents between 1971 and 2002. International Journal of Epidemiology, 36, 916-925.
• Zhang, Q., Zheng, B., Zhang, N., Wang, Y. (2011). Decomposing the intergenerational disparity in income and obesity. The B.E. Journal of Economic Analysis & Policy, 11(3), 1-18.
• Wagstaff, A., van Doorslaer, E., Paci, P. (1989). Equity in the finance and delivery of health Ccare: Ssome tentative cross- country comparisons. Oxford Review of Economic Policy, 5(1), 89-112.
• Wagstaff, A., Paci, P., van Doorslaer. E. (1991). On the measurement of inequalities in health. Soc Sci Med. 545-557.
• Wagstaff, A. (2007). Socioeconomic inequalities in child mortality: comparisons across nine developing countries. Bulletin of the World Health Organization, 8(1), 19-29.
• Wagstaff, A., Van Doorslaer, E., Watanabe, N. (2003). On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam. Journal of Econometrics, 112(1), 207-223.
• Wagstaff, A. (2005). The bounds of the concentration index when the variable of interest is binary with an application to immunization inequality. Health Economics, 14, 429-432.
• WHO World Health Organization (2000). Obesity: preventing and managing the global epidemic, Geneva report.
• WHO World Health Organization: Obesity and Overweight. Access Date: 21.03.2013, http://www.who.int/mediacentre/factsheets/fs311/en/
• WHO World Health Organization: Obesity and Overweight. Access Date: 19.09.2019, https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
• Wolf, A.M. (2002). Economic outcomes of the obese patient. Obesity Research, 10(1), 57-62.