Socioeconomic inequalities of hypercholesterolemia in Kurdistan Province, Iran, in 2005
DOI:
https://doi.org/10.22122/cdj.v3i1.123Keywords:
Inequality, Hypercholesterolemia, Socioeconomic status, IranAbstract
BACKGROUND: Hypercholesterolemia is one of the main risk factors for many non-communicable diseases (NCDs). Many deaths caused by hypercholesterolemia usually occur in low and middle income countries. The aim of the present study was to determine the socioeconomic inequality in the distribution of hypercholesterolemia in Kurdistan Province, Iran, in 2005.
METHODS: The data used in this study were obtained from the results of the Non-Communicable Disease Surveillance Survey (NCDSS) conducted in 2005 in Kurdistan Province. In this study, the socioeconomic status (SES) of participants was determined based on their assets and residential location and using the principal component analysis (PCA) statistical method. The levels of inequality in 5 different socioeconomic groups were determined by calculating the concentration index, comparing odds ratio (OR), and through using logistic regression method.
RESULTS: The prevalence of hypercholesterolemia in the studied subjects was 38.5% [confidence interval (95% CI): 36, 41]. The concentration index of hypercholesterolemia was -0.031 (95% CI: -0.070, 0.009). Moreover, the OR of hypercholesterolemia in the richest group, compared with the poorest, was 0.82 (0.59 to -1.13).
CONCLUSION: In this study, the relationship between socioeconomic status and risk of hypercholesterolemia was not statistically significant; however, usually, SES is associated with hypercholesterolemia. In the comparison of different countries, distribution of hypercholesterolemia in different SES levels depends on the level of development, gross national product (GNP) per capita, and level of income in each country. Inequalities in the distribution of risk factors for hypercholesterolemia can be reduced through increasing disadvantaged groups’ access to health care services and planning special programs for inequality reduction.
References
Fredrickson DS. It's time to be practical. Circulation 1975; 51(2): 209-11.
He J, Gu D, Reynolds K, Wu X, Muntner P, Zhao J, et al. Serum total and lipoprotein cholesterol levels and awareness, treatment, and control of hypercholesterolemia in China. Circulation 2004; 110(4): 405-11.
Veerkamp MJ, de GJ, Hendriks JC, Demacker PN, Stalenhoef AF. Nomogram to diagnose familial combined hyperlipidemia on the basis of results of a 5-year follow-up study. Circulation 2004; 109(24): 2980-5.
Aguilar-Salinas CA, Olaiz G, Valles V, Torres JM, Gomez Perez FJ, Rull JA, et al. High prevalence of low HDL cholesterol concentrations and mixed hyperlipidemia in a Mexican nationwide survey. J Lipid Res 2001; 42(8): 1298-307.
Ridker PM, Buring JE, Cook NR, Rifai N. C-reactive protein, the metabolic syndrome, and risk of incident cardiovascular events: an 8-year follow-up of 14 719 initially healthy American women. Circulation 2003; 107(3): 391-7.
Tikkanen MJ, Huttunen JK, Ehnholm C, Pietinen P. Apolipoprotein E4 homozygosity predisposes to serum cholesterol elevation during high fat diet. Arteriosclerosis 1990; 10(2): 285-8.
Braveman P, Gruskin S. Defining equity in health. J Epidemiol Community Health 2003; 57(4): 254-8.
Morris S, Sutton M, Gravelle H. Inequity and inequality in the use of health care in England: an empirical investigation. Soc Sci Med 2005; 60(6): 1251-66.
Whitehead M. The concepts and principles of equity and health. Int J Health Serv 1992; 22(3): 429-45.
Regidor E. Measures of health inequalities: part 1. J Epidemiol Community Health 2004; 58(10): 858-61.
Khang YH, Lynch JW, Yun S, Lee SI. Trends in socioeconomic health inequalities in Korea: use of mortality and morbidity measures. J Epidemiol Community Health 2004; 58(4): 308-14.
De Maio FG, Linetzky B, Virgolini M. An average/deprivation/inequality (ADI) analysis of chronic disease outcomes and risk factors in Argentina. Popul Health Metr 2009; 7: 8.
Braveman P, Starfield B, Geiger HJ. World Health Report 2000: how it removes equity from the agenda for public health monitoring and policy. BMJ 2001; 323(7314): 678-81.
Wagstaff A. The bounds of the concentration index when the variable of interest is binary, with an application to immunization inequality. Health Econ 2005; 14(4): 429-32.
Kolenikov S, Angeles G. The use of discrete data in PCA: theory, simulations, and applications to socioeconomic indices. Chapel Hill: Carolina Population 2004.
Fotso JC, Kuate-Defo B. Socioeconomic inequalities in early childhood malnutrition and morbidity: modification of the household-level effects by the community SES. Health Place 2005; 11(3): 205-25.
Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan 2006; 21(6): 459-68.
Moradi G, Mohammad K, Majdzadeh R, Ardakani HM, Naieni KH. Socioeconomic Inequality of Non-Communicable Risk Factors among People Living in Kurdistan Province, Islamic Republic of Iran. Int J Prev Med 2013; 4(6): 671-83.
Fuentes R, Uusitalo T, Puska P, Tuomilehto J, Nissinen A. Blood cholesterol level and prevalence of hypercholesterolaemia in developing countries: a review of population-based studies carried out from 1979 to 2002. Eur J Cardiovasc Prev Rehabil 2003; 10(6): 411-9.
Bhargava A. Socio-economic and behavioural factors are predictors of food use in the National Food Stamp Program Survey. Br J Nutr 2004; 92(3): 497-506.
Galobardes B, Costanza MC, Bernstein MS, Delhumeau C, Morabia A. Trends in risk factors for lifestyle-related diseases by socioeconomic position in Geneva, Switzerland, 1993-2000: health inequalities persist. Am J Public Health 2003; 93(8): 1302-9.
Amirian H, Poorolajal H, Roshanaei Gh, Esmailnasab N, Moradi G. Analyzing socioeconomic related health inequality in mothers and children using the concentration index. Epidemiology, Biostatistics and Public Health 2014; 11(3): e9086.
Smith GD, Bartley M, Blane D. The Black report on socioeconomic inequalities in health 10 years on. BMJ 1990; 301(6748): 373-7.