Association of Socioeconomic Status with Overall and Cause Specific Mortality in the Republic of Seychelles: Results from a Cohort Study in the African Region
Background Low socioeconomic status (SES) is consistently associated with higher mortality in high income countries. Only few studies have assessed this association in low and middle income countries, mainly because of sparse reliable mortality data. This study explores SES differences in overall and cause-specific mortality in the Seychelles, a rapidly developing small island state in the African region. Methods All deaths have been medically certified over more than two decades. SES and other lifestyle-related risk factors were assessed in a total of 3246 participants from three independent population-based surveys conducted in 1989, 1994 and 2004. Vital status was ascertained using linkage with vital statistics. Occupational position was the indicator of SES used in this study and was assessed with the same questions in the three surveys. Results During a mean follow-up of 15.0 years (range 0–23 years), 523 participants died (overall mortality rate 10.8 per 1000 person-years). The main causes of death were cardiovascular disease (CVD) (219 deaths) and cancer (142 deaths). Participants in the low SES group had a higher mortality risk for overall (HR = 1.80; 95% CI: 1.24–2.62), CVD (HR = 1.95; 1.04–3.65) and non-cancer/non-CVD (HR = 2.14; 1.10–4.16) mortality compared to participants in the high SES group. Cancer mortality also tended to be patterned by SES (HR = 1.44; 0.76–2.75). Major lifestyle-related risk factors (smoking, heavy drinking, obesity, diabetes, hypertension, hypercholesterolemia) explained a small proportion of the associations between low SES and all-cause, CVD, and non-cancer/non-CVD mortality. Conclusions In this population-based study assessing social inequalities in mortality in a country of the African region, low SES (as measured by occupational position) was strongly associated with overall, CVD and non-cancer/non-CVD mortality. Our findings support the view that the burden of non-communicable diseases may disproportionally affect people with low SES in low and middle income countries.
References
[1]
Stringhini S, Dugravot A, Shipley M, Goldberg M, Zins M, et al. (2011) Health behaviours, socioeconomic status, and mortality: further analyses of the British Whitehall II and the French GAZEL prospective cohorts. PLoS Medicine 8: e1000419. doi: 10.1371/journal.pmed.1000419
[2]
Mackenbach JP, Bos V, Andersen O, Cardano M, Costa G, et al. (2003) Widening socioeconomic inequalities in mortality in six Western European countries. International journal of epidemiology 32: 830–837. doi: 10.1093/ije/dyg209
[3]
Strand BH, Groholt EK, Steingrimsdottir OA, Blakely T, Graff-Iversen S, et al. (2010) Educational inequalities in mortality over four decades in Norway: prospective study of middle aged men and women followed for cause specific mortality, 1960–2000. British Medical Journal 340: c654. doi: 10.1136/bmj.c654
[4]
Hurt LS, Ronsmans C, Saha S (2004) Effects of education and other socioeconomic factors on middle age mortality in rural Bangladesh. Journal of Epidemiology and Community Health 58: 315–320. doi: 10.1136/jech.2003.007351
[5]
Duncan BB, Rumel D, Zelmanowicz A, Mengue SS, dos Santos S, et al. (1995) Social inequality in mortality in Sao Paulo State, Brazil. International Journal of Epidemiology 24: 359–365. doi: 10.1093/ije/24.2.359
[6]
Mohan VR, Muliyil J (2009) Mortality patterns and the effect of socioeconomic factors on mortality in rural Tamil Nadu, south India: a community-based cohort study. Transactions of the Royal Society of Tropical Medicine and Hygiene 103: 801–806. doi: 10.1016/j.trstmh.2009.04.014
[7]
Po JY, Subramanian SV (2011) Mortality burden and socioeconomic status in India. PLoS ONE 6: e16844. doi: 10.1371/journal.pone.0016844
[8]
Liang J, McCarthy JF, Jain A, Krause N, Bennett JM, et al. (2000) Socioeconomic gradient in old age mortality in Wuhan, China. Journals of Gerontology Series B, Psychological Sciences and Social Sciences 55: S222–233. doi: 10.1093/geronb/55.4.s222
[9]
Kaneda T, Zimmer Z, Tang Z (2005) Socioeconomic status differentials in life and active life expectancy among older adults in Beijing. Disability and Rehabilitation 27: 241–251. doi: 10.1080/09638280400006481
[10]
Ferri CP, Acosta D, Guerra M, Huang Y, Llibre-Rodriguez JJ, et al. (2012) Socioeconomic factors and all cause and cause-specific mortality among older people in Latin America, India, and China: a population-based cohort study. PLoS Medicine 9: e1001179. doi: 10.1371/journal.pmed.1001179
[11]
Berhane Y, Hogberg U, Byass P, Wall S (2002) Gender, literacy, and survival among Ethiopian adults, 1987–96. Bull World Health Organ 80: 714–720.
[12]
Sartorius B, Kahn K, Collinson MA, Sartorius K, Tollman SM (2013) Dying in their prime: determinants and space-time risk of adult mortality in rural South Africa. Geospat Health 7: 237–249. doi: 10.3402/gha.v3i0.5225
[13]
Sartorius B, Sartorius K (2013) Identifying and Targeting Mortality Disparities: A Framework for Sub-Saharan Africa Using Adult Mortality Data from South Africa. PLoS ONE 8: e71437. doi: 10.1371/journal.pone.0071437
[14]
Nikoi CA, Odimegwu C (2013) The association between socioeconomic status and adult mortality in rural Kwazulu-Natal, South Africa. Oman Med J 28: 102–107. doi: 10.5001/omj.2013.27
[15]
Rosero-Bixby L, Dow WH (2009) Surprising SES Gradients in mortality, health, and biomarkers in a Latin American population of adults. Journals of Gerontology Series B, Psychological Sciences and Social Sciences 64: 105–117. doi: 10.1093/geronb/gbn004
[16]
Fox AM (2010) The social determinants of HIV serostatus in sub-Saharan Africa: an inverse relationship between poverty and HIV? Public Health Reports 125 Suppl 4: 16–24.
[17]
Stringhini S, Viswanathan B, Gedeon J, Paccaud F, Bovet P (2013) The social transition of risk factors for cardiovascular disease in the African region: Evidence from three cross-sectional surveys in the Seychelles. International Journal of Cardiology 168: 1201–1206. doi: 10.1016/j.ijcard.2012.11.064
[18]
Fleischer NL, Roux AV, Hubbard AE (2012) Inequalities in body mass index and smoking behavior in 70 countries: evidence for a social transition in chronic disease risk. American Journal of Epidemiology 175: 167–176. doi: 10.1093/aje/kwr314
[19]
Chang CL, Marmot MG, Farley TM, Poulter NR (2002) The influence of economic development on the association between education and the risk of acute myocardial infarction and stroke. Journal of Clinical Epidemiology 55: 741–747. doi: 10.1016/s0895-4356(02)00413-4
[20]
Pednekar MS, Gupta R, Gupta PC (2011) Illiteracy, low educational status, and cardiovascular mortality in India. BMC Public Health 11: 567. doi: 10.1186/1471-2458-11-567
[21]
Vathesatogkit P, Batty GD, Woodward M (2014) Socioeconomic disadvantage and disease-specific mortality in Asia: systematic review with meta-analysis of population-based cohort studies. J Epidemiol Community Health 68: 375–383. doi: 10.1136/jech-2013-203053
[22]
Bouchardy C, Parkin DM, Khlat M, Mirra AP, Kogevinas M, et al. (1993) Education and mortality from cancer in Sao Paulo, Brazil. Annals of Epidemiology 3: 64–70. doi: 10.1016/1047-2797(93)90011-r
[23]
Arroyave I, Burdorf A, Cardona D, Avendano M (2014) Socioeconomic inequalities in premature mortality in Colombia, 1998–2007: The double burden of non-communicable diseases and injuries. Prev Med.
[24]
Wardle J, Steptoe A (2003) Socioeconomic differences in attitudes and beliefs about healthy lifestyles. Journal of Epidemiology and Community Health 57: 440–443. doi: 10.1136/jech.57.6.440
[25]
van Lenthe FJ, de Bourdeaudhuij I, Klepp KI, Lien N, Moore L, et al. (2009) Preventing socioeconomic inequalities in health behaviour in adolescents in Europe: background, design and methods of project TEENAGE. BMC Public Health 9: 125. doi: 10.1186/1471-2458-9-125
[26]
Chen WQ, Wong TW, Yu IT (2008) Association of occupational stress and social support with health-related behaviors among Chinese offshore oil workers. Journal of Occupational Health 50: 262–269. doi: 10.1539/joh.l7149
[27]
Kivimaki M, Shipley MJ, Ferrie JE, Singh-Manoux A, Batty GD, et al. (2008) Best-practice interventions to reduce socioeconomic inequalities of coronary heart disease mortality in UK: a prospective occupational cohort study. Lancet 372: 1648–1654. doi: 10.1016/s0140-6736(08)61688-8
[28]
Woodside JV, Yarnell JW, Patterson CC, Arveiler D, Amouyel P, et al. (2012) Do lifestyle behaviours explain socioeconomic differences in all-cause mortality, and fatal and non-fatal cardiovascular events? Evidence from middle aged men in France and Northern Ireland in the PRIME Study. Preventive Medicine 54: 247–253. doi: 10.1016/j.ypmed.2012.01.017
[29]
Stringhini S, Sabia S, Shipley M, Brunner E, Nabi H, et al. (2010) Association of socioeconomic position with health behaviors and mortality. JAMA 303: 1159–1166. doi: 10.1001/jama.2010.297
[30]
Bovet P, Gedeon J (2013) Life expectancy in Seychelles. The Lancet 382: 23. doi: 10.1016/s0140-6736(13)61518-4
[31]
Bovet P, Romain S, Shamlaye C, Mendis S, Darioli R, et al. (2009) Divergent fifteen-year trends in traditional and cardiometabolic risk factors of cardiovascular diseases in the Seychelles. Cardiovascular Diabetology 8: 34. doi: 10.1186/1475-2840-8-34
[32]
Faeh D, William J, Tappy L, Ravussin E, Bovet P (2007) Prevalence, awareness and control of diabetes in the Seychelles and relationship with excess body weight. BMC Public Health 7: 163. doi: 10.1186/1471-2458-7-163
[33]
Danon-Hersch N, Chiolero A, Shamlaye C, Paccaud F, Bovet P (2007) Decreasing association between body mass index and blood pressure over time. Epidemiology 18: 493–500. doi: 10.1097/ede.0b013e318063eebf
[34]
Bovet P, Chiolero A, Shamlaye C, Paccaud F (2008) Prevalence of overweight in the Seychelles: 15 year trends and association with socio-economic status. Obesity Reviews 9: 511–517. doi: 10.1111/j.1467-789x.2008.00513.x
[35]
Stringhini S, Sinon F, Didon J, Gedeon J, Paccaud F, et al. (2012) Declining stroke and myocardial infarction mortality between 1989 and 2010 in a country of the African region. Stroke 43: 2283–2288. doi: 10.1161/strokeaha.112.658468
[36]
Bovet P, Shamlaye C, Gabriel A, Riesen W, Paccaud F (2006) Prevalence of cardiovascular risk factors in a middle-income country and estimated cost of a treatment strategy. BMC Public Health 6: 9. doi: 10.1186/1471-2458-6-9
[37]
Bovet P, Shamlaye C, Kitua A, Riesen WF, Paccaud F, et al. (1991) High prevalence of cardiovascular risk factors in the Seychelles (Indian Ocean). Arteriosclerosis and Thrombosis 11: 1730–1736. doi: 10.1161/01.atv.11.6.1730
[38]
Bovet P, Perret F, Shamlaye C, Darioli R, Paccaud F (1997) The Seychelles Heart Study II: methods and basic findings. Seychelles Medical & Dental Journal 5..
[39]
World Health Organization (2003) ICD-10: international statistical classification of diseases and related health problems: tenth revision.
[40]
Perdrix J, Bovet P, Larue D, Yersin B, Burnand B, et al. (1999) Patterns of alcohol consumption in the Seychelles Islands (Indian Ocean). Alcohol and Alcoholism 34: 773–785. doi: 10.1093/alcalc/34.5.773
[41]
American Diabetes Association (2009) Diagnosis and classification of diabetes mellitus. Diabetes Care 32 Suppl 1: S62–67. doi: 10.2337/dc09-s062
[42]
Breslow NE (1972) Discussion of the paper by D. R. Cox. Journal of the Royal Statistical Society 34: 216–217.
[43]
Stringhini S, Tabak AG, Akbaraly TN, Sabia S, Shipley MJ, et al. (2012) Contribution of modifiable risk factors to social inequalities in type 2 diabetes: prospective Whitehall II cohort study. BMJ 345: e5452. doi: 10.1136/bmj.e5452
[44]
Valeri L, Vanderweele TJ (2013) Mediation Analysis Allowing for Exposure-Mediator Interactions and Causal Interpretation: Theoretical Assumptions and Implementation With SAS and SPSS Macros. Psychological Methods.
[45]
Richiardi L, Bellocco R, Zugna D (2013) Mediation analysis in epidemiology: methods, interpretation and bias. Int J Epidemiol 42: 1511–1519. doi: 10.1093/ije/dyt127
[46]
Subramanian S, Corsi DJ, Subramanyam MA, Davey Smith G (2013) Jumping the gun: the problematic discourse on socioeconomic status and cardiovascular health in India. International Journal of Epidemiology 42: 1410–1426. doi: 10.1093/ije/dyt017
[47]
Andersen PK, Geskus RB, de Witte T, Putter H (2012) Competing risks in epidemiology: possibilities and pitfalls. Int J Epidemiol 41: 861–870. doi: 10.1093/ije/dyr213
[48]
Ozer EJ, Fernald LC, Weber A, Flynn EP, VanderWeele TJ (2011) Does alleviating poverty affect mothers' depressive symptoms? A quasi-experimental investigation of Mexico's Oportunidades programme. Int J Epidemiol 40: 1565–1576. doi: 10.1093/ije/dyr103
[49]
Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G (2006) Indicators of socioeconomic position (part 1). Journal of Epidemiology and Community Health 60: 7–12. doi: 10.1136/jech.2004.023531
[50]
Kouanda S, Bado A, Yameogo M, Nitiema J, Yameogo G, et al. (2013) The Kaya HDSS, Burkina Faso: a platform for epidemiological studies and health programme evaluation. International Journal of Epidemiology 42: 741–749. doi: 10.1093/ije/dyt076
[51]
Chihana M, Floyd S, Molesworth A, Crampin AC, Kayuni N, et al. (2012) Adult mortality and probable cause of death in rural northern Malawi in the era of HIV treatment. Tropical Medicine and International Health 17: e74–83. doi: 10.1111/j.1365-3156.2012.02929.x
