Rejoinder: Socioeconomic gradients and hypertension in low- and middle-income countries: a straw man and no solutions.
نویسندگان
چکیده
J Urban Health 2002;79(Suppl 1):S1–S12. 6. Riha J, Karabarinde A, Ssenyomo G et al. Urbanicity and lifestyle risk factors for cardiometabolic disease in rural Uganda: A cross-sectional study. PLoS Med 2014;11:e1001683. 7. Egger M, Schneider M, Davey Smith G. Spurious precision? Meta-analysis of observational studies. BMJ 1998; 316:140–44. 8. Dutta A, Ray MR. Prevalence of hypertension and pre-hypertension in rural women: a report from the villages of West Bengal, a state in the eastern part of India. Aust J Rural Health 2012; 20:219–25. 9. Kaur P, Rao SR, Radhakrishnan E, Rajasekar D, Gupte MD. Prevalence, awareness, treatment, control and risk factors for hypertension in a rural population in South India. Int J Public Health. 2012;57:87–94. 10. Braveman P, Krieger N, Lynch J. Health inequalities and social inequalities in health. Bull World Health Organ 2000;78: 232–34; discussion 234–35. 11. Dunn JR. Health behavior vs the stress of low socioeconomic status and health outcomes. JAMA. 2010;303:1199–200. 12. Bowman TS, Gaziano JM, Buring JE, Sesso HD. A prospective study of cigarette smoking and risk of incident hypertension in women. J Am Coll Cardiol 2007;50:2085–92. 13. Healton CG, Vallone D, McCausland KL, Xiao H, Green MP. Smoking, obesity, and their co-occurrence in the United States: cross sectional analysis. BMJ 2006;333:25–26. 14. Schisterman EF, Cole SR, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology 2009;20:488–95. 15. Breslow N. Design and analysis of case-control studies. Annu Rev Public Health 1982;3:29–54. 16. Gilman SE, Loucks EB. Another casualty of sibling fixed-effects analysis of education and health: an informative null, or null information? Soc Sci Med; doi: 10.1016/j.socscimed.2014.06.029 17. Hippel von PT, Lynch JL. Why are educated adults slim – causation or selection? Soc Sci Med 2014;105:131–39. 18. Gwatkin DR. Metrics matter: the case of assessing the importance of non-communicable diseases for the poor. Int J Epidemiol 2013;42:1211–14. 19. Pednekar MS, Gupta R, Gupta PC. Illiteracy, low educational status, and cardiovascular mortality in India. BMC Public Health 2011;11:567. 20. Corsi DJ, Subramanian MA, Davey Smith G, Subramanian SV. Authors’ response to Gupta and Pednekar: importance of examining cause-specific proportions of deaths as well as mortality rates. Int J Epidemiol 2014;43:278–80. 21. Law MR, Morris JK, Wald NJ. Use of blood pressure lowering drugs in the prevention of cardiovascular disease: metaanalysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ 2009;338:b1665.
منابع مشابه
Do the socioeconomic and hypertension gradients in rural populations of low- and middle-income countries differ by geographical region? A systematic review and meta-analysis.
BACKGROUND Of the 1 billion people with hypertension globally, two-thirds reside in low- and middle-income countries (LMICs). The risk of hypertension in LMICs is thought to be positively associated with socioeconomic status (SES). However, recent studies have provided data inconsistent with this concept. Thus, we assessed the association between SES and hypertension in rural populations of LMI...
متن کاملAre estimates of socioeconomic inequalities in chronic disease artefactually narrowed by self-reported measures of prevalence in low-income and middle-income countries? Findings from the WHO-SAGE survey
BACKGROUND The use of self-reported measures of chronic disease may substantially underestimate prevalence in low-income and middle-income country settings, especially in groups with lower socioeconomic status (SES). We sought to determine whether socioeconomic inequalities in the prevalence of non-communicable chronic diseases (NCDs) differ if estimated by using symptom-based or criterion-base...
متن کاملThe Implications of Global Neurosurgery for Low- and Middle-Income Countries. The Case of Cameroon.
The unequal distribution of neurosurgical resources and diseases in the world contributes to inequality. Eight in ten neurosurgical cases needing essential neurosurgical care are found in low- and middle-income countries (LMICs); however, LMICs lack the neurosurgical resources to address these needs. Besides, where neurosurgical care is available, it is not financially accessible to the majorit...
متن کاملSES Disparities in Obesity, Diabetes, and Hypertension among Older Adults in Low and Middle Income Countries
Low and middle income countries experienced rapid demographic changes and increased life expectancy during the 1930s-1960s, mainly because of public health interventions and medical innovations. Increasingly larger groups of survivors of poor early life conditions continued to live in poor socioeconomic conditions which continued to produce a stunted population. Older adults from these cohorts ...
متن کاملAvoiding Middle-income Trap in Muslim Majority Countries: The Effect of Total Factor Productivity, Human Capital, and Age Dependency Ratio
In 2010, the World Bank categorized countries in per capita gross domestic product in terms of purchasing power parity (at constant 1990 prices) in three categories: low, middle (lower and upper) and high income. If a country caught at least 28 years in lower middle income level and at least 14 years caught in upper middle-income level, then they are trapped in lower middle and upper middle...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- International journal of epidemiology
دوره 43 5 شماره
صفحات -
تاریخ انتشار 2014