Urban rural differences in prevalence and risk factors of self-reported hypertension among Kenyan women: a population-based study.
Mohammad Abdul Baker ChowdhuryKatrina EpnereMd Aminul HaqueRahma S MkuuPublished in: Journal of human hypertension (2020)
This study investigated rural-urban variation in the prevalence of self-reported hypertension and its risk factors among reproductive-age women in Kenya. The 2014 nationally representative Kenya Demographic and Health Survey (KDHS) data were used in this analysis. The survey adopted a multistage, geographically clustered, and probability-based sampling approach. Multivariable logistic regression was performed to assess the association between risk factors and self-reported hypertension. Overall, 9.38% of the women were hypertensive with higher prevalence among urban 11.61%, compared to rural women, 7.86%. Older age, obesity, having diabetes, and increased the odds of hypertension in both rural and urban areas. We also observed that the odds of hypertension differed by ethnic group. High wealth status was a significant correlate only among urban women with women from rich and richest wealth groups had 2-2.3 times higher odds of hypertension compared to the poor and poorest wealth groups. Women with diabetes had 22 times higher odds of hypertension in both in rural and urban areas compared to women without diabetes. In conclusion, our study found that an estimated 1 out of 10 Kenyan women have hypertension. We believe that this study contributes to better understanding of regional variation of hypertension prevalence and risk factors for reproductive women in Kenya. Future studies should seek to develop evidence-based hypertension prevention and management interventions that are targeted and tailored for urban and rural women in Kenya.
Keyphrases
- blood pressure
- polycystic ovary syndrome
- risk factors
- pregnancy outcomes
- south africa
- type diabetes
- cardiovascular disease
- cervical cancer screening
- breast cancer risk
- metabolic syndrome
- physical activity
- glycemic control
- adipose tissue
- electronic health record
- body mass index
- weight loss
- machine learning
- atomic force microscopy
- high speed