Back

Risk factors of uncontrolled hypertension in urban slums of Central India : A Community health worker based two-year follow up

Pakhare, A. P.; Lahiri, A.; Shrivastava, N.; Krishna, S.; Joshi, A.; Atal, S.; Khadanga, S.; Joshi, R.

2021-02-05 cardiovascular medicine
10.1101/2021.02.02.21251036 medRxiv
Show abstract

BackgroundHypertension is a leading cause of cardiovascular diseases and its control is poor. There is heterogeneity in levels of blood-pressure control among various population sub-groups. The present study was conducted within the framework of National Program for prevention and control of cancer, diabetes, cardiovascular diseases and stroke (NPCDCS) in India. It aims to estimate proportion of optimal blood pressure control and identify potential risk factors pertaining to uncontrolled hypertension consequent to initial screening. MethodsWe assembled a cohort of individuals with hypertension confirmed in a baseline screening in sixteen urban slum clusters of Bhopal (2017-2018). Sixteen Accredited Social Health Activists (ASHAs) were trained from within these slums. Individuals with hypertension were linked to primary care providers and followed-up for next two years. Obtaining optimal blood-pressure control (defined as SBP< 140 and DBP<90 mm of Hg) was a key outcome. ResultsOf a total of 6174 individuals, 1571 (25.4%) had hypertension, of which 813 were previously known and 758 were newly detected during baseline survey. Two year follow up was completed for 1177 (74.9%). Blood-pressure was optimally controlled in 301 (26%) at baseline, and in 442 (38%) individuals at two years (absolute increase of 12%; 95% CI 10.2-13.9). Older age, physical-inactivity, higher BMI and newly diagnosed hypertension were significantly associated with uncontrolled blood-pressure. ConclusionsWe found about six of every ten individuals with hypertension were on-treatment, and about four were optimally controlled. These findings provide a benchmark for NPCDCS, in terms of achievable goals within short periods of follow-up.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.