Back

Exploring Socio-demographic and Geographical Variation of Adults Hypertension in Bangladesh: Spatial Hotspot Analysis

Tabashsum, A.; Mahdee, C. M.; Asha, J. F.; Khan, M. A. I.; Rahman, M. A.

2024-07-05 public and global health
10.1101/2024.07.02.24309855 medRxiv
Show abstract

Hypertension is a chronic medical condition where blood pressure is too high. In Bangladesh, the overall incidence of hypertension is rising, like in other developing countries. Recent studies show hypertension can cause other non-communicable diseases such as cardiovascular diseases, strokes, etc. Utilizing information from the Bangladesh Demographic and Health Survey (BDHS) 2017-18, a cross-sectional and spatial analysis was done to determine the prevalence of hypertension. The existence of spatial autocorrelation is evaluated by using Morans I statistic, hotspot analysis, cold spot analysis, and influential observation analysis. The study was conducted on the basis of different factors such as gender, place of residence, age, BMI, etc. Among 12,926 people (43.19% men, 56.81% women), the women had a higher total prevalence of hypertension (41.18% (95% CI, 41.35-45.67) compared to the mens 58.82% (95% CI, 57.16-60.45). Out of the total number of observations, 27.47% had hypertension. Out of all hypertensive people, 57.56% are unaware of their condition, which is very concerning. The study also finds that 28.4% are from urban areas and 71.6% are from rural areas. People living in the Dhaka division had a higher prevalence of hypertension (20.5%), and those in Sylhet had the lowest prevalence of hypertension (6.2%). There also exists a statistically relevant spatial autocorrelation (hypertension: Morans I index = 0.27, p<0.001). These are the spatial clustering maps, and according to the LISA cluster map, the Northeast districts are the cold spots (8), while the hotspots (4) are Bagerhat, Rajbari, Pirojpur, and Munshiganj. Approximately more than one-fourth of the adult population of Bangladesh had hypertension. The analysis discovered the hotspots and cold spots of the prevalence of hypertension. These findings could facilitate awareness and treatment of hypertension and therefore serve as support for researchers and policymakers.

Matching journals

The top 1 journal accounts 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.