Back

Liver, cardiovascular and metabolic factors as predictors of all-cause mortality in a rural Ugandan Cohort.

Campbell, C.; Mugisha, J.; Kimono, B.; Waddilove, E.; Makanga, R.; Wang, T.; Nambaziira Muzaale, F.; Matthews, P. C.; Newton, R.

2025-04-04 epidemiology
10.1101/2025.04.03.25325170 medRxiv
Show abstract

Markers of liver and metabolic disease have not been well described for many populations in Africa, but could be important to inform individual and public health interventions that reduce morbidity and mortality. We studied longitudinal data from a population in rural Uganda to determine how liver, metabolic and cardiovascular parameters are associated with all-cause mortality. Demographic and laboratory data were collected through the General Population Cohort (GPC) in South-Western Uganda. We summarised cohort characteristics at baseline using descriptive statistics, and used univariable and multivariable Cox proportional hazards models to investigate factors associated with hazards of death. Our dataset includes 7896 individuals, of whom 56% were female and 73% were aged under 45 years. Prevalence of hepatitis B virus (HBV) and human immunodeficiency virus (HIV) was 3% and 7%, respectively, and ALT was above the upper limit of normal in 26%. During the period observed, death was associated with older age (p<0.0001), male sex (aHR 1.56, 95% CI 1.3 to 1.86) and HIV infection (aHR 1.67, 95% CI 1.25 to 2.22). Excess mortality was associated with increase in AST:ALT ratio (aHR 1.17, 95% CI 1.08 to 1.26), a marker of alcoholic hepatitis. A 10mmHg increase in systolic blood pressure was associated with 7% increased hazards of death (aHR 1.07, 95% CI 1.03 to 1.11), and one unit increases in serum HbA1c were associated with 25% increased hazards of death (aHR 1.25, 95% CI 1.13 to 1.38). Under sensitivity analysis restricted to participants with longitudinal follow-up data, HBV infection was associated with death (aHR 5.38, 95% CI 2.01-14.42). Simple interventions to prevent, diagnose and treat hypertension, diabetes, alcohol excess, and HIV and HBV infection could have an important impact on mortality in this setting.

Matching journals

The top 8 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.