Socioeconomic and environmental risk factors among rheumatic heart disease patients in Uganda.

BACKGROUND

Although low socioeconomic status, and environmental factors are known risk factors for rheumatic heart disease in other societies, risk factors for rheumatic heart disease remain less well described in Uganda.

AIMS AND

OBJECTIVE

The objective of this study was to investigate the role of socio-economic and environmental factors in the pathogenesis of rheumatic heart disease in Ugandan patients.

METHODS

This was a case control study in which rheumatic heart disease cases and normal controls aged 5-60 years were recruited and investigated for socioeconomic and environmental risk factors such as income status, employment status, distance from the nearest health centre, number of people per house and space area per person.

RESULTS

486 participants (243 cases and 243 controls) took part in the study. Average age was 32.37+/-14.6 years for cases and 35.75+/-12.6 years for controls. At univariate level, Cases tended to be more overcrowded than controls; 8.0+/-3.0 versus 6.0+/-3.0 persons per house. Controls were better spaced at 25.2 square feet versus 16.9 for cases. More controls than cases were employed; 45.3% versus 21.1%. Controls lived closer to health centers than the cases; 4.8+/-3.8 versus 3.3+/-12.9 kilometers. At multivariate level, the odds of rheumatic heart disease was 1.7 times higher for unemployment status (OR = 1.7, 95% CI = 1.05-8.19) and 1.3 times higher for overcrowding (OR = 1.35, 95% CI = 1.1-1.56). There was interaction between overcrowding and longer distance from the nearest health centre (OR = 1.20, 95% CI = 1.05-1.42).

CONCLUSION

The major findings of this study were that there was a trend towards increased risk of rheumatic heart disease in association with overcrowding and unemployment. There was interaction between overcrowding and distance from the nearest health center, suggesting that the effect of overcrowding on the risk of acquiring rheumatic heart disease increases with every kilometer increase from the nearest health center.