A 35‑year standardized prediction estimates for gynecological lesions in oil and gas exploration and production city in the Niger Delta
Background: The impact of constant emission of hydrocarbons and contaminated water level through oil spillage in the oil and gas exploration and production areas of Niger Delta on women’s health cannot be underestimated. We developed a 35-year standardized prediction estimates for gynecological lesions using data obtained from an integrated specialist hospital serving the residence of the oil and gas exploration and production City of Port Harcourt and the surrounding areas of Niger Delta, Nigeria.
Methods: The study participants comprised of 697 females who received medical care at the Braithwaite Memorial Specialist Hospital (BMSH), Port Harcourt, Rivers State, Nigeria, between 2010 and 2014. Predictive modeling of the diseases was performed using JMP statistical discovery™ software, version 12.0 (SAS Institute, Cary, NC, USA).
Results: The distribution of the gynecological lesions (n = 697) differed significantly (P < 0.001) by year of diagnosis, developmental stage, age category, and types of lesion. The mean age of study participants was 39.1 ± 12.8 years, and most of the lesions (61.8%) occurred among females who were 30‑ to 49‑year old. Leiomyoma recorded the highest 5‑year standardized prevalence rate of 0.508, and with no intervention, it is estimated that the number of cases diagnosed will rise from 235 in 2015 to 1883 by the year 2050. This was followed by ovarian cyst with a prevalence rate of 0.124 and projected increase from 57 in 2015 to 461 by the year 2050. Similarly, the product of conception is also estimated to increase from 34 to 277 by the year 2050.
Conclusion: The over 700% increased prediction of gynecological lesions by 2050 calls for urgent attention by both governmental and private agencies to fund awareness campaigns and screenings for women, especially for those residing in the oil‑ and gas‑producing areas of Niger Delta.
Key words: Gynecological lesions; Niger Delta; Nigeria; prediction estimates