|Year : 2021 | Volume
| Issue : 3 | Page : 102-108
Oil pollution and hypertension prevalence in Rivers State, Nigeria: A comparative study
John Nwolim Paul1, Omosivie Maduka2
1 School of Public Health, University of Port Harcourt, Rivers State, Nigeria
2 School of Public Health, University of Port Harcourt; Department of Preventive and Social Medicine, Faculty of Clinical Sciences, College of Health Sciences, University of Port Harcourt, Rivers State, Nigeria
|Date of Submission||12-Apr-2021|
|Date of Decision||18-May-2021|
|Date of Acceptance||17-Sep-2021|
|Date of Web Publication||22-Nov-2021|
Dr. Omosivie Maduka
Department of Preventive and Social Medicine, University of Port Harcourt, Port Harcourt, Rivers State
Source of Support: None, Conflict of Interest: None
Aims: This study was done to compare the prevalence of hypertension in oil-polluted and non-oil polluted communities in Rivers State
Subjects and Methods: A community-based household analytical cross-sectional study was conducted on oil-polluted communities in Ogoni local government areas and nonoil polluted communities in Abua/Odua LGA both in Rivers State. An interviewer-administered structured World Health Organization STEPS instrument/questionnaire for NCD/chronic disease surveillance was used, and the sample size of 1000 participants was recruited via multistage sampling. Odds ratio (OR) and corresponding 95% confidence intervals (95% CI) we calculated through bivariate and multivariate regression analysis.
Results: The prevalence of hypertension among persons resident in oil-polluted and nonoil-polluted communities was 59.8% and 46.6%, respectively. The comparison of prevalence showed statistical significance between both categories (χ2 = 16.97, P = 0.001). The regression model on crude analysis found residence (OR 1.69, 95% CI 1.32–2.17) and cigarette smoking (OR 1.65, 95% CI 1.19–2.29) were related to being hypertensive.
Conclusions: The study revealed that participants who were residents in oil-polluted areas had 1.69 times higher odds of having hypertension over those in areas without oil pollution. However, moderate and vigorous physical activity reduced the chances of having hypertension by 95%, and 99%, respectively.
Keywords: Community, hypertension, oil pollution, prevalence, residence
|How to cite this article:|
Paul JN, Maduka O. Oil pollution and hypertension prevalence in Rivers State, Nigeria: A comparative study. Int J Non-Commun Dis 2021;6:102-8
|How to cite this URL:|
Paul JN, Maduka O. Oil pollution and hypertension prevalence in Rivers State, Nigeria: A comparative study. Int J Non-Commun Dis [serial online] 2021 [cited 2022 Aug 17];6:102-8. Available from: https://www.ijncd.org/text.asp?2021/6/3/102/330905
| Introduction|| |
The World Health Organization (WHO) and all Member States (194 countries) agreed in 2013 on global mechanisms to reduce the avoidable noncommunicable diseases (NCD) burden including a “Global action plan for the prevention and control of NCDs 2013–2020.” This plan aims to reduce the number of premature deaths from NCDs by 25% by 2025 through nine voluntary global targets. The sixth target in the Global NCD action plan calls for 25% reduction in the global prevalence of raised blood pressure. Raised blood pressure is the leading risk factor for cardiovascular disease. The global prevalence of raised blood pressure (defined as systolic and/or diastolic blood pressure more than or equal to 130/80 mmHg) in adults aged 18 years and over was around 24.1% in men and 20.1% in women in 2015. The number of adults with raised blood pressure increased from 594 million in 1975 to 1.13 billion in 2015, with the increase largely in low- and middle-income countries.,
There is speculation that residents of oil-polluted areas are more prone to having a high prevalence of the NCD probably due to oil exploration, spillage, and gas flaring. 5 A community with oil exploration with at least one incidence of oil spillage or gas flaring is referred to as an oil polluted, while a community without any history of oil exploration, spillage, or gas flaring is referred to as a nonoil polluted.,
Worldwide, environmental air and water pollution has been linked to the development and exacerbation of a number of health problems including high blood pressure, lung cancer, and both chronic and acute respiratory diseases. There are several research papers which addressed lots of issues around hypertension ranging from the risk factors, predictors, and cost-effective management of hypertension.,,,,,,,,, Hence, this study was done to compare the prevalence value of Hypertension in oil-polluted and nonoil polluted communities in Rivers State, Nigeria.
| Subjects and Methods|| |
The study was a cross-sectional community-based survey. The oil-polluted communities were from Ogoni local government areas (LGAs), whereas the non-oil-polluted communities were from Abua/Odua LGA, both in Rivers State. The study population included all adults (18 years and above regardless of gender, previous diagnosis of hypertension who reside in the area of study.
Sample size determination
A sample size of 914 adults (457 residents in oil-polluted communities and 457 residents in nonoil polluted communities) was estimated This number as considered adequate to determine a difference in the prevalence of hypertension among the two groups of communities using the formula for difference between two proportions. The following was used in calculating the sample size power set at 90% (u = 1.28) and a 5% significance level (v = 1.96). From a previous study, the proportion of study participants in the oil-polluted community in Rivers state who were hypertensive (p1) was 39.0%, while the proportion of hypertensive persons in the nonpolluted community (p2) was 28.0%. A 20% mark-up in sample size was done to allow for nonresponse and multiplication by a factor of two used to correct for design effect.
The inclusion criteria for an oil-polluted community is a community with oil exploration with at least one incidence of oil spillage or gas flaring and nonoil-polluted community is one that has no known history of oil exploration, spillage, or gas flaring. Individuals recruited were those who had lived in the community for at least 10 years. Pregnant women, breastfeeding mothers, those on steroids, and nonconsenting adults were excluded from the study.
Multistage sampling technique was adopted for this study in the recruitment of participants from both populations. For the oil-bearing study population, sampling involved three stages: In stage 1: One LGA (Gokana) was selected from all the oil-bearing LGAs in Rivers State by simple random sampling. In stage 2: Two wards (K-Dere and B-Dere) from the LGA were selected by simple random sampling, while stage 3: 500 respondents were finally selected from households in the two selected communities (250 from each community) by systematic sampling. Similarly, sampling for the nonoil bearing community stage 1 involved: Selecting one out of all nonoil-bearing LGAs selected by simple random sampling. In stage 2: Two wards (Omelema and Emilaghan) in Abua were selected by simple random sampling, while in stage 3, a total of 500 respondents (250 each community) were selected from households in the two communities by systematic sampling technique.
An interviewer-administered structured WHO STEPS instrument/questionnaire for NCD/chronic disease surveillance was used. The questionnaire included questions that assessed sociodemographic characteristics in section one, blood glucose level, systolic and diastolic blood pressures in section two, risk factors for NCD (hypertension), and anthropometric measures in section three adapted from the WHO STEPS questionnaire was used to obtain information on morbidity patterns in the study communities. It had the following sections: Consent form, sociodemographic and household information, and physical measurements such as weight, height, and blood pressure.
Anthropometric measurements (height, weight, hip, and waist circumference) were taken using standardized techniques and calibrated equipment. Subjects were also weighed to the nearest 0.1 kg in light indoor clothing and barefoot. Height was measured using a stadiometer; participants stood in erect posture on barefoot, and the results were recorded to the nearest 0.5 cm. Measures were taken twice, and the average was used for the analysis. 18 Body mass index was estimated as the ratio of weight in kilograms to the square of height in meters. Waist circumference was measured by placing a plastic tape to the nearest 0.5 cm horizontally, at the midpoint of the 12th rib and iliac crest along the midaxillary line. Hip circumference was measured around the widest portion of the buttocks, with the tape parallel to the floor and the waist-to-hip ratio (WHR) was then determined 19 Blood pressure was also measured after the subject had rested for 5 min. House-to-house data collection was done by trained research assistants. However, anthropometric measures and blood pressure parameters were checked at nearby primary health-care facility. Research assistants (data collectors) four in the number being university graduates were trained by the principal investigator for 3 days on the study procedures. These data collectors were blinded to the objectives of the study and the purpose of the physical measurements as a means of controlling measurement bias. In each community, additional four persons were recruited who are indigenes to work with each data collector (making up a two-person team of one data collector and one indigene). In all, there were four teams. The local recruits served as interpreters/guides/assistants to each data collector. Data collection was carried out over 8 days (12–20th) January 2020 with an average of 2 days that was spent in each community. Each data collection team collected data from a minimum of 32 adults (16 households) per day. To ensure the quality of the interview and data quality, random checks were carried out by the principal investigator.
The data collected for the study were analyzed using the Statistical Package for the Social Sciences (SPSS), version 25 International Business Machine (IBM), Armonk, New York, USA. Means and proportions were calculated for continuous and discrete variables, respectively. 95% confidence interval was also determined. Other inferential statistics used for the analysis were the Chi-square test, for the test of association for categorical/discrete data and Student's t-test for continuous variables. Bivariate and multivariate regression analysis models were used to test for the association between hypertension and residence. The cutoff for the diagnosis of hypertension was ≥130/80 mmHg for systolic and diastolic blood pressures. The level of significance was set at P ≤ 0.05.
Ethical clearance was obtained from the Research Ethics Committee of the University of Port Harcourt with registration/approval number: UPH/CEREMAD/REC/MM69/024 before the commencement of the study. The aim of the study was explained to the volunteers and only those who gave consent were recruited as participants.
| Results|| |
The result of the study revealed that age group, marital status, and occupation were the socio-demographic characteristics that were significant on comparison with hypertension. The prevalence of hypertension in oil-polluted and nonoil polluted communities were 59.8% and 46.6%, respectively, comparison of hypertension prevalence value according to the categories of residence showed that they differed significantly (χ2 = 16.974, P = 0.001), and the regression model on crude analysis showed that being married/cohabiting 2.569 (1.888–3.495), residence 1.691 (1.316–2.173) were related to being hypertensive [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6].
|Table 1: Comparison of socio-demographics of participants with residence in an oil and non-oil polluted community|
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|Table 2: Comparison of prevalence of hypertension according to socio demographic characteristics|
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|Table 3: Prevalence of hypertension in an oil polluted and non-oil polluted community|
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|Table 4: Comparison of the prevalence of hypertension according to residence|
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|Table 5: Comparison of hypertension prevalence according to the categories of residence|
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| Discussion|| |
This study compared the hypertension status of people resident in oil-polluted host communities with people resident in communities without any form of oil exploration. This study has revealed that the prevalence of hypertension was higher among participants resident in oil-polluted host communities than among residents of nonoil polluted communities. This difference in prevalence was found to be significant at P < 0.05. More than half the number of participants recruited for this study that are resident in the oil-polluted communities were hypertensive, specifically two-thirds of the participants compared to less than half the number of participants who have hypertension and resident in the nonoil polluted communities. This to a large extent points to the fact that there are underlying factors at interplay in the oil-polluted communities that are contributing to this high prevalence value. Furthermore, two in three persons resident in the oil-polluted communities have hypertension while one in three persons resident in the nonoil polluted community have hypertension. This high prevalence is consistent with the reports on high prevalence in areas with high oil exploration and gas flaring.,,,,,
There abound enormous literatures on the ability of tiny particles from oil pollution in the air to course into the bloodstream through the lungs to engineer damages within tiny blood vessels, thereby increasing the resistance of the vessels to blood flow. Long-term exposure to these particulate matter (PM) such as (PM 1.5, 2.5) and many others in the air as pollutants have been reported to be associated with high blood pressure and an increased risk of cardiovascular diseases.,,,, This possibly could be the reason for the high prevalence of hypertension among residents of oil-polluted communities in the report of their study titled “Is living in a gas-flaring host community associated with being hypertensive? Evidence from the Niger Delta region of Nigeria” showed that the prevalence of hypertension in the gas flaring region was 56.94% as at 2017, but this current study has shown a higher prevalence than what was reported in 2017. Between 2017 and 2020 is 3 years and there has been an increase in prevalence to about 2.9%. This comparison further buttresses the fact that there is a high and fast-growing prevalence of hypertension in the communities hosting oil and gas companies in our environment. This requires an urgent intervention which if not done, in the next 20–30 years, there will be an unimaginable prevalence of hypertension in such region.
Sociodemographic characteristics of participants with hypertension
The regression model on crude analysis showed that the widowed participants were four times more likely to be hypertensive than the unmarried, the married/cohabiting participants had over twice the chance of being hypertensive than the unmarried and those who are separated/divorced had over twice chance of being hypertensive than the single. Speaking of the association between marital status and hypertension, Ramezankhani et al. in their study motioned those participants with the status of divorced contributed 15.2% to the incidence of hypertension in the Iranian adult population. This current study showed prevalence greater than what was reported by Ramezankhani et al. It, therefore, suggests that marital status is related to hypertension status and this finding is consistent with previous reports Ramezankhani et al. Again, Ostchega et al. reported the prevalence of hypertension to be 45.5% for 18 years and over in their study. Participants who do moderate physical activity were 0.058 likely to be hypertensive, meaning that the chances of having hypertension have been reduced by 94.2%. Again, those who indulged in vigorous physical activity were 0.007 times likely to have hypertension which also means that they had reduced the chances of being hypertensive by 99.3%. This implies that moderate to vigorous physical activity having a protective effect greatly reduced the chances of being hypertensive. There are reports on the duration and intensity of physical activity ranging from physically inactive to rigorously active could contribute to the prevalence of hypertension. This finding is consistent with the report of Hou et al. who revealed that there is a significant association between the duration of physical activity and the prevalence of hypertension. The findings from this study agree with the previous reports of studies done on similar oil and gas company host communities in which they reported that residents in oil and gas flaring exploration host communities was a significant factor for the high prevalence of hypertension.,,,
| Conclusions|| |
The prevalence of hypertension among person resident in oil-polluted communities was 59.8%, while persons living in communities not exposed to oil pollution had hypertension prevalence of 46.6%. These two prevalence values were significantly different.
The study showed that residence, overweight WHR, and smoking equally increased the chances by more than 1.5 times of being hypertensive; widowhood increased the chances of having hypertension by four times, married/cohabiting status increased the chance by over two times, being separated/divorced had over twice chance of being hypertensive. Although, moderate physical activity reduced the chances of being hypertensive by 94.2%, and vigorous physical activity reduced the chances of being hypertensive by 99.3%. We recommend reduction in gas flaring and oil spillage, remediation and that findings from this study be used as reference for planning intervention and advocacy for efforts to reduce the oil pollution in host communities. In addition, we recommend that exercise be taken more seriously as it reduces the chances of having hypertension.
We appreciate the participants and the research assistants who took part in the study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]