The Impact of Human Activities on River Pollution and Health-Related Quality of Life: Evidence from Ghana

Abstract

Due to rapid development and population growth in Ghana’s urban and peri-urban areas, most freshwater resources are degrading, directly affecting residents in these vicinities. This study, therefore, evaluates how human activities such as urbanization, farming and industrialization affect the Bonsa River and the health-related quality of life of residents living downstream. The study adopted statistical package for the social sciences (SPSS) and partial least square structural equation modeling (PLS-SEM) to assess the data retrieved from the residents living in and around the Bonsa River in Tarkwa Nsuaem, Ghana. The study’s outcome reveals a positive and significant impact of land use change on freshwater resource degradation and poor health-related quality of life of the inhabitants in the catchment area. The study has numerous practical and policy implications for the government, environmental and healthcare industry, and policymakers.

1. Introduction

Fresh water is an essential resource because it only makes up 0.3 percent of all the water on Earth. Water is essential for life and plays a significant role in how humans grow and stay alive (Balasubramanian, 2015). Water availability is affected by both natural elements and things that people do. Nevertheless, the most significant effect on life is how land use change impacts water resource quality [1]. Most of the pollution in the freshwater resource that flows through Ghana, especially Tarkwa Nsuaem, is due to mining, urbanization, and agricultural land use changes. This significantly affects those who live in the catchment area and beyond. Emmanuel, Jerry, and Dzigbodi [2] report that physical, chemical and bacterial tests were done on the water of the Bonsa River. Using comparisons, it was obvious that the drinking water parameters do not satisfy international requirements [3]. So, the Bonsa River cannot be used for drinking, cooking, bathing, or washing clothing.

As the population has expanded, so has the need for sanitary services. The number of people living in the river basin has expanded faster than the number of sanitation services. The municipal officials indicated that they could not fulfill the growing demand since they did not have enough money, equipment, and facilities. The population is growing swiftly, and there is a lot of industry and agriculture in the catchment area. Physical, chemical, and microbiological investigations by A. A. Obiri-Yeboah et al. [4] demonstrated that the Bonsa River is polluted. Polluted water transmits various diseases and drinking or using it has adverse impacts on the resident’s health-related quality of life. Extended literature has established that the main anthropogenic causes of environmental pollution, especially water resource degradation, are industrial, agricultural and household activities. Although, some individual activities also contribute to the sustenance of the environment. This conscious act taken by people to minimize or mitigate the negative influence of human activities on the environment is known as pro-environmental behavior [5]. It is therefore crucial to understand the residents’ perception of how human activities such as farming, mining, and household waste management influence adversely affect freshwater resources, specifically the Bonsa River, and their health-related quality of life [6].

2. Method

2.1. Study Setting

Tarkwa Nsuaem Municipality, the study area is renowned for gold and manganese production, its villages primarily fish and farm. About eight of the nation’s largest mines are located in the Municipality, significantly contributing to the nation’s mining industry, which is located in the Western Region of Ghana. Prestea Huni-Valley district, Nzema East municipality, Ahanta West district, and Mpohor Wassa East district are its northern, western, southern, and eastern neighbors. It has a population of 90,477 and a land area of 905.2 square kilometers [7]. Figure 1 represent the geographical map of Tarkwa Nsuem and Bonsa River.

The Bonsa is 44 kilometres long from where it meets the Ankrobrah to where it emerges at its source. Residents in Bonsa, farther downstream, and at the water treatment facility’s source are likely to suffer negative effects from any hazardous substance that enters the river system. The Bonsa River feeds Ankobrah, which empties into the sea. The Bonsa river is made up of rocks from the Birimian and Tarkwain formations. People think that these types of rocks are what make the water in the area so mineral-rich. The ridges that are part of the gold mining concessions are where almost all of the water that flows into the Bonsa river comes from [7,8]. Figure 2 represent the geological map of Bonsa River and the Tarkwa-Nsuem Municipality, Western Region, Ghana.

2.2. Materials and Methods

This study aimed to determine how human activities affect pollution of the Bonsa River and how that affects the health-related quality of life of the residence. To achieve this aim, a quantitative research was done through convenient sampling from May to August 2021. The survey questions were answered by 300 household heads living in Bonsa, farther downstream... Quesada et al. Reference [9] said that the 10 times rule should be used to determine the minimum sample size for a partial least square structural equation modeling (PLS-SEM) analysis [9]. This criterion says the minimum sample size should be “ten times the highest number of structural routes in a structural model that lead to a specific construct.” This study’s structural model is made up of six constructs. Three of these constructs are independent variables, and one is a dependent variable. Based on the 10 times rule, this criterion needs at least 30 responses. However, after cleaning up the data, 256 answered questionnaires were usable (see Supplementary).

2.3. Analytical Methods

SmartPLS version 3 and SPSS version 26.0 were used to analyse the data. The variance-based structural equation model was employed because it can forecast causal relationships between the construct variables and take into account errors in the indicator variables [10]. The measurement model relates indicators to the latent construct (hypothetical variable), demonstrating how measurement items reveal independent and dependent constructs. The structural equation model ties exogenous constructs to endogenous constructs. Given that the goal of this study is to explain a causal relationship, PLS-SEM is also the best technique to apply.

3. Results

3.1. Demographic Characteristics of the Respondent

Two hundred and fifty-six (256) of the questionnaires were usable and credible. A total of 52.5 percent of the 256 respondents were female, whereas 47.5 percent were male. Nevertheless, 43.2% of respondents were between 30 and 44, whereas 36.3% were between 18 and 29. In addition, 4.8% of respondents were at least 60 years old, whereas 15.2% were between 45 and 59 years old. In addition, 42.3% of respondents held a high school diploma, 32.6% held a degree or less, and 22.2% held a bachelor’s degree or above.

3.2. Analysis of Measurement Models

To evaluate the reflected measurement models, the validity and reliability of each construct were evaluated [10,11].

Table 1. Construct Reliability and Validity.

Latent Variables	Convergent Validity	Internal Consistency Reliability
	The Average Variance Extracted (AVE)	Composite Reliability	Cronbach’s Alpha
	>0.50	>0.70	>0.70
Agriculture	0.631	0.895	0.854
Domestic	0.578	0.872	0.816
HRQoL	0.855	0.946	0.912
Industrial	0.596	0.879	0.827
Water pollution	0.645	0.845	0.725

displays the average variance extracted (AVE) and composite reliability (CR), determined when the measurement model was executed with PLS-SEM. All structures have CRs greater than 0.70 and AVEs greater than 0.50, which satisfies the rule of thumb [12,13]. Each construct’s AVE was more significant than its squared correlation with other constructs [11]. The results of Table 1 posits that for the reflective constructs agricultural activities, domestic activities, HRQoL, industrial activities and water pollution the Cronbach’s alpha are 0.854, 0.816, 0.912, 0.827 and 0.725, the composite reliability scores are 0.895, 0.872, 0.946, 0.879 and 0.845, and AVE are 0.631, 0.578, 0.855, 0.596 and 0.645, respectively. Examining the Heterotrait-Monotrait Ratio (HTMT) of reflective construct indicator values served as a second test for the discriminant validity of reflective measurement models. Compared to other constructs in the structural model, measurement model indicators should have the highest loading of 0.9 or less [13].

These results in

Table 2. Discriminant validity of the variables. Heterotrait-Monotrait Ratio (HTMT).

	Agriculture	Domestic	HRQoL	Industrial	Water Pollution
Agriculture	0.795
Domestic	0.853	0.760
HRQoL	0.828	0.896	0.824
Industrial	0.861	0.855	0.893	0.772
water pollution	0.790	0.811	0.895	0.818	0.803

shows that reflected measuring techniques help identify differences and satisfy the criteria for evaluating discriminant validity. Therefore, the model is valid and reliable for further analysis.

3.3. Evaluation of Structural Model

First, each predictor’s tolerance (VIF) value needs to be higher than 0.20 (less than 5).

Table 3. Effect size (f²) and Predictor’s tolerance (VIF) of the structural model.

	f2	VIF
Water pollution -> HRQoL	4.029	1.000
Agricultural activities -> Water pollution	0.023	4.828
Domestic activities -> Water pollution	0.088	4.626
Industrial activities -> Water pollution	0.105	4.875

displays the VIF for each structure meet the rule of thumb. In the structural model, collinearity between the predictor components is therefore robust, and we can continue to review the results report [14].

The significance of the relationships is then determined using the route coefficients. These outcomes are all shown collectively in

Table 4. Path coefficient of the structural model.

Path Coefficients	Original Sample (O)	T Statistics (|O/STDEV|)	p Values	Decision
Water pollution -> HRQoL	0.895	85.361	0.000	Yes
Agricultural activities -> Water pollution	0.177	3.000	0.003	Yes
Domestic activities -> Water pollution	0.337	6.143	0.000	Yes
Industrial activities -> Water pollution	0.378	6.332	0.000	Yes

. The significance of the link was acknowledged based on the p-value at five percent significance level (<0.05). The R² values of the endogenous latent variables are examined in the third stage. According to our findings, the suggested model can, on average, account for water pollution and HRQoL at 72.1% and 80.1%, respectively [15].

The magnitude of the effect, or f², of interactions between constructs is calculated in Table 4. A small effect size is defined as being between 0.02 and 0.15, a medium effect size is between 0.15 and 0.30, and a high effect size is over 0.30 (Cohen 1998). Table 4 shows structural model results supporting all four (4) hypotheses (H1–H4).

Figure 3 depicts the final structural equation model’s indicator loadings, route coefficients, and R-squared values, which were determined using PLS analysis. The route coefficient for “agricultural activities and water pollution” is 0.177, as depicted in Figure 3, and the bootstrapping p-value is 0.003, which is consistent with this. This indicates that the majority of respondents believe that agriculture has a significant direct impact on water pollution (Bonsa River). The p-values for the path coefficient of “household activities on water pollution,” which is 0.337, and its effect size, f², are likewise less than 0.000. This research demonstrates that residential activities have a substantial beneficial impact and nearly little impact on water contamination. The bootstrapping p-value for the route coefficient between industrial activity and water pollution is 0.000, which is equal to 0.37. This appears to indicate that industrial activity has a significant direct impact on water pollution (Bonsa River). The path coefficient for the relationship between water pollution and HRQoL is 0.895%, the effect size is 4.029, and the p-value is 0.000. This indicates that water pollution has a profoundly negative impact on the health-related quality of life of individuals.

4. Discussion

From the inhabitants’ perspective, it was determined that human activities in and around the Bonsa river basin are the principal causes of the river’s contamination. Thus, the researcher categorized the contamination of the Bonsa River as industrial, residential, and agricultural activities. The researchers also investigated the correlation between the quality of life of the residents living downstream and the pollution of the Bonsa River.

Hypothesis 1 (H1).

Agricultural activities significantly affect the pollution rate of the Bonsa River.

According to Hypothesis 1 (H1) which posits that agricultural activities significantly affect the pollution rate of the Bonsa River. The results revealed a beta value of 0.177 (p = 0.003). In other words, this investigation’s findings support the existing literature. This result is consistent with earlier research by [16], which revealed that agricultural activities such as the wrong application of agro-chemical and the use of dangerous chemicals for fishing are strongly associated with water contamination. In addition, it indicates that pesticides and fertilizers are the most prevalent agricultural contaminants. Although farm animal waste and silt contribute to water contamination, agricultural runoff has the greatest impact [17]. When irrigation, drainage, or precipitation transport herbicides, insecticides, and inorganic fertilizers from agricultural farms, they contaminate rivers and streams [18]).

Wimalawansa and Wimalawansa [19] investigated how alterations in agricultural practices can affect the health of Sri Lankans. They discovered that harmful farming practices include irresponsible overuse of toxic agrochemicals. It is disturbing that the usage of agrochemicals causes land and water contamination. Inorganic fertilizers, insecticides, and herbicides can contain toxic metals. These contaminants cannot be seen or tasted because they are usually in extremely low amounts of water. Therefore, it takes time for their adverse effects on humans to show. Notwithstanding, overtime, they developed or worsen life-threatening diseases, such as chronic renal failure.

When herbicides are applied to water bodies, aquatic animals may suffer because decomposing plants diminish the oxygen content of the water, causing fish to drown. Several herbicides that kill aquatic vegetation, such as copper sulfite, can be hazardous to fish and other aquatic species due to their high concentrations [20].

Hypothesis 2 (H2).

Domestic activities have a direct impact on the pollution of the Bonsa River.

The investigation results supported Hypothesis 2 (H2), which claims that domestic activities have a direct impact on the pollution of the Bonsa River. The statistics suggest that beta equals 0.337 percent (p = 0.000). This is in line with research done in highly populated places, where the detrimental effects of contaminated water are more likely to affect people, such as the Korle Lagoon in Greater Accra. Sewage, household waste, and other new pollutants were some of the worst contaminants found in the water [21,22]. According to recent studies, untreated sewage water entering rivers, lakes, wells, etc., changes their chemical and biological makeup, making these water sources more likely to spread typhoid, cholera, dysentery, and skin issues when consumed [23].

Hypothesis 3 (H3).

Industrial activity directly contributes to the Bonsa River’s pollution.

The study’s findings confirm Hypothesis 3, which claims that industrial activity directly contributes to the Bonsa River’s pollution, according to the test result for this hypothesis (H3). The value of beta, which is 0.378 (p = 0.000), illustrates this. Afroz, Masud, Akhtar, and Duasa [24] define industrial waste or trade effluent as any liquid or solid that leaves an industrial site or any facility for treatment and disposal other than a residential sewage system. The water supply is harmed by the frequent discharge of wastewater into rivers by several businesses along riverbanks. Metals in industrial effluents, including mercury, lead, cadmium, and copper, are harmful to aquatic life, human health, and welfare.

Industrial effluents are the principal cause of water pollution in industrial areas. The discharge of these wastes into water bodies leads to long-term water contamination [25]. Thermal plants that utilize water to cool their generators and produce excess heat cause thermal pollution. Extreme heat impairs biological responses, harming aquatic life and human health [26,27]. Spill from industrial sites can distribute poisons to vast downstream regions.

Mining influences freshwater through the excessive use of water required to process ore, the discharge of mining waste, and seepage from tailings and waste rock impoundments. Water has been described as the “most frequent fatality of mining” [28]. The recognition of the environmental damage caused by industrial operations especially mining done with little to no concern for the environment is growing. By its very nature, mining uses, redirects, and significantly degrades water sources [29]. Acid mine drainage, heavy metal contamination and leaching, processing chemical pollution, erosion, and sedimentation are the four significant mining impacts on water quality [30]. According to studies, the water quality in mining regions has deteriorated dramatically.

Most rivers, streams, and other water sources are contaminated or dry. Small-scale mining is the major contributor to water contamination in Ghana and the second-largest contributor to water contamination in Africa [7,8]. Commonly, small-scale miners mostly work beside or in river bodies, causing bank erosion and increasing the likelihood of flooding during severe rains. Due to this condition, mining villages have recently experienced flooding. As it enters nearby homes and ecosystems, unchecked water flow causes property damage and death. To make room for mining operations, most rivers and streams are diverted from their natural routes and, in some cases, blocked.

Hypothesis 4 (H4).

The Bonsa River has a considerable negative impact on the health of downstream residents.

The test results for Hypothesis 4 (H4) reveal that the Bonsa River has a considerable negative impact on the health of downstream residents. The p-value of 0.000 implies that contaminated water can cause immediate and long-term harm to human health. A person’s exposure to a pollutant has immediate impacts that manifest within hours or days. When exposed to extremely high concentrations, virtually every pollutant can cause acute adverse health effects in humans. Microorganisms such as bacteria and viruses are the contaminants in drinking water that are most likely to reach concentrations high enough to have an immediate adverse effect on health [31]).

As a result of widespread irrigation with contaminated water, harmful effects may linger for several years and have a negative effect on the quality of groundwater and soil. The pollution of water has numerous implications. Some impacts of water contamination emerge immediately, whereas others take months or years to manifest. Additionally, because there are toxins in the water, when animals drink it, and humans consume animal products, the water’s toxins are conveyed to humans. Typhoid and cholera are infectious diseases that can be contracted by the consumption of polluted water [32].Microbiological water contamination is what this is. Regular drinking of polluted water can negatively impact the heart and kidneys of humans. Inadequate blood circulation, diarrhea, skin rashes, vomiting, and brain damage are other health problems associated with contaminated water. Water contamination is the most significant cause of death worldwide [21,22].

Pollution affects our potable water, lakes, rivers, and seas and this is a ubiquitous global concern [31]. In less developed nations, where contaminated water is the primary cause of death, one thousand children each hour die from diarrhea-related illnesses [33]. In order to improve health and sanitation, there must be sufficient availability of potable water. When there is insufficient water for bathing, flushing toilets, and cleaning food, utensils, and clothes, the probability of individuals contracting diseases such as diarrhea rises. The state of surface rivers has a substantial effect on public health.

5. Conclusions

The project aims to determine how domestic, agricultural, and industrial activities affect the Bonsa River and residents’ health. Living, farming, and working along the Bonsa River affects downstream residents’ health and the river’s health. Variance-based structural equation modelling (PLS-SEM) explored the link between human activity, water pollution, and downstream residents’ health. WHO is concerned about the contaminated Bonsa River. Dissolved oxygen, total dissolved solids, electrical conductivity, and pH are beyond WHO-recommended ranges.

The study focuses on the global issue of drinking water shortages and the depletion of freshwater supplies, which affects local populations. Specifically, it examines how people and organizations’ behaviour affects inhabitants’ quality of life and health and the river’s state, which is vital to the planet’s ecosystem. Environment, people, and economy are all interconnected and understanding environmental patterns, relationships, systems, and this causal link is vital.

Hypothesis 1 indicates that agricultural activities have a substantial, direct impact on the pollution of the Bonsa River. The investigation supported hypothesis 2 (H2), which states that domestic activities significantly impact Bonsa River pollution. The results of the H3 test support Hypothesis 3, which states that industrial activities have a direct effect on Bonsa River pollution. Test 4 (H4) results indicate that the Bonsa River pollution impacts residents’ health-related quality of life.

This study’s findings can guide local governments, communities, and other social, economic, and environmental partners in the region in formulating the most effective programmes for mitigating the environmental damage caused by mining operations and revitalizing the local economy and way of life. The case study of the Bonsa river watershed could serve as a roadmap for future inquiries into the dangers and environmental damage caused by abandoned mining activities.

There are significant arguments for adopting a holistic approach to this environmental and health problem. River pollution is an issue that many individuals, businesses, and organizations must address. Due to the situation’s complexity, long-term and short-term possibilities should be considered while determining a solution. Environmental education is an excellent technique for preventing the problems of the twenty-first century from worsening. One way to approach this goal is to understand and implement behavioural models and theories.

The Environmental Protection Agency (EPA), the Tarkwa Nsuaem Local Authority, and other relevant organizations must be strengthened to protect the city’s water resources, especially the Bonsa River. People irresponsibly discharge untreated effluents, defecate outside, channel raw sewage, dispose of industrial waste, and dump trash in the Bonsa River. This can be resolved by educating farmers on agrochemicals and motivating them to use vegetation and farming runoff to purify water. The private sector, notably mining companies, may conserve water resources by channeling and treating the wastewater generated by their activity and investing in environmental sustainability, particularly the water and air quality in the communities where they operate. To better the environment, individuals must alter their behaviour. To purify home wastewater, new or upgraded sanitation networks are necessary.

There is abundant evidence from various sources that drinking clean, portable water is helpful to one’s health. All key human actions that pollute the Bonsa River and impair the local population’s health have been covered.

We argue that further research is required on this topic, especially given the probable difficulty of accomplishing Sustainable Development Goals 3 (health) and 6 (climate change) (water and sanitation). In addition, we believe it will be beneficial for researchers, policymakers, and the government to learn how individuals feel about the societal causes and adverse effects of river pollution on human health. This information can be used to evaluate ways to meet water needs while protecting resources.