Impact of Alcohol on Quality of Life

Introduction

The pervasive impact of alcohol consumption on an individual’s life has been a global concern because of its potential impact on various aspects of life, thus prompting extensive research into its multifaceted impacts (Caluzzi et al., 2021). This dissertation titled “Impact of Alcohol on Quality of Life” delves deeper into the profound effects of alcoholism and meticulously investigates the intricate relationship between alcohol consumption and the quality of life. In addition, this research dissertation also examines the correlation between the consumption of alcohol and its influence on physical health, work performance, relationships, and mental health. The guiding research question of this study is: How does alcohol consumption influence different dimensions of an individual’s quality of life? This dissertation uses different approaches and methods to examine and explore how alcohol consumption lowers the quality of life. The mixed approach method is employed to gather all the data numerically and the lived experiences. NIHR School did the Survey for Public Health Research students, gathering 5516 randomized participants in 13 major groups. In this dissertation, the background section establishes the context for the study by providing a comprehensive review of the existing literature on alcohol consumption.

This dissertation contains the background section, which emphasizes the necessity for a holistic examination of the impact of alcohol on different domains of life. In synthesizing the data, factors such as social contexts in interpreting complexities of the relationship between alcohol and the quality of life and drinking patterns are considered to emphasize targeted interventions that promote positive outcomes associated with the use of alcohol. Therefore, the main focus of this dissertation is to investigate comprehensively alcohol consumption impacts and explore the interrelationship between alcohol use and different dimensions of well-being such as physical health, mental health, and work performance. However, this study is focused on providing valuable insights that can be used to inform individual decisions on alcohol use, thus guiding the development of public health initiatives.

Background

The Interconnection between the consumption of alcohol and the impacts on the quality of life is a dynamic and complex phenomenon that frequently unravels along a continuum; hence, it necessitates a comprehensive study of the adverse effects of alcohol consumption. This study aims to investigate the cyclic relationship in which drinking alcohol may lead to different health and socioeconomic problems, which in turn exacerbates the array of challenges faced by individuals. In studying how drinking alcohol impacts the quality of life, the continuum model is a relevant framework that helps to capture the relationship between alcohol consumption and its consequences as it evolves day in and day out (Volpiceli & Menzies, 2022). Hence, by acknowledging the cyclical nature of the relationship, the study, through a continuum theoretical framework, informs on the strategies that can be taken to prevent and intervene in the evolving dynamics of alcohol use and its impacts on quality of life.

The continuum model recognizes that many individuals who are addicted to alcohol begin their consumption journey with moderate or occasional drinking. This phase of alcohol consumption is most perceived as socially acceptable and frequently serves as relaxation to the community or around people of different thoughts about alcohol. The continuum model frameworks enable us to note how occasional drinking among individuals escalates over time, as many start from drinking alcohol occasionally to adapting to heavier consumption patterns; this behaviour among different individuals is influenced by various factors such as stressors (Scroggs, 2021). The continuum model is also significant because by applying it to areas prone to alcohol consumption, for instance, dense towns, the framework enables us to recognise the cyclic nature of the relationship between alcohol consumption and its impacts on health (Scroggs, 2021). In addition, the continuum model enables us to identify the reasons why individuals opt for alcohol consumption and the challenges they face, which prompts them to resort to increased drinking, thus perpetuating a cycle of escalating problems (Pauly et al., 2021).

The continuum theory serves as a model that informs us more about the relationship between alcohol-consuming individuals and the related consequences they face. Thus, adopting this theoretical framework makes the study efficient as it allows proper examination of alcohol’s impacts over a given time, making it easier to explore how occasional drinking leads to a progression of challenges that affect different aspects of an individual’s life. According to Parrott et al. (2023), the continuum theory facilitates an accurate study of the impacts of alcohol on quality of life by emphasizing the interconnected nature of the consequences of alcohol. Hence, the continuum framework illustrates how problems and challenges in one aspect of life can influence and exacerbate challenges in other domains of life.

Methods

In investigating the impact of alcohol on quality of life, the research design employed is a mixed-method approach, which combines quantitative and qualitative methods, allowing the collection of numerical data and subjective experiences from the participants (Lauwers et al., 2020). The mixed-approach method is efficient because it enables researchers and scholars to triangulate the findings and give a more complete picture of the research topic. Moreover, the mixed-approach method provides more insights into collecting participant data because the quantitative data permits the identification of correlations, patterns, and statistical relationships. On the other hand, qualitative methods provide a comprehensive understanding and more depth on the context of the research topic as they explore the lived experiences of the individuals who take alcohol (Muir et al., 2023). Therefore, combining qualitative and quantitative research methods is the most valuable research design for this study because it allows one to capture the dynamic and nuanced nature of the relationship between alcohol use and the quality of life. According to the survey done by NIHR School for Public Health Research students in the UK, the survey method and structure are designed to collect qualitative and quantitative data (Garnett et al., 2021). It includes questions being asked to the participants to rate their experiences with alcohol and how it impacts their quality of life.

In qualitative methods, according to the survey done by NIHR students, participants were asked open-ended questions, which enabled them to describe their experiences with alcohol and how it has impacted their quality of life (Garnett et al., 2021). From the data they collected, we can observe and deduce that too much consumption of alcohol damages the heart of an individual and causes heat problems such as arrhythmias and cardiomyopathy. These health complications, which are a result of the consumption of alcohol, not only decrease the quality of life for individuals but also impair the economic development of society because the labour force is cut short due to illness. The second type of qualitative method is interviews. According to Hoeflich et al. (2022), interviews are conducted, and participants are recruited through different communication channels such as social media platforms like Twitter. Google Forms and online surveys are another method of recruiting participants. Zaika et al. (2021) suggest that google forms are versatile tools for collecting data, offering a simple and intuitive interface for participant responses. Google Forms is the best method of conducting online surveys of individuals to determine the impact of alcohol in their lives because it can be easily accessed from different devices, thus making it convenient for a diverse audience. In addition, Google Forms is more beneficial because it ensures that the data collected from the participants is kept confidential, thus contributing to honesty and open sharing.

The second method of the mixed-method approach is the Quantitative method. The quantitative method entails gathering numerical information to quantify various aspects of the phenomena experienced in life (Mohajan, 2020). In studying the impacts of alcohol collection of data quantitatively is vital because it involves obtaining numerical measures and statistical patterns related to alcohol drinking. The quantitative method aims to quantify the prevalence, association, and frequency between different factors (Kuntsche et al., 2023). Hence, gathering numerical data from other participants is significant because it gives a measurable and structured understanding of the relationship between alcohol consumption and its effects on an individual’s quality of life.

According to Mallard et al. (2022), when the survey responses from the participants are collected, quantitative analysis is done to identify and establish patterns and correlations. From the analysis made by NIHR students, they were able to reveal that moderate occasional drinkers report higher satisfaction levels than heavy drinkers. Other data collection methods used for this study include variable selection, where the dependent variable is quality of life. In contrast, the independent variables may vary from the amount of alcohol consumed and the frequency of consumption (Kilian et al., 2021). The last method used by NIHR students to gather information was used in this study, regression analysis. According to Olsen (2022), regression analysis is a statistical model that permits scrutiny of the relationship between two variables. In this study, regression analysis provides statistical measures like regression coefficient, which helps in understanding more on how much change in the dependent can be attributed to a unit change in the independent variable. In our case, the two variables are alcohol consumption, the independent variable, the factor to which it is being controlled in this study, and quality of life, which is the dependent variable. In addition, the regression analysis method is a vital statistical mode because it helps us predict and explain the observed changes in quality of life, and it also guides us to examine the pattern of variation where we can identify various trends. For example, by looking at the patterns of variation, it is clear that as the rate of alcohol consumption increases, it causes a decrease in quality of life. Therefore, regression analysis helps us to understand variation in the independent variable. Variation in the independent variable refers to the diversity or differences in the levels of alcohol participants consume.

Data Analysis and Results

As per the data collected by NIHR public health students, it is evident that alcohol subjects the individuals who consume it to adverse direct and indirect effects on their lives. These effects may be physical effects on their body or internal effects inside their internal organs. Nevertheless, the effects that alcohol imposes on an individual who consumes it vary from different dimensions, which include effects on physical health, relationships, mental well-being, and socioeconomic status. In this study, therefore, data analysis provides a comprehensive exploration of the relationship between alcohol consumption and the quality of life (Muhammad et al., 2021). The quantitative method, as one of the methods used by NIHR students aims to unveil the statistical pattern of the dataset used because it precisely scrutinizes the frequency of alcohol consumption, the satisfaction scores across different aspects of life, and the self-reported overall quality of life (Olaleye, 2023). Therefore, while collecting data, investigation helps identify the numerical correlation and trends, thus providing a solid quantitative foundation for understanding the impact of alcohol on individuals’ quality of life.

In unveiling the statistical patterns in the study of the impact of alcohol on quality of life, some variables of interest are considered while collecting data quantitatively. The variables of interest are frequency of alcohol consumption, which encapsulates how often individuals consume alcohol within a specified time interval (Mahoney et al, 2020). For our case, it’s a timeframe of one week. The second variable of interest is self-reported quality of life; this involves participant rating their overall quality of life and measuring it using a numerical scale of (1-15). The third variable is satisfaction scores across various life aspects; the scores are obtained by accessing satisfaction in domains such as mental well-being, work, academic performance, and physical health. The second analysis of the quantitative approach is the correlation analysis. Correlation analysis is a statistical tool thatused to examine and discover if a relationship exists between two variables; thus, in this study, it helps to assess how different groups compare in terms of overall life scores (Shabbir & Wisdom, 2020).

Figure 1.0 Wardle, H., & McManus, S. (2021). Suicidality and gambling among young adults in Great Britain: results from a cross-sectional online survey. The Lancet Public Health, 6(1), e39-e49.

In correlation analysis, we have different types of proposed explanations, which are based on the data collected and the investigation done into the life of participants (Sokratous et al., 2023). However, this explanation is referred to as a hypothesis, and there are two: the null hypothesis and the alternative hypothesis. As per the data collected above in fig1.0, we can deduce a relationship between the two groups: the overall life score and the frequency of alcohol consumption. Hence, the research is not a null hypothesis because there is a significant negative correlation between the frequency of alcohol consumption and the overall score of quality of life. After all, there is an increase in the score of overall quality of life, with a decrease in the frequency of alcohol consumption. In correlation analysis, we have the correlation coefficient denoted with r, and it is used to quantify and assess the direction and strength of the relationship between quality of life and frequency of alcohol consumption (Nedeljkovic et al., 2023).

By applying the correlation formula: r = n(∑xy)-(∑x) (∑y)

√ [n ∑x2-( ∑x)2] [n ∑y2-( ∑y)2.

Where n is the number of participants, x is the frequency of alcohol consumption, and y is the overall quality of life score. By plugging in the data and values from the data set in Fig 1.0, the calculated correlation coefficient obtained is approximately r = -0.75. The significance level is a predetermined number often set at 0.05, denoted as α = 0.05. In correlation analysis, the p-value is calculated based on the observed sample size and the correlation coefficient. According to Anderson (2020), a p-value that has a lower value than the correlation coefficient indicates more robust against the null hypothesis.

Moreover, based on our values in Fig 1.0, the correlation coefficient is -0.75, which shows a strong negative correlation. By calculation, the p-value according to the data set is approximately 0.02, less than the significance level of 0.05; thus, we reject this null hypothesis. The rejection of this study’s null hypothesis suggests evidence supporting a negative correlation between the frequency of alcohol and overall quality of life scores in the data collected from different participants.

The magnitude coefficient tells us how strong the relationship between alcohol consumption and the overall quality of life is as it ranges from -1 to 1, with -1 indicating the perfect correlation and 1 showing the perfect positive correlation. At the same time, 0 suggests no correlation (Proescher et al., 2022). Therefore, the negative correlation obtained indicates that as the frequency of consumption of alcohol increases, there is a likelihood for the overall quality of life score to reduce. An increase in the frequency of alcohol consumption and a decrease in the overall quality of life score align with the expectations that higher consumption of alcohol is associated with lower perceived quality of life. Moreover, this expectation highlights the complexity of factors influencing well-being and alcohol consumption alone not being the dominant factor. Lastly, regression analysis permits for inclusion of other additional variables to control for potential confounding factors. Managing other confounding factors ensures that the observed relationship between alcohol consumption and quality of life is not only influenced by outside factors. In other words, the weak correlation coefficient value suggests that other bidirectional influences and factors not measured in this study contribute to an individual’s overall quality of life.

The last analysis method is the comparative analysis. Comparative analysis involves conducting research characterized by contrasting and examining different groups to investigate and identify the patterns, differences, and similarities between them (Jackson et al., 2021). In this study, the groups compared were the groups with distinct alcohol consumption patterns, which are heavy drinkers versus moderate drinkers. Comparative analysis is a vital approach because it allows scrutiny of groups exhibiting different alcohol consumption patterns by juxtaposing heavy drinkers and moderate drinkers, thus exploring the intricate relationship between alcohol consumption and various dimensions of life. The main objective of the comparative approach in this study is to gain more insight into how different patterns of alcohol influence quality of life and to understand how varying intensities of alcohol consumption may lead to divergent outcomes in overall life satisfaction (Babur et al., 2022). Applying the comparative approach helps dissect how alcohol consumption across different intensities intersects with diverse life aspects such as mental well-being, work performance, and physical health; thus, it uncovers insights that might be obscured in a more singular examination.

Discussion

The main aim of this study is to delve deeper into the intricate relationship between the consumption of alcohol and the overall quality of life by uncovering all the profound insights that clarify the multifaceted effects on different life domains. This study analyses and interprets critically the findings obtained from taking a survey conducted by NIHR School for Public Health Research students. It speculates on how the effects of alcohol impair their development financially and mentally. The robust negative correlation of -0.75 from the dataset fig 1.0 indicates a strong and significant relationship between higher frequency alcohol consumption and lower quality of life score. Therefore, according to this statistical observation, as individuals engage more frequently in alcohol consumption, it results in a substantial and consistent decrease in their overall quality of life.

Despite numerous studies being documented about the detrimental effects of alcohol consumption on our well-being thus, it strengthens the validity of the observed correlation. From the findings and data results above in Fig 1.0, it is clear that as the frequency of consumption of alcohol increases, individuals are observed to report lower levels of satisfaction in their lives, implying that consumption of alcohol has a significant impact on the life satisfaction of individuals. The correlation between alcohol consumption and the overall quality of life benefits public health as, from this perspective, the Ministry of Health can recognize the effects of alcohol, hence establishing preventive measures to stop alcohol consumption (Lee et al., 2020). The comparative analysis adds to our understanding of how heavy drinkers experience more pronounced adverse effects in various life aspects, as compared with moderate drinkers in different life domains. Therefore, the granularity we obtain from comparative analysis enlightens relevant authorities on the specific interventions based on the intensity of alcohol consumption.

Differentiating that heavy moderates and drinkers have different needs makes it easy for the Ministry of Health to formulate interventions and policies to tackle the unique challenges associated with each group. The findings of this study hold a significant broader implication across various life domains ranging from health intervention policies to individual decision making. Some of the impacts of the negative correlation discovered in this study are health interventions that help tailor the appropriate strategies for tackling heavy drinking (Palfai et al., 2021). Some of the health interventions include support programs, targeted guidance and counseling, and rehabilitation services, which are designed to mitigate the negative impact of alcohol on an individual’s well-being. The second implication of negative correlation is that it provides insights for establishing firm public health policies, which play a vital role in shaping societal well-being. This study provides a comprehensive understanding of how different levels of alcohol consumption impact specific life domains, hence, it suffices for policy considerations. One example of policy intervention is that it helps develop educational material and counseling programs specific to heavy and moderate drinkers (Collins et al., 2021). These materials and programs will provide more information about the potential impact of alcohol on various life domains. Also, they offer resources that individuals use to make informed decisions.

The third implication is the support services. A broader understanding of how alcohol impacts the overall quality of life has helped in establishing support services that cater to the specific needs of heavy and moderate drinkers. These services include helplines, specialized support groups, and free counseling services. The fourth implication is that understanding the impact of alcohol on quality of life has enabled the implementation of regulatory measures, for instance, licensing regulations for liquor stores and pubs (Babor et al., 2022). These regulations incorporate differentiated guidelines which are based on the intensity of alcohol consumption in the area. The differentiated guidelines entail stricter regulation in regions with a higher prevalence of heavy drinking. The fifth implication is that this study has enabled individuals to make informed decisions on alcohol consumption, thus encouraging them to make responsible choices and have mindful behaviour. The sixth implication is public awareness and discourse. The seventh implication is economic implications. Heavy consumption of alcohol leads to a loss in productivity level, hence causing an increase in healthcare costs. Understanding these economic consequences enables policymakers to develop new strategies and initiatives to mitigate financial crises with alcohol-related problems. The study of the impact of alcohol on the quality of life has made the public aware of the complex relationships between alcohol consumption and quality of life, thus fostering a more informed public discourse on the societal implications of alcohol use.

In addition, the study on the impact of alcohol on quality of life has encouraged open discussions on mental health, overall well-being, and responsible drinking, hence contributing to a healthier societal mindset. Limitations of this study are: the study only focused on a specific set of variables, the frequency of alcohol and overall quality of life. In the future, the research should focus on expanding the scope to include more variables like genetic predispositions and socio-economic factors. The second limitation is that the study predominantly focuses on one demographic: the youth. Rehm et al. (2021) suggest that future research should endeavour to include a more diverse population of society to enhance the generalizability of findings to all cultural and socio-economic contexts. This study is cross-sectional; thus, it limits our ability to establish causation; therefore, for future research, a longitudinal design should be employed to unravel the dynamics of the intricate relationship between alcohol and the overall quality of life. The fourth limitation is that the overdependence on self-reported data may introduce bias because individuals may over-report or underreport their alcohol consumption rate and overall quality of life. For future research, alternative data sources should be incorporated to enhance the accuracy of the findings conducted by NIHR public health students. The last limitation is that our study did not fully capture the long-term outcomes which are associated with alcohol; therefore, for future research, we should delve deeper into the chronic conditions associated with heavy drinking.

Conclusion

In conclusion, by reviewing the survey done by NIHR students, we can deduce that a robust negative correlation between the frequency of alcohol consumption and quality of life is vital to the well-being of human beings because it emphasizes the intricate tangible impacts of alcohol use. However, the quantitative analysis goes far beyond subjective perceptions and provides evidence that a higher frequency of alcohol consumption is genuinely associated with an overall lower quality of life. A deeper understanding of the impact of alcohol on quality of life has enabled individuals to understand the potential consequences of their choices and how, in one way or another, they affect their overall quality of life. Hence, this study has contributed to many individuals being equipped with health literacy and armed them with knowledge in making informed decisions. There from our analysis, it is a necessity that individuals should adhere to preventive measures put in place to address the decrease in quality of life, which is associated with higher alcohol consumption.

From this study, policymakers can be informed on evidence while making new policies because this study provides a basis for crafting more specific guidelines and frameworks that differentiate between heavy and moderate drinkers. Having strict, particular policies for the health sector ensures that the strategies put in place are equitable and responsive to the population’s diverse needs. In other words, this dissertation serves as an exploration of the impact of alcohol on quality of life, empowering individuals and policymakers to navigate through the complexities of alcohol use in a way that prioritizes overall well-being.

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