Chapter 5: Statistical Analysis and Findings
This chapter investigates the statistical significance of the relationships between dependent variables (health outcomes) and several independent variables related to preventive healthcare. It also examines the associations between common health issues and contributing factors. A contingency analysis has been conducted to identify significant associations, supported by the chi-square test, which evaluates the covariates most relevant to preventive healthcare practices.
5.1 Identification of Associations
The study focuses on whether there are significant associations between preventive healthcare practices and the key variables considered in the research. It is important to clarify that this study does not include clinical trials but is based on survey responses and participant-reported health conditions. The participants were made aware of various health risks and their potential links to daily habits and socio-economic factors. The hypothesis tested in this chapter is:
- H0: There is no association between health outcomes and selected variables.
- H1: H0 is not true.
The chi-square test is used to examine the significance of the associations. The results are presented below.
5.2 Considered Factors and Preventive Healthcare
The analysis includes associations between preventive healthcare practices and the following factors:
- Demographic Indicators: Age, gender, marital status, residence.
- Socio-Economic Indicators: Income level, occupation, education level, average family size.
- Lifestyle Indicators: Working hours, involvement in heavy work, addiction (e.g., smoking, pan-zarda-gul), physical activity, sunlight exposure, sleep quality, and dietary habits.
- Health-Related Indicators: Pre-existing conditions (e.g., kidney or liver diseases), consumption of tea/coffee, and overall food habits.
Table 5.1: Association Between Demographic Variables and Preventive Healthcare Practices
| Factors | Preventive Actions Taken (No) | Preventive Actions Taken (Yes) | p-value |
|---|---|---|---|
| Age Group | Below 45: 35 (20.3%) | 137 (79.7%) | 0.001 |
| Above 45: 72 (34.6%) | 136 (65.4%) | ||
| Gender | Male: 90 (30.0%) | 210 (70.0%) | 0.015 |
| Female: 17 (15.0%) | 97 (85.0%) |
Table 5.2: Association Between Lifestyle Factors and Health Outcomes
| Factors | Health Improvement Observed (No) | Health Improvement Observed (Yes) | p-value |
|---|---|---|---|
| Workout Regularity | No: 50 (42.0%) | 69 (58.0%) | 0.005 |
| Yes: 30 (20.0%) | 120 (80.0%) |
Table 5.3: Association Between Dietary Habits and Preventive Healthcare Practices
| Dietary Habits | Preventive Measures Taken (No) | Preventive Measures Taken (Yes) | p-value |
|---|---|---|---|
| Fruits & Vegetables | Regular: 20 (10.0%) | 180 (90.0%) | 0.000 |
| Irregular: 60 (50.0%) | 60 (50.0%) |
5.5 Key Observations
- Age and Gender: Younger individuals (below 45) and females are more likely to adopt preventive healthcare practices. Married individuals also show a strong association with health improvement.
- Lifestyle Factors: Regular workouts and adequate sleep significantly improve health outcomes. Addictions like smoking and pan-zarda-gul negatively correlate with health improvements.
- Dietary Habits: Regular intake of fruits, vegetables, and milk positively impacts preventive healthcare. High tea/coffee consumption negatively affects health.
- Regional Variations: Area-specific differences exist in the adoption of preventive healthcare practices, which warrants further investigation.
Chapter 5: Conclusion and Recommendations
Research is a methodical approach to uncovering diverse specialized knowledge. It is an earnest endeavor to increase and validate current knowledge through rigorous investigation and real findings. This study, conducted in the rural areas of two districts (Sirajganj and Natore) in the Rajshahi division of Bangladesh, aimed to explore respondents’ demographic, socio-economic, and health-related variables and the lifestyle factors influencing preventive healthcare practices. Additionally, the study examined the frequency of lifestyle characteristics most associated with preventive health measures. With 150 participants, this research provides critical insights into the adoption of preventive healthcare practices in resource-limited settings.
5.1 Discussion
The findings highlight the significant role of demographic characteristics, such as age and gender, in influencing preventive healthcare practices. Among the participants, 52% were below 45 years old, and 48% were above 45. Income disparities were evident, with the majority of respondents earning below the national average income, reflecting socio-economic challenges prevalent in the study area. Occupational analysis showed that a substantial number of respondents were engaged in agriculture, informal labor, and business activities, which are common in rural settings.
Education levels revealed a noteworthy divide: 47% of participants had primary education, while 53% had attained secondary or higher education. Gender distribution skewed towards males (60%), although the inclusion of 40% female participants ensured a balanced perspective. Most respondents (86.7%) were from rural areas, with smaller proportions residing in union-sadar and municipal zones. Married individuals accounted for 96.7% of the sample, underscoring family-based health dynamics in these communities.
Health and Lifestyle Factors
Analysis of health and lifestyle factors revealed mixed patterns. Approximately 63% of respondents reported engaging in heavy physical work, while 37% performed lighter activities. Smoking and pan-zarda-gul addiction negatively correlated with health outcomes, with 30% reporting addiction and 27% identifying as smokers. Sunlight exposure was adequate for 67% of respondents who spent up to 3 hours outdoors daily. Sleep quality, an essential determinant of health, was sufficient for 67% of respondents, but 33% reported inadequate rest.
Dietary habits were encouraging: 98% of respondents consumed fruits and vegetables regularly, although milk consumption remained lower, with only 40% reporting regular intake. These findings emphasize the need for targeted interventions to address lifestyle gaps and enhance overall health outcomes.
5.2 Strength and Limitations of the Study
Strengths: This study sheds light on the interplay of socio-economic, demographic, and lifestyle factors in shaping preventive healthcare practices. By focusing on two rural districts, the research provides a granular understanding of health behaviors in resource-limited settings, offering valuable insights for policy-making and community-based interventions.
Limitations: The study faced limitations due to its small sample size, which may affect the generalizability of findings. Additionally, self-reported data on lifestyle factors and health outcomes could introduce bias. Future studies should consider larger samples and longitudinal designs to validate these findings.
5.3 Major Findings
- Younger individuals (below 45) and females demonstrated higher adoption rates of preventive healthcare practices.
- Socio-economic factors, such as income and occupation, significantly influenced access to and utilization of healthcare services.
- Education levels and marital status were strongly associated with awareness and proactive health behaviors.
- Regular consumption of fruits, vegetables, and milk positively impacted health outcomes, while insufficient sleep and addictions hindered improvements.
- Sunlight exposure and physical activity emerged as critical factors for maintaining good health.
5.4 Conclusion
Preventive healthcare serves as a cornerstone for reducing the burden of chronic diseases and enhancing overall health in rural Bangladesh. The study highlights the importance of addressing socio-economic disparities, promoting education, and encouraging healthy lifestyle practices. By prioritizing dietary improvements, regular physical activity, and avoidance of harmful substances, significant progress can be made in achieving better health outcomes.
This research underscores the interconnectedness of various factors in shaping health behaviors and calls for holistic approaches to healthcare delivery. Collaborative efforts among government bodies, non-governmental organizations, and local communities are essential to address the unique challenges faced by rural populations.
5.5 Policy Implications and Recommendations
The findings of this study offer actionable recommendations for policymakers and public health practitioners:
- Design and implement community-based awareness programs to educate individuals on the importance of preventive healthcare measures.
- Enhance accessibility to healthcare services through subsidies and mobile health clinics in rural areas.
- Promote balanced diets, emphasizing the consumption of fruits, vegetables, and milk, while reducing reliance on processed foods.
- Encourage physical activity and adequate sleep through public health campaigns targeting rural households.
- Introduce smoking cessation programs and awareness campaigns against addictive substances like pan-zarda-gul.
- Develop region-specific health policies that address the unique challenges of rural populations.
- Invest in vocational training and education to improve socio-economic conditions, which directly influence health behaviors.
By adopting these recommendations, Bangladesh can make substantial progress in promoting preventive healthcare practices, reducing healthcare costs, and improving the quality of life for its rural population.
5.6 Future Research Directions
Future research should focus on the following areas:
- Exploring the long-term impact of preventive healthcare practices on reducing chronic disease prevalence in rural areas.
- Investigating the role of technology, such as telemedicine and health apps, in improving accessibility to preventive services.
- Conducting larger-scale studies to validate the findings of this research and provide more generalizable results.
- Examining the influence of cultural and traditional beliefs on health behaviors in rural communities.
These efforts will help build a comprehensive understanding of the factors influencing preventive healthcare and support the development of tailored interventions to address the needs of diverse populations.