Nodes in Visual Explain diagrams represent different operations involved in query execution. These operations can include things like table scans, index scans, sorts, and joins. Understanding these operations helps in analyzing and optimizing query performance. 

The FETCH statement in DB2 cursor operations is used to retrieve the next row from the result set of the cursor. Each time FETCH is executed, it advances the cursor to the next row in the result set, allowing the application to process the rows sequentially. FETCH returns the data from the current row and moves the cursor to the subsequent row for subsequent fetch operations. 

The Reorg utility reorganizes data pages and indexes, which improves database performance by optimizing the physical storage layout, reducing fragmentation, and reclaiming unused space. 

Denormalization involves increasing redundancy by storing redundant data to improve query performance. However, this can lead to potential data inconsistency issues if the redundant data is not properly maintained. While denormalization can enhance query performance by reducing the need for joins, it comes at the cost of increased storage space and the risk of data anomalies. Thus, the trade-offs of denormalization include balancing data redundancy for improved query performance. 

Monitoring in DB2 serves the purpose of identifying performance issues such as slow queries or bottlenecks, enabling administrators to optimize database performance. It involves tracking resource usage, query execution times, and system health indicators. 

Materialized views in DB2 are precomputed result sets stored as tables, providing faster access to frequently accessed or complex data. 

The Health Monitor contributes to database performance optimization by identifying and resolving performance bottlenecks. It continuously monitors database performance metrics such as CPU usage, memory utilization, and I/O operations. By analyzing these metrics, the Health Monitor can pinpoint areas of inefficiency or bottlenecks in the system and suggest optimizations to improve overall performance. 

User-defined functions play a crucial role in enforcing business rules consistently across various database applications in DB2. By encapsulating complex business logic, UDFs ensure that the same rules are applied uniformly across different components of the system. This promotes data integrity, reduces errors, and enhances compliance with business requirements, thereby facilitating seamless operations across applications. 

DB2 ensures data security through encryption at rest, which encrypts the data while it is stored on disk, making it unreadable without the appropriate decryption key. This helps protect sensitive information from unauthorized access even if the physical storage is compromised. 

Option 3, tuning database configuration parameters, involves adjusting settings such as buffer pool size, lock timeout, and memory allocation to optimize database performance. This step can help address issues such as inefficient resource utilization or contention, which may be causing the performance bottleneck during peak hours. Monitoring system resources (option 2) and optimizing indexing strategy (option 4) are important steps but may not directly address configuration issues leading to performance degradation. Analyzing query execution plans (option 1) is helpful for identifying specific queries causing performance issues but may not resolve underlying configuration problems.