Background Persistent health inequalities encourage researchers to identify new ways of understanding the policy process. Research shows that informal relationships are implicated in finding evidence and making decisions for public health policy. However, few studies use specialised methods such a network analysis to identify key relationships and actors in the policy process. Furthermore, little is known about the strategies used by these influential individuals to control the policy process. This study aimed to use relational methods to identify important individuals in the public health policy process, and to produce explanations for their influence.

Methods We combined network and qualitative data to identify the most influential individuals in public health policy in a UK conurbation, and describe strategies they used to influence policy. Network data were collected by asking for nominations of powerful and influential people in public health policy (n = 152, response rate 80%), and 23 semi-structured interviews with a sub-sample of the network population were analysed using a framework approach.

Results The most influential public health policy makers in this conurbation were identified as public health professionals and mid-level managers in the NHS and local government. However, public health professionals were not influential throughout the policy process, playing only a few roles. Influential managers described four main strategies to influence policy: controlling policy processes through gatekeeping key organisations, providing policy content, and managing selected experts and executives to lead on policies. Public health professionals and academics are indirectly connected to policy via managers, but neither group are described in connection with key strategies.

Conclusion The most powerful individuals in public health are managers, not usually considered targets for research. As we show, they are highly influential through all stages of the policy process. Understanding the daily activities of influential policy individuals provides a new framework for understanding policy, and providing concrete examples of influence questions current approaches to knowledge translation. The study demonstrates the utility of using network analysis methods and potential applications of the method for researchers who wish to influence policy are suggested.