Diagnostic analysis of wellness tourism certification bias and public health resource mismatch.

Introduction: Cities promote public health through diverse environmental, service, and access conditions. In China, formal recognition systems shape which health-promoting resource configurations become institutionally visible. These systems rely on standardized templates, so they tend to recognize resources that are easy to measure and compare across regions, while overlooking locally embedded ones. This study asks how heterogeneous configurations translate into recognition signals, and where current systems reach their coverage limits. Methods: Using panel data from 111 prefecture-level cities in the Yangtze River Economic Belt from 2017 to 2024, the analysis builds a recognition benchmark from national and provincial designation records and applies XGBoost with SHAP under strict temporal extrapolation. Results: Recognition concentrates on a small set of highly legible indicators. Forest coverage alone accounts for 15.6 percent of resource-base attribution. Enablers such as transport, digital infrastructure, and service capacity show stronger recognition attribution mainly when the resource base is already strong. The study identifies eight city-level pathways and interprets them as policy-aligned, low-readiness, or boundary-advantage positions. Discussion: Within the Yangtze River Economic Belt, low recognition does not necessarily mean low health value. It can also reflect limits in how current templates read locally embedded resources. These findings refer to institutional visibility, not realized service quality, market performance, or population-health outcomes. The framework helps cities distinguish template alignment, pathway immaturity, and institutional invisibility, supporting differentiated health-and-wellness routes rather than a single recognition-oriented path.