Coupling dynamics of SDGs in Tajikistan from 2001 to 2023

Since the United Nations launched the Sustainable Development Goals (SDGs) in 2015, global implementation has steadily advanced, yet prominent challenges persist. Progress has been uneven across regions and countries, with Tajikistan representing a typical example of such disparities. Based on 81 SDG indicators for Tajikistan from 2001 to 2023, this study applied a three-level coupling network framework: at the microscale, it identified synergies and trade-offs between indicators; at the mesoscale, it examined the strength and direction of linkages within four SDG-related components (society, finance, governance, and environment); and at the global level, it focused on the overall SDG interlinkages. Spearman’s rank correlation, sliding window method, and topological properties were employed to analyze the coupling dynamics of SDGs. Results showed that over 70.00% of associations in the global SDG network were of medium-to-low intensity, alongside extremely strong ones (| r | value approached 1.00, where r is the correlation coefficient). SDG interactions were generally limited, with stable local synergy clusters in core livelihood sectors. Network modularity fluctuated, reflecting a cycle of differentiation, integration, and fragmentation, while coupling efficiency varied with the external environment. Each component exhibited distinct functional characteristics. The social component maintained high connectivity through the “poverty alleviation-education-healthcare” loop. The environmental component shifted toward coordinated eco-economic governance. The governance-related component broke interdepartmental barriers, while the financial component showed weak links between resource-based indicators and consumption/employment indicators. Tajikistan’s SDG coupling evolved through three phases: survival-oriented (2001–2012), policy integration (2013–2018), and shock adaptation (2019–2023). These phases were driven by policy changes, resource industries, governance optimization, and external factors. This study enriches the analytical framework for understanding the dynamic coupling of SDGs in mountainous resource-dependent countries and provides empirical evidence to support similar countries in formulating phase-specific SDG promotion strategies.