Active Ageing: The Need to Address Sub-National Diversity. An Evidence-Based Approach for Italy

Abstract

While active ageing has emerged as a main strategy to address the challenges of population ageing in Europe, recent research has stressed the need to increase knowledge on within-country differences to promote active ageing through appropriate policy responses. This article draws on the Active Ageing Index (AAI) to capture recent trends in active ageing in Italy with a focus on sub-national diversity. To this end, we compute AAI breakdowns by region separately for men and women for four different years: 2007, 2009, 2012 and 2018. Then, we use linear regression to describe the geographical and sex-specific patterns of change in the AAI over the considered period. The results demonstrate the diversity of regional outcomes and trends in the active ageing of Italian men and women, indicating that the widening geographic gap deserves further consideration by national and regional authorities in designing and implementing active ageing policies. By showing the persistence of disparities in the value of the indicator to the disadvantage of women, results also suggest the need to further integrate both the gender dimension and the life-cycle perspective into active ageing strategies. This article provides an example of how the AAI can be used as a practical tool by policy makers to monitor active ageing trends and outcomes at the sub-national level, and to identify target areas that require further action.

Keywords: Active Ageing Index; active ageing; demographic dynamics; equity; evidence-based policy; gender; regional studies; sustainability.

Figure 1

AAI by region. Year 2018. Source: Authors’ calculations based on numerous data sources from ISTAT.

Figure 2

AAI by region and sex. Year 2018. Source: Authors’ calculations based on numerous data sources from ISTAT. Note: ABR–Abruzzo; BAS–Basilicata; CAL–Calabria; CAM–Campania; EMI–Emilia-Romagna; FRI–Friuli-Venezia Giulia: LAZ–Latium; LIG–Liguria; LOM–Lombardy; MAR–Marche; MOL–Molise; PIE–Piedmont and Aosta Valley; PUG–Apulia; SAR–Sardinia; SIC–Sicily; TOS–Tuscany; TRE–Trentino-Alto Adige; UMB–Umbria; VEN–Veneto.

Figure 3

Gender gap in AAI by region. Year 2018. Authors’ calculations based on numerous data sources from ISTAT.

Figure 4

AAI by region and sex. Difference between years 2018 and 2007. Source: Authors’ calculations based on numerous data sources from ISTAT. Note: ABR–Abruzzo; BAS–Basilicata; CAL–Calabria; CAM–Campania; EMI–Emilia-Romagna; FRI–Friuli-Venezia Giulia: LAZ–Latium; LIG–Liguria; LOM–Lombardy; MAR–Marche; MOL–Molise; PIE–Piedmont and Aosta Valley; PUG–Apulia; SAR–Sardinia; SIC–Sicily; TOS–Tuscany; TRE–Trentino-Alto Adige; UMB–Umbria; VEN–Veneto.

Figure 5

AAI trend by macro-region and sex over the 2007–2018 period. Source: Authors’ calculations based on numerous data sources from ISTAT. Note: (a) Northwest includes Piedmont, Aosta Valley, Liguria, Lombardy; (b) Northeast includes Trentino-Alto Adige, Veneto, Friuli-Venezia Giulia, Emilia-Romagna; (c) Centre includes Tuscany, Umbria, Marche, Latium; (d) South includes Abruzzo, Molise, Campania, Apulia, Basilicata, Calabria; (e) Islands include Sicily, Sardinia; (f) Italy.