Executive brief

Solihull has a strong headline story. The internal gaps are the real work.

This brief turns the available figures into the questions a public-health analyst would need to ask next: where the gaps sit, which groups or places are most affected, and what deserves deeper analysis.

The issue

Borough averages can look reassuring while neighbourhood gaps remain large.

The useful question is not whether Solihull performs well on average. It is where the average stops being informative. The available figures point to sharp differences in life expectancy, youth claimant rates, working-age health and future demand from an ageing population.

Life expectancy12.1 yrs / 10.9 yrs

Reported male and female gaps between the most and least deprived deciles.

Young people and work12.3%

Youth claimant rate across the cited North Solihull regeneration wards, compared with 4.8% across the rest of the borough.

Working-age health20.8%

Reported musculoskeletal prevalence in Solihull, compared with 17.6% for England.

Ageing population21%

Share of residents aged 65+ in the current strategy figures.

So what?

The analysis should move from borough summary to targeted intelligence.

Averages are useful for orientation, but they are blunt instruments for prioritising action. The next analytical layer should combine health outcomes, deprivation, age profile, employment, housing and access indicators at compatible geographies.

The work becomes more valuable when it shows overlap: places or groups where several pressures appear together, and where the pattern is clear enough to justify a closer look.

Questions worth asking next

  1. Which outcomes contribute most to premature mortality and life-expectancy gaps?
  2. How do those outcomes vary by deprivation, age, sex and place?
  3. Which wider determinants appear alongside poorer outcomes?
  4. Are the gaps widening, narrowing or holding steady over time?
  5. Which patterns remain convincing after uncertainty, sample size and indicator definition are checked?

Next analytical steps

  • Refresh the OHID indicator series and preserve confidence intervals.
  • Build a small-area deprivation layer from IMD data.
  • Benchmark against England, the West Midlands and suitable comparator authorities.
  • Develop focused deep dives for working-age health, young people and healthy ageing.