Trends and inequalities in cardiovascular disease mortality across 7932 English electoral wards, 1982-2006: Bayesian spatial analysis

Abstract

Background: Cardiovascular disease (CVD) mortality has more than halved in England since the 1980s, but there are few data on small-area trends. We estimated CVD mortality by ward in 5-year intervals between 1982 and 2006, and examined trends in relation to starting mortality, region and community deprivation.

Methods: We analysed CVD death rates using a Bayesian spatial technique for all 7932 English electoral wards in consecutive 5-year intervals between 1982 and 2006, separately for men and women aged 30-64 years and ≥65 years.

Results: Age-standardized CVD mortality declined in the majority of wards, but increased in 186 wards for women aged ≥65 years. The decline was larger where starting mortality had been higher. When grouped by deprivation quintile, absolute inequality between most- and least-deprived wards narrowed over time in those aged 30-64 years, but increased in older adults; relative inequalities worsened in all four age-sex groups. Wards with high CVD mortality in 2002-06 fell into two groups: those in and around large metropolitan cities in northern England that started with high mortality in 1982-86 and could not 'catch up', despite impressive declines, and those that started with average or low mortality in the 1980s but 'fell behind' because of small mortality reductions.

Conclusions: Improving population health and reducing health inequalities should be treated as related policy and measurement goals. Ongoing analysis of mortality by small area is essential to monitor local effects on health and health inequalities of the public health and healthcare systems.

Figure 1

Posterior mean of CVD mortality in 1982–86 and 2002–06 from the Bayesian spatial model, by ward in (a) men aged 30–64 years; (b) women aged 30–64 years; (c) men aged ≥65 years; and (d) women aged ≥65 years. See Supplementary Tables S1–S4 for numerical information by ward. See Supplementary Figure S1 for a map of England that identifies specific regions. See Supplementary Figure S2 for posterior probabilities corresponding to this figure. Each shade in the legend corresponds to a decile of wards in the analysis and includes 793 or 794 wards

Figure 1

Posterior mean of CVD mortality in 1982–86 and 2002–06 from the Bayesian spatial model, by ward in (a) men aged 30–64 years; (b) women aged 30–64 years; (c) men aged ≥65 years; and (d) women aged ≥65 years. See Supplementary Tables S1–S4 for numerical information by ward. See Supplementary Figure S1 for a map of England that identifies specific regions. See Supplementary Figure S2 for posterior probabilities corresponding to this figure. Each shade in the legend corresponds to a decile of wards in the analysis and includes 793 or 794 wards

Figure 2

Change in ward CVD mortality between 1982–86 and 2002–06 from the Bayesian spatial model, in (a) men aged 30–64 years; (b) women aged 30–64 years; (c) men aged ≥65 years; and (d) women aged ≥65 years. Each shade in the legend corresponds to a decile of wards in the analysis and includes 793 or 794 wards

Figure 3

Posterior standardized mortality ratio of CVD mortality 2002–2006 from the Bayesian spatial model without adjustment (left-hand panels), adjusted for urbanicity and Government Office Region (middle panels), and with additional adjustment for modified IMD quintile (right-hand panels) for (a) men aged 30–64 years; (b) women aged 30–64 years; (c) men aged ≥65 years; and (d) women aged ≥65 years. Each tone in the legend corresponds to a decile of wards in the unadjusted panels

Figure 4

Cardiovascular (CVD) mortality by ward arranged by quintiles of ward deprivation. Each dot represents the posterior mean of CVD mortality for one ward. The darkest shade shows the most-deprived quintile and the lightest the least-deprived quintile