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Home»Lifestyle»What’s driving England’s rise in chronic illness? Ageing, not lifestyle, researchers find
Lifestyle

What’s driving England’s rise in chronic illness? Ageing, not lifestyle, researchers find

November 6, 2025No Comments
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Even if smoking, diet, and blood pressure improve across the population, England faces millions more people living with multiple chronic conditions by 2043, highlighting that healthier ageing, not just risk reduction, must drive prevention policy.

Study: Exploring the contribution of risk factors on major illness: a microsimulation study in England, 2023-2043. Image Credit: Hyejin Kang / Shutterstock

Study: Exploring the contribution of risk factors on major illness: a microsimulation study in England, 2023-2043. Image Credit: Hyejin Kang / Shutterstock

In a recent study published in the journal Nature Communications, researchers utilized a validated computer simulation model, IMPACTNCD, to simulate and project the burden of major illnesses for adults in England from 2023 to 2043. The study tested several simulation scenarios, including a 10% relative improvement in eight key risk factors and an ideal “theoretical minimum risk” level.

Study findings revealed that while public health interventions aimed at improving body mass index (BMI), smoking, systolic blood pressure (SBP), total cholesterol, diet, and physical activity have demonstrated benefits, these changes are unlikely to reverse the nation’s growing chronic illness burden, which was found to be primarily driven by an aging population.

Longevity and the Rise of Multimorbidity

While the benefits of modern medicine cannot be overstated, they have resulted in an unexpected public health challenge: humans are living longer than ever before. As a result, more people now survive into older age, where chronic diseases become increasingly common. Consequently, while people are living longer, they are increasingly doing so with multiple, long-term (chronic) health conditions. This “multimorbidity” places a profound strain on health and social care systems and has also been linked to broader societal costs, including reduced economic productivity.

Shared Risk Factors for Chronic Disease

Since many chronic illnesses, like heart disease, diabetes, and certain cancers, share common behavioral risk factors (e.g., smoking, physical inactivity, and unhealthy diets), medicine’s logical expectation was that reducing these risks would, in turn, mitigate multimorbidity.

Gaps in Evidence Linking Risk Reduction to Multimorbidity

Unfortunately, this assumption has not been comprehensively evaluated, with most conventional studies only focusing on how a single risk factor (like obesity) affects a specific disease (like diabetes) or overall mortality. Few studies have modeled the complex, dynamic impact of simultaneously improving multiple risk factors on the total burden of multimorbidity across a whole geographical or ethnic population, presenting a significant knowledge gap.

Using IMPACTNCD to Model Long-Term Health Outcomes

The present study sought to address this gap and inform future public health policy by leveraging the previously validated dynamic discrete-time microsimulation model IMPACTNCD to evaluate the future (20-year) outcomes of English individuals aged 30 and above.

Model training data were obtained from several real-world data sources, including:

  1. the Health Survey for England (2003–2014) for risk factor trends,

  2. the Clinical Practice Research Datalink (CPRD) Aurum linked to Hospital Episode Statistics (HES) and Office for National Statistics (ONS) mortality data (2008–2019) for disease incidence and mortality, and

  3. ONS population estimates and 2021-based projections for demographic structure.

The model leveraged this extensive dataset to simulate the life of each “simulant” (synthetically generated English participant) year by year, updating their attributes, risk factors, and diagnoses for 26 chronic conditions mapped to the 20 conditions included in the Cambridge Multimorbidity Score (CMS). The study’s primary outcome was “major illness,” defined as having a CMS score greater than 1.5.

Health Projection Scenarios and Key Assumptions

Notably, the model was used to project national-scale health outcomes from 2023 to 2043 under three different scenarios:

  • Base-Case: assuming recent (current) trends in risk factors continue;

  • 10% Improvement: a 10% relative improvement in eight key risk factors (BMI, smoking, environmental tobacco smoke exposure, SBP, total cholesterol, fruit intake, vegetable intake, and physical activity); and

  • Theoretical Minimum Risk: an ideal scenario in which all excess risk is eliminated (e.g., all simulated smokers quit, and every individual attains an optimal BMI and SBP).

Projected Illness Trends and Inequality Patterns

Under the base-case scenario, IMPACTNCD projected that if current trends continue, the prevalence of major illness among adults aged 30 and over will rise from 25.7% in 2023 to 29.8% (29.2–30.4) in 2043, equating to approximately 3.4 million more people living with major illness compared with 2023. The model identified BMI as the most influential risk factor, followed by smoking, high SBP, and physical inactivity.

Under the 10% improvement scenario, major illness prevalence was projected to decline by only 0.3 percentage points (0.2–0.4) compared with the base-case estimate for 2043, equivalent to about 220,000 fewer people living with major illness (180,000–270,000). In contrast, the theoretical minimum risk scenario yielded a 2 percentage-point reduction (1.3–2.7) in chronic disease prevalence compared with base-case estimates, lowering projected prevalence in 2043 to 27.8% (27.3–28.4). While a meaningful improvement, this still failed to reverse England’s steadily rising burden of chronic disease. The authors emphasized that even statistically significant improvements translate into modest benefits at the population level.

The study also explored health inequalities by deprivation. Reducing BMI was found to yield the largest absolute benefits in the most deprived groups, while lowering SBP benefited the least deprived more strongly. Other risk factors showed minimal or mixed gradients. The authors noted that middle-aged adults (around 50–54 years in 2023) experienced the greatest projected relative improvements by 2043.

Furthermore, the model revealed a paradoxical dynamic: lowering certain risk factors, such as smoking and physical inactivity, can increase the number of years lived with major illness because reduced mortality allows more people to live long enough to develop chronic disease.

Implications for England’s Public Health Policy

The IMPACTNCD simulation suggests that while current public health interventions in England are crucial for limiting the incidence of chronic disease, they are unlikely to reverse the nation’s growing major illness burden by 2043. Population ageing emerged as a stronger driver of multimorbidity than modifiable behavioral risks alone. The findings highlight the need for equity-focused prevention strategies, healthier ageing initiatives, and coordinated cross-government approaches to manage the projected rise in multimorbidity.

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