London’s inner-city boroughs are predicted to replace former mining towns as Britain’s sickest areas, according to research.

Tower Hamlets and Hackney in East London, and Southwark and Lambeth in South London are developing health problems expected to overtake those of Merthyr Tydfil, South Wales, and Easington, Co Durham.

The findings are presented in a report suggesting which towns and cities are most likely to develop health problems.

By analysing factors such as smoking, single-parent families, fast food consumption, low consumption of fruit and vegetables, income and demographic characteristics, maps have been drawn pinpointing areas where health problems are developing.

The report gathered data and divided areas into four categories: those with unhealthy lifestyles that are building future problems; those with current high levels of illness; those which are generally healthy but have some potential problems; and those that have good health and few lifestyle issues.

The four places the report said were most likely to develop health problems were all London boroughs. Tower Hamlets, Hackney, Southwark and Lambeth are predicted to become the unhealthiest places to live.

Other urban areas, such as Manchester, Nottingham, Hull and Corby, Northamptonshire, are also expected to develop health problems. The Isles of Scilly, Hart in Hampshire, and South Buckinghamshire are the areas least likely to develop health problems, according to the report.

The areas considered to have the worst existing health problems were Merthyr Tydfil, Easington, Rhondda, Neath Port Talbot and Blaenau Gwent. The Prime Minister’s constituency of Sedgefield, Co Durham, came eleventh in this list.

The report was produced by CACI, a market intelligence company which developed a system for classifying consumers, and TNS, a market information company which gathers healthcare data.

They used data from Britain’s 1.9 million postcodes, which have been described using more than 125 demographic statistics within England, Scotland, Wales and Northern Ireland, andtaking into account 287 lifestyle variables.

Ian Thurman, head of location analysis at CACI, said: “The serious illnesses focused on within the report are, to a large extent, caused by lifestyle choices.

“The NHS is already overburdened, but this is nothing compared to the time bomb which is set to explode if people don’t make major changes to their current lifestyles.

“This analysis goes beyond simple measurement of existing health patterns, and identifies where early intervention can be most effective in reducing future illnesses.

“This means healthcare and support can be developed for small communities where ill-health prevention activities can be accurately targeted.”

Wokingham, Surrey, Chiltern, Mole Valley, Hart and Surrey Heath were considered to be generally healthy areas with some concerns.

In the list of areas where health was considered by the report to be good and lifestyle sensible, the Isles of Scilly come top, followed by Eden in the Lake District, the Orkney Islands and the City of London.

“Health-needs mapping”, which aims to predict healthcare needs by analsing data, was piloted with the backing of the Department of Health to identify the people most likely to be affected by type 2 diabetes.

Slough’s primary care trust had found that there were at least 1,000 people in the town whose condition was undiagnosed. The trust wanted to identify exactly where the people who were most at risk lived so it could target its health education message at those who stood to benefit most.

In October the Government unveiled its Health Profile of England, which indicated that a significant North-South health divide still exists.

Northern areas have higher obesity rates, more smoking- related deaths and lower life expectancies, with men in northern counties dying an average of two years earlier than those in the South. Boston, in Lincolnshire, had the highest obesity rate of any town in the country. Women in the North live, on average, one year less than those in the South, according to the statistics.