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Author Archives: N80

Source: ONS

If there’s one thing Pretty Graphs likes as much as graphs it’s maps. Maps are a great way of visualising data and help us to see. Take this map of population density in my beloved city of Southampton, based on data from the 2001 and 2011 census. At first glance it looks fairly similar, but taking a closer look at the area around the town-centre (the area just to the right of the highlighted area) it seems that population density has increased dramatically between censuses.

A key difference: Population density in the centre of the city grew significantly between 2001 and 2011

The main reason for this can be seen on the ground. Walking immediately south, or South East of the CBD you find yourself among  many recently built high-rise apartment blocks where once there had been – and to an extent still is – a maudlin mixture of old warehouses, derelict nightclubs, lorry-parks, and an abandoned school. This was the kind of inner-city imagined by the Sci-fi author Clifford Simak who in the 1950s takes America’s rapid suburbanisation to it’s logical conclusion – the death of the city.

John Smiths £1.50 a pint; Once upon a time this was the beating heart of Southampton’s night-life

One term which was used to describe the kind of urban decay which continued right up until the late 1990s was ‘donut city’ – a city hollowed out with no centre, but then something happened. Green-field building came to a sudden halt, possibly due to changes in planning practice, and developers turned to the city once again, building not low-rise suburban homes, but high-rise apartment blocks.

A recent high-density housing development

Who lives in these blocks? Well, according to the Census data for the areas of interest it isn’t people over 65, and it’s not people aged under 15, both of whom make up a low proportion of the population of the central areas. This is perhaps not surprising as high-rise apartments are unappealing to both the elderly and families; For the elderly they are difficult to access, whilst for families they lack space and access to amenities. The location is also far more likely to appeal to the young, who want to live, work and play in the urban centre.

From a sociological perspective there has been much said on the impacts of high-rise living in terms of community. Indeed, it was reported in one building in the area that there was an issue with some residents not disposing of their rubbish responsibly causing concerns about rats – a small issue perhaps, but illustrative of the difficulties arising with these developments.

Looking at the age data there also seems to be evidence of a form of segregation by age-group as this next map shows:

Source: ONS

Whereas the higher percentages of over 65’s in East and West of the city, as well as the urban periphery seem more-or-less unchanged in 10 years the core of the city, which had a much lower proportion to begin with seems to have seen a reduction in the percentage of this age group.

It appears that two cities emerging; one East of the river Itchen which is older and suburban and another based around the urban core which is much younger, typically childless, and living in high-rise apartments.

All this from a few maps!


It seems like a strange question. Surely the Premier League, which generated 2.5 billion Euros in 2010/11 – making it by a long-shot the highest  revenue generating league in the continent (according to the Deloitte 2012 Annual Review of Football Finance), which attracts the cream of the worlds footballing talent, and is breaking all records in securing £5 billion for its TV rights alone, is far more successful than the Championship, a mere second tier league.

But if we define success in terms of the ability of clubs to attract spectators, as this graph shows in the period since 1985/86, the year English football attendances fell to a post-war low,  what is now known as the Championship has significantly out-performed the Premiership, not in terms of total attendances,   (the Premiership still draws considerably more spectators – on average – per game) or the total increase in numbers (again for much of the period the gap between the two in terms of average attendances has grown), rather the rate at which attendances have grown. As the graph shows if we take the 1985/86 season as the starting point, in percentage terms the growth rate for average attendances over the season in the Championship has been much higher than for the Premier League

So what possible explanations exist for this?

1.) A mathematical quirk

As any student of GDP growth will tell you in percentage terms it is much easier to record high levels of growth when starting from a low-base. In the analysis here The starting figures for the Championship and the Premier League are 7688 and 19563 respectively, so even a lower increase in the total figure for the Championship could see a much higher growth rate in percentage terms. As this graph shows, for much of the period, and particularly during the 1990s, the size of the gap between the season average attendance of the two divisions actually grew.


It is worth noting however, that both League 1 and League 2, also starting from a low base have displayed rated of growth more in line with the Premier league, so a mathematical quirk alone is an insufficient explanation for the Championship’s runaway success.

2.)  The Premier league is too expensive

In economic terms the Championship is like a rump steak to the Premier Leagues fillet i.e a cheaper alternative. Whilst this is sure to anger many football fans who will insist that their club is the club, the question has to be asked as to whether being comparatively cheaper than the Premier League has helped the Championship to higher levels of attendance growth.

It is hard to say whether this is the case, particularly as it is unclear just how much cheaper, if at all, the Championship is compared to the Premier League. As this BBC survey shows in terms of some ticket prices, particularly at the lower end of the range there are cases where Championship clubs have higher prices, for instance Man City’s cheapest season ticket is £275, whilst Hull City in the Championship offer their cheapest at £485.

3.) The Premier League lacks competitiveness 

Along with high prices this is another accusation which has been continually leveled at the Premier League, that it is just uncompetitive, that at the start of the season we know who will win it, or who the top four will be, and that we also know who will be relegated. As the Deloitte report acknowledges in the 2010/11 season there was:

a particularly strong correlation in the Premier League between league finishing position and a club’s wage ranking, implying that, all other things being equal, spending more on wages translates to on-pitch success.

Whereas in the Championship, the report adds, the correlation “remains relatively weak” which it suggests is indicative of the competitive nature of the league.

Whilst this leaves little doubt as to the relative competitiveness of both leagues, the actual affect this has on attendances is more of a grey-area. In their book Why England Lose and Other Curious Football Phenomena Explained Simon Kuper and Stefan Szymanski state that previous research in this area has generated mixed results and they themselves suggest that an unbalanced league can provide more interest. Comparing the Premier League to the much more equal US league, MLS, they argue:

the MLS lacks one of the joys of an unbalanced league; the David v Goliath match. And one reason why fans enjoy those encounters is that surprisingly often, given their respective budgets, David wins.

As someone who counts their most memorable ever match as the time Southampton beat Manchester United 6-3 it is hard to argue with this, though to say the Championship does not have ‘big-teams’ would be to do it an injustice, perhaps it’s success is in its combination of the two; big clubs and a competitive league.

4.) Supply and demand

Ever tried getting hold of a ticket for a Premier League game? It’s not always easy with a number of games selling-out. In the case of sell-outs demand exceeds supply which is in effect capped by stadium size. The solution – increasing stadium size – also isn’t necessarily easy. Notwithstanding the expense there is the need need for planning permission which can often lead to years of wrangling. According to the Deloitte report in 2010/11 average capacity utilisation for the Premier league was 93% whilst the figure for the total Football League stood at a much lower 58%. If supply did match demand for the Premier League it may well be that attendances and attendance growth would be much higher.

Overall – More than a quirk…

Overall  whilst there may be an element of mathematical quirk to the results in the opening graph, this alone does not explain the Championships strong performance. It seems quite possible that a cap on attendances imposed by stadium size has also acted to slow growth in the Premier League, but again the Championship has no more advantage here than League 1, or League  2 clubs which it has also out-performed. Price too (particularly in the current ecomomic climate) along with  competitiveness may also have played a part, along with other factors we have not covered, but overall it seems the Championship has experienced a perfect-storm of factors enabling it to grow at a rate faster than the Premier League. As the Deloitte report states the Championship is the highest revenue generating second-tier league in the world, and that’s more than a mathematical quirk.

For a while now there have been worrying signs that food poverty is becoming an increasing problem in the UK.  This Guardian article reporting on some recent research carried out using a panel of 30 000 UK households highlights one finding as being that the consumption of filling, high-fat, processed foods has grown among households with an annual income below £25 000, which the article uses to raise concerns over nutrition. This took me back to a short literature review on the subject of obesity which I had written for my course last year and which touched on many of the issues which have recently been raised.

Literature review:  Income inequality, social relationships and well-being

 In their book the spirit level Wilkinson and Pickett link income inequality to a range of health and social problems their work forming a response to the puzzle presented by the persistence of social-class gradients in a range of health related measures (Macintyre1997p.735).  The emergence of concerns with these gradients can be seen to coincide with a developing awareness of relative poverty towards the end of the 20th century (see Townsend 1979) whilst similar concerns over health inequalities led in 1977 to the commissioning of the Black Report which despite its marginalisation by an incoming administration is credited as acting as a stimulus and guide for further research into the relationship between social status and health (Smith 1990p.373:Macintyre 1997p.726-730:Marmot 2001 p.1165). One strand of research which took root in the wake of Black was the Psychosocial approach which sought to explain class gradients through an analysis of the relationship between health, social position and stress with particular regard to factors such as self-esteem, social networks and autonomy at work (Macintyre 1997p.736 Brunner 1997 p.1473 Wilkinson 1997 p.593). The work of Wilkinson and Pickett’s seeks to build on the Psychosocial approach by using income inequality to explain differences in these factors between states resulting to observable differences in indicators of health and well-being (Wilkinson & Pickett 2010). Obesity is among the conditions they argue has a correlation with income inequality (Wilkinson & Pickett 2010p.92).

Wilkinson and Pickett discuss several pathways which link a state’s level of income inequality to obesity. These include calorie intake, diet, and the effect of stress in determining food selections and patterns of weight gain (Wilkinson & Pickett 2010p.95-96). They also suggest that considerations of status play a role in determining food selection and implicate the availability of particular types of foods. To illustrate this point they draw on a single source, a series from the Wall Street Journal, providing several examples centring round the consumption of fast-food as a method of demonstrating status, be this financial status or even status as a citizen (p.97-98).  The point underlined by Wilkinson and Pickett is remarkably similar to the suggestion of ethnologist Igor de Garine who in 1987 asserted that

Eating is a form of expression whereby a person in a sense acts out his or her position in a particular society. For this reason, the quest for prestige and distinction is a constant feature of the dynamic of food selection (p.5-6)

It would appear however, that beyond the boundaries of anthropology and ethnology such insights have failed to make an impact on academic work on diet and obesity. A large amount of the current research instead coming in the form of studies which have sought to establish correlations between measures of socio-economic status and various forms of dietary behaviour often putting forward the higher costs of nutrient rich foods as an explanation for observed social-class based differences (see Darmon & Drewnoski 2008: Giskes et al 2009). There has tended to be less emphasis on the meanings people attach to the food they choose to consume and how this relates to conceptions of social status. The role which status considerations plays in food choices have however, received more attention in the mass-media, in a piece cited by Wilkinson and Pickett (p.91), Polly Toynbee suggests that high inequality results in unmet aspirations leading to the poor giving up upon the high-class ideal of thinness in favour of seeking pleasure from eating whilst In a Newsweek article in which Pickett makes a cameo appearance Lisa Miller contrasts the ‘foodie’ culture of wealthier Americans  with what has become termed as the ‘food insecurity’ endured by the poorest who “often eat what they can: highly calorific, mass produced foods like pizza and packaged cakes that fill them up quickly”.

The mass-production of foods is central to numerous structural accounts of obesity such as the impact on, in particular Western diets, of the globalised, subsidised, industrialised food industry which ensures high profits for production of comparatively cheap, energy dense foodstuffs (Lawrence 2008:Delpeuch 2009) Such accounts often locate the fast-food industry within this wider agri-industrial-complex linking its expansion and global spread from an epicentre located in the USA with increased obesity rates in both the developed and developing world (Schlosser 2002: Delpeuch 2009). Interestingly Delpeuch (p.47) also points to the initial take-up of fast food by high-status groups in the developing world, whilst Schlosser presents an alternative explanation for the rise in obesity levels in post-reunification East Germany to that of increased inequality posited by Wilkinson & Pickett (p.101); the construction of East Germany’s first McDonalds branch in 1990 (p.229)

One focus of research which has emerged from the structural accounts is a number of studies seeking to analyse what have been called ‘community nutrition environments’ (Thornton et al p.1423). Some research has suggested there is a link between the concentration of fast-food outlets and neighbourhood-level characteristics such as measures of neighbourhood socioeconomic status (Reidpath et al 2002) or ethnicity (Molaodi et al 2010). There is however much debate as whilst some work supports a link between proximity to fast food outlets and increased odds of obesity (Currie et al 2010p.35) other work disputes the relationship between distribution of fast-food outlets and obesity (Pearce et al 2009 p.196:Thornton et al 2010p.1423) however, intriguingly  Pearce et al suggest their New Zealand based study may have drawn different conclusions to research situated in the U.S  was because of  “lower levels of urban residential segregation” in New Zealand (p.196)

Whilst acknowledging some of the factors put forward by the structural accounts; chiefly availability of “cheap, energy dense foods” (2004p.673 2010 p.96) Wilkinson and Pickett are generally dismissive of their explanatory potential (2004p.673) One work however, seeks to build a bridge between the two positions. Using welfare state regime types in their multiple-regression analysis Offer et al (2010) find that liberal regimes experience the highest levels of obesity. They suggest that this is due to high levels of insecurity, but they also find that low prices of fast-food are lowest within the liberal regimes compared to other regime types (p.301). They suggest that overall any explanations for differences between regime types may lie in the shared “historical and cultural roots” linking states within a regime cluster (p.306). The outright dismissal of such historical and cultural factors is indeed one aspect of Wilkinson & Pickett’s work which has attracted critique (Saunders 2010 p.117) Other research however, stresses the importance of both historical and cultural factors in shaping food preferences; Historian Steve Penfold charting the interplay between economics and cultural meanings which saw the donut becoming entrenched as a symbol of Canadian national identity (Penfold 2008). Perhaps this points to what may be a fertile area for future research on obesity.


Brunner, E. (1997) Socioeconomic determinants of health: Stress and the biology of inequality British Medical Journal 314: 1468-1472

Currie, J, Della Vigna, S, Moretti, E & Pathania, V (2010) The Effect of Fast Food Restaurants on Obesity and Weight Gain American Economic Journal: Economic Policy 2: 32-63

Darmon, N. & Drewnowski, A (2008) Does social class predict diet quality? American Journal of Clinical Nutrition 87: 1107-1117

Delpeuch, F. Maire, B. Monnier, E, Holdsworth, M (2009) Globesity: A Planet Out of Control? Earthscan: London

Garine, I. de. (1987) Food Culture and Society The Courier 1987 40: 4-7

Giskes, K. Avendano, M. Brug, J. & Kunst, A. E (2009) A systematic review of studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adults Obesity Reviews 11: 413-429

Lawrence, F (2008) Eat Your Heart Out: Why the food business is bad for your health London: Penguin

Macintyre, S. (1997)The Black Report And Beyond What Are The Issues? Social Science and Medicine 44 (6) 723-745

Malaodi, O. R., Harding, S, Leyland, A.H, Kearns, A (2010) Area deprivation, ethnic density and fast food outlets, supermarkets and physical activity structures in England Journal of Epidemiology and Community Health Vol. 64

Miller, Lisa (2010) Divided We Eat: As more of us indulge our passion for local, organic delicacies, a growing number of Americans don’t have enough nutritious food to eat. How we can bridge the gap Newsweek 29th November 2010

Offer, A. Pechey, R. & Ulijaszek, S.  (2010) Obesity under affluence varies by welfare regimes: The effect of fast food insecurity, and inequality Economics and Human Biology (8) 297-308

Pearce, J. Hiscock, R. Blakely, T. & Witten, K. (2009) A national study of the association between neighbourhood access to fast-food outlets and the diet and weight of local residents Health & Place 15: 193-197

Penfold, S (2008) The Donut a Canadian history  Toronto: University of Toronto Press

Pickett, K. Kelly, S., Brunner, E. Lobstein, T. Wilkinson, R. G (2005) Wider income gaps, wider waistbands? An ecological study of obesity and income inequality Journal of epidemiology and Community Health 59: 670-674

Reidpath, D. D. Burns, C. Garrard, J. Mahoney, M. & Townsend, M. (2002) An ecological study of the relationship between social and environmental determinants of obesity Health & Place 8: 141-145

Saunders, P. (2010) Beware False Prophets: Equality, the good society and the spirit level. Policy exchange: London

Schlosser, E.(2002) Fast Food Nation: What the all-american meal is doing to the world London: Penguin

Thornton, L, E. Crawford, D. A, Ball, K.(2010) Neighbourhood-socioeconomic variation in women’s diet: the role of nutrition environments European Journal of Clinical Nutrition 64: 1423-1432

Townsend, P. (1979) Poverty in the United Kingdom : a survey of household resources and standards of living Harmondsworth: Penguin

Toynbee, Polly (2004) Inequality is fattening: People will get thinner only when they have things that are worth staying thin for – self-esteem, social status and jobs The Guardian 28th May 2004

Wilkinson, R. & Pickett, K (2010) The Spirit Level: Why equality is better for everyone London: Penguin

Wilkinson, R. (1997) Socioeconomic determinants of health: Health inequalities: relative or absolute material standards? British Medical Journal 314: 591-595

Crowded tube trains – a recipe for anxiety?

It’s 9.30am, just a little over a week ago, and I’ve just managed to squeeze myself onto a packed tube train at London Bridge station – this being the third train to arrive since I took my place on the platform. Grasping a rail to steady myself as the train jerks along I find myself in the kind of close proximity to total strangers which is normally reserved for family, close friends, or else lovers.  A man nearby sneezes leading to the people crushed up against him to wince. Thankfully for me this journey is a one-off, but for the majority of passengers in their smart business attire this must be part of their daily routine, squished together like a glutenous mass of red-blood cells fueling the body of some greater being. At this moment I start wondering to myself ‘just why are Londoners’ so anxious?’

I know Londoners are particularly anxious, because when asked by the Office for National statistics ‘Overall, how anxious did you feel yesterday?’ where nought is ‘not at all’ and ten is ‘completely’  44.5% of Londoners provided a ‘high, or very high’ rating of between 4 and 10 compared to 41.8% in the next highest region, the North East, and 35.5% in the lowest, Northern Ireland. The question was asked as part of the attempt to measure national well-being and featured alongside other questions in which respondents were asked to rate their overall life satisfaction, the extent to which they felt the things they did in their life were worthwhile and their happiness the previous day – all of which Londoners tended to provide a greater amount of poor ratings compared to the rest of the UK.

So why the anxiety? What makes London so different from the rest of the UK? It can’t be just the impact of being crammed on the tube – though that may well explain some of the anxiety. London is particularly prosperous relative to the rest of the UK, but can that really explain why people in London are more anxious? One explanation could be in the way that prosperity is divided; London is by far the most unequal place in the UK with the ratio between the hourly earnings of the 99th and 1st percentile, based on 2011 figures, being 16.2. By contrast the most equal, Wales, has a ratio less than half London’s at 7.0.

Source: ONS. Well-being data Annual Population Survey, Office for National Statistics data from April 2011 – March 2012. Income data for April 2011 from Annual Survey of Hours and Earnings.

In their book, The Spirit Level; Why Equality is Better for Everyone Richard Wilkinson and Kate Pickett argue that though inequality is not the cause of what have been rising levels of anxiety..

Greater Inequality seems to heighten people’s social evaluation anxieties by increasing the importance of social status

They continue that the more the inequality, the more status competition and the higher the levels status anxiety, but were this to be the case we would expect to see a relationship between inequality and the levels of anxiety and a regional level, at least, this appears not to be the case as this scatterplot shows:

Source: ONS

Of course even a fairly strongly correlated result would be far from conclusive owing to the small sample size, but going back to the data The South East which has the  second highest inequality ratio of 9.6 had a fairly middling proportion of people recording high, or very high responses to the anxiety question, 38.8% – lower for instance that the much more equal North East (7.6 & 41.8%).

Perhaps however, it is something else about London. In her seminal work Saskia Sassen (2001), who famously analysed increased income inequality and polarisation in what she termed ‘global cities’,  observed about London:

As in New York, a distinct lifestyle has emerged, and there is a sufficiently critical mass of young, high-income workers engaged in high levels of consumption that it makes itself felt in certain parts of London and the region. New, elegant shops and restaurants – and sharp increases in the prices of housing – manifest the new lifestyle. There has also been high-income gentrification of some parts of London, including areas of inner London once inhabited by lower-income people, especially minorities. (p.272-3)

What Sassen is pointing to is that high levels of inequality have helped to shape the city, both physically and culturally, creating an urban form which may well be more conducive to the sort of status anxiety mentioned by Wilkinson and Pickett which may in turn explain its inhabitants higher than average levels of anxiety. Finally the tube disgorges me at Old Street and thankful and relieved I emerge into the grey morning and gulp down the (relatively) fresh air on the surface. Maybe it is the tube after all, or else as they say on the underground, mind the gap.


Office for National Statistics (2012) First ONS Annual Experimental Subjective Well-being Results 24th July 2012

Sassen, S. (2001) The Global City: New York, London, Tokyo, (2nd edition) Oxford; Princeton University Press

Wilkinson, R. & Pickett, K. (2010) The Spirit Level; Why Equality is Better for Everyone London:Penguin

Can statistics make you happy? Maybe if you’re a stats geek like me, but seriously can the path to happiness, or at least some insights into the path to follow be found through the use of statistics? The Office for National Statistics (ONS) have been engaged in work to create a quantitative measure of our national well-being and despite some criticisms in the mainstream media, along the lines that in many cases it was either pointless, or a case of stating the obvious, the work, carried out on a large scale, has produced some interesting results and points to a number of areas for future research. As the well-being data has been collected through the Labour Force Survey the analysis so far seems particularly revealing about the work we do, or indeed don’t do  (though this is perhaps also a weakness as the data reveals less about other non-work factors) and in this post I will be dealing primarily with these issues of work status, occupation type and their relationship with life-satisfaction.

Is working less the key to happiness? The ONS well-being statistics suggest this may well be the case. Image

The most immediately striking thing about the well-being stats is the affect of age. According to the ONS figures well-being follows a ‘u’ shaped curve according to age as shown by this graph referring to responses to the question ‘Overall, how satisfied are you with your life nowadays? in which respondents were asked to give a rating on a scale of 0 -10 with 0 being not at all and 10 being completely.

Source: Annual Population Survey (APS) – Office for National Statistics. Data Collected between April 2011 and March 2012

What could be the reasons for this similarly high ratings given by members of the older and younger age group? One thing both groups also have in common is their level of satisfaction of the amount of free time they have. When asked  ‘if they were satisfied with the amount of time to do the things that they like doing’ both younger and older people reported the highest levels of satisfaction.

Source: Opinions Survey, Office for National Statistics. Data collected in October 2011, February and June 2012.

It is quite likely that these higher levels are chiefly because both groups are less likely to have family commitments, or to be engaged in paid-work; For younger people this is because they are still in education, whilst for the older age group many of those aged 65+ will be retired from paid-work.

As a slight aside an interesting observation is that whilst in general life satisfaction appears to increase with age, this actually declines for the 80+ age group. There may be a number of possible explanations for this; one being poor health, which is in the ONS analysis also implicated in lower levels of well-being, or an alternative may be that social capital declines at this age leading to isolation.

So in terms of work is it that not working the answer to happiness? Well, not quite. The well-being statistics also showed that unemployment has a significantly detrimental impact on the level of well-being reported by an individual with 45% of unemployed people rating their life satisfaction as low (5-6), or very low (0-4). This compares with a much lower figure of 20% for people in employment whilst for economically inactive people this figure is 27.1% However, this latter category includes  people who are caring for a relative, looking after children, or who are unable to work due to illness/disability along with students, the idle rich and retired people, who we may possibly expect to have higher ratings – indeed more people in the economically inactive group, some 30.5% also rated their life satisfaction as high (9-10) compared with 24.4% of employed people, and 16.3% of unemployed people suggesting this is a rather bifurcated group.

Because of this wide variation among the ‘Economically Inactive’  group it is particularly hard to reach any conclusion without breaking down the category and though we can clearly see that being employed is clearly far more preferable from a well-being perspective to being unemployed – something which may well be due to the stigma and low status of being in the unemployed group – an interesting comparison to make would be between the unemployed and the idle rich.

Annual Population Survey (APS) – Office for National Statistics. Data from April 2011 to March 2012.

But can the type of work we do have an effect on well-being – yes, according to the ONS analysis which states that in terms of the ‘life satisfaction’ ratings, and sthe ‘how happy did you feel yesterday’ question.

higher scores appear to be given by the occupational groups who tend to have more responsibility and control over their work, as well as higher incomes (which were not controlled for in this analysis)

This seems to align the findings of the Whitehall II study,  based on a sample of 10 308 civil servants, which found that low levels of control at work had a particularly detrimental  effect on health. A (2004) pamphlet explaining the results of the research, which was carried out between 1985 and 1998, states:

While it is common for demands to increase as the occupational hierarchy is ascended, degree of control over work decreases with lower position. Whitehall II provides ample documentation of this: the lower the grade of employment, the less control over work. This combination of imbalance between demands and control predicted a range of illnesses. The evidence from Whitehall II suggested that low control was especially important. People in jobs characterised by low control had higher rates of sickness absence, of mental illness, of heart disease and pain in the lower back.

Whilst there is likely to be a correlation between level of control and remuneration  as this was not controlled in the analysis it is not possible to tell form the data if higher levels of pay alone can increase well-being. One interesting finding however, is that those in the occupational group ‘caring, leisure and other service occupations’ as well as those in ‘professional occupations’ achieved the highest average response to the question ‘overall, to what extent do you feel the things you do in your life are worthwhile’ at 8 out of ten. the lowest averages were reported by ‘sales and customer service occupations’, ‘process plant and machine operatives’, and ‘elementary occupations’ who all averaged 7.5.

This would seem to suggest that work which involves a level of altruistic motivation, or else purports to serve a higher purpose, is beneficial for overall well-being, compared to work in which financial reward is the primary, or sole motivation. This finding is particularly relevant to questions into the role of social purpose, or public service in work and in organisations in general. Could it be that individual well-being is enhanced within organisations such as social enterprises, or other voluntary organisations where there is a strong sense of social mission?


In terms of the ONS well-being data it would appear that both younger and older persons, groups who due to their respective ages tend not to be engaged in full-time paid work, report both higher levels of life satisfaction, and higher levels of satisfaction with the time to do things. Though it is not necessarily the case that it is simply full-time work  that results in lower levels of satisfaction in both measures for the other age groups, and it may certainly be the case that other commitments such as looking after children also play a role, it does seem possible that full-time work, can result in dissatisfaction with the time a person has to do things and this in turn may well be linked to the corresponding lower levels of reported well-being for these age groups. Certainly this is an area where future research may be directed as the ONS analysis does not include any details on the relationship between well-being and hours worked, or with a persons satisfaction, or not, with the hours they currently work.

Finally It is also important to note that the LFS does not collect data on voluntary work. It may be the case that, particularly among the retired group, voluntary work may play a key role in well-being. A 2005 Joseph Rowntree Foundation paper Volunteering in Retirement, suggests that voluntary work can be particularly beneficial for the health of retired people. As mentioned the ONS analysis seems to suggest that work which performs a higher purpose is beneficial to well being therefore it may be interesting in particular to analyse the role of voluntary work, or more widely make a comparison of well-being levels between workers in the voluntary, or public sector and the private sector.


Ferrie, J. (2004) Work, Stress and Health: the Whitehall II study CCSU/Cabinet Office

Office for National Statistics (2012) First ONS Annual Experimental Subjective Well-being Results 24th July 2012

Office for National Statistics (2012) Measuring National Well-being –
Measuring young people’s well-being 10th October 2012

Smith & Gay (2005) Active Ageing in Active Communities; Volunteering and the Transition to Retirement Bristol: The Policy Press

This graph was produced using the statistical software package SPSS and shows the relationship between life expectancy at birth and income inequality using data published in UN Human Development Reports ranging from 2004 to 2008.  It was initially created for a presentation on the assertion made within The Spirit Level, an influential book first published in 2009, that once countries pass a certain point of development, measured in terms of national income, the relationship which had hitherto been observed between increases in income and increases in life expectancy breaks down and among these countries it is income distribution within them which becomes a better predictor of life expectancy and a range of other health and wellbeing indicators (Wilkinson and Pickett 2010 p.6-11)

Research by Wilkinson and Pickett (2010),  based on two data sources: International data from 2004 UN HDR and US data from the year 2000, showed a strong correlation between life expectancy and income inequality. For the international data r = -0.44 p-value 0.04 whilst for the US data r = -0.45 p-value = <0.01. This research however, has been criticised for not using the latest available data and for excluding countries based on population in an attempt to exclude tax-havens resulting in the loss of countries with low populations which were in fact not tax havens (Snowdon 2010 p.13)

Conducting his own tests addressing these issues and using data from 2006 UN HDR Snowdon finds R₂ =0.026 whilst based on data from 2009 UN HDR R₂  is reported as = 0.0478 (Snowdon 2010 p.28-29). The graph follows Snowdon’s methodology, using the latest available life-expectancy data from 2011 from which it would appear that the observations do not support Wilkinson & Pickett’s suggestion that higher levels of income inequality are associated with lower levels of life expectancy. In particular Hong-Kong and Singapore which both have a high GNI per capita, but high levels of inequality also have high life expectancies whilst the Czech and Slovak Republics, towards the lower end of the income range both have lower life expectancies despite having lower levels of income equality- Indeed R₂ = 0.059 with a significance of only 0.214 therefore is neither significant at the 1% nor 5% level.

Even when reverting Wilkinson and Pickett’s original methodology the 2011 life expectancy data do not show a strong relationship between life expectancy and income inequality, R₂ remaining a relatively low 0.038 whilst significance is 0.373 as this following graph shows:


The 2011 life expectancy data, when using either Snowdon’s, or Wilkinson & Pickett’s methodology, do not appear to support claims that there is a strong relationship between income inequality and life expectancy. This is not to say however, that Wilkinson and Pickett’s original assertions were necessarily incorrect. Life expectancy for example is generally increasing, so it may well be that recent improvements in this area have led to the relationship Wilkinson & Pickett observed being eroded. This research was also only carried out on only one aspect of the spirit level thesis and therefore is not applicable to other areas covered by Wilkinson & Pickett, such as crime and obesity.

This image has been produced by software developed by Wolfram/Alpha and is based upon data on my friends and mutual friends it has accessed from my Facebook account .

Far more than a pretty graphic, which bears more than a passing resemblance to a map of a galaxy, this chart provides an example of how researchers can harness the power of new computing technology and social media to shed new light on areas of interest; This particular chart mapping my friends and mutual friends provides a great illustration of my ‘social capital’ – broadly speaking the social connections I have and groups I may belong to.

As a researcher I may be interested in how social capital varies by age, gender, ethnicity and employment status. It may also be possible to take a  longitudinal approach; how does my social capital change over time, what happens when I become a parent, emigrate, get a new job, become unemployed, or retire? charts such as this one can be used to make comparisons, or chart changes over a time period.

One issue however, is that Facebook is not wholly representative. There are, of course many people who do not have a Facebook account, particularly older people – therefore any data is likely to be skewed. Looking at a bar chart of the age range of my contacts, also by Wolfram/Alpha, it is interesting to see that the ages of my friends approximates a normal distribution around my own age, but its positive skew is likely to be a result of this age bias.

Age bias among Facebook users

To illustrate what the chart can show I have added my own annotations:

From the chart I can see that much of my social capital seems to be divided into distinct spheres; education, work, family and friends.


In terms of education my connections are strongest from middle school and secondary school.Though there is some overlap with middle school, friends from infant school, or even earlier pre-school do not feature on the chart. This is perhaps likely to be because at that young age we do not form the same type of friendships and connections which we begin to do once at middle school; Friendships in these early stages could well be much more fluid and transient.

Similarly my social capital relating to university seems to be rather sparse; my contacts and mutual connections both being particularly weak. This may be because I attended university in my home town and therefore was less part of the university ‘scene’, but perhaps more importantly university drew people from a very wide catchment reducing the number of mutual contacts compared to someone from school who grew up in the same area and went to work in the same area too. As many of my course-mates left the area following their studies the social network became dispersed.

This is even more so the case when it comes to the two years of my masters degree. As the people on this course came from an even wider area, and as the course covered a shorter time period.


The biggest group in terms of the area it covers is my ‘friends’ group. This is the largest group, though my contacts are less clustered than elsewhere suggesting a more loosely connected web of ‘acquaintances’


In terms of work my latest job is further away from the main clusters; this is as a result of my job being in a different town. Though not far in terms of distance it shows that, in general, peoples networks are closely bounded by geography.  My previous job I had obtained through old friends so it was much closer to my friendship cluster. As my previous jobs have been in very different organisations there is also no over-lap between my work clusters.


this cluster is as expected, however the previously mentioned age bias of social networking is perhaps undercounting this cluster more so than any others.

Wider implications:

Charts such as this one, using data held by social networking sites such as Facebook can provide an  understanding of how social capital is formed and what factors affect this. The relative strength of social capital from school may go in part to explain the enduring power of networks based on the ‘old school tie’. Similarly the intensity of connections related to work can show the importance of professional networks.