Skip to main content

Social determinants of male health: a case study of Leeds, UK



The social determinants of health have a disproportionate impact on mortality in men. A study into the state of health of the male population in Leeds was undertaken to guide public health commissioning decisions. This paper reports on the data relating to the social lives of men.


A cross-sectional study was undertaken, comprising descriptive analysis of data relating to educational attainment, housing, employment (including benefit claimants), marital status and relationships. Data was considered for the whole city and localised at the Middle Super Output Area (MSOA) level and mapped against the Index of Deprivation.


Boys’ educational attainment was found to be lagging behind girls’ from their earliest assessments (Early Years Foundation Stage Profile, 46% vs. 60%, P = 0.00) to GCSEs (53% vs. 63%, P = 0.00), leaving many men with no qualifications. There were 68% more men than women identified as being unemployed, with more men claiming benefits. Men living in social housing are more likely to be housed in high-rise flats. Almost 50% of men aged 16–64 are single, with 2254 lone fathers.


There appears to be a lack of sex/gender analysis of current cross city data. In areas of deprivation a complex picture of multiple social problems emerges, with marked gender differences in the social determinants of health, with males seeming to be more negatively affected. There is a need for more focused planning for reaching out and targeting boys and men in the most deprived inner city areas, so that greater efficiency in service delivery can be obtained.

Peer Review reports


There is a growing recognition that the health of the male population is heavily affected by their social situation, with increasing poverty linked to a widening gap in life expectancy [1, 2]. This is a global phenomenon, with such differences reported across the European Union [3], Asia [4], Australia [5], and within countries such as Ireland [6], Denmark [7], and Germany [8]. This study explores the social situation of men within a substantial metropolitan city in the UK, however the findings should have a resonance with men in other large conurbations.

The opportunities for improving public health through local action has been recognised [9, 10] and with an increasing agenda for targeting activity within the most challenging areas. Leeds is the third largest city in the United Kingdom; since 2010, there has been a 47% reduction in the money that Leeds City Council gets from Government to run local services. To ensure tendered contracts are fit for purpose, Leeds Council’s Joint Strategic Needs Assessment [11] noted that there was a dearth of information on the 400,000 male population across the city. This acted as a stimulant to instigate a study into the State of Men’s Health in Leeds, to act as a guide to future public health planning.

The findings of that study [12,13,14] highlighted that there were large differences in both morbidity and mortality for men across different areas of Leeds, suggesting that the health challenges the men were facing were more than a biological issue specific to being male.

There is strong evidence across a wide range of studies and reports on the impact of the wider determinants of health on a population’s wellbeing [15,16,17,18,19,20,21]. What has been less well-researched is how being sex is affected by these social factors [22,23,24,25,26,27,28,29,30]. There has been a sustained campaign for the disaggregation of data by sex in both research and routinely collected data within public health [3, 31,32,33,34,35], with the recent report on women’s health in Europe calling for improved availability and use of sex-disaggregated data that can be cross-linked to social factors [36]. With the push for gender mainstreaming [37] and also the legal requirements for gender to be recognised as a protected group within health policy strategy and service provision [38] the need for such scrutiny is further supported.

Through the more detailed examination of how sex maps onto intersectional factors (such as age, ethnicity, disabilities and sexuality) and the wider social determinants of health a more efficient targeting of resources may be achieved. By making more explicit how social and environmental factors differentially impact on both men and women we can help guide the development of more gender sensitive policies and practices to ensure equity in provision of services as opposed to the blunter push for equality.

The aim of this paper is to provide an overview of the findings from the Leeds study to highlight the wide disparities that exist within our municipalities with regard to some of the key social determinants of men’s health: educational attainment, housing, employment, poverty and living arrangements.


A cross-sectional study was adopted, which was based on an examination of routinely collected and available data relating to the social determinants of health.

Data sources

Educational attainment included the proportion of girls and boys in Leeds achieving: 1) a good level of development in the Early Years Foundation Stage Profile (EYFSP) [39]; 2) level 2 key stage 1 reading; 3) level 2 key stage 1 writing [40]; and 4) three or more higher grade General Certificate of Secondary Education (GCSE) passes including English and Maths [41]. Educational attainment data relating to looked after children was obtained directly from Leeds Children’s Services. Demographic data for those living in Council-owned high-rise flats was obtained directly from the Environments and Housing department within Leeds City Council (obtained April 2015). Benefits data for job seekers allowance and employment and support allowance were obtained from Leeds City Council Public Health intelligence team. Data showing underlying conditions for Employment and Support Allowance (ESA) claimants were obtained from Data on divorces were obtained from the Office for National Statistics (ONS) [42].

Census data were used for the following:

  • The number of men and women in Leeds with no qualifications [43].

  • The number of men and women living alone [44]

  • Tenure [45]

  • Homelessness [46]

  • Unemployment [47]

  • Long-term unemployment and ‘never worked’ [48]

  • Employment data including status and hours worked [47]

  • The number of men and women economically inactive due to a long-term health problem or disability [49]

  • Marital status [50]

  • Lone fathers [51]

Data analysis

A descriptive analysis was undertaken. Where possible, data were disaggregated by age group, and sex at a city level and by area of residence within Leeds [at the level of the Middle Super Output Area (MSOA)]. Data were calculated as a proportion of the male or female age-specific population in Leeds or within an MSOA where appropriate. Data for each variable were ranked by MSOA with the greatest occurrence within the male population of that area. Mean ± SD sex differences in prevalence of socio-economic factor were analysed using an independent t-test or Mann Whitney U-test where appropriate, with significance set at p < 0.05. Analysis and presentation of data was completed using Microsoft Excel 2013 and SPSS (version 22).


Educational attainment

The proportion of boys in Leeds (of all those eligible to be assessed) in 2013 achieving a good level of development in the Early Years Foundation Stage Profile [EYFSP] was significantly lower than for girls (45.6% ± 13.4% as compared to 60.2% ± 13.0%, P = 0.00) (Table 1). For both sexes, this was below the national average (boys 52.0%, girls 69.0%). In 3 MSOAs in Leeds the proportion of boys achieving a good level of development was at, or below, 20%.

Table 1 Percentage of males and females, for Leeds and national, for Education, housing, employment and marital status and relationships

Boys (aged 5–7 years) were also significantly less likely to achieve level 2+ key stage 1 reading (boys 80.1% ± 6.35%, girls 88.0% ± 6.87%, P = 0.00) and writing (boys 75.1% ± 7.31%, girls 85.5% ± 7.30%, P = 0.00) (Table 1). In 6 MSOAs in Leeds less than 60% of boys achieved level 2+ in writing, and in 11 MSOAs less than 70% of boys achieved level 2+ reading, with 1 MSOA having only 58% of their boys achieve this level. For girls, all MSOAs had more than 60% of girls reaching this level for writing, with only 6 of the 107 MSOAs in Leeds having less than 70% of girls reach this level for reading.

In 2013, the proportion of boys in Leeds achieving five or more higher grade GCSE passes including English and Maths was significantly lower compared to girls (52.4% ± 15.9% vs. 62.9% ± 15.2%, P = 0.00) and was lower compared to boys nationally (55.7%) (Table 1). In 9 MSOAs across Leeds less than 30% of boys are achieving this standard, with all MSOAs seeing more than 30% of girls getting those grades.

Approximately 69% of Looked After Children (LAC) accessing alternative education provision were boys, and the proportion of male LAC achieving a good level of development in the early Years Foundation Stage profile (23%) was similar to that observed in the lowest five ranked MSOAs in Leeds (19–26%). The proportion of male LAC achieving five or more A-C grades at GCSE including English and maths (14%) was less than observed in the lowest ranked MSOA in Leeds (21% for boys).

Across Leeds, 16.1% ± 8.38% of males (16–64) had no qualifications in 2011, however the top ten ranked MSOAs with the highest proportion ranged from 30% to 37% of males with no qualifications.


Approximately 17% of men aged 16+ lived alone in Leeds in 2011, which was similar to the number of women (Table 1). In the top ten ranked MSOAs with the highest proportion this was as high as 26.2% to 42.0% of men. Across Leeds as a whole approximately 16% of men in Leeds aged 16+ lived in social housing (rented from the local council or a not-for-profit housing association approved and regulated by Government) in 2011, however in the top ten ranked MSOAs this was as high as 39.4% to 59.1%.

In April 2015 there were blocks of council-owned high-rise flats in Leeds where 75–85% of residents were males and overall, there was a significantly higher proportion of male residents in this type of housing (62.4% ± 10.1% vs. 37.6% ± 10.1%, P = 0.00). The highest proportion of residents within these complexes were aged between 31 and 60 years of age (Fig. 1).

Fig. 1
figure 1

Percentage of men and women living in council owned high-rise flats in Leeds by age group (from Seims & White 5)

The 2011 census data for Leeds showed that 127 men (aged 16+) were living in a privately owned hostel or temporary shelter for the homeless which is almost double the number of females (64).


The number of unemployed men in Leeds, in 2011 was 68% higher compared to females, a gender difference much higher than for England & Wales, where 48% more men were unemployed compared to women. Unemployment was significantly greater among men than women (5.80% ± 3.12% vs. 3.30% ± 1.92%, P = 0.00) (Table 1), and the top ten ranked MSOAs with the highest proportion ranged from 10.9%–15.7%.

In 2011, significantly more men were classed as long-term unemployed than women (2.70% ± 1.66% vs. 1.69% ± 1.05%, P = 0.00), which was greater than observed for England & Wales (2.2%) (Table 1). The gender gap was also greater in Leeds compared to the data for England & Wales with 60% more men in Leeds classed as long-term unemployed compared to women verses a gap of 32% nationally. The top ten ranked MSOAs with the highest proportion of men (16–64 years) who were long-term unemployed ranged from 5.1% to 7.5%.

In 2011, 2.48% ± 1.96% % of men in Leeds aged 25+ had never worked which was higher than men in England & Wales (2.1%) (Table 1). In the ten highest ranked MSOAs this was as high as 5.2% to 8.2%.

In 2011, those men in work (employed and self-employed) were significantly more likely to be working full time, with nearly 9.87% ± 3.58% of men in Leeds over the age of 16 years working over 49 h a week compared to 3.14% ± 1.46% of women (P = 0.00, (Fig. 2 and Fig. 3). The top ten ranked MSOAs with the highest proportion of male employees (aged 16+ years) working long hours (over 49 h a week) ranged from 10.4% to 13.3% of men.

Fig. 2
figure 2

Hours worked by male and female employees (from Seims & White5)

Fig. 3
figure 3

Hours worked by self-employed males and females (from Seims & White5)

There were 4.19% ± 3.51% of men claiming Job Seekers Allowance in Leeds in 2014, as compared to 2.18% ± 1.92% of women (P = 0.00), but in 3 MSOAs over 14% of the male population were claimants.

In 2011, 4.18% ± 2.32% of men (3.69% ± 1.89% of women) (aged 16+) were economically inactive due to long-term disability or illness (P = 0.23), however the top ten ranked MSOAs with the highest proportion ranged from 7.4% to 10.1%. In 2014, 5.88% ± 3.30% of men (aged 16–64) in Leeds claimed Employment and Support Allowance (ESA) as compared to 5.01% ± 2.67% of women (P = 0.09), with the top ten ranked MSOAs with the highest proportion of male claimants ranging from 10.9 to 13.0%. The most prominent underlying condition was mental and behavioural disorders, accounting for almost 50% of males claiming ESA. In 2014, 10.5% ± 3.65% of men aged over 65 claimed attendance allowance in Leeds (16.8% ± 5.86% of women, P = 0.00), however in the top ten ranked MSOAs this ranged from 14.7 to 25.8% of men in those areas.

Marital status and relationships

In 2011, 48.4% ± 13.5% of men aged 16–64 years were single, which was significantly higher than for women (42.8% ± 14.7%, P = 0.00) (Table 1). Significantly more men within the middle-aged (30–49 year) population of Leeds, were also single men compared to women (39.1% ± 11.3% vs. 27.0% ± 7.82%, P = 0.00).

The data from the 2011 Census for Leeds shows that divorced men are typically aged 30–59 years and that approximately 11% of this age group are divorced, however in the ten MSOAs ranked with the highest proportion of divorced men this ranged from 13.2% to 15.9%.

In 2011 there were 2254 lone fathers (aged 16–74) with dependent children in Leeds (0.85% ± 0.43% of men aged 16–74 in Leeds). This was proportionally similar to data for England and Wales (0.8% and 7.2% of the male and female 16–74 year population were lone fathers and mothers respectively).


Main findings from this study

This is the first study to explore the social determinants of health from a male perspective across an entire city. Our study suggests that there is a clustering of known social determinants that are detrimental to health around deprived areas of Leeds and that there are marked gender differences evident. Although the current analysis did not allow for individual’s experiences to the mapped, it is notable that there was a common group of MSOAs which saw the highest proportion of men struggling with the social determinants of health. Those areas of Leeds that showed poor educational attainment also had a high proportion of long-term unemployed men, a higher proportion of men claiming benefits, more problematic housing and divorced men.

Comparison with the literature

There are well-established links between poverty and health [52,53,54,55,56], with the Marmot report highlighting that men generally have higher rates of premature death when experiencing social and economic hardship [1]. The health implications for men and boys with regard to worsening socio-economic hardship has also been noted both nationally [57] and internationally [2, 3, 58].

Implications of the findings

With the move of Public Health into local government, the link between targeting the social determinants of health as a means of improving the health of the local population has been acknowledged, but fiscal constraints mean more focused provision may prove more cost effective.

Planning services for effective public health requires targeting of resources to achieve maximal effect. What has become apparent through the study is the impact of the social determinants on men have been generally under-reported in the literature and this has perhaps left a cohort of vulnerable men hidden from Commissioners’ eyes. The clustering of factors that influence men and their health suggests they need to be recognised and tackled as a whole; focusing on single items negates the complexity of the broader picture.

Breaking the data down by MSOA gives a more detailed view of where services should be targeted and also gives visibility to the social problems that men are facing and a possible explanation for some of the health challenges they face. This is most starkly seen with regard to the high level of suicide in men within Leeds, with over 5 times more men dying as a result of taking their own life as compared to women, with living in the high rise flats, creating the most notable risky setting [13, 59, 60].

The analysis of educational attainment across the City showed that there is a need to consider not just how to get young boys better engaged with schooling, but that support may be needed for men throughout their lifespan. With some areas of Leeds having nearly a third of their male population with no educational qualifications this adds greatly to their risk of unhealthy lifestyles and risk of premature death [55, 61,62,63]. By targeting boys early in their school life they can be helped to overcome some of their deficits and this has long term benefits with regard to their cognitive skills and achievement, behaviour, mental health, other school related outcomes, and adult outcomes [64].

In support for the need for sex-specific data on the social determinants [32, 36] a key observation made in the Leeds study [13] was that although there were comprehensive locality maps of deprivation produced by the Leeds public health observatory, they rarely offered sex-specific data, leaving the possibility that those most at risk (either male or female) to be missed within any subsequent planning decisions. By making explicit the data on men and women it can also help inform health policies relating to the potential impact of the social world they live in.

The Leeds Report was initiated by the Health and Wellbeing Board and the Director for Public Health, and is now being considered by the Scrutiny Board of the Council, with view to stimulating a City-wide response to the report’s findings. This will be the first time that a whole city has instigated a review of services for men and offers up a model for how other cities can tackle men’s health.

There has already been some response, with, for instance, a new service being introduced into the high rise flats in Leeds. The introduction of the bedroom tax and the system of housing allocation has impacted on where young single unemployed men are being housed, with more now being located in the high rise blocks of flats than previously. The Commissioners have noted that this is creating a new problem, where these mostly white young men are suffering from low self-esteem, depression and social isolation. By offering support on their doorsteps has started to create a safer environment for them and an opportunity to identify physical and emotional problems earlier than previously.

Further research is needed with those living in the high risk areas to determine if they are affected by multiples of the factors identified in this paper, in the same way that are now being identified through the clustering of lifestyle factors such as smoking, drinking and sedentary behaviour [65]. This might enable a much more nuanced level of care planning for those individuals who are the most vulnerable.

Limitations of this study

The data that has been presented gives an overview of some of the key aspects of the social determinants that could be seen to affect the health of men, however the study was based on available data and was part of a bigger study, and therefore should not be seen as comprehensive.

This is not a longitudinal study and therefore the current data cannot be directly matched. There is a growing realisation of the clustering effect of factors that impact on health and wellbeing [66], however the health data available through the public health observatory does not allow for grouping of social factors at the individual level.

There may well be other levels of difference based on the intersectional factors, such as age, ethnicity, sexuality, and disability; this would need to be incorporated into future studies.


Although data collected across the city is disaggregated by sex there appears to be a lack of a gendered analysis of its implications for both men and for women. There is great variance in the social worlds of men across a city, which has implications for their health and wellbeing. In areas of deprivation a complex picture of multiple social problems emerges, with marked gender differences in the social determinants of health, with males seeming to be more negatively affected. By targeting men and boys more effectively greater efficiency in service delivery could be obtained. This examination of men’s social circumstances within a city could act as a model for undertaking similar studies both in the UK and elsewhere.



Employment and support allowance


Early years foundation stage profile


General Certificate of Secondary Education


Looked after Children


Middle super output area


Office for National Statistics


  1. Marmot Review Team. Marmot indicators 2014 a preliminary summary with graphs - strategic review of health inequalities post 2010. London: Institiute of Health Equity; 2014.

    Google Scholar 

  2. Cullen MR, Baiocchi M, Eggleston K, Loftus P, Fuchs V. The weaker sex? Vulnerable men and women’s resilience to socio-economic disadvantage. SSM - Popul Heal. 2016;2:512–24.

    Article  Google Scholar 

  3. EC. The state of Men’s health in Europe: extended report. Luxembourg: European Commission, (authors White, A, de Sousa, B, de Visser, R, Hogston, R, Madsen, SAa, Makara, P, Richardson, N, Zatoński, W); 2011.

    Google Scholar 

  4. Tan HM, Ng CJ, HCK C, Hai, Teo CH. Asian Men’s health report. Kuala Lumpur: Malaysian Men’s Health Initiative; 2013.

    Google Scholar 

  5. AIHW. The health of Australia’s males: 25 years and over. Canberra: Australian Institute of Health & Welfare; 2013.

  6. McEvoy R, Richardson N. Men’s health in Ireland: a report from the Men’s health forum in Ireland. Belfast; 2004. Accessed 26 Jan 2014.

  7. Danish National Board of Health. Mænds sundhed - en oversigt overmænds sundhedstilstand og en gennemgang af effektive forebyggelsesmetoder. [Men’s health: An overview of men’s health and review of effective prevention methods]. Copenhagen: Danish National Board of Health; 2010.

    Google Scholar 

  8. Starker A, Rommel A, Saß A-C. Bericht zur gesundheitlichen Lage der Männer in Deutschland – Fazit und Herausforderungen für eine gendersensible Gesundheitsberichterstattung. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2016;59:979–85.

    Article  PubMed  Google Scholar 

  9. Storm I, den Hertog F, van Oers H, Schuit AJ. How to improve collaboration between the public health sector and other policy sectors to reduce health inequalities? – a study in sixteen municipalities in the Netherlands. Int J Equity Health. 2016;15:97.

    Article  PubMed  PubMed Central  Google Scholar 

  10. La Placa V, Knight A. Well-being: its influence and local impact on public health. Public Health. 2014;128:38–42.

    Article  CAS  PubMed  Google Scholar 

  11. Leeds City Council and NHS Leeds. Leeds joint strategic needs assessment 2012: executive summary. Leeds: Leeds City Council and NHS Leeds; 2012.

    Google Scholar 

  12. Seims A, White A. The state of Men’s health in Leeds: data. Leeds: Leeds Beckett University, Leeds City Council; 2016.

    Google Scholar 

  13. White A, Seims A, Newton R. The state of Men’s health in Leeds: main report. Leeds: Leeds Beckett University, Leeds City Council; 2016.

    Google Scholar 

  14. White A, Seims A, Newton R. The state of Men’s health in Leeds: a summary. Leeds: Leeds Beckett University, Leeds City Council; 2016.

    Google Scholar 

  15. Wilkinson R, Marmot M. Social determinants of health. The solid facts (2nd edition). Copenhagen: World Health Organization; 2003.

    Google Scholar 

  16. Marmot Review Team. Fair society, healthy lives (the marmot review). London: The Marmot Review Team; 2010.

    Google Scholar 

  17. Feeney A, North F, Head J, Canner R, Marmot M. Socioeconomic and sex differentials in reason for sickness absence from the Whitehall II study. Occup Environ Med. 1998;55:91–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. CSDH. A conceptual framework for action on the social determinants of health discussion. 2007.

    Google Scholar 

  19. Deaton A. Policy implications of the gradient of health and wealth. Health Aff. 2002;21:13–30.

    Article  Google Scholar 

  20. Phelan JC, Link BG, Tehranifar P. Social conditions as fundamental causes of health inequalities: theory, evidence, and policy implications. J Health Soc Behav. 2010;51(Suppl Spring):S28–40.

    Article  PubMed  Google Scholar 

  21. Braveman P, Egerter S, Williams DR. The social determinants of health: coming of age. Annu Rev Public Health. 2011;32:381–98.

    Article  PubMed  Google Scholar 

  22. Macdonald J. Shifting paradigms: a social determinants approach to solving problems in men’s health policy and practice. Med J Aust. 2006;185:456–8.

    PubMed  Google Scholar 

  23. Griffith DM, Metzl JM, Gunter K. Considering intersections of race and gender in interventions that address US men’s health disparities. Public Health. 2011;125:417–23.

    Article  CAS  PubMed  Google Scholar 

  24. Hosseinpoor AR, Stewart Williams J, Amin A, Araujo de Carvalho I, Beard J, Boerma T, et al. Social determinants of self-reported health in women and men: understanding the role of gender in population health. PLoS One. 2012;7:e34799.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bates LM, Hankivsky O, Springer KW. Gender and health inequities: a comment on the final report of the WHO Commission on the social determinants of health. Soc Sci Med. 2009;69:1002–4.

    Article  PubMed  Google Scholar 

  26. Scott-Samuel A, Crawshaw P, Oakley A. “Men behaving badly”: patriarchy, public policy and health inequalities. Int J Mens Health. 2015;14:250–8.

    Google Scholar 

  27. Griffith DM. An intersectional approach to Men’s health. J Mens health. 2012;9:106–12.

    Article  Google Scholar 

  28. Macdonald J. A different framework for looking at Men’s health. Int J Men’s Heal. 2016;15:283–95.

    Google Scholar 

  29. Hankivsky O. Women’s health, men’s health, and gender and health: implications of intersectionality. Soc Sci Med. 2012;74:1712–20.

    Article  PubMed  Google Scholar 

  30. Tolhurst R, Leach B, Price J, Robinson J, Ettore E, Scott-Samuel A, et al. Intersectionality and gender mainstreaming in international health: using a feminist participatory action research process to analyse voices and debates from the global south and north. Soc Sci Med. 2012;74:1825–32.

    Article  PubMed  Google Scholar 

  31. Richardson N, Clarker N. Men’s health in Northern Ireland : tackling the root causes of Men’s [ ill ] - health. 2011.

    Google Scholar 

  32. White A, Richardson N. Gendered epidemiology: making men’s health visible in epidemiological research. Public Health. 2011;125:407–10.

    Article  CAS  PubMed  Google Scholar 

  33. Lawrence K, Rieder A. Methodologic and ethical ramifications of sex and gender differences in public health research. Gend Med. 2007;4(Suppl B):S96–105.

    Article  PubMed  Google Scholar 

  34. European Commission. Gender equality and Women’s empowerment: transforming the lives of girls and women through EU external relations 2016–2020. 2015.

    Google Scholar 

  35. Sen G, Östlin P, George A. Unequal, unfair, ineffective and inefficient gender inequity in health: why it exists and how we can change it final report to the WHO Commission on social determinants of health women and gender equity knowledge network Gita sen and Piroska Östlin rev. 2007.

    Google Scholar 

  36. WHO. Women’s health and well-being in Europe: beyond the mortality advantage. Copenhagen; 2016. Accessed 27 June 2017.

  37. Varanka JJ. Mainstreaming men into gender sensitive health policies. J Mens health. 2008;5:189–91.

    Article  Google Scholar 

  38. Kingdom U. Equality act. London: HMSO; 2010.

    Google Scholar 

  39. DfE. Early years foundation stage profile by gender (referenced by location of pupil residence). Data for neighbourhoods and regeneration. 2013.

    Google Scholar 

  40. DfE. Pupil attainment at key stage 1 by gender (referenced by location of pupil residence). Data for neighbourhoods and regeneration. 2013.

    Google Scholar 

  41. DfE. Pupil attainment at GCSE by location of pupil residence. Data for neighbourhoods and regeneration. 2013.

    Google Scholar 

  42. ONS. Divorces in England and Wales, 2011: number of divorces, age at divorce and marital status before marriage. Office for National Statistics,. 2011.

    Google Scholar 

  43. NOMIS. DC5102EW (highest level of qualification by sex by age) - Nomis - official labour market statistics). 2013.

    Google Scholar 

  44. NOMIS. DC1109EW (household composition by age by sex) - Nomis - official labour market statistics. 2013.

    Google Scholar 

  45. NOMIS. DC3409EW (general health by tenure by sex by age) - Nomis - official labour market statistics. 2013. Accessed 17 Oct 2016.

    Google Scholar 

  46. NOMIS. DC4210EWLA (communal establishment management and type by sex by age) - Nomis - official labour market statistics. 2013. Accessed 17 Oct 2016.

    Google Scholar 

  47. NOMIS. DC6302EW (economic activity by hours worked by sex by long-term health problem or disability) - Nomis - official labour market statistics. 2013. Accessed 17 Oct 2016.

    Google Scholar 

  48. NOMIS. DC6114EW (NS-SeC by sex by age) - Nomis - official labour market statistics. 2013. Accessed 17 Oct 2016.

    Google Scholar 

  49. NOMIS. DC6107EW (economic activity by sex by age) - Nomis - official labour market statistics. 2013. Accessed 17 Oct 2016.

    Google Scholar 

  50. NOMIS. DC1107EW (marital and civil partnership status by sex by age). Nomis - official labour market statistics. 2011.

    Google Scholar 

  51. NOMIS. KS107EW - lone parent households with dependent children. Nomis - official labour market statistics. 2011.

    Google Scholar 

  52. Novoa AM, Ward J, Malmusi D, Díaz F, Darnell M, Trilla C, et al. How substandard dwellings and housing affordability problems are associated with poor health in a vulnerable population during the economic recession of the late 2000s. Int J Equity Health. 2015;14:120.

    Article  PubMed  PubMed Central  Google Scholar 

  53. McDaid D, Knapp M, Medeiros H, MHEEN Group. Employment and mental health: assessing the economic impact and the case for intervention. London; 2008. Accessed 12 Feb 2014.

  54. Peruzzi A. From childhood deprivation to adult social exclusion: evidence from the 1970 British cohort study. Soc Indic Res. 2014;120:117–35.

    Article  Google Scholar 

  55. Sasson I. Trends in life expectancy and lifespan variation by educational attainment: United States, 1990–2010. Demography. 2016;53:269–93.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Thomas B, Dorling D, Smith DG. Inequalities in premature mortality in Britain: observational study from 1921 to 2007. BMJ. 2010:341:c3639. doi:

  57. Hacking JM, Muller S, Buchan IE. Trends in mortality from 1965 to 2008 across the english north-south divide: comparative observational study. BMJ. 2011;342 Accessed 16 Feb 2011.

  58. Nusselder WJ, Looman CWN, Oyen H, Robine JM, Jagger C. Gender differences in health of EU10 and EU15 populations: the double burden of EU10 men. Eur J Ageing. 2010;7:219–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Insight. Insight report into preventing male suicide in LS12: final report august 2014. Leeds: Insight; 2014.

    Google Scholar 

  60. Everitt M, Eaton V, Ward C, Sehmbi V. Audit of Suicides and Undetermined Deaths in Leeds 2011-2013. Leeds: Leeds City Council; 2016.

  61. Huisman M, Kunst AE, Bopp M, Borgan J-K, Borrell C, Costa G, et al. Educational inequalities in cause-specific mortality in middle-aged and older men and women in eight western european populations. Lancet. 2005;365:493–500.

    Article  PubMed  Google Scholar 

  62. Ross CE, Masters RK, Hummer RA. Education and the gender gaps in health and mortality. Demography. 2012;49:1157–83.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Viner RM, Ozer EM, Denny S, Marmot M, Resnick M, Fatusi A, et al. Adolescence and the social determinants of health. Lancet. 2012;379:1641–52.

    Article  PubMed  Google Scholar 

  64. Magnuson KA, Kelchen R, Duncan GJ, Schindler HS, Shager H, Yoshikawa H. Do the effects of early childhood education programs differ by gender? A meta-analysis. Early Child Res Q. 2016;36:521–36.

    Article  Google Scholar 

  65. Zwolinsky S, Raine G, Robertson S. Prevalence, co-occurrence and clustering of lifestyle risk factors among UK men. J Mens health. 2016;12:15–24.

    Google Scholar 

  66. Watts P, Buck D, Netuveli G, Renton A. Clustering of lifestyle risk behaviours among residents of forty deprived neighbourhoods in London: lessons for targeting public health interventions. Aust J Public Health. 2016;38:308–15.

    Article  CAS  Google Scholar 

Download references


We thank the Leeds Observatory and Public Health team for their support during the study.


The study was funded by the Leeds City Council.

Availability of data and materials

Raw data are not publically available but were obtained as part of a contractual agreement with Leeds City Council.

Author information

Authors and Affiliations



All authors contributed to the study. AW was the principal investigator, AS conducted data collection and analysis, IC and TT helped interpret the data analysis and reviewed the manuscript critically for content. AW will act as guarantor. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Alan White.

Ethics declarations

Ethics approval and consent to participate

The study was given ethical approval by Leeds Beckett University.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interest.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

White, A., Seims, A., Cameron, I. et al. Social determinants of male health: a case study of Leeds, UK. BMC Public Health 18, 160 (2018).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: