The current world is explicitly divided into developed world characterized by having ultra-modern technological advancement, most efficient communication system, better health care and income opportunities and under developed region with completely opposite scenarios. This huge inequality among the countries depicted in huge differences in health and wellbeing of the populations.. According to the World Health Organization (WHO), there is a 36 years variation between the life expectancy among the countries. The life expectancy of Malawi is only 47 years while in case of Japan it is 83 years. WHO has declared that “there is no biological or genetic reason for [the] alarming differences in health and life opportunity”. The unequal scenario of health status, however, not only persists between countries, but also evident within countries, and surprisingly almost all countries irrespective of rich or poor. There is a distinct differentiation in the health status among people of different socio-economic status (SES). Generally, people with higher SES tend to have better health than that of lower SES (Whitehall Study). That is health status is directly related to social status. This fact is referred to as the social gradient in health ( Kosteniuk and Dickinson, 2003). Since health inequalities are evident despite significant improvement in overall health of the populace, it has become the pivotal agenda in the health policy planning and management.

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Social Gradient in Health
The social gradient in heath refers to the fact that inequalities in population health status are related to inequalities in social status (Kosteniuk and Dickinson, 2003).The poorest of the poor, around the world, have the worst health. Within countries, the evidence shows that in general the lower an individual’s socioeconomic position the worse their health. There is a social gradient in health that runs from top to bottom of the socioeconomic spectrum. This is a global phenomenon, seen in low, middle and high income countries. The social gradient in health means that health inequities affect everyone.
Health inequities, in particular, are avoidable inequalities in health between groups of people within countries and between countries. These inequities arise from inequalities within and between societies (WHO). Below are some examples of health inequities between and within countries extracted from WHO:
the infant mortality rate (the risk of a baby dying between birth and one year of age) is 2 per 1000 live births in Iceland and over 120 per 1000 live births in Mozambique;
the lifetime risk of maternal death during or shortly after pregnancy is only 1 in 17 400 in Sweden but it is 1 in 8 in Afghanistan.
Examples of health inequities within countries:
in Bolivia, babies born to women with no education have infant mortality greater than 100 per 1000 live births, while the infant mortality rate of babies born to mothers with at least secondary education is under 40 per 1000;
life expectancy at birth among indigenous Australians is substantially lower (59.4 for males and 64.8 for females) than that of non-indigenous Australians (76.6 and 82.0, respectively);
life expectancy at birth for men in the Calton neighbourhood of Glasgow is 54 years, 28 years less than that of men in Lenzie, a few kilometres away;
the prevalence of long-term disabilities among European men aged 80+ years is 58.8% among the lower educated versus 40.2% among the higher educated.
Measurement of Social Gradient
SES is generally categorized based on income, academic qualification, social position, occupation, etc. Each of these components is very associated with themselves. For example, better education tends to lead better job which again associated with better income. In UK, two classifications exist. The Registrar-General’s Social Classes were introduced in 1913 and were renamed in 1990 as Social Class based on Occupation. The classes are: Professional occupations (Class I), Managerial and technical occupations (Class II), Skilled non-manual occupations (Class IIIN), Skilled manual occupations (Class IIIM), Partly-skilled occupations (Class IV), and Unskilled occupations (Class V).
Office for National Statistics on the other hand classified social classes into eight categories. Table 1 depicts this classification.
Table 1: Social classification of the Office for National Statistics
Class
Description
1
Higher managerial, administrative and professional occupations
1.1 Large employers and higher managerial and administrative occupations
1.2 Higher professional occupations
2
Lower managerial, administrative and professional occupations
3
Intermediate occupations
4
Small employers and own account workers
5
Lower supervisory and technical occupations
6
Semi-routine occupations
7
Routine occupations
8
Never worked and long-term unemployed
Based on the two above social classification outcome variables (i.e., mortality and life expectancy) are analyzed. Results showed that those who belong to the upper social class tend to have better health in terms of less mortality rate and higher life expectancy than that of the lower class inhabitants. That is health status follows a social gradient.
Current Scenario: UK
The figure 1 below depicts differences in male life expectancy within a small area in London. Travelling from Westminster, every two tube stops represent one year of life expectancy lost.
C:UsersazharDocumentsAcademicTheories & Perspective of HPliteraturevital referencesD-Tube Map on LE 2004-08.jpg
Although life expectancy has increased in all London boroughs since 2000, there has been a widening in the gap between the boroughs with the highest and the lowest life expectancy. In 1999-2001, this gap was 5.4 years for men and 4.2 years for women. In 2006-2008, the gap had increased to 9.2 years for men and 8.5 years for women (ONS data sources).
Regarding different social class mortality rate also varies significantly. From the data of the figure 2, we can see that mortality rate per 100,000 people increased to almost double from class I to class VII.
This is a graph showing age-standardised mortality rate by NS-SEC: men aged 25-64, England and Wales 2001-03Figure 2: Age-standardised mortality rate by NS-SEC: men aged 25-64, England and Wales 2001-03
Explanations for Inequalities
In order to explain why these inequalities exist, a number of explanations have been offered. These are briefly explained below:
Artefact
The relationship between social class and health is probably an artefact of measurement systems used to determine social class as well as health status. Mortality ratios calculated on basis of number of deaths per social class divided by number from each class determined by census returns may be inaccurate reporting of social class.
However, this explanation can be questioned in way that inequalities have been demonstrated using a number of different systems of measurement of social class. For example, occupation, property ownership, educational status and access to social resources. Nonetheless, still there is room for improvement in the measurement system by which classification and health status are determined.
Downward drift (Darwinian selection)
Based on the Darwin’s assumption, this explanation suggests that the illness will slide down the social class while the healthier people will have a greater chance of social advancement.
However, the fact that many health problems only seen in adulthood, often once career choices have been made and social class has been determined. Now, if illness causes downward shift then the explanation of healthy rise class is less likely be true.
Cultural explanations
Health damaging behaviours are differentially distributed across social classes and contribute to observed gradients. This suggests that the lower social classes prefer less healthy lifestyles, eat more fatty foods, smoke more and exercise less than the middle and upper classes.
Using the Canadian National Population Health (NPH) Survey (1994-1995) data of 7720 men and 9269 women 15 to over 80 years of age, (Kosteniuk and Dickinson, 2003) found higher household income, being retired, and aging are associated with better physical health and lower mental distress when accounting for their role in lowering stressor levels and bolstering control, self-esteem, social support, and social involvement. This evidence can partly be of supportive with the cultural explanations. However, more investigation is needed why this variation in behaviour of different social class.
The material explanation
Physical and psychosocial features associated with the class structure influence health and contribute to observed gradients. This indicates that poverty, poor housing conditions, lack of resources in health and educational provision as well as higher risk occupations for the poor determines the gradient in health. No doubt poverty impacts negatively in the health outcomes. However, only improving materialistic access might not lead better health and less social gradient.
Consider the example of Bangladesh, India and Pakistan. Having around double income per person than that of Bangladesh in last decade, India and Pakistan left behind in almost all the health indicators (see Figure 3). Life expectancy at birth increase for Bangladesh is 17% while the figures for India and Pakistan are 12% and 6.56% respectively. In case of infant (ageFigure 3: Health and income status of Bangladesh, India & Pakistan from 1990 to 2011 (extracted from The Economist, 3rd November 2012)
Social class is a complex construct that may involve status, wealth, culture, background and employment. It would therefore be naive to look for a simple causal relationship between class and ill health. Each individual will experience a number of different influences on their health, some of which also come under the umbrella of social class.
Actions to combat social gradient in health
Marmot’s review (2010) noted ‘The implications of the social gradient in health are profound. It is tempting to focus limited resources on those in most need.’ Although social gradients in health affecting almost everyone, interventions however are very crucial for people in need most. But so far the policy, programmes and interventions aiming to reduce social gradient in health mounted a lot and itself create problems for the root level personnel. A report from the Audit Commission says ‘there has been too much policy and accompanying guidance issued by central government for people working in the field to keep up with. It is also critical that trusts and local authorities have often faced conflicting demands from central government and calls for a more “consistent and lasting set of policy statements” to aid implementation on the ground.’
We are unlikely to be able to eliminate the social gradient in health completely, but it is possible to have a shallower social gradient in health and wellbeing than is currently the case for England. This is evidenced by the fact that there is a steeper socioeconomic gradient in health in some regions than in others, as shown in Figure 2.
To reduce the steepness of the social gradient in health, actions must be universal, but with a scale and intensity that is proportionate to the level of disadvantage. We call this proportionate universalism. Greater intensity of action is likely to be needed for those with greater social and economic disadvantage, but focusing solely on the most disadvantaged will not reduce the health gradient, and will only tackle a small part of the problem.
Potential area of intervention: Unhealthy behaviour
Potential target group: group at in risk
Conclusion
Unhealthy behaviour
Smoking
Poor Diet
Less physical activity
Alcoholism
Determinants of health
In today’s debates, the determinants of health include all the major non-genetic and non-biological influences on health. The term therefore covers individual risk factors, such as smoking, and what are often called ‘wider determinants’ (Hilary Graham* and Michael P Kelly, Health inequalities: concepts, frameworks and policy)
Smoking is responsible for one in six deaths in the UK. It is overall the one area where behavioural change would make the greatest impact on health inequalities. A clear divide remains in smoking levels between manual and non-manual groups, and there are also significant differences between different ethnicities and genders. Over 40% of Bangladeshi men smoke, compared to around 5% of Bangladeshi women, and more than one in four women of Irish descent are smokers.
Smoking is the largest recognised cause of premature death and disability, and is responsible for about one in six deaths (over 100,000 in total) every year in the UK. Smoking prevalence has fallen dramatically in the most affluent sectors of society over the past 30 years, but much less so among the most disadvantaged. Women who smoke during pregnancy are more likely to have babies born prematurely, twice as likely to have low birth weight babies and up to three times more likely to die from sudden unexpected death in infancy (SUDI). Low birth weight babies experience increased risk of cardiovascular disease and diabetes.
Long-term smokers bear the heaviest burden of death and disease related to their smoking and is disproportionately drawn from lower socio-economic groups. Smokers in poorer social groups tend to have started smoking at an earlier age: 31% of smokers in managerial and professional households started before they were 16, compared with 45% of those in routine and manual households.
Obesity and its risks are not experienced equally across society, in some cases this is related to particular behaviours. There is evidence that people whose ethnic background is Pakistani or Bangladeshi are much less likely to engage in high levels of physical exercise.
There are marked differences in satisfaction with primary care services. People from black and minority ethnic groups report significantly worse access than white British people. Performance on access is worst for people from Pakistani and Bangladeshi backgrounds: their satisfaction with their level of access is 10-20 percentage points below that reported by people from white British backgrounds.
It is clear that more needs to be done to address the needs of people with disabilities. Compared with people without disabilities, they are more likely to live in poverty, less likely to have educational qualifications, more likely to be economically inactive, more likely to experience problems with hate crime or harassment, and more likely to experience problems with housing and transport. These correlations appear to work in both directions: people are also more likely to become disabled if they have a low income, are out of work or have low educational qualifications.
Stroke is the single largest cause of disability in England.1 Approximately half of those who survive a stroke will be left with long-term disability problems six months afterwards and will be dependent on others.
People with disabilities often experience multiple forms of labour market disadvantage: more than 40% of people with disabilities are low-skilled; around 25% of those of working age are over 50; and around 10% are from black and minority ethnic groups.
One study2 has estimated that people with learning disabilities or long-term mental health problems are 58% more likely to die before age 50 than non-disabled people. And studies of psychiatric patients in hospitals show that up to 70% smoke.
Access to care services has been reported as an issue. Around a quarter (24%) of deaf or hearing-impaired people miss care appointments, and 19% miss more than five appointments, because of poor communication. Two-fifths (40%) of visually impaired people believe that their GPs are not fully aware of their needs, rising to 60% for other surgery staff. Disabled people are also four times more likely than the general population to find their dentist’s surgery inaccessible.
Stigma and shame are barriers to the engagement and employment of people with mental illness. Negative media images add to this discrimination. Only 21% of people with long-term mental illness are employed, the lowest proportion of any disabled group.
People with severe mental illness are 1.5 times more likely to die prematurely than others, often from preventable causes, and they are also less likely to access routine health checks.
There are also differences in alcohol related deaths. There are now around 23,260 deaths related to alcohol every year in England. Every man dying of alcohol-related causes loses on average 21 years of life, and every woman loses 15 years.
The prevalence of disability increases rapidly with age. Approximately 75% of men and women aged 85 and over are disabled.
Alcohol is a particular problem in the mid years. Around 26% of adults in England are drinking at hazardous, harmful or dependent levels. The largest increase in the number of NHS alcohol-related hospital admissions is in the 35-49 age group. These include admissions where alcoholic liver disease, the toxic effect of alcohol or mental and behavioural disorder due to alcohol are identified as the primary or secondary diagnosis.
The social pattern of problem drinking is complex, but more disadvantaged communities have higher levels of mortality, hospital admission, crime, absence from work, school exclusions, teenage pregnancy and road traffic accidents due to alcohol consumption. Within localities, the most disadvantaged individuals – typically unemployed, low-income older smokers – have 4 to 15 times greater alcohol-specific mortality and 4 to 10 times greater alcohol-specific admission to hospital than the most affluent.
Alcohol has a serious effect on behaviour and relationships in the home, affecting the mental health and behaviour of children of alcohol-misusing parents.15 Furthermore, harmful drinking is linked to psychiatric morbidity including depression, and around a third of incidents of domestic violence are linked to alcohol misuse. Around one million children live in families where at least one parent misuses alcohol, and by the age of 15 young people in families with a parent who drinks at harmful levels have rates of psychiatric disorder that are between 2.2 and 3.9 times higher than those of other young people.16
Since the mid-1990s, newly diagnosed cases of HIV have been increasing. Increased testing will have contributed in part to this, and also enables earlier intervention. Men who have sex with men continue to be disproportionately affected. By 2006, men having sex with men accounted for up to three-quarters of UK-acquired HIV infections, and they remain the behavioural group at greatest risk of acquiring HIV in the UK. An estimated 31% of men having sex with men aged 15-59 were unaware of their infection in 2006. Among HIV-infected men having sex with men, diagnosed late are 14 times more likely to die within one year of diagnosis than those diagnosedearlier.17