20. Challenge 2: Burden of disease
90% of the
• Caries world's
• Oral cancer population
have had
• Periodontal disease
oral pain in
• Noma their lifetime
• Birth defects
• Trauma
21. Challenge 2: Burden of disease
90% of the
• Caries world's
• Oral cancer population
have had
• Periodontal disease
oral pain in
• Noma their lifetime
Dental caries is the
most common • Birth defects
chronic disease
• Trauma
worldwide
Background in public health & behaviour change, 4 years @ FDI, policy, advocacy, communication & project management \nIllustrated with maps & images from The Oral Health Atlas -2009\nSocial Exclusion is what can happen when people or areas suffer from a combination of linked problems - unemployment, poor skills, low incomes, poor housing, high crime, bad health and family breakdown. It is characterised by the inter-relatedness of problems that are mutually reinforcing; combined they create a fast moving, complex and vicious cycle. - Inclusion Institute, University of Central Lancashire\n
Background in public health & behaviour change, 4 years @ FDI, policy, advocacy, communication & project management \nIllustrated with maps & images from The Oral Health Atlas -2009\nSocial Exclusion is what can happen when people or areas suffer from a combination of linked problems - unemployment, poor skills, low incomes, poor housing, high crime, bad health and family breakdown. It is characterised by the inter-relatedness of problems that are mutually reinforcing; combined they create a fast moving, complex and vicious cycle. - Inclusion Institute, University of Central Lancashire\n
Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
Social inclusion / exclusion seen through 4 lenses: exposure to risk factors, burden of disease, access to services and costs.\n
Major risk factors, such as tobacco use, physical inactivity and a diet high in fat, salt and sugar, contribute to a range of chronic diseases, such as obesity, diabetes, cardiovascular diseases and oral diseases.\nPoverty and chronic disease are linked into a vicious cycle; chronic diseases can exacerbate poverty and the poor have greater exposure to risk and less access to health services.\n
The average person in the Democratic Republic of Congo consumes less than one teaspoon of sugar a day, while the average person in the USA consumes more than 19\n The average American consumes 336 liters of soft drinks a year; nearly a liter a day\nThere are also disparities within countries & risks alone do not determine health\n
The average person in the Democratic Republic of Congo consumes less than one teaspoon of sugar a day, while the average person in the USA consumes more than 19\n The average American consumes 336 liters of soft drinks a year; nearly a liter a day\nThere are also disparities within countries & risks alone do not determine health\n
Many risk factors are results of broader determining factors, such as lifestyle, socio-economic status, or living conditions.\nAlmost 80% of diabetes deaths occur in low- and middle-income countries\n
Caries is a middle-income problem\nAccess is care increases with income\nlinks between oral diseases and socio-economic status\nWHO Commission on Social Determinants on Health (2008) expressed so clearly: “In countries at all levels of income, health and illness follow a social gradient: the lower the socio-economic position, the worse the health.”\nMaori women are five times more likely than New Zealand Caucasian women to be toothless.\n
Caries is a middle-income problem\nAccess is care increases with income\nlinks between oral diseases and socio-economic status\nWHO Commission on Social Determinants on Health (2008) expressed so clearly: “In countries at all levels of income, health and illness follow a social gradient: the lower the socio-economic position, the worse the health.”\nMaori women are five times more likely than New Zealand Caucasian women to be toothless.\n
Caries is a middle-income problem\nAccess is care increases with income\nlinks between oral diseases and socio-economic status\nWHO Commission on Social Determinants on Health (2008) expressed so clearly: “In countries at all levels of income, health and illness follow a social gradient: the lower the socio-economic position, the worse the health.”\nMaori women are five times more likely than New Zealand Caucasian women to be toothless.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Not going to focus on perio, the data is incomplete\n Links to general disease: type II diabetes, cardiovascular, premature &-low birth weight, etc.\n
Tooth decay is a middle income disease but lack of treatment mostly affects the poor\nGenerally, caries rates are highest in middle-income countries where sugar consumption is high but access to prevention and care is low. \n Breakdown of treatment by income\n Yellow is untreated disease\n
Tooth decay is a middle income disease but lack of treatment mostly affects the poor\nGenerally, caries rates are highest in middle-income countries where sugar consumption is high but access to prevention and care is low. \n Breakdown of treatment by income\n Yellow is untreated disease\n
Tooth decay is a middle income disease but lack of treatment mostly affects the poor\nGenerally, caries rates are highest in middle-income countries where sugar consumption is high but access to prevention and care is low. \n Breakdown of treatment by income\n Yellow is untreated disease\n
6% of Californians, or about 1.8 million people, miss work or school each year due to dental problems\n In the Philippines, 85% of 6-year-old children had signs of dental infection\nBetween 1997 and 2006 there has been a 66% increase in the number of children admitted into hospital for tooth extraction in the UK.\n
6% of Californians, or about 1.8 million people, miss work or school each year due to dental problems\n In the Philippines, 85% of 6-year-old children had signs of dental infection\nBetween 1997 and 2006 there has been a 66% increase in the number of children admitted into hospital for tooth extraction in the UK.\n
Once case study from the Philippines\n
Once case study from the Philippines\n
Once case study from the Philippines\n
Once case study from the Philippines\n
Once case study from the Philippines\n
Once case study from the Philippines\n
Once case study from the Philippines\n
Once case study from the Philippines\n
World average: 6.3, Highest: Papua New Guinea 40.9, Lowest: El Salvador 0.4 \nThe average 5-year survival rate of oral cancer among white high-income males in Mumbai is 30%, whereas i the USA it i 70%\n
World average: 6.3, Highest: Papua New Guinea 40.9, Lowest: El Salvador 0.4 \nThe average 5-year survival rate of oral cancer among white high-income males in Mumbai is 30%, whereas i the USA it i 70%\n
The problem is worst in South-East Asia; Paan use is a key factor\n Smoking is associated with about 75% of oral cancer cases.\n The risk for oral cancer is 15 times higher when the two main risk factors, tobacco use and alcohol, are combined.\n
The problem is worst in South-East Asia; Paan use is a key factor\n Smoking is associated with about 75% of oral cancer cases.\n The risk for oral cancer is 15 times higher when the two main risk factors, tobacco use and alcohol, are combined.\n
Noma is a good example of an oral disease with a low incidence rate but a high impact, fatal in about 80% of cases\n While there have been cases of noma around the world, it is currently a mainly African problem\n
Noma is a good example of an oral disease with a low incidence rate but a high impact, fatal in about 80% of cases\n While there have been cases of noma around the world, it is currently a mainly African problem\n
Noma is a good example of an oral disease with a low incidence rate but a high impact, fatal in about 80% of cases\n While there have been cases of noma around the world, it is currently a mainly African problem\n
risk 40% higher fro deprived ares of the UK\n Boys are almost twice as likely to experience dental trauma as girls.\n
risk 40% higher fro deprived ares of the UK\n Boys are almost twice as likely to experience dental trauma as girls.\n
risk 40% higher fro deprived ares of the UK\n Boys are almost twice as likely to experience dental trauma as girls.\n
The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
The dentist-to population ratio is a rough indicator of service availability, but does not necessarily result in the improvement in oral health. \nIllegal practitioners often fill the gap, sometimes causing more harm than good\nRural neglect = dentists are concentrated in the urban areas\nThere are only 16 dentists in Eritrea, and 15 of them work in the capital.\nIn India, the dentist:population ratio in rural areas is 1:300,000 and 1:27,000 in urban areas.\n Migration = low-income to high-income = brain drain\nThere are more dentists from Benin in France than in Benin.\n22% of dentists practicing in the UK are foreign born.\n
80% of all oral health care is concentrated in 20% of the population\n
80% of all oral health care is concentrated in 20% of the population\n
Dental treatment accounted for only 3% of the reduction in tooth decay in 12-year-olds in industrialised countries during the last 40 years. The main\nfactors were fluoride toothpaste and general socio-economic development. \nautomatic fluoride helps the socially excluded most, however they have the least access to toothpaste\n For every US$1 spent on salt fluoridation, around US$250 are saved in treatment costs.\n
In India and Nepal tax accounts for 25% of the retail price of toothpaste; in Burkina Faso this is up to 50%\n In the Netherlands an average 300g of toothpaste are used per person per year; in Myanmar 35g\nZambia it can take over 30 days to pay for toothpaste\n
In India and Nepal tax accounts for 25% of the retail price of toothpaste; in Burkina Faso this is up to 50%\n In the Netherlands an average 300g of toothpaste are used per person per year; in Myanmar 35g\nZambia it can take over 30 days to pay for toothpaste\n
In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
In 2004, only 44% of US citizens went to see a dentist. The average treatment took 2.1 sessions and the average cost was US$560.\n
Prevention is cheaper than treatment, however most health systems do not pay dentists for prevention or invest in it.\nIn the USA alone, 2.4 million days of work and 1.6 million days of school were lost due to oral disease in 1996.\n
Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
Prevention = fluoride, risk-factors, social-determinants\nBehaviour change for population, professionals, policy makers, insurance\nevidence-based such as school health\nTraining dentists is expense and time consuming. Many countries have to send them abroad where they are unlikely to return. Even when they do they work in urban areas. \nSyria has invested significantly in scaling up the dental workforce:\ndentist numbers increased from 1,975 dentists (1981) to 14,610 (2002). However, the percentage of untreated caries and DMFT remained more or less unchanged.\nTraining other health workers to do simple extractions, ART and referral is more realistic\n
The Atlas can be purchased from www.OralHealthAtlas.org, www.Amazon.co.uk\nFDI Data Mirror is an online tool that will let you play with some of this data\n
The Atlas can be purchased from www.OralHealthAtlas.org, www.Amazon.co.uk\nFDI Data Mirror is an online tool that will let you play with some of this data\n
