Session 3: Nick Wareham

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Professor Nick Wareham: Supporting and Undertaking International Public Health Research in NCD prevention

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  • Big changes from the last edition are mostly due to new data from China, MENA, and Africa Most people with diabetes are 40 – 59 years of age 80% of people with diabetes live in LMICs 2/3 people with diabetes are under 60 More people live in urban than rural areas (63% in urban, almost 2:1 ratio)
  • This slide shows the MAIN FINDINGS OF MY ANALYSIS: Explain graph Highly significant, inverse trend People in Norfolk who met all 5 goals, none went on to develop diabetes, highest rate in those who met no goals Overall incidence similar to that in other UK populations Sensitivity analyses show robustness of the trend –missing data, sex
  • Biggest changes will be in Africa, followed very closely by MENA. NAC and Europe will change the least.
  • Note sparse, mainly linear habitation pattern. Abundance of surrounding forest/farmland.
  • Note dense cluster habitation with almost inexistent green space!
  • Urban dwellers had a significantly lower PAEE than rural dwellers (44 · 6 ± 20 · 2 kJ/kg/day vs. 58 · 6 ± 24 · 5 kJ/kg/day, p<0 · 001). However, note that this difference corresponds to a rural-to-urban left shift in the population distribution of PAEE. So, rural vs. urban difference in physical activity may not only be attributable to a few high risk individuals, but involves a change in the whole population.
  • Trend analysis adjusted for age, sex, residential area, smoking, alcohol consumption, fruit and vegetable consumption, and number of years of education.
  • Note that physical activity in rural Cameroonians is predominantly carried out for work or travel, and very little for leisure. In urban dwellers, the is a much lower time spent for work or travel related activity, with no significant difference in leisure time activity. Urbanization may be causing a large reduction in physical activity for work/travel, but there is still no culture of replacing this with leisure time activity.
  • Seasonal trends and differences in physical activity levels between rural and urban dwellers in Cameroon (N=588). Dark bars = Rural, Light bars = Urban. Bars are means and error bars are SEM. Seasons are: Long Dry, Dec-May; Light Rain, June; Short Dry, July-Sept; Heavy Rain, Oct-Nov
  • Seasonal trends and differences in physical activity levels between rural and urban dwellers in Cameroon (N=588). Dark bars = Rural, Light bars = Urban. Bars are means and error bars are SEM. Seasons are: Long Dry, Dec-May; Light Rain, June; Short Dry, July-Sept; Heavy Rain, Oct-Nov
  • BMI, level of education and light intensity occupations all showed significant inverse associations with PAEE independent of age, sex or residential area. Frequent consumption of fruits and vegetables was associated with higher PAEE. Data are regression coefficients, which represent the expected change in PAEE (kJ/kg/day) for a unit change in exposure. Estimates are adjusted for age, sex and residential area.
  • Session 3: Nick Wareham

    1. 1. Supporting and Undertaking International Public Health Research in NCD prevention Nick Wareham
    2. 2. Source: Global Diabetes Plan, IDF 2011
    3. 3. <ul><li>Training and capacity development </li></ul><ul><li>Supporting epidemiological research </li></ul><ul><li>Supporting public health research </li></ul>
    4. 4. <ul><li>Training and capacity development </li></ul><ul><li>Supporting epidemiological research </li></ul><ul><li>Supporting public health research </li></ul>
    5. 5. <ul><li>Cambridge Seminar on Epidemiology and Public Health aspects of Diabetes </li></ul><ul><li>Free, 2 week course, Residential with resident faculty </li></ul><ul><li>International with priority given to people from countries where training is difficult to obtain </li></ul><ul><li>People selected on the basis of capacity to make a difference once they return to their countries of origin </li></ul>
    6. 6. The 1 st Cambridge Seminar 1981 Harry Keen John Jarrett
    7. 7. The 11 th Cambridge Seminar, 2011
    8. 8. Regional linked seminars Cambridge Seminar in Hangzhou, China 2010
    9. 9. <ul><li>Training and capacity development </li></ul><ul><li>Supporting epidemiological research </li></ul><ul><li>Supporting public health research </li></ul>
    10. 11. Source: The International Expert Committee. Diabetes Care 2009
    11. 12. The IDF Diabetes Atlas 5 th Edition A summary of the figures and key findings
    12. 13. Prevalence of diabetes, 2011
    13. 14. The global burden <ul><li>366 million people have diabetes in 2011; by 2030 this will have risen to 552 million </li></ul><ul><li>The number of people with type 2 diabetes is increasing in every country </li></ul><ul><li>80% of people with diabetes live in low-and middle-income countries </li></ul><ul><li>The greatest number of people with diabetes are between 40 to 59 years of age </li></ul><ul><li>183 million people (50%) with diabetes are undiagnosed </li></ul><ul><li>Diabetes caused 4.6 million deaths in 2011 </li></ul><ul><li>Diabetes caused at least USD 465 billion dollars in healthcare expenditures in 2011; 11% of total healthcare expenditures in adults (20-79 years) </li></ul><ul><li>78,000 children develop type 1 diabetes every year </li></ul>
    14. 15. WHO multinational study International collaboration for study on disease outcomes Source: Fuller et al, Diabetologia 2001
    15. 16. <ul><li>Training and capacity development </li></ul><ul><li>Supporting epidemiological research </li></ul><ul><li>Supporting public health research </li></ul>
    16. 17. Source: Gillies et al, BMJ 2007 Meta-analysis of RCTs
    17. 18. <ul><ul><ul><li>Percentage progression to diabetes by successful achievement of intervention targets </li></ul></ul></ul>Success score % 0 5 10 15 20 25 30 35 40 45 50 0 1 2 3 4 5 Intervention Control
    18. 19. <ul><li>Rate of developing diabetes according to the number of diabetes healthy behaviour goals met </li></ul>χ² test for trend p <0.001 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 Number of diabetes healthy behaviour goals met Diabetes incidence rate/1000 p-yrs Source: Simmons et al, Diabetologia 2006
    19. 20. Shift the whole population distribution of risk factor <ul><li>Focus on high risk individuals </li></ul><ul><li>Low impact on population attributable risk (PAR) or preventable fraction </li></ul><ul><li>Ineffective public health strategy </li></ul>
    20. 21. <ul><li>Aim: to develop effective public health interventions for population level change in dietary and physical activity behaviour </li></ul><ul><li>CEDAR Partnership: </li></ul><ul><ul><li>Medical Research Council Units, University of East Anglia, University of Cambridge </li></ul></ul><ul><ul><li>Erpho – East of England Public Health Observatory </li></ul></ul>
    21. 22. The Indian Diabetes Prevention Programmes Prof A Ramachandran Source: Ramachandran et al, Diabetologia 2006
    22. 23. MRC-ICMR initiative Chennai-Imperial-Cambridge Evaluation of a scaleable and feasible mass intervention to promote lifestyle changes
    23. 24. Professor Jean-Claude Mbanya President IDF
    24. 25. Diabetes prevalence in Africa Source: Mbanya et al, Lancet 2010
    25. 27. Felix Assah Attendee Cambridge Seminar MPhil in Epidemiology PhD in Epidemiology Wellcome Trust Clinical Fellow “ The Cambridge sequence … has been invaluable in providing an Introduction to NCD research and then going further to provide expert level training over a five year period. I am ready to give back to my society the knowledge and skills acquired through hands-on training of students and junior researchers.”
    26. 29. Rural Area in Cameroon Mbankomo
    27. 30. Rural lifestyle
    28. 31. Urban Area in Cameroon Biyem-Assi, Yaounde
    29. 32. Urban lifestyle
    30. 33. Objectives <ul><li>To objectively quantify physical activity levels in an urban and a rural population in Cameroon </li></ul><ul><li>To describe patterns of activities in these populations </li></ul><ul><li>to examine possible correlates of physical activity levels. </li></ul>
    31. 34. Population distribution of physical activity energy expenditure (PAEE) Assah FK et al, Diabetes Care 2011
    32. 35. Activity and Clustered Metabolic Risk in Cameroon Rural and urban differences in 552 adults p<0.001 for trend Source: Assah et al, Diabetes Care 2011
    33. 36. Domains of Physical Activity in Rural and Urban dwellers Assah FK et al, Unpublished, 2010
    34. 37. Seasonal trends of physical activity Dark bars = Rural Light bars = Urban
    35. 38. Seasonal trends of physical activity Dark bars = Rural Light bars = Urban
    36. 39. Some correlates of physical activity PAEE (kJ/kg/day) Rural (N=271) Urban ( N= 317) Correlates β SE p value β SE p value Demographic and anthropometric BMI (kg/m 2 ) -1.53 0.33 <0.001 -1.0 0.21 <0.001 Normal -- -- Overweight -11.11 3.41 0.001 -4.50 2.60 0.09 Obese -17.15 4.78 <0.001 -11.52 2.69 <0.001 Related lifestyle behaviours Smoking 0.57 5.70 0.9 12.77 3.81 0.001 Alcohol drinking 5.05 3.56 0.2 4.84 2.56 0.06 Fruits and vegetables <3 times/week -- -- 3 – 6 times/week 9.19 3.35 0.007 4.34 2.23 0.05 >=7 times/week 11.53 3.98 0.004 8.28 3.23 0.01 School duration (years) -0.55 0.35 0.1 -0.98 0.19 <0.001
    37. 40. <ul><li>Training and capacity development </li></ul><ul><li>- sustainable support for integrated programme of training and capacity building at different levels </li></ul><ul><li>Supporting epidemiological research </li></ul><ul><li>Supporting public health research </li></ul><ul><li>- focus on building global capacity to undertake translational public health research for NCD prevention </li></ul>

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