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Urbanization, Wealth and Overweight in Sub-Saharan Africa

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Title: Main presentation title goes here. Author: Lynsey Allen Last modified by: Madise N.J. Created Date: 7/17/2008 9:55:46 AM Document presentation format – PowerPoint PPT presentation

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Title: Urbanization, Wealth and Overweight in Sub-Saharan Africa


1
Urbanization, Wealth and Overweight in
Sub-Saharan Africa
  • Nyovani Madise Gobopamang Letamo University
    of Botswana
  • 12th June 2014. Population Health Conference,
    Southampton

2
Rationale
  • Increasing prevalence of overweight and obesity
    globally
  • Africa is no exception- levels particularly high
    among women ages 20 years (31) compared with
    23 among males.
  • Overweight/obesity risk factor for many
    non-communicable diseases
  • Estimated 3 million premature deaths per year
    dues to NCDs
  • Urbanization is rising. By 2030, 50 will be
    urban
  • Growing middle-class

3
The Nutrition Transition
  • Popkin and Gordon Larsen (2004) describe 5
    patterns
  • Collecting Food
  • Famine
  • Receding famine
  • Nutrition-related NCDs
  • Behavioural Change
  • Patterns not restricted to time periods
  • Links with epidemiological demographic
    transitions

4
Our Assumptions
  • Household wealth strongly associated with the
    risk of being overweight or obese
  • Risk is higher among urban than rural women,
    except where national prevalence is very high
  • The most affluent women in urban areas may be the
    first to adopt behaviour change towards healthier
    diets and exercise.

5
By far the largest problem is under-nutrition
among young childrenPercentage of under 5
children who were stunted
Country Early 2000s Post 2005
Burundi 63 58
Madagascar 48 50
Malawi 48 48
Ethiopia 58 44
6
Data
  • Nationally representative surveys from 30
    countries in sub-Saharan Africa conducted between
    2006 and 2012
  • Demographic and Health Survey programme
  • In total 208,656 women 15-49 years
  • Individual country sample sizes range
    2,960-26,500
  • Mean age 28.8 years (SD9.8)
  • Mean children ever born 2.84
  • 33 had no formal education 4 had tertiary
    education

7
Methods
  • Individual country-level logistic regression
    analyses
  • Dependent variable BMI gt25
  • Key variables urban/rural residence, wealth
    status and their interaction
  • Also controlled for age, highest education,
    religion, region of residence, marital status
  • Excluded those pregnant and given birth in the 4
    months before surveys
  • Identified three groups of countries based on
    interaction between wealth status and urban/rural
    residence

8
Methods
  • Pooled data according to three groups
  • Used macro-level variables to explain patterns
  • Gross National Income per capita (PPP constant
    2005, international )
  • Life Expectancy at birth
  • Population living in urban areas
  • Percent under-five who are stunted.
  • Overall percent of all adult women
    overweight/obese

9
Results
10
Source of data WHO Global Health Observatory.
11
(No Transcript)
12
Group 1 Traditional African PatternLow
national income (median1149), Medium
Urbanization (36), Low life expectancy (57
years) Lower female overweight/obesity (25)
Benin, Burkina Faso, Burundi, Cameroon, Ethiopia,
Democratic Republic of Congo, Congo Brazzaville,
Guinea, Senegal, Sierra Leone, Uganda
13
Group 2 Urban/Rural Cross-OverLower-middle
income (median 1416) High urbanization (43)
Medium life expectancy (62 years) High female
overweight/obesity (32)
Botswana, Namibia, Tanzania, Zambia, Kenya,
Gabon, Ghana, Madagascar, Niger, Liberia
14
Group 3 Universally High Overweight/ObesityMidd
le income (median 1881) Low urbanization (28)
Low level of life expectancy 56 years- HIV
effectVery high levels of female
overweight/obesity (43)
SADC countries Lesotho, Swaziland, Mozambique,
Zimbabwe. Plus Rwanda
15
Prevalence of overweight/obesity by age of woman
and Group Type
16
Concluding Remarks
  • Prevalence of overweight and obesity in Africa
    31 over 70 in North Africa (e.g. Egypt) and
    South Africa
  • Urban residents and wealthiest most at risk BUT
    cross-over towards overweight/obesity among rural
    residents
  • Some regions e.g. southern Africa affected by HIV
  • Body size preferences linked to HIV fears
  • Still high child malnutrition levels

17
Acknowledgment
  • STARND EDULINK partners (Universities of
    Botswana,, Malawi, Namibia, the Witwatersrand,
    Zambia, Eduardo Mondlane, Lesotho)
  • ACP EDULINK Grant Contract 2008/197619.

18
(No Transcript)
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