CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013
Socio-cultural, environmental and behavioural
determinants of obesity in black South African women
LISA K MICKLESFIELD, ESTELLE V LAMBERT, DAVID JOHN HUME, SARAH CHANTLER, PAULA R PIENAAR,
KASHA DICKIE, THANDI PUOANE, JULIA H GOEDECKE
South Africa (SA) is undergoing a rapid epidemiological
transition and has the highest prevalence of obesity in sub-
Saharan Africa (SSA), with black women being the most
affected (obesity prevalence 31.8%). Although genetic factors
are important, socio-cultural, environmental and behaviour-
al factors, as well as the influence of socio-economic status,
more likely explain the high prevalence of obesity in black
SA women. This review examines these determinants in black
SA women, and compares them to their white counterparts,
black SA men, and where appropriate, to women from SSA.
Specifically this review focuses on environmental factors
influencing obesity, the influence of urbanisation, as well
as the interaction with socio-cultural and socio-economic
factors. In addition, the role of maternal and early life factors
and cultural aspects relating to body image are discussed.
This information can be used to guide public health interven-
tions aimed at reducing obesity in black SA women.
Keywords: South Africa, obesity, food security, diet, physical
activity, body image, socio-economic status
Submitted 12/6/13, accepted 12/9/13
Cardiovasc J Afr 2013; 24: online publication www.cvja.co.za
Prevalence of obesity
According to the World Health Organisation (WHO), obesity
is a global epidemic that affects 500 million people worldwide,
and is predicted to increase to one billion people by 2030.1 The
rising prevalence of obesity is associated with an increased risk
of non-communicable diseases (NCDs), such as cardiovascular
disease, type 2 diabetes and several types of cancer.2
Until recently, Africa has been spared from this epidemic as
it grappled with under-nutrition, as well as infectious diseases
such as HIV and tuberculosis. However, over the last century the
continent has seen a rapid rise in the prevalence of overweight
and obesity, and their associated co-morbidities.3-5 This dual
burden of disease in Africa is particularly devastating as it is
compounded by the metabolic consequences of the roll out of
anti-retroviral medications in certain countries.6,7
Within sub-Saharan Africa (SSA), the prevalence of obesity
differs widely from as low as 1% in Ethiopia8 to as high as 27%
in South Africa (SA).9 Only three other countries in SSA report
a national obesity prevalence of over 20%, including Mauritania
(23.3%),10 Swaziland (23.1%)11 and Gabon (21.5%).10
In SA, statistics from the 1998 National Demographic and
Health survey (SADHS) reported an obesity prevalence of
30% in all women over the age of 15 years, which is more than
three times higher than the prevalence in men (7.5%).12 Those
most affected were black women, with a prevalence of 31.8%,
compared to 6% in black men, 22.7% in white women, 21.1% in
Indian women and 26.3% in women of mixed ancestry.
The most recent SADHS undertaken in 20039 reported that the
prevalence of obesity remains high in black women (28.5%). Of
concern is the large increase in the prevalence of obesity among
black SA adolescent girls,13 who will soon be entering adulthood
and will therefore be at increased risk for future NCDs.
For the purposes of this review, we attempted to outline the
socio-cultural, environmental and behavioural determinants of
obesity in black SA women, and compare them to their white
counterparts, black SA men, and where appropriate, to women
from SSA. The literature included in this review was selected
from the available literature to highlight the magnitude and
complexity of the determinants of obesity in this population
Definitions of race, ethnicity and culture
To contextualise this review, it is necessary to consider our
definitions of race, ethnicity and culture, and the potential
interactions between these constructs, particularly within the
MRC/Wits Developmental Pathways for Health Research
Unit, Department of Paediatrics, Faculty of Health Sciences,
University of the Witwatersrand, Johannesburg, South Africa
LISA K MICKLESFIELD, PhD, email@example.com
UCT/MRC Research Unit for Exercise Science and Sports
Medicine, Department of Human Biology, UCT School of
Health Sciences, University of Cape Town, South Africa
LISA K MICKLESFIELD, PhD
ESTELLE V LAMBERT, PhD
DAVID JOHN HUME, BSc (Med) (Hons)
SARAH CHANTLER, BSc (Med) (Hons)
PAULA R PIENAAR, BSc (Med) (Hons)
KASHA DICKIE, MSc (Med)
JULIA H GOEDECKE
School of Public Health, University of the Western Cape,
THANDI PUOANE, PhD
South African Medical Research Council, Parow, South Africa
JULIA H GOEDECKE, PhD
CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013
SA context where there are the potentially confounding effects
of socio-economic status. Race has been defined by Williams
et al.14 as ‘a complex multidimensional construct reflecting
the confluence of biological factors and geographical origins,
culture, economic, political, and legal factors, as well as racism’.
In a recent commentary,15 it was suggested that race and
ethnicity share a similar definition, however, the difference
between the two constructs lies in the fact that ethnicity is usually
defined by the group itself, whereas race is typically defined
by others outside ‘the group’. Culture, on the other hand, has
been defined as ‘the learned and shared beliefs, values, and life
ways of a designated or particular group which are generally
transmitted inter-generationally and influences one’s thinking and
action modes’.15 For demographic and restitution purposes, the
Government currently classifies race into black (ethnic Africans),
white (Europeans, Jews and Middle Easterners), coloured or
mixed ancestry (mixed race) and Indian (South Asian).
Socio-economic status and education
Historically, black South Africans have been compromised in
terms of education, access to healthcare and earning capacity
under apartheid laws. This is still currently reflected in the
2008/2009 South African Living Conditions of Household
Survey (LCS),16 in which it was demonstrated that 25% of black
households fell within the lowest quintile of annual household
consumption expenditure compared to 0.7% of white households,
whereas 81% of white households fell within the highest quintile
compared to 8.2% of black households. Differences in obesity
and disease prevalence between these ethnic groups may be
partly attributed to or mediated by these social inequalities.17
Studies in developed countries have shown an inverse
relationship between socio-economic status and obesity,18,19
however studies in SA,12,20-22 as well as other SSA countries23-26
show a consistent positive association between obesity and
socio-economic status. In these studies, obesity was positively
associated with access to clean water and electricity,21,25 reduced
housing density,22,25 as well as more money spent on food,27
higher energy intake,25 commuting by taxi/vehicle28 and reduced
physical activity or increased sedentary behaviour,22,28-31 factors
representing a transition towards a more Western lifestyle.
In addition, in many black African communities, obesity or
overweight may still be considered a sign of good health
and beauty, as well as affluence,32,33 further impacting on the
relationship between socio-economic status and obesity.
On the other hand, level of education, although highly related
to socio-economic status has been shown to be independently
associated with obesity in SA and other SSA countries. Studies
in many SSA countries,23,24,27 as well as regions in SA with lower
socio-economic status,21 have shown a positive association
between level of education and obesity.
By contrast, results from the SADHS suggest that the
relationship between education and obesity is not linear, as
women with no education and women with a tertiary education
had a lower body mass index (BMI) than those with some
schooling.12 This may reflect the wider distribution of both
education and socio-economic status in SA, which has recently
been re-classified as a middle-income country,1 and which has
one of the highest GINI coefficients in the world, suggesting
extreme inequality with regard to poverty and wealth.34
Studies in SA12,20,21,35 and other SSA countries23,25,26,28,29 have
consistently reported that the prevalence of obesity is greater in
women than men. Case and Menendez,20 using data collected
from an informal urban settlement in SA, identified two factors
to explain the gender difference in obesity rates in their study:
(1) being nutritionally deprived as children; and (2) having a
higher socio-economic status. These factors were associated with
obesity in women, but not in men.
Traditionally, black SA households are strongly patriarchal,
with men holding a dominant position. For this reason, boys
have been better cared for and nourished as babies and infants, so
they do not necessarily experience the same level of nutritional
deprivation at a young age as girls.36 However, due to migrant
labour and high death rates related to HIV/AIDS among young
adults, nearly half of all households in SA are headed by
women.37 These households are among the poorest and most
marginalised.16 In 2009, more than 20% of female-headed
households reported experiencing hunger (skipping meals or
running out of money) compared to only 15% of male-headed
Rural and urban black SA communities have historically faced
very different public health challenges, with infectious diseases
associated with under-nutrition prevalent in rural communities,
and a rising prevalence of NCDs associated with over-nutrition
in urban-dwelling communities.30 This rural–urban gradient is
still present in most SSA countries,30 but in SA, the disparities
between rural and urban settings are attenuated. The 2003
SADHS reported a 21% prevalence of obesity in rural black SA
women compared to 31% in urban black SA women.
Urbanisation is accompanied by the adoption of a Westernised
lifestyle, however in SA many cultural beliefs around lifestyle
behaviours and body image are retained.36 Differences in diet
have been identified as one of the possible causes of urban–
rural differences in obesity prevalence,39 and the term ‘nutrition
Fig. 1. A schematic representation of the inter-relation-
ships between the socio-cultural, behavioural and envi-
ronmental determinants of obesity in black South African
women discussed in this review.
and early life
CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013
transition’ is now commonly used to refer to changes in the diet
that occur with urbanisation.
Recent data also suggest however that the nutrition transition
is occurring within rural areas, possibly explaining the increasing
prevalence of obesity in less developed settings.40-42 Another
major contributing factor to the high prevalence of obesity in
urban versus rural communities in SA and SSA is the increase in
physical inactivity and the adoption of a more sedentary lifestyle
Maternal and early life factors
Nutrient deprivation and the timing thereof during the intra-
uterine period leads to foetal programming, resulting in genetic
and epigenetic adaptations.44,45 These biological adaptations
predispose an individual to obesity when exposed later in life
to an environment abundant with energy-dense and/or high-fat
foods, as is currently experienced in middle-income countries
such as SA.46
The prevalence of low birth weight (< 2.5 kg), very often
the consequence of nutrient deprivation in utero, is 15% in SA,
which is marginally higher than the overall prevalence of 13%
in SSA.47 The COHORTS initiative, a study of birth cohorts in
five low- or middle-income countries including SA, has shown
that size at birth is linked to major features of the metabolic
syndrome in adulthood, including obesity.48,49 However the
relationship between pre-natal exposure and obesity in later life
has been shown to fit a U-shaped curve. More specifically, low
birth weight has been associated with increased levels of adult
abdominal adiposity, while high birth weight was associated with
overall adult adiposity.50,51
High birth weight has been shown to be a result of excessive
maternal body weight or excessive weight gain during
pregnancy.52,53 This is of concern in SA, given the high prevalence
of obesity in SA adolescents and adult women. It is compounded
further by healthcare inequalities, associated perceptions of the
healthcare system, and the periodic lack of adequate resources
that have led to late or poor attendance rates at antenatal clinics.54,55
Under-nutrition during the first six months of life increases
the risk of stunting. Global statistics indicate that in SSA, the
prevalence of stunting under the age of five years is 39%, with
stunting rates ranging from 27% in Ghana to 55% in Niger,
and SA reporting a stunting prevalence of 24%.47 In transitional
societies of SSA, stunting and adolescent obesity may co-exist in
the same geographic population.56
A cross-sectional growth survey conducted in rural SA
children and adolescents aged one to 20 years showed that
an estimated one in five children aged one to four years was
stunted. Concurrently, the prevalence of combined overweight/
obesity was 20–25% among girls in late adolescence.56 Steyn et
al. showed that stunting in children under the age of nine years
resulted in a 1.8-fold increased risk of obesity.57 Moreover, other
evidence suggests that individuals who were stunted as children
were more likely to be overweight as adults.58 Furthermore,
excessive weight gain during childhood was associated with
adult body composition.59
Physical activity may be defined as any bodily movement
produced by skeletal muscle that requires energy expenditure.60
Prior to the early 2000s, the evidence base for physical activity
and health in SSA was limited, fragmented and localised,
with few nationally representative samples. Self-report physical
activity questionnaires were not standardised, often not validated
in the populations in which they were being applied, and the
focus was primarily on energy balance and seasonal agriculture-
related physical activity and under-nutrition.
Recent WHO Stepwise surveillance initiatives, using
a common instrument called the Global Physical Activity
Questionnaire (GPAQ), have yielded a growing body of evidence
on the global trends in physical activity and inactivity.61 The
physical activity recommendations for health in adults are
defined as engaging in at least 150 minutes of moderate-intensity
activity per week, or 75 minutes of vigorous-intensity activity
per week, or an equivalent combination of moderate- and
vigorous-intensity activity.62 Physical inactivity has been defined
as ‘doing no or very little at work, at home, for transport or
during discretionary time’.63
In the African region, estimates of the prevalence of inactivity
are widely varying, ranging from as low as 3.8 and 1.5% in
women and men in the Comoros, to 15 and 9% in Ghanaian
women and men, and 48 and 45% in SA women and men,
respectively.61,63,64 The highest reported prevalences of inactivity
in this region are similar in magnitude to those seen in North
America, and higher than those reported in South America,
Western Pacific or Asia.10
It appears that the inactivity gradient and obesity seem to be
related to development within the region and within the country.
An ecological evaluation of inactivity in women and men in 13
SSA countries demonstrated a significant correlation between
gross national income (per capita) and prevalence of self-
Sobngwi et al.66 studied over 1 600 Cameroonian adults living
in either rural or urban settings and found that lowered the odds
for overweight and obesity in a dose-dependent manner, and that
the odds for overweight and obesity, as well as impaired glucose
tolerance, were significantly increased with increased lifetime
exposure to an urban environment (percentage of life in a city).
Conversely, in SA, results from the THUSA study showed
that among a group of black adult women, physical inactivity
was a stronger correlate of obesity than socio-economic status
and dietary factors.31 As physical activity has been identified
as playing a key role in influencing health outcomes, even in
communities undergoing epidemiological transition, trends in
physical activity behaviour have implications for public health
and the emerging burden of NCDs in the region.
Armstrong and Bull67 highlighted that in developing countries,
‘occupational-, domestic- and transport-related activities may
contribute more to overall energy expenditure than leisure-time
or recreational activity’, and therefore a multi-domain approach
to the measurement of physical activity is essential. A recent
study including data from 22 African countries showed a higher
proportion of adult men compared to women (84 vs 76%) meeting
the global physical activity recommendations.64 Although levels
of physical activity varied greatly across these countries and
population sub-groups, the study found that leisure time activity
(5%) was consistently low, irrespective of gender, whereas work
activity (moderate and vigorous combined) contributed the most
(49%) to total physical activity time, followed by transport-
related activity (46%).64
CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013
In SA, 25–37% of adults are sufficiently active,63 and data
from the 2003 SADHS has shown that half the population
are insufficiently active.9 Moreover, the SA survey shows a
rural-to-urban gradient, with reduced physical activity levels
with increasing urbanisation. Moreover, increasing education
is associated with reduced occupational physical activity and
increased leisure activity. These findings are corroborated by
objective measurement in smaller regional studies in SSA,
which demonstrate similar physical activity trends, with adult
men being more physically active compared to adult women in
both urban and rural settings, and education level affecting the
domain of activity.68-70
Traditional methods for collecting physical activity by self-
report may over- or under-estimate actual levels.71 Moreover,
‘light activity’ is overlooked entirely. This is despite the fact that
urban-dwelling persons in low- or middle-income countries such
as SA are likely to spend a relatively large portion of their day
in at least light activity, as opposed to being entirely sedentary
(Kroff, pers commun, 2012). Importantly, work by Cook et al.43
has demonstrated that even light activity (accumulated steps
per day) is associated with a reduced risk for obesity in a dose-
dependent manner. Adjusting for age, motor vehicle access,
education, tobacco use and co-morbidities, and BMI was 1.4 kg/
m2 lower per 5 000 steps/day, and compared to being sedentary,
the risk of obesity (BMI ≥ 30 kg/m2) was 52% lower for 10 000
In countries such as SA, factors such as culture, socio-
economic status and the built environment may act as barriers
to physical activity. For example, in a convenience sample of
largely urban-dwelling South Africans, self-reported leisure-
time moderate to vigorous physical activity was significantly
higher in those persons living in neighbourhoods in which crime
was not perceived to be a problem. These results are supported
by recent work from Nigeria where they showed that perceived
safety, aesthetics and cleanliness were inversely associated with
obesity and positively associated with physical activity.72
However, in SA communities, walking for transport has still
been shown to be higher in persons from communities in which
there are no pavements (Lambert, Tshabangu and Naidoo, pers
commun, 2012), suggesting that many behaviours are outside
of an individuals own volition. Cultural barriers to physical
activity in black SA women include the acceptability of wearing
tight-fitting clothing when participating in sport, as well as the
perception that participating in leisure-time physical activity
takes time away from household chores.73
Diet and eating behaviour
Dietary intake and quality have been shown to be associated
with the prevalence and risk of obesity.74 Obesogenic dietary
behaviours include a high-energy intake, high dietary fat and sugar
intake, low-fibre fruit and vegetable intake, or a combination of
the above. Several of these dietary habits and behaviours are
associated with the adoption of a more Western lifestyle and
represent the nutrition transition in developing countries.
When compared to other SSA countries, SA is considered to
be further along the nutrition transition, characterised by higher
intakes of dietary energy (600 kCal above the mean for 39 other
SSA countries) and fat intake (24.5% vs sample mean of 18.9%),
as well as higher levels of obesity than other countries.46 In a
study of Kenyan and SA women, Steyn et al.75 showed that the
rural environment differed between countries, with more than
60% of rural Kenyan women having access to land, which was
associated with a higher nutrient mean adequacy ratio, dietary
diversity score and food variety score than rural SA women.
This finding highlights the difference in the effect of the rural–
urban environment of different populations along the nutrition
In SA, data from the 2003 SADHS showed an increase
in dietary quality with urbanisation, as characterised by an
improvement in micronutrient intake (micronutrient score based
on tertiles of the RDA).9 In contrast, Oldewage-Theron et al.76
reported that nutrient quality was poor in peri-urban black SA
women, with low food variety and diversity scores attributed
to low household food security and availability. Consistent
within all of these SA studies, including the THUSA study,39
urbanisation was associated with an increase in dietary fat intake,
which corresponded to the increased prevalence of obesity in
urban compared to rural women.
Most black South Africans who urbanise do so into informal
settlements that may not be situated close to any of the large food
chains that offer a greater variety and quality of food. The most
convenient place to purchase food is from informal vendors who
sell inexpensive and less varied foods of poor quality. Indeed,
data from a study in SA children showed that the lack of grocery-
style shops and many accessible tuck shops and street vendors
is shaping new buying habits of children that include a higher
intake of less nutritious foods.77
For example, a study of adolescents in the same cohort
reported the frequent purchase of the ‘quarter’, a combination
of white bread, polony, fried chips and cheese, as a meal.78 The
‘quarter’ is of good economical value based on the cost/kCal,
but is low in fibre and micronutrient quality. Temple et al. have
shown that a healthy diet is more expensive than a less healthy
diet, and therefore is not affordable for the majority of South
Socio-economic status is another important factor that
influences dietary quality and food choices. Increased wealth
and disposable income contribute to food choices and are
associated with the aspiration to consume more meat products,
bigger portion sizes, and a more frequent intake of fast foods.73
Conversely, low household food security is associated with poor
dietary quality, characterised by low food variety and diversity
Household food security may be described as a continuum,
from food secure, food insufficiency (some concern regarding
having enough funds to buy food for the month, without
changing diet), low food security (typically reducing the quality
of the diet), to food insecure (where there is a reduced food
intake and skipping meals).81 Notably, mothers who are food
insecure are more likely to be overweight or obese than men and
women without children, and food-insecure fathers.
Martin and Lippert81 showed that this is not as a result of
biological changes that occur with pregnancy, but rather may
be the adoption of strategies, albeit unhealthy, to protect their
children when faced with food insecurity. Furthermore, single
mothers appear to be at greater risk for food insecurity and
obesity, compared to women with partners. However, once
households are truly food insecure, women are more likely to be
CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013
In low-income countries in SSA, children of overweight
mothers are often underweight,82 which differs from the situation
in SA in which children of overweight mothers are more likely
to be overweight.83 The notion that food insecurity is implicated
in adult obesity is paradoxical, but may be explained by the
consumption of energy-dense foods of low nutritional value.
Cross-sectional studies have revealed that, unlike the vast majority
of women who favour the lean, Westernised archetype, there is
a preference for a larger body size among black SA women.32
This ideal stems from a cluster of culture-bound beliefs, which
promote lifestyle behaviours commonly associated with obesity.
International research has consistently shown that, after
controlling for age, education, socio-economic status and body
weight, men, irrespective of ethnicity, and black women display
the lowest degrees of body size dissatisfaction compared to other
ethnic groups.84-87 Furthermore, results from the SADHS confirm
that black women were more likely to under-estimate their body
size compared to women of other ethnic groups.12 In addition
to black SA families showing a greater tolerance for increased
body size,33 strong mother–daughter resemblances have been
identified for numerous body image constructs, including body
size ideals and perceptions of body size dissatisfaction.88
Socialisation moulds the body image of these women
throughout all life stages, and may explain why this ideal is
so well maintained from early childhood into adulthood. For
instance, young girls are encouraged to be plump, with weight
gain prior to marriage indicative of fertility and the ability to
bear children.89 In addition, while men are socialised to do hard
labour, girls are expected to perform light labour, which may
provide limited motivation for a leaner body since activities of
this nature do not necessitate high levels of physical aptitude.90
Similarly, low physical activity is due to the belief that
physical activity is associated with weight loss, as well as
sub-optimal environmental conditions such as a high crime rate
and overcrowding.12,32 Notably, similar attitudes toward weight
control have been found among black women in rural areas,
where it was shown that most overweight and obese women did
not desire weight loss.91
Ethnic body size preferences have been shown to govern how
individuals respond to insults such as disease and sexual abuse.
For example, a widely held belief among black SA women is
that large people are happy and healthy, whereas those who are
slender are perceived to experience personal problems and that
they may have diseases such as HIV/AIDS.92
Furthermore, Goedecke et al.93 demonstrated that ethnicity
altered the relationship between childhood sexual abuse and
obesity. In this small study, white women who were sexually
abused as children were more likely to be obese as adults. As
obesity is viewed as less attractive, this has been suggested
to protect against future sexual advances/abuses. By contrast,
black women who were sexually abused as children were more
likely to be lean, which was suggested as a means of protecting
themselves from further abuse. Furthermore, other studies have
reported that large women are respected, dignified and cannot be
The influence of family and community also alters body
size and satisfaction. For example, once a woman marries, she
is encouraged to gain weight as this signifies her husband’s
ability to support her financially.32 In addition, the mother of
the household is expected to be an authoritative figure capable
of commanding respect from her children.36 This, combined
with the expectation by black SA communities that people in
positions of power should be big, promotes the adoption of
higher degrees of tolerance for an increased body size. Puoane
et al.32 conducted a study on SA community health workers, who
are respected and important members of the community and
who play an important role in assisting with the communication
between the community and the formal health sector, and found
that 95% were overweight or obese.
Given that media influences extend further into disadvantaged
areas as the economy improves, black SA women are increasingly
exposed to conflicting body size ideals. Future studies should
therefore monitor the effect of such influences on body size
There is compelling evidence that the prevalence of obesity is
increasing in SSA, and that this increase is linked to urbanisation,
economic development and concomitant lifestyle risk factors,
such as physical inactivity and poor dietary practices. In addition,
there are a number of paradoxes that have emerged, including the
positive association between food insecurity and obesity, the
non-linear association between education and obesity, as well
as the distinct differences between patterns and determinants of
obesity in men and women in the region.
Although this was not a systematic review, which may be
considered a limitation, this review highlights the complexity
of various socio-cultural, environmental and behavioural factors
associated with obesity in black SA women. Public health
interventions targeted at individual behavioural risk factors,
although important, may have limited success in reducing
obesity if other contributing factors such as culture, environment
and socio-economic status are not considered.
1. The prevalence of obesity is increasing in SSA, and is linked
to urbanisation, economic development, and concomitant
lifestyle risk factors, such as physical inactivity and poor
2. Socio-cultural, environmental and behavioural factors, as
well as the influence of socio-economic status, contribute
significantly to the high prevalence of obesity in black SA
3. Barriers to physical activity in black SA women include
culture, socio-economic status and the built environment.
4. Food insecurity and dietary quality contribute to the preva-
lence of obesity in SA.
1. WHO. World Health Statistics 2008. US Patent Office, 2008.
2. Dalal S, Beunza JJ, Volmink J, Adebamowo C, Bajunirwe F, Njelekela
M, et al. Non-communicable diseases in sub-Saharan Africa: what we
know now. Int J Epidemiol 2011; 40: 885–901.
3. Ziraba AK, Fotso JC, Ochako R. Overweight and obesity in urban
Africa: A problem of the rich or the poor? BMC Public Health 2009;
4. Abubakari AR, Lauder W, Agyemang C, Jones M, Kirk A, Bhopal RS.
CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013
Prevalence and time trends in obesity among adult West African popu-
lations: a meta-analysis. Obes Rev 2008; 9: 297–311.
Mayosi BM, Flisher AJ, Lalloo UG, Sitas F, Tollman SM, Bradshaw
D. The burden of non-communicable diseases in South Africa. Lancet
2009; 374: 934–947.
De Wit S, Sabin CA, Weber R, Worm SW, Reiss P, Cazanave C, et
al. Incidence and risk factors for new-onset diabetes in HIV-infected
patients: the Data Collection on Adverse Events of Anti-HIV Drugs
(D:A:D) study. Diabetes Care 2008; 31: 1224–1229.
Dave JA, Lambert EV , Badri M, West S, Maartens G, Levitt NS. Effect
of nonnucleoside reverse transcriptase inhibitor-based antiretrovi-
ral therapy on dysglycemia and insulin sensitivity in South African
HIV-infected patients. J Acquir Immun Defic Syndr 2011; 57: 284–289.
Central Statistical Agency [Ethiopia] and ICF International. 2012.
Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia
and Calverton, Maryland, USA: Central Statistical Agency and ICF
SADHS. South Africa Demographic and Health Survey 2003.
10. Global status report on NCDs. Global status report on NCDs 2010.
2011 Jul 15: 1–176. http://www.who.int/nmh/publications/ncd_report_
11. Central Statistical Office (CSO) [Swaziland], and Macro International
Inc. 2008. Swaziland Demographic and Health Survey 2006-07.
Mbabane, Swaziland: Central Statistical Office and Macro International
12. Puoane T, Steyn K, Bradshaw D, Laubscher R, Fourie J, Lambert V , et
al. Obesity in South Africa: the South African demographic and health
survey. Obesity 2002; 10: 1038–1048.
13. Reddy SP, Resnicow K, James S, Funani IN, Kambaran NS, Omardien
RG, et al. Rapid increases in overweight and obesity among South
African adolescents: comparison of data from the South African
National Youth Risk Behaviour Survey in 2002 and 2008. Am J Public
Health 2012; 102: 262–268.
14. Williams DR. Race and health: basic questions, emerging directions.
Ann Epidemiol 1997; 7: 322–333.
15. DeAngelis T. A fresh look at race and ethnicity. Monitor Psychol 2008;
16. Living Conditions of Households in South Africa 2008/2009,
Statistics South Africa. http://www.statssa.gov.za/publications/P0310/
17. Myer L, Ehrlich RI, Susser ES. Social epidemiology in South Africa.
Epidemiol Rev 2004; 26: 112–123.
18. McLaren L. Socioeconomic status and obesity. Epidemiol Rev 2007;
19. Roskam AJR, Kunst AE, Van Oyen H, Demarest S, Klumbiene J,
Regidor E, et al. Comparative appraisal of educational inequalities in
overweight and obesity among adults in 19 European countries. Int J
Epidemiol 2010; 39: 392–404.
20. Case A, Menendez A. Sex differences in obesity rates in poor countries:
Evidence from South Africa. Econ Hum Biol 2009; 7: 271–282.
21. Mfenyana K, Griffin M, Yogeswaran P, Modell B, Modell M, Chandia
J, et al. Socio-economic inequalities as a predictor of health in South
Africa – the Yenza cross-sectional study. S Afr Med J 2006; 96:
22. Kruger HS, Venter CS, Vorster HH. Obesity in African women in the
North West Province, South Africa is associated with an increased risk
of non-communicable diseases: the THUSA study. Transition and Health
during Urbanisation of South Africans. Br J Nutr 2001; 86: 733–740.
23. Letamo G. The prevalence of, and factors associated with, overweight
and obesity in Botswana. J Biosoc Sci 2011; 43: 75–84.
24. Dake FA, Tawiah EO, Badasu DM. Sociodemographic correlates
of obesity among Ghanaian women. Public Health Nutr 2010; 14:
25. Steyn NP, Nel JH, Parker WA, Ayah R, Mbithe D. Dietary, social, and
environmental determinants of obesity in Kenyan women. Scand J of
Public Health 2011; 39: 88–97.
26. Olatunbosun ST, Kaufman JS, Bella AF. Prevalence of obesity and over-
weight in urban adult Nigerians. Obes Rev 2010; 12: 233–241.
27. Villamor E, Msamanga G, Urassa W, Petraro P, Spiegelman D, Hunter
DJ, et al. Trends in obesity, underweight, and wasting among women
attending prenatal clinics in urban Tanzania, 1995-2004. Am J Clin Nutr
2006; 83: 1387–1394.
28. Baalwa J, Byarugaba BB, Kabagambe EK, Kabagambe KE, Otim AM.
Prevalence of overweight and obesity in young adults in Uganda. Afr
Health Sci 2010; 10: 367–373.
29. Shayo GA, Mugusi FM. Prevalence of obesity and associated risk
factors among adults in Kinondoni municipal district, Dar es Salaam
Tanzania. BMC Public Health 2011; 11: 365–376.
30. Delisle H, Ntandou-Bouzitou G, Agueh V , Sodjinou R, Fayomi B.
Urbanisation, nutrition transition and cardiometabolic risk: the Benin
study. Br J Nutr 2012; 107: 1534–1544.
31. Kruger HS, Venter CS, Vorster HH, Margetts BM. Physical inactiv-
ity is the major determinant of obesity in black women in the North
West Province, South Africa: the THUSA study. Transition and Health
During Urbanisation of South Africa. Nutrition 2002; 18: 422–427.
32. Puoane T, Fourie JM, Shapiro M, Rosling L, Tshaka NC, Oelefse A.
“Big is beautiful” – an exploration with urban black community health
workers in a South African township. S Afr J Clin Nutr 2005; 18: 6–15.
33. Mvo Z, Dick J, Steyn K. Perceptions of overweight African women
about acceptable body size of women and children. Curationis 1999;
34. The World Bank. 2012 Available from: http://data.worldbank.org/indi-
35. Kruger A, Wissing MP, Towers GW, Doak CM. Sex differences inde-
pendent of other psycho-sociodemographic factors as a predictor of
body mass index in black South African adults. J Health Popul Nutr
2012; 30: 56–65.
36. Puoane T, Mciza Z. Socio-cultural and environmental factors related to
obesity in black Africans: A perspective from South Africa. In: Sinha R,
Kapoor S, eds. Obesity: A Multidimensional Approach to Contemporary
Global Issue. New Delhi: Dhanraj Book House; 2009: 91–98.
37. Bank L. Matrifocality, patriarchy and globalisation: changing family
forms in a South African city. In: Gonzalez AM, Oloo F, DeRose L, eds.
Frontiers of Globalization: Kinship and Family Structures in Africa.
Trenton: Africa World Press, 2008.
38. Jacobs P. Food insecurity among female-headed households, rapid
food price inflation and the economic downturn In South Africa.
Available from: http://www.iese.ac.mz/lib/publication/III_Conf2012/
39. Vorster HH, Venter CS, Wissing MP, Margetts BM. The nutrition and
health transition in the North West Province of South Africa: a review
of the THUSA (Transition and Health during Urbanisation of South
Africans) study. Public Health Nutr 2005; 8: 480–490.
40. Keding GB, Msuya JM, Maass BL, Krawinkel MB. Dietary patterns
and nutritional health of women: the nutrition transition in rural
Tanzania. Food Nutr Bull 2011; 32: 218–226.
41. Fezeu LK, Assah FK, Balkau B, Mbanya DS, Kengne A-P, Awah PK, et
al. Ten-year Changes in Central Obesity and BMI in Rural and Urban
Cameroon. Obesity 2008; 16: 1144–1147.
42. Bourne LT, Lambert EV , Steyn K. Where does the black population
of South Africa stand on the nutrition transition? Public Health Nutr
2002; 5: 157–162.
43. Cook I, Alberts M, Lambert EV . Relationship between adiposity and
pedometer-assessed ambulatory activity in adult, rural African women.
Int J Obes 2008; 32: 1327–1330.
44. Roseboom TJ, van der Meulen JH, Ravelli AC, Osmond C, Barker DJ,
Bleker OP. Effects of prenatal exposure to the Dutch famine on adult
disease in later life: an overview. Mol Cell Endocrinol 2001; 185: 93–98.
45. Josefson MD J. Metabolic programming of obesity in utero: is there
sufficient evidence to explain increased obesity rates? J Devel Orig
Health Dis 2012; 3: 70–72.
46. Abrahams Z, Mchiza Z, Steyn NP. Diet and mortality rates in sub-
Saharan Africa: Stages in the nutrition transition. BMC Public Health
2011; 11: 801–812.
47. World Health Organization. World Health Statistics 2012.
48. Yajnik CS. Nutrition, growth, and body size in relation to insulin resist-
ance and type 2 diabetes. Curr Diab Rep 2003; 3: 108–114.
49. Norris SA, Osmond C, Gigante D, Kuzawa CW, Ramakrishnan L,
CARDIOVASCULAR JOURNAL OF AFRICA • Advance Online Publication, September 2013 Download full-text
Lee NR, et al. Size at birth, weight gain in infancy and childhood, and
adult diabetes risk in five low- or middle-income country birth cohorts.
Diabetes Care 2012; 35: 72–79.
50. Oken E, Gillman MW. Fetal origins of obesity. Obes Res 2003; 11:
51. Ali AT, Crowther NJ. Factors predisposing to obesity: a review of the
literature. SA Family Practice 2010; 52: 193–197.
52. Ludwig DS, Currie J. The association between pregnancy weight
gain and birthweight: a within-family comparison. Lancet 2010; 376:
53. Lawlor DA, Lichtenstein P, Fraser A, Langstrom N. Does maternal
weight gain in pregnancy have long-term effects on offspring adiposity?
A sibling study in a prospective cohort of 146,894 men from 136,050
families. Am J Clin Nutr 2011; 94: 142–148.
54. Pretorius CFC, Greeff MM. Health-service utilization by pregnant
women in the greater Mafikeng-Mmabatho district. Curationis 2004;
55. Myer L, Harrison A. Why do women seek antenatal care late?
Perspectives from rural South Africa. J Midwifery Wom Heal 2003; 48:
56. Kimani-Murage EW, Kahn K, Pettifor JM, Tollman SM, Dunger DB,
Gómez-Olivé XF, et al. The prevalence of stunting, overweight and
obesity, and metabolic disease risk in rural South African children.
BMC Public Health 2010; 10: 158-170.
57. Steyn NP, Labadarios D, Maunder E, Nel J, Lombard C. Secondary
anthropometric data analysis of the National Food Consumption Survey
in South Africa: The double burden. Nutrition 2005; 21: 4–13.
58. Sawaya AL, Roberts S. Stunting and future risk of obesity: principal
physiological mechanisms. Cad Saude Publica 2003; 19: S21–8.
59. Kuzawa CW, Hallal PC, Adair L, Bhargava SK, Fall CHD, Lee N, et
al. Birth weight, postnatal weight gain, and adult body composition in
five low and middle income countries. Am J Hum Biol 2012; 24: 5–13.
60. World Health Organization. The World Health Report 2002: Reducing
Risks, Promoting Healthy Life (World Health Reports).
61. Guthold R, Ono T, Strong KL, Chatterji S, Morabia A. Worldwide
Variability in Physical Inactivity. Am J Prev Med 2008; 34: 486–494.
62. WHO. WHO Global Recommendations on Physical Activity for
Health. 2010 Nov 17: 1–60. http://whqlibdoc.who.int/publications/
63. Joubert J, Norman R, Lambert EV , Groenewald P, Schneider M, Bull F,
et al. Estimating the burden of disease attributable to physical inactivity
in South Africa in 2000. S Afr Med J 2007; 97: 725–731.
64. Guthold R, Louazani SA, Riley LM, Cowan MJ, Bovet P, Damasceno
A, et al. Physical Activity in 22 African Countries. Am J Prev Med
2011; 41: 52–60.
65. Lambert EV . Physical activity and obesity in Africa: Can we prevent
or reduce the growing burden of non-communicable disease? 10th
International Conference on Obesity. Sydney, 2006.
66. Sobngwi E. Exposure over the life course to an urban environment and
its relation with obesity, diabetes, and hypertension in rural and urban
Cameroon. Int J Epidemiol 2004; 33: 769–776.
67. Armstrong T, Bull F. Development of the World Health Organization
Global Physical Activity Questionnaire (GPAQ). J Public Health 2006;
68. Cook II, Alberts MM, Brits JSJ, Choma SRS, Mkhonto SSS. Descriptive
epidemiology of ambulatory activity in rural, black South Africans.
Med Sci Sport Exer 2010; 42: 1261–1268.
69. Assah FK, Ekelund U, Brage S, Mbanya JC, Wareham NJ. Urbanization,
physical activity, and metabolic health in sub-Saharan Africa. Diabetes
Care 2011; 34: 491–496.
70. Christensen DL, Faurholt-Jepsen D, Boit MK, Mwaniki DL, Kilonzo
B, Tetens I, et al. Cardiorespiratory fitness and physical activity in Luo,
Kamba, and Maasai of rural Kenya. Am J Hum Biol 2012; 24: 723–729.
71. Prince SA, Adamo KB, Hamel M, Hardt J, Connor Gorber S, Tremblay
M. A comparison of direct versus self-report measures for assessing
physical activity in adults: a systematic review. Int J Behav Nutr Phys
Act 2008; 5: 56–79.
72. Oyeyemi AL, Adegoke BO, Oyeyemi AY, Deforche B, De Bourdeaudhuij
I, Sallis JF. Environmental factors associated with overweight among
adults in Nigeria. Int J Behav Nutr Phys Act 2012; 9: 32–40.
73. Puoane T, Matwa P, Bradley H, Hughes GD. Socio-cultural factors
influencing food consumption patterns in the black African population
in an urban township in South Africa. Hum Ecol (special issue) 2006;
74. Boggs DA, Palmer JR, Spiegelman D, Stampfer MJ, Adams-Campbell
LL, Rosenberg L. Dietary patterns and 14-y weight gain in African
American women. Am J Clin Nutr 2011; 94: 86–94.
75. Steyn NP, Nel JH, Parker W, Ayah R, Mbithe D. Urbanisation and the
nutrition transition: A comparison of diet and weight status of South
African and Kenyan women. Scan J Public Health 2012; 40: 229–238.
76. Oldewage-Theron W, Kruger R. Dietary diversity and adequacy of
women caregivers in a peri-urban informal settlement in South Africa.
Nutrition 2011; 27: 420–427.
77. Pedro TM, MacKeown JM, Norris SA. Variety and total number of
food items recorded by a true longitudinal group of urban black South
African children at five interceptions between 1995 and 2003: the
Birth-to-Twenty (Bt20) Study. Public Health Nutr 2008; 11: 616–623.
78. Feeley A, Pettifor J, Norris S. Fast-food consumption among 17-year-
olds in the Birth to Twenty cohort [electronic resource]. S Afr J Clin
Nutr 2009; 22: 118–123.
79. Temple NJ, Steyn NP. The cost of a healthy diet: A South African
perspective. Nutrition 2011; 27: 505–508.
80. Oldewage-Theron W. Nutrition knowledge and nutritional status of
primary school children in QwaQwa. S Afr J Clin Nutr 2010; 23:
81. Martin MA, Lippert AM. Feeding her children, but risking her health:
The intersection of gender, household food insecurity and obesity. Soc
Sci Med 2012; 74: 1754–1764.
82. Garrett J, Ruel MT. The coexistence of child undernutrition and mater-
nal overweight: prevalence, hypotheses, and programme and policy
implications. Matern Child Nutr 2005; 1: 185–196.
83. Steyn NP, Labadarios D, Nel J, Kruger HS, Maunder EMW. What is
the nutritional status of children of obese mothers in South Africa?
Nutrition 2011; 27: 904–911.
84. Fitzgibbon MLM, Blackman LRL, Avellone MEM. The relationship
between body image discrepancy and body mass index across ethnic
groups. Obesity 2000; 8: 582–589.
85. Cachelin FMF, Rebeck RMR, Chung GHG, Pelayo EE. Does ethnicity
influence body-size preference? A comparison of body image and body
size. Obesity 2002; 10: 158–166.
86. Paeratakul S, White MA, Williamson DA, Ryan DH, Bray GA. Sex,
race/ethnicity, socioeconomic status, and BMI in relation to self-
perception of overweight. Obesity 2002; 10: 345–350.
87. Sanchez-Johnsen LAPS, Fitzgibbon ML, Martinovich Z, Stolley
MR, Dyer AR, Van Horn L. Ethnic Differences in correlates of
obesity between Latin-American and black Women. Obesity 2004; 12:
88. Mchiza ZJ, Goedecke JH, Lambert EV . Intra-familial and ethnic effects
on attitudinal and perceptual body image: a cohort of South African
mother-daughter dyads. BMC Public Health 2011; 11: 433–440.
89. Salamon H, Juhasz E. Goddesses of flesh and metal: Gazes on the
tradition of fattening Jewish brides in Tunisia. J Middle East Women’s
Studies 2011; 7: 1–38.
90. Feinstein S, Feinstein R, Sabrow S. Gender Inequality in the Division
of Household Labour in Tanzania. Afr Sociolog Rev/Revue Africaine de
Sociologie 2010; 14: 98–109.
91. Faber M, Kruger HS. Dietary intake, perceptions regarding body
weight, and attitudes toward weight control of normal weight, over-
weight, and obese Black females in a rural village in South Africa.
Ethnic Dis 2005; 15: 238–245.
92. Matoti-Mvalo T, Puoane TB. Perceptions of body size and its associa-
tion with HIV/AIDS. S Afr J Clin Nutr 2011; 24: 40–45.
93. Goedecke JH, Forbes J, Stein D. Differences in the association between
childhood trauma and obesity in black and white South African women.
Afr J Psychiatry 2013; 16: 201–205.
94. Puoane T, Tsolekile L, Steyn N. Perceptions about body image and
sizes among black African girls living in Cape Town. Ethnic Dis 2010;