Literature DB >> 33293748

Transitions between body mass index categories, South Africa.

Muchiri E Wandai1, Jens Aagaard-Hansen2, Samuel Om Manda3, Shane A Norris1.   

Abstract

OBJECTIVE: To profile the prevalence of the three body mass index (BMI) categories by sociodemographic characteristics, and to calculate the percentage transitioning (or not) from one BMI category to another, to inform South African health policy for the control of obesity and noncommunicable diseases.
METHODS: We used data from the National Income Dynamics Study, including sociodemographic characteristics and BMI measurements collected in 2008, 2010, 2012, 2014 and 2017. For each data collection wave and each population group, we calculated mean BMI and prevalence by category. We also calculated the percentage making an upwards transition (e.g. from overweight to obese), a downwards transition or remaining within a particular category. We used a multinomial logistic regression model to estimate transition likelihood.
FINDINGS: Between 2008 and 2017, mean BMI increased by 2.3 kg/m2. We calculated an increased prevalence of obesity from 19.7% (3686/18 679) to 23.6% (3412/14 463), with the largest increases in prevalence for those aged 19-24 years and those with at least high school education. The percentages of upwards transitions to overweight or obese categories increased sharply between the ages of 19 and 50 years. Once overweight or obese, the likelihood of transitioning to a normal BMI is low, particularly for women, those of higher age groups, and those with a higher income and a higher level of education.
CONCLUSION: In the development of national strategies to control obesity and noncommunicable diseases, our results will allow limited public health resources to be focused on the relevant population groups. (c) 2020 The authors; licensee World Health Organization.

Entities:  

Mesh:

Year:  2020        PMID: 33293748      PMCID: PMC7716104          DOI: 10.2471/BLT.20.255703

Source DB:  PubMed          Journal:  Bull World Health Organ        ISSN: 0042-9686            Impact factor:   9.408


Introduction

The mean body mass index (BMI) of the African population is increasing, resulting in a steady rise of the prevalence of people being overweight or obese across Africa, with the southern part of Africa being most affected., In 2016, the prevalence of the population aged ≥ 15 years being overweight or obese in South Africa was 68% for women and 31% for men. Global efforts to combat obesity include the World Health Organization (WHO) Global strategy on diet, physical activity and health, the Global action plan for the prevention and control of noncommunicable diseases 2013–2020 and the United Nations (UN) High-level meetings of the General Assembly on prevention and control of non-communicable diseases., The Global action plan proposes the promotion of healthy diets by Member States to halt the rise in the prevalence of school children, adolescents and adults being overweight or obese. Similarly, the 2011 Sixty-sixth session of the UN Political Declaration of the High-level Meeting of the General Assembly on the Prevention and Control of Non-communicable Diseases committed to strengthening national policies and health systems by promoting multisectoral and multistakeholder engagement to reverse, stop and decrease the rising trends of obesity in child, youth and adult populations. In line with global strategies and policies, the South African Department of Health developed the Strategic plan for the prevention and control of non-communicable diseases 2013–2017 and the Strategy for the prevention and control of obesity in South Africa 2015–2020; the targets of these strategic plans were to reduce obesity prevalence by 3% by 2017 and by 10% by 2020 in all age groups. These two strategic plans are aligned with the agenda of the country’s 2030 National development plan for the promotion of healthy diets and physical activity at schools, workplaces and in the general community. Promotion and support through research is an essential component of global and national strategies for prevention and control of obesity and noncommunicable diseases.,,, We anticipate that a better understanding of transitions between the BMI categories – normal, overweight and obese (Table 1) – will allow the improvement of interventions to reduce the prevalence of obesity. Our objectives are: (i) to profile the prevalence of the three BMI categories within a study population according to various sociodemographic characteristics, and to estimate the percentage of these population groups that underwent transitions (or not) between BMI categories; (ii) to identify the factors associated with transitions between BMI categories; and (iii) to discuss the key public health implications of our findings for national obesity control strategies.
Table 1

Body mass index categories for children and adults, according to WHO

BMI categoryz-BMI of children (≤ 18 years)BMI of adults (> 19 years) (kg/m2)
Normal> –2SD to ≤ 1SD≥ 18.5 to < 25
Overweight> 1SD to ≤ 2SD≥ 25 to < 30
Obese> 2SD≥ 30

BMI: body mass index; SD: standard deviation of mean BMI; WHO: World Health Organization; z-BMI: z score for BMI = (BMI – mean BMI)/SD.

BMI: body mass index; SD: standard deviation of mean BMI; WHO: World Health Organization; z-BMI: z score for BMI = (BMI – mean BMI)/SD.

Methods

Study population

The National Income Dynamics Study, first conducted in 2008, is a nationally representative panel study that collects information on a wide variety of social, demographic, economic and health characteristics of the civilian non-institutionalized population., We used data from the five completed waves of the panel survey (the subsequent four waves were conducted in 2010, 2012, 2014 and 2017) from participants for which anthropometric measurements had also been recorded. In the first wave in 2008, the survey recorded weight and height measurements for the calculation of BMI for 21 002 individuals; 2323 (11.1%) were immediately lost to follow-up. Of the remaining 2008 sample of 18 679 individuals for which at least a second BMI calculation was recorded, 13 298 (71.2%), 15 331 (82.1%), 15 623 (83.6%) and 14 463 (77.4%) are represented in the 2010, 2012, 2014 and 2017 waves, respectively.

Study variables

Our main study variable of interest is whether transition occurred from one BMI category to another during a particular period in time. This derived variable has seven possible outcomes: two downwards transitions (either from obese to overweight or from overweight to normal); two upwards transitions (either from normal to overweight or from overweight to obese); and three no-transition outcomes, when a person’s BMI category does not change from either normal, overweight or obese between two waves of the survey. If a population is experiencing a higher number of upwards than downwards transitions, the prevalence of adverse conditions will increase. Our independent time-invariant variables were sex and race, and baseline time-variant variables were age, whether urban or rural residence, education level, equivalized income level and frequency of physical exercise. To account for the economies of scale in household consumption, we used the equivalization method of the Organisation for Economic Co-operation and Development of dividing household income by the square root of the number of people within the household.

Statistical analysis

For each BMI category and for each of the five waves of data collection, we calculated both average BMI with 95% confidence intervals and prevalence. To visualize how prevalence varies with age, we calculated the prevalence of all three BMI categories for all ages and averaged over all five data collection waves (2008–2017). We also calculated the percentage within each population subgroup either transitioning to an upwards or downwards BMI category or remaining within the same category during the four periods between subsequent waves (i.e. ending in 2010, 2012, 2014 and 2017). We used a multinomial logistic regression to model the probability of transitioning (or not) from one BMI category to another, relative to the probability of remaining within the normal category. We performed all statistical analyses using Stata SE Version 15.0 (StataCorp, College Station, United States of America).

Results

Average BMI and prevalence

Between 2008 and 2017, mean BMI increased by 2.3 kg/m2, from 23.1 to 25.4 kg/m2. We observed that the age group 7–13 years experienced the highest increase (by 4.7 kg/m2), followed by the age groups 14–18 years (3.3 kg/m2) and 19–24 years (3.2 kg/m2; Table 2; available at: http://www.who.int/bulletin/volumes/98/12/20-255703). We note that the groups that demonstrated at least an average increase in mean BMI (i.e. ≥ 2.3 kg/m2) include women, Africans and Caucasians, rural dwellers, those with some education and those whose level of physical exercise was unknown. When examining the data by income, those with the lowest income demonstrated the largest increase in mean BMI (2.5 kg/m2). We also observed that women, those aged ≥ 25 years, Caucasians, urban dwellers, those with no formal schooling, those with a high school education or more, those within the highest-income tertile and those exercising < 3 times per week had an average BMI of > 25.0 kg/m2 for most, if not all, of the study period, contributing to the high prevalence of people being overweight and obese (Table 2).
Table 2

Mean body mass index and percentage of study population within each body mass index category by sociodemographic characteristics and data collection wave, South Africa, 2008–2017

Sociodemographic property/data collection wavenMean BMI, kg/m2 (95% CI)No. (%) within each category
NormalOverweightObese
Sex
Female
  200810 68724.8 (24.5–25.1)5 444 (50.9)2 374 (22.2)2 869 (26.8)
  20107 88726.3 (25.9–26.6)3 504 (44.4)1 881 (23.8)2 502 (31.7)
  20128 93626.4 (26.1–26.7)4 033 (45.1)2 270 (25.4)2 633 (29.5)
  20149 04027.3 (27.0–27.7)3 853 (42.6)2 154 (23.8)3 033 (33.6)
  20178 46127.9 (27.5–28.2)3 473 (41.0)2 057 (24.3)2 931 (34.6)
Male
  20087 99221.1 (20.8–21.3)5 885 (73.6)1 290 (16.1)817 (10.2)
  20105 41122.2 (21.9–22.6)3 737 (69.1)1 054 (19.5)620 (11.5)
  20126 39522.4 (22.0–22.7)4 539 (71.0)1 196 (18.7)660 (10.3)
  20146 58322.4 (22.1–22.7)4 985 (75.7)1 036 (15.7)562 (8.5)
  20176 00222.5 (22.2–22.7)4 552 (75.8)969 (16.1)481 (8.0)
Baseline age (years)
0–6
  20082 77016.8 (16.6–17.0)1 792 (64.7)544 (19.6)434 (15.7)
  20101 62716.7 (16.4–16.9)1 106 (68.0)275 (16.9)246 (15.1)
  20122 46817.0 (16.8–17.3)1 780 (72.1)387 (15.7)301 (12.2)
  20142 57117.9 (17.6–18.1)2 090 (81.3)321 (12.5)160 (6.2)
  20172 47919.2 (18.9–19.4)2 029 (81.8)314 (12.7)136 (5.5)
7–13
  20083 45817.8 (17.4–18.1)2 781 (80.4)378 (10.9)299 (8.6)
  20102 32719.8 (19.4–20.2)1 733 (74.5)359 (15.4)235 (10.1)
  20122 97320.7 (20.5–21.0)2 306 (77.6)485 (16.3)182 (6.1)
  20143 02621.8 (21.5–22.0)2 375 (78.5)459 (15.2)192 (6.3)
  20172 80722.5 (22.2–22.8)2 128 (75.8)442 (15.7)237 (8.4)
14–18
  20082 38421.5 (21.2–21.8)1 899 (79.7)329 (13.8)156 (6.5)
  20101 76123.1 (22.7–23.4)1 230 (69.8)358 (20.3)173 (9.8)
  20121 80323.7 (23.3–24.0)1 254 (69.6)368 (20.4)181 (10.0)
  20141 95324.2 (23.9–24.5)1 253 (64.2)387 (19.8)313 (16.0)
  20171 80324.8 (24.4–25.3)1 070 (59.3)392 (21.7)341 (18.9)
19–24
  20082 07923.5 (23.2–23.9)1 445 (69.5)407 (19.6)227 (10.9)
  20101 45524.6 (24.1–25.1)871 (59.9)334 (23.0)250 (17.2)
  20121 56325.5 (24.9–26.1)847 (54.2)395 (25.3)321 (20.5)
  20141 70326.2 (25.7–26.7)838 (49.2)431 (25.3)434 (25.5)
  20171 58126.7 (26.1–27.2)718 (45.4)414 (26.2)449 (28.4)
25–34
  20082 19925.8 (25.5–26.2)1 184 (53.8)536 (24.4)479 (21.8)
  20101 59726.4 (25.9–26.9)721 (45.1)430 (26.9)446 (27.9)
  20121 72126.9 (26.5–27.4)741 (43.1)493 (28.6)487 (28.3)
  20141 83127.6 (27.1–28.0)749 (40.9)458 (25.0)624 (34.1)
  20171 70527.4 (26.9–27.9)689 (40.4)425 (24.9)591 (34.7)
35–44
  20081 96627.7 (27.3–28.2)790 (40.2)495 (25.2)681 (34.6)
  20101 51428.4 (27.8–29.0)539 (35.6)387 (25.6)588 (38.8)
  20121 63428.6 (28.0–29.1)562 (34.4)425 (26.0)647 (39.6)
  20141 64728.8 (28.2–29.4)560 (34.0)376 (22.8)711 (43.2)
  20171 55628.7 (28.1–29.2)507 (32.6)379 (24.4)670 (43.1)
45–54
  20081 68728.8 (28.2–29.3)630 (37.3)400 (23.7)657 (38.9)
  20101 30529.3 (28.6–29.9)424 (32.5)330 (25.3)551 (42.2)
  20121 41529.4 (28.8–30.0)458 (32.4)378 (26.7)579 (40.9)
  20141 37029.6 (28.9–30.2)425 (31.0)343 (25.0)602 (43.9)
  20171 26029.5 (28.9–30.2)403 (32.0)320 (25.4)537 (42.6)
> 55
  20082 13628.4 (27.9–28.9)808 (37.8)575 (26.9)753 (35.3)
  20101 71228.4 (27.9–28.9)617 (36.0)462 (27.0)633 (37.0)
  20121 75428.0 (27.6–28.4)624 (35.6)535 (30.5)595 (33.9)
  20141 52228.1 (27.5–28.7)548 (36.0)415 (27.3)559 (36.7)
  20171 27228.0 (27.4–28.6)481 (37.8)340 (26.7)451 (35.5)
Race
African
  200815 62122.9 (22.6–23.1)9 592 (61.4)3 049 (19.5)2 980 (19.1)
  201011 53624.3 (24.0–24.6)6 262 (54.3)2 569 (22.3)2 705 (23.4)
  201212 94124.2 (24.0–24.5)7 312 (56.5)2 937 (22.7)2 692 (20.8)
  201413 22824.8 (24.5–25.0)7 581 (57.3)2 714 (20.5)2 933 (22.2)
  201712 31725.3 (25.0–25.5)6 945 (56.4)2 557 (20.8)2 815 (22.9)
Mixed ancestry
  20082 36024.0 (23.3–24.6)1 441 (61.1)405 (17.2)514 (21.8)
  20101 40024.4 (23.6–25.2)821 (58.6)254 (18.1)325 (23.2)
  20121 88724.9 (24.3–25.4)1 091 (57.8)356 (18.9)440 (23.3)
  20141 92325.4 (24.9–26.0)1 087 (56.5)332 (17.3)504 (26.2)
  20171 77025.8 (25.3–26.3)949 (53.6)348 (19.7)473 (26.7)
Asian
  200819923.4 (22.9–23.9)116 (58.3)46 (23.1)37 (18.6)
  201012823.8 (22.9–24.7)72 (56.3)31 (24.2)25 (19.5)
  201214125.5 (25.0–26.0)66 (46.8)45 (31.9)30 (21.3)
  201415224.4 (23.5–25.2)77 (50.7)42 (27.6)33 (21.7)
  201714524.0 (22.9–25.1)63 (43.4)49 (33.8)33 (22.8)
Caucasian
  200849925.7 (24.6–26.8)180 (36.1)164 (32.9)155 (31.1)
  201023426.9 (25.1–28.7)86 (36.8)81 (34.6)67 (28.6)
  201236227.8 (26.8–28.8)103 (28.5)128 (35.4)131 (36.2)
  201432028.2 (26.8–29.6)93 (29.1)102 (31.9)125 (39.1)
  201723128.3 (26.8–29.7)68 (29.4)72 (31.2)91 (39.4)
Residence
Rural
  200810 84922.2 (21.9–22.5)6 916 (63.7)2 060 (19.0)1 873 (17.3)
  20107 93723.8 (23.5–24.1)4 374 (55.1)1 791 (22.6)1 772 (22.3)
  20128 42023.6 (23.3–23.9)4 912 (58.3)1 916 (22.8)1 592 (18.9)
  20148 15224.2 (23.9–24.4)4 825 (59.2)1 646 (20.2)1 681 (20.6)
  20177 50124.7 (24.4–25.0)4 369 (58.2)1 546 (20.6)1 586 (21.1)
Urban
  20087 83024.0 (23.7–24.3)4 413 (56.4)1 604 (20.5)1 813 (23.2)
  20105 36125.1 (24.6–25.5)2 867 (53.5)1 144 (21.3)1 350 (25.2)
  20126 91125.3 (24.9–25.7)3 660 (53.0)1 550 (22.4)1 701 (24.6)
  20147 47125.7 (25.4–26.1)4 013 (53.7)1 544 (20.7)1 914 (25.6)
  20176 96225.8 (25.5–26.2)3 656 (52.5)1 480 (21.3)1 826 (26.2)
Education
None
  20081 76125.2 (24.8–25.6)921 (52.3)382 (21.7)458 (26.0)
  20101 39126.3 (25.8–26.7)638 (45.9)324 (23.3)429 (30.8)
  20121 43725.8 (25.4–26.1)687 (47.8)384 (26.7)366 (25.5)
  20141 34525.9 (25.5–26.2)672 (50.0)316 (23.5)357 (26.5)
  20171 16826.1 (25.7–26.5)583 (49.9)274 (23.5)311 (26.6)
Pre-school
  20082 60316.8 (16.6–16.9)1 666 (64.0)522 (20.1)415 (15.9)
  20101 50816.7 (16.5–16.9)1 020 (67.6)251 (16.6)237 (15.7)
  20122 32416.9 (16.8–17.1)1 677 (72.2)358 (15.4)289 (12.4)
  20142 41817.5 (17.4–17.7)1 969 (81.4)295 (12.2)154 (6.4)
  20172 33818.9 (18.7–19.0)1 919 (82.1)290 (12.4)129 (5.5)
Primary schoola
  200811 50423.0 (22.9–23.2)7 356 (63.9)2 043 (17.8)2 105 (18.3)
  20108 44124.6 (24.5–24.7)4 760 (56.4)1 823 (21.6)1 858 (22.0)
  20129 33524.8 (24.7–24.9)5 374 (57.6)2 057 (22.0)1 904 (20.4)
  20149 57325.4 (25.3–25.6)5 416 (56.6)1 953 (20.4)2 204 (23.0)
  20178 86425.9 (25.7–26.0)4 848 (54.7)1 884 (21.3)2 132 (24.1)
High school and above
  20082 81126.3 (26.1–26.6)1 386 (49.3)717 (25.5)708 (25.2)
  20101 95827.4 (27.1–27.6)823 (42.0)537 (27.4)598 (30.5)
  20122 23527.9 (27.6–28.2)834 (37.3)667 (29.8)734 (32.8)
  20142 28728.6 (28.3–28.9)781 (34.1)626 (27.4)880 (38.5)
  20172 09329.0 (28.7–29.3)675 (32.3)578 (27.6)840 (40.1)
Income level
Low
  200811 22022.1 (21.9–22.4)7 236 (64.5)2 055 (18.3)1 929 (17.2)
  20108 16223.7 (23.6–23.9)4 625 (56.7)1 771 (21.7)1 766 (21.6)
  20129 26423.4 (23.3–23.6)5 548 (59.9)2 019 (21.8)1 697 (18.3)
  20149 58224.0 (23.9–24.1)5 861 (61.2)1 858 (19.4)1 863 (19.4)
  20178 97424.6 (24.4–24.7)5 371 (59.9)1 770 (19.7)1 833 (20.4)
Middle
  20084 56423.5 (23.1–23.9)2 738 (60.0)868 (19.0)958 (21.0)
  20103 24324.6 (24.4–24.9)1 777 (54.8)683 (21.1)783 (24.1)
  20123 78024.6 (24.3–24.8)2 094 (55.4)809 (21.4)877 (23.2)
  20143 77625.1 (24.9–25.4)2 060 (54.6)757 (20.0)959 (25.4)
  20173 50125.5 (25.3–25.8)1 866 (53.3)745 (21.3)890 (25.4)
High
  20082 89525.0 (24.6–25.5)1 355 (46.8)741 (25.6)799 (27.6)
  20101 89326.1 (25.7–26.4)839 (44.3)481 (25.4)573 (30.3)
  20122 28726.5 (26.2–26.7)930 (40.7)638 (27.9)719 (31.4)
  20142 26527.0 (26.7–27.3)917 (40.5)575 (25.4)773 (34.1)
  20171 98827.5 (27.2–27.8)788 (39.6)511 (25.7)689 (34.7)
Physical exercise
< 3 times per week
  200810 45226.3 (26.0–26.5)5 342 (51.1)2 404 (23.0)2 706 (25.9)
  20107 95027.2 (27.0–27.3)3 521 (44.3)2 002 (25.2)2 427 (30.5)
  20128 31527.5 (27.3–27.6)3 503 (42.1)2 239 (26.9)2 573 (30.9)
  20148 44427.8 (27.7–28.0)3 440 (40.7)2 068 (24.5)2 936 (34.8)
  20177 74228.1 (27.9–28.3)3 056 (39.5)1 935 (25.0)2 751 (35.5)
≥ 3 times per week
  20081 46024.0 (23.5–24.6)981 (67.2)274 (18.8)205 (14.0)
  201098524.7 (24.3–25.0)591 (60.0)228 (23.1)166 (16.9)
  20121 13525.2 (24.9–25.5)646 (56.9)288 (25.4)201 (17.7)
  20141 14325.6 (25.2–25.9)623 (54.5)266 (23.3)254 (22.2)
  20171 04025.8 (25.4–26.1)550 (52.9)255 (24.5)235 (22.6)
Unknown
  20086 76717.6 (17.4–17.8)5 006 (74.0)986 (14.6)775 (11.5)
  20104 36319.0 (18.8–19.1)3 129 (71.7)705 (16.2)529 (12.1)
  20125 88119.3 (19.1–19.4)4 423 (75.2)939 (16.0)519 (8.8)
  20146 03620.2 (20.0–20.3)4 775 (79.1)856 (14.2)405 (6.7)
  20175 68121.2 (21.0–21.3)4 419 (77.8)836 (14.7)426 (7.5)
Total
200818 67923.1 (22.9–23.4)11 329 (60.7)3 664 (19.6)3 686 (19.7)
201013 29824.5 (24.2–24.7)7 241 (54.5)2 935 (22.1)3 122 (23.5)
201215 33124.6 (24.3–24.8)8 572 (55.9)3 466 (22.6)3 293 (21.5)
201415 62325.1 (24.8–25.3)8 838 (56.6)3 190 (20.4)3 595 (23.0)
201714 46325.4 (25.1–25.6)8 025 (55.5)3 026 (20.9)3 412 (23.6)

BMI: body mass index; CI: confidence interval.

a Includes those who may have started high school but dropped out before completing.

BMI: body mass index; CI: confidence interval. a Includes those who may have started high school but dropped out before completing. Our data show an increase in the prevalence of obesity from 19.7% (3686/18 679) in 2008 to 23.6% (3412/14 463) in 2017. In terms of age group, we observed the highest increase in the prevalence of obesity over this period in those aged 19–24 years from 10.9% (227/2079) to 28.4% (449/1581). In terms of education level, those with the most education (high school and above) demonstrated the largest increase in the prevalence of obesity from 25.2% (708/2811) to 40.1% (840/2093). The prevalence of people being overweight and obese was lowest for those aged around 11–18 years (Fig. 1). The prevalence of obesity increases steeply after this age up to around 50 years, when it reaches a plateau (Fig. 1). Between the ages of 40 and 70 years, the prevalence of obesity is higher than that of normal BMI.
Fig. 1

Prevalence of body mass index categories by age, South Africa

Prevalence of body mass index categories by age, South Africa Note: Data are averaged over the five waves (2008, 2010, 2012, 2014 and 2017) of the National Income Dynamics Study data collection.

Transitions between categories

We provide percentages of the study population groups who transitioned (or not) from one BMI category to another during the four periods ending 2010, 2012, 2014 and 2017 in Table 3 (available at: http://www.who.int/bulletin/volumes/98/12/20-255703). As the cohort for each risk factor aged throughout the study period, the percentages transitioning generally decreased as the percentages remaining within a particular BMI category increased. The exceptions to this general observation, that is, the groups that demonstrated decreasing percentages of retaining a normal BMI, included those of age 14–18 years (from 61.7%; 1086/1761 to 54.6%; 984/1803) and 19–24 years (from 51.6%; 751/1455 to 41.0%; 648/1581), Asians (from 51.6%; 66/128 to 38.6%; 56/145), individuals with at least a high school education (from 34.3%; 671/1958 to 28.1%; 589/2093) and those who reported physical exercise ≥ 3 times per week (from 53.0%; 522/985 to 48.6%; 505/1040). Within all these groups, our data show that the decreasing percentages of those retaining a normal BMI was accompanied by upwards transition percentages that were much higher than downwards transition percentages. For example, for the age group 19–24 years, the percentage transitioning upwards by 2010 (22.4%; (187+139)/1455) was more than double that of those transitioning downwards (10.1%; (100+47)/1455). The percentage of those retaining a normal BMI remained relatively constant throughout the study period for women (~35%) and for those aged > 35 years (~28%). At the end of every period, the percentage of those who retained a normal BMI was higher for those who exercised ≥ 3 times per week (e.g. for the period ending 2010, 53.0%; 522/985) compared with those who exercised < 3 times per week (e.g. for the period ending 2010, 36.1%; 2868/7950).
Table 3

Number and percentage of study population transitioning from one body mass index category to another (or not) by sociodemographic characteristics and year of end of transition period, South Africa, 2010–2017

Sociodemographic characteristic/end of transition periodnNo. (%)
Transitioned upwards
Transitioned downwards
Unchanged
Normal to overweightOverweight to obeseOverweight to normalObese to overweightNormalOverweightObese
Sex
Female
  20107 887750 (9.5)845 (10.7)526 (6.7)575 (7.3)2752 (34.9)782 (9.9)1657 (21.0)
  20128 936844 (9.4)790 (8.8)602 (6.7)826 (9.2)3097 (34.7)934 (10.5)1843 (20.6)
  20149 040775 (8.6)876 (9.7)546 (6.0)470 (5.2)3142 (34.8)1074 (11.9)2157 (23.9)
  20178 461521 (6.2)481 (5.7)382 (4.5)364 (4.3)3022 (35.7)1241 (14.7)2450 (29.0)
Male
  20105 411563 (10.4)390 (7.2)361 (6.7)285 (5.3)3201 (59.2)381 (7.0)230 (4.3)
  20126 395559 (8.7)362 (5.7)531 (8.3)441 (6.9)3725 (58.2)479 (7.5)298 (4.7)
  20146 583388 (5.9)227 (3.4)530 (8.1)359 (5.5)4224 (64.2)520 (7.9)335 (5.1)
  20176 002288 (4.8)142 (2.4)269 (4.5)164 (2.7)4232 (70.5)568 (9.5)339 (5.6)
Baseline age (years)
0–6
  20101 627128 (7.9)168 (10.3)189 (11.6)177 (10.9)806 (49.5)81 (5.0)78 (4.8)
  20122 468165 (6.7)223 (9.0)254 (10.3)309 (12.5)1333 (54.0)106 (4.3)78 (3.2)
  20142 571142 (5.5)92 (3.6)243 (9.5)247 (9.6)1668 (64.9)111 (4.3)68 (2.6)
  20172 479130 (5.2)62 (2.5)116 (4.7)80 (3.2)1868 (75.4)149 (6.0)74 (3.0)
7–13
  20102 327244 (10.5)178 (7.6)137 (5.9)130 (5.6)1501 (64.5)80 (3.4)57 (2.4)
  20122 973278 (9.4)117 (3.9)224 (7.5)227 (7.6)1914 (64.4)148 (5.0)65 (2.2)
  20143 026237 (7.8)114 (3.8)220 (7.3)125 (4.1)2068 (68.3)184 (6.1)78 (2.6)
  20172 807181 (6.4)109 (3.9)128 (4.6)50 (1.8)1984 (70.7)227 (8.1)128 (4.6)
14–18
  20101 761237 (13.5)128 (7.3)105 (6.0)68 (3.9)1086 (61.7)92 (5.2)45 (2.6)
  20121 803219 (12.1)102 (5.7)157 (8.7)90 (5.0)1043 (57.8)113 (6.3)79 (4.4)
  20141 953202 (10.3)188 (9.6)133 (6.8)63 (3.2)1095 (56.1)147 (7.5)125 (6.4)
  20171 803162 (9.0)112 (6.2)76 (4.2)46 (2.6)984 (54.6)194 (10.8)229 (12.7)
19–24
  20101 455187 (12.9)139 (9.6)100 (6.9)47 (3.2)751 (51.6)120 (8.2)111 (7.6)
  20121 563209 (13.4)144 (9.2)102 (6.5)78 (5.0)713 (45.6)140 (9.0)177 (11.3)
  20141 703190 (11.2)171 (10.0)107 (6.3)63 (3.7)708 (41.6)201 (11.8)263 (15.4)
  20171 581118 (7.5)97 (6.1)62 (3.9)50 (3.2)648 (41.0)254 (16.1)352 (22.3)
25–34
  20101 597186 (11.6)175 (11.0)97 (6.1)90 (5.6)590 (36.9)188 (11.8)271 (17.0)
  20121 721199 (11.6)165 (9.6)117 (6.8)113 (6.6)583 (33.9)222 (12.9)322 (18.7)
  20141 831148 (8.1)167 (9.1)116 (6.3)75 (4.1)612 (33.4)256 (14.0)457 (25.0)
  20171 70584 (4.9)85 (5.0)80 (4.7)70 (4.1)598 (35.1)282 (16.5)506 (29.7)
35–44
  20101 514121 (8.0)147 (9.7)84 (5.5)112 (7.4)423 (27.9)186 (12.3)441 (29.1)
  20121 634110 (6.7)156 (9.5)89 (5.4)123 (7.5)439 (26.9)226 (13.8)491 (30.0)
  20141 64791 (5.5)141 (8.6)82 (5.0)80 (4.9)458 (27.8)225 (13.7)570 (34.6)
  20171 55665 (4.2)64 (4.1)60 (3.9)77 (4.9)438 (28.1)246 (15.8)606 (38.9)
45–54
  20101 30592 (7.0)130 (10.0)64 (4.9)96 (7.4)334 (25.6)168 (12.9)421 (32.3)
  20121 41591 (6.4)111 (7.8)67 (4.7)130 (9.2)355 (25.1)193 (13.6)468 (33.1)
  20141 37068 (5.0)113 (8.2)66 (4.8)78 (5.7)343 (25.0)213 (15.5)489 (35.7)
  20171 26032 (2.5)48 (3.8)53 (4.2)64 (5.1)344 (27.3)230 (18.3)489 (38.8)
≥ 55
  20101 712118 (6.9)170 (9.9)111 (6.5)140 (8.2)462 (27.0)248 (14.5)463 (27.0)
  20121 754132 (7.5)134 (7.6)123 (7.0)197 (11.2)442 (25.2)265 (15.1)461 (26.3)
  20141 52285 (5.6)117 (7.7)109 (7.2)98 (6.4)414 (27.2)257 (16.9)442 (29.0)
  20171 27237 (2.9)46 (3.6)76 (6.0)91 (7.2)390 (30.7)227 (17.8)405 (31.8)
Race
African
  201011 5361192 (10.3)1134 (9.8)777 (6.7)764 (6.6)5129 (44.5)969 (8.4)1571 (13.6)
  201212 9411225 (9.5)981 (7.6)1033 (8.0)1130 (8.7)5709 (44.1)1152 (8.9)1711 (13.2)
  201413 2281021 (7.7)950 (7.2)971 (7.3)746 (5.6)6234 (47.1)1323 (10.0)1983 (15.0)
  201712 317696 (5.7)531 (4.3)583 (4.7)451 (3.7)6251 (50.8)1521 (12.3)2284 (18.5)
Mixed ancestry
  20101 40086 (6.1)78 (5.6)88 (6.3)71 (5.1)696 (49.7)134 (9.6)247 (17.6)
  20121 887130 (6.9)116 (6.1)77 (4.1)107 (5.7)975 (51.7)158 (8.4)324 (17.2)
  20141 923109 (5.7)122 (6.3)70 (3.6)56 (2.9)1001 (52.1)183 (9.5)382 (19.9)
  20171 77091 (5.1)76 (4.3)48 (2.7)63 (3.6)892 (50.4)203 (11.5)397 (22.4)
Asian
  201012810 (7.8)5 (3.9)5 (3.9)4 (3.1)66 (51.6)18 (14.1)20 (15.6)
  201214113 (9.2)8 (5.7)7 (5.0)5 (3.5)58 (41.1)28 (19.9)22 (15.6)
  201415213 (8.6)9 (5.9)11 (7.2)7 (4.6)65 (42.8)23 (15.1)24 (15.8)
  201714511 (7.6)7 (4.8)7 (4.8)6 (4.1)56 (38.6)32 (22.1)26 (17.9)
Caucasian
  201023425 (10.7)18 (7.7)17 (7.3)21 (9.0)62 (26.5)42 (17.9)49 (20.9)
  201236235 (9.7)47 (13.0)16 (4.4)25 (6.9)80 (22.1)75 (20.7)84 (23.2)
  201432020 (6.3)22 (6.9)24 (7.5)20 (6.3)66 (20.6)65 (20.3)103 (32.2)
  201723111 (4.8)9 (3.9)13 (5.6)8 (3.5)55 (23.8)53 (22.9)82 (35.5)
Residence
Rural
  20107 937882 (11.1)826 (10.4)536 (6.8)508 (6.4)3585 (45.2)654 (8.2)946 (11.9)
  20128 420801 (9.5)625 (7.4)711 (8.4)793 (9.4)3780 (44.9)743 (8.8)967 (11.5)
  20148 152609 (7.5)572 (7.0)639 (7.8)515 (6.3)3920 (48.1)788 (9.7)1109 (13.6)
  20177 501410 (5.5)289 (3.9)365 (4.9)283 (3.8)3929 (52.4)928 (12.4)1297 (17.3)
Urban
  20105 361431 (8.0)409 (7.6)351 (6.5)352 (6.6)2368 (44.2)509 (9.5)941 (17.6)
  20126 911602 (8.7)527 (7.6)422 (6.1)474 (6.9)3042 (44.0)670 (9.7)1174 (17.0)
  20147 471554 (7.4)531 (7.1)437 (5.8)314 (4.2)3446 (46.1)806 (10.8)1383 (18.5)
  20176 962399 (5.7)334 (4.8)286 (4.1)245 (3.5)3325 (47.8)881 (12.7)1492 (21.4)
Education
None
  20101 391115 (8.3)145 (10.4)84 (6.0)104 (7.5)506 (36.4)153 (11.0)284 (20.4)
  20121 437134 (9.3)105 (7.3)102 (7.1)156 (10.9)519 (36.1)160 (11.1)261 (18.2)
  20141 34590 (6.7)85 (6.3)107 (8.0)76 (5.7)543 (40.4)172 (12.8)272 (20.2)
  20171 16852 (4.5)36 (3.1)65 (5.6)53 (4.5)506 (43.3)181 (15.5)275 (23.5)
Pre-school
  20101 508116 (7.7)160 (10.6)181 (12.0)165 (10.9)735 (48.7)74 (4.9)77 (5.1)
  20122 324153 (6.6)212 (9.1)245 (10.5)295 (12.7)1247 (53.7)95 (4.1)77 (3.3)
  20142 418127 (5.3)87 (3.6)224 (9.3)238 (9.8)1571 (65.0)104 (4.3)67 (2.8)
  20172 338118 (5.0)59 (2.5)106 (4.5)78 (3.3)1768 (75.6)139 (5.9)70 (3.0)
Primary schoola
  20108 441868 (10.3)718 (8.5)505 (6.0)477 (5.7)4041 (47.9)692 (8.2)1140 (13.5)
  20129 335865 (9.3)617 (6.6)657 (7.0)671 (7.2)4389 (47.0)849 (9.1)1287 (13.8)
  20149 573753 (7.9)685 (7.2)631 (6.6)415 (4.3)4608 (48.1)962 (10.0)1519 (15.9)
  20178 864518 (5.8)402 (4.5)405 (4.6)317 (3.6)4391 (49.5)1101 (12.4)1730 (19.5)
High school and above
  20101 958214 (10.9)212 (10.8)117 (6.0)114 (5.8)671 (34.3)244 (12.5)386 (19.7)
  20122 235251 (11.2)218 (9.8)129 (5.8)145 (6.5)667 (29.8)309 (13.8)516 (23.1)
  20142 287193 (8.4)246 (10.8)114 (5.0)100 (4.4)644 (28.2)356 (15.6)634 (27.7)
  20172 093121 (5.8)126 (6.0)75 (3.6)80 (3.8)589 (28.1)388 (18.5)714 (34.1)
Income level
Low
  20108 162897 (11.0)803 (9.8)555 (6.8)529 (6.5)3798 (46.5)617 (7.6)963 (11.8)
  20129 264894 (9.7)647 (7.0)779 (8.4)811 (8.8)4330 (46.7)753 (8.1)1050 (11.3)
  20149 582733 (7.6)644 (6.7)747 (7.8)541 (5.6)4827 (50.4)871 (9.1)1219 (12.7)
  20178 974525 (5.9)373 (4.2)418 (4.7)298 (3.3)4876 (54.3)1024 (11.4)1460 (16.3)
Middle
  20103 243276 (8.5)254 (7.8)216 (6.7)187 (5.8)1486 (45.8)295 (9.1)529 (16.3)
  20123 780294 (7.8)297 (7.9)238 (6.3)289 (7.6)1734 (45.9)348 (9.2)580 (15.3)
  20143 776271 (7.2)266 (7.0)216 (5.7)174 (4.6)1769 (46.8)387 (10.2)693 (18.4)
  20173 501193 (5.5)140 (4.0)154 (4.4)148 (4.2)1673 (47.8)443 (12.7)750 (21.4)
High
  20101 893140 (7.4)178 (9.4)116 (6.1)144 (7.6)669 (35.3)251 (13.3)395 (20.9)
  20122 287215 (9.4)208 (9.1)116 (5.1)167 (7.3)758 (33.1)312 (13.6)511 (22.3)
  20142 265159 (7.0)193 (8.5)113 (5.0)114 (5.0)770 (34.0)336 (14.8)580 (25.6)
  20171 98891 (4.6)110 (5.5)79 (4.0)82 (4.1)705 (35.5)342 (17.2)579 (29.1)
Physical exercise
< 3 times per week
  20107 950769 (9.7)792 (10.0)487 (6.1)497 (6.3)2868 (36.1)902 (11.3)1635 (20.6)
  20128 315799 (9.6)724 (8.7)530 (6.4)648 (7.8)2754 (33.1)1011 (12.2)1849 (22.2)
  20148 444636 (7.5)784 (9.3)502 (5.9)412 (4.9)2823 (33.4)1135 (13.4)2152 (25.5)
  20177 742399 (5.2)387 (5.0)354 (4.6)349 (4.5)2653 (34.3)1236 (16.0)2364 (30.5)
≥ 3 times per week
  2010985125 (12.7)64 (6.5)51 (5.2)40 (4.1)522 (53.0)81 (8.2)102 (10.4)
  20121 135119 (10.5)73 (6.4)85 (7.5)57 (5.0)546 (48.1)127 (11.2)128 (11.3)
  20141 143102 (8.9)87 (7.6)75 (6.6)35 (3.1)536 (46.9)141 (12.3)167 (14.6)
  20171 04064 (6.2)47 (4.5)38 (3.7)38 (3.7)505 (48.6)160 (15.4)188 (18.1)
Unknown
  20104 363419 (9.6)379 (8.7)349 (8.0)323 (7.4)2563 (58.7)180 (4.1)150 (3.4)
  20125 881485 (8.2)355 (6.0)518 (8.8)562 (9.6)3522 (59.9)275 (4.7)164 (2.8)
  20146 036425 (7.0)232 (3.8)499 (8.3)382 (6.3)4007 (66.4)318 (5.3)173 (2.9)
  20175 681346 (6.1)189 (3.3)259 (4.6)141 (2.5)4096 (72.1)413 (7.3)237 (4.2)
Total
201013 2981313 (9.9)1235 (9.3)887 (6.7)860 (6.5)5953 (44.8)1163 (8.7)1887 (14.2)
201215 3311403 (9.2)1152 (7.5)1133 (7.4)1267 (8.3)6822 (44.5)1413 (9.2)2141 (14.0)
201415 6231163 (7.4)1103 (7.1)1076 (6.9)829 (5.3)7366 (47.1)1594 (10.2)2492 (16.0)
201714 463809 (5.6)623 (4.3)651 (4.5)528 (3.7)7254 (50.2)1809 (12.5)2789 (19.3)

a Includes those who may have started high school but dropped out before completing.

a Includes those who may have started high school but dropped out before completing.

Likelihood of transitions

The probability of transitioning upwards or downwards to another BMI category decreased with time, while the probability of remaining within the overweight or obese categories increased with time. The particular groups that demonstrated the largest probabilities of remaining within the overweight or obese categories, compared with other groups, also demonstrated the greatest likelihoods of transitioning either upwards or downwards. These groups included women, Caucasians, and those with at least a high school education and with a high income (Table 4).
Table 4

Probability of transitioning from one body mass index category to another (or not) by sociodemographic characteristics and year of end of transition period, South Africa, 2010–2017

Sociodemographic factor/year of end of transition periodOR (P) relative to that of retaining a normal BMI
Transition upwardsaTransition downwardsbRemain obese or overweight
End of transition period
20101.001.001.00
20120.93 (0.032)1.24 (0.000)1.13 (0.000)
20140.77 (0.000)0.93 (0.066)1.28 (0.000)
20170.50 (0.000)0.59 (0.000)1.56 (0.000)
Sex
Male1.001.001.00
Female2.56 (0.000)1.82 (0.000)4.81 (0.000)
Baseline age (years)
0–61.001.001.00
7–130.93 (0.565)0.72 (0.009)1.14 (0.435)
14–181.21 (0.196)0.71 (0.021)1.50 (0.028)
19–241.40 (0.029)0.81 (0.180)2.75 (0.000)
25–341.59 (0.003)1.19 (0.276)4.92 (0.000)
35–441.65 (0.001)1.54 (0.007)8.33 (0.000)
45–541.67 (0.001)1.75 (0.001)10.44 (0.000)
≥ 551.65 (0.001)2.17 (0.000)9.68 (0.000)
Race
African1.001.001.00
Mixed ancestry0.64 (0.000)0.54 (0.000)0.68 (0.000)
Asian0.68 (0.005)0.60 (0.001)0.71 (0.003)
Caucasian1.39 (0.002)1.26 (0.043)1.21 (0.037)
Residence
Rural1.001.001.00
Urban0.85 (0.000)0.92 (0.005)1.08 (0.002)
Education level
None1.001.001.00
Pre-school1.11 (0.448)1.50 (0.003)1.76 (0.001)
Primary schoolc1.16 (0.005)1.18 (0.002)1.50 (0.000)
High school and above1.69 (0.000)1.43 (0.000)2.27 (0.000)
Income level
Low1.001.001.00
Middle0.98 (0.623)0.94 (0.066)1.18 (0.000)
High1.46 (0.000)1.28 (0.000)2.06 (0.000)
Physical exercise
< 3 times per week1.001.001.00
≥ 3 times per week0.93 (0.160)0.86 (0.014)0.83 (0.000)
Unknown0.77 (0.001)0.91 (0.322)0.66 (0.000)

BMI: body mass index; OR: odds ratio.

a Transition from normal to overweight, or overweight to obese.

b Transition from obese to overweight, or overweight to normal.

c Includes those who may have started high school but dropped out before completing.

BMI: body mass index; OR: odds ratio. a Transition from normal to overweight, or overweight to obese. b Transition from obese to overweight, or overweight to normal. c Includes those who may have started high school but dropped out before completing. We note that the likelihood of either transitioning upwards or downwards, or of remaining within the overweight or obese categories, relative to that of retaining a normal BMI, increased with age. Our data show that women were 2.56 and 1.82 times more likely than men to transition upwards and downwards, respectively, and 4.81 times more likely than men to remain within the overweight or obese category. Men were therefore more likely to retain a normal BMI. We note that Caucasians were 1.39 and 1.26 times more likely than Africans to transition upwards and downwards, respectively, and 1.21 times more likely than Africans to remain within the overweight or obesity category. Those of mixed ancestry and Asians demonstrated a higher probability of retaining a normal BMI than Africans and Caucasians. Urban dwellers were slightly more likely (1.08 times) than rural dwellers to remain within the overweight or obese categories, but less likely to transition upwards or downwards. We observed that individuals with a high school education and greater were more likely than the other education-level groups to either transition upwards or downwards or to remain within the overweight or obese categories. Compared with those with a low or middle income, high-income groups were more likely to transition upwards or downwards and remain within the overweight or obese categories; high-income groups were therefore less likely to retain a normal BMI than lower-income groups. Those who exercised ≥ 3 times per week and those whose frequency of physical exercise was unknown (data were unavailable for those of age < 15 years) were less likely to remain within the overweight or obese categories, and therefore more likely to retain a normal BMI, compared with those who exercised < 3 times per week.

Discussion

Our data show a sharply rising prevalence of obesity coinciding with entry into adulthood in the community at large. We note that the prevalence of obesity increased by the greatest amount for the group aged 19–24 years between 2008 and 2017. This age group also reported the highest percentage of upwards transitions, as well as the largest difference between the percentage transitioning upwards and the percentage transitioning downwards. Although this age group had a normal-category mean BMI during the first two study periods, the subsequent sharp increase in BMI resulted in an increased prevalence of being overweight and obese with time. The South African Department of Health targeted a 3% reduction in the prevalence of obesity by 2017 for all age groups through diet and physical activity., To determine whether this target was achieved, we must compare data from different individuals of the same age at different times. However, by examining how BMI values change as a particular cohort ages, we were able to identify periods of increased obesity prevalence within a person’s lifetime during which interventions may be critical. Our data show that there exists a decreasing trend in prevalence of being overweight or obese from birth to the age of 18 years, when most children usually leave high school. As our results are not capable of attributing this downwards trajectory from birth to age 18 years to the effectiveness of national strategies for obesity prevention and control (our data were obtained from an observational study), further research is required. Guidance for healthy eating for the population aged ≤ 18 years is provided in South Africa by the Guidelines for early childhood development services,, and the National school nutrition programme annual report and Guidelines for tuck shop operators. The teaching of life skills in primary and high schools, which includes nutrition education, is aimed at educating students to make nutritious food choices and develop healthy eating habits. In averaging our data for all ages over the period 2008–2017, we found that the lowest combined prevalence of being overweight and obese was for those aged 7–18 years; the fact that prevalence rises steadily after this age highlights that, despite these strategies on controlling obesity, there remain substantial problems in communicating healthy food choices to children and adolescents. Other studies have also shown that these strategies are not functioning optimally.– A synthesis of studies conducted between 2006 and 2014 on the South African school food environment revealed that over half (from 51.1%; 1233/2412 to 69.3%; 330/476) of the students bought available and unhealthy foods from either tuck shops or vendors in their neighbourhood. The population of age 15–24 years has also been identified as the largest consumers of sugar-sweetened beverages. Low levels of physical activity, especially in female adolescents (aged 10–19 years) and in older teenagers (aged 16–18 years) of both sexes, could also be contributing to the existing prevalence of being overweight and obese. Physical activity policies include the Strategic plan 2009–2013: An active and winning nation, of which one of the aims was to facilitate the implementation of sports in schools. In the National sport and recreation plan, one of the objectives is to maximize access to sport, recreation and physical education in every school. Consolidated findings on the level of physical activity in children aged 3–19 years (e.g. early childhood physical activity, organized sport participation, active play and active transportation) showed an average participation of around 50%, although the percentage of those in early childhood (age 3–6 years) participating in physical activity was generally found to be high (~80%). Since pre-school children are naturally active, a physical activity intervention for this age group was only deemed necessary for promoting the engagement of teachers and parents or caregivers, and for outcomes such as cognitive development. The South African noncommunicable disease strategy targeted an increase in the prevalence of physical activity (150 minutes of moderate-intensity physical activity per week, or equivalent) by 10% by 2020, and the WHO global action plan for noncommunicable diseases targeted a 10% relative reduction in the prevalence of insufficient physical activity by 2020. Although our data do not allow a detailed analysis of types of physical activity, we demonstrated the importance of physical exercise. About half of those who exercised ≥ 3 times per week maintained a normal BMI even as the cohort aged. However, the fact that the proportion of this group who maintained a normal BMI decreased slightly over time may reflect decreasing levels of energy expenditure with age. Interventions that increase physical activity may therefore be necessary to reduce the large percentages of groups who remain either overweight or obese. Studies on obesity, especially in women, have identified obese participants who meet the WHO guidelines on physical activity but have very poor cardiorespiratory fitness, possibly attributable to a lack of high-intensity physical activity., Suggested interventions include encouraging participation in high-intensity activities, such as sports and aerobics, and discouraging sedentary behaviour. The recent introduction of higher tax on products such as sugar-sweetened beverages will probably reduce consumption and consequently reduce the percentages transitioning upwards. However, the life course approach, the basis of many WHO strategies and recommendations for disease prevention and control,, may be a better strategy for maintaining normal BMI from this age. The life course approach stresses the importance of early intervention by considering which stages, transitions and settings of a person’s life are critical for promoting or restoring health. For example, the workplace has been found to be an important setting for health promotion during adulthood. Effective interventions include the promotion of healthy food options in canteens, and the provision of nutrition education and counselling. Similar interventions in settings such as community centres, churches and recreational facilities should also be promoted. Barriers to leisure activity participation, including lack of time and facilities, safety issues and negative community perceptions regarding weight loss, may also need to be addressed, along with the accessibility and affordability of healthy food options through subsidies. Population groups that demonstrated a higher probability of remaining within the obese category included women, higher age groups (> 35 years), and those with a higher income and higher level of education. These groups are usually the target of public interventions and of the weight management programmes of private health-care providers. However, our data show a high resistance to a downwards transition from either overweight or obese categories, and this resistance increases with time. Other studies have shown that although weight loss can be achieved through lifestyle changes,, maintaining this weight loss over the longer term can be difficult; only approximately one-fifth (20.6%; 47/228) of those who achieve weight loss maintain it for ≥ 1 year,, and the majority of those who embark on a weight-loss programme give up before achieving success.– Our results indicate that, despite considerable percentages of the cohort transitioning downwards, any reductions in the prevalence of obesity were cancelled out by the larger percentages of these population groups transitioning upwards; we therefore believe that the South African target of achieving a 10% reduction in the prevalence of obesity by 2020 will not be met. The main strength of our study was our analysis of BMI transitions within a nationally representative sample of participants from a panel survey spanning birth to adulthood. However, our study had limitations. Some of the risk factors associated with higher BMI categories in this study, such as household income, education level and amount of physical exercise, were self-reported and therefore prone to minor errors that may have affected our results. A second limitation was loss to follow-up from one wave of data collection to another. Since we assume those lost to follow-up were randomly distributed throughout the study population, and the remaining numbers at each subsequent data collection wave were sufficiently high, we consider our results to be free of bias. To conclude, we have demonstrated that the proportion of upwards transitions to overweight and obese categories in the South African population increases sharply between the ages of 19 and 50 years. Once overweight or obese, the likelihood of transitioning to a normal BMI is low, particularly for women, those of higher age groups, and those with a higher income and a higher level of education. With this evidence, we provide essential guidance for the South African Department of Health in the development of strategies to control obesity and noncommunicable diseases. Our study results will allow limited public health resources to be focused on the necessary population segments in which the largest reductions in the prevalence of obesity can be made.
  17 in total

Review 1.  Long-term weight loss maintenance.

Authors:  Rena R Wing; Suzanne Phelan
Journal:  Am J Clin Nutr       Date:  2005-07       Impact factor: 7.045

Review 2.  NIH working group report: Innovative research to improve maintenance of weight loss.

Authors:  Paul S MacLean; Rena R Wing; Terry Davidson; Leonard Epstein; Bret Goodpaster; Kevin D Hall; Barry E Levin; Michael G Perri; Barbara J Rolls; Michael Rosenbaum; Alexander J Rothman; Donna Ryan
Journal:  Obesity (Silver Spring)       Date:  2014-12-02       Impact factor: 5.002

3.  10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study.

Authors:  William C Knowler; Sarah E Fowler; Richard F Hamman; Costas A Christophi; Heather J Hoffman; Anne T Brenneman; Janet O Brown-Friday; Ronald Goldberg; Elizabeth Venditti; David M Nathan
Journal:  Lancet       Date:  2009-10-29       Impact factor: 79.321

4.  Cardiorespiratory Fitness and Light-Intensity Physical Activity Are Independently Associated with Reduced Cardiovascular Disease Risk in Urban Black South African Women: A Cross-Sectional Study.

Authors:  Kasha Dickie; Lisa K Micklesfield; Sarah Chantler; Estelle V Lambert; Julia H Goedecke
Journal:  Metab Syndr Relat Disord       Date:  2015-11-13       Impact factor: 1.894

5.  Nonsurgical weight loss for extreme obesity in primary care settings: results of the Louisiana Obese Subjects Study.

Authors:  Donna H Ryan; William D Johnson; Valerie H Myers; Tiffany L Prather; Meghan M McGlone; Jennifer Rood; Phillip J Brantley; George A Bray; Alok K Gupta; Alan P Broussard; Bryan G Barootes; Brian L Elkins; David E Gaudin; Robert L Savory; Ricky D Brock; Geralyn Datz; Srininvasa R Pothakamuri; G Tipton McKnight; Kaj Stenlof; Lars V Sjöström
Journal:  Arch Intern Med       Date:  2010-01-25

Review 6.  Long term maintenance of weight loss with non-surgical interventions in obese adults: systematic review and meta-analyses of randomised controlled trials.

Authors:  S U Dombrowski; K Knittle; A Avenell; V Araújo-Soares; F F Sniehotta
Journal:  BMJ       Date:  2014-05-14

7.  Developing Intervention Strategies to Optimise Body Composition in Early Childhood in South Africa.

Authors:  Catherine E Draper; Simone A Tomaz; Matthew Stone; Trina Hinkley; Rachel A Jones; Johann Louw; Rhian Twine; Kathleen Kahn; Shane A Norris
Journal:  Biomed Res Int       Date:  2017-01-16       Impact factor: 3.411

8.  Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies.

Authors: 
Journal:  Int J Epidemiol       Date:  2017-10-01       Impact factor: 7.196

9.  Eight-year weight losses with an intensive lifestyle intervention: the look AHEAD study.

Authors: 
Journal:  Obesity (Silver Spring)       Date:  2014-01       Impact factor: 5.002

10.  Patterns, levels and correlates of self-reported physical activity in urban black Soweto women.

Authors:  Philippe Jean-Luc Gradidge; Nigel J Crowther; Esnat D Chirwa; Shane A Norris; Lisa K Micklesfield
Journal:  BMC Public Health       Date:  2014-09-08       Impact factor: 3.295

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