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. 2021 Mar 30;53(1):495–507. doi: 10.1080/07853890.2021.1897665

Estimating the prevalence of overweight and obesity in Nigeria in 2020: a systematic review and meta-analysis

Davies Adeloye a,✉, Janet O Ige-Elegbede b, Martinsixtus Ezejimofor c,d, Eyitayo O Owolabi e, Nnenna Ezeigwe f, Chiamaka Omoyele f, Rex G Mpazanje g, Mary T Dewan g, Emmanuel Agogo h, Muktar A Gadanya i, Wondimagegnehu Alemu j, Michael O Harhay k, Asa Auta l, Akindele O Adebiyi m
PMCID: PMC8018557  PMID: 33783281

Abstract

Background

Targeted public health response to obesity in Nigeria is relatively low due to limited epidemiologic understanding. We aimed to estimate nationwide and sub-national prevalence of overweight and obesity in the adult Nigerian population.

Methods

MEDLINE, EMBASE, Global Health, and Africa Journals Online were systematically searched for relevant epidemiologic studies in Nigeria published on or after 01 January 1990. We assessed quality of studies and conducted a random-effects meta-analysis on extracted crude prevalence rates. Using a meta-regression model, we estimated the number of overweight and obese persons in Nigeria in the year 2020.

Results

From 35 studies (n = 52,816), the pooled crude prevalence rates of overweight and obesity in Nigeria were 25.0% (95% confidence interval, CI: 20.4–29.6) and 14.3% (95% CI: 12.0–15.5), respectively. The prevalence in women was higher compared to men at 25.5% (95% CI: 17.1–34.0) versus 25.2% (95% CI: 18.0–32.4) for overweight, and 19.8% (95% CI: 3.9–25.6) versus 12.9% (95% CI: 9.1–16.7) for obesity, respectively. The pooled mean body mass index (BMI) and waist circumference were 25.6 kg/m2 and 86.5 cm, respectively. We estimated that there were 21 million and 12 million overweight and obese persons in the Nigerian population aged 15 years or more in 2020, accounting for an age-adjusted prevalence of 20.3% and 11.6%, respectively. The prevalence rates of overweight and obesity were consistently higher among urban dwellers (27.2% and 14.4%) compared to rural dwellers (16.4% and 12.1%).

Conclusions

Our findings suggest a high prevalence of overweight and obesity in Nigeria. This is marked in urban Nigeria and among women, which may in part be due to widespread sedentary lifestyles and a surge in processed food outlets, largely reflective of a trend across many African settings.

KEY MESSAGES

  • About 12 million persons in Nigeria were estimated to be obese in 2020, with prevalence considerably higher among women. Nutritional and epidemiological transitions driven by demographic changes, rising income, urbanization, unhealthy lifestyles, and consumption of highly processed diets appear to be driving an obesity epidemic in the country.

Keywords: Obesity, overweight, prevalence, non-communicable diseases, epidemiology, Nigeria

Introduction

The disease burden from overweight and obesity has continued to increase globally [1]. The World Health Organization (WHO) reported that overweight and obese persons nearly tripled between 1975 and 2016 [1]. Recently, Ng et al. [2] reported that the prevalence of overweight and obesity increased significantly worldwide in children and young adults between 1980 and 2013 [2]. In 2016, more than 1.9 billion adults aged 18 years or more were overweight, with 650 million obese [1]. Obesity and overweight are strongly linked with several cardio-metabolic disorders including high blood pressure, high blood glucose, insulin resistance, high blood cholesterols, coronary heart disease, stroke and cancers [3]. These are important contributors to poor health outcomes, particularly for many cases of COVID-19 in African population groups. Globally, over 3 million deaths and an estimated 36 million DALYs were attributed to overweight and obesity annually [1,2].

Although, previously thought to be challenges in high-income settings, current trends reveal overweight and obesity are on the rise across urban settings in several low- and middle-income countries (LMICs) [2]. While a plateauing in obesity prevalence have been recorded since the mid-2000s in many high-income countries, prevalence rates have been increasing rapidly in LMICs, including several African countries, over the same period [4]. In sub-Saharan Africa, about 30% and 10% of adults are overweight and obese, respectively [4,5]. In Nigeria, nutritional and epidemiological transitions driven by demographic changes, rising income, urbanization, unhealthy lifestyles, and consumption of highly processed diets are among the leading contributors to overweight and obesity [5,6]. In fact, the burden has extended to younger population age groups in the country with about 9% of children aged 5–9 years estimated to be obese or overweight [6,7]. Recent evidence on the high burden of cardiovascular disease [8,9], diabetes mellitus [10] and hypertension [11] in Nigeria mirrors the classic population pyramid that depicts a greater proportion of younger population with increased vulnerability [12]. These chronic conditions have also been linked to the clustering of major risk factors in many epidemiological studies [8–10,13], with overweight and obesity being the common denominators. Obesity and related co-morbidities have greatly impacted on individuals’ health, self-esteem, educational attainment, quality of life and overall productivity [7].

Ng et al. [2] noted that obesity is not only increasing globally, there are also relatively no national success stories on its prevention in the past three decades from several countries, necessitating urgent global action to help countries effectively intervene. Recently, the WHO member nations, including Nigeria, have targeted halting the rise in obesity by 2025 [7]. Since then, there have been widespread in-country calls for regular monitoring of changes in overweight and obesity prevalence across populations, albeit affected by a dearth of data and information on the prevalence of overweight and obesity in Nigeria. Despite some emerging reports in recent times, gaps still exist in the understanding of nationwide predictors of overweight and obesity particularly in the adult population [10,14]. This study, therefore, aims to estimate nation-wide and zonal (sub-national) prevalence of obesity and overweight in the adult Nigerian population. This would be essential to quantify health effects and prompt decision-makers to prioritize relevant actions.

Methods

The study was conducted in compliance with the PRISMA guidelines [15].

Search strategy

Databases searched include MEDLINE, EMBASE, Global Health, and Africa Journals Online (AJOL). At this stage, we broadly searched for studies on overweight and/or obesity in Nigeria (see search terms in Table 1). Searches were conducted on 01 July 2020 and limited to studies published after 01 January 1990. Unpublished documents were sourced from Google Scholar and Google searches. Titles and abstracts of studies were reviewed, and full-texts of relevant studies accessed (see Selection criteria). References of accessed full-texts were further hand-searched for additional studies. Authors of selected papers were contacted for any missing information on study characteristics and prevalence estimates.

Table 1.

Search terms.

Number Searches
1 africa/ or africa, sub-sahara/ or africa, western/ or nigeria/
2 exp vital statistics/
3 (incidence* or prevalence* or morbidity or mortality).tw.
4 (disease adj3 burden).tw.
5 exp “cost of illness”/
6 case fatality rate.tw
7 hospital admissions.tw
8 Disability adjusted life years.mp.
9 (initial adj2 burden).tw.
10 exp risk factors/
11 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10
12 exp obesity / or obese/ or overweight/ or high bmi or waist circumference
13 1 and 11 and 12
14 Limit 13 to “1990-current”
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Selection criteria

Population- or community-based studies reporting on the prevalence of overweight and/or obesity in a Nigerian setting were selected. We also selected studies on cardio-metabolic risks and extracted data on overweight and obesity from such studies when reported. We excluded hospital-based reports, studies on Nigerians in diaspora, reviews, editorials, view-points and commentaries.

Case definitions

We checked for definition of overweight and obesity in selected studies, with both broadly identified as abnormal or excessive fat accumulation presenting a risk to health [1]. For analysis, we ensured studies employed crude population measure of obesity using body mass index (BMI), equivalent to a person’s weight (in kilograms, kg) divided by the square of his or her height (in metres, m). A person is considered obese if the BMI is 30 or higher, while a BMI of 25 or higher is considered overweight.

Data extraction

Assessment of eligible studies was conducted independently by two reviewers – DA (PhD) and AA (PhD) – with an eligibility guideline based on the selection criteria to ensure consistency. Disagreements in study selection were resolved by consensus. We extracted data on the study location (including geo-political zones), period, design, setting (urban or rural), sample size, diagnostic criteria and mean age of sample population. These were matched with corresponding data on overweight or obese persons and respective prevalence rates reported in each study. For multiple studies reporting data from the same study site, population or cohort, the first published study was selected, and all additional data from the other studies were extracted and merged with data from the selected paper.

Quality assessment

JOI (MSc) and EOO (PhD) independently assessed quality of selected studies with disagreements resolved in another meeting with DA. Adapting a validated quality assessment guideline for studies on epidemiology of chronic diseases [16,17], already used in previous studies [10], we based our grading on three broad criteria. These include: (i) design – appropriate approach to statistical analysis with limitations sufficiently described, (ii) identification of cases – case ascertainment using standard or acceptable guideline or protocol, and (iii) sampling – appropriate approach to sampling representative of the larger population of the study location, e.g. the town, city or local government area. Studies were finally graded as high, moderate, or low quality (see Tables 2 and 3 for details of all full-text manuscripts accessed and quality grading).

Table 2.

Approach to quality assessment.

Quality criteria Assessment Score Maximum score
Sampling (was it described and representative of a target subnational population?) Yes 2 2
Not representative 1
Not described 0
Appropriateness of statistical analysis Yes 1 1
No 0
Case ascertainment (was the procedure for identification of cases clearly described?) Yes 2 2
Ambiguous 1
Not described 0
Total [high (4–5), moderate (2–3), or low quality (0–1)] 5
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Table 3.

Characteristics of studies on prevalence of overweight or obesity in Nigeria.

First author Study period Location Geopolitical zone Study design Study setting Quality
1. Abegunde [20] 2011 Oyo State South-west Descriptive cross-sectional study Mixed High
2. Agaba [21] 2014 Jos, Plateau State North-central Descriptive cross-sectional study Urban High
3. Akinbodewa [22] 2014 Akure & Ondo, Ondo State South-west Descriptive cross-sectional study Mixed High
4. Emerole [23] 2007 Owerri, Imo State South-east Descriptive cross-sectional study Urban Moderate
5. Ibekwe [24] 2012 Oghara, Delta State South-south Descriptive cross-sectional study Rural Moderate
6. Odey [25] 2011 Calabar, Cross River State South-south Descriptive cross-sectional study Urban Moderate
7. Odugbemi [26] 2010 Tejuosho, Lagos South-west Descriptive cross-sectional study Urban High
8. Lawoyin [27] 1998 Idikan Ibadan, Oyo State South-west Population-based cross-sectional study Rural Moderate
9. Ugwuja [28] 2008 Abakaliki, Ebonyi State South-east Descriptive cross-sectional study Urban High
10. Oladapo [29] 2005 Egbeda, Oyo State South-west Descriptive cross-sectional study Rural High
11. Okaka [30] 2013 Ovia, Edo state South-south Population-based cross-sectional study Rural High
12. Odenigbo [31] 2008 Asaba, Delta State South-south Population-based cross-sectional study Semi-urban High
13. Okagua [32] 2016 Port-Harcourt, Rivers State South-south Population-based cross-sectional study Urban Moderate
14. Adesina [33] 2010 Port-Harcourt, Rivers State South-south Population-based cross-sectional study Urban Moderate
15. Oyeyemi [34] 2013 Maiduguri, Yobe State North-east Population-based cross-sectional study Semi-urban High
16. Iwuala [35] 2014 Lagos State South-west Descriptive cross-sectional study Urban High
17. Musa [36] 2012 Benue State North-central Descriptive cross-sectional study Mixed Moderate
18. Yusuf [37] 2013 Kano State North-west Descriptive cross-sectional study Urban High
19. Odunaiya [38] 2010 Ibadan, Oyo State South-west Population-based cross-sectional study Urban High
20. Ezejimofor [39] 2014 Niger Delta, Delta State South-south Community-based cross-sectional study Rural High
21. Ojji [40] 2010 Abuja, FCT North-central Prospective cohort study Urban High
22. Akintunde [41] 2010 Osogbo, Osun State South-west Population-based cross-sectional study Mixed High
23. Akpan [42] 2015 Akwa Ibom States South-south Population-based cross-sectional study Urban High
24. Chukwuonye [43] 2013 Abia State South-east Population-based house-to-house survey Mixed High
25. Ezekwesili [44] 2016 Anambra State South-east Population-based cross-sectional study Mixed High
26. Iloh [45] 2009 Imo State South-east Descriptive cross-sectional study Rural High
27. Iloh [46] 2008 Imo State South-east Descriptive cross-sectional study Rural Moderate
28. Iloh [47] 2010 Owerri, Imo State South-east Descriptive cross-sectional study Urban Moderate
29. Murthy [48] 2013 National National Population-based cross-sectional study Mixed High
30. Okafor [49] 2014 Enugu, Enugu State South-east Population-based cross-sectional study Urban Moderate
31. Ogah [50] 2012 Umuahia, Abia State South-east Population-based cross-sectional study Mixed High
32. Olamoyegun [51] 2016 Ekiti State South-west Population-based cross-sectional study Semi-urban Moderate
33. Shittu [52] 2017 Oke Ogun, Oyo State South-west Population-based cross-sectional study Rural Moderate
34. Suleiman [53] 2011 Amassoma, Bayelsa State South-south Descriptive cross-sectional study Semi-urban Moderate
35. Wahab [54] 2006 Katsina, Katsina State North-west Population-based cross-sectional study Urban High
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Data analysis

We first conducted a random-effects meta-analysis, using the DerSimonian and Laird Method [18], on the individual study estimates to generate crude national and regional pooled estimates of the prevalence of obesity or overweight in Nigeria. We estimated standard errors from individual study prevalence and population denominators, assuming a binomial (or Poisson) distribution. Heterogeneity between studies was assessed using I-squared (I2) statistics. Subgroup analysis (based on regions and settings) was conducted to explore sources of heterogeneity. We investigated publication bias by conducting an Egger’s test and visual inspecting a Funnel plot of the logarithm of obesity prevalence and its standard error. A meta-regression epidemiologic model accounting for study sample size, study period, and age was constructed to determine prevalence distribution of overweight and obesity by age of the Nigerian population. From the age-adjusted prevalence rates, we estimate the absolute number of overweight and obese persons in Nigeria at midpoints of the United Nation (UN) population 5-year age groups for Nigeria for the year 2020 [19]. This approach to data analysis has been employed in previous studies [10,11]. All statistical analyses were conducted on STATA V.14 (Stata Corp, College Station, TX, USA).

Results

Search results

A total of 1337 studies were retrieved from the databases – MEDLINE 580, EMBASE 665, Global Health 74, and AJOL 18. Additional 14 studies were identified through Google Scholar, Google searches, and hand-searching reference lists of relevant studies. After duplicates have been removed, 653 titles were screened for relevance (i.e. any population- or community-based studies on overweight or obesity in Nigeria). On applying the selection criteria, 565 studies were excluded. Hence, 88 full-texts assessed which were screened explicitly using the selection and quality criteria. Thirty-five studies [20–54] were selected for the review (Figure 1).

Figure 1.

Figure 1.

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Flow chart of selection of studies on obesity or overweight in Nigeria.

Study characteristics

The 35 studies spread across the southern and northern parts of Nigeria (Table 3). South-south had the highest output with 10 studies, closely followed by South-east and South-west with nine studies each. Three studies were retrieved from the North-central, two from the North-west and one from the North-east. Most studies (n = 19) were conducted in urban settings, nine in rural and seven in mixed urban-rural settings. Twenty-two studies were rated as high quality, with the remaining 13 rated as moderate quality. Study period ranged from 1993 to 2017, with most studies conducted within a one-year period. There were 56 data-points extracted from all studies, covering a population of 52,816, with mean age ranging from 14.7 to 61.7 years (Table 3). Heterogeneity was high across studies, with I-squared (I2) mostly above 99.0% (p < .001) across different settings. When sub-groups (regions and settings) were separately considered, our data returned highest heterogeneity from the North-central (99.7%), North-west (99.7%) and rural settings (99.8%). The Funnel plot suggests some degree of publication bias with large studies reporting high prevalence rates mainly published. The Egger’s test confirms presence of small study effects (p < .001) (Supplementary material).

Prevalence of overweight in Nigeria

The prevalence of overweight varies widely across different settings in Nigeria, ranging from 1.9% in Egbeda, Oyo State, a rural setting in South-west Nigeria [29] to 53.3% in Katsina, North-west Nigeria [54]. From all data points, the pooled crude prevalence of overweight persons in Nigeria was 25.0% (95% CI: 20.4–29.6) (Figure 2). The prevalence in women was slightly higher at 25.5% (17.1–34.0) compared to men at 25.2% (18.0–32.4) (Table 4, Supplementary material). The prevalence was highest in South-east (33.0%, 26.4–40.0). Although, both the North-east and North-west had limited datapoints, the prevalence of overweight in both regions was also high at 30.1% (24.5–35.3) and 27.6% (22.7–77.9), respectively. The South-west and South-east had relatively similar rates at 23.0% (16.2–29.7) and 22.4% (8.0–36.7), respectively. The prevalence of overweight persons was higher among urban dwellers (27.2%, 20.1–34.3) compared to rural settings (16.4%, 4.7–28.1) (Table 4).

Figure 2.

Figure 2.

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Crude prevalence rate of overweight in Nigeria, by geopolitical zones.

Table 4.

Pooled crude estimates of prevalence of overweight and obesity in Nigeria, by sub-groups.

  Both sexes
 Men
 Women
Prevalence % (95% CI) I2 %, p value Prevalence % (95% CI) I2 %, p value Prevalence % (95% CI) I2 %, p value
Nation-wide            
 Overweight 25.0 (20.4–29.5) 99.5, .000 25.2 (18.0–32.4) 99.0, .000 25.5 (17.1–34.0) 99.2, .000
 Obesity 14.3 (12.0–16.5) 99.2, .000 12.9 (9.1–16.7) 98.7, .000 19.8 (13.9–25.6) 99.2, .000
 Geopolitical zone            
  North-central            
   Overweight 9.7 (8.5–10.9) – – 94.8, .000 – –
   Obesity 18.5 (1.4–38.3) 99.7, .000 14.4 (6.9–21.8) 93.4, .000 42.0 (26.5–57.5) 96.0, .000
  North-east            
   Overweight 30.1 (24.5–35.3) – 36.3 (29.5–43.1) – 26.8 (18.2–35.0) –
   Obesity 24.0 (19.1–28.9) – 42.1 (35.1–49.1) – 14.3 (7.5–21.1) –
  North-west            
   Overweight 27.6 (22.7–77.9) 99.7, .000 21.4 (18.4–61.6) 98.8, .000 32.1 (26.3–90.5) 99.6, .000
   Obesity 10.8 (8.9–30.5) 98.6, .000 4.6 (3.8–13.1) 91.0, .000 15.8 (13.1–43.4) 98.5, .000
  South-east            
   Overweight 33.0 (26.4–40.0) 94.7, .000 32.7 (22.7–42.6) 90.5, .000 30.3 (19.0–41.8) 95.0, .000
   Obesity 13.6 (8.4–18.8) 99.3, .000 15.4 (2.7–28.2) 98.8, .000 20.5 (7.2–33.8) 98.9, .000
  South-south            
   Overweight 22.4 (8.0–36.7) 99.5, .000 3.7 (2.0–5.4) – 9.4 (6.8–12.0) –
   Obesity 13.6 (9.4–17.8) 98.3, .000 2.6 (0.9–6.0) 85.6, .000 8.5 (2.1–14.9) 94.1, .000
  South-west            
   Overweight 23.0 (16.2–29.7) 99.5, .000 25.2 (3.7–467) 99.1, .000 23.0 (4.6–41.4) 92.6, .000
   Obesity 14.9 (9.6–20.1) 99.4, .000 12.3 (3.0–21.5) 98.8, .000 16.8 (5.4–28.2) 99.3, .000
 Settings            
  Urban            
   Overweight 27.2 (20.1–34.3) 99.1, .000 26.9 (17.4–36.4) 98.4, .000 28.1 (15.6–40.5) 98.9, .000
   Obesity 14.4 (11.1–17.7) 98.9, .000 10.9 (7.3–14.5) 97.3, .000 18.5 (11.7–25.2) 98.7, .000
  Rural            
   Overweight 16.4 (4.7–28.1) 99.8, .000 1.9 (0.9–2.8) – 1.8 (1.0–2.6) –
   Obesity 12.1 (8.5–15.8) 99.1, .000 14.0 (10.5–38.5) 99.6, .000 13.4 (8.7–36.4) 99.7, .000
  Mixed            
   Overweight 24.9 (18.6–31.2) 99.0, .000 31.1 (17.6–44.6) 96.3, .000 27.8 (20.6–35.1) 61.3, .004
   Obesity 16.7 (10.3–23.1) 99.6, .000 18.2 (3.2–33.3) 99.2, .000 28.6 (11.8–45.0) 87.6, .000
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Prevalence of obesity in Nigeria

From all studies, the highest prevalence of obesity was reported in Umuahia, Abia State, South-east Nigeria in 2012 at 33.7% [50], with the lowest rate recorded in Kano, North-west Nigeria in 2013 at 0.84% [37]. The pooled (from all data points) crude prevalence of obesity in Nigeria was 14.3 (95% CI: 12.0–15.5) (Figure 3). As observed among overweight persons, the prevalence was higher among women (19.8%, 13.9–25.6) compared to the pooled rate in men (12.9%, 9.1–16.7) (Table 4, Supplementary material). Across geopolitical zones, the highest prevalence was in the North-east at 24.0 (19.1–28.9), although this was mainly from a single survey in the region. However, the North-central recorded a high pooled rate of obesity at 18.5% (1.4–38.3), while the North-west had the lowest rate at 10.8% (8.9–30.5). While the estimates from the Northern regions are marked by wide uncertainty intervals and may still be subject to further validation, the high estimates of obesity (and overweight) in at least two regions call for some public health concerns in these settings. Meanwhile, the Southern regions had nearly similar rates of obesity with the South-west at 14.9% (9.6–20.1), South-east 13.6% (8.4–18.8) and South-south 13.6% (9.4–17.8). The prevalence of obesity was higher in urban settings at 14.4% (11.1–17.7) compared to rural settings at 12.1% (8.5–15.8) (Table 4).

Figure 3.

Figure 3.

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Crude prevalence rate of obesity in Nigeria, by geopolitical zones.

Pooled mean BMI and waist circumference in Nigeria

From individual study estimates, the mean population BMI ranged from being normal (23.4 kg/m2) recorded in a rural setting in Ekiti State, South-west Nigeria [51], to an overweight population (27.7 kg/m2) recorded in the urban metropolis of Lagos State, also in the South-west [35]. The mean population waist circumference has a narrow margin, ranging from 85.7 centimetres (cm) recorded in Abia State, South-east Nigeria [43] to 88.3 cm measured in Egbeda Oyo State, South-west Nigeria [29]. From all data-points, the pooled mean BMI in Nigeria was 25.6 kg/m2 and the mean waist circumference was 86.5 cm, which both suggest that several persons may be slightly overweight in the country (Figure 4).

Figure 4.

Figure 4.

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Pooled mean BMI and waist circumference in Nigeria. Note: BMI (kg/m2), waist circumference (cm).

Estimated number of overweight or obese persons in Nigeria

The meta-regression epidemiologic modelling, adjusted for study period and sample size, was applied to mean ages and crude prevalence rates of overweight and obesity extracted from individual studies (Supplementary material). Although advancing age was a significant variable, year of study was not, so we did not conduct any trend analyses. Using the United Nations demographic projections for Nigeria, the absolute number of overweight persons among persons aged 15 years or more in the country was 20.9 million in 2020, with an age-adjusted prevalence of 20.3% (Table 5). In the same year, obese persons in Nigeria were estimated at 12 million, accounting for 11.6% among persons age 15 years or more (Table 5).

Table 5.

Absolute number of overweight and obese persons in Nigeria, aged 15 years or more in 2020.

Age (years) Overweight
 Obese
Prevalence (%) Population (000) Cases (000) Prevalence (%) Population (000) Cases (000)
15–19 12.0 18,603.868 2229.674 4.7 18,603.868 871.777
20–24 14.3 15,981.820 2292.592 6.7 15,981.820 1065.348
25–29 16.7 14,051.044 2347.227 8.6 14,051.044 1214.853
30–34 19.1 12,102.265 2307.297 10.6 12,102.265 1285.987
35–39 21.4 9982.646 2138.782 12.6 9982.646 1258.412
40–44 23.8 7767.685 1847.544 14.6 7767.685 1132.995
45–49 26.1 6008.701 1570.975 16.6 6008.701 995.401
50–54 28.5 4993.836 1423.493 18.5 4993.836 926.157
55–59 30.9 4146.148 1279.709 20.5 4146.148 851.038
60–64 33.2 3325.733 1104.975 22.5 3325.733 748.489
65–69 35.6 2554.200 908.912 24.5 2554.200 625.421
70–74 37.9 1821.521 691.176 26.5 1821.521 482.084
75–79 40.3 1077.611 434.331 28.4 1077.611 306.537
80+ 44.1 721.755 318.157 31.6 721.755 228.176
All 20.3 103,138.833 20,894.843 11.6 103,138.833 11,992.676
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Note: Estimates based on epidemiologic model.

Discussion

With about 21 million overweight and 12 million obese persons in Nigeria in 2020, Nigeria possibly represents the most affected country in Africa. Low levels of physical activity, urban drifts, unhealthy diets, socio-economic changes, and psychosocial factors are largely responsible for this high burden [55]. Many have reported that the introduction of processed foods, growth in the economy and relatively improved standards of living have resulted in fast rising rates of obesity across many Africa countries [56]. As noted, the health consequences are also fast accumulating, with increase in the prevalence of several chronic diseases, further stretching already weakened health systems in these settings. Our findings thus illuminate this burden on a national scale, hopefully prompting renewed interest and response from policy makers and stakeholders.

The age-adjusted prevalence rates of overweight and obesity in Nigeria were 20.3% and 11.3%, respectively. Our estimates are relatively similar to some previous studies, suggesting that the prevalence of obesity in Nigeria may have not changed significantly over the years. For example, in 2005, Abubakari and Bhopal [57] estimated a pooled prevalence of obesity in Nigeria at 8.8%, with this increasing to 10% in 2008 [58]. From a 2008 demographic and health survey in Nigeria, Kandala et al. [59] estimated a combined prevalence of obesity and overweight at 20.9%. In 2013, Chukwuonye et al. [60] reported that that the prevalence of overweight across Nigeria ranged from 20 to 35%, and obesity from 8 to 22%. However, Commodore-Mensah et al. [61] noted a wide range of combined prevalence of overweight and obesity in Nigeria at 4–49%, which perhaps reflects the varying demographics, geographical settings, socio-economic status and wealth index of the populations from which the data were pooled [59]. When compared to other African countries, Neupane et al. [62] reported that prevalence of overweight ranged from 6% in Madagascar to 28% Swaziland, and obesity from 1 to 23% also in the two countries. The WHO also reported that the prevalence of obesity in Sub-Saharan Africa ranges between 3.3% and 18.0% [63], which are relatively within our reported estimates for Nigeria.

The higher estimates of overweight and obesity among women compared to men that we reported are well supported by many studies. According to the 2010 WHO survey data on Nigeria, the prevalence of overweight in the country was 37% and 26%, while obesity was lower at 8% and 3%, among women and men, respectively [63]. Abubakari et al. [57] specifically noted that women were more likely to be obese than men with odds consistently between 3.2 and 4.8 across various settings in Nigeria. Some authors [13,62,64] further linked this to socio-economic status, noting that women in urban residence with higher education and wealth index had higher likelihood of being overweight or obese. Generally, across Africa, obesity appears to be a major issue among urban women aged 15–49 years, as demonstrated from the results of demographic and health survey from 24 African countries [62], with consequences being more serious as this is the average reproductive age of most women [55]. Asides the known cardio-metabolic risks, maternal obesity has resulted in higher rates of miscarriages, still births and congenital disorders [65,66].

The prevalence of overweight and obesity across the geographical regions was marked by wide uncertainties especially in the northern parts of the country, with our estimates subject to further validation. From the 2008 Nigerian demographic and health survey, Kandala et al. [59] reported striking variations in the prevalence of overweight and obesity across Nigeria ranging from 10.5% in Yobe (North-east Nigeria) to 50.2% in Lagos (South-west Nigeria). However, the South-east had highest pooled prevalence of overweight persons (33%) and one of the leading prevalence of obesity (14%) in this study. Ubesie et al. [67] reported that child obesity is major public health issue in Enugu, South-east, Nigeria, with this possibly reflecting in adolescence, young adults and the overall population over time. The authors did note that this is even more common among children of the higher socio-economic class residing in core urban settings in the city. As estimated in this study, urbanization is widely associated with increased risk of overweight and obesity. Addressing lifestyles and diet of urban dwellers is in fact a major step in the response to reducing overweight and obesity in Nigeria. Sedentary lifestyles and consumption of processed foods are on the increase in several urban settings in the country [64]. Despite seemingly high prices of processed foods, many have continued to associate with this as a way to display affluence among peers, as against the relatively cheap fruits, vegetables and whole grains [13]. In fact, higher rates of obesity appear to be correlated with national wealth status, as the epidemic of overweight and obesity is fast rising in African countries with relatively higher domestic product per capita, of which Nigeria is one [64]. As observed from number of persons affected (21 million) and the relatively high mean population BMI and waist circumference in Nigeria at 26 kg/m2 and 87 cm, respectively, there is need for urgent and comprehensive nationwide awareness and effective population strategies to address this growing epidemic.

Our study has some important limitations. First, heterogeneity across studies was high, which is a reflection of widespread variations in study designs, data collation, and population covered. We also observed some degree of publication bias, suggesting mainly large studies reporting high prevalence rates of obesity and overweight were getting published. Second, although our approach to quality assessment has been consistently employed in previous studies, we recognize that there are other important quality measures that could have been assessed, including missing data and response rate. Of note, we did not assess studies for standard survey guidelines (e.g. the WHO STEPwise approach to Surveillance (STEPS) of non-communicable diseases); rather, we explored case definitions as an alternative, given that prevalence rates of obesity and/or overweight were not primary focus of many studies, hence they do not necessarily employ the WHO STEPs or related protocols. Third, while the meta-regression (random-effects) accounted for sample population across the individual data-points, it could not explain (and represent) the variations across the six geopolitical zones, the 36 States and the Federal Capital Territory (FCT). Indeed, limited data point across the States, particularly in the Northern regions, meant we could only present the pooled crude estimates for these settings. For example, of the 35 studies retained, only six (17%) were from the northern parts of the country, with wide uncertainties in the pooled estimates. Lastly, although we attempted to contact authors for missing data, we only found information on study characteristics most useful in many cases, as we could not correlate several missing figures provided with published data. This also reflects in our inability to provide comprehensive estimates of BMI and waist circumference by age, sex and geographical regions. However, with 35 studies covering a population of 52,816, we believe our estimates fairly represent the epidemiology of overweight and obesity in Nigeria, and provides a robust data pool on which future studies can be based.

Conclusions

Our findings suggest a high prevalence of overweight and obesity in Nigeria. This is marked in urban Nigeria and among women, which may in part be due to widespread sedentary lifestyles and proliferation of processed food outlets. Besides, the social status associated with these lifestyles appear to be a major factor in urban Nigeria. We call on government, policy makers, health professionals and all stakeholders to jointly work towards addressing this public health issue. There is need for population-wide awareness, health education and promotion activities relevant for home and work places, increased taxes on processed foods, and creating a conducive and safe environment for physical activity.

Supplementary Material

Supplemental Material
Click here for additional data file. (192.3KB, docx)

Acknowledgements

The authors acknowledge the support of the Nigeria Federal Ministry of Health and the WHO Nigeria Country Office in the conduct of this study.

Author contributions

DA conceived and designed the study. DA, JOI, EOO and AA conducted the literature searches, data extraction and quality assessment. DA, MOH and ME wrote the first draft. DA and MOH conducted the analysis. DA, NE, CO, RGM, MTD, MOH, EA, WA, MAG, AOA contributed to the final draft and checked for important intellectual content. All authors approved the manuscript as submitted.

Disclosure statement

The authors declare no conflicts of interest.

Data availability statement

All underlying data in this study are included in the supplementary material. Further enquiries can be directed at the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Material
Click here for additional data file. (192.3KB, docx)

Data Availability Statement

All underlying data in this study are included in the supplementary material. Further enquiries can be directed at the corresponding author.

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