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Corresponding author. Department of Family and Home Economics, Advanced Teachers Training College for Technical Education (ATTCTE), University of Douala, Cameroon.
Department of Family and Home Economics, Advanced Teachers Training College for Technical Education (ATTCTE), University of Douala, CameroonMicrobiology, Immunology-Hematology and Morphologic Sciences Laboratory (LMIHSM), Doctoral Training Unit in Health Sciences (UFD-SCS), Doctoral School, Douala University, P.O. Box 2701, Douala, CameroonInserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, France
Inserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, France
Microbiology, Immunology-Hematology and Morphologic Sciences Laboratory (LMIHSM), Doctoral Training Unit in Health Sciences (UFD-SCS), Doctoral School, Douala University, P.O. Box 2701, Douala, Cameroon
Inserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, France
Inserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, France
Inserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, FranceNutrition Resources Center of the Nouvelle Aquitaine Regional Health Agency (CERENUT), Isle, France
Inserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, FranceNutrition Resources Center of the Nouvelle Aquitaine Regional Health Agency (CERENUT), Isle, FranceNutrition Unit, CHU Limoges, Limoges, France
Inserm U1094, IRD U270, Univ. Limoges, CHU Limoges, EpiMaCT - Epidemiology of Chronic Diseases in Tropical Zone, Institute of Epidemiology and Tropical Neurology, OmegaHealth, Limoges, FranceNutrition Resources Center of the Nouvelle Aquitaine Regional Health Agency (CERENUT), Isle, FranceNutrition Unit, CHU Limoges, Limoges, France
Undernutrition, overweight and obesity are noted among elderly people, but African data were scattered, and no structured synthesis has yet been performed to review studies on nutritional status (NS) of this population. The aim of this study was to assess NS using Body Mass Index (BMI), among elderly living in communities in Africa.
Methods
Literature was extracted from six databases looking for studies addressing NS among the people aged≥60y. The systematic search was performed up to January 31st, 2021. Countries and overall prevalences were calculated. Link between NS and Human Development Index (HDI) was assessed through Pearson's correlation.
Results
Thirty-two studies conducted in 14 countries covering almost all socio-geographical areas of the African continent were included. The sample size was from 62 to 2091 participants and the mean age ranged from 65 to 79.7 years. Undernutrition (20.9±8.6%) was higher in Central African Republic (33.4%) and lower in South Africa (3.4%). Overweight (13.8±7.2%) was higher in South Africa (27.6%) and lower in Ethiopia (2.3%) when obesity (13.2:0.7–50.4%) was higher in South Africa (50.4%) and lower in Tanzania (0.7%). Overweight and obesity were positively correlated with HDI (r=0.7, p=0.023; r=0.7, p=0.016, respectively). This study was the first structured one about NS of elderly in Africa.
Conclusion
Nearly one among five older people in Africa is undernourished and about 30% are overweight or obese. This should be a challenge to African authorities, especially since excess weight could be a problem in the future due to the nutritional transition.
Aging is characterized by physiological and psychological changes that modify the structure and functions of the body with an increased prevalence of chronic and/or degenerative diseases (cardiovascular diseases, diabetes, cancer, obesity, osteoporosis, undernutrition) [
]. Undernutrition of elderly is associated with an increased risk of frailty, falls, dependence on activities of daily living, hospitalization and prolonged hospital stay, increased health care costs, poor quality of life, and increased mortality [
] when obesity is associated with decline of functional abilities, the metabolic syndrome, cardiovascular disease, arthritis, pulmonary abnormalities, urinary incontinence, visual impairments, and various cancers [
]. Several studies have been carried out in Africa to assess the nutritional status of older persons but are scattered and have not yet been subjected to a structured review. Moreover, there is no consensus on tools for nutrition assessment of elderly as well as cut-off age to define old people.
Considering that the Body Mass Index (BMI) is the WHO recommended tool for nutritional assessment among elderly [
], the aim of this article was to synthesize the studies conducted in Africa using the BMI i) to assess the nutritional status of people aged ≥ 60 years (in accordance with the WHO World Aging Report 2015 [
] which stated that the main burdens of disability and death resulting from age-related losses of hearing, vision and mobility, and non-communicable diseases including heart disease, stroke, chronic respiratory disorders, and dementia occurred at age 60) living exclusively in communities ii) to study the relationship between the nutritional status and the Human Development Index (HDI) of the countries.
2. Materials & methods
This systematic review followed the PRISMA approach [
]. It includes successively: protocol and registration, eligibility criteria, information sources, search approach, study selection, data collection process, data items, risk of bias in individual studies, summary measures and synthesis of results.
2.1 Protocol and registration
The systematic review was registered in Prospective International Register of Systematic Reviews (PROSPERO) under number CRD42021216268.
2.2 Eligibility criteria
Inclusion criteria: i) The studies selected were those that addressed NS among people aged≥60 years in Africa, irrespective of the geographical area, ii) Cross-sectional studies and simple literature reviews if the cited articles were neither available nor accessible and if the cited authors did not react to our e-mails. There was no restriction according to language and publication period.
Exclusion criteria: i) Studies conducted in hospitals/nursing homes, ii) Using assessment tools other than BMI, iii) Studies on refugees and with insufficient information on methodology or with racial or gender discrimination, iii) case-control, qualitative studies, case report and experimental studies.
2.3 Information's sources
Articles were checked in six data bases: Web of Science, Google Scholar, PubMed, Research4life, AJOL, and Scopus.
2.4 Search approach
The search approach includes the definition of key words (nutritional status, undernutrition, malnutrition, overweight, obesity), the use of MeSH (Medical Subject Headings) and Boolean AND/OR operator to establish logical relation. The search method was either automatic or manual covering publication's period from January 1, 1960, to December 31, 2019.
For automatic research, the main equations used were as follows:
∗
“Nutritional status” AND (“Older person” OR “Elderly” OR “Aged person”) AND “Africa".
∗
“Nutritional status” AND (“Older person” OR “Elderly” OR “Aged person”) AND “Country” (for each of the 54 African countries)
∗
(“Undernutrition” OR Malnutrition) AND (“Older person” OR “Elderly” OR “Aged person”) AND “Africa".
∗
(“Undernutrition” OR Malnutrition) AND (“Older person” OR “Elderly” OR “Aged person”) AND “country” (for each of the 54 African countries)
∗
“Overweight” AND (“Older person” OR “Elderly” OR “Aged person”) AND “Africa".
∗
“Overweight” AND (“Older person” OR “Elderly” OR “Aged person”) AND “country” (for each of the 54 African countries)
∗
“Obesity” AND (“Older person” OR “Elderly” OR “Aged person”) AND “Africa";
∗
“Obesity” AND (“Older person” OR “Elderly” OR “Aged person”) AND “country” (for each of the 54 African countries)
The manual search consisted in searching for second source references and contacting some authors for more information. The systematic search was performed up to January 31st, 2021.
2.5 Study selection
The obtained records were saved and stored in Rayyan [
] where duplicates were first automatically excluded. The remaining duplicates were excluded manually by two reviewers (GM and TM). These two reviewers then examined the titles and abstracts to exclude irrelevant studies. After reading the full text and confrontations between GM and TM the opinion of JCD and PJ was required for the final inclusion or exclusion.
2.6 Data collection process
The following data were extracted: country, authors, year of publication and study, if possible, study design, number, and characteristics of the sample (age ranges: mean or median and sex-ratio, the prevalence of undernutrition, overweight and obesity.
In the United Nations Development Program (UNDP) database, the HDI of the year/period of study/publication was extracted [
The HDI is a summary measure of average achievement in key dimensions of human development: a long and healthy life (life expectancy), access to education (expected years of schooling and mean year of schooling) and have a decent standard of living (Gross National Income (GNI) per Capita) [
]. The HDI is the geometric mean of normalized indices for each of the three dimensions: According to HDI, countries can be categorized as very high HDI (≥0.800), high HDI (0.700–0.799), medium HDI (0.557–0.699) and low HDI (<0.557) [
The Newcastle-Ottawa Quality Assessment Scale (NOQAS-adapted for cross sectional studies) was used to assess the quality of the articles. The tool classifies the studies according to the number of stars recorded (0–10) using the following distribution: Selection: 0–5 stars; Comparability: 0–2 stars; Outcome: 0–3 stars [
]. According to scores, studies are classified into four categories and qualified as follows: =<4 (poor), 5–6 (average), 7–8 (good), and 9–10 (very good). The quality classification was carried out independently by two researchers (GM and TM) and the differences were solved after discussion. One of the senior researchers (JCD, PJ) was consulted, if necessary.
2.9 Statistical analysis
SPSS 26.0 (SPSS Software, Chicago, USA) software was used for statistical analyses. The prevalences of undernutrition, overweight and obesity were pooled by country and calculated for the continent. Correlations between nutritional disorders (undernutrition/overweight/obesity) and HDI were sought for the continent. The level of significance was p<0.05.
3. Results
3.1 Study selection
The flow chart is presented by Fig. 1. Only 32 studies were finally selected for the systematic review.
The studies were published between 2002 and 2019. They were conducted in 14 of the 54 independent African countries, representing 25.9% of the continent. Details of the studies by country are given in Table 1. Regions of the African continent were represented as follows: Northern Africa: 7.1% [
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
]. NS of the studies ranged by country are presented in Tables 2. The overall prevalence was 20.9±8.6%, 13.8±7.2% and 13.2(min: 0.7; max: 50.4)% for undernutrition, overweight and obesity respectively (Table 3), with undernutrition ranged from 3.4% (South Africa) to 34.1% (Kenya) and obesity from 0.7% (Tanzania) to 50.4% (South Africa). Details are provided in Fig. 2.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
Samba H, Guerchet M, Ndamba-Bandzouzi B, Mbelesso P, Lacroix P, Dartigues J-F, et al. Dementia-associated mortality and its predictors among older adults in sub-Saharan Africa: results from a 2-year follow-up in Congo (the EPIDEMCA-FU study). Age Ageing. 45(680–687). Available from: https://pubmed.ncbi.nlm.nih.gov/27230914/.
HDI was positively correlated with overweight (r=0.7, p=0.021) and obesity (r=0.7, p=0.016) separately and together (r=0.6, p=0.045).
3.3 Quality evaluation
All studies were of fairly good quality with scores ranging from 6 to 9/10. Two publications could not be classified because they synthesize published or unpublished research [
]. These publications had at least the advantage of presenting data for certain countries (Senegal for example) that had not been published elsewhere. The main shortcomings identified in some studies were a very small and potentially non-representative sample [
Nearly one among five older people was undernourished and about 30% were overweight or obese. This study was the first structured and systematic review on NS of elderly (aged ≥ 60 years) in Africa and had a significant estimation value. However, given the dispersion in periods (investigation and publication), methodologies, age range and sex ratio it was not representative of the whole of Africa. Overall and countries prevalence of undernutrition, overweight and obesity are presented in Fig. 2.
Only one study to our knowledge presented undernutrition 19.5–36.1% and 13.1–27% among elderly men and women respectively in Africa. This relatively old review (2001) was limited by the inclusion of refugees and the limited number of countries covered (four: Ethiopia, Kenya, Malawi, and Tanzania) to represent the African continent [
Prevalence of protein-energy malnutrition risk in European older adults in community, residential and hospital settings, according to 22 malnutrition screening tools validated for use in adults ≥65 years: A systematic review and meta-analysis.
Malnutrition in Older Adults in the United States.
in: Preedy V. Patel V.B. Handbook of famine, starvation, and nutrient deprivation: from biology to policy. Springer International Publishing,
Cham2017: 1-20
], regardless of the tools and methodologies used. Most African countries (92.3%) had higher prevalence of undernutrition (≥10%) than Western (=<10%) [
Prevalence of protein-energy malnutrition risk in European older adults in community, residential and hospital settings, according to 22 malnutrition screening tools validated for use in adults ≥65 years: A systematic review and meta-analysis.
], confirming the general observation made for the continents. This might be explained by the socio-economic differences with the main low- and middle-income countries located in Africa. The national prevalences in Africa (3.4–34.1%) were not similar to those obtained in Brazil (27.3–33.0%) [
Only one country, South Africa (3.4%) had undernutrition prevalence below 10%. This might be explained by the leading economic situation of the country among others in Africa. However, in this review, no correlation was found between undernutrition and the HDI, probably because of methodological specificities of studies included and country's realities that might have escaped the HDI assessment. If undernutrition remains high, some African countries may experience many deleterious consequences [
]. Undernutrition might be due to poor education, inactivity, isolation, various conflicts and their impact on family and/or community stability, climate change and its impact on agricultural production and productivity, reduced food intake due to poor health condition (polypathology and polymedication), prolongation of the satiety period, functional and neurocognitive disorders, and above all poverty [
Association between mild cognitive impairment and dementia and undernutrition among elderly people in Central Africa: some results from the EPIDEMCA (Epidemiology of Dementia in Central Africa) programme.
To our knowledge, no study was found on the overall prevalence of overweight among the elderly in Africa. The overall overweight of our study was 13.8±7.2%, ranged from 2.3 (Ethiopia) to 27.6% (South Africa). Although overweight may have benefits such as increased bone mass and reduced osteoporosis, falls and fractures in the elderly [
], it should be better controlled to avoid the development of the co-morbidities linked to excess of weight. For studies that would have distinguished gender in their analysis, there was a positive association between overweight and/or obesity and female gender [
]. This aspect was not covered by our study because most studies did not provide gender-specific prevalence. In this review, most countries (75%) had a prevalence of overweight between 10 and 28%, lower than the data obtained in Europe. According to Peralta et al. (2018), average overweight in 10 European countries was of 41.1% among participants aged≥50 years [
]. In our study the HDI was positively and significantly correlated with the prevalences of overweight (r=0.7, p=0.02) and obesity (r=0.7, p=0.016) taken separately and together (r=0.6, p=0.045). The nutrition transition in some African countries [
] might lead to an increase in overweight among the elderly as observed in European context.
To our knowledge, no study was found on the overall prevalence of obesity among the elderly in Africa. Obesity has always been and might remain a major public health problem in any environment. The overall obesity in this study was 13.2 (0.7–50.4) %, ranged from 0.7% (Tanzania) to 50.4 (South Africa). The overall obesity of the continent was low compared to the USA (34.6%) [
]. South Africa seemed to be the country with most obesity with highest overweight (27.6%) and lowest undernutrition (3.4%), a westernization of the nutritional status of the elderly that might be deleterious to the country. Obesity in the elderly can exacerbate the decline in physical function with decreased ability to perform activities of daily living. Obesity in this various countries might be associated with functional disorders, metabolic syndrome, cardiovascular disease, arthritis, pulmonary disorders, urinary incontinence, visual impairment, various cancers and increased mortality in the elderly. [
]. The nutrition transition is characterized by demographic, epidemiological, and socioeconomic changes resulting from globalization, urbanization, and development (increasing wealth) [
]. In this transition, predictable changes in diet follow five patterns (hunter-gatherers; early agriculture; end of famine; overeating, obesity-related diseases; behavior change) [
] noted an increase in nutrition-related chronic diseases in developing countries caused mainly by the nutrition transition. This observation was also made by Bosu [
] who noted an increase in the consumption of dietary energy, fats, sugars and proteins with low consumption of fruits and vegetables, foods consumed being mainly traditional, with the main food groups being within recommended limits. For Bosu, while most African countries are in the early stages of the nutrition transition, some, such as Ghana and Senegal, are in stages 4 (over-nutrition, obesity-related diseases) as confirmed by this study. These two countries might quickly move towards the rarely and hardly achieved Stage 5, characterized by consumption of whole and minimally processed foods close to Stage 1 dietary intakes, with a higher share of plant-based foods and nutrients, and lower intakes of meats and ultra-refined foods. To achieve this by shortening/minimising Stage 4, it is imperative that governments put in place appropriate strategies to promote a healthier eating environment that supports human health, increased physical activity, and reduced sedentary time [
]. Bosu proposed concerted national actions involving governments, partners, the private sector, and civil society to reorient health systems and build capacity, regulate the food and beverage industry, and promote healthy eating throughout the life cycle to address the double nutritional burden observed in most developing countries [
] not assessed by this study. According to Case et al. (2009), obesity higher among women than men in Africa might be explained by food deprivation in childhood, the desire to catch up in adulthood, and weight gain being considered as a sign of “good life” [
Some limitations of our study might be the use of cross-sectional studies (potential source of bias), few studies covering urban and rural areas (26.5%), different thresholds of age of people inclusion (from 60 to 71 y. o), dispersion of sample (62–2091), periods of investigation and publication, and sex ratio. Our study might have a major advantage by providing national indicators for several countries in Africa.
5. Conclusion
This literature review, which was carried out in four stages, enabled the selection of 32 studies among people aged ≥60 years conducted in 14 countries and covering almost all the socio-geographical environments of the African continent. 47.9% of the elderly in Africa had an altered NS (undernutrition, overweight or obesity). Nearly one among five older people was undernourished and about 30% were overweight or obese. Considering the impact of nutritional troubles on diseases evolutions, mortality and quality of life, these troubles in African elder population might be a new burden for local economies requiring appropriate policies to cope with it.
Funding statement
This work was supported the ALAIR-LIMOUSIN Association and Health Network of the Nouvelle Aquitaine Regional Health Agency Limousin Nutrition (LINUT).
Authors' contributions
Gustave Mabiama: Conceptualization, drafting, revising, final approval and editing, Therno Millimono: Drafting, revising and final approval, Dieudonné Adiogo: Conceptualization, revising, final approval, Farid Boumediene: Conceptualization, revising, final approval, Pierre Marie Preux: Conceptualization, revising and final approval, Jean-Claude Desport: Conceptualization, drafting, revising and final approval, Philippe Fayemendy: Drafting, revising and final approval, Pierre Jésus: Conceptualization, revising and final approval.
Conflicts of interest
No conflict to declare.
Acknowledgements
We would like to thank members of “Groupe de Recherche sur le Vieillissement au Cameroun” (GRVC) for their assistance: Dr (Mrs) Véronique Priscille Nguiamba, Mrs Aurélie Michelle Mimba Mengue, Nadège Mayan Matouki, Edwige Laure Nzié, Cécile Nadège Kingué Ekamé, Didja Wassah, Annie Gaëlle Dekembaye, Brigitte Floriane Ombous, Anne Marie Ngo Manyim Ma Mayada, and Mr François Etotogo, Thierry Roland Njille Ehawa, Samaki Charles Yaya, Maurice Menzo, Lionel Wilfried Mbono Mbono.
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