Undernutrition and obesity among elderly people living in two cities of developing countries: Prevalence and associated factors in the EDAC study

Undernutrition in obese older adults by fat percentage

OBJECTIVE

The prevalence of obesity by fat percentage has seen a steady increase in older adults in recent years, secondary to increases in fat mass in body composition, even in healthy aging. Malnutrition is a common geriatric syndrome with serious clinical outcomes. Increases in fat mass and waist circumference with healthy aging should not prevent the risk of malnutrition from being masked. Malnutrition is often ignored in obese older people due to low BMI cut-off values in many screening tests. The present study seeks to raise awareness of the need to assess the frequency of undernutrition and related factors in obese older adults.

METHODS

The data of 2013 community-dwelling patients aged ≥ 60 years who applied to a university geriatrics outpatient clinic between April 2012 and November 2022 were analyzed retrospectively, of which 296 were found to be obese based on fat percentage and were included in the study. Demographic data and the presence of any geriatric syndromes were obtained retrospectively from the patient files, functional status was assessed using the KATZ Activities of Daily Living (ADL) Scale and the LAWTON-BRODY Instrumental Activities of Daily Living Scale (IADL); frailty was screened using FRAIL-scale; and the sample was assessed for malnutrition using the Mini Nutritional Assessment-Short Form (MNA-SF), with undernutrition defined as an MNA-SF score of [Formula: see text] The patients' fat percentage and weight were measured using a bioimpedance analyzer. Fatty obesity was defined using the Zoico methodology (fat percentage [Formula: see text] 27.3% for males, [Formula: see text] 40.7% for females)[Formula: see text] handgrip strength (HGS) was measured using a hand dynamometer, and probable sarcopenia was defined as low HGS based on regional cut-off values (35 kg for males, 20 kg for females).

RESULTS

The mean age of the 296 fatty obese older adults (102 males/194 females) was 74.4 + 6.5 years, and the median fat was 42.2% (27.4-59.5). Undernutrition was detected in 19.6% of the patients based on MNA-SF screening. A univariate analysis revealed age, sex, educational status, daily physical activity status, depression, difficulty in swallowing, chewing difficulty, probable sarcopenia, number of chronic diseases, and IADL to be associated with undernutrition, while a multivariate logistic regression analysis revealed depression [OR = 3.662, 95% CI (1.448-9.013), p = 0.005] and daily physical activity status [OR:0.601, 95% CI (0.417-0.867), p = 0.006] to be independently associated with malnutrition in obese older adults based on fat percentage.

CONCLUSION

 The present study clarifies the significance of undernutrition in obese older adults also in our country, and recommends undernutrition screening to be carried out, by fat percentage, on obese older adults, especially with depression and low daily physical activity.

Magnitude of undernutrition and its association with dietary diversity among older persons in Ethiopia: a systematic review and meta-analysis, 2023

Undernutrition in elders remains under-detected, under-treated, and under-resourced and leads to further weight loss, increased infections, and delay in recovery from illness as well as increased hospital admissions and length of stay. The reports of the findings were fragmented and inconsistent in Ethiopia. Therefore, the main objective of this meta-analysis was to estimate the pooled prevalence of undernutrition and its association with dietary diversity among older persons in Ethiopia. Online databases (Medline, PubMed, Scopus, and Science Direct), Google, Google Scholar, and other grey literature were used to search articles until the date of publication. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline was followed. The random effect model was used to estimate the pooled prevalence; whereas subgroup analysis and meta-regression were performed to identify the probable source of heterogeneity using Stata version 14.0 software. Out of 522 studies accessed, 14 met our criteria and were included in the study. A total of 7218 older people (aged above 60 years old) were included in the study. The pooled proportion of undernutrition among older persons in Ethiopia was 20⋅6 % (95 % CI 17⋅3, 23⋅8). Elders who consumed low dietary diversity scores were strongly associated with undernutrition among older persons. Therefore, promoting appropriate intervention strategies for elders to improve dietary diversity practices and nutritional status is crucial.

Nutritional status and associated factors among the elderly in Guinea: a first national cross-sectional study

Aging of the Guinean population is a public health concern for the coming years, and the nutritional status of older people is virtually unknown. We also know that this population is growing and that undernutrition and obesity can affect the health of older adults. This study aimed to assess the nutritional status of older people in the general population of Guinea and its associated factors. A representative cross-sectional survey was conducted using sociodemographic, clinical, and anthropometric data (weight and height). Oral status was assessed by using the University of Nebraska Oral Status Scale. Visual acuity was assessed using the Monoyer scale. The standardized prevalence ratio (SPR) of the nutritional status was calculated for each region. The sample included 1698 subjects with a mean BMI of 22.6 ± 4.3 kg/m2. A total of 50.3% had impaired oral status and 20.3% had moderately to severely impaired visual acuity. The prevalence of undernutrition was 14.4% and of obesity 5.7%. Differences in the prevalence of nutritional status were found between regions, with an SPR > 1 for undernutrition in the Labé region (SPR 1.9, 95% CI = 1.5-2.5) and for obesity in the Conakry and Kindia regions (SPR of 2.90, 95% CI = 2.0-4.05 and 2.32, 95% CI = 1.5-3.3, respectively). In Guinea, The prevalence of nutritional disorders was approximately 20%. Screening and management of the health and nutritional status of older adults should be a national priority, and management should be adapted to each region of the country.

Nutritional status and its associated factors among elderly people in Ilu Aba Bor Zone, Southwest Ethiopia: a community-based cross-sectional study

OBJECTIVES

This study aimed to assess the nutritional status and its associated factors among elderly people.

DESIGN

A community-based cross-sectional study.

SETTING

The study was conducted in urban and semiurban areas.

PARTICIPANTS

The study included 620 elderly community dwellers in Southwest Ethiopia from 3 October 2021 to 10 November 2021. Those who were seriously ill, could not get around or were on special diets were excluded from the study.

OUTCOME MEASURE

The Mini Nutritional Assessment was used to evaluate nutritional status and the STEPwise approach was used to collect data on backgrounds and lifestyle. SPSS V.22.0 was used for data analysis. Logistic regression was computed. The level of significance was set at 0.05.

RESULTS

Elderly people who were malnourished or at risk of malnutrition were found to make up 48.1% (44.1%) and 17.4% (14.5%) of the population, respectively. Those aged 80 years and older had a chance of being at risk of malnutrition (adjusted OR (AOR)=22.555; 95% CI: 7.963 to 63.881), while the odds of being malnourished were 11.5 times higher (AOR=11.755; 95% CI: 4.825 to 28.638). Informal education was a significant predictor of being at risk of malnutrition (AOR=6.102; 95% CI: 2.684 to 13.871). Urban dwellers were 8.9 times more likely to be malnourished. Inadequate financial resources make people 3.7 times more likely to be malnourished. A lower wealth index was a significant predictor of being at risk of malnutrition (AOR=4.156; 95% CI: 1.361 to 12.692). Single elderly people had a 3.4-fold higher risk of malnutrition. Elderly people with chronic pain, who were smokers and alcoholics, and who had depression were all at risk of nutritional problems.

CONCLUSION

The risk of malnutrition and malnourishment was high. Age, urbanisation, finances, education, economics, being a woman, smoking and alcohol are associated factors. Interventional studies are warranted to minimise malnutrition challenges in the study population.

Undernutrition and associated factors among older adults in Ethiopia: systematic review and meta-analysis

OBJECTIVE

Undernutrition contributes to decreased physical and cognitive functional status, higher healthcare consumption, premature institutionalisation and increased mortality. So, the objective of this study was to determine the pooled prevalence and factors associated with undernutrition among older adults in Ethiopia.

DESIGN

Systematic review and meta-analysis was used. Articles that presented original data on undernutrition using body mass index (BMI) were included. We made an inclusive literature search from PubMed, Medline and Google Scholar. The I² test was used to examine the heterogeneity of the studies considered in this meta-analysis. Stata software V.14 and METANDI command were used.

SETTING

Studies conducted in Ethiopia were included.

PARTICIPANTS

Eight independent studies were eligible and enrolled for final analysis.

OUTCOME

Prevalence and determinants of undernutrition. A selection of publications, data extraction and reported results for the review was designed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

RESULTS

A total of eight unique studies were enrolled for final analysis. The pooled prevalence of undernutrition was 20.53% (95% CI 17.39% to 23.67%). The study revealed that males had lesser odds of being undernutrition with AOR 0.17 (95% CI 0.15 to 0.20). Older adults in the age range of 65-74 years were less likely to be undernourished as compared with those whose age was above 85 years with Adjusted Odds Ratio (AOR) 022 (95% CI 0.22 to 0.25). Older adults who were depressed had higher odds of undernutrition as compared with their counterparts with AOR 1.27 (95% CI 1.19 to 1.37). However, older adults from households with poor wealth indexes were two times more likely to be undernourished as compared with those who were from rich households.

CONCLUSION

The burden of undernutrition in Ethiopia is significant. The limitation of the current study was that all included studies were observational, mainly cross-sectional.

Prevalence of malnutrition among old people in Africa: systematic review and meta-analysis

OBJECTIVE

To summarise available evidence and estimate the pooled prevalence of malnutrition among old people in Africa.

DESIGN

Systematic review and meta-analysis.

SETTING

Any healthcare or community research reporting the prevalence or incidence of malnutrition in Africa from January 2000 to October 2021.

PARTICIPANTS

Old people, aged above 60 years.

OUTCOME MEASURES

Malnutrition, either undernutrition or overnutrition.

RESULTS

A total of 1442 studies were retrieved based on the search strategy, where only 36 studies (n=15 266 participants) reported from 11 African countries were included for meta-analysis. The reported prevalence of malnutrition ranges from 2.2% to 77.3% across the continent. Overall, the pooled prevalence rates of undernutrition and overnutrition were 18% (95% CI: 15% to 22%; I²=98.1; p<0.001) and 33% (95% CI: 22% to 44%; p<0. 001), respectively.

CONCLUSION

The prevalence of malnutrition in old African people is high and differs by setting, assessment tool and country of residence. Hence, due attention to geriatric nutrition is mandatory, and the need for a valid, reliable and simple screening tool should be thought of.

Prevalence of malnutrition among old age people in Africa

Background: Improved health care and rising life expectancy are creating a growing pool of old age people all over the world, including Africa. Malnutrition in the old age people is associated with both short- and long-term negative health outcomes. However, the reported burdens of malnutrition are fragmented and inconsistent, where more compiled evidence is warranted to aid decision-makers. Hence, this paper is aimed to estimate the pooled prevalence of malnutrition among old age people in Africa. Methods: A systematic search for research reporting the prevalence of malnutrition among old age people (aged above 60 years) was conducted from HINARI/PubMed and Google Scholar databases using combination keywords. Published articles in English language starting from January 2000 to October 2021 were screened. We presented the results based on the standard for reporting systematic review and meta-analysis of observational studies. A random-effect meta-analysis was done to estimate the prevalence of malnutrition along with the 95% confidence intervals. The publication bias was assessed using the funnel plot. Results: A total of 1,442 studies were retrieved based on the search strategy, where only 36 studies (n = 15,266 participants) reported from 11 African countries were included for meta-analysis. The reported prevalence of malnutrition ranges from 2.2 to 77.3% across Africa. Overall, the pooled prevalence of malnutrition was 18% (95% CI: 15-22; I2 = 98.1; p < 0.001). The prevalence is higher in the Central Africa (3.8%; 95% CI: 3.2-4.4), in the community (3.1%; 95% CI: 2.7-3.7), and among advanced age (3.5%; 95% CI: 2.3-5.4). Conclusion: The prevalence of malnutrition in African old age people is high and differs by setting, assessment tool, and country of residence. Hence, due attention to geriatric nutrition is mandatory, and the need for a valid, reliable, and simple screening tool should be thought of.

Nutritional status and associated factors of older persons in sub-Saharan Africa: a scoping review

BACKGROUND

The older person population is rapidly increasing globally, including sub-Saharan Africa (SSA). Concurrently, malnutrition is also increasing among older persons in SSA, with a dearth of empirical evidence on nutritional status and associated factors among the older persons in the region to inform effective interventions to promote healthy ageing.

AIM/OBJECTIVE

This review assessed the nutritional status and associated factors among older persons in SSA.

METHOD

PubMed, Google Scholar, and Cochrane Library electronic databases were searched for published articles from 2010 to 2021 using keywords and Boolean logic. Also, we carried out a free web-based search to retrieve other relevant evidence that assesses the older persons' nutritional status. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow chart was used to appraise the research articles that responded to the study's research questions.

FINDINGS

Twenty studies met the inclusion criteria, from which data were extracted as findings. The malnutrition prevalence was between 6 to 54% among older persons in SSA. We found that the prevalence of malnutrition vary and could be as high as 28.4% in a low socio-economic status area. Of these studies, twelve (12) provided data on undernutrition with prevalence ranging from 2.9 to 41%;10 provided data on overweight (8.1-54.1%) and 5 on obesity (2.7-44.7%). Seventeen of the studies evaluated factors associated with malnutrition; 4 studies revealed the association between socioeconomic status and malnutrition, 7 studies reported a significant association between dietary habits and malnutrition. Four studies showed an association between educational status and malnutrition. Disease conditions associated with malnutrition were reported in four of the studies.

CONCLUSION

This review shows that malnutrition is a problem among older persons in SSA coupled with many risk factors which should be given critical attention. We recommend nutrition education for older persons as well as the development of nutrition interventions for this vulnerable group.

Phenotypic Characterization of Chronic Kidney Patients Through Hierarchical Clustering

Chronic kidney disease is a major public health problem around the world and this disease early diagnosis is still a great challenge as it is asymptomatic in its early stages. Thus, in order to identify variables capable of assisting CKD diagnosis and monitoring, machine learning techniques and statistical analysis use has shown itself to be extremely promising. For this work, unsupervised machine learning, statistical analysis techniques and discriminant analysis were used.Clinical Relevance - Discriminating variables characterization assist to differentiate groups of patients in different stages of Chronic Kidney Disease and it has important outcomes in the development of future models to aid clinical decision-making, as they can generate models with a greater predictive capacity for Chronic Kidney Disease, predominantly aiding the early diagnosis capacity of this pathology.

Nutritional status and associated factors among community-dwelling elderly

BACKGROUND AND AIMS

Although the ageing of the Cameroonian population is a public health issue in the coming years, the nutritional status of the elderly is unknown. The aim of the study was to assess the nutritional status, health status and associated socio-demographic factors among elderly in Cameroon.

METHODS

A cross-sectional study of 599 elderly (aged ≥ 60) was conducted in urban and rural areas. Several socio-demographic, sanitary, and anthropometric (weight, height, body mass index (BMI), Waist Circumference (WC), Mid-Upper Arm Circumference (MUAC)) data were collected. Nutritional status was defined according to WHO. Multinomial analysis was performed to identify factors associated with nutritional status. The threshold of statistical significance was 5%.

RESULTS

The population, representative of the elderly, was aged 68.9 ± 7.2 years, with sex ratio M/F = 0.93, weight 68.5 ± 14.7 kg, BMI 24.7 ± 5.3, WC 90.1 ± 12.8 cm and MUAC 28.2 ± 5.0 cm. According to BMI, undernutrition was 19.7%, normal status 37.9%, overweight 24.9%, obesity 17.5%. The concordance for undernutrition between BMI and MUAC was weak (kappa = 0.3). In multinomial analysis, only no medication was negatively associated with undernutrition (OR = 0.3). Obesity was positively associated with the urban environment (OR = 4.8) and inactivity (OR = 2.9) and negatively associated with male gender (OR = 0.4), widowed (OR = 0.2), head of household (OR = 0.4), no income (OR = 0.3), one pathology (OR = 0.4), no medication (OR = 0.2), having normal diastolic pressure (OR = 0.2).

CONCLUSIONS

Undernutrition and obesity (more frequent in women, and in urban area) affect 37.2% of the elderly. These nutritional disorders are a public health problem that cannot be ignored.

Association between alcohol intake and overweight and obesity: a systematic review and dose-response meta-analysis of 127 observational studies

Several studies have assessed the relationship between alcohol intake and overweight/obesity; however, the reported results are inconsistent. Therefore, the present systematic review and dose-response meta-analysis of observational studies was designed to investigate the association between alcohol intake and general and abdominal obesity among the adults. Literature search was conducted in the PubMed/Medline and Web of Science databases up to August 2020. Odds ratio (OR), risk ratio (RR), or hazard ratio (HR) with 95% confidence interval (95% CI) were used to pool effect size. To conduct dose-response meta-analysis, amount of alcohol intake was classified into three categories including light (<14 g/d), moderate (14-28 g/d), and heavy (>28 g/d). In the present study, 127 eligible studies were included. In cohort studies, there was no significant association between alcohol drinking and risk of overweight (OR: 0.93, 95% CI: 0.46 to 1.89), obesity (OR: 0.84, 95% CI: 0.52 to 1.37), overweight/obesity (OR: 1.15, 95% CI: 0.84 to 1.58), and abdominal obesity (OR: 1.13, 95% CI: 0.90 to 1.41). In cross-sectional studies, alcohol intake was associated with the increased odds of overweight (OR: 1.11, 95% CI: 1.05 to 1.18), overweight/obesity (OR: 1.23, 95% CI: 1.11 to 1.37), and abdominal obesity (OR: 1.19, 95% CI: 1.09 to 1.29); but not obesity (OR: 1.03, 95% CI: 0.95 to 1.12). Results of dose-response analysis indicated that heavy alcohol drinking was positively associated with odds of overweight (OR: 1.12, 95% CI: 1.01 to 1.24), overweight/obesity (OR: 1.32, 95% CI: 1.16 to 1.51), and abdominal obesity (OR: 1.25, 95% CI: 1.12 to 1.38) compared to non- or light alcohol drinking. There was no publication bias among studied on outcomes of interest. In conclusion, our results revealed alcohol drinkers, especially heavy alcohol drinkers, had increased odds of overweight, overweight/obesity, and abdominal obesity than non-alcohol drinker or light alcohol drinkers among cross-sectional studies but not cohort studies.

Sleeve Gastrectomy Versus Roux-en-Y Gastric Bypass in the Elderly: 1-Year Preliminary Outcomes in a Randomized Trial (BASE Trial)

PURPOSE

Despite the increasing prevalence of elderly obese patients, bariatric surgery remains controversial in this population. Recent publications have focused on perioperative safety, but few studies have addressed clinical outcomes.

OBJECTIVES

This study aimed to evaluate 1-year outcomes of laparoscopic sleeve gastrectomy (LSG) compared to laparoscopic Roux-en-Y gastric bypass (LRYGB) in patients 65 years or older.

METHODS

Thirty-six elderly obese patients were recruited for an open-label randomized trial from September 2017 to May 2019, comparing LSG to LRYGB. One-year outcomes were evaluated based on weight loss, functionality, and control of clinical conditions.

RESULTS

The median age (67 × 67 years; p=0.67) and initial body mass index (BMI) (46.3 × 51.3 kg/m²; p=0.28) were similar between groups. Preoperative BMI (after weight loss pre-operative treatment) was higher in LRYGB group (41.9 × 47.6 kg/m²; p= 0.03). After 12 months, EWL and TWL were higher in LRYGB group (60 × 68%; p=0.04; 24.9 × 31.4%; p<0.01). HbA1c reduction was higher after LRYGB (-1.1 × -0.5%; p<0.01) as well as LDL control (-27.5 × +11.5 mg/dL p= 0.02). No difference was noted between LRYGB and LSG concerning hypertension control, triglycerides, HDL, and functionality.

CONCLUSION

Weight loss, diabetes, and LDL control were better achieved with LRYGB after 12 months.

Comorbidities and the COVID-19 pandemic dynamics in Africa

The debate around the COVID‐19 response in Africa has mostly focused on effects and implications of public health measures, in light of the socio‐economic peculiarities of the continent. However, there has been limited exploration of the impact of differences in epidemiology of key comorbidities, and related healthcare factors, on the course and parameters of the pandemic. We summarise what is known about (a) the pathophysiological processes underlying the interaction of coinfections and comorbidities in shaping prognosis of COVID‐19 patients, (b) the epidemiology of key coinfections and comorbidities, and the state of related healthcare infrastructure that might shape the course of the pandemic, and (c) implications of (a) and (b) for pandemic management and post‐pandemic priorities. There is a critical need to generate empirical data on clinical profiles and the predictors of morbidity and mortality from COVID‐19. Improved protocols for acute febrile illness and access to diagnostic facilities, not just for SARS‐CoV‐2 but also other viral infections, are of urgent importance. The role of malaria, HIV/TB and chronic malnutrition on pandemic dynamics should be further investigated. Although chronic non‐communicable diseases account for a relatively lighter burden, they have a significant effect on COVID‐19 prognosis, and the fragility of care delivery systems implies that adjustments to clinical procedures and re‐organisation of care delivery that have been useful in other regions are unlikely to be feasible. Africa is a large region with local variations in factors that can shape pandemic dynamics. A one‐size‐fits‐all response is not optimal, but there are broad lessons relating to differences in epidemiology and healthcare delivery factors, that should be considered as part of a regional COVID‐19 response framework.

Predictive formulas for estimation of height in sub-Saharan African older people: A new formula (EPIDEMCA study)

OBJECTIVES

Chumlea's formulas are a way of predicting height from knee height (KHt), including among individuals >60 y of age who cannot stand upright. However, the formulas were developed with white and African American people and have not yet been validated in native Africans >60 y of age. The aims of the study were to assess Chumlea's formulas in older people in central Africa and to propose a new validated formula for the same population.

METHODS

Height (MHt) and KHt were measured in a population of individuals >65 y of age from the Republic of Congo and the central African Republic. Predicted height (PHt) was calculated using Chumlea's formulas for the American black population (CBP) and for whites (CC). The percentages of accurate predictions (±5 cm) were compared between MHt and PHt. A new formula was estimated after randomization in a derivation sample (n = 877) and assessed for accuracy in a validation sample (n = 877).

RESULTS

The study included 1754 individuals. Prediction was accurate (±5 cm) in 66.8% and 63.2% of CBP and CC, respectively. Overestimation was as high as 24.1% and 29%, respectively. Because an overestimation is unacceptable in clinical practice and population surveys, a new formula was proposed: height (cm) = 72.75 + (1.86 × KHt [cm]) - (0.13 × age [y]) + 3.41 × sex (0: women; 1: men). This new formula significantly increases accuracy (71.3%) and decreases overestimation (14.7%). The nutritional status based on body mass index did not differ with the MHt and the PHt by the new formula.

CONCLUSION

Chumlea's formulas provided a poor estimate of height in this population sample. The proposed formula more accurately estimates height in older native Africans. This formula should be tested in other sub-Saharan African countries to extend its use in clinical practice and in future studies.

A Retrospective Population Study to Develop a Predictive Model of Prediabetes and Incident Type 2 Diabetes Mellitus from a Hospital Database in Japan Between 2004 and 2015

Background

Type 2 diabetes mellitus is a global public health problem. Prediabetes may be reversed by weight loss, diet, and lifestyle changes. However, without intervention, between 30–50% of individuals with prediabetes develop type 2 diabetes. This retrospective population study was conducted to develop a predictive model of prediabetes and incident type 2 diabetes mellitus using data from 2004 to 2015 from the DRYAD Japanese hospital database.

Material/Methods

A retrospective longitudinal population study was conducted using the DRYAD database from Murakami Memorial Hospital, Gifu, Japan, to construct a predictive model for prediabetes and incident type 2 diabetes mellitus in the population. Univariate analysis and multivariate analysis were performed to identify the variables that were associated with prediabetes. These variables were used to construct (75% samples) and verify (25% samples) the predictive model.

Results

From 2004 to 2015, a total of 11,113 cases were identified. Multivariate logistic regression analysis included the six variables of age, waist circumference, smoking history, the presence of fatty liver, fasting blood glucose (FBG), and glycated hemoglobin (HbA1c) level. Data were used to construct (75% samples) and verify (25% samples) in a predictive model. The area under the receiver operating characteristic (ROC) curve (AUC) of the predictive model was 0.87 (0.85–0.89) in the training cohort and 0.87 (0.86–0.90) in the validation cohort.

Conclusions

A prognostic model based on six variables was predictive for incident type 2 diabetes mellitus and prediabetes in a healthy population in Japan.

Social and Economic Factors and Malnutrition or the Risk of Malnutrition in the Elderly: A Systematic Review and Meta-Analysis of Observational Studies

Malnutrition in the elderly could be tackled by addressing socioeconomic factors. This study aimed to determine the magnitude of the relationship between socioeconomic factors and the malnutrition or malnutrition risk (MR) in the elderly. The PubMed and SCOPUS databases were searched for observational studies that included assessment of malnutrition or/and MR and socioeconomic variables (educational level, living alone, marital status, income and occupational level, feeling of loneliness, place of residence, and food expenditure) in ≥60-year-old subjects, published in English among 2000–2018 (PROSPERO: CRD42019137097). The systematic review included 40 observational studies (34 cross-sectional and 4 cohort studies) and 16 cross-sectional studies in the meta-analysis (34,703 individuals) of malnutrition and MR in relation to low educational level (Odds Ratio (OR): 1.48; 95% Confidence Interval (CI): 1.33–1.64; p < 0.001), living alone (OR: 1.92; 95% CI: 1.73–2.14; p < 0.001), being single, widowed, or divorced (OR: 1.73; 95% CI: 1.57–1.90; p < 0.001), and low income level (OR: 2.69; 95% CI: 2.35–3.08; p < 0.001), and considering these four socioeconomic factors, malnutrition and MR is associated with them (OR: 1.83; 95% CI: 1.73–1.93; p < 0.001). Malnutrition and MR could be reduced by increasing economic level, supporting people living alone or being single, widowed, and divorced, and improving lifelong learning.

Predictors of undernutrition among the elderly in Sodo zuriya district Wolaita zone, Ethiopia

Background

In any society, the elderly are among the vulnerable and high risk groups with regard to health status. In persons over the age of 60 years, nutrition is among the important determinants of health. However, undernutrition among the elderly is often under diagnosed and/or neglected. Hence, in this study, we looked at prevalence and factors associated with undernutrition among the elderly.

Methods

A community based cross-sectional study was conducted at Sodo Zuriya district. Multi-stage systematic sampling method was used to select 578 elderly. A structured questionnaire was used to collect data on socio-demographics, dietary diversity, and health status of the elderly.Measurements of weight and height were taken using digital weighing scale and stadio-meter, respectively. Data was entered and cleaned in Epi-Data version3.1and exported to SPSS version 20 for analysis. Binary and multivariate logistic regressions were done and odds ratios with 95% confidence intervals were calculated.

Results

The overall prevalence of undernutrition was 17.1%. On multivariate logistic regression, being unable to read and write (AOR = 2.09), not being married (AOR = 2.02), history of decline in food intake (AOR = 2.1), smoking (AOR = 4.9) and monthly income <$20 (AOR = 7.5) were factors positively associated with undernutrition.

Conclusion

The study revealed that prevalence of undernutrition in the district was relatively high. Hence, it is among the major public health burdens in the district. Hence, to improve nutritional status of elderly the district health office and health professionals should consider behavioral support interventions to assist in cessation of smoking. There is also a need to financially empower the elderly in the district.

Development of a Computational Model to Predict Excess Body Fat in Adolescents through Low Cost Variables

BACKGROUND

Excess body fat has been growing alarmingly among adolescents, especially in low income and middle income countries where access to health services is scarce. Currently, the main method for assessing overweight in adolescents is the body mass index, but its use is criticized for its low sensitivity and high specificity, which may lead to a late diagnosis of comorbidities associated with excess body fat, such as cardiovascular diseases. Thus, the aim of this study was to develop a computational model using linear regression to predict obesity in adolescents and compare it with commonly used anthropometric methods. To improve the performance of our model, we estimated the percentage of fat and then classified the nutritional status of these adolescents.

METHODS

The model was developed using easily measurable socio-demographic and clinical variables from a database of 772 adolescents of both genders, aged 10-19 years. The predictive performance was evaluated by the following metrics: accuracy, sensitivity, specificity, and area under ROC curve. The performance of the method was compared to the anthropometric parameters: body mass index and waist-to-height ratio.

RESULTS

Our model showed a high correlation (R = 0.80) with the body fat percentage value obtained through bioimpedance. In addition, regarding discrimination, our model obtained better results compared to BMI and WHtR: AUROC = 0.80, 0.64, and 0.55, respectively. It also presented a high sensitivity of 92% and low false negative rate (6%), while BMI and WHtR showed low sensitivity (27% and 9.9%) and a high false negative rate (65% and 53%), respectively.

CONCLUSIONS

The computational model of this study obtained a better performance in the evaluation of excess body fat in adolescents, compared to the usual anthropometric indicators presenting itself as a low cost alternative for screening obesity in adolescents living in Brazilian regions where financial resources are scarce.

The prevalence and characteristics of frailty by frailty phenotype in rural Tanzania

Background

The frailty phenotype is defined by the presence of three from the following five clinical features: weakness, slow walking speed, unintentional weight loss, exhaustion, and low physical activity. It has been widely applied in different research and clinical contexts, including across many low and middle-income countries. However, there is evidence that the operationalisation of each component of the frailty phenotype significantly alters its characteristics and predictive validity, and care is needed when applying the phenotype across settings. The study’s objective was to operationalise the frailty phenotype in a rural Tanzanian population of older community-dwelling adults.

Methods

Consenting adults aged ≥60 years, and resident in five randomly selected villages of Hai district Demographic Surveillance Site, were eligible to participate in this cross-sectional study. From a screened sample of 1207 older adults, 235 were randomised and consented to an assessment of their frailty status by the frailty phenotype. Trained research fieldworkers (Tanzanian medical doctors and nurses) carried out measurements and questionnaires at local village centres or at participants’ homes.

Results

The prevalence of the frailty phenotype, calculated from complete data for 196 participants, was 9.25% (95% CI 4.39–14.12) When missing data were counted as meeting frailty criterion (i.e. missing due to inability to perform an assessment), the prevalence increased to 11.22% (95% CI 7.11–15.32). Frailty by phenotype criteria was more common in older age groups, and was associated with self-assessed poor health and depression symptoms.

Conclusions

Frailty can be successfully estimated using the frailty phenotype, however there are challenges in its operationalisation cross-culturally. Further work is needed to explore the potential clinical application of the frailty phenotype in such settings.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0967-0) contains supplementary material, which is available to authorized users.