Gait speed and its associated factors among older black adults in Sub-Saharan Africa: Evidence from the WHO study on Global AGEing in older adults (SAGE)

Gait speed is an essential predictor of functional and cognitive decline in older adults. The study aimed to investigate the gait speed of older adults in Ghana and South Africa and to determine its associated factors, as the Sub-Saharan representatives in the World Health Organization's Study on Global AGEing in Older Adults (SAGE). A secondary analysis of data from the SAGE study which consists of nationally representative data involving participants aged ≥50+ years with smaller samples of younger adults aged 18-49 years in Ghana and South Africa was conducted. SAGE study employed a multistage, stratified clustered sample design and involved the use of a standardised questionnaire to obtain participants' (n = 5808) demographic, anthropometric and gait speed information. The standard 4 metre-gait speed was used. Median gait speed for the study group, which comprised African/Black participants aged ≥50+ years was 0.769(Q1 = 0.571, Q3 = 0.952)m/s for males and 0.667 (Q1 = 0.500,Q3 = 0.833)m/s for females. For every unit increase in age, the odds of being in a higher-ranked gait speed category was 0.96(95%CI 0·96, 0·97, p<0.001) times that of the previous age. Females had odds of 0.55 (95%CI 0.50, 0.61, p<0.001) of recording higher gait speed, as compared to males. Rural dwellers had odds of 1.43 (95%CI 1.29, 1.58, p < 0.001) of being in a higher-ranked category of gait speed compared to urban dwellers. Underweight (OR = 0.85, 95%C1 = 0.73-1.00, p<0.05) and obesity (OR = 0.53, 95%CI = 0.46-0.61, p<0.001) were associated with slower gait speed. Amongst functional indices, the World Health Organization Disability Assessment Schedule (WHODAS) score was the biggest determinant of gait speed. Having a "Severe/Extreme" WHODAS score had the strongest association with gait speed (OR = 0.18, 95%CI = 0.14-0.23, p<0.001). These gait speed results provide an essential reference for older adults' care in Ghana and South Africa.

Application of Hierarchical/Multilevel Models and Quality of Reporting (2010-2020): A Systematic Review

Introduction

Multilevel models have gained immense popularity across almost every discipline due to the presence of hierarchy in most data and phenomena. In this paper, we present a systematic review on the adoption and application of multilevel models and the important information reported on the results generated from the use of these models.

Methods

The review was performed by searching Google Scholar for original research articles on the application of multilevel models published between 2010 and 2020. The search strategy involved topics such as "multilevel models," "hierarchical linear models," and "mixed models with hierarchy." The search placed more emphasis on the application of hierarchical models in any discipline but excluded software methodological development and related articles.

Results

A total of 121 articles were initially obtained from the search results. However, 65 articles met the inclusion criteria for the review. Out of the 65 articles reviewed, 46.2% were related to health/epidemiology, 15.4% to education and psychology, and 16.9% to social life. The majority of the articles (78.5%) were two-level models, and most of these studies modelled univariate responses. However, the few that modelled more than one response modelled them separately. Moreover, 83.1% were cross-sectional design, and 9.2% and 6.2% were longitudinal and repeated measures, respectively. Moreover, a little over half (55.4%) of articles reported on the intraclass correlation measure, and all articles indicated the response variable distribution where most (47.7%) were normally distributed. Only 58.5% of articles reported on the estimation methods used as Bayesian (20%) and MLE (18.5%). Again, model validation measures and statistical software were reported in 70.8% and 90.8% articles, respectively.

Conclusion

There is an increase in the utilization of multilevel modelling in the last decade, which could be attributed to the presence of clustered and hierarchically correlated data structures. There is a need for improvement in the area of measurement and reporting on the intraclass correlation, parameter estimation, and variable selection measures to further improve the quality of the application of multilevel models. The integration of spatial effects into multilevel models is very limited and needs to be explored in the future.

Examining the risk factors for overweight and obesity among women in Ghana: A multilevel perspective

Overweight/obesity prevalence is on the increase in epidemic proportions across Low- and Middle-Income countries (LMICs). The public health burden associated with obesity/overweight cannot be underestimated due to its association with chronic health outcomes. This study investigated the individual- and community level risk factors for obesity/overweight among reproductive women. The data used consist of 4393 reproductive women and form part of the 2014 Ghana Demographic and Health Survey (GDHS). Information on these women are clustered within 427 communities. A 2-tier random intercept multilevel logistic model was used to assess the effect of individual- and community level factors on the likelihood of a woman to be obese/overweight. The obesity/overweight prevalence among reproductive women was estimated to be 35.5% (95% CI: 34.04, 36.90%), which significantly differed across clusters. Most at risk were women from middle-income households (aOR = 2.85; 95% CI: 2.28, 3.56), upper-income households (aOR = 5.019, 95% CI: 3.85, 6.55), attaining secondary education (aOR = 1.74; 95% CI: 1.41, 2.16), and higher (aOR = 1.63; 95% CI: 1.14, 2.33), old age (20-29 years (aOR = 4.26; 95% CI: 3.142,5.78); 30-39 years (aOR = 8.59; 95% CI: 6.15, 12.00); 40-49 years (aOR = 12.81; 95% CI: 9.10, 18.16)). Significant differences in the probability of being overweight/obese between different communities were observed (MOR = 1.39). The high prevalence of overweight/obesity requires urgent public health interventions to prevent future public health crises. Efforts to strengthen the healthcare system, encourage lifestyle modification, and public health education are needed to solidify the gains of ensuring a healthy population by 2030 (SDG 3).

Structural equation modeling of pedestrian behavior at footbridges in Ghana

This study was undertaken to fill the information gap by exploring pedestrian behavior at footbridges in the Greater Accra and Kumasi Metropolitan areas of Ghana. Further, the study modelled the behavior of 69,840 pedestrians at the footbridges using Structural Equation Modeling (SEM). Pedestrians were observed as users and non-users of seven selected footbridges in the morning (7:00 am-9:00 am), afternoon (11:00 am-1:00 pm), and evening (3:00 pm-5:00 pm) periods for seven consecutive days (Monday to Sunday). Selected footbridges were characterized by traffic generators as schools, shopping malls, bus stops, office complexes, and restaurants in different matrices. The results showed that 30.7% of the observed pedestrians did not use the footbridges, males and young pedestrians were more likely not to use the footbridges as opposed to females and the elderly with more than half of observed pedestrians carrying luggage or load. Footbridge users were more likely to talk and hold phones than non-users and the elderly were more likely to run and ride compared to young pedestrians. Officials of the National Road Safety Authority should carry out effective public education on pedestrian safety targeting males and young pedestrians to encourage the use of pedestrian footbridges.

Spatial analysis of the prevalence of obesity and overweight among women in Ghana

OBJECTIVE

Identifying hot spots for the overweight aids in effective public health interventions due to the associated public health burden and morbidities. This study, therefore aimed to explore and determine the spatial disparities in the overweight/obesity prevalence among women in Ghana. The study also aims at modelling the average body mass index (BMI) values using the spatial regression and the performance compared with the standard regression model.

DESIGN

This is a cross-sectional study using data from the 2014 Ghana Demographic and Health Survey (GDHS).

SETTING

The study was set in Ghana.

PARTICIPANTS AND METHODS

Data on 4393 non-pregnant women aged 15-49 years from the 2014 GDHS. Both global (Moran's I) and the local indicators for spatial dependence were examined through the mapped BMI values across the country by clusters. An estimated spatial lag model was used to explain the spatial differences in the average body sizes of women.

RESULTS

The overall prevalence of overweight/obesity among reproductive women in Ghana was 35.4%, and this was highly prevalent among educated women (p<0.001), those from wealthy households (p<0.001) and dwelling in an urban setting (p<0.001). Significant clustering (Moran's I=0.3145, p<0.01) of overweight/obesity was observed with hot spots (clustering) in Greater Accra, Central, Western and Ashanti regions. The spatial lag model was the best fit based on the Likelihood ratio test and the Akaike information criterion and Bayesian information criterion values. The mean age of women and household wealth were significant factors accounting for the increase in the average cluster body size (BMI) of women and the spatial differences.

CONCLUSION

The prevalence of overweight/obesity was high and spatially clustered in the southern, middle and coastal regions. Geographic specific and effective public health interventions and strategies are needed to address the growing morbidity burden associated with the rise in the average body sizes of reproductive women.