Birth weight mediates the association of maternal undernutrition with child undernutrition prevalence in West Africa.

BACKGROUND: Maternal nutritional status before and during pregnancy is an important determinant of foetal health. In West Africa, maternal and child undernutrition remains a major public health problem and it is important to establish the mechanistic pathway linking the two disorders to help address the problem. We therefore assessed the mediating role of low birth weight (LBW) in the relationship of maternal undernutrition with child undernutrition in West Africa. METHODS: We included recent (2010-2019) DHS data from thirteen West African countries. Poisson regression model with robust standard errors was used to assess the relationship between maternal undernutrition (body mass index and anaemia) and child undernutrition (stunting, wasting, underweight, and anaemia). Structural equation modelling was used to conduct the mediation analysis. RESULTS: Prevalence of stunting, wasting, underweight, and anaemia among under-five children in West Africa was found to be 32.4%, 8.1%, 20.1%, and 71.5%, respectively. We found children of underweight mothers to be more likely to be undernourished (stunted, wasted, and underweight) and anaemic compared to children of normal-weight mothers. Also, children of anaemic mothers were more likely to be stunted and anaemic but not wasted compared with children of non-anaemic mothers. LBW mediated the observed relationships between maternal BMI and childhood stunting (22.6%), and maternal anaemia and childhood stunting (24.9%), wasting (11.7), and anaemia (6.6%). CONCLUSION: We found maternal undernutrition to be associated with child undernutrition in West Africa with LBW noted to be a mediator of the observed relationship. We recommend that, to address the child undernutrition problem in West Africa, governments and policymakers must integrate measures to address the burden of LBW.

Predictors of Multimorbidity (Defined as Diabetes + Hypertension) Amongst Males Aged 15-54 in India: An Urban/Rural Split Analysis.

Objectives: This study aimed to determine which sociodemographic and lifestyle factors may act as predictors of multimorbidity (defined as diabetes + hypertension) amongst men aged 15-54 within urban and rural areas of India. Methods: Data from the latest 2019-2021 India NFHS-5 survey were utilized. Presumed cases of multimorbidity were defined as men who had DM + HTN. A total of 22,411 men in urban areas and 66,768 rural men were analyzed using mixed-effect multi-level binary logistic regression models. Results: Various predictors were found to have a statistically significant association to multimorbidity. Urban areas: Age, region of residence, wealth, religion, occupation, and BMI. Rural areas: Age, education, region of residence, wealth, occupation, caste, BMI, alcohol consumption, media exposure, and tobacco consumption. Conclusion: Departing from the broad operational definitions often studied within literature, this study provided insight into one of the most prevalent specific multimorbidities across India. The urban/rural split analyses revealed substantial differences in high-risk characteristics across both areas, which have commonly been overlooked. These findings may better inform policymakers and assist in effectively reducing multimorbidity-related burden through area-specific preventative programs.

Bayesian spatio-temporal analysis of malaria prevalence in children between 2 and 10 years of age in Gabon.

BACKGROUND: Gabon still bears significant malaria burden despite numerous efforts. To reduce this burden, policy-makers need strategies to design effective interventions. Besides, malaria distribution is well known to be related to the meteorological conditions. In Gabon, there is limited knowledge of the spatio-temporal effect or the environmental factors on this distribution. This study aimed to investigate on the spatio-temporal effects and environmental factors on the distribution of malaria prevalence among children 2-10 years of age in Gabon. METHODS: The study used cross-sectional data from the Demographic Health Survey (DHS) carried out in 2000, 2005, 2010, and 2015. The malaria prevalence was obtained by considering the weighting scheme and using the space-time smoothing model. Spatial autocorrelation was inferred using the Moran's I index, and hotspots were identified with the local statistic Getis-Ord General Gi. For the effect of covariates on the prevalence, several spatial methods implemented in the Integrated Nested Laplace Approximation (INLA) approach using Stochastic Partial Differential Equations (SPDE) were compared. RESULTS: The study considered 336 clusters, with 153 (46%) in rural and 183 (54%) in urban areas. The prevalence was highest in the Estuaire province in 2000, reaching 46%. It decreased until 2010, exhibiting strong spatial correlation (P < 0.001), decreasing slowly with distance. Hotspots were identified in north-western and western Gabon. Using the Spatial Durbin Error Model (SDEM), the relationship between the prevalence and insecticide-treated bed nets (ITNs) coverage was decreasing after 20% of coverage. The prevalence in a cluster decreased significantly with the increase per percentage of ITNs coverage in the nearby clusters, and per degree Celsius of day land surface temperature in the same cluster. It slightly increased with the number of wet days and mean temperature per month in neighbouring clusters. CONCLUSIONS: In summary, this study showed evidence of strong spatial effect influencing malaria prevalence in household clusters. Increasing ITN coverage by 20% and prioritizing hotspots are essential policy recommendations. The effects of environmental factors should be considered, and collaboration with the national meteorological department (DGM) for early warning systems is needed.

Determinants and spatial factors of anemia in women of reproductive age in Democratic Republic of Congo (drc): a Bayesian multilevel ordinal logistic regression model approach.

BACKGROUND: As a global public health problem, anemia affects more than 400 million women of reproductive age worldwide, mostly in Africa and India. In the DRC, the prevalence of anemia has decreased slightly from 52.9% in 2007, to 46.4% in 2012 and 42.4% in 2019. However, there is considerable regional variation in its distribution. The aim of this study is to determine the factors contributing to anemia in women of reproductive age and to explore its spatial distribution in the DRC. METHODS: Based on the Bayesian Multilevel Spatial Ordinal Logistic Regression Model, we used the 2013 Democratic Republic of Congo Demographic and Health Survey (DHS-DRC II) data to investigate individual and environmental characteristics contributing to the development of anemia in women of reproductive age and the mapping of anemia in terms of residual spatial effects. RESULTS: Age, pregnancy status, body mass index, education level, current breastfeeding, current marital status, contraceptive and insecticide-treated net use, source of drinking water supply and toilet/latrine use including the province of residence were the factors contributing to anemia in women of reproductive age in DRC. With Global Moran's I = -0.00279, p-value ≥ 0.05, the spatial distribution of anemia in women of reproductive age in DRC results from random spatial processes. Thus, the observed spatial pattern is completely random. CONCLUSION: The Bayesian Multilevel Spatial Ordinal Logistic Regression statistical model is able to adjust for risk and spatial factors of anemia in women of reproductive age in DRC highlighting the combined role of individual and environmental factors in the development of anemia in DRC.

Analysis of predictors of malnutrition in adult hospitalized patients: social determinants and food security.

Background: Malnutrition in hospitalized patients is becoming a priority during the patient care process due to its implications for worsening health outcomes. It can be the result of numerous social factors beyond clinical ones. This study aimed to evaluate the link between these various risk factors considered social determinants of health, food security levels, and malnutrition and to identify potential predictors. Methods: A cross-sectional observational study was conducted on a random sample of adult patients in five different hospitals in Lebanon. Malnutrition was assessed using the Global Leadership Initiative on Malnutrition (GLIM) criteria. Patients were interviewed to collect social and economic characteristics and were categorized into four criteria: (1) area of residence (urbanization level), (2) level of education, (3) employment status, and (4) source of health coverage. The food security level was screened by a validated two-question tool, adapted from the US Department of Agriculture Household Food Security Survey, targeting both quantity and quality. Results: In a random sample of 343 patients, the prevalence of malnutrition according to the GLIM criteria was 35.6%. Patients with low levels of food security, mainly low quality of food, had higher odds of being malnourished (OR = 2.93). Unemployed or retired patients and those who have only completed only elementary school had higher odds of being diagnosed with malnutrition as compared to those who were employed or had university degrees, respectively (OR = 4.11 and OR = 2.33, respectively). Employment status, education level, and type of health coverage were identified as predictors of malnutrition in the multiple regression model. Household location (urban vs. rural) was not associated with malnutrition. Conclusion: The social determinants of health identified in our study, mainly the level of education and income level, in addition to food security, were identified as predictors of malnutrition in hospitalized patients. These findings should guide healthcare professionals and national policies to adopt a broader perspective in targeting malnutrition by including social determinants in their nutrition care.

Prevalence of Malnutrition in Hospitalized Patients in Lebanon Using Nutrition Risk Screening (NRS-2002) and Global Leadership Initiative on Malnutrition (GLIM) Criteria and Its Association with Length of Stay.

(1) Background: Prevalence studies on hospital malnutrition are still scarce in the Middle East region despite recent global recognition of clinical malnutrition as a healthcare priority. The aim of this study is to measure the prevalence of malnutrition in adult hospitalized patients in Lebanon using the newly developed Global Leadership Initiative on Malnutrition tool (GLIM), and explore the association between malnutrition and the length of hospital stay (LOS) as a clinical outcome. (2) Methods: A representative cross-sectional sample of hospitalized patients was selected from a random sample of hospitals in the five districts in Lebanon. Malnutrition was screened and assessed using the Nutrition Risk Screening tool (NRS-2002) and GLIM criteria. Mid-upper arm muscle circumference (MUAC) and handgrip strength were used to measure and assess muscle mass. Length of stay was recorded upon discharge. (3) Results: A total of 343 adult patients were enrolled in this study. The prevalence of malnutrition risk according to NRS-2002 was 31.2%, and the prevalence of malnutrition according to the GLIM criteria was 35.6%. The most frequent malnutrition-associated criteria were weight loss and low food intake. Malnourished patients had a significantly longer LOS compared to patients with adequate nutritional status (11 days versus 4 days). Handgrip strength and MUAC measurements were negatively correlated with the length of hospital stay. (4) Conclusion and recommendations: the study documented the valid and practical use of GLIM for assessing the prevalence and magnitude of malnutrition in hospitalized patients in Lebanon, and highlighted the need for evidence-based interventions to address the underlying causes of malnutrition in Lebanese hospitals.

Bayesian Hierarchical Framework from Expert Elicitation in the South African Coal Mining Industry for Compliance Testing.

Occupational exposure assessment is important in preventing occupational coal worker's diseases. Methods have been proposed to assess compliance with exposure limits which aim to protect workers from developing diseases. A Bayesian framework with informative prior distribution obtained from historical or expert judgements has been highly recommended for compliance testing. The compliance testing is assessed against the occupational exposure limits (OEL) and categorization of the exposure, ranging from very highly controlled to very poorly controlled exposure groups. This study used a Bayesian framework from historical and expert elicitation data to compare the posterior probabilities of the 95th percentile (P95) of the coal dust exposures to improve compliance assessment and decision-making. A total of 10 job titles were included in this study. Bayesian framework with Markov chain Monte Carlo (MCMC) simulation was used to draw a full posterior probability of finding a job title to an exposure category. A modified IDEA ("Investigate", "Discuss", "Estimate", and "Aggregate") technique was used to conduct expert elicitation. The experts were asked to give their subjective probabilities of finding coal dust exposure of a job title in each of the exposure categories. Sensitivity analysis was done for parameter space to check for misclassification of exposures. There were more than 98% probabilities of the P95 exposure being found in the poorly controlled exposure group when using expert judgments. Historical data and non-informative prior tend to show a lower probability of finding the P95 in higher exposure categories in some titles unlike expert judgments. Expert judgements tend to show some similarity in findings with historical data. We recommend the use of expert judgements in occupational risk assessment as prior information before a decision is made on current exposure when historical data are unavailable or scarce.

Do dietary practices and household environmental quality mediate socio-economic inequalities in child undernutrition risk in West Africa?

OBJECTIVE: We investigated the relationship between socio-economic status and child undernutrition in West Africa (WA), and further examined the mediating role of dietary practices (measured as minimum dietary diversity (MDD), minimum meal frequency (MMF) and minimum acceptable diet (MAD)) and household environmental quality (HEQ) in the observed relationship. DESIGN: Thirteen countries were included in the study. We leveraged the most recent Demographic and Health Surveys datasets ranging from 2010 to 2019. Poisson regression model with robust standard errors was used to estimate prevalence ratios and their corresponding 95 % CI. Structural equation modelling was used to conduct the mediation analysis. SETTING: West Africa. PARTICIPANTS: 132 448 under-five children born within 5 years preceding the survey were included. RESULTS: Overall, 32·5 %, 8·2 %, 20·1 % and 71·7 % of WA children were stunted, wasted, underweight and anaemic, respectively. Prevalence of undernutrition decreased with increasing maternal education and household wealth (Trend P-values < 0·001). Secondary or higher maternal education and residence in rich households were associated with statistically significant decrease in the prevalence of stunting, wasting, underweight and anaemia among children in WA. MAD was found to mediate the association of low maternal education and poor household wealth with childhood stunting and underweight by 35·9 % to 44·5 %. MDD, MMF and HEQ did not mediate the observed relationship. CONCLUSIONS: The study findings enables an evaluation and improvement of existing intervention strategies through a socio-economic lens to help address the high burden of child undernutrition in WA and other developing regions.

Forecasting Malaria Morbidity to 2036 Based on Geo-Climatic Factors in the Democratic Republic of Congo.

BACKGROUND: Malaria is a global burden in terms of morbidity and mortality. In the Democratic Republic of Congo, malaria prevalence is increasing due to strong climatic variations. Reductions in malaria morbidity and mortality, the fight against climate change, good health and well-being constitute key development aims as set by the United Nations Sustainable Development Goals (SDGs). This study aims to predict malaria morbidity to 2036 in relation to climate variations between 2001 and 2019, which may serve as a basis to develop an early warning system that integrates monitoring of rainfall and temperature trends and early detection of anomalies in weather patterns. METHODS: Meteorological data were collected at the Mettelsat and the database of the Epidemiological Surveillance Directorate including all malaria cases registered in the surveillance system based on positive blood test results, either by microscopy or by a rapid diagnostic test for malaria, was used to estimate malaria morbidity and mortality by province of the DRC from 2001 to 2019. Malaria prevalence and mortality rates by year and province using direct standardization and mean annual percentage change were calculated using DRC mid-year populations. Time series combining several predictive models were used to forecast malaria epidemic episodes to 2036. Finally, the impact of climatic factors on malaria morbidity was modeled using multivariate time series analysis. RESULTS: The geographical distribution of malaria prevalence from 2001 and 2019 shows strong disparities between provinces with the highest of 7700 cases per 100,000 people at risk for South Kivu. In the northwest, malaria prevalence ranges from 4980 to 7700 cases per 100,000 people at risk. Malaria has been most deadly in Sankuru with a case-fatality rate of 0.526%, followed by Kasai (0.430%), Kwango (0.415%), Bas-Uélé, (0.366%) and Kwilu (0.346%), respectively. However, the stochastic trend model predicts an average annual increase of 6024.07 malaria cases per facility with exponential growth in epidemic waves over the next 200 months of the study. This represents an increase of 99.2%. There was overwhelming evidence of associations between geographic location (western, central and northeastern region of the country), total evaporation under shelter, maximum daily temperature at two meters altitude and malaria morbidity (p < 0.0001). CONCLUSIONS: The stochastic trends in our time series observed in this study suggest an exponential increase in epidemic waves over the next 200 months of the study. The increase in new malaria cases is statistically related to population density, average number of rainy days, average wind speed, and unstable and intermediate epidemiological facies. Therefore, the results of this research should provide relevant information for the Congolese government to respond to malaria in real time by setting up a warning system integrating the monitoring of rainfall and temperature trends and early detection of anomalies in weather patterns.

Acupuncture for treating overactive bladder in adults.

BACKGROUND: Overactive bladder is a common, long-term symptom complex, which includes frequency of micturition, urgency with or without associated incontinence and nocturia. Around 11% of the population have symptoms, with this figure increasing with age. Symptoms can be linked to social anxiety and adaptive behavioural change. The cost of treating overactive bladder is considerable, with current treatments varying in effectiveness and being associated with side effects. Acupuncture has been suggested as an alternative treatment. OBJECTIVES: To assess the effects of acupuncture for treating overactive bladder in adults, and to summarise the principal findings of relevant economic evaluations. SEARCH METHODS: We searched the Cochrane Incontinence Specialised Register, which contains trials identified from the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (including In-Process, Epub Ahead of Print, Daily), ClinicalTrials.gov and WHO ICTRP (searched 14 May 2022). We also searched the Allied and Complementary Medicine database (AMED) and bibliographic databases where knowledge of the Chinese language was necessary: China National Knowledge Infrastructure (CNKI); Chinese Science and Technology Periodical Database (VIP) and WANFANG (China Online Journals), as well as the reference lists of relevant articles.  SELECTION CRITERIA: We included randomised controlled trials (RCTs), quasi-RCTs and cross-over RCTs assessing the effects of acupuncture for treating overactive bladder in adults. DATA COLLECTION AND ANALYSIS: Four review authors formed pairs to assess study eligibility and extract data. Both pairs used Covidence software to perform screening and data extraction. We assessed risk of bias using Cochrane's risk of bias tool and assessed heterogeneity using the Chi2 testand I2 statistic generated within the meta-analyses. We used a fixed-effect model within the meta-analyses unless there was a moderate or high level of heterogeneity, where we employed a random-effects model. We used the GRADE approach to assess the certainty of evidence. MAIN RESULTS: We included 15 studies involving 1395 participants in this review (14 RCTs and one quasi-RCT). All included studies raised some concerns regarding risk of bias. Blinding of participants to treatment group was only achieved in 20% of studies, we considered blinding of outcome assessors and allocation concealment to be low risk in only 25% of the studies, and random sequence generation to be either unclear or high risk in more than 50% of the studies. Acupuncture versus no treatment One study compared acupuncture to no treatment. The evidence is very uncertain regarding the effect of acupuncture compared to no treatment in curing or improving overactive bladder symptoms and on the number of minor adverse events (both very low-certainty evidence). The study report explicitly stated that no major adverse events occurred. The study did not report on the presence or absence of urinary urgency, episodes of urinary incontinence, daytime urinary frequency or episodes of nocturia. Acupuncture versus sham acupuncture Five studies compared acupuncture with sham acupuncture. The evidence is very uncertain about the effect of acupuncture on curing or improving overactive bladder symptoms compared to sham acupuncture (standardised mean difference (SMD) -0.36, 95% confidence interval (CI) -1.03 to 0.31; 3 studies; 151 participants; I2 = 65%; very low-certainty evidence). All five studies explicitly stated that there were no major adverse events observed during the study. Moderate-certainty evidence suggests that acupuncture probably makes no difference to the incidence of minor adverse events compared to sham acupuncture (risk ratio (RR) 1.28, 95% CI 0.30 to 5.36; 4 studies; 222 participants; I² = 0%). Only one small study reported data for the presence or absence of urgency and for episodes of nocturia. The evidence is of very low certainty for both of these outcomes and in both cases the lower confidence interval is implausible. Moderate-certainty evidence suggests there is probably little or no difference in episodes of urinary incontinence between acupuncture and sham acupuncture (mean difference (MD) 0.55, 95% CI -1.51 to 2.60; 2 studies; 121 participants; I2 = 57%). Two studies recorded data regarding daytime urinary frequency but we could not combine them in a meta-analysis due to differences in methodologies (very low-certainty evidence). Acupuncture versus medication Eleven studies compared acupuncture with medication. Low-certainty evidence suggests that acupuncture may slightly increase how many people's overactive bladder symptoms are cured or improved compared to medication (RR 1.25, 95% CI 1.10 to 1.43; 5 studies; 258 participants; I2 = 19%). Low-certainty evidence suggests that acupuncture may reduce the incidence of minor adverse events when compared to medication (RR 0.34, 95% CI 0.26 to 0.45; 8 studies; 1004 participants; I² = 51%). The evidence is uncertain regarding the effect of acupuncture on the presence or absence of urinary urgency (MD -0.40, 95% CI -0.56 to -0.24; 2 studies; 80 participants; I2 = 0%; very low-certainty evidence) and episodes of urinary incontinence (MD -0.33, 95% CI -2.75 to 2.09; 1 study; 20 participants; very low-certainty evidence) compared to medication. Low-certainty evidence suggests there may be little to no effect of acupuncture compared to medication in terms of daytime urinary frequency (MD 0.73, 95% CI -0.39 to 1.85; 4 studies; 360 participants; I2 = 28%). Acupuncture may slightly reduce the number of nocturia episodes compared to medication (MD -0.50, 95% CI -0.65 to -0.36; 2 studies; 80 participants; I2 = 0%, low-certainty evidence). There were no incidences of major adverse events in any of the included studies. However, major adverse events are rare in acupuncture trials and the numbers included in this review may be insufficient to detect these events. AUTHORS' CONCLUSIONS: The evidence is very uncertain about the effect acupuncture has on cure or improvement of overactive bladder symptoms compared to no treatment. It is uncertain if there is any difference between acupuncture and sham acupuncture in cure or improvement of overactive bladder symptoms. This review provides low-certainty evidence that acupuncture may result in a slight increase in cure or improvement of overactive bladder symptoms when compared with medication and may reduce the incidence of minor adverse events. These conclusions must remain tentative until the completion of larger, higher-quality studies that use relevant, comparable outcomes. Timing and frequency of treatment, point selection, application and long-term follow-up are other areas relevant for research.

Bayesian Hierarchical Modelling of Historical Data of the South African Coal Mining Industry for Compliance Testing.

Bayesian hierarchical framework for exposure data compliance testing is highly recommended in occupational hygiene. However, it has not been used for coal dust exposure compliance testing in South Africa (SA). The Bayesian analysis incorporates prior information, which increases solid decision making regarding risk management. This study compared the posterior 95th percentile (P95) of the Bayesian non-informative and informative prior from historical data relative to the occupational exposure limit (OEL) and exposure categories, and the South African Mining Industry Code of Practice (SAMI CoP) approach. A total of nine homogenous exposure groups (HEGs) with a combined 243 coal mine workers' coal dust exposure data were included in this study. Bayesian framework with Markov chain Monte Carlo (MCMC) simulation to draw a full P95 posterior distribution relative to the OEL was used to investigate compliance. We obtained prior information from historical data and employed non-informative prior distribution to generate the posterior findings. The findings were compared to the SAMI CoP. The SAMI CoP 90th percentile (P90) indicated that one HEG was compliant (below the OEL), while none of the HEGs in the Bayesian methods were compliant. The analysis using non-informative prior indicated a higher variability of exposure than the informative prior according to the posterior GSD. The median P95 from the non-informative prior were slightly lower with wider 95% credible intervals (CrI) than the informative prior. All the HEGs in both Bayesian approaches were in exposure category four (poorly controlled), with the posterior probabilities slightly lower in the non-informative uniform prior distribution. All the methods mainly indicated non-compliance from the HEGs. The non-informative prior, however, showed a possible potential of allocating HEGs to a lower exposure category, but with high uncertainty compared to the informative prior distribution from historical data. Bayesian statistics with informative prior derived from historical data should be highly encouraged in coal dust overexposure assessments in South Africa for correct decision making.

Geo-Climatic Factors of Malaria Morbidity in the Democratic Republic of Congo from 2001 to 2019.

Background: Environmentally related morbidity and mortality still remain high worldwide, although they have decreased significantly in recent decades. This study aims to forecast malaria epidemics taking into account climatic and spatio-temporal variations and therefore identify geo-climatic factors predictive of malaria prevalence from 2001 to 2019 in the Democratic Republic of Congo. Methods: This is a retrospective longitudinal ecological study. The database of the Directorate of Epidemiological Surveillance including all malaria cases registered in the surveillance system based on positive blood test results, either by microscopy or by a rapid diagnostic test for malaria was used to estimate malaria morbidity and mortality by province of the DRC from 2001 to 2019. The impact of climatic factors on malaria morbidity was modeled using the Generalized Poisson Regression, a predictive model with the dependent variable Y the count of the number of occurrences of malaria cases during a period of time adjusting for risk factors. Results: Our results show that the average prevalence rate of malaria in the last 19 years is 13,246 (1,178,383−1,417,483) cases per 100,000 people at risk. This prevalence increases significantly during the whole study period (p < 0.0001). The year 2002 was the most morbid with 2,913,799 (120,9451−3,830,456) cases per 100,000 persons at risk. Adjusting for other factors, a one-day in rainfall resulted in a 7% statistically significant increase in malaria cases (p < 0.0001). Malaria morbidity was also significantly associated with geographic location (western, central and northeastern region of the country), total evaporation under shelter, maximum daily temperature at a two-meter altitude and malaria morbidity (p < 0.0001). Conclusions: In this study, we have established the association between malaria morbidity and geo-climatic predictors such as geographical location, total evaporation under shelter and maximum daily temperature at a two-meter altitude. We show that the average number of malaria cases increased positively as a function of the average number of rainy days, the total quantity of rainfall and the average daily temperature. These findings are important building blocks to help the government of DRC to set up a warning system integrating the monitoring of rainfall and temperature trends and the early detection of anomalies in weather patterns in order to forecast potential large malaria morbidity events.

Secular trends in low birth weight and child undernutrition in West Africa: evidence from complex nationwide surveys, 1985-2019.

OBJECTIVE: We present prevalence estimates and secular trends of stunting, wasting, underweight, and anaemia among children under 5 years of age and low birth weight (LBW) over the period 1985-2019 in West Africa (WA). DESIGN: Analysis of Demographic and Health Survey (DHS) and World Bank data. DerSimonian-Laird random effect model with the Knapp-Hartung adjustment to the standard error was used to derive overall prevalence estimates. We used fixed effect ordinary least square regression models with cluster robust standard error to conduct time trends analyses. SETTING: West Africa. PARTICIPANTS: Children aged 0 to 59 months. RESULTS: Three distinct periods (1986-1990, 1993-1996 and 1997-2000) of sharp increases in prevalence of all outcomes was observed. After the year 2000, prevalence of all outcomes except LBW started to decline with some fluctuations. LBW prevalence showed a steady increase after 2000. We observed a decline in prevalence of stunting (ß = -0·20 %; 95 % CI -0·43 %, 0·03 %), log-wasting (ß = -0·02 %; 95 % CI -0·02 %, -0·01 %), log-underweight (ß = -0·02 %; 95 % CI -0·03 %, -0·01 %) anaemia (ß = -0·44; 95 % CI -0·55 %, -0·34 %), and an increase in LBW (ß = 0·06 %; 95 % CI -0·10 %, 0·22 %) in WA over the period. Pooled prevalence of stunting, wasting, underweight, anaemia and LBW in WA for the period 1985-2019 was 26·1 %, 16·4 %, 22·7 %, 76·2 % and 11·3 %, respectively. CONCLUSIONS: Child undernutrition prevalence varied greatly between countries and the year cohorts. We observed marginal reductions in prevalence of all outcomes except anaemia where the reductions were quite striking and LBW where an increase was noted. There is the need for more rigorous and sustained targeted interventions in WA.

Correction: Mind the gap: What explains the poor-non-poor inequalities in severe wasting among under-five children in low- and middle-income countries? Compositional and structural characteristics.

[This corrects the article DOI: 10.1371/journal.pone.0241416.].

Compliance Testing and Homogenous Exposure Group Assessment in the South African Coal Mining Industry.

OBJECTIVES: Globally, several strategies for compliance testing and within-group exposure variability have been suggested. This study aimed to evaluate the performance of the South African Mining Industry Code of Practice (SAMI CoP) approach for grouping and compliance testing against international standards. METHODS: A total of 28 homogenous exposure groups (HEGs) with 728 underground coal mine workers' eight-hour time-weighted average coal dust concentration data were obtained. Compliance testing was assessed using 10% exceedance above occupational exposure limit (OEL) for SAMI CoP, and the 95th percentile of the lognormal distribution was computed for the European Standardization Committee (CEN) and American Industrial Hygiene Association (AIHA). Comparison of the homogeneity of the HEGs was done between SAMI CoP which mandates that both the arithmetic mean (AM) and 90th percentile must fall in the same exposure band to certify homogeneity and the global geometric standard deviation (GSD) and Rappaport ratio (R-ratio) with specific acceptability criteria. To test the homogeneity of exposure within job titles, eight non-homogenous HEGs that have two or more job titles with three measurements were investigated using GSD and the SAMI CoP criteria. RESULTS: A total of 21 HEGs out of 28 were non-compliant to the OEL across SAMI CoP, CEN, and AIHA criteria. Compliance to the OEL was observed for seven HEGs according to the SAMI CoP approach, whereas only one HEG was compliant according to both the SAMI CoP and CEN approaches. The GSD criterion and SAMI CoP revealed that 11 and 6 HEGs were homogenous, respectively, and only on 4 occasions, the 2 approaches agreed. The job titles of the majority of non-homogenous HEGs in both SAMI CoP and GSD were actually homogenous. Five out of 10 sub-groups have their AM above that of HEG B. Other HEGs had at least one of their AM and 90th percentile values above that of their respective parent HEGs. CONCLUSIONS: All three approaches mainly confirmed non-compliance of HEGs. SAMI CoP tended to show compliance of HEGs more than CEN. Non-homogenous HEGs had many job titles that were homogenous according to both SAMI CoP and GSD criteria. There was no perfect agreement of homogeneity by all the indicators. For both future constitutions of HEGs as well as a retrospective assessment of high exposure groups, homogeneity can be improved by using job titles.

Mapping the Burden of Hypertension in South Africa: A Comparative Analysis of the National 2012 SANHANES and the 2016 Demographic and Health Survey.

This study investigates the provincial variation in hypertension prevalence in South Africa in 2012 and 2016, adjusting for individual level demographic, behavioural and socio-economic variables, while allowing for spatial autocorrelation and adjusting simultaneously for the hierarchical data structure and risk factors. Data were analysed from participants aged ≥15 years from the South African National Health and Nutrition Examination Survey (SANHANES) 2012 and the South African Demographic and Health Survey (DHS) 2016. Hypertension was defined as blood pressure ≥ 140/90 mmHg or self-reported health professional diagnosis or on antihypertensive medication. Bayesian geo-additive regression modelling investigated the association of various socio-economic factors on the prevalence of hypertension across South Africa's nine provinces while controlling for the latent effects of geographical location. Hypertension prevalence was 38.4% in the SANHANES in 2012 and 48.2% in the DHS in 2016. The risk of hypertension was significantly high in KwaZulu-Natal and Mpumalanga in the 2016 DHS, despite being previously nonsignificant in the SANHANES 2012. In both survey years, hypertension was significantly higher among males, the coloured population group, urban participants and those with self-reported high blood cholesterol. The odds of hypertension increased non-linearly with age, body mass index (BMI), waist circumference. The findings can inform decision making regarding the allocation of public resources to the most affected areas of the population.

Analysing Normative Influences on the Prevalence of Female Genital Mutilation/Cutting among 0-14 Years Old Girls in Senegal: A Spatial Bayesian Hierarchical Regression Approach.

BACKGROUND: Female genital mutilation/cutting (FGM/C) is a harmful traditional practice affecting the health and rights of women and girls. This has raised global attention on the implementation of strategies to eliminate the practice in conformity with the Sustainable Development Goals (SDGs). A recent study on the trends of FGM/C among Senegalese women (aged 15-49) which examined how individual- and community-level factors affected the practice, found significant regional variations in the practice. However, the dynamics of the practice among girls (0-14 years old) is not fully understood. This paper attempts to fill this knowledge gap by investigating normative influences in the persistence of the practice among Senegalese girls, identify and map 'hotspots'. METHODS: We do so by using a class of Bayesian hierarchical geospatial modelling approach implemented in R statistical software (R Foundation for Statistical Computing, Vienna, Austria) using R2BayesX package. We employed Markov Chain Monte Carlo (MCMC) techniques for full Bayesian inference, while model fit and complexity assessment utilised deviance information criterion (DIC). RESULTS: We found that a girl's probability of cutting was higher if her mother was cut, supported FGM/C continuation or believed that the practice was a religious obligation. In addition, living in rural areas and being born to a mother from Diola, Mandingue, Soninke or Poular ethnic group increased a girl's likelihood of being cut. The hotspots identified included Matam, Tambacounda and Kolda regions. CONCLUSIONS: Our findings offer a clearer picture of the dynamics of FGM/C practice among Senegalese girls and prove useful in informing evidence-based intervention policies designed to achieve the abandonment of the practice in Senegal.

Evaluating changes in the prevalence of female genital mutilation/cutting among 0-14 years old girls in Nigeria using data from multiple surveys: A novel Bayesian hierarchical spatio-temporal model.

Female genital mutilation/cutting (FGM/C) is considered a public health and human rights concern, mainly concentrated in Africa, and has been targeted for elimination under the sustainable development goals. Interventions aimed at ending the practice often rely on data from household surveys which employ complex designs leading to outcomes that are not totally independent, thus requiring advanced statistical techniques. Combining data from multiple surveys within robust statistical framework holds promise to provide more precise estimates due to increased sample size, and accurately identify 'hotspots' and allow for assessment of changes over time. In this study, rich datasets from six (6) successive waves of the Nigeria Demographic and Health Surveys and Multiple Indicator Cluster Surveys undertaken between 2003 and 2016/17, were combined and analyzed in order to better assess changes in the likelihood and prevalence of FGM/C among 0-14-year old girls in Nigeria. We used Bayesian hierarchical regression models which explicitly accounted for the inherent spatial and temporal autocorrelations within the data while simultaneously adjusting for variations due to different survey methods and the effects of linear and non-linear covariates. Parameters were estimated using Markov chain Mote Carlo techniques and model fit assessments were based on Deviance Information Criterion. Results show that prevalence of FGM/C among 0-14 years old girls in Nigeria varied over time and across geographical locations and peaked in 2008 with a shift from South to North. A girl was more likely to be cut if her mother was cut, supported FGM/C continuation, or had no higher education. The effects of mother's age, wealth and type of residence (urban-rural) were no longer significant in 2016. These results reflect the gains of interventions over the years, but also echo the belief that FGM/C is a social norm thus requiring tailored all-inclusive interventions for the total abandonment of FGM/C in Nigeria.

Prevalence of multimorbidity of cardiometabolic conditions and associated risk factors in a population-based sample of South Africans: A cross-sectional study.

Objectives: Ageing populations have led to a growing prevalence of multimorbidity. Cardiometabolic multimorbidity (CM), the co-existence of two or more cardiometabolic disorders in the same person, is rapidly increasing. We examined the prevalence and risk factors associated with CM in a population-based sample of South African adults. Study design: Data were analysed on individuals aged ≥15 years from the South African National Health and Nutrition Examination Survey (SANHANES), a cross sectional population-based survey conducted in 2011-2012. Methods: CM was defined as having ≥2 of hypertension, diabetes, stroke and angina. Hypertension was defined as blood pressure ≥140/90 mmHg or self-reported antihypertensive medication use. Diabetes was defined by HbA1c ≥ 6.5% or self-reported medication use. Stroke and angina were assessed by self-report. Multivariable logistic regression was used to investigate the sociodemographic and modifiable risk factors associated with CM. The association of CM with the functional status of individuals was examined using logistic regression, where functional status was measured by the WHO DAS 2.0 12-item instrument. Results: Of the 3832 individuals analysed, the mean age was 40.8 years (S.D. 18.3), 64.5% were female and 18% were ≥60 years. The prevalence of CM was 10.5%. The most prevalent CM cluster was hypertension and diabetes (7.3%), followed by hypertension and angina (2.6%) and hypertension and stroke (1.9%). Of the individuals with diabetes, nearly three quarters had multimorbidity from co-occurring hypertension, angina and/or stroke and of those with hypertension, 30% had co-occurring diabetes, angina and/or stroke. Age (30-44 years Adjusted Odds Ratio (AOR) = 2.68, 95% CI: 1.15-6.26), 45-59 years AOR = 16.32 (7.38-36.06), 60-74 years AOR = 40.14 (17.86-90.19), and ≥75 years AOR = 49.54 (19.25-127.50) compared with 15-29 years); Indian ethnicity (AOR = 2.58 (1.1-6.04) compared with black African ethnicity), overweight (AOR = 2.73 (1.84-4.07)) and obesity (AOR = 4.20 (2.75-6.40)) compared with normal or underweight) were associated with increased odds of CM. When controlling for age, sex and ethnicity, having ≥2 conditions was associated with significantly higher WHO DAS percentage scores (ß = 5.4, S.E. = 1.1, p < 0.001). Conclusions: A tenth of South Africans have two or more cardiometabolic conditions. The findings call for immediate prioritisation of prevention, screening and management of cardiometabolic conditions and their risk factors to avert large scale health care costs and adverse health outcomes associated with multimorbidity.

Embedded rehabilitation in major trauma: Retrospective pre-post observational study of service and patient outcomes.

INTRODUCTION: Major trauma describes serious and often multiple injuries where there is a strong possibility of death or residual disability. There is little robust evidence on the effects of embedded rehabilitation within the trauma care pathway. Trauma rehabilitation services therefore remain fragmented and poorly integrated. This study aimed to determine changes in hospital length of stay (LoS), intensive care unit (ICU) LoS, 30-day mortality and Glasgow Outcome Scale following implementation of an embedded rehabilitation service into a Major Trauma Centre (MTC). METHODS: Retrospective pre-post observational study of a rehabilitation service introduced into an MTC, consisting of a dedicated 10-bedded inpatient unit, co-ordinating rehabilitation hub, and specialist multi-disciplinary outpatient clinic. Overall hospital LoS, ICU LoS, 30-day mortality and GOS were selected as outcome measures. Patient characteristics (age, sex, injury mechanism, injury severity score, Glasgow Coma Scale, and most injured body region) were compared and controlled for when analysing outcomes. RESULTS: The study cohort included 6,484 patients, of which 4,298 were pre-intervention and 2,186 post-intervention. Patients in the post-intervention cohort were older than those in the pre-intervention cohort (58.3 compared to 56.6, p<0.001) and had higher injury severity scores (48.7% >15 compared to 43.9% >15). Moderate but significant changes to the most injured body region were also observed (p<0.001), with fewer injuries affecting the limbs (25.8% to 24.9%), spine (15.3% to 12.1%), multiple locations (11.3% to 10.7%), abdomen (2.7% to 2.4%) and face/other (1.9% to 1.5%) and more injuries affecting the head (27.5% to 31.5%) and chest (15.6% to 16.9%). Controlling for changes to patient characteristics between the two time periods, there was a reduction in overall hospital LoS of 2.56 days (b=-2.56, p<0.001) and ICU LoS of 0.94 days (b=-0.96, p<0.001). There was a 31% reduced chance of 30-day mortality in post-intervention patients (OR=0.69, 95%CI=0.54 to 0.88), and almost two times higher relative chance of GOS Good Recovery (RR=1.94, CI=1.51 to 2.49). DISCUSSION: Embedded rehabilitation is an important and necessary component of an effective trauma system that is associated with improved service and patient outcomes. Future research should examine prospectively how a dedicated rehabilitation service affects medium- and long-term patient-centred outcomes.