Survival Patterns Among Patients With Breast Cancer in Sub-Saharan Africa: A Systematic Review and Meta-Analysis.

Importance: Breast cancer is the most prevalent cancer globally with tremendous disparities both within specific regions and across different contexts. The survival pattern of patients with breast cancer remains poorly understood in sub-Saharan African (SSA) countries. Objective: To investigate the survival patterns of patients with breast cancer in SSA countries and compare the variation across countries and over time. Data Sources: Embase, PubMed, Web of Science, Scopus, and ProQuest were searched from inception to December 31, 2022, with a manual search of the references. Study Selection: Cohort studies of human participants that reported 1-, 2-, 3-, 4-, 5-, and 10-year survival from diagnosis among men, women, or both with breast cancer in SSA were included. Data Extraction and Synthesis: Independent extraction of study characteristics by multiple observers was performed using open-source software, then exported to a standard spreadsheet. A random-effects model using the generalized linear mixed-effects model was used to pool data. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guideline for reporting was followed. Main Outcome and Measures: Survival time from diagnosis. Results: Forty-nine studies were included in the review with a sample size ranging from 21 to 2311 (total, 14 459; 196 [1.35%] men, 13 556 [93.75%] women, and 707 [4.90%] unspecified; mean age range, 38 to 71 years), of which 40 were summarized using meta-analysis. The pooled 1-year survival rate of patients with breast cancer in SSA was 0.79 (95% CI, 0.67-0.88); 2-year survival rate, 0.70 (95% CI, 0.57-0.80); 3-year survival rate, 0.56 (95% CI, 0.45-0.67); 4-year survival rate, 0.54 (95% CI, 0.43-0.65); and 5-year survival rate, 0.40 (95% CI, 0.32-0.49). The subgroup analysis showed that the 5-year survival rate ranged from 0.26 (95% CI, 0.06-0.65) for studies conducted earlier than 2010 to 0.47 (95% CI, 0.32-0.64) for studies conducted later than 2020. Additionally, the 5-year survival rate was lower in countries with a low human development index (HDI) (0.36 [95% CI, 0.25-0.49) compared with a middle HDI (0.46 [95% CI, 0.33-0.60]) and a high HDI (0.54 [95% CI, 0.04-0.97]). Conclusions and Relevance: In this systematic review and meta-analysis, the survival rates for patients with breast cancer in SSA were higher in countries with a high HDI compared with a low HDI. Enhancing patient survival necessitates a comprehensive approach that involves collaboration from all relevant stakeholders.

Performance of mid-upper arm circumference to identify adolescents with obesity and metabolic syndrome: NHANES 2011-2018 analysis.

BACKGROUND: Mid-upper arm circumference (MUAC) was recommended for screening of adolescents with obesity, although its diagnostic performance with respect to high-precision assessment of body composition remains unknown. OBJECTIVE: To evaluate the diagnostic performance of MUAC in identifying obesity and metabolic syndrome in U.S. adolescents. METHODS: A cross-sectional study was conducted using National Health and Nutrition Examination Survey (NHANES) data (2011-2018) of adolescents aged 12-19. We calculated the area under the receiver operating characteristic curve, sensitivity, specificity, positive and negative predictive values and likelihood ratios of MUAC in identifying obesity and metabolic syndrome. RESULTS: In our study, data of 5496 adolescents, including 2665 females, were analysed. The prevalence of obesity was higher in boys (14%) than girls (10%), whilst metabolic syndrome was more common in males (2.6%) than females (1.7%). The area under the curve (AUC) of MUAC in identifying obesity was 0.69 in boys and 0.86 in girls, whilst the AUC of MUAC in identifying metabolic syndrome was 0.91 in boys and 0.87 in girls. The optimal MUAC cut-off for identifying adolescents with obesity was 28.3 cm in boys (sensitivity: 64.8%, specificity: 85.5%) and 30.8 cm in girls (sensitivity: 67.9%, specificity: 90.1%). CONCLUSIONS: MUAC was a good indicator of both obesity and metabolic syndrome, with higher accuracy in girls.

Association between long-term weight loss and obesity-related complications defined by Edmonton obesity staging system: analysis from the NHANES (2011-2018).

BACKGROUND/OBJECTIVE: A successful Long-Term Weight Loss (LTWL) is associated with a more favorable metabolic disease risk profile. However, evidence is limited on the association of LTWL with obesity-related complications defined by Edmonton obesity staging system (EOSS). Hence, our study aims to assess the association between LTWL thresholds and obesity-related complications defined by EOSS among the adult US population. SUBJECTS/METHODS: We used data from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. Adults 18 years or older with overweight/obesity and long-term weight loss were included in the analysis. The association between long-term weight loss and obesity-related complications defined by EOSS was investigated. A multivariable logistic regression model was employed by adjusting for potential covariates. RESULTS: A total of 22,223 adults were included in the analysis. Overall, 61.8% of participants had long-term weight loss of <5%, and 4.8% of participants had successful long-term weight loss of 20% or greater. The highest long-term weight loss threshold ( ≥ 20%) had the lowest odds of EOSS stage ≥ 2 (odds ratio [OR] = 0.60; 95% CI:0.50, 0.72; p < 0.001). The lowest LTWL threshold (5-9.9%) was relatively associated with lower odds for EOSS stage ≥ 2 [OR = 0.69 95% CI: 0.61, 0.78, p < 0.001]. CONCLUSIONS: The LTWL categories were significantly associated with lower odds of EOSS stage ≥ 2 compared to EOSS 0 or 1. Future longitudinal research assessing the association between LTWL and EOSS components is recommended.

Predictive ability of anthropometric indices in identifying metabolic syndrome among US adolescents 10 to 19 years old: Analysis from the National Health and Nutrition Examination Survey 2011 to 2018 data set.

OBJECTIVE: The aim of this study was to identify the best anthropometric indices for predicting metabolic syndrome in US adolescents. METHODS: A cross-sectional study analyzed data of adolescents ages 10 to 19 y using the National Health and Nutrition Examination Survey 2011 to 2018 data. The receiver operating characteristic areas under the curve (AUCs) of waist circumference z score, body roundness index, body mass index, and A Body Shape Index in identifying predicting metabolic syndrome were assessed. Furthermore, sensitivity, specificity, positive predictive value, negative predictive value, and positive and negative likelihood ratios of all anthropometric indices were calculated. RESULTS: A total of 5496 adolescents were included in the analysis. Waist circumference z score had an AUC of 0.90 (95% CI, 0.89-0.91), sensitivity of 95.0% (95% CI, 89.4-98.1), and specificity of 74.8% (95% CI, 73.6, 76.0). Body roundness index had an AUC of 0.88 (95% CI, 0.87-0.89), sensitivity of 96.7% (95% CI, 91.7-99.1), and specificity of 75.2% (95% CI, 74.1-76.4). Body mass index z score had an AUC of 0.83 (95% CI, 0.81-0.85), sensitivity of 97.5% (95% CI, 92.9-99.5), and specificity of 68.2% (95% CI, 66.9-69.4). A Body Shape Index had an AUC of 0.59 (95% CI, 0.56-0.61), sensitivity of 75.0% (95% CI, 66.3-82.5), and specificity of 50.9% (95% CI, 49.5-52.2). CONCLUSIONS: Our study found waist circumference z score and body roundness index were the best predictors of predicting metabolic syndrome compared with body mass index z score and A Body Shape Index in both boys and girls. We recommend that future studies develop global cutoff points for these anthropometric indices and examine their performance in a multi-country setting.

Dietary diversity and its determinants among children aged 6-23 months in Ethiopia: evidence from the 2016 Demographic and Health Survey.

Dietary diversity in children may be influenced not only by individual circumstances but also by the features of the community in which they live. Our study aimed to assess community and individual-level determinants of minimum dietary diversity among children aged 6-23 months in Ethiopia. We included 2960 children aged 6-23 months from the recent Ethiopia Demographic and Health Survey. A minimum dietary diversity was defined as the consumption of at least five food groups out of the eight reference food groups within 24 h by children aged 6-23 months. Multilevel logistic regression was used to investigate the drivers of minimum dietary diversity in Ethiopian children aged 6-23 months. About 12⋅5 % of children met the bare minimum of dietary diversification. Age of the child (9-11 months AOR, 3⋅3 (95 % CI 1⋅8, 5⋅6), 12-17 months AOR, 4⋅0 (95 % CI 2⋅4, 6⋅7), 18-23 months AOR, 3⋅5 (95 % CI 2⋅0, 5⋅8)), caregiver listening radio at least once a week AOR, 1⋅6 (95 % CI 1⋅1, 2⋅4) and wealth quantiles (Second AOR, 1⋅8 (95 % CI 1⋅1, 3⋅1), Fourth AOR, 2⋅9 (95 % CI 1⋅6, 5⋅2) and Highest AOR, 2⋅2 (95 % CI 1⋅1, 4⋅2)) were individual characteristics associated with dietary diversity. Place of residence was the only community-level characteristic associated with children's dietary diversity (Rural AOR, 0⋅4 (95 % CI 0⋅2, 0⋅6)). The minimum dietary diversity among Ethiopian children is suboptimal. Nutrition programmes aimed at enhancing dietary diversity should be strengthened in this population, particularly for those from poor families and residing in rural areas.

Diagnostic ability of mid-upper arm circumference-to-length ratio in detecting wasting among infants aged 1-6 months in Ethiopia.

Mid-upper arm circumference (MUAC) is an age-sensitive anthropometric measurement in infants. However, exact age is difficult to know, particularly in low-income countries. We evaluated the diagnostic accuracy of an age-independent mid-upper arm circumference-to-length (MUAC/L) ratio measurement in detecting wasting among infants aged 1-6 months in Ethiopia. A facility-based diagnostic accuracy study was conducted on 467 in-patient infants aged 1-6 months from March to May 2019. The receiver operating characteristic (ROC) curve was used to evaluate the ability of MUAC/L to detect wasting. Sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and positive and negative predictive values were calculated. The magnitude of severe wasting was 21⋅6 % and moderate wasting was 13⋅0 %. The area under the ROC curve (AUC) of MUAC/L was 0⋅77 (95 % CI 0⋅73, 0⋅81) for detecting moderate wasting and 0⋅92 (95 % CI 0⋅89, 0⋅94) for detecting severe wasting. MUAC/L had a sensitivity of 91⋅1 % (95 % CI 81⋅3, 94⋅4), a specificity of 84⋅7 % (95 % CI 80⋅6, 88⋅2), a positive likelihood ratio of 5⋅82 (95 % CI 4⋅53, 7⋅48) and a negative likelihood ratio of 0⋅13 (95 % CI 0⋅07, 0⋅22) in total infants. The optimal MUAC/L cut-off was <0⋅190 for boys and <0⋅185 for girls. MUAC/L had an AUC of 0⋅77 and 0⋅92 in predicting moderate and severe wasting in infants aged 1-6 months, respectively. Using MUAC/L to treat Ethiopian infants with severe wasting and infants with similar characteristics in other countries could improve treatment coverage.

The performance of mid-upper arm circumference for identifying children and adolescents with overweight and obesity: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to synthesise the existing evidence on the performance of mid-upper arm circumference (MUAC) to identify children and adolescents with overweight and obesity. DESIGN: Systematic review and meta-analysis. SETTING: We searched PubMed, EMBASE, SCOPUS, Cochrane Library, Web of Science, CINAHL and Google scholar databases from their inception to December 10, 2021, for relevant studies. There were no restrictions regarding the language of publication. Studies reporting measures for the diagnostic performance of MUAC compared with a reference standard for diagnosing overweight and obesity in children and adolescents aged 2-19 years were included. PARTICIPANTS: A total of 54 381 children and adolescents from twenty-one studies were reviewed; ten studies contributed to meta-analyses. RESULTS: In boys, MUAC showed a pooled AUC of 0·92 (95 % CI 0·89, 0·94), sensitivity of 84·4 (95 % CI 84·6, 90·8) and a specificity of 86·0 (95 % CI 79·2, 90·8), when compared against BMI z-score, defined overweight and obesity. As for girls, MUAC showed a pooled AUC of 0·93 (95 % CI 0·90, 0·95), sensitivity of 86·4 (95 % CI 79·8, 91·0), specificity of 86·6 (95 % CI 82·2, 90·1) when compared against overweight and obesity defined using BMI z-scores. CONCLUSION: In comparison with BMI, MUAC has an excellent performance to identify overweight and obesity in children and adolescents. However, no sufficient evidence on the performance of MUAC compared with gold standard measures of adiposity. Future research should compare performance of MUAC to the 'golden standard' measure of excess adiposity.