Socio-Economic Inequalities in Access to Drinking Water among Inhabitants of Informal Settlements in South Africa.

While evidence from several developing countries suggests the existence of socio-economic inequalities in the access to safe drinking water, a limited number of studies have been conducted on this topic in informal settlements. This study assessed socio-economic inequalities in the use of drinking water among inhabitants of informal settlements in South Africa. The study used data from "The baseline study for future impact evaluation for informal settlements targeted for upgrading in South Africa." Households eligible for participation were living in informal settlements targeted for upgrading in all nine provinces of South Africa. Socio-economic inequalities were assessed by means of multinomial logistic regression analyses, concentration indices, and concentration curves. The results showed that the use of a piped tap on the property was disproportionately concentrated among households with higher socio-economic status (concentration index: +0.17), while households with lower socio-economic status were often limited to the use of other inferior (less safe or distant) sources of drinking water (concentration index for nearby public tap: -0.21; distant public tap: -0.17; no-tap water: -0.33). The use of inferior types of drinking water was significantly associated with the age, the marital status, the education status, and the employment status of the household head. Our results demonstrate that reducing these inequalities requires installing new tap water points in informal settlements to assure a more equitable distribution of water points among households. Besides, it is recommended to invest in educational interventions aimed at creating awareness about the potential health risks associated with using unsafe drinking water.

Sex differences in cardiometabolic risk factors, pharmacological treatment and risk factor control in type 2 diabetes: findings from the Dutch Diabetes Pearl cohort.

INTRODUCTION: Sex differences in cardiometabolic risk factors and their management in type 2 diabetes (T2D) have not been fully identified. Therefore, we aimed to examine differences in cardiometabolic risk factor levels, pharmacological treatment and achievement of risk factor control between women and men with T2D. RESEARCH DESIGN AND METHODS: Cross-sectional data from the Dutch Diabetes Pearl cohort were used (n=6637, 40% women). Linear and Poisson regression analyses were used to examine sex differences in cardiometabolic risk factor levels, treatment, and control. RESULTS: Compared with men, women had a significantly higher body mass index (BMI) (mean difference 1.79 kg/m2 (95% CI 1.49 to 2.08)), while no differences were found in hemoglobin A1c (HbA1c) and systolic blood pressure (SBP). Women had lower diastolic blood pressure (-1.94 mm Hg (95% CI -2.44 to -1.43)), higher total cholesterol (TC) (0.44 mmol/L (95% CI 0.38 to 0.51)), low-density lipoprotein cholesterol (LDL-c) (0.26 mmol/L (95% CI 0.22 to 0.31)), and high-density lipoprotein cholesterol (HDL-c) sex-standardized (0.02 mmol/L (95% CI 0.00 to 0.04)), and lower TC:HDL ratio (-0.29 (95% CI -0.36 to -0.23)) and triglycerides (geometric mean ratio 0.91 (95% CI 0.85 to 0.98)). Women had a 16% higher probability of being treated with antihypertensive medication in the presence of high cardiovascular disease (CVD) risk and elevated SBP than men (relative risk 0.84 (95% CI 0.73 to 0.98)), whereas no sex differences were found for glucose-lowering medication and lipid-modifying medication. Among those treated, women were less likely to achieve treatment targets of HbA1c (0.92 (95% CI 0.87 to 0.98)) and LDL-c (0.89 (95% CI 0.85 to 0.92)) than men, while no differences for SBP were found. CONCLUSIONS: In this Dutch T2D population, women had a slightly different cardiometabolic risk profile compared with men and a substantially higher BMI. Women had a higher probability of being treated with antihypertensive medication in the presence of high CVD risk and elevated SBP than men, and were less likely than men to achieve treatment targets for HbA1c and LDL levels.

Trajectory of body mass and skeletal muscle indices and disease progression in metastatic colorectal cancer patients.

BACKGROUND: Knowledge of the evolution of BMI and skeletal muscle index (SMI) measurements during advanced cancer and their relationships with disease progression (PD) is relevant to improve the timing of interventions that may improve cachexia-associated outcomes. OBJECTIVES: We investigated BMI and SMI trajectories and their associations with PD in metastatic colorectal cancer (mCRC) patients during consecutive palliative systemic regimens. METHODS: In a secondary analysis of the primary CAIRO3 trial, we included 533 mCRC patients with BMI measurements repeated every 3 wk and 95 randomly selected patients with SMI measurements repeated every 9 wk. We studied 2 periods: p1, during first-line maintenance capecitabine + bevacizumab or observation until the first progression of disease (PD1); and p2, during capecitabine + oxaliplatin + bevacizumab or another reintroduction treatment from PD1 until the second progression of disease (PD2). BMI and SMI trajectories were modeled separately throughout both periods, and joint longitudinal-survival modeling was used to investigate the relationships between slopes in BMI and SMI with PD at 9 and 3 wk pre-PD. A multivariate longitudinal joint model was used to investigate the association between the BMI trajectory and PD at time of PD, independent of SMI. RESULTS: During p1, the slopes in BMI and SMI were associated with early PD1 [HRs for 9-wk BMI: 1.54 (95% CI: 1.33, 1.76); 9-wk SMI: 1.38 (95% CI: 0.87, 1.89), NS; 3-wk BMI: 1.74 (95% CI: 1.48, 1.99); 3-wk SMI: 2.65 (95% CI: 1.97, 3.32)]. During p2, only the slope in SMI was related to PD2 [9-wk BMI: 1.09 (95%: CI: 0.73, 1.45), NS; 9-wk SMI: 1.64 (95% CI: 1.25, 2.04); 3-wk BMI: 1.17 (95% CI: 0.77, 1.57); 3-wk SMI: 1.11 (95% CI: 0.70, 1.53)]. In models mutually adjusting for BMI and SMI, SMI was associated with PD in p1 [p1 ( n = 95), HR BMI: 1.32 (95% CI: 0.74, 2.39), NS; p1, HR SMI: 1.50 (95% CI: 1.04, 2.14); p2 ( n = 50), BMI: 0.98 (95% CI: 0.55, 1.75), NS; p2, HR SMI: 1.11 (95% CI: 0.61, 2.05), NS]. CONCLUSIONS: In mCRC patients during palliative systemic treatment, SMI losses, irrespective of BMI losses, may be a marker for the early initiation of cachexia interventions.

Factors Contributing to Cancer-Related Muscle Wasting During First-Line Systemic Treatment for Metastatic Colorectal Cancer.

BACKGROUND: Increasing evidence indicates that loss of muscle mass is associated with adverse outcomes in metastatic colorectal cancer. Here, we investigate which demographic, lifestyle- (smoking), tumor-, and treatment-related factors are associated with muscle loss in patients with metastatic colorectal cancer during first-line palliative systemic treatment. METHODS: Data from 300 patients with computed tomography scans both at start and after six initial cycles of capecitabine plus oxaliplatin and bevacizumab was used (CAIRO3). From computed tomography, muscle mass normalized for stature (skeletal muscle index [SMI]) was calculated. A priori-selected variables were tested using multivariable linear regression models (P values ≤.05). Two models were developed: Model 1 contained variables measured at start and Model 2 contained variables assessed after initial therapy. RESULTS: In Model 1, loss of SMI was statistically significantly associated with a higher initial SMI (-0.32%, 95% confidence interval [CI] = -0.45% to -0.19% per unit increase in initial SMI), smoking status (-2.74%, 95% CI = -5.29% to -0.19% for smokers), and interval of metastases (-3.02%, 95% CI = -5.50% to -0.53%) for metachronous vs synchronous metastases), and primary tumor resection was statistically significantly associated with a gain in SMI (2.17%, 95% CI = 0.13% to 4.21% for resection vs no resection). In Model 2, loss of SMI was statistically significantly associated with response to capecitabine plus oxaliplatin and bevacizumab (-2.48%, 95% CI = -4.33% to -0.62% for stable disease vs partial/complete response). CONCLUSIONS: Our results highlight, given the association of sarcopenia and survival, that patients with higher SMI should not be ignored. In addition, smoking is a potentially modifiable factor associated with muscle loss. The association between smoking and muscle loss might relate to worse clinical outcomes in smokers with metastatic colorectal cancer.