Spatial Variation of Survival for Colorectal Cancer in Malaysia.

A patient's survival may depend on several known and unknown factors and it may also vary spatially across a region. Socioeconomic status, accessibility to healthcare and other environmental factors are likely to contribute to survival rates. The aim of the study was to model the spatial variation in survival for colorectal cancer patients in Malaysia, accounting for individual and socioeconomic risk factors. We conducted a retrospective study of 4412 colorectal cancer (ICD-10, C18-C20) patients diagnosed from 2008 to 2013 to model survival in CRC patients. We used the data recorded in the database of the Malaysian National Cancer Patient Registry-Colorectal Cancer (NCPR-CRC). Spatial location was assigned based on the patients' central district location, which involves 144 administrative districts of Malaysia. We fitted a parametric proportional hazards model in which the spatially correlated frailties were modelled by a log-Gaussian stochastic process to analyse the spatially referenced survival data, which is also known as a spatial survival model. After controlling for individual and area level characteristics, our findings indicate wide spatial variation in colorectal cancer survival across Malaysia. Better healthcare provision and higher socioeconomic index in the districts where patients live decreased the risk of death from colorectal cancer, but these associations were not statistically significant. Reliable measurement of environmental factors is needed to provide good insight into the effects of potential risk factors for the disease. For example, a better metric is needed to measure socioeconomic status and accessibility to healthcare in the country. The findings provide new information that might be of use to the Ministry of Health in identifying populations with an increased risk of poor survival, and for planning and providing cancer control services.

Using the intrinsic growth rate of the mosquito population improves spatio-temporal dengue risk estimation.

Understanding geographic population dynamics of mosquitoes is an essential requirement for estimating the risk of mosquito-borne disease transmission and geographically targeted interventions. However, the use of population dynamics measures, such as the intrinsic growth rate, as predictors in spatio-temporal point processes has not been investigated before. In this work we compared the predictive accuracy of four spatio-temporal log-Gaussian Cox models: (i) With no predictors; (ii) mosquito abundance as predictor; (iii) intrinsic growth rate as predictor; (iv) intrinsic growth rate and mosquito abundance as predictors. This analysis is based on Aedes aegypti mosquito surveillance and human dengue data obtained from the urban area of Caratinga, Brazil. We used a statistical Moran Curve approach to estimate the intrinsic growth rate and a zero inflated Poisson kriging model for estimating mosquito abundance at locations of dengue cases. The incidence of dengue cases was positively associated with mosquito intrinsic growth rate and this model outperformed, in terms of predictive accuracy, the abundance and the null models. The latter includes only the spatio-temporal random effect but no predictors. In the light of these results we suggest that the intrinsic growth rate should be investigated further as a potential tool for predicting the risk of dengue transmission and targeting health interventions for vector-borne diseases.

Differences in survival among adults with HIV-associated Kaposi's sarcoma during routine HIV treatment initiation in Zomba district, Malawi: a retrospective cohort analysis.

Background: The HIV epidemic is a major public health concern throughout Africa. Malawi is one of the worst affected countries in sub-Saharan Africa with a 2014 national HIV prevalence currently estimated at 10% (9.3-10.8%) by UNAIDS. Study reports, largely in the African setting comparing outcomes in HIV patients with and without Kaposi's sarcoma (KS) indicate poor prognosis and poor health outcomes amongst HIV+KS patients. Understanding the mortality risk in this patient group could help improve patient management and care. Methods: Using data for the 559 adult HIV+KS patients who started ART between 2004 and September 2011 at Zomba clinic in Malawi, we estimated relative hazard ratios for all-cause mortality by controlling for age, sex, TB status, occupation, date of starting treatment and distance to the HIV+KS clinic. Results: Patients with tuberculosis (95% CI: 1.05-4.65) and patients who started ART before 2008 (95% CI: 0.34-0.81) were at significantly greater risk of dying. A random-effects Cox model with Log-Gaussian frailties adequately described the variation in the hazard for mortality. Conclusion: The year of starting ART and TB status significantly affected survival among HIV+KS patients. A sub-population analysis of this kind can inform an efficient triage system for managing vulnerable patients.

Modelling and forecasting spatio-temporal variation in the risk of chronic malnutrition among under-five children in Ghana.

BACKGROUND: Spatio-temporal variation in under-5-year-old children malnutrition remains unstudied in most developing countries like Ghana. This study explores and forecasts the spatio-temporal patterns in childhood chronic malnutrition among these children. We also investigate the effect of maternal education on childhood malnutrition. METHODS: We analysed data on 10,036 children residing in 1516 geographic locations. A spatio-temporal model was fitted to the data and was used to produce predictive maps of spatio-temporal variation in the probability of stunting. RESULTS: The study found substantial spatio-temporal variation in the prevalence of stunting. Also, higher levels of mother's education were associated with decreased risk of being stunted. CONCLUSION: Our spatio-temporal model captured variations in childhood stunting over place and time. Our method facilitates and enriches modelling and forecasting of future stunting prevalence to identify areas at high risk. Improving maternal education could be given greater consideration within an overall strategy for addressing childhood malnutrition.

Childhood Malnutrition and Its Determinants among Under-Five Children in Ghana.

BACKGROUND: Childhood malnutrition adversely affects short- and long-term health and economic well-being of children. Malnutrition is a global challenge and accounts for around 40% of under-five mortality in Ghana. Limited studies are available indicating determinants of malnutrition among children. This study investigates prevalence and determinants of malnutrition among children under-five with the aim of providing advice to policymakers and other stakeholders responsible for the health and nutrition of children. METHODS: The study used data from the 2008 Ghana Demographic and Health Survey (GDHS). Analyses were conducted on 2083 children under 5 years old nested within 1641 households with eligible anthropometric measurements, using multilevel regression analysis. Results from the multilevel models were used to compute probabilities of malnutrition. RESULTS: This study observed that 588 (28%), 276 (13%), and 176 (8%) of the children were moderately 'stunted', moderately 'underweight', and moderately 'wasted' respectively. Older ages are associated with increased risk of stunting and underweight. Longer breast-feeding duration, multiple births, experience of diarrhoeal episodes, small size at birth, absence of toilet facilities in households, poor households, and mothers who are not covered by national health insurance are associated with increased risk of malnutrition. Increase in mother's years of education and body mass index are associated with decreased malnutrition. Strong residual household-level variations in childhood nutritional outcomes were found. CONCLUSION: Policies and intervention strategies aimed at improving childhood nutrition and health should address the risk factors identified and the need to search for additional risk factors that might account for the unexplained household-level variations.