BackgroundA clear understanding of the effects of housing structure, education, occupation, income, and wealth on malaria can help to better design socioeconomic interventions to control the disease. This literature review summarizes the relationship of housing structure, educational level, occupation, income, and wealth with the epidemiology of malaria in sub-Saharan Africa (SSA).MethodsA systematic review and meta-analysis was conducted following the preferred reporting items for systematic reviews and meta-analyses guidelines. The protocol for this study is registered in PROSPERO (ID=CRD42017056070), an international database of prospectively registered systematic reviews. On January 16, 2016, available literature was searched in PubMed, Embase, CINAHL, and Cochrane Library. All but case studies, which reported prevalence or incidence of Plasmodium infection stratified by socioeconomic status among individuals living in SSA, were included without any limits. Odds Ratio (OR) and Relative Risk (RR), together with 95% CI and p-values were used as effect measures. Heterogeneity was assessed using chi-square, Moran’s I2, and tau2 tests. Fixed (I2<30%), random (I2≥30%) or log-linear dose-response model was used to estimate the summary OR or RR.ResultsAfter removing duplicates and screening of titles, abstracts, and full text, 84 articles were found eligible for systematic review, and 75 of them were included in the meta-analyses. Fifty-seven studies were cross-sectional, 12 were prospective cohort, 10 were case-control, and five were randomized control trials. The odds of Plasmodium infection increased among individuals who were living in poor quality houses (OR 2.13, 95% CI 1.56–3.23, I2 = 27.7), were uneducated (OR 1.36, 95% CI 1.19–1.54, I2 = 72.4.0%), and were farmers by occupation (OR 1.48, 95% CI 1.11–1.85, I2 = 0.0%) [p<0.01 for all]. The odds of Plasmodium infection also increased with a decrease in the income (OR 1.02, 95% CI 1.01–1.03, tau2<0.001), and wealth index of individuals (OR 1.25, 95% CI 1.18–1.35, tau2 = 0.028) [p<0.001 for both]. Longitudinal studies also showed an increased risk of Plasmodium infection among individuals who were living in poor quality houses (RR 1.86, 95% CI 1.47–2.25, I2 = 0.0%), were uneducated (OR 1.27, 1.03–1.50, I2 = 0.0%), and were farmers (OR 1.36, 1.18–1.58) [p<0.01 for all].ConclusionsLack of education, low income, low wealth, living in poorly constructed houses, and having an occupation in farming may increase risk of Plasmodium infection among people in SSA. Public policy measures that can reduce inequity in health coverage, as well as improve economic and educational opportunities for the poor, will help in reducing the burden of malaria in SSA.
Objective: Financial problems in cancer survivors are associated with distress and reduced quality of life. Most studies have been cross-sectional, and a longitudinal study is needed to guide clinical interventions. Method: We used data from two surveys of the National Health and Aging Trends Study (NHATS). Participants ( n = 307) reported whether they experienced six indicators of financial burden. The Patient Health Questionnaire 4 assessed depressive symptoms and general anxiety. Cross-lagged panel analyses assessed whether financial burden predicted distress and health or vice versa. Results: In the total sample, financial burden at the first survey predicted depressive symptoms ( p < .01), general anxiety ( p < .01), and self-rated health ( p < .01) at the second survey. Depressive symptoms, general anxiety, and self-rated health at the first survey did not predict later financial burden ( ps > .05). Discussion: Results suggest financial problems predict later distress and poor health. This study highlights the need to address financial burden in cancer survivors.
PURPOSE: Systemic therapy use in the last 30 days of life (DOL) for patients with advanced cancer is a low-value medical practice. We hypothesized that systemic therapy use in the last 30 DOL increased after approval of antiprogrammed cell death protein 1 immune checkpoint inhibitors (ICIs) and has contributed to increased health care utilization and spending. METHODS: We investigated the change in prevalence of any systemic therapy use in the last 30 DOL among patients with advanced solid tumors in the 4 years before and after antiprogrammed cell death protein 1 ICI approval in 2014. We used cases from the Western Washington Cancer Surveillance System linked to commercial and Medicare insurance. We calculated the difference in prevalence between the pre- and post-ICI periods. We also calculated the annual prevalence of any systemic therapy and ICI use in the last 30 DOL and measured health care utilization (emergency department visits and hospitalizations) and costs during the last 30 DOL. RESULTS: Eight thousand eight hundred seventy-one patients (median age 73 years) were included; 34% and 66% in the pre-and post-ICI period, respectively. Systemic therapy use in the last 30 DOL was lower in the post-ICI versus pre-ICI period (12.4% v 14.4%; difference −2.0% [95% CI, −3.5 to −0.5]). The annual prevalence of systemic therapy use in the last 30 DOL also declined, although ICI use rose. Patients treated with ICIs in last 30 DOL had more emergency department visits, hospitalizations, and higher costs. CONCLUSION: Systemic therapy use in the last 30 DOL was lower in the period after ICI approval. However, ICI use rose over time and had higher utilization and costs in the last 30 DOL. Systemic therapy use in the last 30 DOL warrants monitoring, especially as more ICI indications are approved.
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