8 research outputs found

    Dual use of Medicare and the Veterans Health Administration: are there adverse health outcomes?

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    BACKGROUND: Millions of veterans are eligible to use the Veterans Health Administration (VHA) and Medicare because of their military service and age. This article examines whether an indirect measure of dual use based on inpatient services is associated with increased mortality risk. METHODS: Data on 1,566 self-responding men (weighted N = 1,522) from the Survey of Assets and Health Dynamics among the Oldest Old (AHEAD) were linked to Medicare claims and the National Death Index. Dual use was indirectly indicated when the self-reported number of hospital episodes in the 12 months prior to baseline was greater than that observed in the Medicare claims. The independent association of dual use with mortality was estimated using proportional hazards regression. RESULTS: 96 (11%) of the veterans were classified as dual users. 766 men (50.3%) had died by December 31, 2002, including 64.9% of the dual users and 49.3% of all others, for an attributable mortality risk of 15.6% (p < .003). Adjusting for demographics, socioeconomics, comorbidity, hospitalization status, and selection bias at baseline, as well as subsequent hospitalization for ambulatory care sensitive conditions, the independent effect of dual use was a 56.1% increased relative risk of mortality (AHR = 1.561; p = .009). CONCLUSION: An indirect measure of veterans' dual use of the VHA and Medicare systems, based on inpatient services, was associated with an increased risk of death. Further examination of dual use, especially in the outpatient setting, is needed, because dual inpatient and dual outpatient use may be different phenomena

    Risk factors and a predictive model for under-five mortality in Nigeria: evidence from Nigeria demographic and health survey

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    <p>Abstract</p> <p>Background</p> <p>Under-5 mortality is a major public health challenge in developing countries. It is essential to identify determinants of under-five mortality (U5M) childhood mortality because these will assist in formulating appropriate health programmes and policies in order to meet the United Nations MDG goal. The objective of this study was to develop a predictive model and identify maternal, child, family and other risk factors associated U5M in Nigeria.</p> <p>Methods</p> <p>Population-based cross-sectional study which explored 2008 demographic and health survey of Nigeria (NDHS) with multivariable logistic regression. Likelihood Ratio Test, Hosmer-Lemeshow Goodness-of-Fit and Variance Inflation Factor were used to check the fit of the model and the predictive power of the model was assessed with Receiver Operating Curve (ROC curve).</p> <p>Results</p> <p>This study yielded an excellent predictive model which revealed that the likelihood of U5M among the children of mothers that had their first marriage at age 20-24 years and ≥ 25 years declined by 20% and 30% respectively compared to children of those that married before the age of 15 years. Also, the following factors reduced odds of U5M: health seeking behaviour, breastfeeding children for > 18 months, use of contraception, small family size, having one wife, low birth order, normal birth weight, child spacing, living in urban areas, and good sanitation.</p> <p>Conclusions</p> <p>This study has revealed that maternal, child, family and other factors were important risk factors of U5M in Nigeria. This study has identified important risk factors that will assist in formulating policies that will improve child survival.</p

    Association between fertility and HIV status: what implications for HIV estimates?

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    Background: Most estimates of HIV prevalence have been based on sentinel surveillance of pregnant women which may either under-estimate or over-estimate the actual prevalence in adult female population. One situation which can lead to either an underestimate or an overestimate of the actual HIV prevalence is where there is a significant difference in fertility rates between HIV-positive and HIV-negative women. Our aim was to compare the fertility rates of HIV-infected and HIV-uninfected women in Cameroon in order to make recommendations on the appropriate adjustments when using antenatal sentinel data to estimate HIV prevalence Methods: Cross-sectional, population-based study using data from 4493 sexually active women aged 15 to 49 years who participated in the 2004 Cameroon Demographic and Health Survey. Results: In the rural area, the age-specific fertility rates in both HIV positive and HIV negative women increased from 15-19 years age bracket to a maximum at 20-24 years and then decreased monotonically till 35-49 years. Similar trends were observed in the urban area. The overall fertility rate for HIV positive women was 118.7 births per 1000 woman-years (95% Confidence Interval [CI] 98.4 to 142.0) compared to 171.3 births per 1000 woman-years (95% CI 164.5 to 178.2) for HIV negative women. The ratio of the fertility rate in HIV positive women to the fertility rate of HIV negative women (called the relative inclusion ratio) was 0.69 (95% CI 0.62 to 0.75). Conclusion: Fertility rates are lower in HIV-positive than HIV-negative women in Cameroon. The findings of this study support the use of summary RIR for the adjustment of HIV prevalence (among adult female population) obtained from sentinel surveillance in antenatal clinics
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