Objectively Measured Residential Environment and Self-Reported Health: A Multilevel Analysis of UK Census Data

Little is known about the association between health and the quality of the residential environment. What is known is often based on subjective assessments of the environment rather than on measurements by independent observers. The aim of this study, therefore, was to determine the association between self-reported general health and an objectively assessed measure of the residential environment. We studied over 30,000 residents aged 18 or over living in 777 neighbourhoods in south Wales. Built environment quality was measured by independent observers using a validated tool, the Residential Environment Assessment Tool (REAT), at unit postcode level. UK Census data on each resident, which included responses to a question which assessed self-reported general health, was linked to the REAT score. The Census data also contained detailed information on socio-economic and demographic characteristics of all respondents and was also linked to the Welsh Index of Multiple Deprivation. After adjusting for both the individual characteristics and area deprivation, respondents in the areas of poorest neighbourhood quality were more likely to report poor health compared to those living in areas of highest quality (OR 1.36, 95% confidence interval 1.22–1.49). The particular neighbourhood characteristics associated with poor health were physical incivilities and measures of how well the residents maintained their properties. Measures of green space were not associated with self-reported health. This is the first full population study to examine such associations and the results demonstrate the importance for health of the quality of the neighbourhood area in which people live and particularly the way in which residents behave towards their own and their neighbours’ property. A better understanding of causal pathways that allows the development of interventions to improve neighbourhood quality would offer significant potential health gains.     

Using Health Extension Workers for Monitoring Child Mortality in Real-Time: Validation against Household Survey Data in Rural Ethiopia

Background

Ethiopia has scaled up its community-based programs over the past decade by training and deploying health extension workers (HEWs) in rural communities throughout the country. Consequently, child mortality has declined substantially, placing Ethiopia among the few countries that have achieved the United Nations’ fourth Millennium Development Goal. As Ethiopia continues its efforts, results must be assessed regularly to provide timely feedback for improvement and to generate further support for programs. More specifically the expansion of HEWs at the community level provides a unique opportunity to build a system for real-time monitoring of births and deaths, linked to a civil registration and vital statistics system that Ethiopia is also developing. We tested the accuracy and completeness of births and deaths reported by trained HEWs for monitoring child mortality over 15 -month periods.

Methods and Findings

HEWs were trained in 93 randomly selected rural kebeles in Jimma and West Hararghe zones of the Oromia region to report births and deaths over a 15-month period from January, 2012 to March, 2013. Completeness of number of births and deaths, age distribution of deaths, and accuracy of resulting under-five, infant, and neonatal mortality rates were assessed against data from a large household survey with full birth history from women aged 15–49. Although, in general HEWs, were able to accurately report events that they identified, the completeness of number of births and deaths reported over twelve-month periods was very low and variable across the two zones. Compared to household survey estimates, HEWs reported only about 30% of births and 21% of under-five deaths occurring in their communities over a twelve-month period. The under-five mortality rate was under-estimated by around 30%, infant mortality rate by 23% and neonatal mortality by 17%. HEWs reported disproportionately higher number of deaths among the very young infants than among the older children.

Conclusion

Birth and death data reported by HEWs are not complete enough to support the monitoring of changes in childhood mortality. HEWs can significantly contribute to the success of a CRVS in Ethiopia, but cannot be relied upon as the sole source for identification of vital events. Further studies are needed to understand how to increase the level of completeness.     

Detection of Cyclic Trends in Incidence Data Using the Efficiency Score Method

In studies involving a cyclic regularity, researchers usually have a good working knowledge regarding the peak time in the cycle. Capitalizing on this information, we derive the asymptotically uniformly most powerful unbiased test for detecting a cyclic trend using the likelihood score, and present the asymptotic power function of the test and the approximate formula for sample size. Numerical studies demonstrate great advantages of the proposed test over the standard test in terms of power and sample size. Asymptotic power of the score test is satisfactorily close to actual power. We also generalize this method so that it is applicable for incidence data from unequally spaced intervals or risk populations of unequal size.     

Estimation and Short-Term Prediction of the Course of the HIV Epidemic Using Demographic and Health Survey Methodology-Like Data

Background

Mathematical models have played important roles in the understanding of epidemics and in the study of the impacts of various behavioral or medical measures. However, modeling accurately the future spread of an epidemic requires context-specific parameters that are difficult to estimate because of lack of data. Our objective is to propose a methodology to estimate context-specific parameters using Demographic and Health Survey (DHS)-like data that can be used in mathematical modeling of short-term HIV spreading.

Methods and Findings

The model splits the population according to sex, age, HIV status, and antiretroviral treatment status. To estimate context-specific parameters, we used individuals’ histories included in DHS-like data and a statistical analysis that used decomposition of the Poisson likelihood. To predict the course of the HIV epidemic, sex- and age-specific differential equations were used. This approach was applied to recent data from Kenya. The approach allowed the estimation of several key epidemiological parameters. Women had a higher infection rate than men and the highest infection rate in the youngest age groups (15–24 and 25–34 years) whereas men had the highest infection rate in age group 25–34 years. The immunosuppression rates were similar between age groups. The treatment rate was the highest in age group 35–59 years in both sexes. The results showed that, within the 15–24 year age group, increasing male circumcision coverage and antiretroviral therapy coverage at CD4 ≤ 350/mm³ over the current 70% could have short-term impacts.

Conclusions

The study succeeded in estimating the model parameters using DHS-like data rather than literature data. The analysis provides a framework for using the same data for estimation and prediction, which can improve the validity of context-specific predictions and help designing HIV prevention campaigns.     

Child Mortality Estimation: A Global Overview of Infant and Child Mortality Age Patterns in Light of New Empirical Data

Background

The under-five mortality rate (the probability of dying between birth and age 5 y, also denoted in the literature as U5MR and ₅ q ₀) is a key indicator of child health, but it conceals important information about how this mortality is distributed by age. One important distinction is what amount of the under-five mortality occurs below age 1 y (₁ q ₀) versus at age 1 y and above (₄ q ₁). However, in many country settings, this distinction is often difficult to establish because of various types of data errors. As a result, it is common practice to resort to model age patterns to estimate ₁ q ₀ and ₄ q ₁ on the basis of an observed value of ₅ q ₀. The most commonly used model age patterns for this purpose are the Coale and Demeny and the United Nations systems. Since the development of these models, many additional sources of data for under-five mortality have become available, making possible a general evaluation of age patterns of infant and child mortality. In this paper, we do a systematic comparison of empirical values of ₁ q ₀ and ₄ q ₁ against model age patterns, and discuss whether observed deviations are due to data errors, or whether they reflect true epidemiological patterns not addressed in existing model life tables.

Methods and Findings

We used vital registration data from the Human Mortality Database, sample survey data from the World Fertility Survey and Demographic and Health Surveys programs, and data from Demographic Surveillance Systems. For each of these data sources, we compared empirical combinations of ₁ q ₀ and ₄ q ₁ against combinations provided by Coale and Demeny and United Nations model age patterns. We found that, on the whole, empirical values fall relatively well within the range provided by these models, but we also found important exceptions. Sub-Saharan African countries have a tendency to exhibit high values of ₄ q ₁ relative to ₁ q ₀, a pattern that appears to arise for the most part from true epidemiological causes. While this pattern is well known in the case of western Africa, we observed that it is more widespread than commonly thought. We also found that the emergence of HIV/AIDS, while perhaps contributing to high relative values of ₄ q ₁, does not appear to have substantially modified preexisting patterns. We also identified a small number of countries scattered in different parts of the world that exhibit unusually low values of ₄ q ₁ relative to ₁ q ₀, a pattern that is not likely to arise merely from data errors. Finally, we illustrate that it is relatively common for populations to experience changes in age patterns of infant and child mortality as they experience a decline in mortality.

Conclusions

Existing models do not appear to cover the entire range of epidemiological situations and trajectories. Therefore, model life tables should be used with caution for estimating ₁ q ₀ and ₄ q ₁ on the basis of ₅ q ₀. Moreover, this model-based estimation procedure assumes that the input value of ₅ q ₀ is correct, which may not always be warranted, especially in the case of survey data. A systematic evaluation of data errors in sample surveys and their impact on age patterns of ₁ q ₀ and ₄ q ₁ is urgently needed, along with the development of model age patterns of under-five mortality that would cover a wider range of epidemiological situations and trajectories. Please see later in the article for the Editors'' Summary.     

Trauma-Related Mortality among Adults in Rural Western Kenya: Characterising Deaths Using Data from a Health and Demographic Surveillance System

Background

Information on trauma-related deaths in low and middle income countries is limited but needed to target public health interventions. Data from a health and demographic surveillance system (HDSS) were examined to characterise such deaths in rural western Kenya.

Methods And Findings

Verbal autopsy data were analysed. Of 11,147 adult deaths between 2003 and 2008, 447 (4%) were attributed to trauma; 71% of these were in males. Trauma contributed 17% of all deaths in males 15 to 24 years; on a population basis mortality rates were greatest in persons over 65 years. Intentional causes accounted for a higher proportion of male than female deaths (RR 2.04, 1.37-3.04) and a higher proportion of deaths of those aged 15 to 65 than older people. Main causes in males were assaults (n=79, 25%) and road traffic injuries (n=47, 15%); and falls for females (n=17, 13%). A significantly greater proportion of deaths from poisoning (RR 5.0, 2.7-9.4) and assault (RR 1.8, 1.2-2.6) occurred among regular consumers of alcohol than among non-regular drinkers. In multivariate analysis, males had a 4-fold higher risk of death from trauma than females (Adjusted Relative Risk; ARR 4.0; 95% CI 1.7-9.4); risk of a trauma death rose with age, with the elderly at 7-fold higher risk (ARR 7.3, 1.1-49.2). Absence of care was the strongest predictor of trauma death (ARR 12.2, 9.4-15.8). Trauma-related deaths were higher among regular alcohol drinkers (ARR 1.5, 1.1-1.9) compared with non-regular drinkers.

Conclusions

While trauma accounts for a small proportion of deaths in this rural area with a high prevalence of HIV, TB and malaria, preventive interventions such as improved road safety, home safety strategies for the elderly, and curbing harmful use of alcohol, are available and could help diminish this burden. Improvements in systems to record underlying causes of death from trauma are required.     

An Arsenic Exposure Model: Probabilistic Validation Using Empirical Data

This paper describes development of a multi-pathway arsenic exposure model. The model uses information on arsenic concentrations in food, water, soil, and dust, combined with estimates of intake and medium-specific absorption. Urinary arsenic is predicted assuming that 60% of absorbed arsenic is excreted in urine under steady state conditions. Fecal arsenic is predicted assuming all unabsorbed arsenic is excreted in feces. We applied this model at a former copper smelter site. Site specific distributions were available for the following parameters: soil and dust arsenic concentration (geometric mean approximately 100 to 200?ppm and 50 to 100?ppm, respectively); the combined childhood soil and dust ingestion rate (geometric mean of 20?mg/d); soil and dust arsenic relative bioavailability (geometric mean 0.20 and 0.28, respectively); exposure duration; water arsenic concentration; air arsenic concentration; and total arsenic in food. Monte Carlo simulation was used to predict daily arsenic uptake and excretion in urine and feces for children. Predicted urine arsenic levels were less than measured levels (73% to 88% of measured values, depending on region of site). On the other hand, predicted fecal arsenic levels exceeded measured levels by a factor of 1.7 to 4.6. We were able to improve the correspondence between predicted and measured arsenic excretion rates by decreasing the assumed value of the combined soil and dust ingestion rate, and increasing the assumed bioavailability of arsenic in soil and dust.     

Prediction of Vigilant Attention and Cognitive Performance Using Self-Reported Alertness,Circadian Phase,Hours since Awakening,and Accumulated Sleep Loss

Sleep restriction causes impaired cognitive performance that can result in adverse consequences in many occupational settings. Individuals may rely on self-perceived alertness to decide if they are able to adequately perform a task. It is therefore important to determine the relationship between an individual’s self-assessed alertness and their objective performance, and how this relationship depends on circadian phase, hours since awakening, and cumulative lost hours of sleep. Healthy young adults (aged 18–34) completed an inpatient schedule that included forced desynchrony of sleep/wake and circadian rhythms with twelve 42.85-hour “days” and either a 1:2 (n = 8) or 1:3.3 (n = 9) ratio of sleep-opportunity:enforced-wakefulness. We investigated whether subjective alertness (visual analog scale), circadian phase (melatonin), hours since awakening, and cumulative sleep loss could predict objective performance on the Psychomotor Vigilance Task (PVT), an Addition/Calculation Test (ADD) and the Digit Symbol Substitution Test (DSST). Mathematical models that allowed nonlinear interactions between explanatory variables were evaluated using the Akaike Information Criterion (AIC). Subjective alertness was the single best predictor of PVT, ADD, and DSST performance. Subjective alertness alone, however, was not an accurate predictor of PVT performance. The best AIC scores for PVT and DSST were achieved when all explanatory variables were included in the model. The best AIC score for ADD was achieved with circadian phase and subjective alertness variables. We conclude that subjective alertness alone is a weak predictor of objective vigilant or cognitive performance. Predictions can, however, be improved by knowing an individual’s circadian phase, current wake duration, and cumulative sleep loss.     

Identifying and Targeting Mortality Disparities: A Framework for Sub-Saharan Africa Using Adult Mortality Data from South Africa

Background

Health inequities in developing countries are difficult to eradicate because of limited resources. The neglect of adult mortality in Sub-Saharan Africa (SSA) is a particular concern. Advances in data availability, software and analytic methods have created opportunities to address this challenge and tailor interventions to small areas. This study demonstrates how a generic framework can be applied to guide policy interventions to reduce adult mortality in high risk areas. The framework, therefore, incorporates the spatial clustering of adult mortality, estimates the impact of a range of determinants and quantifies the impact of their removal to ensure optimal returns on scarce resources.

Methods

Data from a national cross-sectional survey in 2007 were used to illustrate the use of the generic framework for SSA and elsewhere. Adult mortality proportions were analyzed at four administrative levels and spatial analyses were used to identify areas with significant excess mortality. An ecological approach was then used to assess the relationship between mortality “hotspots” and various determinants. Population attributable fractions were calculated to quantify the reduction in mortality as a result of targeted removal of high-impact determinants.

Results

Overall adult mortality rate was 145 per 10,000. Spatial disaggregation identified a highly non-random pattern and 67 significant high risk local municipalities were identified. The most prominent determinants of adult mortality included HIV antenatal sero-prevalence, low SES and lack of formal marital union status. The removal of the most attributable factors, based on local area prevalence, suggest that overall adult mortality could be potentially reduced by ∼90 deaths per 10,000.

Conclusions

The innovative use of secondary data and advanced epidemiological techniques can be combined in a generic framework to identify and map mortality to the lowest administration level. The identification of high risk mortality determinants allows health authorities to tailor interventions at local level. This approach can be replicated elsewhere.     

Empirical Bayes Estimation and Prediction Using Summary-Level Information From External Big Data Sources Adjusting for Violations of Transportability

Large external data sources may be available to augment studies that collect data to address a specific research objective. In this article we consider the problem of building regression models for prediction based on individual-level data from an “internal” study while incorporating summary information from an “external” big data source. We extend the work of Chatterjee et al. (J Am Stat Assoc 111(513):107–117, 2006) by introducing an adaptive empirical Bayes shrinkage estimator that uses the external summary-level information and the internal data to trade bias with variance for protection against departures in the conditional probability distribution of the outcome given a set of covariates between the two populations. We use simulation studies and a real data application using external summary information from the Prostate Cancer Prevention Trial to assess the performance of the proposed methods in contrast to maximum likelihood estimation and the constrained maximum likelihood (CML) method developed by Chatterjee et al. (J Am Stat Assoc 111(513):107–117, 2006). Our simulation studies show that the CML method can be biased and inefficient when the assumption of a transportable covariate distribution between the external and internal populations is violated, and our empirical Bayes estimator provides protection against bias and loss of efficiency.     

Using Health Surveillance Systems Data to Assess the Impact of AIDS and Antiretroviral Treatment on Adult Morbidity and Mortality in Botswana

Introduction

Botswana''s AIDS response included free antiretroviral treatment (ART) since 2002, achieving 80% coverage of persons with CD4<350 cells/µl by 2009–10. We explored impact on mortality and HIV prevalence, analyzing surveillance and civil registration data.

Methods

Hospital natural cause admissions and deaths from the Health Statistics Unit (HSU) over 1990–2009, all-cause deaths from Midnight Bed Census (MNC) over 1990–2011, institutional and non-institutional deaths recorded in the Registry of Birth and Deaths (RBD) over 2003–2010, and antenatal sentinel surveillance (ANC) over 1992–2011 were compared to numbers of persons receiving ART. Mortality was adjusted for differential coverage and completeness of institutional and non-institutional deaths, and compared to WHO and UNAIDS Spectrum projections.

Results

HSU deaths per 1000 admissions declined 49% in adults 15–64 years over 2003–2009. RBD mortality declined 44% (807 to 452/100,000 population in adults 15–64 years) over 2003–2010, similarly in males and females. Generally, death rates were higher in males; declines were greater and earlier in younger adults, and in females. In contrast, death rates in adults 65+, particularly females increased over 2003–2006. MNC all-age post-neonatal mortality declined 46% and 63% in primary and secondary level hospitals, over 2003–2011. We estimated RBD captured 80% of adult deaths over 2006–2011. Comparing empirical, completeness-adjusted deaths to Spectrum estimates, declines over 2003–2009 were similar overall (47% vs. 54%); however, Spectrum projected larger and earlier declines particularly in women. Following stabilization and modest decreases over 1998–2002, HIV prevalence in pregnant women 15–24 and 25–29-years declined by >50% and >30% through 2011, while continuing to increase in older women.

Conclusions

Adult mortality in Botswana fell markedly as ART coverage increased. HIV prevalence declines may reflect ART-associated reductions in sexual transmission. Triangulation of surveillance system data offers a reasonable approach to evaluate impact of HIV/AIDS interventions, complementing cohort approaches that monitor individual-level health outcomes.     

Impaired Glucose Metabolism among Those with and without Diagnosed Diabetes and Mortality: A Cohort Study Using Health Survey for England Data

Background

The extent that controlled diabetes impacts upon mortality, compared with uncontrolled diabetes, and how pre-diabetes alters mortality risk remain issues requiring clarification.

Methods

We carried out a cohort study of 22,106 Health Survey for England participants with a HbA1_C measurement linked with UK mortality records. We estimated hazard ratios (HRs) of all-cause, cancer and cardiovascular disease (CVD) mortality and 95% confidence intervals (CI) using Cox regression.

Results

Average follow-up time was seven years and there were 1,509 deaths within the sample. Compared with the non-diabetic and normoglycaemic group (HbA1_C <5.7% [<39mmol/mol] and did not indicate diabetes), undiagnosed diabetes (HbA1_C ≥6.5% [≥48mmol/mol] and did not indicate diabetes) inferred an increased risk of mortality for all-causes (HR 1.40, 1.09–1.80) and CVD (1.99, 1.35–2.94), as did uncontrolled diabetes (diagnosed diabetes and HbA1_C ≥6.5% [≥48mmol/mol]) and diabetes with moderately raised HbA1_C (diagnosed diabetes and HbA1_C 5.7-<6.5% [39-<48mmol/mol]). Those with controlled diabetes (diagnosed diabetes and HbA<5.7% [<39mmol/mol]) had an increased HR in relation to mortality from CVD only. Pre-diabetes (those who did not indicate diagnosed diabetes and HbA1_C 5.7-<6.5% [39-<48mmol/mol]) was not associated with increased mortality, and raised HbA1_C did not appear to have a statistically significant impact upon cancer mortality. Adjustment for BMI and socioeconomic status had a limited impact upon our results. We also found women had a higher all-cause and CVD mortality risk compared with men.

Conclusions

We found higher rates of all-cause and CVD mortality among those with raised HbA1_C, but not for those with pre-diabetes, compared with those without diabetes. This excess differed by sex and diabetes status. The large number of deaths from cancer and CVD globally suggests that controlling blood glucose levels and policies to prevent hyperglycaemia should be considered public health priorities.     

The Ophthalmic Branch of the Gutenberg Health Study: Study Design,Cohort Profile and Self-Reported Diseases

Purpose

This paper describes the study design, methodology, cohort profile and self-reported diseases in the ophthalmological branch of the Gutenberg Health Study (GHS).

Methods

The GHS is an ongoing, prospective, interdisciplinary, single-center, population-based cohort study in Germany. The main goals of the ophthalmological section are to assess the prevalence and incidence of ocular diseases and to explore risk factors, genetic determinants and associations with systemic diseases and conditions. The eye examination at baseline included a medical history, self-reported eye diseases, visual acuity, refractive errors, intraocular pressure, visual field, pachymetry, keratometry, fundus photography and tear sampling. The 5-year follow-up visit additionally encompassed optical coherence tomography, anterior segment imaging and optical biometry. The general examination included anthropometry; blood pressure measurement; carotid artery ultrasound; electrocardiogram; echocardiography; spirometry; cognitive tests; questionnaires; assessment of mental conditions; and DNA, RNA, blood and urine sampling.

Results

Of 15,010 participants (aged 35-74 years at the time of inclusion), ocular data are available for 14,700 subjects (97.9%). The mean visual acuity (standard deviation), mean spherical equivalent, median decimal visual acuity, and mean intraocular pressure were 0.08 (0.17) logMar, -0.42 (2.43) diopters, 0.9 and 14.24 (2.79) mm Hg, respectively. The frequencies of self-reported strabismus, glaucoma, surgery for retinal detachment and retinal vascular occlusions were 2.7%, 2.3%, 0.2% and 0.4%, respectively.

Conclusions

The GHS is the most extensive dataset of ophthalmic diseases and conditions and their risk factors in Germany and one of the largest cohorts worldwide. This dataset will provide new insight in the epidemiology of ophthalmic diseases and related medical specialties.     

Estimating the Biases Associated with Self-Perceived,Self-Reported,and Measured BMI on Mental Health

Purpose

The purpose of the study is to explore the relationship between individuals'' perceptions of their weight-status, self-reported height and weight, and measured weight status.

Methods

A national survey of 9,248 adolescents (47% male) between the ages of 11 and 27 is analyzed to determine whether inaccuracies in reporting are caused by misperception or conscious intent, and whether there tends to be a systematic bias in how individuals self-report. Self-esteem was used as an example of an important outcome variable in order to illustrate the magnitudes of the biases that may arise when using different measures of body size.

Results

Our results indicate that measured obesity status is associated with the reduction in Rosenberg Self-Esteem (RSE) of 0.30 points (p-value 0.005) among adolescents and 0.20 points (p-value 0.002) among young adults; in addition, using self-reported height and weight as opposed to measured height and weight does not result in a statistically detectable difference in the estimates.

Conclusions

Individuals'' self-reports of height and weight are not as unreliable as we might have expected. Although estimates from measured height and weight are preferred, in the absence of such measures, self-reported measures would likely be a reliable alternative. The differences in self-perception of weight status, however, imply that it is not comparable to measured weight categories.     

The Differences in Health Care Utilization between Medical Aid and Health Insurance: A Longitudinal Study Using Propensity Score Matching

Study Objectives

Health care utilization has progressively increased, especially among Medical Aid beneficiaries in South Korea. The Medical Aid classifies beneficiaries into two categories, type 1 and 2, on the basis of being incapable (those under 18 or over 65 years of age, or disabled) or capable of working, respectively. Medical Aid has a high possibility for health care utilization due to high coverage level. In South Korea, the national health insurance (NHI) achieved very short time to establish coverage for the entire Korean population. However there there remaine a number of problems to be solved. Therefore, the objective of this study was to investigate the differences in health care utilization between Medical Aid beneficiaries and Health Insurance beneficiaries.

Methods & Design

Data were collected from the Korean Welfare Panel Study from 2008 to 2012 using propensity score matching. Of the 2,316 research subjects, 579 had Medical Aid and 1,737 had health insurance. We also analyzed three dependent variables: days spent in the hospital, number of outpatient visits, and hospitalizations per year. Analysis of variance and longitudinal data analysis were used.

Results

The number of outpatient visits was 1.431 times higher (p<0.0001) in Medical Aid beneficiaries, the number of hospitalizations per year was 1.604 times higher (p<0.0001) in Medical Aid beneficiaries, and the number of days spent in the hospital per year was 1.282 times higher (p<0.268) for Medical Aid beneficiaries than in individuals with Health Insurance. Medical Aid patients had a 0.874 times lower frequency of having an unmet needs due to economic barrier (95% confidence interval: 0.662-1.156).

Conclusions

Health insurance coverage has an impact on health care utilization. More health care utilization among Medical Aid beneficiaries appears to have a high possibility of a moral hazard risk under the Health Insurance program. Therefore, the moral hazard for Medical Aid beneficiaries should be avoided.     

Repeated Measurement of the Intermountain Risk Score Enhances Prognostication for Mortality

Background

The Intermountain Risk Score (IMRS), composed of the complete blood count (CBC) and basic metabolic profile (BMP), predicts mortality and morbidity in medical and general populations. Whether longitudinal repeated measurement of IMRS is useful for prognostication is an important question for its clinical applicability.

Methods

Females (N = 5,698) and males (N = 5,437) with CBC and BMP panels measured 6 months to 2.0 years apart (mean 1.0 year) had baseline and follow-up IMRS computed. Survival analysis during 4.0±2.5 years (maximum 10 years) evaluated mortality (females: n = 1,255 deaths; males: n = 1,164 deaths) and incident major events (myocardial infarction, heart failure [HF], and stroke).

Results

Both baseline and follow-up IMRS (categorized as high-risk vs. low-risk) were independently associated with mortality (all p<0.001) in bivariable models. For females, follow-up IMRS had hazard ratio (HR) = 5.23 (95% confidence interval [CI] = 4.11, 6.64) and baseline IMRS had HR = 3.66 (CI = 2.94, 4.55). Among males, follow-up IMRS had HR = 4.28 (CI = 3.51, 5.22) and baseline IMRS had HR = 2.32 (CI = 1.91, 2.82). IMRS components such as RDW, measured at both time points, also predicted mortality. Baseline and follow-up IMRS strongly predicted incident HF in both genders.

Conclusions

Repeated measurement of IMRS at baseline and at about one year of follow-up were independently prognostic for mortality and incident HF among initially hospitalized patients. RDW and other CBC and BMP values were also predictive of outcomes. Further research should evaluate the utility of IMRS as a tool for clinical risk adjustment.     

Self-Reported Hindering Health Complaints of Community-Dwelling Older Persons: A Cross-Sectional Study

Purpose

Proactive care for community-dwelling older persons targeting self-reported hindering health complaints might prevent a decline in function. We investigated the spectrum of self-reported hindering complaints of community-dwelling older persons, the association with functional outcomes, and help-seeking behavior for these complaints.

Methods

Within the ISCOPE trial, participants (aged ≥75 years) received the ISCOPE screening questionnaire, including the open-ended question “At the moment, which health complaints limit you the most in your day-to-day life?”. After coding the answers with the ICPC-1-NL, we examined the prevalence and the association between the number and type of complaints and functional outcomes (Groningen Activities Restriction Scale, quality of life measured on Cantril’s Ladder, Mini-Mental State Examination, Geriatric Depression Scale-15, and De Jong Gierveld Loneliness Scale). Electronic patient registers were searched for the most reported complaints.

Results

7285 participants (median age: 81.0 years [IQR 77.8–85.3], 38.6% males) reported 13,524 hindering complaints (median 1, range 0–18); 32.7% reported no complaints. Participants mostly reported problems with walking/standing (22.1%), pain (20.8%) or weakness/tiredness (8.5%). These complaints were mentioned in the electronic patient registers in 28.3%, 91.3% and 55.5%, respectively. Higher numbers of hindering complaints were related to poorer scores on the number of domains with problems, Cantril’s Ladder for quality of life, Groningen Activities Restriction Scale, Geriatric Depression Scale, and De Jong Gierveld Loneliness Scale. Self-reported weakness, problems with walking/standing, visual limitations, cognitive problems, dyspnea and back complaints were associated with poorer scores on the number of domains with problems, Groningen Activities Restriction Scale, MMSE or Geriatric Depression Scale.

Conclusion

One third of the participants reported no hindering complaints. Problems with walking/standing, pain, and weakness/tiredness were most reported, but not always found in electronic patient registers. A higher number of, and specific self-reported hindering complaints, were associated with poorer scores on functional outcomes. It may be helpful for general practitioners to ask about these complaints and their influence on daily life.     

A Quantitative Test of the Neutral Theory Using Pooled Allozyme Data

Neutral theory predicts a positive correlation between the amount of polymorphism within species and evolutionary rate. Previous tests of this prediction using both allozyme and DNA data have led to conflicting conclusions about the influence of selection and mutation drift. It is argued here that quantitative conclusions about the adequacy of neutral theory can be obtained by analyzing genetic data pooled from many sources. Using this approach, a large database containing information on allozyme variation in over 1500 species is used to examine the relationship between heterozygosity and genetic distance. The results provide support for the hypothesis that a major percentage of protein variation can be explained by variation in neutral mutation rate, and a minor percentage by strong selection.     

Prediction of Risk Factors for Coronary Heart Disease Using Framingham Risk Score in Korean Men

Background

Currently, there is sparse data available on the relationship between coronary heart disease (CHD) and its risk factors estimated by the Framingham Risk Score (FRS) in Korea. This is particularly true when looking at risk factors of CHD associated with the FRS after adjustment for other covariates especially in healthy subjects.

Methodology/Principal Findings

We conducted a prospective cohort study to examine the association between the risk factors of CHD and the risk for CHD estimated by FRS in 15,239 men in 2005 and 2010. The FRS is based on six coronary risk factors: gender, age, total cholesterol, high-density lipoprotein (HDL)-cholesterol, systolic blood pressure (BP), and smoking habit. Multiple linear regression analysis was used to analyze the relationships between the FRS and risk factors for CHD. This study reported that apolipoproetein B (apoB), apoA-I, apoB/apoA-I, alcohol intake, log-transformed TG, log-transformed hsCRP, LDL-cholesterol, hypertension, diabetes, regular exercise, and BMI were significantly associated with the FRS. Above all, the partial R-square of apoB was 14.77%, which was overwhelmingly bigger than that of other variables in model V. This indicated that apoB accounted for 14.77% of the variance in FRS.

Conclusion/Significance

In this study, apoB was found to be the most important determinant for the future development of CHD during a 5-year follow-up in healthy Korean men.     

Beyond Proximity: The Importance of Green Space Useability to Self-Reported Health

Access to parks and green spaces within residential neighbourhoods has been shown to be an important pathway to generating better physical and mental health for individuals and communities. Early research in this area often failed to identify specific attributes that contributed to reported health outcomes, with more recent research focused on exploring relationships between health outcomes and aspects of access and design. A mixed methods research project conducted in Perth, Western Australia examined the role that neighbourhood green space played in influencing residents’ self-reported health status, and this paper identifies significant relationships found between perceptions of green space quality and self-reported health. It focuses on the factors that were found to be most positively associated with better health outcomes: proximity, retention, useability and visitation of neighbourhood green space.