http://www.pophealthmetrics.com The latest research articles published by Population Health Metrics 2010-08-17T00:00:00Z This is an RSS newsfeed from BioMed Central It is intended to be used with an RSS reader. For more information about RSS newsfeeds from BioMed Central, visit http://www.biomedcentral.com/info/about/rss/ Background: A previous estimate of the burden of schizophrenia in Thailand relied on epidemiological estimates from elsewhere. The aim of this study is to estimate the prevalence and disease burden of schizophrenia in Thailand using local data sources that recently have become available. Methods: The prevalence of schizophrenia was estimated from a community mental health survey supplemented by a count of hospital admissions. Using data from recent meta-analyses of the risk of mortality and remission, we derived incidence and average duration using DisMod software. We used treated disability weights based on patient and clinician ratings from our own local survey of patients in contact with mental health services and applied methods from Australian Burden of Disease and cost-effectiveness studies. We applied untreated disability weights from the Global Burden of Disease (GBD) study. Uncertainty analysis was conducted using Monte Carlo simulation. Results: The prevalence of schizophrenia at ages 15-59 in the Thai population was 8.8 per 1,000 (95% CI: 7.2, 10.6) with a male-to-female ratio of 1.1-to-1. The disability weights from local data were somewhat lower than the GBD weights. The disease burden in disability-adjusted life years was similar in men (70,000; 95% CI: 64,000, 77, 000) and women (75,000; 95% CI: 69,000, 83,000). The impact of using the lower Thai disability weights on the DALY estimates was small in comparison to the uncertainty in prevalence. Conclusions: Prevalence of schizophrenia was more critical to an accurate estimate of burden of disease in Thailand than variations in disability weights. http://www.pophealthmetrics.com/content/8/1/24 Pudtan Phanthunane Theo Vos Harvey Whiteford Melanie Bertram Pichet Udomratn Population Health Metrics 2010, 8:24 2010-08-17T00:00:00Z doi:10.1186/1478-7954-8-24 Population Health Metrics 1478-7954 8 24 2010-08-17T00:00:00Z PDF ObjectiveThis study assessed the agreement between medical physicians in their interpretation of verbal autopsy (VA) interview data for identifying causes of neonatal deaths in rural Bangladesh. Methods: The study was carried out in Matlab, a rural sub-district in eastern Bangladesh. Trained persons conducted the VA interview with the mother or another family member at the home of the deceased. Three physicians and a medical assistant independently reviewed the VA interviews to assign causes of death using the International Classification of Diseases - Tenth Revision (ICD-10) codes. A physician assigned cause was decided when at least two physicians agreed on a cause of death. Cause-specific mortality fraction (CSMF), kappa (k) statistic, sensitivity, specificity, and positive predictive values were applied to compare agreement between the reviewers. Results: Of the 365 neonatal deaths reviewed, agreement on a direct cause of death was reached by at least two physicians in 339 (93%) of cases. Physician and medical assistant reviews of causes of death demonstrated the following levels of diagnostic agreement for the main causes of deaths: for birth asphyxia the sensitivity was 84%, specificity 93%, and kappa 0.77. For prematurity/low birth weight, the sensitivity, specificity, and kappa statistics were, respectively, 53%, 96%, and 0.55, for sepsis/meningitis they were 48%, 98%, and 0.53, and for pneumonia they were 75%, 94%, and 0.51. Conclusion: This study revealed a moderate to strong agreement between physician- assigned and medical assistant- assigned major causes of neonatal death. A well-trained medical assistant could be considered an alternative for assigning major causes of neonatal deaths in rural Bangladesh and in similar settings where physicians are scarce and their time costs more. A validation study with medically confirmed diagnosis will improve the performance of VA for assigning cause of neonatal death. http://www.pophealthmetrics.com/content/8/1/23 Hafizur Chowdhury Sandra Thompson Mohammed Ali Nurul Alam Mohammed Yunus Peter Streatfield Population Health Metrics 2010, 8:23 2010-08-17T00:00:00Z doi:10.1186/1478-7954-8-23 Population Health Metrics 1478-7954 8 23 2010-08-17T00:00:00Z XML Background: Participant nonresponse in an HIV serosurvey can affect estimates of HIV prevalence. Nonresponse can arise from a participant's refusal to provide a blood sample or the failure to trace a sampled individual. In a serosurvey conducted by the African Population and Health Research Center and Kenya Medical Research Centre in the slums of Nairobi, 43% of sampled individuals did not provide a blood sample. This paper describes selective participation in the serosurvey and estimates bias in HIV prevalence figures. Methods: The paper uses data derived from an HIV serosurvey nested in an on-going demographic surveillance system. Nonresponse was assessed using logistic regression and multiple imputation methods to impute missing data for HIV status using a set of common variables available for all sampled participants. Results: Age, residence, high mobility, wealth, and ethnicity were independent predictors of a sampled individual not being contacted. Individuals aged 30-34 years, females, individuals from the Kikuyu and Kamba ethnicity, married participants, and residents of Viwandani were all less likely to accept HIV testing when contacted. Although men were less likely to be contacted, those found were more willing to be tested compared to females. The overall observed HIV prevalence was overestimated by 2%. The observed prevalence for male participants was underestimated by about 1% and that for females was overestimated by 3%. These differences were small and did not affect the overall estimate substantially as the observed estimates fell within the confidence limits of the corrected prevalence estimate. Conclusions: Nonresponse in the HIV serosurvey in the two informal settlements was high, however, the effect on overall prevalence estimate was minimal. http://www.pophealthmetrics.com/content/8/1/22 Abdhalah Ziraba Nyovani Madise Mwau Matilu Eliya Zulu John Kebaso Samoel Khamadi Vincent Okoth Alex Ezeh Population Health Metrics 2010, 8:22 2010-07-22T00:00:00Z doi:10.1186/1478-7954-8-22 Population Health Metrics 1478-7954 8 22 2010-07-22T00:00:00Z XML Background: Developing countries generally lack complete vital registration systems that can produce cause of death information for health planning in their populations. As an alternative, verbal autopsy (VA) - the process of interviewing family members or caregivers on the circumstances leading to death - is often used by Demographic Surveillance Systems to generate cause of death data. Physician review (PR) is the most common method of interpreting VA, but this method is a time- and resource-intensive process and is liable to produce inconsistent results. The aim of this paper is to explore how a computer-based probabilistic model, InterVA, performs in comparison with PR in interpreting VA data in the Nairobi Urban Health and Demographic Surveillance System (NUHDSS). Methods: Between August 2002 and December 2008, a total of 1,823 VA interviews were reviewed by physicians in the NUHDSS. Data on these interviews were entered into the InterVA model for interpretation. Cause-specific mortality fractions were then derived from the cause of death data generated by the physicians and by the model. We then estimated the level of agreement between both methods using Kappa statistics. Results: The level of agreement between individual causes of death assigned by both methods was only 35% (κ = 0.27, 95% CI: 0.25 - 0.30). However, the patterns of mortality as determined by both methods showed a high burden of infectious diseases, including HIV/AIDS, tuberculosis, and pneumonia, in the study population. These mortality patterns are consistent with existing knowledge on the burden of disease in underdeveloped communities in Africa. Conclusions: The InterVA model showed promising results as a community-level tool for generating cause of death data from VAs. We recommend further refinement to the model, its adaptation to suit local contexts, and its continued validation with more extensive data from different settings. http://www.pophealthmetrics.com/content/8/1/21 Samuel Oti Catherine Kyobutungi Population Health Metrics 2010, 8:21 2010-06-29T00:00:00Z doi:10.1186/1478-7954-8-21 Population Health Metrics 1478-7954 8 21 2010-06-29T00:00:00Z XML Background: Many epidemiological studies rely on self-reported information, the accuracy of which is critical for unbiased estimates of population health. Previously, accuracy has been analyzed by comparing self-reports to other sources, such as cancer registries. Cancer is believed to be a well-reported condition. This paper uses novel panel data to test the consistency of cancer reports for respondents with repeated self-reports. Methods: Data come from 978 adults who reported having been diagnosed with cancer in at least one of four waves of the Panel Study of Income Dynamics, 1999-2005. Consistency of cancer occurrence reports and precision of timing of onset were studied as a function of individual and cancer-related characteristics using logistic and ordered logistic models. Results: Almost 30% of respondents gave inconsistent cancer reports, meaning they said they never had cancer after having said they did have cancer in a previous interview; 50% reported the year of diagnosis with a discrepancy of two or more years. More recent cancers were reported with a higher consistency and timing precision; cervical cancer was reported more inaccurately than other cancer types. Demographic and socio-economic factors were only weak predictors of reporting quality. Conclusions: Results suggest that retrospective reports of cancer contain significant measurement error. The errors, however, are fairly random across different social groups, meaning that the results based on the data are not systematically biased by socio-economic factors. Even for health events as salient as cancer, researchers should exercise caution about the presumed accuracy of self-reports, especially if the timing of diagnosis is an important covariate. http://www.pophealthmetrics.com/content/8/1/20 Anna Zajacova Jennifer Dowd Robert Schoeni Robert Wallace Population Health Metrics 2010, 8:20 2010-06-25T00:00:00Z doi:10.1186/1478-7954-8-20 Population Health Metrics 1478-7954 8 20 2010-06-25T00:00:00Z XML Background: Verbal autopsy analyses are widely used for estimating cause-specific mortality rates (CSMR) in the vast majority of the world without high-quality medical death registration. Verbal autopsies -- survey interviews with the caretakers of imminent decedents -- stand in for medical examinations or physical autopsies, which are infeasible or culturally prohibited.Methods and FindingsWe introduce methods, simulations, and interpretations that can improve the design of automated, data-derived estimates of CSMRs, building on a new approach by King and Lu (2008). Our results generate advice for choosing symptom questions and sample sizes that is easier to satisfy than existing practices. For example, most prior effort has been devoted to searching for symptoms with high sensitivity and specificity, which has rarely if ever succeeded with multiple causes of death. In contrast, our approach makes this search irrelevant because it can produce unbiased estimates even with symptoms that have very low sensitivity and specificity. In addition, the new method is optimized for survey questions caretakers can easily answer rather than questions physicians would ask themselves. We also offer an automated method of weeding out biased symptom questions and advice on how to choose the number of causes of death, symptom questions to ask, and observations to collect, among others. Conclusions: With the advice offered here, researchers should be able to design verbal autopsy surveys and conduct analyses with greatly reduced statistical biases and research costs. http://www.pophealthmetrics.com/content/8/1/19 Gary King Ying Lu Kenji Shibuya Population Health Metrics 2010, 8:19 2010-06-23T00:00:00Z doi:10.1186/1478-7954-8-19 Population Health Metrics 1478-7954 8 19 2010-06-23T00:00:00Z XML Background: The ongoing increase in life expectancy in developed countries is associated with changes in the shape of the survival curve. These changes can be characterized by two main, distinct components: (i) the decline in premature mortality, i.e., the concentration of deaths around some high value of the mean age at death, also termed rectangularization of the survival curve; and (ii) the increase of this mean age at death, i.e., longevity, which directly reflects the reduction of mortality at advanced ages. Several recent observations suggest that both mechanisms are simultaneously taking place. Methods: We propose a set of indicators aiming to quantify, disentangle, and compare the respective contribution of rectangularization and longevity increase to the secular increase of life expectancy. These indicators, based on a nonparametric approach, are easy to implement. Results: We illustrate the method with the evolution of the Swiss mortality data between 1876 and 2006. Using our approach, we are able to say that the increase in longevity and rectangularization explain each about 50% of the secular increase of life expectancy. Conclusion: Our method may provide a useful tool to assess whether the contribution of rectangularization to the secular increase of life expectancy will remain around 50% or whether it will be increasing in the next few years, and thus whether concentration of mortality will eventually take place against some ultimate biological limit. http://www.pophealthmetrics.com/content/8/1/18 Valentin Rousson Fred Paccaud Population Health Metrics 2010, 8:18 2010-06-09T00:00:00Z doi:10.1186/1478-7954-8-18 Population Health Metrics 1478-7954 8 18 2010-06-09T00:00:00Z XML Background: The aim of this epidemiological study was to investigate the relationship of thermal discomfort with cold extremities (TDCE) to age, gender, and body mass index (BMI) in a Swiss urban population. Methods: In a random population sample of Basel city, 2,800 subjects aged 20-40 years were asked to complete a questionnaire evaluating the extent of cold extremities. Values of cold extremities were based on questionnaire-derived scores. The correlation of age, gender, and BMI to TDCE was analyzed using multiple regression analysis. Results: A total of 1,001 women (72.3% response rate) and 809 men (60% response rate) returned a completed questionnaire. Statistical analyses revealed the following findings: Younger subjects suffered more intensely from cold extremities than the elderly, and women suffered more than men (particularly younger women). Slimmer subjects suffered significantly more often from cold extremities than subjects with higher BMIs. Conclusions: Thermal discomfort with cold extremities (a relevant symptom of primary vascular dysregulation) occurs at highest intensity in younger, slimmer women and at lowest intensity in elderly, stouter men. http://www.pophealthmetrics.com/content/8/1/17 Maneli Mozaffarieh Paolo Fontana Gasio Andreas Schotzau Selim Orgul Josef Flammer Kurt Krauchi Population Health Metrics 2010, 8:17 2010-06-04T00:00:00Z doi:10.1186/1478-7954-8-17 Population Health Metrics 1478-7954 8 17 2010-06-04T00:00:00Z XML ObjectiveTo determine the value of maternal height and weight data on birth certificate records when estimating prevalence of overweight and obese adults at the neighborhood level.Research Design and MethodsRegression analysis was used to determine how much variation in the percentage of the adult population with a body mass index (BMI) of ≥ 25 (based on survey data) could be accounted for by the percentage of mothers with BMI ≥ 25 (based on birth certificate data) -- alone and in combination with other sociodemographic characteristics of census tracts. Results: Alone, the percentage of mothers with BMI ≥ 25 explained more than half (R2 = .52) of the variation in the percentage of all residents in census tracts with BMI ≥ 25; in combination with several measures of the sociodemographic characteristics of the census tracts, 75% ( R2 = 75.2) of the variation is explained. Conclusions: Maternal height and weight data available from birth certificate records may be useful for identifying neighborhoods with relatively high or low prevalence of adult residents who are overweight or obese. This is especially true if used in combination with readily available census data. http://www.pophealthmetrics.com/content/8/1/16 David Webb Jessica Robbins Joan Bloch Jennifer Culhane Population Health Metrics 2010, 8:16 2010-05-25T00:00:00Z doi:10.1186/1478-7954-8-16 Population Health Metrics 1478-7954 8 16 2010-05-25T00:00:00Z XML Background: Complete and accurate ascertainment of mortality is critically important in any longitudinal study. Tracking of mortality is particularly essential among US military members because of unique occupational exposures (e.g., worldwide deployments as well as combat experiences). Our study objectives were to describe the early mortality experience of Panel 1 of the Millennium Cohort, consisting of participants in a 21-year prospective study of US military service members, and to assess data sources used to ascertain mortality. Methods: A population-based random sample (n = 256,400) of all US military service members on service rosters as of October 1, 2000, was selected for study recruitment. Among this original sample, 214,388 had valid mailing addresses, were not in the pilot study, and comprised the group referred to in this study as the invited sample. Panel 1 participants were enrolled from 2001 to 2003, represented all armed service branches, and included active-duty, Reserve, and National Guard members. Crude death rates, as well as age- and sex-adjusted overall and age-adjusted, category-specific death rates were calculated and compared for participants (n = 77,047) and non-participants (n = 137,341) based on data from the Social Security Administration Death Master File, Department of Veterans Affairs (VA) files, and the Department of Defense Medical Mortality Registry, 2001-2006. Numbers of deaths identified by these three data sources, as well as the National Death Index, were compared for 2001-2004. Results: There were 341 deaths among the participants for a crude death rate of 80.7 per 100,000 person-years (95% confidence interval [CI]: 72.2,89.3) compared to 820 deaths and a crude death rate of 113.2 per 100,000 person-years (95% CI: 105.4, 120.9) for non-participants. Age-adjusted, category-specific death rates highlighted consistently higher rates among study non-participants. Although there were advantages and disadvantages for each data source, the VA mortality files identified the largest number of deaths (97%). Conclusions: The difference in crude and adjusted death rates between Panel 1 participants and non-participants may reflect healthier segments of the military having the opportunity and choosing to participate. In our study population, mortality information was best captured using multiple data sources. http://www.pophealthmetrics.com/content/8/1/15 Tomoko Hooper Gary Gackstetter Cynthia LeardMann Edward Boyko Lisa Pearse Besa Smith Paul Amoroso Tyler Smith For the Millennium Cohort Study Team Population Health Metrics 2010, 8:15 2010-05-24T00:00:00Z doi:10.1186/1478-7954-8-15 Population Health Metrics 1478-7954 8 15 2010-05-24T00:00:00Z XML