Population Health Metrics

Publications in this journal

• Article: Age of onset in chronic diseases: new method and application to dementia in Germany.

  Ralph Brinks, Sandra Landwehr, Regina Waldeyer
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  ABSTRACT: BACKGROUND: Age of onset is an important outcome to characterize a population with a chronic disease. With respect to social, cognitive, and physical aspects for patients and families, dementia is especially burdensome. In Germany, like in many other countries, it is highly prevalent in the older population and imposes enormous efforts for caregivers and society. METHODS: We develop an incidence-prevalence-mortality model to derive the mean and variance of the age of onset in chronic diseases. Age- and sex-specific incidence and prevalence of dementia is taken from published values based on health insurance data from 2002. Data about the age distribution in Germany in 2002 comes from the Federal Statistical Office. RESULTS: Mean age of onset of a chronic disease depends on a) the age-specific incidence of the disease, b) the prevalence of the disease, and c) the age distribution of the population. The resulting age of onset of dementia in Germany in 2002 is 78.8 +/- 8.1 years (mean +/- standard deviation) for men and 81.9 +/- 7.6 years for women. CONCLUSIONS: Although incidence and prevalence of dementia in men are not greater than in women, men contract dementia approximately three years earlier than women. The reason lies in the different age distributions of the male and the female population in Germany.
  Population Health Metrics 05/2013; 11(1):6.
• Article: Mortality following the Haitian earthquake of 2010: a stratified cluster survey.

  Shannon Doocy, Megan Cherewick, Thomas Kirsch
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  ABSTRACT: INTRODUCTION: Research that seeks to better understand vulnerability to earthquakes and risk factors associated with mortality in low resource settings is critical to earthquake preparedness and response efforts. This study aims to characterize mortality and associated risk factors in the 2010 Haitian earthquake. METHODS: In January 2011, a survey of the earthquake affected Haitian population was conducted in metropolitan Port-au-Prince. A stratified 60x20 cluster design (n = 1200 households) was used with 30 clusters sampled in both camp and neighborhood locations. Households were surveyed regarding earthquake impact, current living conditions, and unmet needs. RESULTS: Mortality was estimated at 24 deaths (confidence interval [CI]: 20--28) per 1,000 in the sample population. Using two approaches, extrapolation of the survey mortality rate to the exposed population yielded mortality estimates ranging from a low of 49,033 to a high of 86,555. No significant difference in mortality was observed by sex (p = .786); however, age was significant with adults age 50+ years facing increased mortality risk. Odds of death were not significantly higher in camps, with 27 deaths per 1,000 (CI: 22--34), compared to neighborhoods, where the death rate was 19 per 1,000 (CI: 15--25; p = 0.080). Crowding and residence in a multistory building were also associated with increased risk of death. CONCLUSIONS: Haiti earthquake mortality estimates are widely varied, though epidemiologic surveys conducted to date suggest lower levels of mortality than officially reported figures. Strategies to mitigate future mortality burden in future earthquakes should consider improvements to the built environment that are feasible in urban resource-poor settings.
  Population Health Metrics 04/2013; 11(1):5.
• Article: Association of blood lipids, creatinine, albumin, and CRP with socioeconomic status in Malawi.

  Iliana V Kohler, Beth J Soldo, Philip Anglewicz, Ben Chilima, Hans-Peter Kohler
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  ABSTRACT: BACKGROUND: The objective of this analysis is to document the relationship between biomarker-based indicators of health and socioeconomic status (SES) in a low-income African population where the cumulative effects of exposure to multiple stressors on physiological functions and health in general are expected to be highly detrimental for the well-being of individuals. METHODS: Biomarkers were collected subsequent to the 2008 round of the Malawi Longitudinal Study of Families and Health (MLSFH), a population-based study in rural Malawi, including blood lipids (total cholesterol, LDL, HDL, ratio of total cholesterol to HDL), biomarkers of renal and liver organ function (albumin and creatinine) and wide-range C-reactive protein (CRP) as a non-specific biomarker for inflammation. These biomarkers represent widely used indicators of health that are individually or cumulatively recognized as risk factors for age-related diseases among prime-aged and elderly individuals. Quantile regressions are used to estimate the age-gradient and the within-day variation of each biomarker distribution. Differences in biomarker levels by socioeconomic status are investigated using descriptive and multivariate statistics. RESULTS: Overall, the number of significant associations between the biomarkers and socioeconomic measures is very modest. None of the biomarkers significantly varies with schooling. Except for CRP where being married is weakly associated with lower risk of having an elevated CRP level, marriage is not associated with the biomarkers measured in the MLSFH. Similarly, being Muslim is associated with a lower risk of having elevated CRP, but otherwise religion does not predict being in the high-risk quartiles of any of the MLSFH biomarkers. Wealth does not predict being in the high-risk quartile of any of the MLSFH biomarkers, with the exception of a weak effect on creatinine. Being overweight or obese is associated with increased likelihood of being in the high-risk quartile for cholesterol, Chol/HDL ratio, and LDL. CONCLUSIONS: The results provide only weak evidence for variation of the biomarkers by socioeconomic indicators in a poor Malawian context. Our findings underscore the need for further research to understand the determinants of health outcomes in a poor low-income context such as rural Malawi.
  Population Health Metrics 02/2013; 11(1):4.
• Article: Mortality and excess risk in US adults with pre-diabetes and diabetes: a comparison of two nationally representative cohorts, 1988-2006.

  Andrew Stokes, Neil K Mehta
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  ABSTRACT: BACKGROUND: There is strong evidence on the efficacy of behavioral modification and treatment for reducing diabetes incidence and diabetes-related morbidity and mortality in persons with pre-diabetes and diabetes. But the extent to which the evidence has translated into gains in health in these population sub-groups in the United States is unclear. Monitoring national diabetes-related mortality levels over time is important for evaluating the effectiveness of the US health system response to diabetes. METHODS: We identified individuals with pre-diabetes and diabetes using Hemoglobin A1c. Two consecutive periods for investigating differences in mortality according to categories of glycemia were derived using nationally representative survey data on US adults ages 35-74 from subsequent rounds of the National Health and Nutrition Examination Survey (1988-1994 and 1999-2002). Age-standardized mortality rates were calculated for individuals with pre-diabetes and diabetes and proportional hazards models were used to assess change in the relative risks of dysglycemia (pre-diabetes and diabetes) adjusting for multiple confounding factors. RESULTS: Age-standardized mortality rates in individuals with pre-diabetes and diabetes showed no statistically significant change between 1988-2001 and 1999-2006. In individuals with pre-diabetes, mortality rates were 11.19 and 14.02 deaths per 1,000 person-years in the early and later period, respectively. The corresponding values for individuals with diabetes were 20.34 and 20.82 deaths per 1,000 person-years. In contrast, the absolute level of mortality in the normo-glycemic population declined significantly between 1988-2001 and 1999-2006 (7.81 to 6.04; p for difference less than 0.05). Adjusting for social and demographic variables, smoking and body mass index in a multivariate analysis, the hazard ratio of dysglycemia increased from 1.62 (95% CI: 1.36-1.93) in 1988-2001 to 2.36 (95% CI: 1.70-3.27) in 1999-2006 (p for difference less than 0.05). CONCLUSIONS: We find no evidence of declines in excess mortality in persons with dysglycemia between 1988-2001 and 1999-2006, a result that was robust to adjustment for social and demographic variables, smoking, and body mass index. In the context of long-term secular declines in mortality in the US population, our findings suggest that individuals with pre-diabetes and diabetes should be an important focus of future interventions aimed at improving population health in the US.
  Population Health Metrics 02/2013; 11(1):3.
• Article: Mortality in an Aboriginal Medical Service (Redfern) cohort.

  Stephen Morrell, Bronwen Phillips, Richard J Taylor, John Daniels, Kate Burgess, Naomi Mayers
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  ABSTRACT: BACKGROUND: Published estimates of Aboriginal mortality and life expectancy (LE) for the eastern Australian states are derived from demographic modelling techniques to estimate the population and extent of under-recording of Aboriginality in death registration. No reliable empirical information on Aboriginal mortality and LE exists for New South Wales (NSW), the most populous Australian state in which 29% of Aboriginal people reside. This paper estimates mortality and LE in a large, mainly metropolitan cohort of Aboriginal clients from the Aboriginal Medical Service (AMS) Redfern, Sydney, NSW. METHODS: Identifying information from patient records accrued by the AMS Redfern since 1980 of definitely Aboriginal clients, without distinction between Aboriginal and Torres Strait Islander (n=24,035), was extracted and linked to the National Death Index (NDI) at the Australian Institute of Health and Welfare (AIHW). Age-specific mortality rates and LEs for each sex were estimated using the AMS patient population as the denominator, discounted for deaths. Directly age-standardised mortality and LEs were estimated for 1995-1999, 2000-2004, and 2005-2009, along with 95% confidence intervals. Comparisons were made with other estimates of Aboriginal mortality and LE and with the total Australian population. RESULTS: Mortality declined in the AMS Redfern cohort over 1995-2009 and the decline occurred mostly in the under-44 age group. Male LE at birth was estimated to be 64.4 years (95%CI:62.6-66.1) in 1995-1999, 65.6 years (95%CI:64.1-67.1) in 2000-2004, and 67.6 years (95%CI:65.9-69.2) for 2005-2009. In females, these LE estimates were 69.6 (95%CI:68.0-71.2), 71.1 (95%CI:69.9-72.4), and 71.4 (95%CI:70.0-72.8) years. LE in the AMS cohort was 11 years lower for males and 12 years lower for females than corresponding all-Australia LEs for the same periods. These were similar to estimates for Australian Aboriginal people overall for the same period by the Aboriginal Burden of Disease for 2009, using the General Growth Balance (GGB) model approach, and by the Australian Bureau of Statistics (ABS) for 2005-2007. LE in the AMS cohort was somewhat lower than these estimates for NSW Aboriginal people, and higher than ABS 2005-2007 estimates for Aboriginal people from Northern Territory, South Australia, and Western Australia. CONCLUSIONS: The AMS Redfern cohort has provided the first empirically based estimates of mortality and LE trends in a large sample of Aboriginal people from NSW.
  Population Health Metrics 02/2013; 11(1):2.
• Article: Decomposing the Indigenous life expectancy gap by risk factors: a life table analysis.

  Yuejen Zhao, Jo Wright, Stephen Begg, Steven Guthridge
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  ABSTRACT: BACKGROUND: The estimated gap in life expectancy (LE) between Indigenous and non-Indigenous Australians was 12 years for men and 10 years for women, whereas the Northern Territory Indigenous LE gap was at least 50% greater than the national figures. This study aims to explain the Indigenous LE gap by common modifiable risk factors. METHODS: This study covered the period from 1986 to 2005. Unit record death data from the Northern Territory were used to assess the differences in LE at birth between the Indigenous and non-Indigenous populations by socioeconomic disadvantage, smoking, alcohol abuse, obesity, pollution, and intimate partner violence. The population attributable fractions were applied to estimate the numbers of deaths associated with the selected risks. The standard life table and cause decomposition technique was used to examine the individual and joint effects on health inequality. RESULTS: The findings from this study indicate that among the selected risk factors, socioeconomic disadvantage was the leading health risk and accounted for one-third to one-half of the Indigenous LE gap. A combination of all six selected risks explained over 60% of the Indigenous LE gap. CONCLUSIONS: Improving socioeconomic status, smoking cessation, and overweight reduction are critical to closing the Indigenous LE gap. This paper presents a useful way to explain the impact of risk factors of health inequalities, and suggests that reducing poverty should be placed squarely at the centre of the strategies to close the Indigenous LE gap.
  Population Health Metrics 01/2013; 11(1):1.
• Article: Household food access and child malnutrition: Results from the eight-country MAL-ED study.

  Stephanie Psaki, Zulfiqar A Bhutta, Tahmeed Ahmed, Shamsir Ahmed, Pascal Bessong, Munirul Islam, Sushil John, Margaret Kosek, Aldo Lima, Cebisa Nesamvuni, Prakash Shrestha, Erling Svensen, Monica McGrath, Stephanie Richard, Jessica Seidman, Laura Caulfield, Mark Miller, William Checkley
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  ABSTRACT: BACKGROUND: Stunting results from decreased food intake, poor diet quality, and a high burden of early childhood infections, and contributes to significant morbidity and mortality worldwide. Although food insecurity is an important determinant of child nutrition, including stunting, development of universal measures has been challenging due to cumbersome nutritional questionnaires and concerns about lack of comparability across populations. We investigate the relationship between household food access, one component of food security, and indicators of nutritional status in early childhood across eight country sites. METHODS: We administered a socioeconomic survey to 800 households in research sites in eight countries, including a recently validated nine-item food access insecurity questionnaire, and obtained anthropometric measurements from children aged 24 to 60 months. We used multivariable regression models to assess the relationship between household food access insecurity and anthropometry in children, and we assessed the invariance of that relationship across country sites. RESULTS: Average age of study children was 41 months. Mean food access insecurity score (range: 0--27) was 5.8, and varied from 2.4 in Nepal to 8.3 in Pakistan. Across sites, the prevalence of stunting (42%) was much higher than the prevalence of wasting (6%). In pooled regression analyses, a 10-point increase in food access insecurity score was associated with a 0.20 SD decrease in height-for-age Z score (95% CI 0.05 to 0.34 SD; p = 0.008). A likelihood ratio test for heterogeneity revealed that this relationship was consistent across countries (p = 0.17). CONCLUSIONS: Our study provides evidence of the validity of using a simple household food access insecurity score to investigate the etiology of childhood growth faltering across diverse geographic settings. Such a measure could be used to direct interventions by identifying children at risk of illness and death related to malnutrition.
  Population Health Metrics 12/2012; 10(1):24.
• Article: Looking at the smoking epidemic through the lens of population pyramids: sociodemographic patterns of smoking in Italy, 1983 to 2005.

  Bruno Federico, Giovanni Capelli, Giuseppe Costa, Johan P Mackenbach, Anton E Kunst
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  ABSTRACT: BACKGROUND: Surveillance systems often present data by means of summary measures, like age-standardized rates. In this study, we aimed at comparing information derived from commonly used measures of smoking with that presented in modified population pyramids (PPs), using the example of the diffusion of smoking in Italy over the past two decades. METHODS: Data were derived from four National Health Interview Surveys carried out in 1983, 1990 to 1991, 1999 to 2000, and 2004 to 2005. After computing both age-specific and age-standardised rates of current, former, and never smoking, we constructed modified PPs by stratifying the male and female populations according to smoking status and educational level. RESULTS: Modified PPs showed several features of the smoking epidemic in Italy that were not apparent from conventional surveillance techniques. First, they showed that the population of smokers is aging, with most current smokers in 2005 being males aged 25 to 39 and females aged 40 to 49, whereas in 1983 most smokers belonged to the youngest age groups. Second, they showed that in 2005 most smokers were found among subjects with middle and higher education, whereas two decades earlier most smokers were (male) subjects with the lowest education. CONCLUSIONS: Modified PPs were able to show how absolute numbers of smokers were distributed by age and sex, how these numbers varied between population subgroups, and how they changed over time. PPs may help provide information on past and future trends in the absolute number of smokers and in their sociodemographic characteristics, which may be missed using only traditional surveillance methods.
  Population Health Metrics 11/2012; 10(1):23.
• Article: National, regional, and global trends in adult overweight and obesity prevalences.

  Gretchen A Stevens, Gitanjali M Singh, Yuan Lu, Goodarz Danaei, John K Lin, Mariel M Finucane, Adil N Bahalim, Russell K McIntire, Hialy R Gutierrez, Melanie Cowan, Christopher J Paciorek, Leanne Riley, Majid Ezzati
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  ABSTRACT: BACKGROUND: Overweight and obesity prevalence are commonly used for public and policy communication of the extent of the obesity epidemic, yet comparable estimates of trends in overweight and obesity prevalence by country are not available. METHODS: We estimated trends between 1980 and 2008 in overweight and obesity prevalence and their uncertainty for adults 20 years of age and older in 199 countries and territories. Data were from a previous study, which used a Bayesian hierarchical model to estimate mean body mass index (BMI) based on published and unpublished health examination surveys and epidemiologic studies. Here, we used the estimated mean BMIs in a regression model to predict overweight and obesity prevalence by age, country, year, and sex. The uncertainty of the estimates included both those of the Bayesian hierarchical model and the uncertainty due to cross-walking from mean BMI to overweight and obesity prevalence. RESULTS: The global age-standardized prevalence of obesity nearly doubled from 6.4% (95% uncertainty interval 5.7-7.2%) in 1980 to 12.0% (11.5-12.5%) in 2008. Half of this rise occurred in the 20 years between 1980 and 2000, and half occurred in the 8 years between 2000 and 2008. The age-standardized prevalence of overweight increased from 24.6% (22.7-26.7%) to 34.4% (33.2-35.5%) during the same 28-year period. In 2008, female obesity prevalence ranged from 1.4% (0.7-2.2%) in Bangladesh and 1.5% (0.9-2.4%) in Madagascar to 70.4% (61.9-78.9%) in Tonga and 74.8% (66.7-82.1%) in Nauru. Male obesity was below 1% in Bangladesh, Democratic Republic of the Congo, and Ethiopia, and was highest in Cook Islands (60.1%, 52.6-67.6%) and Nauru (67.9%, 60.5-75.0%). CONCLUSIONS: Globally, the prevalence of overweight and obesity has increased since 1980, and the increase has accelerated. Although obesity increased in most countries, levels and trends varied substantially. These data on trends in overweight and obesity may be used to set targets for obesity prevalence as requested at the United Nations high-level meeting on Prevention and Control of NCDs.
  Population Health Metrics 11/2012; 10(1):22.
• Article: The influence of measurement error on calibration, discrimination, and overall estimation of a risk prediction model.

  Laura C Rosella, Paul Corey, Therese A Stukel, Cam Mustard, Jan Hux, Doug G Manuel
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  ABSTRACT: BACKGROUND: Self-reported height and weight are commonly collected at the population level; however, they can be subject to measurement error. The impact of this error on predicted risk, discrimination, and calibration of a model that uses body mass index (BMI) to predict risk of diabetes incidence is not known. The objective of this study is to use simulation to quantify and describe the effect of random and systematic error in self-reported height and weight on the performance of a model for predicting diabetes. METHODS: Two general categories of error were examined: random (nondirectional) error and systematic (directional) error on an algorithm relating BMI in kg/m2 to probability of developing diabetes. The cohort used to develop the risk algorithm was derived from 23,403 Ontario residents that responded to the 1996/1997 National Population Health Survey linked to a population-based diabetes registry. The data and algorithm were then simulated to allow for estimation of the impact of these errors on predicted risk using the Hosmer-Lemeshow goodness-of-fit chi2 and C-statistic. Simulations were done 500 times with sample sizes of 9,177 for males and 10,618 for females. RESULTS: Simulation data successfully reproduced discrimination and calibration generated from population data. Increasing levels of random error in height and weight reduced the calibration and discrimination of the model. Random error biased the predicted risk upwards whereas systematic error biased predicted risk in the direction of the bias and reduced calibration; however, it did not affect discrimination. CONCLUSION: This study demonstrates that random and systematic errors in self-reported health data have the potential to influence the performance of risk algorithms. Further research that quantifies the amount and direction of error can improve model performance by allowing for adjustments in exposure measurements.
  Population Health Metrics 11/2012; 10(1):20.
• Article: Incidence, prevalence, and hybrid approaches to calculating disability-adjusted life years.

  S Andrew Schroeder
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  ABSTRACT: When disability-adjusted life years are used to measure the burden of disease on a population in a time interval, they can be calculated in several different ways: from an incidence, pure prevalence, or hybrid perspective. I show that these calculation methods are not equivalent and discuss some of the formal difficulties each method faces. I show that if we don't discount the value of future health, there is a sense in which the choice of calculation method is a mere question of accounting. Such questions can be important, but they don't raise deep theoretical concerns. If we do discount, however, choice of calculation method can change the relative burden attributed to different conditions over time. I conclude by recommending that studies involving disability-adjusted life years be explicit in noting what calculation method is being employed and in explaining why that calculation method has been chosen.
  Population Health Metrics 09/2012; 10(1):19.
• Article: Sentinel site community surveillance of mortality and nutritional status in southwestern Central African Republic, 2010.

  Grazia M Caleo, Aly Penda Sy, Serge Balandine, Jonathan Polonsky, Pedro Pablo Palma, Rebecca Freeman Grais, Francesco Checchi
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  ABSTRACT: During 2010, a community-based, sentinel site prospective surveillance system measured mortality, acute malnutrition prevalence, and the coverage of a Médecins Sans Frontières (MSF) intervention in four sous-préfectures of Lobaye prefecture in southwestern Central African Republic. We describe this surveillance system and its evaluation. Within 24 randomly selected sentinel sites, home visitors performed a census, weekly demographic surveillance of births, deaths, and in- or out-migration, and weekly anthropometry on a sample of children. We evaluated the system through various methods including capture-recapture analysis and repeat census. The system included 18,081 people at baseline. Over 32 weeks, the crude death rate was 1.0 (95% confidence interval [CI]: 0.8-1.2) deaths per 10,000 person-days (35 deaths per 1,000 person-years), with higher values during the rainy season. The under-5 death rate was approximately double. The prevalence of severe acute malnutrition (SAM) was 3.0% (95% CI: 2.3-4.0), almost half featuring kwashiorkor signs. The coverage of SAM treatment was 29.1%. The system detected >90% of deaths, and >90% of death reports appeared valid. However, demographic surveillance yielded discrepancies with the census and an implausible rate of population growth, while the predictive value of SAM classification was around 60%. We found evidence of a chronic health crisis in this remote region. MSF's intervention coverage improved progressively. Mortality data appeared valid, but inaccuracies in population denominators and anthropometric measurements were noted. Similar systems could be implemented in other remote settings and acute emergencies, but with certain technical improvements.
  Population Health Metrics 09/2012; 10(1):18.
• Article: Measuring infertility in populations: constructing a standard definition for use with demographic and reproductive health surveys.

  Maya N Mascarenhas, Hoiwan Cheung, Colin D Mathers, Gretchen A Stevens
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  ABSTRACT: BACKGROUND: Infertility is a significant disability, yet there are no reliable estimates of its global prevalence. Studies on infertility prevalence define the condition inconsistently, rendering the comparison of studies or quantitative summaries of the literature difficult. This study analyzed key components of infertility to develop a definition that can be consistently applied to globally available household survey data. METHODS: We proposed a standard definition of infertility and used it to generate prevalence estimates using 53 Demographic and Health Surveys (DHS). The analysis was restricted to the subset of DHS that contained detailed fertility information collected through the reproductive health calendar. We performed sensitivity analyses for key components of the definition and used these to inform our recommendations for each element of the definition. RESULTS: Exposure type (couple status, contraceptive use, and intent), exposure time, and outcomes were key elements of the definition that we proposed. Our definition produced estimates that ranged from 0.6 % to 3.4 % for primary infertility and 8.7 % to 32.6 % for secondary infertility. Our sensitivity analyses showed that using an exposure measure of five years is less likely to misclassify fertile unions as infertile. Additionally, using a current, rather than continuous, measure of contraceptive use over five years resulted in a median relative error in secondary infertility of 20.7 % (interquartile range of relative error [IQR]: 12.6 %-26.9 %), while not incorporating intent produced a corresponding error in secondary infertility of 58.2 % (IQR: 44.3 %-67.9 %). CONCLUSIONS: In order to estimate the global burden of infertility, prevalence estimates using a consistent definition need to be generated. Our analysis provided a recommended definition that could be applied to widely available global household data. We also summarized potential biases that should be considered when making estimates of infertility prevalence using household survey data.
  Population Health Metrics 08/2012; 10(1):17.
• Article: Health states for schizophrenia and bipolar disorder within the Global Burden of Disease 2010 Study.

  Alize J Ferrari, Sukanta Saha, John J McGrath, Rosana Norman, Amanda J Baxter, Theo Vos, Harvey A Whiteford
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  ABSTRACT: A comprehensive revision of the Global Burden of Disease (GBD) study is expected to be completed in 2012. This study utilizes a broad range of improved methods for assessing burden, including closer attention to empirically derived estimates of disability. The aim of this paper is to describe how GBD health states were derived for schizophrenia and bipolar disorder. These will be used in deriving health state-specific disability estimates. A literature review was first conducted to settle on a parsimonious set of health states for schizophrenia and bipolar disorder. A second review was conducted to investigate the proportion of schizophrenia and bipolar disorder cases experiencing these health states. These were pooled using a quality-effects model to estimate the overall proportion of cases in each state. The two schizophrenia health states were acute (predominantly positive symptoms) and residual (predominantly negative symptoms). The three bipolar disorder health states were depressive, manic, and residual. Based on estimates from six studies, 63% (38%-82%) of schizophrenia cases were in an acute state and 37% (18%-62%) were in a residual state. Another six studies were identified from which 23% (10%-39%) of bipolar disorder cases were in a manic state, 27% (11%-47%) were in a depressive state, and 50% (30%-70%) were in a residual state. This literature review revealed salient gaps in the literature that need to be addressed in future research. The pooled estimates are indicative only and more data are required to generate more definitive estimates. That said, rather than deriving burden estimates that fail to capture the changes in disability within schizophrenia and bipolar disorder, the derived proportions and their wide uncertainty intervals will be used in deriving disability estimates.
  Population Health Metrics 08/2012; 10(1):16.
• Article: OBAYA (obesity and adverse health outcomes in young adults): feasibility of a population-based multiethnic cohort study using electronic medical records.

  Corinna Koebnick, Ning Smith, Karl Huang, Mayra P Martinez, Heather A Clancy, Andrew E Williams, Lawrence H Kushi
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  ABSTRACT: BACKGROUND: Although obesity is a risk factor for many chronic diseases, we have only limited knowledge of the magnitude of these associations in young adults. A multiethnic cohort of young adults was established to close current knowledge gaps; cohort demographics, cohort retention, and the potential influence of migration bias were investigated. METHODS: For this population-based cross-sectional study, demographics, and measured weight and height were extracted from electronic medical records of 1,929,470 patients aged 20 to 39 years enrolled in two integrated health plans in California from 2007 to 2009. RESULTS: The cohort included about 84.4% of Kaiser Permanente California members in this age group who had a medical encounter during the study period and represented about 18.2% of the underlying population in the same age group in California. The age distribution of the cohort was relatively comparable to the underlying population in California Census 2010 population, but the proportion of women and ethnic/racial minorities was slightly higher. The three-year retention rate was 68.4%. CONCLUSION: These data suggest the feasibility of our study for medium-term follow-up based on sufficient membership retention rates. While nationwide 6% of young adults are extremely obese, we know little to adequately quantify the health burden attributable to obesity, especially extreme obesity, in this age group. This cohort of young adults provides a unique opportunity to investigate associations of obesity-related factors and risk of cancer in a large multiethnic population.
  Population Health Metrics 08/2012; 10(1):15.
• Article: Mortality trends in Tonga: an assessment based on a synthesis of local data.

  Sione Hufanga, Karen L Carter, Chalapati Rao, Alan D Lopez, Richard Taylor
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  ABSTRACT: BACKGROUND: Accurate measures of mortality level by age group, gender, and region are critical for health planning and evaluation. These are especially required for a country like Tonga, which has limited resources and works extensively with international donors. Mortality levels in Tonga were examined through an assessment of available published information and data available from the four routine death reporting systems currently in operation. METHODS: Available published data on infant mortality rate (IMR) and life expectancy (LE) in Tonga were sought through direct contact with the Government of Tonga and relevant international and regional organizations. Data sources were assessed for reliability and plausibility of estimates on the basis of method of estimation, original source of data, and data consistency. Unreliable sources were censored from further analysis and remaining data analysed for trends.Mortality data for 2001 to 2009 were obtained from both the Health Information System (based on medical certificates of death) and the Civil Registry. Data from 2005 to 2009 were also obtained from the Reproductive Health System of the Ministry of Health (MoH) (based on community nursing reports), and for 2005[EN DASH]2008, data were also obtained from the Prime Minister's office. Records were reconciled to create a single list of unique deaths and IMR and life tables calculated. Completeness of the reconciled data was examined using the Brass growth-balance method and capture-recapture analysis using two and three sources. RESULTS: Published IMR estimates varied significantly through to the late 1990s when most estimates converge to a narrower range between 10 and 20 deaths per 1,000 live births. Findings from reconciled data were consistent with this range, and did not demonstrate any significant trend over 2001 to 2009.Published estimates of LE from 2000 onwards varied from 65 to 75 years for males and 68 to 74 years for females, with most clustered around 70 to 71 for males and 72 to 73 for females. Reconciled empirical data for 2005 to 2009 produce an estimate of LE of 65.2 years (95 % confidence interval [CI]: 64.6 - 65.8) for males and 69.6 years (95 % CI: 69.0 [EN DASH] 70.2) for females, which are several years lower than published MoH and census estimates. Adult mortality (15 to 59 years) is estimated at 26.7 % for males and 19.8 % for females. Analysis of reporting completeness suggests that even reconciled data are under enumerated, and these estimates place the plausible range of LE between 60.4 to 64.2 years for males and 65.4 to 69.0 years for females, with adult mortality at 28.6 % to 36.3 % and 20.9 % to 27.7 %, respectively. CONCLUSIONS: The level of LE at a relatively low IMR and high adult mortality suggests that non-communicable diseases are having a profound limiting effect on health status in Tonga. There has been a sustained history of incomplete and erroneous mortality estimates for Tonga. The findings highlight the critical need to reconcile existing data sources and integrate reporting systems more fully to ensure all deaths in Tonga are captured and the importance of local empirical data in monitoring trends in mortality.
  Population Health Metrics 08/2012; 10(1):14.
• Article: Health, well-being, and measuring the burden of disease.

  Daniel M Hausman
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  ABSTRACT: This essay asks whether the global burden of diseases, injuries, and risk factors (GBD) shouldbe measured in terms of their consequences for health, as maintained by most of those whoare attempting to measure the GBD, or in terms of their consequences for well-being, asargued by John Broome. It answers that the burden of disease should be understood in termsof the consequences of disease for health, and it defends the wider efforts to measure healthby those who are in other ways skeptical of the project of measuring the GBD.
  Population Health Metrics 08/2012; 10(1):13.
• Article: Developing a comprehensive time series of GDP per capita for 210 countries from 1950 to 2015.

  Spencer L James, Paul Gubbins, Christopher Jl Murray, Emmanuela Gakidou
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  ABSTRACT: Income has been extensively studied and utilized as a determinant of health. There are severalsources of income expressed as gross domestic product (GDP) per capita, but there are notime series that are complete for the years between 1950 and 2015 for the 210 countries forwhich data exist. It is in the interest of population health research to establish a global timeseries that is complete from 1950 to 2015. METHODS: We collected GDP per capita estimates expressed in either constant US dollar terms orinternational dollar terms (corrected for purchasing power parity) from seven sources. Weapplied several stages of models, including ordinary least-squares regressions and mixedeffects models, to complete each of the seven source series from 1950 to 2015. The three USdollar and four international dollar series were each averaged to produce two new GDP percapita series. RESULTS AND DISCUSSION: Nine complete series from 1950 to 2015 for 210 countries are available for use. These seriescan serve various analytical purposes and can illustrate myriad economic trends and features.The derivation of the two new series allows for researchers to avoid any series-specific biasesthat may exist. The modeling approach used is flexible and will allow for yearly updating asnew estimates are produced by the source series. CONCLUSION: GDP per capita is a necessary tool in population health research, and our development andimplementation of a new method has allowed for the most comprehensive known time seriesto date.
  Population Health Metrics 07/2012; 10(1):12.
• Article: Predicting mortality with biomarkers: a population-based prospective cohort study for elderly Costa Ricans.

  Luis Rosero-Bixby, William H Dow
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  ABSTRACT: BACKGROUND: Little is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality. METHODS: This is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths. Main outcome: prospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models. RESULTS: Biomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP), glycated hemoglobin (HbA1c), and dehydroepiandrosterone sulfate (DHEAS). Strikingly, high blood pressure (BP) and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects. CONCLUSIONS: This study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow), are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in other settings: despite the continued medical focus on drugs for BP and cholesterol, high levels of BP and cholesterol have little predictive value of mortality in this elderly population.
  Population Health Metrics 06/2012; 10(1):11.