4 resultados para Health statistics

em University of Queensland eSpace - Australia


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Childhood obesity is a serious public health problem because of its strong association with adulthood obesity and the related adverse health consequences. The published literature indicates a rising prevalence of childhood obesity in both developed and developing countries. However no data exists on the prevalence in Northeast Thailand, one of the poorest regions of the country and one that has experienced a recent economic transition. The objective of this study was to estimate the prevalence of obesity in seven to nine year old children in urban Khon Kaen, Northeast Thailand. A cross-sectional school based survey was conducted to determine the prevalence of obesity in children of urban Khon Kaen, Thailand. Multi-staged cluster sampling was used to select 12 school clusters of 72 children each between the ages of 7 and 9 years, in primary school grades 1, 2 and 3 from government, private and demonstration schools. A total of 864 seven to nine year old school children were studied. Anthropometric measurements of standing height and weight were taken for all subjects to the nearest tenth of a centimetre and tenth of a kilogram respectively. Childhood obesity was defined as a weight-for-height Z-score above 2.0 standard deviations of the National Center for Health Statistics/World Health Organisation reference population median. The prevalence of childhood obesity was 10.8% (95% CI: 7.6, 13.9). Obesity was significantly more prevalent in boys than girls. The biggest difference was observed between the three school types, with the highest prevalence of obesity found at teacher training demonstration schools and the lowest at the government schools. This study provides the first data on childhood obesity prevalence in Northeast Thailand. The prevalence of 10.8 per cent is lower than that found in two other urban areas of Thailand but slightly higher than expected for this relatively poor region. If this prevalence rate increases, as observed in other countries in economic transition, the incidence of non-communicable diseases associated with obesity is also likely to increase, thus raising cause for concern and reason for intervention to both control and prevent obesity during childhood.

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In large epidemiological studies missing data can be a problem, especially if information is sought on a sensitive topic or when a composite measure is calculated from several variables each affected by missing values. Multiple imputation is the method of choice for 'filling in' missing data based on associations among variables. Using an example about body mass index from the Australian Longitudinal Study on Women's Health, we identify a subset of variables that are particularly useful for imputing values for the target variables. Then we illustrate two uses of multiple imputation. The first is to examine and correct for bias when data are not missing completely at random. The second is to impute missing values for an important covariate; in this case omission from the imputation process of variables to be used in the analysis may introduce bias. We conclude with several recommendations for handling issues of missing data. Copyright (C) 2004 John Wiley Sons, Ltd.

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Registration of births, recording deaths by age, sex and cause, and calculating mortality levels and differentials are fundamental to evidence-based health policy, monitoring and evaluation. Yet few of the countries with the greatest need for these data have functioning systems to produce them despite legislation providing for the establishment and maintenance of vital registration. Sample vital registration (SVR), when applied in conjunction with validated verbal autopsy, procedures and implemented in a nationally representative sample of population clusters represents an affordable, cost-effective, and sustainable short- and medium-term solution to this problem. SVR complements other information sources by producing age-, sex-, and cause-specific mortality data that are more complete and continuous than those currently available. The tools and methods employed in an SVR system, however, are imperfect and require rigorous validation and continuous quality assurance; sampling strategies for SVR are also still evolving. Nonetheless, interest in establishing SVR is rapidly growing in Africa and Asia. Better systems for reporting and recording data on vital events will be sustainable only if developed hand-in-hand with existing health information strategies at the national and district levels; governance structures; and agendas for social research and development monitoring. If the global community wishes to have mortality measurements 5 or 10 years hence, the foundation stones of SVR must be laid today.

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In 1992 the Australian Government adopted the National Mental Health Strategy in an attempt to improve the provision of mental health services. A component was to improve geographical access to hospital-based mental health services. This paper is concerned with determining if this objective has been achieved. Time-series data on patients (at a regional level) with mental illness in the State of Queensland are available for the years from 1968-69 to 2002-03. A change in regional classification by the Australian Bureau of Statistics complicates the analysis by precluding certain empirical tests such as converging utilisation rates by region. To overcome this problem, it was decided to apply concepts of concentration and equality that are commonly employed in industrial economics to the regional data. The empirical results show no evidence of improving regional access following the National Mental Health Strategy: in fact the statistical results show the opposite, i.e. declining regional access.