129 resultados para non-communicable disease (NCD)

em Deakin Research Online - Australia


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Private-sector organizations play a critical role in shaping the food environments of individuals and populations. However, there is currently very limited independent monitoring of private-sector actions related to food environments. This paper reviews previous efforts to monitor the private sector in this area, and outlines a proposed approach to monitor private-sector policies and practices related to food environments, and their influence on obesity and non-communicable disease (NCD) prevention. A step-wise approach to data collection is recommended, in which the first (‘minimal’) step is the collation of publicly available food and nutrition-related policies of selected private-sector organizations. The second (‘expanded’) step assesses the nutritional composition of each organization's products, their promotions to children, their labelling practices, and the accessibility, availability and affordability of their products. The third (‘optimal’) step includes data on other commercial activities that may influence food environments, such as political lobbying and corporate philanthropy. The proposed approach will be further developed and piloted in countries of varying size and income levels. There is potential for this approach to enable national and international benchmarking of private-sector policies and practices, and to inform efforts to hold the private sector to account for their role in obesity and NCD prevention.

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BACKGROUND: Historically, the focus of Non Communicable Disease (NCD) prevention and control has been cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), cancer and chronic respiratory diseases. Collectively, these account for more deaths than any other NCDs. Despite recent calls to include the common mental disorders (CMDs) of depression and anxiety under the NCD umbrella, prevention and control of these CMDs remain largely separate and independent. DISCUSSION: In order to address this gap, we apply a framework recently proposed by the Centers for Disease Control with three overarching objectives: (1) to obtain better scientific information through surveillance, epidemiology, and prevention research; (2) to disseminate this information to appropriate audiences through communication and education; and (3) to translate this information into action through programs, policies, and systems. We conclude that a shared framework of this type is warranted, but also identify opportunities within each objective to advance this agenda and consider the potential benefits of this approach that may exist beyond the health care system.

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Aim of this study was to investigate the poorly understood relationship between the process of urbanization and non-communicable diseases (NCDs) in Sri Lanka using a multi-component, quantitative measure of urbanicity.

NCD prevalence data were taken from the Sri Lankan Diabetes and Cardiovascular Study comprising a representative sample of people from seven of the nine provinces in Sri Lanka (n=4,485/5,000; response rate=89.7%). We constructed a measure of the urban environment for seven areas using a seven-item scale based on data from study clusters to develop an ―urbanicity” scale. The items were population size, population density, and access to markets, transportation, communications/media, economic factors, environment/sanitation, health, education, and housing quality. Linear and logistic regression models were constructed to examine the relationship between urbanicity and chronic disease risk factors.

Among men, urbanicity was positively associated with physical inactivity (OR: 3.22; 2.27 – 4.57), high body mass index (OR: 2.45; 95% CI: 1.88 – 3.20) and diabetes mellitus (OR: 2.44; 95% CI: 1.66 – 3.57). Among women, too, urbanicity was positively associated with physical inactivity (OR: 2.29; 95% CI: 1.64 – 3.21), high body mass index (OR: 2.92;95% CI: 2.41 – 3.55) and diabetes mellitus (OR: 2.10; 95% CI: 1.58 – 2.80).

There is a clear relationship between urbanicity and common modifiable risk factors for chronic disease in a representative sample of Sri Lankan adults.

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Aims. To evaluate the effectiveness of a health promotion
programme targeting dietary behaviours and physical
activity among male hourly-paid workers and to explore
demographic and attitudinal influences on dietary patterns
at baseline.
Methods. A controlled field trial compared workers at one
intervention and one control worksite. The intervention
comprised nutrition displays in the cafeteria and monthly
30-minute workshops for six months. Key outcome
measures at six and twelve-months were self-reported
dietary and lifestyle behaviours, nutrition knowledge, body
mass index (BMI), waist circumference and blood pressure.
Results. 132 men at the intervention site and 121 men at the
control site participated in the study and a high retention rate
(94% at 6-months and 89% at 12-months) was achieved. At
baseline, 40% of the total sample (253) were obese, 30% had
elevated blood pressure, 59% indicated an excessive fat intake
and 92% did not meet the recommended vegetable and fruit
intake. The intervention reduced fat intake, increased
vegetable intake and physical activity, improved nutrition
knowledge and reduced systolic blood pressure when
compared to the control site. There was no difference in
change in mean BMI or waist circumference. Reduction in
BMI was associated with reduction in fat intake.
Discussion. Low intensity workplace intervention can
significantly improve reported health behaviours and
nutrition knowledge although the impact on more
objective measures of risk was variable. A longer duration
or more intensive intervention may be required to achieve
further reduction in risk factors.

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Coordinated systems are required to ensure evidence-informed practice and evaluation of community-based interventions (CBIs). Knowledge translation and exchange (KTE) strategies show promise, but these require evaluation. This paper describes implementation and evaluation of COOPS, a national KTE platform to support best practice in obesity prevention CBIs. A logic model guides KTE activities including knowledge brokering, networking, tailored communications, training, and needs assessments. A mixed-methods evaluation includes communications data, knowledge brokering database, annual survey of CBIs, pre- and post-event questionnaires, interviews, social network analysis, and case studies. This evaluation will contribute to understanding the process of implementing a KTE platform with CBIs and its reach, quality and effectiveness.

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BACKGROUND: The WHO framework for non-communicable disease (NCD) describes risks and outcomes comprising the majority of the global burden of disease. These factors are complex and interact at biological, behavioural, environmental and policy levels presenting challenges for population monitoring and intervention evaluation. This paper explores the utility of machine learning methods applied to population-level web search activity behaviour as a proxy for chronic disease risk factors. METHODS: Web activity output for each element of the WHO's Causes of NCD framework was used as a basis for identifying relevant web search activity from 2004 to 2013 for the USA. Multiple linear regression models with regularisation were used to generate predictive algorithms, mapping web search activity to Centers for Disease Control and Prevention (CDC) measured risk factor/disease prevalence. Predictions for subsequent target years not included in the model derivation were tested against CDC data from population surveys using Pearson correlation and Spearman's r. RESULTS: For 2011 and 2012, predicted prevalence was very strongly correlated with measured risk data ranging from fruits and vegetables consumed (r=0.81; 95% CI 0.68 to 0.89) to alcohol consumption (r=0.96; 95% CI 0.93 to 0.98). Mean difference between predicted and measured differences by State ranged from 0.03 to 2.16. Spearman's r for state-wise predicted versus measured prevalence varied from 0.82 to 0.93. CONCLUSIONS: The high predictive validity of web search activity for NCD risk has potential to provide real-time information on population risk during policy implementation and other population-level NCD prevention efforts.

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BACKGROUND: Non-communicable diseases (NCD) are the leading cause of premature death and disability in the Pacific. In 2011, Pacific Forum Leaders declared "a human, social and economic crisis" due to the significant and growing burden of NCDs in the region. In 2013, Pacific Health Ministers' commitment to 'whole of government' strategy prompted calls for the development of a robust, sustainable, collaborative NCD monitoring and accountability system to track, review and propose remedial action to ensure progress towards the NCD goals and targets. The purpose of this paper is to describe a regional, collaborative framework for coordination, innovation and application of NCD monitoring activities at scale, and to show how they can strengthen accountability for action on NCDs in the Pacific. A key component is the Dashboard for NCD Action which aims to strengthen mutual accountability by demonstrating national and regional progress towards agreed NCD policies and actions.

DISCUSSION: The framework for the Pacific Monitoring Alliance for NCD Action (MANA) draws together core country-level components of NCD monitoring data (mortality, morbidity, risk factors, health system responses, environments, and policies) and identifies key cross-cutting issues for strengthening national and regional monitoring systems. These include: capacity building; a regional knowledge exchange hub; innovations (monitoring childhood obesity and food environments); and a robust regional accountability system. The MANA framework is governed by the Heads of Health and operationalised by a multi-agency technical Coordination Team. Alliance membership is voluntary and non-conditional, and aims to support the 22 Pacific Island countries and territories to improve the quality of NCD monitoring data across the region. In establishing a common vision for NCD monitoring, the framework combines data collected under the WHO Global Framework for NCDs with a set of action-orientated indicators captured in a NCD Dashboard for Action.

SUMMARY : Viewing NCD monitoring as a multi-component system and providing a robust, transparent mutual accountability mechanism helps align agendas, roles and responsibilities of countries and support organisations. The dashboard provides a succinct communication tool for reporting progress on implementation of agreed policies and actions and its flexible methodology can be easily expanded, or adapted for other regions.

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Background: Estimates of the economic cost of risk factors for chronic disease to the NHS provide evidence for prioritization of resources for prevention and public health. Previous comparable estimates of the economic costs of poor diet, physical inactivity, smoking, alcohol and overweight/obesity were based on economic data from 1992–93.

Methods: Diseases associated with poor diet, physical inactivity, smoking, alcohol and overweight/obesity were identified. Risk factor-specific population attributable fractions for these diseases were applied to disease-specific estimates of the economic cost to the NHS in the UK in 2006–07.

Results: In 2006–07, poor diet-related ill health cost the NHS in the UK £5.8 billion. The cost of physical inactivity was £0.9 billion. Smoking cost was £3.3 billion, alcohol cost £3.3 billion, overweight and obesity cost £5.1 billion.

Conclusion: The estimates of the economic cost of risk factors for chronic disease presented here are based on recent financial data and are directly comparable. They suggest that poor diet is a behavioural risk factor that has the highest impact on the budget of the NHS, followed by alcohol consumption, smoking and physical inactivity.

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Background : Although urban residence is consistently identified as one of the primary correlates of non-communicable disease in low- and middle-income countries, it is not clear why or how urban settings predispose individuals and populations to non-communicable disease (NCD), or how this relationship could be modified to slow the spread of NCD. The urban–rural dichotomy used in most population health research lacks the nuance and specificity necessary to understand the complex relationship between urbanicity and NCD risk. Previous studies have developed and validated quantitative tools to measure urbanicity continuously along several dimensions but all have been isolated to a single country. The purposes of this study were 1) To assess the feasibility and validity of a multi-country urbanicity scale; 2) To report some of the considerations that arise in applying such a scale in different countries; and, 3) To assess how this scale compares with previously validated scales of urbanicity.

Methods : Household and community-level data from the Young Lives longitudinal study of childhood poverty in 59 communities in Ethiopia, India and Peru collected in 2006/2007 were used. Household-level data include parents’ occupations and education level, household possessions and access to resources. Community-level data include population size, availability of health facilities and types of roads. Variables were selected for inclusion in the urbanicity scale based on inspection of the data and a review of literature on urbanicity and health. Seven domains were constructed within the scale: Population Size, Economic Activity, Built Environment, Communication, Education, Diversity and Health Services.

Results : The scale ranged from 11 to 61 (mean 35) with significant between country differences in mean urbanicity; Ethiopia (30.7), India (33.2), Peru (39.4). Construct validity was supported by factor analysis and high corrected item-scale correlations suggest good internal consistency. High agreement was observed between this scale and a dichotomized version of the urbanicity scale (Kappa 0.76; Spearman’s rank-correlation coefficient 0.84 (p < 0.0001). Linear regression of socioeconomic indicators on the urbanicity scale supported construct validity in all three countries (p < 0.05).

Conclusions : This study demonstrates and validates a robust multidimensional, multi-country urbanicity scale. It is an important step on the path to creating a tool to assess complex processes like urbanization. This scale provides the means to understand which elements of urbanization have the greatest impact on health.

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The liberalization of international trade and foreign direct investment through multilateral, regional and bilateral agreements has had profound implications for the structure and nature of food systems, and therefore, for the availability, nutritional quality, accessibility, price and promotion of foods in different locations. Public health attention has only relatively recently turned to the links between trade and investment agreements, diets and health, and there is currently no systematic monitoring of this area. This paper reviews the available evidence on the links between trade agreements, food environments and diets from an obesity and non-communicable disease (NCD) perspective. Based on the key issues identified through the review, the paper outlines an approach for monitoring the potential impact of trade agreements on food environments and obesity/NCD risks. The proposed monitoring approach encompasses a set of guiding principles, recommended procedures for data collection and analysis, and quantifiable 'minimal', 'expanded' and 'optimal' measurement indicators to be tailored to national priorities, capacity and resources. Formal risk assessment processes of existing and evolving trade and investment agreements, which focus on their impacts on food environments will help inform the development of healthy trade policy, strengthen domestic nutrition and health policy space and ultimately protect population nutrition.

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For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

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BACKGROUND: Most populations are consuming too much salt which is the main contributor of high blood pressure, a leading risk factor of cardiovascular disease and stroke. The South Pacific Office of the World Health Organization has been facilitating the development of salt reduction strategies in Pacific Island Countries and areas (PICs). The objective of this analysis was to review progress to date and identify regional actions needed to support PICs and ensure they achieve the global target to reduce population salt intake by 30% by 2025.
METHODS: Relevant available national food, health and non-communicable disease (NCD) plans from all 22 PICs were reviewed. NCD co-ordinators provided updates and relayed experiences through semi-structured interviews. All activities were systematically categorised according to an existing salt reduction framework for the development of salt reduction strategies.
RESULTS: Salt reduction consultations had been held in 14 countries and final strategies or action plans developed in nine of these, with drafts available in a further three. Three other countries had integrated salt reduction into NCD strategic plans. Baseline monitoring of salt intake had been undertaken in three countries, salt levels in foods in nine countries and salt knowledge, attitude and behaviour surveys in four countries. Most countries were at early stages of implementation and identified limited resources as a barrier to action. Planned salt reduction strategies included work with food industry or importers, implementing regional salt reduction targets, reducing salt levels in school and hospital meals, behaviour change campaigns, and monitoring and evaluation.
CONCLUSIONS: There had been good progress on salt reduction planning in PICs. The need for increased capacity to effectively implement agreed activities, supported by regional standards and the establishment of improved monitoring systems, were identified as important steps to ensure the potential cardiovascular health benefits of salt reduction could be fully realised in the region.