Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Mental health and growing up factsheet. Cannabis and mental health: information for young people.

About this leaflet This is one in a series of leaflets for parents, teachers and young people entitled Mental Health and Growing Up. These leaflets aim to provide practical, up-to-date information about mental health problems (emotional, behavioural and psychiatric disorders) that can affect children and young people. This leaflet gives you some basic facts about cannabis and also how it might affect your mental health. Introduction Lots of young people want to know about drugs. Often, people around you are taking them, and you may wonder how it will make you feel. You may even feel under pressure to use drugs in order to fit in, or be â?~coolâ?T. You may have heard that cannabis is no worse than cigarettes, or that it is harmless. What is cannabis? The cannabis plant is a member of the nettle family that has grown wild throughout the world for centuries. People have used it for lots of reasons, other than the popular relaxing effect. It comes in two main forms: ï,§ resin, which is a brown black lump also known as bhang, ganja or hashish ï,§ herbal cannabis, which is made up of the dried leaves and flowering tops, and is known as grass, marijuana, spliff, weed, etc. Skunk cannabis is made from a cannabis plant that has more active chemicals in it (THC), and the effect on your brain is stronger. Because â?~streetâ?T cannabis varies so much in strength, you will not be able to tell exactly how it will make you feel at any particular time. What does it do to you? When you smoke cannabis, the active compounds reach your brain quickly through your bloodstream. It then binds/sticks to a special receptor in your brain. This causes your nerve cells to release different chemicals, and causes the effects that you feel. These effects can be enjoyable or unpleasant. Often the bad effects take longer to appear than the pleasant ones. ï,§ Good/pleasant effects: You may feel relaxed and talkative, and colours or music may seem more intense. ï,§ Unpleasant effects: Feeling sick/panicky, feeling paranoid or hearing voices, feeling depressed and unmotivated. Unfortunately, some people can find cannabis addictive and so have trouble stopping use even when they are not enjoying it. The effects on your mental health Using cannabis triggers mental health problems in people who seemed to be well before, or it can worsen any mental health problems you already have. Research has shown that people who are already at risk of developing mental health problems are more likely to start showing symptoms of mental illness if they use cannabis regularly. For example if someone in your family has depression or schizophrenia, you are at higher risk of getting these illness when you use cannabis. The younger you are when you start using it, the more you may be at risk. This is because your brain is still developing and can be more easily damaged by the active chemicals in cannabis. If you stop using cannabis once you have started to show symptoms of mental illness, such as depression, paranoia or hearing voices, these symptoms may go away. However, not everyone will get better just by stopping smoking. If you go on using cannabis, the symptoms can get worse. It can also make any treatment that your doctor might prescribe for you, work less well. Your illness may come back more quickly, and more often if you continue to use cannabis once you get well again. Some people with mental health problems find that using cannabis makes them feel a bit better for a while. Unfortunately this does not last, and it does nothing to treat the illness. In fact, it may delay you from getting help you need and the illness may get worse in the longer term. [For the full factsheet, click on the link above]This resource was contributed by The National Documentation Centre on Drug Use.

Caring for Seniors With Alzheimer's Disease: Canadian Institute for Health Information

Caring for Seniors In 2007-2008, one in five seniors (20%) in Canada receiving long-term home care had a diagnosis of Alzheimer's disease or other dementia. Nearly one in six (17%) of these clients with dementia were suffering from moderate to severe impairment in cognition and daily functioning yet still managed to remain at home.This study from the Canadian Institute for Health Information also found that one in six (17%) seniors with dementia living in residential care facilities (such as nursing or long-term care homes) in 2008-2009 had relatively low levels of impairment or could still perform basic functions quite well on their own. The odds of a senior with low impairment being placed in residential care were seven times more likely if the senior had a tendency to wander. Marital status was also a factor in determining whether a senior with low impairment was newly admitted to a care facility rather than at home with home care. 

Dementia, lesbians and gay men: Alzheimer's Australia

This paper was commissioned by Alzheimer's Australia to promote an informed discussion about the issues affecting lesbians or gay men with dementia or caring for someone with dementia. It addresses the issues associated with the interaction between service providers and lesbian and gay men with dementia and their family carers, including the complexity of family relationships and barriers that may affect care provision and quality of life.The focus of this paper is on lesbian and gay seniors, including their same-sex partners. Not all people with dementia are seniors; however younger lesbians and gay men living with dementia may have a number of similar concerns and needs to those of lesbian and gay seniors. This paper also includes information about the needs of younger lesbians and gay men who are supporting a heterosexual family member living with dementia.Some issues and concerns identified in this paper are shared by transgender people, as well as additional specific issues such as the impact of medical interventions on ageing, including surgical changes and hormone treatments over a long period of time. This paper encompasses the needs of those members of the transgender community to the extent to which they identify themselves as gay or lesbian, but does not address the specific needs of transgender people.This paper seeks to contextualise the issues involved and inform readers by way of discussion and case examples.Full paper available at: http://www.apo.org.au/node/23373

The Marmot Review: Updated data and information 2 years on

To mark the two year anniversary since The Marmot Review ('Fair Society, Healthy Lives') was published, on the 15th of February the UCL Institute of Health Equity published new data on key health inequalities indicators at local authority level in England.Main Findings:Life Expectancy – this has historically been one of the main indicators of health inequalities.The Marmot Indicators from this year’s charts show the average life expectancy for eachlocal authority and the level of inequality within each authority area (7):-While overall life expectancy at birth in England increased by 0.3 years for both menand women between 2007-9 and 2008-10, inequalities in life expectancy betweenneighbourhoods increased by 0.1 years for men and showed no change for women-Among the 150 upper tier local authorities in England, life expectancy improved inthe majority of cases (133 areas saw improvements for men and 125 sawimprovements for women). However inequalities also increased in the majority ofareas (104 for men and 92 for women).-The largest increase in inequality in life expectancy was in West Berkshire for men(2.0 years) and inMiddlesbrough for women (2 years). The largest decreases ininequality were in Kensington and Chelsea for both men and women (1.9 and 1.1years respectively. To find out more, please read: - The press release, including key figures and main findings. - A blog by Michael Marmot about the data and it's implications. - Press coverage of the data in national and local newspapers and websites. - A powerpoint presentation on the key findings.

Inventory and description of disease management programs in Switzerland

Background: Disease management, a system of coordinated health care interventions for populations with chronic diseases in which patient self-care is a key aspect, has been shown to be effective for several conditions. Little is known on the supply of disease management programs in Switzerland. Objectives: To systematically search, record and evaluate data on existing disease management programs in Switzerland. Methods: Programs met our operational definition of disease management if their interventions targeted a chronic disease, included a multidisciplinary team and lasted at least 6 months. To find existing programs, we searched Swiss official websites, Swiss web-pages using Google, medical electronic database (Medline), and checked references from selected documents. We also contacted personally known individuals, those identified as possibly working in the field, individuals working in major Swiss health insurance companies and people recommended by previously contacted persons (snow ball strategy). We developed an extraction grid and collected information pertaining to the following 8 domains: patient population, intervention recipient, intervention content, delivery personnel, method of communication, intensity and complexity, environment and clinical outcomes (measures?). Results: We identified 8 programs fulfilling our operational definition of disease management. Programs targeted patients with diabetes, hypertension, heart failure, obesity, alcohol dependence, psychiatric disorders or breast cancer, and were mainly directed towards patients. The interventions were multifaceted and included education in almost all cases. Half of the programs included regularly scheduled follow-up, by phone in 3 instances. Healthcare professionals involved were physicians, nurses, case managers, social workers, psychologists and dietitians. None fulfilled the 6 criteria established by the Disease Management Association of America. Conclusions: Our study shows that disease management programs, in a country with universal health insurance coverage and little incentive to develop new healthcare strategies, are scarce, although we may have missed existing programs. Nonetheless, those already implemented are very interesting and rather comprehensive. Appropriate evaluation of these programs should be performed in order to build upon them and try to design a generic disease management framework suited to the Swiss healthcare system.

Information sources on ethnicity and health and healthcare

This report provides a summary of work to date on a joint regional mapping project of ethnicity and health inequalities. It also covers equity of access to health care and initiatives (national and local) to address health inequalities between ethnic groups.

Information and Intelligence forum presentation 2007: Jon Cox

Presentation from Jon Cox (Norfolk PCT) at the May 2007 Public Health Information and Intelligence forum

Informing healthier choices: Information and intelligence for healthy populations

One of the commitments given in the Choosing Health white paper was to develop and implement a comprehensive public health information and intelligence strategy. This work was led by a specially constituted Task Force and informed by extensive public and professional consultation conducted in 2006. The resulting strategy sets out an approach that will strengthen health information and intelligence resources across England.This document reports on the results of consultation on the strategy.

Finding Public Health Knowledge and Information - A Guide for the South East

The leaflet contains a list of 'key' public health knowledge and information resources and contacts. Last updated August 2007.

Information Update 100 - Feb 2010

An information briefing produced by the Department of Health - South East, based at the Government Office for the South East. The briefing acts as a signpost to public health and social care resources, evidence, policy, news and events.

Health Poverty Index information and resources

This is a collection of HPI resources stored on the SEPHO web site

Spearhead Health Inequalities Intervention Tool: background information

This document provides background information on the context for the Spearhead Health Inequalities Intervention Tool.