Report on changes in utilization and need determinations for selected services between the 1999 and 2002 editions of the inventory of health care facilities.

"P.O. #233024"--Colophon.

Statewide health interview survey, 1982 /

On cover: Survey stats.

The relationship of socioeconomic and environmental factors with health trends in Illinois /

Cover title.

Vital and health statistics.

Published: Rockville, Md. <, 1973- >

National health interview survey questionnaires.

Mode of access: Internet.

National Health Interview Survey /

Mode of access: Internet.

Personality disorders in the community: Results from the Australian National Survey of Mental Health and Well-Being Part III - Relationships between specific type of personality disorder, Axis 1 mental disorders and physical conditions with disability and health consultations

Background The aims of this study were threefold. First, to ascertain whether personality disorder (PD) was a significant predictor of disability (as measured in a variety of ways) over and above that contributed by Axis I mental disorders and physical conditions. Second, whether the number of PD diagnoses given to an individual resulted in increasing severity of disability, and third, whether PD was a significant predictor of health and mental health consultations with GPs, psychiatrists, and psychologists, respectively, over the last 12 months. Method Data were obtained from the National Survey of Mental Health and Wellbeing, conducted between May and August 1997. A stratified random sample of households was generated, from which all those aged 18 and over were considered potential interviewees. There were 10 641 respondents to the survey, and this represented a response rate of 78%. Each interviewee was asked questions indexing specific ICD-10 PD criteria. Results Five measures of disability were examined. It was found that PD was a significant predictor of disability once Axis I and physical conditions were taken into account for four of the five disability measures. For three of the dichotomously-scored disability measures, odds ratios ranged from 1.88 to 6.32 for PD, whilst for the dimensionally-scored Mental Summary Subscale of the SF-12, a beta weight of -0.17 was recorded for PD. As regards number of PDs having a quasi-linear relationship to disability, there was some indication of this on the SF-12 Mental Summary Subscale and the two role functioning measures, and less so on the other two measures. As regards mental consultations, PD was a predictor of visits to GPs, psychiatrists and psychologists, over and above Axis I disorders and physical conditions. Conclusion The study reports findings from a nationwide survey conducted within Australia and as such the data are less influenced by the selection and setting bias inherent in other germane studies. However, it does support previous findings that PD is a significant predictor of disability and mental health consultations independent of Axis I disorders and physical conditions.

Socioeconomic disadvantage and changes in health risk behaviours in Australia: 1989-90 to 2001

Objective. Lower socioeconomic status (SES) is associated in industrialized countries with unhealthy lifestyle characteristics, such as smoking, physical inactivity and being overweight or obese. This paper examines changes over time in the association between SES and smoking status, physical activity and being overweight or obese in Australia. Methods. Data were taken from three successive national health surveys in Australia carried out in 1989-90 (n = 54 576), 1995 (n = 53 828) and 2001 (n = 26 863). Participants in these surveys were selected using a national probability sampling strategy, and aggregated data for geographical areas are used to determine the changing association between SES and lifestyle over time. Findings. Overall, men had less healthy lifestyles, In 2001 inverse SES trends for both men and women showed that those living in lower SES areas were more likely to smoke and to be sedentary and obese, There were some important socioeconomic changes over the period 1989-90 to 2001. The least socioeconomically disadvantaged areas had the largest decrease in the percentage of people smoking tobacco (24% decrease for men and 12% for women) and the largest decrease in the percentage of people reporting sedentary activity levels (25% decrease for men and 22% for women). While there has been a general increase in the percentage over time of those who are overweight or obese, there is a modest trend for being overweight to have increased (by about 16% only among females) among those living in areas of higher SES. Conclusion. Socioeconomic inequalities have been increasing for several key risk behaviours related to health; this suggests that T specific population-based prevention strategies intended to reduce health inequalities are needed.

Employment status and health in Spain before and after the Great Recession

This article analyzes the relationship between employment status (ES), on one hand, and self-rated health and psychological distress, on the other, in the context of the Great Recession beginning in 2008. For this purpose, it is necessary to move beyond the employment/unemployment dichotomy characteristics of previous theories and research concerning the relationship between the labor market, recession, and health. The authors use data from the Spanish National Health Surveys in 2006 (n = 15,128), before the crisis, and in 2012 (n = 11,124), when its consequences had taken effect. The results of the regression analysis indicate a structural change in the relationship between ES and health. Health inequality patterns changed during the crisis, with increased deterioration in the health of unemployed, especially the long-term unemployed, and self-employed workers. Health inequalities were reduced for temporary workers. The results support the idea that the structure of the association between ES and health varies according to the economic cycle. The association between recession, ES, and health would be directly related to the specific characteristics of the economic and employment contexts under study. In the Spanish case, labor market segmentation processes based on numerical flexibility—a key feature of the Mediterranean Variety of Capitalism—may explain the results obtained.

Socioeconomic Status and Health Behavior in Nepal

Thesis (Master's)--University of Washington, 2016-07

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

Is change in global self-rated health associated with change in affiliation with a primary care provider? Findings from a longitudinal study from New Zealand

To investigate the association of self-rated health and affiliation with a primary care provider (PCP) in New Zealand.
Methods

We used data from a New Zealand panel study of 22,000 adults. The main exposure was self-rated health, and the main outcome measure was affiliation with a PCP. Fixed effects conditional logistic models were used to control for observed time-varying and unobserved time-invariant confounding.
Results

In any given wave, the odds of being affiliated with a PCP were higher for those in good and fair/poor health relative to those in excellent health. While affiliation for Europeans increased as reported health declined, the odds of being affiliated were lower for Māori respondents reporting very good or good health relative to those in excellent health. No significant differences in the association by age or gender were observed.
Conclusions

Our data support the hypothesis that those in poorer health are more likely to be affiliated with a PCP. Variations in affiliation for Māori could arise for several reasons, including differences in care-seeking behaviour and perceived need of care. It may also mean that the message about the benefits of primary health care is not getting through equally to all population groups.

Relationship of the perceived social and physical environment with mental health-related quality of life in middle-aged and older adults: mediating effects of physical activity

BACKGROUND: Mental health conditions are among the leading non-fatal diseases in middle-aged and older adults in Australia. Proximal and distal social environmental factors and physical environmental factors have been associated with mental health, but the underlying mechanisms explaining these associations remain unclear. The study objective was to examine the contribution of different types of physical activity in mediating the relationship of social and physical environmental factors with mental health-related quality of life in middle-aged and older adults. METHODS: Baseline data from the Wellbeing, Eating and Exercise for a Long Life (WELL) study were used. WELL is a prospective cohort study, conducted in Victoria, Australia. Baseline data collection took place in 2010. In total, 3,965 middle-aged and older adults (55-65 years, 47.4% males) completed the SF-36 Health Survey, the International Physical Activity Questionnaire, and a questionnaire on socio-demographic, social and physical environmental attributes. Mediation analyses were conducted using the MacKinnon product-of-coefficients test. RESULTS: Personal safety, the neighbourhood physical activity environment, social support for physical activity from family or friends, and neighbourhood social cohesion were positively associated with mental health-related quality of life. Active transportation and leisure-time physical activity mediated 32.9% of the association between social support for physical activity from family or friends and mental health-related quality of life. These physical activity behaviours also mediated 11.0%, 3.4% and 2.3% respectively, of the relationship between the neighbourhood physical activity environment, personal safety and neighbourhood social cohesion and mental health-related quality of life. CONCLUSIONS: If these results are replicated in future longitudinal studies, tailored interventions to improve mental health-related quality of life in middle-aged and older adults should use a combined strategy, focusing on increasing physical activity as well as social and physical environmental attributes.

Characterising the extent of misreporting of high blood pressure, high cholesterol, and diabetes using the Australian Health Survey

BACKGROUND: Measuring and monitoring the true prevalence of risk factors for chronic conditions is essential for evidence-based policy and health service planning. Understanding the prevalence of risk factors for cardiovascular disease (CVD) in Australia relies heavily on self-report measures from surveys, such as the triennial National Health Survey. However, international evidence suggests that self-reported data may substantially underestimate actual risk factor prevalence. This study sought to characterise the extent of misreporting in a large, nationally-representative health survey that included objective measures of clinical risk factors for CVD.

METHODS: This study employed a cross-sectional analysis of 7269 adults aged 18 years and over who provided fasting blood samples as part of the 2011-12 Australian Health Survey. Self-reported prevalence of high blood pressure, high cholesterol and diabetes was compared to measured prevalence, and univariate and multivariate logistic regression analyses identified socio-demographic characteristics associated with underreporting for each risk factor.

RESULTS: Approximately 16 % of the total sample underreported high blood pressure (measured to be at high risk but didn't report a diagnosis), 33 % underreported high cholesterol, and 1.3 % underreported diabetes. Among those measured to be at high risk, 68 % did not report a diagnosis for high blood pressure, nor did 89 % of people with high cholesterol and 29 % of people with high fasting plasma glucose. Younger age was associated with underreporting high blood pressure and high cholesterol, while lower area-level disadvantage and higher income were associated with underreporting diabetes.

CONCLUSIONS: Underreporting has important implications for CVD risk factor surveillance, policy planning and decisions, and clinical best-practice guidelines. This analysis highlights concerns about the reach of primary prevention efforts in certain groups and implications for patients who may be unaware of their disease risk status.