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      Bienestar material de la provincia de residencia e inactividad física Translated title: Material well-being of the province of residence and leisure-time physical inactivity

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          Abstract

          Objetivo: Estimar la asociación entre el bienestar material de la provincia de residencia y la inactividad física durante el tiempo libre en la población española mayor de 15 años. Métodos: Los datos proceden de la encuesta de Discapacidades, Deficiencias y Estado de Salud, realizada por el Instituto Nacional de Estadística en 1999. Se analizaron los datos de 24.561 mujeres y 21.133 varones. Se consideró un sujeto inactivo cuando declaraba no realizar ningún tipo de actividad física durante el tiempo libre. La medida de bienestar material fue la renta per cápita de la provincia agrupada en cuartiles. La medida de asociación entre la renta per cápita y la inactividad física fue la odds ratio (OR) estimada mediante modelos logit multinivel. Resultados: En los individuos ≥ 45 años de edad se encontró una asociación entre la renta per cápita y la inactividad física. Las provincias con mayor renta per cápita presentaron la menor prevalencia de inactividad física. No obstante, la OR de mayor magnitud se encontró en el cuartil 2 de renta per cápita, no observándose diferencias estadísticamente significativas entre el cuartil más rico y el cuartil más pobre. Al ajustar por características socioeconómicas y otras variables individuales, esa asociación persistió en las mujeres y desapareció en los varones. En las mujeres la asociación fue mayor en el grupo de ingresos personales más bajos. Conclusiones: Los resultados sugieren que en las mujeres mayores de 45 años la inactividad física podría estar relacionada no sólo con las características individuales, sino también con el contexto socioeconómico del área de residencia.

          Translated abstract

          Objective: To estimate the association between material wellbeing of the province of residence and leisure-time physical inactivity in the Spanish population aged 16 years and older. Methods: We used data from the Survey on Disabilities, Impairments and Health Status carried out by the Statistical National Institute in 1999. We analyse 24,561 women and 21,133 men. Respondents were classified as inactive if they reported no leisure-time physical activity. The measure of material wellbeing was the per capita income of the province of residence grouped in quartiles. The measure of the association between per capita income and physical inactivity was the odds ratio (OR) estimated from logit multilevel models. Results: Association between per capita income and physical inactivity was observed in people aged 45 years and older. The lower prevalence of physical inactivity was observed in provinces with the higher per capita income. However the higher OR was found in quartile 2 of per capita income, because no significant difference was observed between quartile 4 (richest) and quartile 1 (poorest). After adjusting for socioeconomic characteristics and other individual variables, association remained significant in women and disappeared in men. In women, association between per capita income and physical inactivity was higher in the population group with lower personal income. Conclusions: Results suggest that physical inactivity in women aged 45 years and older could be related not only with individual characteristics but with the socioeconomic context of the area of residence.

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          Neighborhood of residence and incidence of coronary heart disease.

          Where a person lives is not usually thought of as an independent predictor of his or her health, although physical and social features of places of residence may affect health and health-related behavior. Using data from the Atherosclerosis Risk in Communities Study, we examined the relation between characteristics of neighborhoods and the incidence of coronary heart disease. Participants were 45 to 64 years of age at base line and were sampled from four study sites in the United States: Forsyth County, North Carolina; Jackson, Mississippi; the northwestern suburbs of Minneapolis; and Washington County, Maryland. As proxies for neighborhoods, we used block groups containing an average of 1000 people, as defined by the U.S. Census. We constructed a summary score for the socioeconomic environment of each neighborhood that included information about wealth and income, education, and occupation. During a median of 9.1 years of follow-up, 615 coronary events occurred in 13,009 participants. Residents of disadvantaged neighborhoods (those with lower summary scores) had a higher risk of disease than residents of advantaged neighborhoods, even after we controlled for personal income, education, and occupation. Hazard ratios for coronary events in the most disadvantaged group of neighborhoods as compared with the most advantaged group--adjusted for age, study site, and personal socioeconomic indicators--were 1.7 among whites (95 percent confidence interval, 1.3 to 2.3) and 1.4 among blacks (95 percent confidence interval, 0.9 to 2.0). Neighborhood and personal socioeconomic indicators contributed independently to the risk of disease. Hazard ratios for coronary heart disease among low-income persons living in the most disadvantaged neighborhoods, as compared with high-income persons in the most advantaged neighborhoods were 3.1 among whites (95 percent confidence interval, 2.1 to 4.8) and 2.5 among blacks (95 percent confidence interval, 1.4 to 4.5). These associations remained unchanged after adjustment for established risk factors for coronary heart disease. Even after controlling for personal income, education, and occupation, we found that living in a disadvantaged neighborhood is associated with an increased incidence of coronary heart disease.
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            Distribution and determinants of sedentary lifestyles in the European Union.

            Many studies have shown the health burden of a sedentary lifestyle. The main goal of this study was to determine the prevalence of sedentary lifestyles in the 15 Member States of the European Union (EU) and to identify the main correlates of a sedentary lifestyle. Nationally representative samples (n approximately 1000 subjects in each country; >15 years) completed a questionnaire concerning attitudes to physical activity, body weight, and health; in total 15 239 subjects. Sedentary people were defined in two ways: (1) those expending less than 10% of their leisure time expenditure in activities involving >/=4 metabolic equivalents (MET). (2) Those who did not practice any leisure-time physical activity and who also were above the median in the number of hours spent sitting down during leisure time. Logistic regression models were fitted to analyse the association between sedentary lifestyles and gender, age, body mass index (BMI), educational level, weight change in the last 6 months, and marital and smoking status. Percentages of sedentary lifestyles across European countries ranged between 43.3% (Sweden) and 87.8% (Portugal) according to the first definition. According to both definitions, a lower prevalence of sedentary lifestyle was found in Northern countries (especially Scandinavian countries) as compared with Mediterranean countries, whereas the prevalence was higher among older, obese, less educated, widowed/divorced individuals, and current smokers. Similar relative differences between countries and socio-demographic groups were found independently of the method used to define a sedentary lifestyle. Prevalence of sedentary lifestyle in the EU is high, especially among inhabitants of some Mediterranean countries, obese subjects, less-educated people, and current smokers. This high prevalence involves important public health burdens and preventive strategies are urgently needed.
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              Changes in physical fitness and changes in mortality.

              Point estimates of physical fitness give important information on the risk of death in healthy people, but there is little information available on effects of sequential changes in physical fitness on mortality. We studied this latter aspect in healthy middle-aged men over a total follow-up period of 22 years. 2014 healthy men aged 40-60 years had a bicycle exercise test and clinical examination, and completed a questionnaire in 1972-75 (survey 1). This was repeated for 1756 (91%) of 1932 men still alive by Dec 31, 1982 (survey 2). The exercise scores were adjusted for age. The change in exercise scores between surveys was divided into quartiles (Q1=least fit, Q4=fittest). An adjusted Cox's proportional hazards model was used to study the association between changes in physical fitness and mortality, with the Q1 men used as controls. By Dec 31, 1994, 238 (17%) of the 1428 men had died, 120 from cardiovascular causes. There were 37 deaths in the Q4 group (19 cardiovascular); their relative risks of death were 0.45 (95% CI 0.29-0.69) for any cause and 0.47 (0.26-0.86) for cardiovascular causes. There was a graded, inverse relation between changes in physical fitness and mortality irrespective of physical fitness status at survey 1. Change in physical fitness in healthy middle-aged men is a strong predictor of mortality. Even small improvements in physical fitness are associated with a significantly lowered risk of death. If confirmed, these findings should be used to influence public health policy.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                gs
                Gaceta Sanitaria
                Gac Sanit
                Ediciones Doyma, S.L. (Barcelona )
                0213-9111
                December 2005
                : 19
                : 6
                : 424-432
                Affiliations
                [1 ] Universidad Complutense de Madrid España
                [2 ] Universidad Autónoma de Madrid España
                Article
                S0213-91112005000600002
                219939a6-9ade-4c34-8d44-a2238fb7731a

                http://creativecommons.org/licenses/by/4.0/

                History
                Categories
                Health Policy & Services

                Public health
                Per capita income,Material wellbeing,Leisure-time physical inactivity,Multilevel analysis,Spain,Renta per cápita,Bienestar material,Inactividad física en el tiempo libre,Análisis multinivel,España

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