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The 2008 economic recession may have affected health-related indicators differently depending on the living environment. We analyze health-related indicators in Spain using data from four Spanish health surveys (2006, 2011, 2014, and 2017, 95 924 individuals aged ≥16 years). In 2006-2011, physical activity decreased among men and women, while in 2006-2017, physical activity only decreased among urban women. Daily vegetable intake, except in rural women, increased in 2006-2011 but decreased in 2006-2017 in all groups. Smoking decreased among urban women in 2006-2011 and 2006-2014 but only decreased among men, and even increased among rural women, in 2006-2017. In 2006-2017, obesity increased among men and urban women, good self-rated health status increased in all groups and flu vaccination declined. Blood pressure and cholesterol control decreased in urban women in 2006-2011 but increased in 2006-2017 in all groups, as well as mammographic and cytological control. Our findings highlight the differential impact of the economic recession on health-related lifestyles according to sex and place of residence, underscoring the need for targeted health policies to address evolving health disparities over time.
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Recesión Económica , Estado de Salud , Masculino , Humanos , Femenino , España , Estilo de Vida Saludable , Encuestas EpidemiológicasRESUMEN
Urban-rural disparities in resources, services and facilities not only impact daily living conditions but also contribute to inequalities in physical activity, which may be associated with variations in basic public resources between urban and rural areas. This study aims to examine the evolution of perceived opportunities for physical activity in European urban and rural environments from 2002 to 2017 and their association with an active lifestyle. Data from four waves (2002, 2005, 2013 and 2017) of cross-sectional Eurobarometer surveys were collected (n = 101 373), and multilevel binomial logistic regressions were conducted. Firstly, the time trend of perceived opportunities for physical activity between urban and rural environments was explored, and secondly, the effect of urban-rural perceived opportunities on achieving an active lifestyle over the years was estimated. The findings revealed that individuals residing in rural settings encountered less opportunities to be physically active. Conversely, urban settings experienced an increase in perceived opportunities. The significance of health promotion through perceived physical activity opportunities lies in the increased likelihood of being physically active, regardless of place of residence or individual socioeconomic factors [in the area: odds ratio (OR) = 1.40, 95% confidence interval (CI) = 1.34-1.47; provided by local sport clubs: OR = 1.29, 95% CI = 1.23-1.35]. Modifying environmental aspects, such as enhancing the quantity, quality and accessibility of physical activity opportunities in both rural and urban areas, may lead to improved physical activity and health promotion, particularly among individuals who are more physically inactive.
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Ejercicio Físico , Estilo de Vida , Humanos , Estudios Transversales , Factores Socioeconómicos , Europa (Continente) , Población Rural , Población UrbanaRESUMEN
BACKGROUND: Misinformation hampers vaccine uptake. The European Union (EU) employed a coordinated effort to curb misinformation during the Covid-19 pandemic. In this context, we investigated relationships between sources of information, vaccine safety/effectiveness, satisfaction with government vaccination strategy, and vaccination intent. METHODS: We used cross-sectional survey data (May 2021) from Flash Eurobarometer 494, a population-adjusted dataset comprised of a representative sample of those ≥15 years from 27 EU nations. We employed a latent class analysis to create clusters of information sources as the independent variable and beliefs in vaccine safety/efficacy, satisfaction with government vaccination strategy, and vaccine intent as four outcome variables. We first estimated the association between source clusters and each of the first three outcomes separately. Then, using these three as intermediate variables, we employed structural equation modeling to estimate the relationship between sources and vaccine intent. We adjusted for individual and country-level variables. RESULTS: Among 23 012 respondents, four clusters of information sources emerged: (1) national authorities/health professionals (n = 9602; 42%), (2) mostly health professionals (6184; 27%), (3) mixed (n = 1705; 17%) and (4) social media/family/friends (n = 5524; 24%). Using cluster (3) as the referent, we found decreasing odds of beliefs in vaccine safety/effectiveness, satisfaction and vaccine intent across clusters (1), (2) and (4), respectively. Demographics played a role. CONCLUSION: In the context of the Covid pandemic, these results provide the first EU-wide estimates of the association between sources of information about vaccine safety/effectiveness, satisfaction and vaccine intent. The coordinated approach promulgated by the EU to minimize misinformation provides a model for managing future pandemics.
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This study aims to report what motivates individuals to be physically active, to determine whether motivating factors influence physical activity (PA) levels, and whether this differs across the lifespan. This is a cross-sectional study with 498 individuals: 117 adolescents, 306 adults, and 75 older adults. PA was assessed using Baecke's questionnaire, and motivating factors for practicing sports were investigated using a scale with twelve questions. The factor analysis identified three motivating factors for sports practice: psychosocial, bodily, and well-being. The scale's overall reliability and internal consistency indicated a Cronbach's alpha of 0.885. The analysis of covariance (ANCOVA) adjusted for sex indicated the three factors as having a significant effect on PA (p < 0.050); however, only the well-being factor showed a significant interaction with age groups (p = 0.023, ηp2 = 0.030). Subsequently, the effect of the well-being factor on PA scores in each age group was explored through regression analyses. Only older adults showed a significant association in the unadjusted [OR = 0.378, p = 0.001, R2 = 0.243] and the sex-adjusted analysis [OR = 0.377, p = 0.001, R2 = 0.288]. These results help us to better understand the underlying motivational reasons in different age groups for engaging in sports.
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BACKGROUND: A low socioeconomic status (SES) presents lower physical activity; however, the relationship between SES and sedentary behavior (SB) remains unclear. We aimed to assess this association of SES with physical activity (PA) and SB. METHODS: We employed representative self-reported data of the European Union from the cross-sectional survey Eurobarometer 2017, comprising a final sample of 13,708 citizens (18-64 y old), to assess the association of SES (education, occupation, and economic issues) with PA and sitting time quartiles, and to describe inequalities in vigorous, moderate, and walking activity and sitting time. RESULTS: Multinomial regressions revealed that people from higher SESs were more likely to report higher PA; nonetheless, higher educational attainment and occupations were also associated with higher sitting time but not with lower economic issues. The inequality, shown by Gini coefficients, describes a socioeconomic gradient in vigorous and moderate activity, from higher inequality in lower statuses to lower inequality in higher statuses. The Gini coefficients also indicated higher socioeconomic inequalities in PA than SB. CONCLUSIONS: Higher SESs showed paradoxically more PA and SB; however, sitting time presented smaller differences and a more homogeneous distribution across the population.
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Ejercicio Físico , Conducta Sedentaria , Humanos , Estudios Transversales , Europa (Continente) , Estatus Socioeconómico Bajo , Factores SocioeconómicosRESUMEN
AIMS: Obesity levels have increased worldwide with serious public health concerns. However, weight status is related to socioeconomic status (SES), which may also influence health-related lifestyles. Here, we study the association between SES and obesity mediated by diet and physical activity. METHODS AND RESULTS: Using cross-sectional data from 2006, 2011, 2014, and 2017 Spanish health surveys (the final sample consisted of 61 768 adults aged between 18 and 64 years), we conducted a latent class analysis to estimate health-related lifestyle clusters (based on dietary patterns and physical activity) and mediation analyses to evaluate the association of SES and obesity through the clustering of health-related lifestyles. In both men and women, SES was inversely related to obesity (P < 0.001) and positively related to healthier lifestyle classes (P < 0.001). Obesity was inversely related to healthier lifestyle classes (P < 0.001). A small-although significant-proportion mediated by the clustering of lifestyles was found as follows: 4.9%, 95% CI (6.6%, 3.2%) in men and 2.3%, 95% CI (3.4%, 1.3%) in women for educational attainment, 5.3%, 95% CI (7.2%, 3.6%) in men and 2.0%, 95% CI (2.9%, 1.1%) in women for occupational social class, and 4.9%, 95% CI (6.5%, 3.1%) and 1.9%, 95% CI (2.9%, 1.1%) combining the above two SES indicators. CONCLUSIONS: SES is related to obesity through clustering health-related lifestyles, with greater emphasis on men. However, the complex relationship between SES and weight status also suggests other indicators that contribute to the social gradient of obesity.
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This study aimed (1) to investigate the association between body mass index (BMI), physical activity (PA), and physical function (PF) with health-related quality of life (HRQoL), and (2) to examine in-depth whether PA and PF mediate the relationship between BMI and HRQoL in older adults. We investigated 802 individuals (mean age 69.8 ± 5.6 years), residents of the Autonomous Region of Madeira, Portugal. Harmol and PA were assessed using the SF-36 and Baecke questionnaires, respectively, and PF by the Senior Fitness Test. The prevalence of overweight was 71.3%, 26.5% for normal weight, and 2.1% for underweight. We verified a small correlation between age and sex with BMI, PA, PF, and medium borderline with HRQoL. After adjusting for covariates (i.e., sex, age, comorbidities), the multivariate regression analysis indicated a 93.1% chance of improvement in HRQoL for low BMI, while PA and PF revealed a chance of increasing HRQoL by 91.8% and 60.0%, respectively. According to the serial mediation pathway, PA and PF partially mediated the association between BMI and HRQoL by 32.3% and 81.5%, respectively. The total variance of the model was 90%. It was concluded that BMI can negatively affect HRQoL. On the other hand, PA and PF are able to increase HRQoL levels during the aging process.
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Obesidad , Calidad de Vida , Humanos , Anciano , Persona de Mediana Edad , Índice de Masa Corporal , Obesidad/epidemiología , Ejercicio Físico , Sobrepeso/epidemiologíaRESUMEN
Background: People more socioeconomically vulnerable tend to have a poorer health-related quality of life (HRQoL). Studies are trying to analyse the factors that may condition this relationship, including physical activity (PA), which may influence the relationship between socioeconomic status (SES) and HRQoL. This study aimed to analyse the relationship between SES and HRQoL through specific domains of PA. Methods: A total of 381 adults (≥18 years) from the Autonomous Region of Madeira completed the measurements. Mediation analyses using bootstrapping methods adjusted for confounding variables were performed to relate SES and HRQoL; the latter was evaluated using the physical component score (PCS) of the SF-12, the mental component score (MCS) of the SF-12, and the total score in the SF-12 questionnaire (SF-12 score), through physical activity. Results: Educational level was positively related to PCS and SF-12 score. Leisure-time PA (not including sports PA) and PA at work, as single mediating variables, did not mediate the relationship between SES and HRQoL. The total PA suppressed the socioeconomic gradient of HRQoL by 8-10%, 39-46%, and 15-16%, respectively, for the PCS, MCS, and the SF-12 score; sports PA mediated the relationship by 13-16%, 50%, and 15-21%, respectively. Conclusions: The results suggest that sports PA contributes to reducing the socioeconomic gradient of HRQoL.
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Longevidad , Calidad de Vida , Adulto , Estudios Transversales , Ejercicio Físico , Humanos , Portugal , Encuestas y CuestionariosRESUMEN
BACKGROUND: Living standards determine population's physical activity (PA); however, more women are systemically insufficiently active, suggesting social gender inequality factors. Thus, we assessed the association between gender inequality, PA differences between genders, and total PA. METHODS: We used three independent cross-sectional databases at country-level: PA prevalence (i.e., Active Lifestyle) from the World Health Organization with 1.9 million individuals from 168 countries; daily steps (smartphone registers) of 693 806 people from 46 countries and sport participation in the 2016 Summer Olympics with 11 191 athletes. Gender Inequality Index was used to evaluate aspects surrounding gender equality controlling for overall economic and health status. RESULTS: Higher gender inequality was associated with gender differences in PA (Active Lifestyle, 0.402, P < 0.001; Steps, 0.542, P < 0.001; Olympic participation, 0.346, P = 0.001). Likewise, lower gender inequality was associated with increased women activity (Active Lifestyle, -0.838, P < 0.001; Steps, -0.81, P < 0.001; Olympic participation, -0.577, P < 0.001), and men activity (Active Lifestyle, -0.453, P < 0.001; Steps, -0.461, P = 0.002). CONCLUSIONS: Lower women PA levels could be influenced by gender inequality. Public health policies aimed to improve women living conditions which may promote their participation in PA and sport.
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Ejercicio Físico , Deportes , Humanos , Femenino , Masculino , Factores Sexuales , Factores Socioeconómicos , Estado de SaludRESUMEN
Here we evaluate the time trends of urban-rural differences in physical activity in the European Union between 2002 and 2017 and the contribution of urbanization on total physical activity changes, using four Eurobarometer surveys (n = 101,373). Trajectories of urban-rural differences in physical activity varied considerably among EU-28 countries. Hierarchical linear regression models revealed that inactivity increased in both urban and rural settings, although it was higher in the latter. Thereby, the urban-rural gap diminished and was even eliminated in some countries. Also, national changes across time were driven by urban places, showing little contribution from urbanization. Our findings suggest that inactivity has risen in Europe regardless of living environments and with regional urbanization development having little influence.
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Ejercicio Físico , Población Rural , Europa (Continente) , Humanos , Población Urbana , UrbanizaciónRESUMEN
PURPOSE: Social determinants as occupational social class or educational attainment might influence health outcomes. This phenomenon is known as the social gradient of health and is related to a skewed distribution of health behaviours that might explain differences in morbidity and mortality between social groups. But social class and educational attainment differ in their nature and might have distinct effects on health. Here we study the combined effect of educational attainment and occupational social class on health-related lifestyle. METHODS: We retrieved data from four large-scale, national representative Spanish surveys (n = 67,171). A latent class regression analysis was run to identify clusters of health-related lifestyle behaviours. Clusters were made according to sociodemographic factors, including a combined analysis of education and occupational social class. RESULTS: Higher educational attainment and occupational social class were associated with a healthier lifestyle for both sexes. The combined analysis of education and social class indicated that women with secondary education showed a high risk combination of unhealthy behaviours, as men with middle, primary or no education. CONCLUSIONS: Regardless of social class, a higher educational attainment redresses the effect of occupational social class on health-related behaviours. Our results suggest that education likely plays a crucial role in population health outcomes through its effects on lifestyle.
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Conductas Relacionadas con la Salud , Clase Social , Escolaridad , Femenino , Encuestas Epidemiológicas , Humanos , Estilo de Vida , MasculinoRESUMEN
INTRODUCCIÓN: la actividad física es una conducta relacionada con la salud que se asocia a un mayor bienestar de la población que padece enfermedades musculoesqueléticas. OBJETIVO: el objetivo es evaluar la asociación de diferentes factores de salud y estilo de vida con la actividad física en el tiempo libre de la población española que padece enfermedades musculoesqueléticas. MÉTODOS: hemos utilizado datos de la Encuesta Europea de Salud en España de 2014. La población se clasificó en función del diagnóstico médico o no de enfermedad musculoesquelética (artrosis, dolor de espalda, osteoporosis o varias de estas enfermedades). La encuesta recoge datos sobre la actividad física y otras conductas relacionadas con la salud (alimentación, consumo de alcohol y tabaco, entre otras) y otros indicadores de salud (estado de salud percibido, dolor percibido, salud mental, limitaciones físicas, entre otros). Hemos empleado modelos de regresión logística multivariante para analizar la relación entre las diferentes variables estudiadas en la población con diagnóstico de enfermedad musculoesquelética. RESULTADOS: la actividad física se asocia a la ingesta diaria de fruta y verdura, independientemente de la edad y el sexo, y al consumo diario de pescado en las mujeres mayores de 45 años. El consumo de tabaco es mayor en las mujeres y los hombres inactivos, mientras que el consumo semanal de alcohol se asocia a una mayor actividad física (excepto en las mujeres de entre 15 y 44 años). CONCLUSIONES: la actividad física habitual es una conducta que se asocia a un mejor estado de salud y un estilo de vida más saludable en la población española con enfermedad musculoesquelética
BACKGROUND: physical activity is a health-related behavior that is associated with increased well-being in people living with musculoskeletal disease. OBJECTIVE: we assessed the association of different health and lifestyle factors with physical activity in the Spanish population living with musculoskeletal disease. METHODS: we used data from the 2014 European Health Survey for Spain. The population was classified according to their musculoskeletal disease (including osteoarthritis, back pain, osteoporosis, or several of these diseases) diagnostic status. The survey collected data on habitual physical activity and other health-related behaviors (diet, alcohol and tobacco consumption, among others) and other health indicators (self-perceived health status, perceived pain, mental health, physical limitations, among others). We used multivariate logistic regression models to analyze the relationship between the different variables studied in the population living with musculoskeletal disease. RESULTS: physical activity is associated with daily fruit and vegetable intake, regardless of age and sex, and with daily fish consumption in women aged 45 years and older. Tobacco smoking is higher in inactive women and men, while weekly consumption of alcohol is associated with more physical activity (except in women aged 15-44 years). CONCLUSIONS: physical activity is a behavior associated with a better health status and healthier lifestyle in the Spanish population living with musculoskeletal disease
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Humanos , Masculino , Femenino , Adolescente , Adulto Joven , Adulto , Enfermedades Musculoesqueléticas/epidemiología , Actividad Motora , Estilo de Vida , España , Estado de Salud , Estudios Transversales , Análisis por Conglomerados , Índice de Masa Corporal , Salud Mental , Modelos LogísticosRESUMEN
Study of the long-term impact of economic recession on lifestyle according to socioeconomic groups is scarce. This study examines health-related lifestyle and preventive medical attendance in different socioeconomic groups in the Spanish adult population (18-64 years of age) before, during and after an economic recession. Data were collected from three waves of the Spanish National Health Survey (2006, 2012 and 2017). Self-perceived health, health-related lifestyle and common preventive medical attendance were evaluated by means of multivariate logistic models. The increase in good self-perceived health in 2006-2012 was 7.1%, 6.9% and 8.3% for the high, middle and low group, respectively, and 5.2%, 5.9% and 7.9% for the high, middle and low group, respectively, in 2006-2017. In 2006-2012 and 2006-2017, the gap increased between people of the high and low groups in smoking prevalence (2.8%-4.7%), physical activity (2.0%-4.0%), daily fruit (1.0%-6.3%) and vegetable intake (2.5%-6.1%). The probability of women´s gynaecological attendance increased statistically significant for cytology in three groups in 2006-2012 and 2006-2017 (OR = 1.35, 95% CI = 1.08-1.67; OR = 1.42, 95% CI = 1.18-1.7; OR = 1.34, 95% CI = 1.21-1.47 for the high, middle and low groups, respectively, in 2006-2012 and OR = 1.34, 95% CI = 1.08-1.67; OR = 1.62, 95% CI = 1.35-1.95; OR = 1.51, 95% CI = 1.37-1.66 for the high, middle and low groups, respectively, in 2006-2017), but not for mammography. This study reveals long-term socioeconomic inequalities in lifestyle behaviours after the economic recession. Health policies must be emphasised in these population subgroups and in more disadvantaged populations.
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Recesión Económica , Estilo de Vida , Adulto , Estudios Transversales , Atención a la Salud , Femenino , Humanos , Factores Socioeconómicos , España/epidemiologíaRESUMEN
INTRODUCTION: Background: physical activity is a health-related behavior that is associated with increased well-being in people living with musculoskeletal disease. Objective: we assessed the association of different health and lifestyle factors with physical activity in the Spanish population living with musculoskeletal disease. Method: we used data from the 2014 European Health Survey for Spain. The population was classified according to their musculoskeletal disease (including osteoarthritis, back pain, osteoporosis, or several of these diseases) diagnostic status. The survey collected data on habitual physical activity and other health-related behaviors (diet, alcohol and tobacco consumption, among others) and other health indicators (self-perceived health status, perceived pain, mental health, physical limitations, among others). We used multivariate logistic regression models to analyze the relationship between the different variables studied in the population living with musculoskeletal disease. Results: physical activity is associated with daily fruit and vegetable intake, regardless of age and sex, and with daily fish consumption in women aged 45 years and older. Tobacco smoking is higher in inactive women and men, while weekly consumption of alcohol is associated with more physical activity (except in women aged 15-44 years). Conclusions: physical activity is a behavior associated with a better health status and healthier lifestyle in the Spanish population living with musculoskeletal disease.
INTRODUCCIÓN: Introducción: la actividad física es una conducta relacionada con la salud que se asocia a un mayor bienestar de la población que padece enfermedades musculoesqueléticas. Objetivo: el objetivo es evaluar la asociación de diferentes factores de salud y estilo de vida con la actividad física en el tiempo libre de la población española que padece enfermedades musculoesqueléticas. Métodos: hemos utilizado datos de la Encuesta Europea de Salud en España de 2014. La población se clasificó en función del diagnóstico médico o no de enfermedad musculoesquelética (artrosis, dolor de espalda, osteoporosis o varias de estas enfermedades). La encuesta recoge datos sobre la actividad física y otras conductas relacionadas con la salud (alimentación, consumo de alcohol y tabaco, entre otras) y otros indicadores de salud (estado de salud percibido, dolor percibido, salud mental, limitaciones físicas, entre otros). Hemos empleado modelos de regresión logística multivariante para analizar la relación entre las diferentes variables estudiadas en la población con diagnóstico de enfermedad musculoesquelética. Resultados: la actividad física se asocia a la ingesta diaria de fruta y verdura, independientemente de la edad y el sexo, y al consumo diario de pescado en las mujeres mayores de 45 años. El consumo de tabaco es mayor en las mujeres y los hombres inactivos, mientras que el consumo semanal de alcohol se asocia a una mayor actividad física (excepto en las mujeres de entre 15 y 44 años). Conclusiones: la actividad física habitual es una conducta que se asocia a un mejor estado de salud y un estilo de vida más saludable en la población española con enfermedad musculoesquelética.
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Ejercicio Físico , Estilo de Vida Saludable , Enfermedades Musculoesqueléticas , Adolescente , Adulto , Consumo de Bebidas Alcohólicas , Dolor de Espalda , Dolor Crónico , Dieta , Femenino , Frutas , Conductas Relacionadas con la Salud , Estado de Salud , Encuestas Epidemiológicas , Humanos , Modelos Logísticos , Masculino , Salud Mental , Persona de Mediana Edad , Enfermedades Musculoesqueléticas/clasificación , Osteoartritis , Osteoporosis , Percepción del Dolor , España , Uso de Tabaco , Verduras , Adulto JovenRESUMEN
OBJECTIVES: To analyse relationships of social stratification on physical activity (PA) prevalence and barriers in the European population. METHODS: Data were retrieved from Eurobarometer 88.4, a cross-sectional survey conducted in 2017 with 28,031 over 15-year-old inhabitants of the European Union. PA prevalence was calculated along with the probability to be physically inactive by social stratification. Logistic regressions were run in the inactive population to show the social class effect on each barrier adjusted by sociodemographic factors employing a propensity score matched method. RESULTS: Low social class presented higher inactivity prevalence (43.11%), whilst the high social class reported the lowest prevalence (23.30%). Also, the low (OR 0.52; 95% CI 0.47-0.58) and middle (OR 0.71; 95% CI 0.64-0.79) social classes were less likely to be active compared to high social class. In the inactive population, the low social class had mostly higher odds to report each barrier. CONCLUSIONS: Social class is a relevant factor for low PA, with more barriers in the lower social classes. Public health institutions should implement strategies on more influential PA barriers and disadvantaged social groups.
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Actitud Frente a la Salud , Ejercicio Físico/psicología , Población Rural/estadística & datos numéricos , Conducta Sedentaria , Clase Social , Población Urbana/estadística & datos numéricos , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Estudios Transversales , Europa (Continente) , Femenino , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Adulto JovenRESUMEN
An extensive number of self-reported methods for physical activity (PA) measurement are available, including short and long recall questionnaires ranging from a few to tens of questions. Due to the fact that simple, time-saving methods could be more practical and desirable for use in a busy clinical context, as well as in public health surveys, we evaluated how a single-item question might be a useful and cost-effective method for assessing compliance with PA guidelines. Using multiple receiver operating characteristics (ROC), we assessed the classification performance of a single brief question, employing the short version of the International Physical Activity Questionnaire as criterion instrument, in a total of 55,950 people (30,601 women and 25,349 men). Both those who practice PA almost daily and a few times a week presented an upper threshold (1042.5 metabolic equivalent minutes (MET) minutes/week) to the established compliance PA guidelines (600 MET minutes/week) with high specificity and sensitivity, using a sedentary group as reference. Otherwise, the occasionally physically active group did not reach the minimum (349.5 MET minutes/week) and obtained a poorer classification performance. A single brief question is a pragmatic and alternative method for assessment of compliance with PA guidelines.
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Ejercicio Físico , Autoinforme , Adulto , Femenino , Humanos , Masculino , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Encuestas y CuestionariosRESUMEN
OBJECTIVE: Smoking is one of the health risk factors most associated with population morbidity and mortality. In Spain, legal restrictions have been introduced for the use of tobacco. The objective of this study was to analyse the smoking prevalence in Spain during the period 2009-2017, following the implementation of these legal restrictions, and the relationship and evolution between smoking and other health-related lifestyle factors. METHODS: We analyzed data in 2019 from the European Health Survey in Spain 2009 and National Health Surveys of Spain 2012 and 2017. Smoking, selfperceived health status, weight status and other health-related lifestyle behaviors (physical activity, vegetable intake, fruit intake and alcohol use). A multinomial logistic regression analysis was used to obtain the odds ratio adjusted to sex and age ("odds ratio" and 95% confidence interval). RESULTS: Smoking decreased by 3.13% during 2009-2012, and by 4.81% during 2009-2017. Smoking population presenting 2 or 3 risk factors in 2009 was OR=1.17 (1.08-1.26), p<0.0001, in 2012 OR=1.23 (1.12-1, 34), p<0.0001, and in 2017 OR=1.32 (1.21-1.44), p<0.0001. For 4 or 5 risk factors it was in 2009 OR=1.51 (1.31-1.74), p<0.0001, in 2012 OR=1.60 (1.42-1.81), p <0.0001, and in 2017 OR=1.70 (1.51-1.92), p <0.0001. For ex-smokers, the probability of presenting 2 or 3 risk factors in 2009 is not significant, in 2012 OR=0.88 (0.80-0.98), p = 0.013, and in 2017 it is not significant. In the case of 4 or 5 risk factors in 2009 it is not significant, in 2012 OR=0.86 (0.75-1.00), p = 0.045, and in 2017 OR=1.15 (1.02 -1.30), p =0.028. CONCLUSIONS: There is a decrease in the smoking population in Spain during 2009-2017. People who smoke have also an unhealthy lifestyle. People who smoke presented a greater number of health-related risk factors.
OBJETIVO: El tabaquismo es una de las conductas de riesgo para la salud más asociadas a morbilidad y mortalidad de la población. En España se han implantado restricciones legales para el uso del tabaco. El objetivo de este estudio fue analizar la prevalencia del uso del tabaco en España durante el período 2009-2017, tras la implantación de estas restricciones, y la relación y evolución entre uso del tabaco y otros factores del estilo de vida relacionados con la salud. METODOS: Durante 2019, se analizaron los datos de la Encuesta Europea de Salud en España correspondiente a 2009 y de la Encuesta Nacional de Salud de España en 2012 y 2017. Se analizó el uso del tabaco, el estado de salud percibido, el estatus de peso y otras conductas de la salud (actividad física, consumo de frutas y verduras y consumo de alcohol). Se obtuvo la razón de probabilidades ajustada a sexo y edad ("odds ratio" e intervalo de confianza al 95%), mediante un análisis de regresión logística multinomial. RESULTADOS: La población fumadora disminuyó un 3,13% durante el período 2009-2012, y un 4,81% durante el período 2009-2017. Para la población fumadora, la probabilidad de presentar 2 o 3 factores de riesgo reflejó un odds ratio (OR) de 1,17 (1,08-1,26), p<0,0001 en 2009; de 1,23 (1,12-1,34), p<0,0001 en 2012; y de 1,32 (1,21-1,44), p<0,0001 en 2017. La probabilidad de presentar 4 o 5 factores de riesgo reflejó un OR de 1,51 (1,31-1,74), p<0,0001 en 2009; de 1,60 (1,42-1,81), p<0,0001 en 2012; y de 1,70 (1,51-1,92), p<0,0001 en 2017. En cuanto a la población exfumadora, la probabilidad de presentar 2 o 3 factores de riesgo no fue significativa en 2009, con un OR de 0,88 (0,80-0,98), p=0,013 en 2012; y no fue significativa en 2017. En el caso de la probabilidad de presentar 4 o 5 factores de riesgo no fue significativa en 2009, con un OR de 0,86 (0,75-1,00), p=0,045 en 2012, y con 1,15 (1,02-1,30), p=0,028 en 2017. CONCLUSIONES: La población fumadora disminuyó durante el período 2009-2017. Las personas que fuman presentan un estilo de vida menos saludable. Las personas que fuman muestran, en las sucesivas encuestas, un incremento de conductas de riesgo.
Asunto(s)
Conductas Relacionadas con la Salud , Estilo de Vida Saludable , Contaminación por Humo de Tabaco/legislación & jurisprudencia , Uso de Tabaco/epidemiología , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Estudios Transversales , Femenino , Encuestas Epidemiológicas , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Oportunidad Relativa , Prevalencia , Factores de Riesgo , España/epidemiología , Contaminación por Humo de Tabaco/prevención & control , Contaminación por Humo de Tabaco/estadística & datos numéricos , Uso de Tabaco/legislación & jurisprudencia , Uso de Tabaco/prevención & control , Uso de Tabaco/psicología , Adulto JovenRESUMEN
OBJETIVO: El tabaquismo es una de las conductas de riesgo para la salud más asociadas a morbilidad y mortalidad de la población. En España se han implantado restricciones legales para el uso del tabaco. El objetivo de este estudio fue analizar la prevalencia del uso del tabaco en España durante el período 2009-2017, tras la implantación de estas restricciones, y la relación y evolución entre uso del tabaco y otros factores del estilo de vida relacionados con la salud. MÉTODOS: Durante 2019, se analizaron los datos de la Encuesta Europea de Salud en España correspondiente a 2009 y de la Encuesta Nacional de Salud de España en 2012 y 2017. Se analizó el uso del tabaco, el estado de salud percibido, el estatus de peso y otras conductas de la salud (actividad física, consumo de frutas y verduras y consumo de alcohol). Se obtuvo la razón de probabilidades ajustada a sexo y edad ("odds ratio" e intervalo de confianza al 95%), mediante un análisis de regresión logística multinomial. RESULTADOS: La población fumadora disminuyó un 3,13% durante el período 2009-2012, y un 4,81% durante el período 2009-2017. Para la población fumadora, la probabilidad de presentar 2 o 3 factores de riesgo reflejó un odds ratio (OR) de 1,17 (1,08-1,26), p<0,0001 en 2009; de 1,23 (1,12-1,34), p<0,0001 en 2012; y de 1,32 (1,21-1,44), p<0,0001 en 2017. La probabilidad de presentar 4 o 5 factores de riesgo reflejó un OR de 1,51 (1,31-1,74), p<0,0001 en 2009; de 1,60 (1,42-1,81), p<0,0001 en 2012; y de 1,70 (1,51-1,92), p<0,0001 en 2017. En cuanto a la población exfumadora, la probabilidad de presentar 2 o 3 factores de riesgo no fue significativa en 2009, con un OR de 0,88 (0,80-0,98), p=0,013 en 2012; y no fue significativa en 2017. En el caso de la probabilidad de presentar 4 o 5 factores de riesgo no fue significativa en 2009, con un OR de 0,86 (0,75-1,00), p=0,045 en 2012, y con 1,15 (1,02-1,30), p=0,028 en 2017. CONCLUSIONES: La población fumadora disminuyó durante el período 2009-2017. Las personas que fuman presentan un estilo de vida menos saludable. Las personas que fuman muestran, en las sucesivas encuestas, un incremento de conductas de riesgo
OBJECTIVE: Smoking is one of the health risk factors most associated with population morbidity and mortality. In Spain, legal restrictions have been introduced for the use of tobacco. The objective of this study was to analyse the smoking prevalence in Spain during the period 2009-2017, following the implementation of these legal restrictions, and the relationship and evolution between smoking and other health-related lifestyle factors. METHODS: We analyzed data in 2019 from the European Health Survey in Spain 2009 and National Health Surveys of Spain 2012 and 2017. Smoking, selfperceived health status, weight status and other health-related lifestyle behaviors (physical activity, vegetable intake, fruit intake and alcohol use). A multinomial logistic regression analysis was used to obtain the odds ratio adjusted to sex and age ("odds ratio" and 95% confidence interval). RESULTS: Smoking decreased by 3.13% during 2009-2012, and by 4.81% during 2009-2017. Smoking population presenting 2 or 3 risk factors in 2009 was OR=1.17 (1.08-1.26), p<0.0001, in 2012 OR=1.23 (1.12-1, 34), p<0.0001, and in 2017 OR=1.32 (1.21-1.44), p<0.0001. For 4 or 5 risk factors it was in 2009 OR=1.51 (1.31-1.74), p<0.0001, in 2012 OR=1.60 (1.42-1.81), p <0.0001, and in 2017 OR=1.70 (1.51-1.92), p <0.0001. For ex-smokers, the probability of presenting 2 or 3 risk factors in 2009 is not significant, in 2012 OR=0.88 (0.80-0.98), p = 0.013, and in 2017 it is not significant. In the case of 4 or 5 risk factors in 2009 it is not significant, in 2012 OR=0.86 (0.75-1.00), p = 0.045, and in 2017 OR=1.15 (1.02 -1.30), p =0.028. CONCLUSIONS: There is a decrease in the smoking population in Spain during 2009-2017. People who smoke have also an unhealthy lifestyle. People who smoke presented a greater number of health-related risk factors