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Clustering of behavioural risk factors and their association. Consejería de Sanidad y Consumo de la Comunidad de Madrid. Facultad de Medicina. Universidad Autónoma de Madrid. What is classical theories of crime causation Objectives : To describe the clustering of behavioural risk factors in the adult population of the Autonomous Community of Madrid Spainand to evaluate the association between the level of aggregation of such factors and suboptimal subjective health.
We studied the relationships between tobacco use, high-risk alcohol consumption, leisure-time inactivity and unbalanced diet in 16, people agedcomparing observed against expected proportions. Logistic regression was used to estimate the association between aggregation of risk factors and suboptimal health fair, poor and very poor health. In both sexes, smoking was the individual factor most frequently associated with the remaining risk factors.
Aggregation of risk factors was more frequent among men, in younger age groups and among subjects with low educational level. What traits are examples of incomplete dominance : Behavioural risk factors tend to aggregate, and this clustering is higher among men, in younger age groups and among subjects with a low educational level.
A greater level of clustering is associated with a higher frequency of suboptimal self-rated health. Palabras clave: Behavioural risk factors. Subjective health. Resumen Objetivos : Describir la agregación de factores de riesgo what are some common characteristics of healthy relationship and unhealthy relationship con el comportamiento en la población adulta de la Comunidad de Madrid y evaluar la asociación del grado de agregación de dichos factores con la salud subjetiva subóptima.
Las relaciones entre el consumo de tabaco, el consumo de alcohol de riesgo, el sedentarismo en tiempo libre y la dieta desequilibrada fueron estudiadas en Conclusiones : Los factores de riesgo ligados al comportamiento se agregan, y esta acumulación es superior en varones, en personas jóvenes y con bajo nivel de estudios. Un mayor grado de agregación se asocia a mayor frecuencia de salud percibida subóptima.
Keywords: Factores de hexlthy asociados al comportamiento. Salud percibida. The Spanish version of this manuscript can be downloaded PDF format from the web www. Servicio de Epidemiología. Relatonship iñaki. Received : 14 de septiembre de Acepted : 10 de enero de Several behavioural risk factors such as smoking, excessive alcohol consumption, inactivity and an unbalanced diet unhalthy responsible for most of the burden of disease in developed societies, expressed in terms of general mortality 1or premature unhealtgy and disability 2.
The simultaneous occurrence of several factors in the same individual has been associated with a greater risk of general mortality, and more specifically with mortality from cancer, heart disease and stroke Furthermore, the accumulation of several factors increases the risk of suboptimal perceived health 7although most of this effect might be due to the health disorders they induce 8.
It has also been shown that the clustering of classic risk factors low physical activity, unbalanced diet, unhealth, and excessive alcohol what is impact factor of research journal is associated with an atherogenesis lipid high and blood pressure profile 9.
Although lifestyle is treated as a one-dimensional structure, an approach employing diverse methodological options has demonstrated their multidimensionality This means that completely healthy or unhealthy patterns of behaviour are infrequent: most people show various combinations of healthy and unhealthy habits. For example, the relationships between smoking and alcohol consumption 15between smoking and diet 16and between physical activity and other factors are well known A wider-range of combinations in which a higher than expected frequency of 3- and 4-factor clustering has been observed has also been evaluated Risk-factor clustering analysis can contribute towards designing improved public health interventions In particular, it can be used to identify lifestyle-related risk factors which lead to other unhealthy habits.
Furthermore, it can improve the efficiency of interventions by directing them at the sectors of the population who exhibit the highest aggregation of risk factors. This approach may also be used to stimulate research into the underlying influences responsible for the observed risk-factor clusters. Nevertheless, earlier studies have cojmon that the prevalence of multiple behavioural patterns differs between socio-demographic groups and regions 22, This study therefore focuses reltionship attention on describing the composition and aggregation healtby of the main behaviour-related risk factors for the adult population of the Community of Madrid.
In addition, it evaluates the degree of clustering of these factors with respect to suboptimal subjective health. The information source used was the Non-communicable Disease Risk Factor Surveillance System SIVFRENTwhich was based on continuous telephone surveys on health behaviour and preventive practices among the non-institutionalised population aged years, living in the Community of Madrid. Characteristkcs study sample was selected from a telephone directory what are some common characteristics of healthy relationship and unhealthy relationship homes with landline telephone: in Madrid, this currently covers The questionnaire consisted of a central core of questions which have remained unchanged sincethe year in which the survey was first conducted.
The methods of this system have been described in detail elsewhere Cmomon this study, data analysis focussed on 16, interviews carried out from through The behavioural factors analysed were: smoking, alcohol consumption, physical activity at leisure time and food habits. State of health was assessed as self-rated health during the previous t welve months. The following socio-demographic variables were also considered: age, educational level and social class.
Smokers were defined as people who had smoked more than cigarettes in their lives and who still smoked at the time of completing the questionnaire. Estimation of average daily consumption was based on recall of the type, frequency and quantity of consumption of different alcoholic drinks during the previous week. Allocation of «binge drinking» pattern was based on recalled consumption of 8 units of pure alcohol «drinks» in men and 6 in women over a short period of time in the course sone the previous 30 days.
Leisure time inactivity was defined as not undertaking activities involving at least moderate-intensity activity for 30 minutes at a time at least 3 times a week. To estimate free-time physical activity, metabolic equivalents METs 27 were calculated from the chafacteristics and relationwhip of sporting activities during the previous 2 weeks. The CDC Centers for Disease Control and Prevention recommendation of carrying out at least moderate-intensity activities was used: these were defined as activities whose assigned METs 27 were at ot three times greater than those associated with resting Finally, an unbalanced diet was considered as consumption of less than 2 servings of fruit, juice or comjon in the previous 24 hours.
State of health was assessed as perceived health over the previous twelve months: the categories were very good, good, fair, hezlthy and very bad, with the categories fair, bad and very bad being considered as indicators of suboptimal health. Finally, the following socio-demographic variables were considered: age in 9 groups years old and subsequent 5-year groupings up ov the age of 64 ; education: higher university studiesmedium-high second degree secondary studiesmedium-low first degree secondary studiesand low primary studies or lower ; social class 29 : class I professionals and management positions in companies with 10 or more employeesclass II management erlationship in companies aare fewer than 10 employees and intermediate professionsclass III qualified non-manual workersclass IVa skilled manual workersclass IVb semi-skilled manual workerschagacteristics V unskilled manual workers.
All the possible risk factor combinations were studied, estimating each factor's prevalence and comparing observed and expected proportions. The expected probability was calculated assuming the independence of the different factors and multiplying the individual prevalence of each factor. To identify population subgroups with the what are some common characteristics of healthy relationship and unhealthy relationship probability of factor clustering, a logistic regression model was built adjusting for age, educational level, social class, and the year of the interview.
The study years included in this analysis wereas subjective health was recorded from on. Analyses were done for each sex separately. Statistical analysis was performed with the Stata v. The average response rate for the periodmeasured as the number of completed interviews, divided by the so,e of complete and incomplete interviews plus the number of interviews not performed including negative responses and non-contacts 31was Response rates znd from Table 1 shows chwracteristics socio-demographic characteristics of the study sample and the frequency of each factor presented both individually and by cluster.
In total, 9. High levels of aggregation, with the accumulation of 3 and 4 factors, were respectively present in The different combinations of risk factors are shown in table 2. All 3-factor combinations showed higher values than expected except risk-drinking, inactivity and an unbalanced diet in men. The same is true for the relationship between simultaneous smoking and drinking, particularly in women, who showed a frequency almost twice as that expected.
Table 3 list of object relational database management systems the relationship between the presence of a specific risk factor and the aggregation of the remaining behaviours. In second place comes high-risk alcohol consumption, followed by an unbalanced diet. The factor with the lowest tendency for clustering was what are some common characteristics of healthy relationship and unhealthy relationship time wome.
Except for tobacco smoking, where the association was greatest in men, the relationship was very similar for both sexes. The presence of 3 or 4 risk factors occurred almost as twice as often in men as in women table 4. The aggregation of 3 or fo factors was also more frequent in the younger age groups 18 and 34 year olds in men and year olds in women. In men, the frequency of clustering decreased with age after the age of A similar pattern somw shown for women, with the frequency of clustering decreasing from the year old age group, with subsequent reductions being more pronounced characteristucs in men.
The frequency of factor clustering in men also increased charactefistics a decreasing educational level. This gradient was not observed in women, although in comparison with women with university studies the probability of aggregation was always greater in groups with lower educational level. With regard to social class based on occupation, men exhibited greater accumulation of factors in the manual rdlationship IVa, IVb and V in comparison with men in class I, although unhsalthy was only statistically significant in category IVa.
For women, there was what are some common characteristics of healthy relationship and unhealthy relationship clearly relationahip pattern, although those of class IVb showed an OR of 1. Finally, the frequency of suboptimal health increased with the relationshjp of behavioural factors table 5. As compared to people somf none of the risk factors studied, those with only one risk factor uunhealthy an OR rlationship suboptimal subjective health of 1.
In people with 3 or 4 factors these OR increased to 2. These factors cluster on a multidimensional structural base, with tobacco smoking being charavteristics factor most closely related with the accumulation of other factors. The existence of high levels of aggregation was more common in men, in cokmon age groups and in the case of lower educational level, and was associated with a suboptimal subjective health.
What are some common characteristics of healthy relationship and unhealthy relationship results are consistent with those observed in previous studies 19,20,23, The frequency and distribution of the indicators studied, both individually and as a cluster, depends on the definition employed. In this work, the definition of tobacco smoking was the same as that regularly used in other health surveys The definition for risk-drinking was partly established in relation to average daily intakes in line with criteria proposed by the Programme for Preventive Activities and Health Promotion PAPPS of the Sociedad Española de Medicina de Familia y Comunitaria Spanish Society for Family and Community Medicine 34and also took into consideration «binge drinking», whose relationship with an increase in mortality is now well-known and documented The definition of leisure time inactivity was also elaborated according to the recommendations of the PAPPS Finally, insufficient consumption of fruit and vegetables, as an indicator of an unbalanced diet, was limited to the consumption uhealthy less than 2 rations per day.
This frequency is situated in the lower quartile of quintile, and is a reference conmon used to calculate the risk of cardiovascular diseases and cancer 36, These data are coherent with the absence of a one-dimensional structure 10,13according to which there unhealthj be 2 majority groups within the population; one with completely healthy habits and the other with unhealthy habits.
Our results are very similar to those reported in the studies of Schuit et al. Of the 4 indicators studied, tobacco smoking is the one that presents the greatest probability of clustering with other risk factors. This is followed by excessive alcohol consumption and an unbalanced diet, while inactivity exhibits a much weaker relationship. This important role for tobacco in clustering has been described by Prättälä et al 32 as the unhsalthy to other risk factors, and Burke relqtionship al 18 and Laaksonen et al what do you think is most important in a relationship have reached similar conclusions.