The stability of lifestyle behaviour

Mulder, Mirjam; Ranchor, Adelita V.; Sanderman, Robbert; Bouma, J.; Heuvel, van den Wim

doi:10.1093/ije/27.2.199

Cited by 84 publications

(70 citation statements)

References 14 publications

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“…While some studies have investigated dietary stability, many of these use dietary scores based on a limited number of foods or food behaviours and results between studies are inconsistent. Mulder et al (46) used a dietary score based on seven food behaviours and found great variability over a 4-year period, while Mishra et al (47) used a dietary pattern score based on factor analysis and found that healthier eating behaviours were more stable than other behaviours. In contrast, van Dam et al (48) found higher stability with the Western pattern in comparison to the 'Prudent' dietary pattern.…”

Section: Study Implicationsmentioning

confidence: 99%

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort

Harrington

Dahly

Fitzgerald

et al. 2014

Public Health Nutr.

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Objective: Data-driven approaches to dietary patterns are under-utilized; latent class analyses (LCA) are particularly rare. The present study used an LCA to identify subgroups of people with similar dietary patterns, explore changes in dietary patterns over a 10-year period and relate these dynamics to sociodemographic factors and health outcomes. Design: The 1998 baseline and 2008 follow-up of the Cork and Kerry Diabetes and Heart Disease Study. Diets were assessed with a standard FFQ. LCA, under the assumption of conditional independence, was used to identify mutually exclusive subgroups with different dietary patterns, based on food group consumption. Setting: Republic of Ireland. Subjects: Men and women aged 50-69 years at baseline (n 923) and at 10-year follow-up (n 320). Results: Three dietary classes emerged: Western, Healthy and Low-Energy. Significant differences in demographic, lifestyle and health outcomes were associated with class membership. Between baseline and follow-up most people remained 'stable' in their dietary class. Most of those who changed class moved to the Healthy class. Higher education was associated with transition to a healthy diet; lower education was associated with stability in an unhealthy pattern. Transition to a healthy diet was associated with higher CVD risk factors at baseline: respondents were significantly more likely to be smokers, centrally obese and to have hypertension (non-significant). Conclusions: LCA is useful for exploring dietary patterns transitions. Understanding the predictors of longitudinal stability/transitions in dietary patterns will help target public health initiatives by identifying subgroups most/least likely to change and most/least likely to sustain a change.

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Section: Study Implicationsmentioning

confidence: 99%

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort

Harrington

Dahly

Fitzgerald

et al. 2014

Public Health Nutr.

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“…In fact, dietary habits from a decade ago and those close to the presentation of the disease could both be of importance. Dietary habits are, however, relatively stable 2 and the ability to change food habits varies between individuals 3 . Dietary changes over time may occur because active decisions are made about lifestyle and dietary behaviours 4 -6 .…”

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confidence: 99%

Past food habit change is related to obesity, lifestyle and socio-economic factors in the Malmo Diet and Cancer Cohort

Sonestedt

Wirfält

Gullberg

et al. 2005

Public Health Nutr.

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Objectives: To examine if obesity status and socio-economic and lifestyle factors are associated with self-reported past food habit change, and also whether the level of obesity depends on the reason for change. Design: Cross-sectional analysis within the Malmo Diet and Cancer (MDC) study using data from the baseline examination and the extensive socio-economic and lifestyle questionnaire including questions of past food habit change. The risk of having changed food habits in the past was examined using logistic regression. Mean differences in obesity status across categories of reasons for past food habit change were examined using analysis of variance. Setting: Malmö, the third largest city in Sweden. Subjects: A sub-sample (15 282 women and 9867 men) from the MDC cohort recruited from 1992 to 1996. Results: Individuals with body mass index (BMI) . 30 kg m 22 had an increased risk of having reported past food habit change compared with individuals with BMI , 25 kg m 22 (odds ratio (OR) ¼ 1.63, 95% confidence interval (CI) ¼ 1.48-1.83 for women; OR ¼ 1.53, 95% CI ¼ 1.32-1.76 for men). The highest level of obesity was observed among individuals who had changed their diet due to reasons related to the metabolic syndrome. Changers were more likely to be highly educated and to live alone, be retired, ex-smokers and non-drinkers at baseline. Conclusions: Because past food habit change is related to obesity and other lifestyle and socio-economic factors, a complex confounding situation may exist that could seriously influence observed relationships between diet and disease. Studies need to collect information on past food habit change and take this information into account in the analysis and when interpreting study outcomes.

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“…En primer lugar, aquellas que son propias del diseño del estudio como es, por ejemplo, cierto grado de infradeclaración en determinadas variables recogidas en la encuesta 14 , o errores derivados de la conexión de los registros 15 . Respecto al análisis estadístico hay que tener en cuenta que no consideramos los cambios que se pueden producir en algunas variables a lo largo del tiempo 16 .…”

Section: Discussionunclassified

La edad como escala de tiempo en el análisis de la supervivencia por trastornos crónicos

Gibert¹,

Albarracin²

2006

Rev. Esp. Salud Publica

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(*) Este estudio fue financiado parcialmente por el Fondo de Investigación Sanitaria (FIS 98/0053-01) y forma parte de los trabajos para la obtención del doctorado en Salud Pública e Investigación Biomédica de la Universidad Autóno-ma de Barcelona de Cristina Rius. RESUMENFundamento: El análisis de supervivencia de estudios de cohortes no tiene en cuenta la edad a la que un individuo muere sino durante el cual ha estado siendo incluido en el seguimiento. El objetivo de este trabajo es valorar las diferencias que resultan en el cálculo del riesgo relativo cuando se utiliza la edad en lugar de seguimiento como escala de tiempo en el análisis de supervivencia de los trastornos crónicos.Métodos: Se analizan los datos de la cohorte de seguimiento de 5 años de la encuesta de salud de Cataluña (COHESCA). Se ajustan modelos de Cox con el tiempo de seguimiento (enfoque «habitual») y la edad (enfoque «alternativo») como escala de tiempo. Como principal covariable se usa el índice de comorbilidad y se ajusta por variables demográficas, estilos de vida y salud auto-percibida.Resultados: En los hombres de 40-64 años en el enfoque "habitual" no se observa aumento significativo del riesgo relativo de morir. En las mujeres de 40-64 años con puntuación 3-4 del índice hay un incremento significativo del riesgo relativo. En las personas mayores de 64 años se observa un aumento significativo del riesgo para la puntuación 3-4 [RRhombres=2,1 (1,3-2,5); RRmujeres=2,1 (1,2-3,7)] y >=5 del índice (RRhombres=3,4 (1,7-6,9); RRmujeres=4,0 (2,1-7,7). En el enfoque «alternativo», el riesgo relativo fue de 1,0 (0,7-1,4) en los hombres con una puntuación de 1-2, 1,5 (1,0-2,3) para los de 3-4 y 2,6 (1,4-4,9) para los de >=5. En las mujeres, los RR fueron respectivamente 0,8 (0,5-1,2), 1,7 (1,1-2,7) y 2,6 (1,5-4,8).Conclusiones: Ambos enfoques muestran un aumento del riesgo relativo según el índice de comorbilidad. Sin embargo, en el enfoque «alternativo», se ajusta por el efecto confundidor de la edad.Palabras clave: Estudios de cohortes. Modelos de riesgos proporcionales. Análisis de supervivencia. Trastornos crónicos. Factores confusores. ABSTRACT Age as Time-Scale: An Application to the Survival Analysis of Chronic DiseasesBackground: Cohort study survival analysis does not take into account the age at which an individual dies, but rather the age throughout which the individual has been included in the follow-up. This study is aimed at assessing the resulting differences in the calculation of the relative risk (RR) when the age is used instead of follow-up as a timescale in the chronic diseases survival analysis.

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The stability of lifestyle behaviour

Abstract: The four lifestyle behaviours differed in the degree of variation over a 4-year period. Only a small group (11%) changed two or more lifestyle behaviours. This implies that lifestyle behaviour is not a unified concept and should not be treated in that way in public health campaigns.

Cited by 84 publications

References 14 publications

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort

Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort

Past food habit change is related to obesity, lifestyle and socio-economic factors in the Malmo Diet and Cancer Cohort

La edad como escala de tiempo en el análisis de la supervivencia por trastornos crónicos

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