Effects of changes in residential fast-food outlet exposure on Body Mass Index change: longitudinal evidence from 92,211 Lifelines participants.

BACKGROUND: Evidence on the association between fast-food outlet exposure and Body Mass Index (BMI) remains inconsistent and is primarily based on cross-sectional studies. We investigated the associations between changes in fast-food outlet exposure and BMI changes, and to what extent these associations are moderated by age and fast-food outlet exposure at baseline. METHODS: We used 4-year longitudinal data of the Lifelines adult cohort (N = 92,211). Participant residential addresses at baseline and follow-up were linked to a register containing fast-food outlet locations using geocoding. Change in fast-food outlet exposure was defined as the number of fast-food outlets within 1 km of the residential address at follow-up minus the number of fast-food outlets within 1 km of the residential address at baseline. BMI was calculated based on objectively measured weight and height. Fixed effects analyses were performed adjusting for changes in covariates and potential confounders. Exposure-moderator interactions were tested and stratified analyses were performed if p < 0.10. RESULTS: Participants who had an increase in the number of fast-food outlets within 1 km had a greater BMI increase (B(95% CI): 0.003 (0.001,0.006)). Decreases in fast-food outlet exposure were not associated with BMI change (B(95% CI): 0.001 (-0.001,0.004)). No clear moderation pattern by age or fast-food outlet exposure at baseline was found. CONCLUSIONS: Increases in residential fast-food outlet exposure are associated with BMI gain, whereas decreases in fast-food outlet exposure are not associated with BMI loss. Effect sizes of increases in fast-food outlet exposure on BMI change were small at individual level. However, a longer follow-up period may have been needed to fully capture the impact of increases in fast-food outlet exposure on BMI change. Furthermore, these effect sizes could still be important at population level considering the rapid rise of fast-food outlets across society. Future studies should investigate the mechanisms and changes in consumer behaviours underlying associations between changes in fast-food outlet exposure and BMI change.

Work- and mental health-related events and body mass index trajectories during the Covid-19 lockdown. Evidence from the lifelines cohort study in the Netherlands.

BACKGROUND: The aim of this study was to identify heterogeneity in trajectories of body mass index (BMI) during the Covid-19 pandemic in the Netherlands. Moreover, we aimed to investigate whether work- and mental health-related disruptive events experienced during the pandemic, such as job insecurity or depression, were associated with such BMI trajectories. METHODS: Longitudinal data from the Lifelines Covid Questionnaire was used (21 waves between April 2020 and July 2021; n = 64,630). Different trajectories were identified using group-based trajectory models. Multinomial regression models were fitted to analyse the main determinants of experiencing changes in BMI during the pandemic. RESULTS: Trajectories of increased BMI, and, to a lesser extent also trajectories of decreased BMI, were more common among those who experienced disruptive work-related events (e.g., being laid-off or having a temporary contract) and mental health-related events (e.g., anxiety or depression) during the pandemic. Those experiencing multiple events were particularly likely to show trajectories of increased or decreased BMI. CONCLUSIONS: During the Covid-19 pandemic, strong heterogeneity was observed in BMI trajectories. This was partially related to work- and mental health-related events.

Educational inequalities in metabolic syndrome prevalence, timing, and duration amongst adults over the life course: a microsimulation analysis based on the lifelines cohort study.

BACKGROUND: Educational inequalities in metabolic syndrome (MetS) are a growing public health concern. Intervening on modifiable factors may help reduce these inequalities, but there is a need for evidence on the long-term impact of intervening on these factors. Thus, we simulate the development of educational inequalities in MetS across the life course and assess the impact of intervening on the modifiable factors that contribute to these inequalities. METHODS: We used data from the prospective multigenerational Dutch Lifelines Cohort Study to estimate the required input for a continuous-time microsimulation. The microsimulation projects the development of educational inequalities in MetS between ages 18 and 65, and assesses the potential benefit of intervening on smoking, alcohol use, diet quality, and health literacy. FINDINGS: The likelihood of ever experiencing MetS between ages 18 and 65 varies from 32.5% among high educated women to 71.5% among low educated men. On average, 27.6% more individuals with low education will ever experience MetS between ages 18 and 65 compared to those with high education. Additionally, individuals with low education generally will develop MetS 2.3 years earlier, and will spend an extra 2.6 years with MetS, compared to individuals with high education. Changes to smoking behaviours in individuals with low education produced the largest effect; it would reduce inequalities in prevalence, timing and duration by an average of 7.5%, 9.5%, and 6.9%, respectively. CONCLUSIONS: Interventions targeting the modifiable factors included in this study, especially smoking, could help reduce the estimated educational inequalities in MetS over the life course.

Lifestyle factors related to prevalent chronic disease multimorbidity: A population-based cross-sectional study.

BACKGROUND: Multimorbidity is associated with poor quality of life, polypharmacy, health care costs and mortality, with those affected potentially benefitting from a healthy lifestyle. We assessed a comprehensive set of lifestyle factors in relation to multimorbidity with major chronic diseases. METHODS: This cross-sectional study utilised baseline data for adults from the prospective Lifelines Cohort in the north of the Netherlands (N = 79,345). We defined multimorbidity as the co-existence of two or more chronic diseases (i.e. cardiovascular disease, cancer, respiratory disease, type 2 diabetes) and evaluated factors in six lifestyle domains (nutrition, physical (in)activity, substance abuse, sleep, stress, relationships) among groups by the number of chronic diseases (≥2, 1, 0). Multinomial logistic regression models were created, adjusted for appropriate confounders, and odds ratios (OR) with 95% confidence intervals (95%CI) were reported. RESULTS: 3,712 participants had multimorbidity (4.7%, age 53.5 ± 12.5 years), and this group tended to have less healthy lifestyles. Compared to those without chronic diseases, those with multimorbidity reported physical inactivity more often (OR, 1.15; 95%CI, 1.06-1.25; not significant for one condition), chronic stress (OR, 2.14; 95%CI, 1.92-2.38) and inadequate sleep (OR, 1.70; 95%CI, 1.41-2.06); as expected, they more often watched television (OR, 1.70; 95%CI, 1.42-2.04) and currently smoked (OR, 1.91; 95%CI, 1.73-2.11), but they also had lower alcohol intakes (OR, 0.66; 95%CI, 0.59-0.74). CONCLUSIONS: Chronic stress and poor sleep, in addition to physical inactivity and smoking, are lifestyle factors of great concern in patients with multimorbidity.

Fast-food environments and BMI changes in the Dutch adult general population: the Lifelines cohort.

OBJECTIVE: This study investigated cross-sectional and longitudinal associations of fast-food outlet exposure with BMI and BMI change, as well as moderation by age and genetic predisposition. METHODS: This study used Lifelines' baseline (n = 141,973) and 4-year follow-up (n = 103,050) data. Participant residential addresses were linked to a register with fast-food outlet locations (Nationwide Information System of Workplaces [Dutch: Landelijk Informatiesysteem van Arbeidsplaatsen, LISA]) using geocoding, and the number of fast-food outlets within 1 km was computed. BMI was measured objectively. A weighted BMI genetic risk score was computed, representing overall genetic predisposition toward elevated BMI, based on 941 single-nucleotide polymorphisms genome-wide significantly associated with BMI for a subsample with genetic data (BMI: n = 44,996; BMI change: n = 36,684). Multivariable multilevel linear regression analyses and exposure-moderator interactions were tested. RESULTS: Participants with ≥1 fast-food outlet within 1 km had a higher BMI (B [95% CI]: 0.17 [0.09 to 0.25]), and those with ≥2 fast-food outlets within 1 km increased more in BMI (B [95% CI]: 0.06 [0.02 to 0.09]) than participants with no fast-food outlets within 1 km. Effect sizes on baseline BMI were largest among young adults (age 18-29 years; B [95% CI]: 0.35 [0.10 to 0.59]) and especially young adults with a medium (B [95% CI]: 0.57 [-0.02 to 1.16]) or high genetic risk score (B [95% CI]: 0.46 [-0.24 to 1.16]). CONCLUSIONS: Fast-food outlet exposure was identified as a potentially important determinant of BMI and BMI change. Young adults, especially those with a medium or high genetic predisposition, had a higher BMI when exposed to fast-food outlets.

Changes in anxiety and depression symptoms during the Covid-19 lockdown in the Netherlands. The moderating role of pre-existing mental health, employment situation and alcohol consumption.

PURPOSE: Evidence suggests an increase of depression and anxiety symptoms during the Covid-19 pandemic but most studies relied on cross-sectional designs and/or small samples, and they often overlooked subgroup effects in the impact of the lockdown. We investigated the effect of the pandemic on depression and anxiety symptoms, and whether it differed by employment situation and alcohol consumption. METHODS: This longitudinal study used 23 waves of the Covid-Questionnaire (April 2020-July 2021), within the Lifelines cohort from the Netherlands (n = 76,254). Depression and anxiety symptoms were combined in a "mental health score". Linear fixed-effects models were fitted to analyse trends in mental health throughout the observation period. The moderating role of pre-existing mental health, employment situation, and alcohol consumption was tested. RESULTS: Depression and anxiety symptoms fluctuated considerably during the observation period, with clear peaks in winter 2021, during the strictest lockdown period. Moreover, temporal patterns differed by employment situation and alcohol consumption patterns, suggesting that various subgroups reacted to the pandemic and the lockdown in different ways. CONCLUSION: Lockdowns increased depression and anxiety symptoms in the Netherlands. The effect was particularly strong for unemployed individuals, those with risky alcohol consumption patterns and those with pre-existing mental health disorders.

Relationship Between Childhood Abuse and Body Mass Index in Young Adulthood: Mediated by Depression and Anxiety?

We examined whether childhood abuse is related to body mass index (BMI) in young adults and whether this relationship is mediated by depression and anxiety. Data are from the Dutch longitudinal cohort study TRAILS (nfemales = 836, nmales = 719). At wave 4, childhood sexual, physical and verbal abuse, and lifetime major depressive disorder (MDD) and generalized anxiety disorder (GAD) were assessed. BMI was measured at wave 4 and 5 (mean age = 19.2/22.4 years). Sex-stratified structural equation models were estimated. Females who had experienced sexual abuse had a higher BMI at wave 4 (B = 0.97, 95%CI = [-0.01,1.96]) and a higher increase in BMI between wave 4 and 5 (B = 0.52, 95%CI = [0.04,1.01]) than females who had not experienced sexual abuse. Additionally, MDD and BMI at wave 4 were related in females (B = 1.35, 95%CI = [0.52,2.18]). MDD mediated the relationship between sexual abuse and BMI at wave 4 in females. In addition, sexual abuse moderated the relationship between MDD and BMI at wave 4. The relationship was stronger among females who had experienced sexual abuse than among females who had not. Prevention of BMI changes among females who experienced sexual abuse may thus be warranted, particularly when they developed MDD. MDD treatment, such as abuse-focused psychotherapy, may aid this prevention.

Neighborhood socioeconomic differences in BMI: The role of fast-food outlets and physical activity facilities.

OBJECTIVE: The goal of this study was to investigate the association between neighborhood socioeconomic status (NSES) and BMI and to what extent this association is moderated by availability of fast-food (FF) outlets and pay-for-use physical activity (PA) facilities. METHODS: Baseline data of adults in Lifelines (N = 146,629) were linked to Statistics Netherlands and a register using geocoding to compute, respectively, NSES (i.e., low, middle, high) and the number of FF outlets and PA facilities within 1 km of the residential address. Multivariable multilevel linear regression analyses were performed to examine the association between NSES and BMI. Two-way and three-way interaction terms were tested to examine moderation by FF outlets and PA facilities. RESULTS: Participants living in low NSES areas had a higher BMI than participants living in high (B [95% CI]: 0.76 [0.65 to 0.87]) or middle NSES areas (B [95% CI]: 0.40 [0.28 to 0.51]), independent of individual socioeconomic status. Although two- and three-way interactions between NSES, FF outlets, and PA facilities were significant, stratified analyses did not show consistent moderation patterns. CONCLUSIONS: People living in lower NSES areas had a higher BMI, independent of their individual socioeconomic status. The study found no clear moderation of FF outlets and PA facilities. Environmental factors that may mitigate NSES differences in BMI should be the subject of future research.

Disentangling the association between alcohol consumption and employment status: causation, selection or confounding?

BACKGROUND: Alcohol use constitutes a major health risk and is related to unemployment. However, the direction of this relationship is unclear: unemployment may change drinking patterns (causation), but heavy drinkers may also be more prone to lose their job (selection). We simultaneously examined selection and causation, and assessed the role of residual confounding. Moreover, we paid attention to the subgroup of abstainers and occupationally disabled, often disregarded in the literature. METHODS: Longitudinal data (three waves collected between 2006 and 2018) of the Lifelines Cohort study from the Netherlands were used (138 875 observations of 55 415 individuals, aged 18-60 at baseline). Alcohol use was categorized as 'abstaining', 'moderate drinking' and 'binge drinking' (≥5 drinks/occasion for male; ≥4 for women). Employment status included occupational disability, short (<6 months) and long-term (≥6 months) unemployment. Random- and fixed-effects multinomial regression models were fitted in order to account for residual confounding. Reciprocal causality was assessed through generalized structural equation modelling with fixed-effects. RESULTS: Long unemployment spells increase the risk for both binge drinking (ß = 0.23; 95% CI 0.04-0.42) and abstinence (ß = 0.27; 95% CI 0.11-0.44), and the effects hold after accounting for reciprocal causality and time-constant confounding. Contrarily, the effect of binge drinking on unemployment is weak (ß = 0.14; 95% CI -0.03 to 0.31). Abstinence is strongly associated with occupational disability (ß = 0.40; 95% CI 0.24-0.57). CONCLUSIONS: We find evidence supporting the causation hypothesis (unemployment altering drinking patterns), whereas evidence for the selection hypothesis is weak and mostly confounded by unobserved variables, such as poor health prior to baseline.

Socioeconomic differences in metabolic syndrome development among males and females, and the mediating role of health literacy and self-management skills.

BACKGROUND: Our aim was to investigate sex differences in the associations between socioeconomic position (SEP) and metabolic syndrome (MetS) development, and to what extent these associations are mediated by health literacy and self-management skills. METHODS: A subsample (n = 88,384, 59.5% female) of the adult Lifelines Cohort Study was used. MetS development according to NCEP-ATPIII criteria was assessed on average 3.8 years after baseline. SEP-MetS associations were assessed for moderation by sex, and sex-stratified accordingly. Associations between SEP measures (education, income and occupational prestige), health literacy and self-management skills, and MetS development were investigated using logistic regression analyses. The mediating effects of health literacy and self-management skills on the SEP-MetS associations were investigated using the Karlson-Holm-Breen method. RESULTS: Among males and females, respectively 9.4% and 7.1% developed MetS. For males, education was inversely associated with MetS development; health literacy (7.1%) and self-management skills (1.9%) mediated a proportion of these educational differences. For females, education, income and occupational prestige were inversely associated with MetS development; health literacy (respectively 5.9% and 6.4%) and self-management skills (respectively 4.1% and 3.7%) mediated a proportion of the educational and occupational differences in MetS development. Neither health literacy nor self-management skills mediated female income differences in MetS development. CONCLUSIONS: Socioeconomic differences in MetS development differ between males and females. Both for males and females, health literacy and self-management skills mediated a small proportion of socioeconomic differences in MetS development.

Socioeconomic differences in major depressive disorder onset among adults are partially explained by lifestyle factors: A longitudinal analysis of the Lifelines Cohort Study.

BACKGROUND: Major depressive disorder (MDD) onset varies by socioeconomic position (SEP), this could be explained by lifestyle factors, but little is known about this pathway. Our study aims to disentangle the interplay between SEP measures (i.e., education, income and occupational prestige) and MDD onset and to examine to what extent these associations are mediated by lifestyle (i.e., occupational- and leisure time physical activity, smoking, alcohol intake, diet quality, sleep and central adiposity). METHODS: A subsample (n = 76,045) of the Lifelines Cohort Study without MDD at baseline was included. MDD onset was measured after a median follow-up time of 3.8 years with the Mini International Neuropsychiatric Interview (MINI). Direct associations between SEP, lifestyle and MDD onset were estimated using logistic regression analyses. Mediating percentages were estimated using the Karlson-Holm-Breen method. RESULTS: 1864 participants (2.5 %) showed MDD at follow-up. SEP was inversely associated with MDD onset, with education showing the strongest association. Educational, income and occupational differences in MDD onset were for 18.7 %, 5.9 % and 21.7 % explained by lifestyle factors (mainly smoking, alcohol intake and central adiposity). LIMITATIONS: SEP and lifestyle factors were measured simultaneously at baseline. MDD status (only based on a screening tool) was only measured at baseline and 3.8 years later. CONCLUSIONS: Compared to their lower SEP counterparts, higher SEP individuals had a lower risk of MDD onset. This was partially explained by a healthier lifestyle (mainly less smoking, alcohol intake and central adiposity) of the higher SEP individuals.

The association between the presence of fast-food outlets and BMI: the role of neighbourhood socio-economic status, healthy food outlets, and dietary factors.

BACKGROUND: Evidence on the association between the presence of fast-food outlets and Body Mass Index (BMI) is inconsistent. Furthermore, mechanisms underlying the fast-food outlet presence-BMI association are understudied. We investigated the association between the number of fast-food outlets being present and objectively measured BMI. Moreover, we investigated to what extent this association was moderated by neighbourhood socio-economic status (NSES) and healthy food outlets. Additionally, we investigated mediation by frequency of fast-food consumption and amount of fat intake. METHODS: In this cross-sectional study, we used baseline data of adults in Lifelines (N = 149,617). Geo-coded residential addresses were linked to fast-food and healthy food outlet locations. We computed the number of fast-food and healthy food outlets within 1 kilometre (km) of participants' residential addresses (each categorised into null, one, or at least two). Participants underwent objective BMI measurements. We linked data to Statistics Netherlands to compute NSES. Frequency of fast-food consumption and amount of fat intake were measured through questionnaires in Lifelines. Multivariable multilevel linear regression analyses were performed to investigate associations between fast-food outlet presence and BMI, adjusting for individual and environmental potential confounders. When exposure-moderator interactions had p-value < 0.10 or improved model fit (∆AIC ≥ 2), we conducted stratified analyses. We used causal mediation methods to assess mediation. RESULTS: Participants with one fast-food outlet within 1 km had a higher BMI than participants with no fast-food outlet within 1 km (B = 0.11, 95% CI: 0.01, 0.21). Effect sizes for at least two fast-food outlets were larger in low NSES areas (B = 0.29, 95% CI: 0.01, 0.57), and especially in low NSES areas where at least two healthy food outlets within 1 km were available (B = 0.75, 95% CI: 0.19, 1.31). Amount of fat intake, but not frequency of fast-food consumption, explained this association for 3.1%. CONCLUSIONS: Participants living in low SES neighbourhoods with at least two fast-food outlets within 1 km of their residential address had a higher BMI than their peers with no fast-food outlets within 1 km. Among these participants, healthy food outlets did not buffer the potentially unhealthy impact of fast-food outlets. Amount of fat intake partly explained this association. This study highlights neighbourhood socio-economic inequalities regarding fast-food outlets and BMI.

Measurement properties of the Dutch PROMIS-29 v2.1 profile in people with and without chronic conditions.

PURPOSE: To investigate the structural validity, internal consistency, measurement invariance, and construct validity of the Dutch PROMIS-29 v2.1 profile, including seven physical (e.g., pain, physical function), mental (e.g., depression, anxiety), and social (e.g., role functioning) domains of health, in a Dutch general population sample including subsamples with and without chronic diseases. METHODS: The PROMIS-29 was completed by 63,602 participants from the Lifelines cohort study. Structural validity of the PROMIS-29, including unidimensionality of each domain and the physical and mental health summary scores, was evaluated using factor analyses (criteria: CFI ≥ 0.95, TLI ≥ 0.95, RMSEA ≤ 0.06, SRMR ≤ 0.08). Internal consistency, measurement invariance (no differential item functioning (DIF) for age, gender, administration mode, educational level, ethnicity, chronic diseases), and construct validity (hypotheses on known-groups validity and correlations between domains) were assessed per domain. RESULTS: The factor structure of the seven domains was supported (CFI = 0.994, TLI = 0.993, RMSEA = 0.046, SRMR = 0.031) as was unidimensionality of each domain, both in the entire sample and the subsamples. Model fit of the physical and mental health summary scores reached the criteria, and scoring coefficients were obtained. Cronbach's alpha for the seven PROMIS-29 domains ranged from 0.75 to 0.96 in the complete sample. No DIF was detected. Of the predefined hypotheses, 78% could be confirmed. CONCLUSION: Sufficient structural validity, internal consistency and measurement invariance were found, both in the entire sample and in subsamples with and without chronic diseases. Requirements for sufficient evidence for construct validity were (almost) met for most subscales. Future studies should investigate test-retest reliability, measurement error, and responsiveness of the PROMIS-29.

Socioeconomic differences in metabolic syndrome development: examining the mediating role of chronic stress using the Lifelines Cohort Study.

BACKGROUND: Metabolic syndrome (MetS) development strongly varies based on individuals' socioeconomic position (SEP), but to date, no studies have assessed the mediating role of perceived stress from long-term difficulties (chronic stress) in this association. The aim of this study is to examine the mediating role of chronic stress in the associations of the SEP measures education, occupational prestige and income, with MetS development, and whether associations between chronic stress and MetS are moderated by sex. METHODS: We used an adult subsample (n = 53,216) from the Lifelines Cohort Study without MetS at baseline. MetS development was measured 3.9 years after baseline (follow-up), and defined according to National Cholesterol Education Program's Adult Treatment Panel III (NCEP-ATPIII) criteria. Direct associations between SEP, chronic stress and MetS development were estimated using multivariable logistic and linear regression analyses, and were adjusted for age, sex, the other SEP measures, and time between baseline and follow-up. The mediating percentages of chronic stress explaining the associations between SEP and MetS development were estimated using the Karlson-Holm-Breen method. RESULTS: Upon follow-up, 7.4% of the participants had developed MetS. Years of education and occupational prestige were inversely associated with MetS development. Chronic stress suppressed the association between education and MetS development (5.6%), as well as the association between occupational prestige and MetS development (6.2%). No effect modification of sex on the chronic stress-MetS pathway was observed. CONCLUSIONS: Chronic stress does not explain educational and occupational differences in developing MetS. In fact, individuals with more years of education or higher occupational prestige perceive more chronic stress than their lower SEP counterparts. Further, no difference between males and females was observed regarding the relationship between chronic stress and MetS development.

The impact of the COVID lockdown on alcohol consumption in the Netherlands. The role of living arrangements and social isolation.

BACKGROUND: The COVID-19 pandemic and the subsequent lockdown have a strong impact on health and health behaviours, such as alcohol consumption. Although there is some evidence of an overall decline in alcohol consumption during the lockdown, studies also show an increase in risky drinking patterns, e.g. solitary drinking, and differences between subgroups of individuals, e.g. depending on their living arrangement. Yet most studies rely on cross-sectional designs with retrospective questions, and small samples. METHODS: A longitudinal study was conducted using 13 waves of the COVID-Questionnaire within the Lifelines cohort from the northern Netherlands (n = 63,194). The outcome was alcohol consumption (glasses per week) between April 2020 and July 2021. Linear fixed-effects models were fitted to analyse trends in alcohol consumption, and these were compared with pre-COVID drinking levels. Moreover, the role of living arrangement and feelings of social isolation as potential moderators was tested. RESULTS: Alcohol consumption during the pandemic was lower than in previous years, and the seasonal pattern differed from the pre-COVID one, with levels being lower when lockdown measures were stricter. Moreover, the seasonal pattern differed by living arrangement: those living alone saw a relative increase in drinking throughout tight lockdown periods, whereas those living with children showed the strongest increase during the summer. Social isolation showed a weaker moderation effect. CONCLUSIONS: Overall alcohol levels were down in the pandemic, and in particular during strict lockdowns. Those living on their own and those who felt more isolated reacted more strongly to the lockdown, the longer it lasted.

Determinants of trajectories of fatigability and mobility among older medical patients during and after hospitalization; an explorative study.

BACKGROUND: Fatigability is an important marker of functional decline in community dwelling older people, yet its relationship with functional decline after hospitalization is unclear. The objectives of this study were to identify trajectories of fatigability and mobility over time and to examine the association between demographic and clinical characteristics and these trajectories in medical patients aged 70 years and older admitted to a Dutch tertiary care teaching hospital. METHODS: In this prospective cohort study with baseline (in-hospital), discharge, three-, and six-months post discharge follow-up measurements, fatigability was assessed by the physical subscale of the Pittsburgh Fatigability Scale (PFS). Mobility was assessed by the De Morton Mobility Index (DEMMI). Group-based trajectory modeling was used to identify joint trajectories of fatigability and mobility. Covariates included demographic (age, sex, living situation, education) and clinical characteristics (functional status, frailty status, depression, comorbidity, length of hospital stay). RESULTS: Among 44 patients, three distinct fatigability trajectories and two mobility trajectories were identified over the course from hospital admission up to six months after discharge. Subsequently, three joint trajectories were identified, including low fatigability and high mobility (11%), improving fatigability and high mobility (52%), and high fatigability and low mobility (36%). Controlling for baseline functional status, patients with a lower comorbidity score (OR: 0.27, 95%CI 0.10; 0.74) and higher frailty status (OR: 1.36, 95%CI: 1.07; 1.74) were more likely to be a member of the high fatigability and low mobility trajectories. CONCLUSIONS: From hospital admission up to six months after discharge, three distinct trajectories of fatigability and mobility were identified among older medical patients. Our results should be interpreted with caution due to the small sample size, but may inspire other researchers to determine the value of fatigability assessment in identifying older medical patients at risk for developing mobility problems.

The association between fast-food outlet proximity and density and Body Mass Index: Findings from 147,027 Lifelines Cohort Study participants.

Unhealthy food environments may contribute to an elevated Body Mass Index (BMI), which is a chronic disease risk factor. We examined the association between residential fast-food outlet exposure, in terms of proximity and density, and BMI in the Dutch adult general population. Additionally, we investigated to what extent this association was modified by urbanisation level. In this cross-sectional study, we linked residential addresses of baseline adult Lifelines Cohort participants (n = 147,027) to fast-food outlet locations using geo-coding. We computed residential fast-food outlet proximity, and density within 500 m, 1, 3, and 5 km. We used stratified (urban versus rural areas) multilevel linear regression models, adjusting for age, sex, partner status, education, employment, neighbourhood deprivation, and address density. The mean BMI of participants was 26.1 (SD 4.3) kg/m2. Participants had a mean (SD) age of 44.9 (13.0), 57.3% was female, and 67.0% lived in a rural area. Having two or more (urban areas) or five or more (rural areas) fast-food outlets within 1 km was associated with a higher BMI (B = 0.32, 95% confidence interval (CI): 0.03, 0.62; B = 0.23, 95% CI: 0.10, 0.36, respectively). Participants in urban and rural areas with a fast-food outlet within <250 m had a higher BMI (B = 0.30, 95% CI: 0.03, 0.57; B = 0.20, 95% CI: 0.09, 0.31, respectively). In rural areas, participants also had a higher BMI when having at least one fast-food outlet within 500 m (B = 0.10, 95% CI: 0.02, 0.18). In conclusion, fast-food outlet exposure within 1 km from the residential address was associated with BMI in urban and rural areas. Also, fast-food outlet exposure within 500 m was associated with BMI in rural areas, but not in urban areas. In the future, natural experiments should investigate changes in the fast-food environment over time.

Association between dementia parental family history and mid-life modifiable risk factors for dementia: a cross-sectional study using propensity score matching within the Lifelines cohort.

OBJECTIVE: Individuals with a parental family history (PFH) of dementia have an increased risk to develop dementia, regardless of genetic risks. The aim of this study is to investigate the association between a PFH of dementia and currently known modifiable risk factors for dementia among middle-aged individuals using propensity score matching (PSM). DESIGN: A cross-sectional study. SETTING AND PARTICIPANTS: A subsample of Lifelines (35-65 years), a prospective population-based cohort study in the Netherlands was used. OUTCOME MEASURES: Fourteen modifiable risk factors for dementia and the overall Lifestyle for Brain Health (LIBRA) score, indicating someone's potential for dementia risk reduction (DRR). RESULTS: The study population included 89 869 participants of which 10 940 (12.2%) had a PFH of dementia (mean (SD) age=52.95 (7.2)) and 36 389 (40.5%) without a PFH of dementia (mean (SD) age=43.19 (5.5)). Of 42 540 participants (47.3%), PFH of dementia was imputed. After PSM, potential confounding variables were balanced between individuals with and without PFH of dementia. Individuals with a PFH of dementia had more often hypertension (OR=1.19; 95% CI 1.14 to 1.24), high cholesterol (OR=1.24; 95% CI 1.18 to 1.30), diabetes (OR=1.26; 95% CI 1.11 to 1.42), cardiovascular diseases (OR=1.49; 95% CI 1.18 to 1.88), depression (OR=1.23; 95% CI 1.08 to 1.41), obesity (OR=1.14; 95% CI 1.08 to 1.20) and overweight (OR=1.10; 95% CI 1.05 to 1.17), and were more often current smokers (OR=1.20; 95% CI 1.14 to 1.27) and ex-smokers (OR=1.21; 95% CI 1.16 to 1.27). However, they were less often low/moderate alcohol consumers (OR=0.87; 95% CI 0.83 to 0.91), excessive alcohol consumers (OR=0.93; 95% CI 0.89 to 0.98), socially inactive (OR=0.84; 95% CI 0.78 to 0.90) and physically inactive (OR=0.93; 95% CI 0.91 to 0.97). Having a PFH of dementia resulted in a higher LIBRA score (RC=0.15; 95% CI 0.11 to 0.19). CONCLUSION: We found that having a PFH of dementia was associated with several modifiable risk factors. This suggests that middle-aged individuals with a PFH of dementia are a group at risk and could benefit from DRR. Further research should explore their knowledge, beliefs and attitudes towards DRR, and whether they are willing to assess their risk and change their lifestyle to reduce dementia risk.

Understanding socioeconomic differences in metabolic syndrome remission among adults: what is the mediating role of health behaviors?

BACKGROUND: Although the incidence of metabolic syndrome (MetS) strongly varies based on individuals' socioeconomic position (SEP), as yet no studies have examined the SEP-MetS remission relationship. Our aim is to longitudinally assess the associations between SEP measures education, income and occupational prestige, and MetS remission, and whether these associations are mediated by health behaviors, including physical activity, smoking, alcohol intake and diet quality. METHODS: A subsample (n = 16,818) of the adult Lifelines Cohort Study with MetS at baseline was used. MetS remission was measured upon second assessment (median follow-up time 3.8 years), defined according to NCEP-ATPIII criteria. To estimate direct associations between SEP, health behaviors and MetS remission multivariable logistic regression analyses were used. To estimate the mediating percentages of health behaviors that explain the SEP-MetS remission relationship the Karlson-Holm-Breen method was used. Analyses were adjusted for age, sex, the other SEP measures and follow-up time. RESULTS: At the second assessment, 42.7% of the participants experienced MetS remission. Education and income were positively associated with MetS remission, but occupational prestige was not. The association between education and MetS remission could partly (11.9%) be explained by health behaviors, but not the association between income and MetS remission. CONCLUSIONS: Individuals with higher education more often experienced remission from MetS, mainly because individuals with higher education were more likely to have healthier behaviors. However, individuals with higher income more often experienced MetS remissions, regardless of their health behaviors. The occupational prestige of individuals was not associated with MetS remission.

Reproducibility and responsiveness of the Frailty Index and Frailty Phenotype in older hospitalized patients.

BACKGROUND: There is growing interest for interventions aiming at preventing frailty progression or even to reverse frailty in older people, yet it is still unclear which frailty instrument is most appropriate for measuring change scores over time to determine the effectiveness of interventions. The aim of this prospective cohort study was to determine reproducibility and responsiveness properties of the Frailty Index (FI) and Frailty Phenotype (FP) in acutely hospitalized medical patients aged 70 years and older. METHODS: Reproducibility was assessed by Intra-Class Correlation Coefficients (ICC), standard error of measurement (SEM) and smallest detectable change (SDC); Responsiveness was assessed by the standardized response mean (SRM), and area under the receiver operating characteristic curve (AUC). RESULTS: At baseline, 243 patients were included with a median age of 76 years (range 70-98). The analytic samples included 192 and 187 patients in the three and twelve months follow-up analyses, respectively. ICC of the FI were 0.85 (95 % confidence interval [CI]: 0.76; 0.91) and 0.84 (95% CI: 0.77; 0.90), and 0.65 (95% CI: 0.49; 0.77) and 0.77 (95% CI: 0.65; 0.84) for the FP. SEM ranged from 5 to 13 %; SDC from 13 to 37 %. SRMs were good in patients with unchanged frailty status (< 0.50), and doubtful to good for deteriorated and improved patients (0.43-1.00). AUC's over three months were 0.77 (95% CI: 0.69; 0.86) and 0.71 (95% CI: 0.62; 0.79) for the FI, and 0.68 (95% CI: 0.58; 0.77) and 0.65 (95% CI: 0.55; 0.74) for the FP. Over twelve months, AUCs were 0.78 (95% CI: 0.69; 0.87) and 0.82 (95% CI: 0.73; 0.90) for the FI, and 0.78 (95% CI: 0.69; 0.87) and 0.75 (95% CI: 0.67; 0.84) for the FP. CONCLUSIONS: The Frailty Index showed better reproducibility and responsiveness properties compared to the Frailty Phenotype among acutely hospitalized older patients.