Neighbourhood characteristics as a predictor of adherence to dietary recommendations: A population-based cohort study of Finnish adults.

Aims: To investigate the association of six-year cumulative level of socioeconomic neighbourhood disadvantage and population density with subsequent adherence to dietary recommendations, controlling for preceding dietary adherence, in adults in Finland. Methods: Population-based Health and Social Support (HeSSup) study participants from four age groups (20-24, 30-34, 40-44 and 50-54 years at baseline in 1998). Data on diet and alcohol consumption were obtained from the 2003 and 2012 surveys and information on neighbourhoods from Statistics Finland Grid database (n = 10,414 men and women). Participants diet was measured as adherence to Nordic Nutrition recommendation (score range 0-100). Neighbourhood disadvantage was measured by median household income, proportion of those with primary education only and unemployment rate, and population density by the number of adult population between years 2007 and 2012. Linear models were used to assess the associations of neighbourhood characteristics with the score for adherence to dietary recommendations in 2012. Results: Cumulative neighbourhood socioeconomic disadvantage was associated with slightly weaker (1.49 (95% confidence interval (CI) -1.89 to -1.09) point decrease in dietary score) adherence while higher population density was associated with better (0.70 (95% CI 0.38-1.01) point increase in dietary score) adherence to dietary recommendations. These associations remained after controlling for prior dietary habits, sociodemographic, chronic cardio-metabolic diseases, and severe life events. Conclusions: These longitudinal findings support the hypothesis that neighbourhood characteristics affect dietary habits.

Modifications to residential neighbourhood characteristics and risk of 79 common health conditions: a prospective cohort study.

BACKGROUND: Observational studies have identified a link between unfavourable neighbourhood characteristics and increased risk of morbidity, but it is unclear whether changes in neighbourhoods affect future disease risk. We used a data-driven approach to assess the impact of neighbourhood modification on 79 health outcomes. METHODS: In this prospective cohort study, we used pooled, individual-level data from two Finnish cohort studies: the Health and Social Support study and the Finnish Public Sector study. Neighbourhood characteristics (mean educational level, median income, and employment rate of residents, and neighbourhood green space) and individual lifestyle factors of community-dwelling individuals were assessed at baseline (at different waves starting between 1998 and 2013). We repeated assessment of neighbourhood characteristics and lifestyle factors approximately 5 years from each baseline assessment, after which follow-up began for health conditions diagnosed according to the WHO International Classification of Diseases for 79 common health conditions using linkage to electronic health records. We used Cox proportional hazard regression models to compute adjusted hazard ratios (HRs) of incident disease associated with neighbourhood characteristics and changes in neighbourhood characteristics over time and logistic regression analysis to compute adjusted odds of association between changes in neighbourhood characteristics and individual lifestyle factors. FINDINGS: 114 786 individuals (87 012 [75·8%] women; mean age 44·4 years [SD 11·1]) had complete data and were included in this cohort study. During 1·17 million person-years at risk, we recorded 164 368 new-onset health conditions and 3438 deaths. Favourable changes in neighbourhood characteristics were associated with reduced risk of all-cause mortality and incidence of 19 specific health conditions. Unfavourable changes were correspondingly associated with increased risk of mortality and 27 specific health conditions. Among participants who did not move residence during the observation period, relative to individuals who continually lived in disadvantaged neighbourhoods, those who experienced favourable modifications in neighbourhood characteristics had a lower risk of future diabetes (HR 0·84, 95% CI 0·75-0·93), stroke (0·49, 0·29-0·83), skin disease (0·72, 0·53-0·97), and osteoarthritis (0·87, 0·77-0·99). Living in a neighbourhood with improving characteristics was also associated with improvements in individual-level health-related lifestyle factors. Among participants who lived in advantaged residential environments at baseline, unfavourable changes in neighbourhood characteristics were associated with an increased risk of diabetes, stroke, skin disease, and osteoarthritis compared with individuals who lived in advantaged neighbourhoods throughout the study period. INTERPRETATION: Favourable modifications to residential neighbourhoods showed robust, longitudinal associations with a range of improvements in health outcomes, including improved health behaviours and reduced risk of cardiometabolic, infectious, and orthopaedic conditions. FUNDING: UK Medical Research Council, US National Institute on Aging, NordForsk, and Academy of Finland.

Educational Differences in Decline in Maximum Gait Speed in Older Adults Over an 11-Year Follow-up.

BACKGROUND: This study examined educational differences in decline in maximum gait speed over an 11-year follow-up in the general Finnish population aged 55 years and older and assessed the contribution of lifestyle factors, body mass index, physical workload, and chronic conditions on the association. METHOD: Data from the nationally representative Health 2000 Survey and its 11-year follow-up were used. Participants aged 55 years and older with maximum gait speed measured at both time points were included (n = 1128). Information on education, age, sex, lifestyle factors, body mass index, physical workload, and chronic conditions was collected at baseline. General linear model was used to examine differences in decline in maximum gait speed between education groups. Mediation analyses using the product method was conducted to partition the total effect of education on decline in maximum gait speed into direct effect and indirect effect acting through mediators. RESULTS: Decline in maximum gait speed was greater in low and intermediate education groups in comparison to the high education group (0.24 m/s [95% confidence interval 0.21-0.26], 0.24 m/s [0.21-0.28], 0.10 m/s [0.07-0.14], respectively]. The most important mediators were higher body mass index and lifetime exposure to physical workload among the less educated, accounting for 10% and 11% of the total effect, respectively. CONCLUSIONS: Education-based disparities in objectively measured mobility increase with age as lower education is associated with greater decline in gait speed. Higher body mass index and physical workload among less educated contributed most to the educational disparities in age-related decline in maximum gait speed.

Cross-sectional associations of neighbourhood socioeconomic disadvantage and greenness with accelerometer-measured leisure-time physical activity in a cohort of ageing workers.

OBJECTIVE: Neighbourhood characteristics may affect the level of physical activity (PA) of the residents. Few studies have examined the combined effects of distinctive neighbourhood characteristics on PA using objective data or differentiated between activity during working or non-working days. We examined the associations of socioeconomic disadvantage and greenness with accelerometer-measured leisure-time PA during working and non-working days. DESIGN: Cross-sectional study. SETTING: Finnish Retirement and Aging (FIREA) study. PARTICIPANTS: 708 workers (604 women, mean age 62.4 ranging from 58 to 64 years,) participating in the FIREA study who provided PA measurement data for at least 1 working and non-working day. PRIMARY AND SECONDARY OUTCOMES: PA was measured with wrist-worn accelerometer on average of 4 working and 2 non-working days. Outcomes were total PA, light PA (LPA) and moderate-to-vigorous PA (MVPA). These measurements were linked to data on neighbourhood socioeconomic disadvantage and greenness within the home neighbourhood (750×750 m). Generalised linear models were adjusted for possible confounders. RESULTS: On non-working days, higher neighbourhood disadvantage associated with lower levels of total PA (p value=0.07) and higher level of neighbourhood greenness associated with higher level of total PA (p value=0.04). Neighbourhood disadvantage and greenness had an interaction (p value=0.02); in areas of low disadvantage higher greenness did not associate with the level of total PA. However, in areas of high disadvantage, 2 SD higher greenness associated with 46 min/day (95% CI 8.4 to 85) higher total PA. Slightly stronger interaction was observed for LPA (p=0.03) than for the MVPA (p=0.09). During working days, there were no associations between neighbourhood characteristics and leisure-time total PA. CONCLUSIONS: Of the disadvantaged neighbourhoods, those characterised by high levels of greenness seem to associate with higher levels of leisure-time PA during non-working days. These findings suggest that efforts to add greenness to socioeconomically disadvantaged neighbourhoods might reduce inequalities in PA.

Association between socioeconomic status and the development of mental and physical health conditions in adulthood: a multi-cohort study.

BACKGROUND: Socioeconomic disadvantage is a risk factor for many diseases. We characterised cascades of these conditions by using a data-driven approach to examine the association between socioeconomic status and temporal sequences in the development of 56 common diseases and health conditions. METHODS: In this multi-cohort study, we used data from two Finnish prospective cohort studies: the Health and Social Support study and the Finnish Public Sector study. Our pooled prospective primary analysis data comprised 109 246 Finnish adults aged 17-77 years at study entry. We captured socioeconomic status using area deprivation and education at baseline (1998-2013). Participants were followed up for health conditions diagnosed according to the WHO International Classification of Diseases until 2016 using linkage to national health records. We tested the generalisability of our findings with an independent UK cohort study-the Whitehall II study (9838 people, baseline in 1997, follow-up to 2017)-using a further socioeconomic status indicator, occupational position. FINDINGS: During 1 110 831 person-years at risk, we recorded 245 573 hospitalisations in the Finnish cohorts; the corresponding numbers in the UK study were 60 946 hospitalisations in 186 572 person-years. Across the three socioeconomic position indicators and after adjustment for lifestyle factors, compared with more advantaged groups, low socioeconomic status was associated with increased risk for 18 (32·1%) of the 56 conditions. 16 diseases formed a cascade of inter-related health conditions with a hazard ratio greater than 5. This sequence began with psychiatric disorders, substance abuse, and self-harm, which were associated with later liver and renal diseases, ischaemic heart disease, cerebral infarction, chronic obstructive bronchitis, lung cancer, and dementia. INTERPRETATION: Our findings highlight the importance of mental health and behavioural problems in setting in motion the development of a range of socioeconomically patterned physical illnesses. Policy and health-care practice addressing psychological health issues in social context and early in the life course could be effective strategies for reducing health inequalities. FUNDING: UK Medical Research Council, US National Institute on Aging, NordForsk, British Heart Foundation, Academy of Finland, and Helsinki Institute of Life Science.

Association between retirement and mortality: working longer, living longer? A systematic review and meta-analysis.

AIM: This study summarised available evidence on the association between early and on-time retirement, compared with continued working, and mortality. Moreover, this study investigated whether and to what extent gender, adjustment for demographics and prior health status influence this association. METHODS: A systematic literature search of longitudinal studies was conducted. A qualitative analysis of the included studies was performed, followed by a meta-regression analysis to assess the influence of gender, prior health and demographics. Random-effects models were used in a meta-analysis to estimate the pooled effects for relevant subgroups identified in the meta-regression. RESULTS: In total, 25 studies were included. Adjustment for prior health and demographics influenced the association between retirement and mortality (p<0.05). The results of the meta-analysis of 12 studies are presented for 'insufficiently adjusted' and 'fully adjusted' subgroups. There was no association between early retirement and mortality compared with working until retirement (fully adjusted subgroup: HR 1.05, 95% CI 0.87 to 1.28). On-time retirement was associated with a higher risk of mortality compared with working beyond retirement (insufficiently adjusted subgroup: HR 1.56, 95% CI 1.41 to 1.73). However, in the subgroup that adjusted for prior health, on-time retirement was not associated with mortality (HR 1.12, 95% CI 0.98 to 1.28). CONCLUSION: Early retirement was not associated with a higher risk of mortality. On-time retirement was associated with a higher risk of mortality, which might reflect the healthy worker effect. It is important to consider information on prior health and demographics when studying the association between retirement and mortality to avoid biased findings.

Socioeconomic Inequalities in Disability-free Life Expectancy in Older People from England and the United States: A Cross-national Population-Based Study.

BACKGROUND: We examined socioeconomic inequalities in disability-free life expectancy in older men and women from England and the United States and explored whether people in England can expect to live longer and healthier lives than those in the United States. METHODS: We used harmonized data from the Gateway to Global Aging Data on 14,803 individuals aged 50+ from the U.S. Health and Retirement Study (HRS) and 10,754 from the English Longitudinal Study of Ageing (ELSA). Disability was measured in terms of impaired activities and instrumental activities of daily living. We used discrete-time multistate life table models to estimate total life expectancy and life expectancy free of disability. RESULTS: Socioeconomic inequalities in disability-free life expectancy were of a similar magnitude (in absolute terms) in England and the United States. The socioeconomic disadvantage in disability-free life expectancy was largest for wealth, in both countries: people in the poorest group could expect to live seven to nine fewer years without disability than those in the richest group at the age of 50. CONCLUSIONS: Inequalities in healthy life expectancy exist in both countries and are of similar magnitude. In both countries, efforts in reducing health inequalities should target people from disadvantaged socioeconomic groups.

Socioeconomic differences in healthy and disease-free life expectancy between ages 50 and 75: a multi-cohort study.

BACKGROUND: There are striking socioeconomic differences in life expectancy, but less is known about inequalities in healthy life expectancy and disease-free life expectancy. We estimated socioeconomic differences in health expectancies in four studies in England, Finland, France and Sweden. METHODS: We estimated socioeconomic differences in health expectancies using data drawn from repeated waves of the four cohorts for two indicators: (i) self-rated health and (ii) chronic diseases (cardiovascular, cancer, respiratory and diabetes). Socioeconomic position was measured by occupational position. Multistate life table models were used to estimate healthy and chronic disease-free life expectancy from ages 50 to 75. RESULTS: In all cohorts, we found inequalities in healthy life expectancy according to socioeconomic position. In England, both women and men in the higher positions could expect 82-83% of their life between ages 50 and 75 to be in good health compared to 68% for those in lower positions. The figures were 75% compared to 47-50% for Finland; 85-87% compared to 77-79% for France and 80-83% compared to 72-75% for Sweden. Those in higher occupational positions could expect more years in good health (2.1-6.8 years) and without chronic diseases (0.5-2.3 years) from ages 50 to 75. CONCLUSION: There are inequalities in healthy life expectancy between ages 50 and 75 according to occupational position. These results suggest that reducing socioeconomic inequalities would make an important contribution to extending healthy life expectancy and disease-free life expectancy.

Neighborhood socioeconomic status and adherence to dietary recommendations among Finnish adults: A retrospective follow-up study.

Neighborhood socioeconomic status (SES) is associated with dietary habits among the residents, but few studies have examined this association separately among long-term residents and movers. We calculated cumulative neighborhood SES score weighted by residential time in each address over 6 years for non-movers (n = 7704) and movers (n = 8818) using national grid database. Increase in average neighborhood SES was associated with higher adherence to dietary recommendations in both groups. Among the movers, an upward trajectory from low to high neighborhood SES was also associated with better adherence. Our findings suggest high SES areas might offer healthier food environments than low SES areas.

Relationship transitions and change in health behavior: A four-phase, twelve-year longitudinal study.

RATIONALE: Extensive scientific evidence shows an association between involvement in social relationships and healthy lifestyle. Prospective studies with many participants and long follow-ups are needed to study the dynamics and change in social factors within individuals over time. OBJECTIVE: Our aim was to determine whether a change in relationship status (single, married, divorced, widow, cohabiting) is followed by a change in health behavior (smoking, alcohol consumption, physical activity, and body mass index). METHODS: We used data from 81,925 healthy adults participating in the prospective longitudinal Finnish Public Sector Study in the period 2000-2013. We analyzed 327,700 person-observations from four data collection phases. Missing data were multiply imputed. A within-individual methodology was used to minimize the possibility of selection effects affecting the interpretation. RESULTS: All four health behaviors showed associations with relationship status. The effects were very similar and in the same direction in women and men, although there were gender differences in the magnitudes of the effects. The end of a relationship was followed by a decrease in body mass index, increased odds of being a smoker, increase in physical activity, and increase in alcohol consumption (widowed men). The effects were reverse when forming a new relationship. CONCLUSION: A change in relationship status is associated with a change in health behavior. The association is not explained by socioeconomic status, subjective health status, or anxiety level. People leaving or losing a relationship are at increased risk of unhealthy behavior (smoking and alcohol consumption), but at the same time they have a lower BMI and show higher physical activity compared to the time they were in a relationship. It is not clear if the cumulative health effect of these health behavior changes is positive or negative.

Short Physical Performance Battery and all-cause mortality: systematic review and meta-analysis.

BACKGROUND: The Short Physical Performance Battery (SPPB) is a well-established tool to assess lower extremity physical performance status. Its predictive ability for all-cause mortality has been sparsely reported, but with conflicting results in different subsets of participants. The aim of this study was to perform a meta-analysis investigating the relationship between SPPB score and all-cause mortality. METHODS: Articles were searched in MEDLINE, the Cochrane Library, Google Scholar, and BioMed Central between July and September 2015 and updated in January 2016. Inclusion criteria were observational studies; >50 participants; stratification of population according to SPPB value; data on all-cause mortality; English language publications. Twenty-four articles were selected from available evidence. Data of interest (i.e., clinical characteristics, information after stratification of the sample into four SPPB groups [0-3, 4-6, 7-9, 10-12]) were retrieved from the articles and/or obtained by the study authors. The odds ratio (OR) and/or hazard ratio (HR) was obtained for all-cause mortality according to SPPB category (with SPPB scores 10-12 considered as reference) with adjustment for age, sex, and body mass index. RESULTS: Standardized data were obtained for 17 studies (n = 16,534, mean age 76 ± 3 years). As compared to SPPB scores 10-12, values of 0-3 (OR 3.25, 95%CI 2.86-3.79), 4-6 (OR 2.14, 95%CI 1.92-2.39), and 7-9 (OR 1.50, 95%CI 1.32-1.71) were each associated with an increased risk of all-cause mortality. The association between poor performance on SPPB and all-cause mortality remained highly consistent independent of follow-up length, subsets of participants, geographic area, and age of the population. Random effects meta-regression showed that OR for all-cause mortality with SPPB values 7-9 was higher in the younger population, diabetics, and men. CONCLUSIONS: An SPPB score lower than 10 is predictive of all-cause mortality. The systematic implementation of the SPPB in clinical practice settings may provide useful prognostic information about the risk of all-cause mortality. Moreover, the SPPB could be used as a surrogate endpoint of all-cause mortality in trials needing to quantify benefit and health improvements of specific treatments or rehabilitation programs. The study protocol was published on PROSPERO (CRD42015024916).

Change in Neighborhood Disadvantage and Change in Smoking Behaviors in Adults: A Longitudinal, Within-individual Study.

BACKGROUND: Evidence for an association between neighborhood disadvantage and smoking is mixed and mainly based on cross-sectional studies. To shed light on the causality of this association, we examined whether change in neighborhood socioeconomic disadvantage is associated with within-individual change in smoking behaviors. METHODS: The study population comprised participants of the Finnish Public Sector study who reported a change in their smoking behavior between surveys in 2008/2009 and 2012/2013. We linked participants' residential addresses to a total population database on neighborhood disadvantage with 250 × 250-m resolution. The outcome variables were changes in smoking status (being a smoker vs. not) as well as the intensity (heavy/moderate vs. light smoker). We used longitudinal case-crossover design, a method that accounts for time-invariant confounders by design. We adjusted models for time-varying covariates. RESULTS: Of the 3,443 participants, 1,714 quit, while 967 began to smoke between surveys. Smoking intensity increased among 398 and decreased among 364 participants. The level of neighborhood disadvantage changed for 1,078 participants because they moved residence. Increased disadvantage was associated with increased odds of being a smoker (odds ratio of taking up smoking 1.23 [95% confidence interval: 1.2, 1.5] per 1 SD increase in standardized national disadvantage score). Odds ratio for being a heavy/moderate (vs. light) smoker was 1.14 (95% confidence interval: 0.85, 1.52) when disadvantage increased by 1 SD. CONCLUSIONS: These within-individual results link an increase in neighborhood socioeconomic disadvantage, due to move in residence, with subsequent smoking behaviors.

Association of Self-Rated Health in Midlife With Mortality and Old Age Frailty: A 26-Year Follow-Up of Initially Healthy Men.

BACKGROUND: The aim was to investigate the relationship between self-rated health (SRH) in healthy midlife, mortality, and frailty in old age. METHODS: In 1974, male volunteers for a primary prevention trial in the Helsinki Businessmen Study (mean age 47 years, n = 1,753) reported SRH using a five-step scale (1 = "very good," n = 124; 2 = "fairly good," n = 862; 3 = "average," n = 706; 4 = "fairly poor," or 5 = "very poor"; in the analyses, 4 and 5 were combined as "poor", n = 61). In 2000 (mean age 73 years), the survivors were assessed using a questionnaire including the RAND-36/SF-36 health-related quality of life instrument. Simplified self-reported criteria were used to define phenotypic prefrailty and frailty. Mortality was retrieved from national registers. RESULTS: During the 26-year follow-up, 410 men had died. Frailty status was assessed in 81.0% (n = 1,088) of survivors: 434 (39.9%), 552 (50.7%), and 102 (9.4%) were classified as not frail, prefrail, and frail, respectively. With fairly good SRH as reference, and adjusted for cardiovascular risk in midlife and comorbidity in old age, midlife SRH was related to mortality in a J-shaped fashion: significant increase with both very good and poor SRH. In similar analyses, average SRH in midlife (n = 425) was related to prefrailty (odds ratio: 1.52, 95% confidence interval: 1.14-2.04) and poor SRH (n = 31) both to prefrailty (odds ratio: 3.56, 95% confidence interval: 1.16-10.9) and frailty (odds ratio: 8.38, 95% confidence interval: 2.32-30.3) in old age. CONCLUSIONS: SRH in clinically healthy midlife among volunteers of a primary prevention trial was related to the development of both prefrailty and frailty in old age, independent of baseline cardiovascular risk and later comorbidity.

Childhood Psychosocial Adversity and Adult Neighborhood Disadvantage as Predictors of Cardiovascular Disease: A Cohort Study.

BACKGROUND: Childhood adverse psychosocial factors (eg, parental divorce, long-term financial difficulties) and adult neighborhood disadvantage have both been linked to increased cardiovascular disease (CVD). However, their combined effects on disease risk are not known. METHODS AND RESULTS: Participants were 37 699 adults from the Finnish Public Sector study whose data were linked to a national neighborhood disadvantage grid with the use of residential addresses between the years 2000 and 2008 and who responded to a survey on childhood psychosocial adversities and adult CVD risk behaviors in 2008 to 2009. Survey data were also linked to national registers on hospitalization, mortality, and prescriptions to assess CVD risk factors in 2008 to 2009 and to ascertain incident CVD (coronary heart disease or cerebrovascular disease) between the survey and the end of December 2011 (mean follow-up, 2.94 years; SD=0.44 years). Combined exposure to high childhood adversity and high adult disadvantage was associated with CVD risk factors (hypertension, dyslipidemia, diabetes mellitus, obesity, smoking, heavy alcohol use, and physical inactivity) and with a 2.25-fold (95% confidence interval, 1.39-3.63) hazard of incident CVD compared with a low childhood adversity and low adult disadvantage. This hazard ratio was attenuated by 16.6% but remained statistically significant after adjustment for the CVD risk factors (1.96; 95% confidence interval, 1.22-3.16). Exposure to high childhood adversity or high adult neighborhood disadvantage alone was not significantly associated with CVD in fully adjusted models. CONCLUSIONS: These findings suggest that individuals with both childhood psychosocial adversity and adult neighborhood disadvantage are at an increased risk of CVD. In contrast, those with only 1 of these exposures have little or no excess risk after controlling for conventional risk factors.

Clinical and laboratory characteristics of active and healthy aging (AHA) in octogenarian men.

OBJECTIVES: To investigate clinical and laboratory variables associated with good subjective and objective health ("active and healthy aging", AHA) in a cohort of octogenarian men. DESIGN: Cross-sectional analyses of a longitudinal study. SETTING: The Helsinki Businessmen Study in Finland. PARTICIPANTS: A socioeconomically homogenous cohort of men (baseline n = 3293), born in 1919-1934, has been followed up from the 1960s. From 2000, the men have been regularly sent mailed questionnaires and mortality has been retrieved from national registers. MEASUREMENTS: In 2010 survey, AHA was defined as independently responding to the mailed survey, feeling happy without cognitive or functional impairments and without major diseases. In 2010/11, a random subgroup men was clinically investigated and survivors with healthy and nonhealthy aging were compared. RESULTS: By 2010, 1788 men of the baseline cohort had died, and 894 men responded to the mailed survey. 154 (17.2 %) of those fulfilled the present AHA criteria. Increasing number of criteria were negatively (P < 0.001) related to short-term mortality. In 2011, a random sample of 458 men were clinically investigated, 90 of them with AHA. Men with AHA had higher serum LDL cholesterol and diastolic blood pressure (partially explained by less frequent drug use) but no significant difference was observed in other risk factors. Men with AHA had significantly faster walking speed (P < 0.001), stronger handgrip (P = 0.017), better self-rated health and less phenotypic frailty (P = 0.02). CONCLUSION: Less than 5 % enjoyed active and healthy aging over their life course, which was significantly related to markers of frailty but not to the traditional vascular risk factors.