Time and place: putting individual health into context. A multilevel analysis of the British household panel survey, 1991–2001

Associations between Socio-Economic Status and Unfavorable Social Indicators of Child Wellbeing; a Neighbourhood Level Data Design

Background: Living in deprivation is related to ill health. Differences in health outcomes between neighbourhoods may be attributed to neighbourhood socio-economic status (SES). Additional to differences in health, neighbourhood differences in child wellbeing could also be attributed to neighbourhood SES. Therefore, we aimed to investigate the association between neighbourhood deprivation, and social indicators of child wellbeing. Methods: Aggregated data from 3565 neighbourhoods in 390 municipalities in the Netherlands were eligible for analysis. Neighbourhood SES scores and neighbourhood data on social indicators of child wellbeing were used to perform repeated measurements, with one year measurement intervals, over a period of 11 years. Linear mixed models were used to estimate the associations between SES score and the proportion of unfavorable social indicators of child wellbeing. Results: After adjustment for year, population size, and clustering within neighbourhoods and within a municipality, neighbourhood SES was inversely associated with the proportion of ‘children living in families on welfare’ (estimates with two cubic splines: −3.59 [CI: −3.99; −3.19], and −3.00 [CI: −3.33; −2.67]), ‘delinquent youth’ (estimate −0.26 [CI: −0.30; −0.23]) and ‘unemployed youth’ (estimates with four cubic splines: −0.41 [CI: −0.57; −0.25], −0.58 [CI: −0.73; −0.43], −1.35 [−1.70; −1.01], and −0.96 [1.24; −0.70]). Conclusions: In this study using repeated measurements, a lower neighbourhood SES was significantly associated with a higher prevalence of unfavorable social indicators of child wellbeing. This contributes to the body of evidence that neighbourhood SES is strongly related to child health and a child’s ability to reach its full potential in later life. Future studies should consist of larger longitudinal datasets, potentially across countries, and should attempt to take the interpersonal variation into account with more individual-level data on SES and outcomes.

Development of reserves over the life course and onset of vulnerability in later life

This Review develops a theoretical framework for the development and onset of vulnerability in later life based on the concept of reserves. We stress the advantages of using the concept of reserves in interdisciplinary life-course studies, compared with related concepts such as resources and capital. We enrich the definition of vulnerability as a lack of reserves and a reduced capacity of an individual to restore reserves. Two dimensions of reserves, originating from lifespan psychology and gerontology, are of particular importance: their constitution and sustainability by behaviours and interaction with the environment (the 'use it or lose it' paradigm) and the presence of thresholds, below which functioning becomes highly challenging. This heuristic approach reveals the potential for a conceptualization of reserves and is exemplified in an empirical illustration. Further interdisciplinary research based on the concept is needed.

Comparison of Methods for Estimating Prevalence of Chronic Diseases and Health Behaviors for Small Geographic Areas: Boston Validation Study, 2013

Introduction

Local health authorities need small-area estimates for prevalence of chronic diseases and health behaviors for multiple purposes. We generated city-level and census-tract–level prevalence estimates of 27 measures for the 500 largest US cities.

Methods

To validate the methodology, we constructed multilevel logistic regressions to predict 10 selected health indicators among adults aged 18 years or older by using 2013 Behavioral Risk Factor Surveillance System (BRFSS) data; we applied their predicted probabilities to census population data to generate city-level, neighborhood-level, and zip-code–level estimates for the city of Boston, Massachusetts.

Results

By comparing the predicted estimates with their corresponding direct estimates from a locally administered survey (Boston BRFSS 2010 and 2013), we found that our model-based estimates for most of the selected health indicators at the city level were close to the direct estimates from the local survey. We also found strong correlation between the model-based estimates and direct survey estimates at neighborhood and zip code levels for most indicators.

Conclusion

Findings suggest that our model-based estimates are reliable and valid at the city level for certain health outcomes. Local health authorities can use the neighborhood-level estimates if high quality local health survey data are not otherwise available.

Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China

BACKGROUND

Robust malaria vector surveillance is essential for optimally selecting and targeting vector control measures. Sixty-two vector surveillance sites were established between 2005 and 2008 by the national malaria surveillance program in China to measure Anopheles sinensis human biting rates. Using these data to determine the primary ecological drivers of malaria vector human biting rates in malaria epidemic-prone regions of China will allow better targeting of vector control resources in space and time as the country aims to eliminate malaria.

METHODS

We analyzed data from 62 malaria surveillance sentinel sites from 2005 to 2008. Linear mixed effects models were used to identify the primary ecological drivers for Anopheles sinensis human biting rates as well as to explore the spatial-temporal variation of relevant factors at surveillance sites throughout China.

RESULTS

Minimum semimonthly temperature (β = 2.99; 95% confidence interval (CI) 2.07- 3.92), enhanced vegetation index (β =1.07; 95% CI 0.11-2.03), and paddy index (the percentage of rice paddy field in the total cultivated land area of each site) (β = 0.86; 95% CI 0.17-1.56) were associated with greater An. Sinensis human biting rates, while increasing distance to the nearest river was associated with lower An. Sinensis human biting rates (β = -1.47; 95% CI -2.88, -0.06). The temporal variation (σ(s0)(2) = 0.83) in biting rates was much larger than the spatial variation (σ(t)(2) = 1.35), with 19.3% of temporal variation attributable to differences in minimum temperature and enhanced vegetation index and 16.9% of spatial variance due to distance to the nearest river and the paddy index.

DISCUSSION

Substantial spatial-temporal variation in An. Sinensis human biting rates exists in malaria epidemic-prone regions of China, with minimum temperature and enhanced vegetation index accounting for the greatest proportion of temporal variation and distance to nearest river and paddy index accounting for the greatest proportion of spatial variation amongst observed ecological drivers.

CONCLUSIONS

Targeted vector control measures based on these findings can support the ongoing malaria elimination efforts in China more effectively.

A multilevel model for comorbid outcomes: obesity and diabetes in the US

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Neighborhood context and infant birthweight among recent immigrant mothers: a multilevel analysis

OBJECTIVES

We compared the influence of the residential environment and maternal country of origin on birthweight and low birthweight of infants born to recent immigrants to urban Ontario.

METHODS

We linked delivery records (1993-2000) to an immigration database (1993-1995) and small-area census data (1996). The data were analyzed with cross-classified random-effects models and standard multilevel methods. Higher-level predictors included 4 independent measures of neighborhood context constructed by factor analysis and maternal world regions of origin.

RESULTS

Births (N = 22 189) were distributed across 1396 census tracts and 155 countries of origin. The associations between neighborhood indices and birthweight disappeared after we controlled for the maternal country of origin in a cross-classified multilevel model. Significant associations between world regions and birthweight and low birthweight persisted after we controlled for neighborhood context and individual characteristics.

CONCLUSIONS

The residential environment has little, if any, influence on birthweight among recent immigrants to Ontario. Country of origin appears to be a much more important factor in low birthweight among children of recent immigrants than current neighborhood. Findings of neighborhood influences among recent immigrants should be interpreted with caution.

Social risks for disabling pain in older people: a prospective study of individual and area characteristics

Pain is common in adult life, and the extent to which pain interferes with daily activities rises with age. Little is known about the social factors associated with disabling pain. The objective was to determine the individual and neighbourhood social factors that predict pain that interferes with daily activities. This was a prospective cohort study set within the North Staffordshire Osteoarthritis Project (NorStOP). People aged 50 and over registered with six general practices were sent baseline and 3-year questionnaires. Individual predictors of the onset of pain interference were determined through multilevel modelling. Neighbourhood impact was examined using measures of deprivation taken from the UK Index of Multiple Deprivation 2004. 19% of the 3644 people without pain interference at baseline reported it at follow-up. Baseline social factors were weaker predictors than baseline age, multiple-site pain and anxiety or depression. However, perceived financial strain was a significant predictor (OR 1.5; 95% CI: 1.2, 1.8). Onset of pain interference varied by local area deprivation status. Those living in areas of high health deprivation had an increased risk of developing pain interference (OR 1.6; 95% CI: 1.1, 2.3). Whilst the onset of pain which disrupts daily life is influenced mainly by the characteristics of the pain and by the psychological factors, there are links with the social factors, particularly individual measures of perceived income adequacy. The onset of disabling pain is also influenced by the place where one lives. Policies to prevent disabling pain need to consider the contribution of neighbourhood deprivation and income inequalities to the extent of the problem.