Unit for Social Epidemiology, Faculty of Medicine, Lund University, CRC, Jan Waldeströms gata, 35, S-205 02, Malmö, Sweden. sten.axelsson_fisk@med.lu.se.
While psychosocial theory claims that socioeconomic status (SES), acting through social comparisons, has an important influence on susceptibility to disease, materialistic theory says that socioeconomic position (SEP) and related access to material resources matter more. However, the relative role of SEP versus SES in chronic obstructive pulmonary disease (COPD) risk has still not been examined.
We investigated the association between SES/SEP and COPD risk among 667 094 older adults, aged 55 to 60, residing in Sweden between 2006 and 2011. Absolute income in five groups by population quintiles depicted SEP and relative income expressed as quintile groups within each absolute income group represented SES. We performed sex-stratified logistic regression models to estimate odds ratios and the area under the receiver operator curve (AUC) to compare the discriminatory accuracy of SES and SEP in relation to COPD.
Even though both absolute (SEP) and relative income (SES) were associated with COPD risk, only absolute income (SEP) presented a clear gradient, so the poorest had a three-fold higher COPD risk than the richest individuals. While the AUC for a model including only age was 0.54 and 0.55 when including relative income (SES), it increased to 0.65 when accounting for absolute income (SEP). SEP rather than SES demonstrated a consistent association with COPD.
Our study supports the materialistic theory. Access to material resources seems more relevant to COPD risk than the consequences of low relative income.
Notes
Cites: COPD. 2014 Aug;11(4):431-7 PMID 24568315
Cites: Am J Respir Crit Care Med. 2001 Apr;163(5):1256-76 PMID 11316667
Cites: Int J Epidemiol. 2006 Jun;35(3):633-43 PMID 16452106
Cites: Lakartidningen. 2007 Mar 28-Apr 3;104(13):1028-31 PMID 17476903
Cites: Lancet. 1991 Jun 8;337(8754):1387-93 PMID 1674771
Cites: Am J Public Health. 2003 Apr;93(4):652-7 PMID 12660213
Cites: BMC Pulm Med. 2011 Jun 14;11:36 PMID 21672193
The burden of celiac disease (CD) is increasingly recognized as a global problem. However, whether this situation depends on genetics or environmental factors is uncertain. The authors examined these aspects in Sweden, a country in which the risk of CD is generally considered to be high. If environmental factors are relevant, CD risk in second-generation immigrant children should be related to maternal length of stay in Sweden before delivery.
Linking the Swedish Medical Birth Registry to other national registries, the authors investigated all singleton children (n = 792,401) born in Sweden between 1987 and 1993. They studied the risk of CD in children before age 6 as a function of the mother's geographical region of birth and length of stay in Sweden before delivery using Cox regression models.
In children whose mothers immigrated to Sweden from a country outside of Europe, a maternal length of stay in Sweden of more than 5 years increased the hazard ratio (HR) of CD (1.73, 95% confidence interval (CI) 1.06-2.81). The authors observed a similar result among children born to mothers from a Nordic country outside of Sweden (HR 1.57, 95% CI 0.89-2.75), but a non-conclusive protective effect was observed in second-generation immigrant children from a non-Nordic European country (HR 0.65, 95% CI 0.39-1.09).
The risk of CD among second-generation immigrants seems to be conditioned by maternal length of stay in Sweden before delivery, suggesting that environmental factors contribute to the variation in CD risk observed across populations.
Mental health problems among adolescents have become a major public health issue, and it is therefore important to increase knowledge on the contextual determinants of adolescent mental health. One such determinant is the socioeconomic structure of the neighbourhood. The present study has two central objectives, (i) to examine if neighbourhood socioeconomic deprivation is associated to individual variations in utilisation of psychiatric care in a Swedish context, and (ii) to investigate if neighbourhood boundaries are a valid construct for identifying contexts that influence individual variations in psychiatric care utilization. Data were obtained from the Longitudinal Multilevel Analysis in Scania (LOMAS) database. The study population consists of all boys and girls aged 13-18 years (N=18,417), who were living in the city of Malmö, Sweden, in 2005. Multilevel logistic regression analysis was applied to estimate the probability of psychiatric care utilisation. The results from the study indicate that the neighbourhood of residence had little influence on psychiatric care utilisation. Although we initially found a variation between neighbourhoods, this general contextual effect was very small (i.e. 1.6%). The initial conclusive association between the neighbourhood level of disadvantage and psychiatric care utilisation (specific contextual effect) disappeared following adjustment for individual and family level variables. Our results suggest the neighbourhoods in Malmö (at least measured in terms of SAMS-areas), do not provide accurate information for discriminating adolescents utilisation of psychiatric care. The SAMS-areas appears to be an inappropriate construct of the social environment that influences adolescent utilisation of psychiatric care. Therefore, public health interventions should be directed to the whole city rather than to specific neighbourhoods. However, since geographical, social or cultural contexts may be important for our understanding of adolescent mental health further research is needed to identify such contexts.
Notes
Cites: J Epidemiol Community Health. 2009 Dec;63(12):1043-819666637
Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that distinguishes between "specific" (measures of association) and "general" (measures of variance) contextual effects. Performing two empirical examples we illustrate the methodology, interpret the results and discuss the implications of this kind of analysis in public health.
We analyse 43,291 individuals residing in 218 neighbourhoods in the city of Malmö, Sweden in 2006. We study two individual outcomes (psychotropic drug use and choice of private vs. public general practitioner, GP) for which the relative importance of neighbourhood as a source of individual variation differs substantially. In Step 1 of the analysis, we evaluate the OR and the area under the receiver operating characteristic (AUC) curve for individual-level covariates (i.e., age, sex and individual low income). In Step 2, we assess general contextual effects using the AUC. Finally, in Step 3 the OR for a specific neighbourhood characteristic (i.e., neighbourhood income) is interpreted jointly with the proportional change in variance (i.e., PCV) and the proportion of ORs in the opposite direction (POOR) statistics.
For both outcomes, information on individual characteristics (Step 1) provide a low discriminatory accuracy (AUC = 0.616 for psychotropic drugs; = 0.600 for choosing a private GP). Accounting for neighbourhood of residence (Step 2) only improved the AUC for choosing a private GP (+0.295 units). High neighbourhood income (Step 3) was strongly associated to choosing a private GP (OR = 3.50) but the PCV was only 11% and the POOR 33%.
Applying an innovative stepwise multilevel analysis, we observed that, in Malmö, the neighbourhood context per se had a negligible influence on individual use of psychotropic drugs, but appears to strongly condition individual choice of a private GP. However, the latter was only modestly explained by the socioeconomic circumstances of the neighbourhoods. Our analyses are based on real data and provide useful information for understanding neighbourhood level influences in general and on individual use of psychotropic drugs and choice of GP in particular. However, our primary aim is to illustrate how to perform and interpret a multilevel analysis of individual heterogeneity in social epidemiology and public health. Our study shows that neighbourhood "effects" are not properly quantified by reporting differences between neighbourhood averages but rather by measuring the share of the individual heterogeneity that exists at the neighbourhood level.
Notes
Cites: Behav Res Methods. 2012 Dec;44(4):1191-622477439
The concept of social capital has gained wide interest in public health research in recent years. However, we suggest a concept that was introduced and developed by Fukuyama, named "miniaturization of community", as an alternative to that of social capital. The concept of miniaturization of community emphasizes that a high level of social participation can be accompanied by a low level of trust, both at the individual and at the community level, which may in turn result in social disorder and lack of social cohesion. When society becomes more disordered, people may tend to feel more insecure and anxious. Use of anxiolytic-hypnotic drugs (AHDs) could under such circumstances be a coping strategy. In this study, we first wanted to investigate whether the contextual component of the miniaturization of community concept (i.e. area high social participation and low trust) is associated with individual AHD use, over and above individual characteristics. Secondly, we aimed to study whether people living in the same municipality share a similar probability of AHD use, after adjusting for individual characteristics, and if so, how large this contextual phenomenon is. We used data on 20,319 women and 17,850 men aged 18-79 years from 58 municipalities in six regions in central Sweden, who participated in the Life & Health year 2000 postal survey. We applied multilevel logistic regression analysis with individuals at the first level and areas at the second level. Our results suggest that living in an area with a high level of miniaturization of community seems to be associated with individual AHD use, beyond people's individual characteristics including their own level of social participation and trust. The concept of miniaturization of community may be an extension of the classic concept of social capital and may increase our understanding of contextual effects on health.
Applying measures of discriminatory accuracy to revisit traditional risk factors for being small for gestational age in Sweden: a national cross-sectional study.
Small for gestational age (SGA) is considered as an indicator of intrauterine growth restriction, and multiple maternal and newborn characteristics have been identified as risk factors for SGA. This knowledge is mainly based on measures of average association (ie, OR) that quantify differences in average risk between exposed and unexposed groups. Nevertheless, average associations do not assess the discriminatory accuracy of the risk factors (ie, its ability to discriminate the babies who will develop SGA from those that will not). Therefore, applying measures of discriminatory accuracy rather than measures of association only, our study revisits known risk factors of SGA and discusses their role from a public health perspective.
Cross-sectional study. We measured maternal (ie, smoking, hypertension, age, marital status, education) and delivery (ie, sex, gestational age, birth order) characteristics and performed logistic regression models to estimate both ORs and measures of discriminatory accuracy, like the area under the receiver operating characteristic curve (AU-ROC) and the net reclassification improvement.
Data were obtained from the Swedish Medical Birth Registry.
Our sample included 731 989 babies born during 1987-1993.
We replicated the expected associations. For instance, smoking (OR=2.57), having had a previous SGA baby (OR=5.48) and hypertension (OR=4.02) were strongly associated with SGA. However, they show a very small discriminatory accuracy (AU-ROC˜0.5). The discriminatory accuracy increased, but remained unsatisfactorily low (AU-ROC=0.6), when including all variables studied in the same model.
Traditional risk factors for SGA alone or in combination have a low accuracy for discriminating babies with SGA from those without SGA. A proper understanding of these findings is of fundamental relevance to address future research and to design policymaking recommendations in a more informed way.
In the present study, we used a multilevel approach to investigate the role of maternal country of birth (MCOB) in predicting adolescent use of psychotropic medication in Sweden.
Using the Swedish Medical Birth Register we identified all 428,314 adolescents born between 1987 and 1990 and who were residing in Sweden in the year they turned 18. We applied multilevel logistic regression analysis with adolescents (level 1) nested within MCOBs (level 2). Measures of association (odds ratio) and measures of variance (intra-class correlation (ICC)) were calculated, as well as the discriminatory accuracy by calculating the area under the Receiver Operator Characteristic (AU-ROC) curve.
In comparison with adolescents with Swedish-born mothers, adolescents with mothers born in upper-middle, lower-middle and low-income countries were less likely to use psychotropic medication. However, the variance between MCOBs was small (ICC = 2.5 in the final model) relative to the variation within MCOBs. This was confirmed by an AU-ROC value of 0.598.
Even though we found associations between MCOB and adolescent use of psychotropic medication, the small ICC and AU-ROC indicate that MCOB appears to be an inaccurate context for discriminating adolescent use of psychotropic medication in Sweden.
In the present study, we used a multilevel approach to investigate the role of maternal country of birth (MCOB) in predicting adolescent use of psychotropic medication in Sweden.
Using the Swedish Medical Birth Register we identified all 428,314 adolescents born between 1987 and 1990 and who were residing in Sweden in the year they turned 18. We applied multilevel logistic regression analysis with adolescents (level 1) nested within MCOBs (level 2). Measures of association (odds ratio) and measures of variance (intra-class correlation (ICC)) were calculated, as well as the discriminatory accuracy by calculating the area under the Receiver Operator Characteristic (AU-ROC) curve.
In comparison with adolescents with Swedish-born mothers, adolescents with mothers born in upper-middle, lower-middle and low-income countries were less likely to use psychotropic medication. However, the variance between MCOBs was small (ICC = 2.5 in the final model) relative to the variation within MCOBs. This was confirmed by an AU-ROC value of 0.598.
Even though we found associations between MCOB and adolescent use of psychotropic medication, the small ICC and AU-ROC indicate that MCOB appears to be an inaccurate context for discriminating adolescent use of psychotropic medication in Sweden.
The logistic regression model is frequently used in epidemiologic studies, yielding odds ratio or relative risk interpretations. Inspired by the theory of linear normal models, the logistic regression model has been extended to allow for correlated responses by introducing random effects. However, the model does not inherit the interpretational features of the normal model. In this paper, the authors argue that the existing measures are unsatisfactory (and some of them are even improper) when quantifying results from multilevel logistic regression analyses. The authors suggest a measure of heterogeneity, the median odds ratio, that quantifies cluster heterogeneity and facilitates a direct comparison between covariate effects and the magnitude of heterogeneity in terms of well-known odds ratios. Quantifying cluster-level covariates in a meaningful way is a challenge in multilevel logistic regression. For this purpose, the authors propose an odds ratio measure, the interval odds ratio, that takes these difficulties into account. The authors demonstrate the two measures by investigating heterogeneity between neighborhoods and effects of neighborhood-level covariates in two examples--public physician visits and ischemic heart disease hospitalizations--using 1999 data on 11,312 men aged 45-85 years in Malmo, Sweden.
Area-aggregated assessments of perceived environmental attributes may overcome single-source bias in studies of green environments and health: results from a cross-sectional survey in southern Sweden.
Most studies assessing health effects of neighborhood characteristics either use self-reports or objective assessments of the environment, the latter often based on Geographical Information Systems (GIS). While objective measures require detailed landscape data, self-assessments may yield confounded results. In this study we demonstrate how self-assessments of green neighborhood environments aggregated to narrow area units may serve as an appealing compromise between objective measures and individual self-assessments.
The study uses cross-sectional data (N = 24,847) from a public health survey conducted in the county of Scania, southern Sweden, in 2008 and validates the Scania Green Score (SGS), a new index comprising five self-reported green neighborhood qualities (Culture, Lush, Serene, Spacious and Wild). The same qualities were also assessed objectively using landscape data and GIS. A multilevel (ecometric) model was used to aggregate individual self-reports to assessments of perceived green environmental attributes for areas of 1,000 square meters. We assessed convergent and concurrent validity for self-assessments of the five items separately and for the sum score, individually and area-aggregated.
Correlations between the index scores based on self-assessments and the corresponding objective assessments were clearly present, indicating convergent validity, but the agreement was low. The correlation was even more evident for the area-aggregated SGS. All three scores (individual SGS, area-aggregated SGS and GIS index score) were associated with neighborhood satisfaction, indicating concurrent validity. However, while individual SGS was associated with vitality, this association was not present for aggregated SGS and the GIS-index score, suggesting confounding (single-source bias) when individual SGS was used.
Perceived and objectively assessed qualities of the green neighborhood environment correlate but do not agree. An index score based on self-reports but aggregated to narrow area units can be a valid approach to assess perceived green neighborhood qualities in settings where objective assessments are not possible or feasible.
Notes
Cites: Occup Environ Med. 1997 Jan;54(1):44-89072033
Cites: Environ Health. 2004 Mar 31;3(1):315056391
Cites: Am J Prev Med. 2005 Feb;28(2 Suppl 2):126-3315694520
Cites: Scand J Work Environ Health. 2005 Jun;31(3):184-9015999570
Cites: J Epidemiol Community Health. 2006 Jul;60(7):587-9216790830
Cites: BMC Public Health. 2006;6:14916759375
Cites: Int J Epidemiol. 2006 Oct;35(5):1361-317008359
Cites: Am J Epidemiol. 2007 Apr 15;165(8):858-6717329713
Cites: Health Place. 2007 Dec;13(4):839-5017392016
Cites: Int Arch Occup Environ Health. 2007 Nov;81(2):179-9117541626
Cites: J Epidemiol Community Health. 2007 Dec;61(12):1042-918000125
Cites: Am J Epidemiol. 2000 Jul 1;152(1):75-8310901332
Cites: J Epidemiol Community Health. 2003 Aug;57(8):550-212883048
