Dataset Information

Bayesian smoothed small-areas analysis of urban inequalities in fertility across 1999-2013.

ABSTRACT: Background:Since the 2008 economic crisis in Spain, overall fertility has continued to decrease, while urban inequalities have increased. There is a general lack of studies of fertility patterns in small-areas of Spanish cities. We explored the effects of the economic crisis on fertility during three time periods in urban settings in Spain. Methods:We studied the distribution of fertility rates among women (15-49?years) from Spain and low-middle income countries (LIC) who were living in 13 Spanish cities. We mapped fertility and the MEDEA socioeconomic deprivation index in small-areas, and analyzed age-related trends in fertility rates. We performed an ecological regression analysis of fertility and the deprivation index in two pre-crisis periods (1999-2003 and 2004-2008) and one crisis period (2009-2013). Fertility rates were calculated and smoothed using the hierarchical Bayesian model (BYM). Results:Higher fertility was generally associated with socioeconomic deprivation, with adjustment for the mothers' age and nationality. While Spanish citizens tended to delay childbearing throughout the three study periods, fertility increased among Spanish adolescents from deprived urban areas during the economic crisis. There was a general decline in fertility among immigrants after the crisis, especially in southern cities. Overall, fertility appeared to be stable, with higher fertility in more deprived areas. Conclusion:Increased unemployment and changes to government family policies may have contributed to delayed childbearing in Spain. For immigrants, more restrictive immigration policies may have played a crucial role in decreasing fertility rates. Reforming such policies will be key for better reproductive rights and improved fertility rates across all population cohorts in Spain.

SUBMITTER: Leon-Gomez BB

PROVIDER: S-EPMC6925428 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bayesian smoothed small-areas analysis of urban inequalities in fertility across 1999-2013.

León-Gómez Brenda Biaani BB Gotsens Mercè M Marí-Dell'Olmo Marc M Domínguez-Berjón Ma Felicitas MF Luque-Fernandez Miguel Ángel MÁ Martin Unai U Rodríguez-Sanz Maica M Pérez Gloria G

Fertility research and practice 20191221

<h4>Background</h4>Since the 2008 economic crisis in Spain, overall fertility has continued to decrease, while urban inequalities have increased. There is a general lack of studies of fertility patterns in small-areas of Spanish cities. We explored the effects of the economic crisis on fertility during three time periods in urban settings in Spain.<h4>Methods</h4>We studied the distribution of fertility rates among women (15-49 years) from Spain and low-middle income countries (LIC) who were liv ...[more]

PMID: 31890237

Similar Datasets

Project description:BackgroundMost epidemiological risk indicators strongly depend on the age composition of populations, which makes the direct comparison of raw (unstandardized) indicators misleading because of the different age structures of the spatial units of study. Age-standardized rates (ASR) are a common solution for overcoming this confusing effect. The main drawback of ASRs is that they depend on age-specific rates which, when working with small areas, are often based on very few, or no, observed cases for most age groups. A similar effect occurs with life expectancy at birth and many more epidemiological indicators, which makes standardized mortality ratios (SMR) the omnipresent risk indicator for small areas epidemiologic studies.MethodsTo deal with this issue, a multivariate smoothing model, the M-model, is proposed in order to fit the age-specific probabilities of death (PoDs) for each spatial unit, which assumes dependence between closer age groups and spatial units. This age-space dependence structure enables information to be transferred between neighboring consecutive age groups and neighboring areas, at the same time, providing more reliable age-specific PoDs estimates.ResultsThree case studies are presented to illustrate the wide range of applications that smoothed age specific PoDs have in practice . The first case study shows the application of the model to a geographical study of lung cancer mortality in women. This study illustrates the convenience of considering age-space interactions in geographical studies and to explore the different spatial risk patterns shown by the different age groups. Second, the model is also applied to the study of ischaemic heart disease mortality in women in two cities at the census tract level. Smoothed age-standardized rates are derived and compared for the census tracts of both cities, illustrating some advantages of this mortality indicator over traditional SMRs. In the latest case study, the model is applied to estimate smoothed life expectancy (LE), which is the most widely used synthetic indicator for characterizing overall mortality differences when (not so small) spatial units are considered.ConclusionOur age-space model is an appropriate and flexible proposal that provides more reliable estimates of the probabilities of death, which allow the calculation of enhanced epidemiological indicators (smoothed ASR, smoothed LE), thus providing alternatives to traditional SMR-based studies of small areas.

Project description:To examine HMG-CoA reductase inhibitor (statin) drug dispensing patterns to Nova Scotia Seniors' Pharmacare program (NSSPP) beneficiaries over a 14-year period in response to: 1) rosuvastatin market entry in 2003, 2) JUPITER trial publication in 2008, and 3) generic atorvastatin availability in 2010.All NSSPP beneficiaries who redeemed at least one prescription for a statin from April 1, 1999 to March 31, 2013 were included. Aggregated, anonymous monthly prescription counts were extracted by the Nova Scotia Department of Health and Wellness (Nova Scotia, Canada) and changes in dispensing patterns of statins were measured. Data were analyzed using descriptive analyses and interrupted time series methods.The percentage of NSSPP beneficiaries dispensed any statin increased from 5.3% in April 1999 to 20.7% in March 2013. In 1999, most NSSPP beneficiaries were dispensed either simvastatin (29.5%) or atorvastatin (28.7%). When rosuvastatin was added to the NSSPP Formulary in August 2003, prescriptions dispensed for simvastatin, lovastatin, pravastatin, and fluvastatin declined significantly (slope change, -0.0027; 95% confidence interval (CI), (-0.0046, -0.0009)). This significant decline continued following the publication of JUPITER (level change, -0.1974; 95% CI, (-0.2991, -0.0957)) and the availability of generic atorvastatin (level change, -0.2436; 95% CI, (-0.3314, -0.1558)). Atorvastatin was not significantly affected by any of the three interventions, although it maintained an overall decreasing trend. Only upon the availability of generic atorvastatin did the upward trend in rosuvastatin use decrease significantly (slope change, -0.0010, 95% CI, (-0.0015, -0.0005)).The type and rate of statins dispensed to NSSPP beneficiaries changed from 1999 to 2013 in response to the availability of new agents and publication of the JUPITER trial. The overall proportion of NSSPP beneficiaries dispensed a statin increased approximately 4-fold during the study period. In 2013, rosuvastatin was the most commonly dispensed statin (44.1%) followed by atorvastatin (39.1%).

Project description:ObjectiveSignificant inequalities in access to healthcare system exist between residents of world megacities, even if they have different healthcare systems. The aim of this study was to estimate avoidable hospitalisations in the metropolitan area of Milan (Italy) and explore inequalities in access to healthcare between patients and across their areas of residence.DesignRetrospective observational study.SettingPublic and accredited private hospitals in the metropolitan area of Milan. Data obtained from the hospital discharge database of the Italian Health Ministry.Participants472 579 patients hospitalised for ambulatory care sensitive conditions and resident in the metropolitan area of Milan from 2005 to 2016.Outcome measureAge-adjusted rates of avoidable hospitalisations; OR for hospital admissions with ambulatory care sensitive conditions.MethodsAge-adjusted rates of avoidable hospitalisations in the metropolitan area of Milan were estimated from 2005 to 2016 using direct standardisation. For the hospitalised population, multilevel logistic regression model with patient random effects was used to identify patients, hospitals and municipalities' characteristics associated with risk of avoidable hospitalisation in the period 2012-2016.ResultsThe rate of avoidable hospitalisation in Milan fell steadily between 2005 and 2016 from 16.6 to 10.5 per 1000. Among the hospitalised population, the odds of being hospitalised with an ambulatory care sensitive condition was higher for male (OR 1.42, 95% CI 1.36 to 1.48), older (OR 1.012, 95% CI 1.01 to 1.014), low-educated (elementary school vs degree OR 4.23, 95% CI 3.72 to 4.81) and single (vs married OR 2.08, 95% CI 2.01 to 2.16) patients with comorbidities (OR 1.47, 95% CI 1.38 to 1.56); avoidable admissions were more frequent in public non-teaching hospitals while municipality's characteristics did not appear to be correlated with hospitalisation for ambulatory care sensitive conditions.ConclusionsThe health system in metropolitan Milan has experienced a reduction in avoidable hospitalisations between 2005 and 2016, quite homogeneously across its 134 municipalities. The study design allowed to explore inequalities among the hospitalised population for which we found specific sociodemographic disadvantages.

Project description:BackgroundSmall-area studies of health inequalities often have an urban focus, and may be limited in their translatability to non-urban settings. Using small-area units representing communities, this study assessed the influence of living in different settlement types (urban, town and rural) on the prevalence of four chronic diseases (heart disease, cancer, diabetes and stroke) and compared the degrees of associations with individual-level and community-level factors among the settlement types.MethodsThe associations between community-level and individual-level characteristics and prevalence of the chronic diseases were assessed using logistic regression (multilevel and non-multilevel) models. Individual-level data were extracted from the Canadian Community Health Survey (2007-2011). Indices of material deprivation and social isolation and the settlement type classification were created using the Canadian Census.ResultsRespondents living in towns were 21% more likely to report one of the diseases than respondents living in urban communities even after accounting for individual-level and community-level characteristics. Having dependent children appeared to have protective effects in towns, especially for males (OR: 0.49 (95% CI 0.27 to 0.90)). Unemployment had a strong association for all types of communities, but being unemployed appeared to be particularly damaging to health of males in urban communities (OR: 2.48 (95% CI 1.43 to 4.30)).ConclusionsThe study showed that those living in non-urban settings, particularly towns, experience extra challenges in maintaining health above and beyond the socioeconomic condition and social isolation of the communities, and individual demographic, behavioural and socioeconomic attributes. Our findings also suggest that health inequality studies based on urban-only settings may underestimate the risks by some factors. Ways to devise meaningful small-area units comparable in all settlement types are necessary to help plan effective provision of chronic disease-related health services and programmes on a regional scale.

Dataset Information

Bayesian smoothed small-areas analysis of urban inequalities in fertility across 1999-2013.

Publications

Bayesian smoothed small-areas analysis of urban inequalities in fertility across 1999-2013.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets