The interactions between municipal socioeconomic status and age on hip fracture risk.

SUMMARY: Age modifies the effect of area-level socioeconomic status (SES) in the risk of fragility hip fractures (HF). For older individuals, the risk of HF increases as SES increases. For younger individuals, risk of HF increases as SES decreases. Our study may help decision-makers to better direct the implementation of political decisions. INTRODUCTION: The effect of socioeconomic status (SES) on hip fracture (HF) incidence remains unclear. The objective of this study is to evaluate the association between HF incidence and municipality-level SES as well as interactions between age and SES. METHODS: From the Portuguese Hospital Discharge Database, we selected hospitalizations (2000-2010) of patients aged 50+, with HF diagnosis (codes 820.x, ICD9-CM), caused by traumas of low/moderate energy, excluding bone cancer cases and readmissions for aftercare. Municipalities were classified according to SES (deprived to affluent) using 2001 Census data. A spatial Bayesian hierarchical regression model (controlling for data heterogeneity and spatial autocorrelation), using the Poisson distribution, was used to quantify the relative risk (RR) of HF, 95% credible interval (95%CrI), and analyze the interaction between age and SES after adjusting for rural conditions. RESULTS: There were 96,905 HF, 77.3% of which were on women who, on average, were older than men (mean age 81.2±8.5 vs 78.2±10.1 years) at admission (p<0.001). In women, there was a lower risk associated with better SES: RR=0.83 (95%CrI 0.65-1.00) for affluent versus deprived. There was an inverse association between SES and HF incidence rate in the youngest and a direct association in the oldest, for both sexes, but significant only between deprived and affluent in older ages (≥75 years). CONCLUSIONS: Interaction between SES and age may be due to inequalities in lifestyles, access to health systems, and preventive actions. These results may help decision-makers to better understand the epidemiology of hip fractures and to better direct the available funding.

Hip fractures cluster in space: an epidemiological analysis in Portugal.

UNLABELLED: Using Portuguese hospital registers (2000-2002) we calculated age-standardized incidence rates of hip fractures. Spatial clusters of high incidence rates were found, with annual averages (per 100,000 inhabitants) varying from 154.4 to 572.2 and 77.3 to 231.5 for women and men, respectively. Geographic inequalities in the occurrence of hip fractures were also found. INTRODUCTION: The aim of this study was to identify spatial patterns in the incidence of hip fracture in Portugal during the period 2000 to 2002. METHODS: From the National Hospital Discharge Register, admissions of patients (50 years of age or more) with low-energy hip fracture were selected. Age-standardized incidence rates in relation to the municipality of the patients' place of residence were calculated. Empirical Bayes estimators were used to smooth the local risk and spatial statistics methods were used to identify spatial clusters. RESULTS: Of 25,634 hip fractures in individuals aged 50 years or more caused by low or moderate impact, 19,759 occurred in women (age, mean+/-SD, 80.6+/-8.6 years) and 5,875 in men (age 77.7+/-10.0 years). Incidence rates increased exponentially with age, being higher in women nation-wide (female to male ratio from 1.5 to 5.1). Significant geographic differences were found: the incidence rates (95% CI) varied from 154.4 (153.6-155.3) to 572.2 (569.5-575.0) in women and 77.3 (76.64-78.05) to 231.5 (229.9-233.0) in men per 100,000 inhabitants. Spatial autocorrelation values (Moran index) were 0.56 and 0.45 for women and men, respectively. CONCLUSION: Spatial clusters (p<0.0001) of high incidences were identified. Geographic differences in incidence rates were about threefold. Some regions had incidence rates as high as some north European countries. The geographic inequalities could be due to environmental or socioeconomic factors, but further investigation needs to be done to confirm this hypothesis.

Delayed examination of synovial fluid by ordinary and polarised light microscopy to detect and identify crystals.

OBJECTIVE: To determine the reliability of a delay in the microscopic examination of synovial fluid (SF) to detect and identify crystals. METHODS: Ninety one SF samples were examined, 31 with monosodium urate (MSU) crystals, 30 with crystals of calcium pyrophosphate dihydrate (CPPD), and 30 containing no crystals. The specimens were stored with EDTA, sodium heparin, and without anticoagulant at 4 degrees C before examination at 24 and 72 hours with ordinary and polarised light microscopy. Another aliquot of the same samples was stored in a plastic container without anticoagulant at -80 degrees C and examined after two months. RESULTS: When the samples stored at 4 degrees C were re-examined after 24 hours, intracellular crystals of MSU were seen in 90/93 (97%) cases where they had been identified previously and 89/93 (96%) cases after 72 hours. Similarly, CPPD crystals were identified in 90/90 (100%) and 87/90 (97%) cases after 24 and 72 hours. Examination of the samples stored at -80 degrees C showed intracellular MSU crystals in 25/31 (81%) of cases and CPPD crystals in 25/30 (83%). No crystals were seen in any sample which had previously been diagnosed as crystal-free. CONCLUSIONS: Deferred microscopic examination of refrigerated or deep frozen SF provides a strong probability of detecting MSU or CPPD crystals if these are present initially.

Health conditions and residential concentration of poverty: a study in Rio de Janeiro, Brazil.

STUDY OBJECTIVES: To establish the geographical relation of health conditions to socioeconomic status in the city of Rio de Janeiro, Brazil. DESIGN: All reported deaths in the municipality of Rio de Janeiro, from 1987 to 1995, obtained from the Mortality Information System, were considered in the study. The 24 "administrative regions" that compose the city were used as the geographical units. A geographical information system (GIS) was used to link mortality data and population census data, and allowed the authors to establish the geographical pattern of the health indicators considered in this study: "infant mortality rate"; "standardised mortality rate"; "life expectancy" and "homicide rate". Information on location of low income communities (slums) was also provided by the GIS. A varimax rotation principal component analysis combined information on socioeconomic conditions and provided a two dimension basis to assess contextual variation. MAIN RESULTS: The 24 administrative regions were aggregated into three different clusters, identified as relevant to reflect the socioeconomic variation. Almost all health indicator thematic maps showed the same socioeconomic stratification pattern. The worst health situation was found in the cluster composed of the harbour area and northern vicinity, precisely in the sector where the highest concentration of slum residents are present. This sector of the city exhibited an extremely high homicide rate and a seven year lower life expectancy than the remainder of the city. The sector that concentrates affluence, composed of the geographical units located along the coast, showed the best health situation. Intermediate health conditions were found in the west area, which also has poor living standards but low concentration of slums. CONCLUSIONS: The findings suggest that social and organisation characteristics of low income communities may have a relevant role in understanding health variations. Local health and other social programmes specifically targeting these communities are recommended.

[Linkage of environmental and health data: health risk analysis of the Rio de Janeiro water supply by using geographical information systems]. / Inter-relacionamento de dados ambientais e de saúde: análise de risco á saúde aplicada ao abastecimento de água no Rio de Janeiro utilizando Sistemas de Informações Geográficas.

Exposure assessment of population groups is based on linkage of environmental and health data. This relationship can be hard to establish due to spatial and temporal lags in data sets. Environmental data generally refer to scattered sampling points, while epidemiological data integrate periods of time within administrative territories. GIS can be used as a basis for organizing health-related and environmental data sets. We examined potential health risk in the Rio de Janeiro city water supply based on the overlay of information layers containing data on the presence and quality of water supply services. We used census tracts as the primary georeferenced data, since they contain information on how households are supplied, water supply pipes, sources, and reservoirs, and water quality according to the monitoring program. Population groups exposed to risks were located and quantified using spatial operations among these layers and adopting different risk criteria. The main problems related to water supply are located on the northern slope of the Tijuca Mountain Range (involving the absence or poor quality of water) and in the western area of the city of Rio, where the population relies on alternative water supply sources. The different origins, objectives, and structures of data have to be analyzed critically, and GIS can be used as a data validation tool as well as an instrument for detailed identification of inconsistencies.