Oral abstracts 3: RA Treatment and outcomesO13. Validation of jadas in all subtypes of juvenile idiopathic arthritis in a clinical setting

Background: Juvenile Arthritis Disease Activity Score (JADAS) is a 4 variable composite disease activity (DA) score for JIA (including active 10, 27 or 71 joint count (AJC), physician global (PGA), parent/child global (PGE) and ESR). The validity of JADAS for all ILAR subtypes in the routine clinical setting is unknown. We investigated the construct validity of JADAS in the clinical setting in all subtypes of JIA through application to a prospective inception cohort of UK children presenting with new onset inflammatory arthritis. Methods: JADAS 10, 27 and 71 were determined for all children in the Childhood Arthritis Prospective Study (CAPS) with complete data available at baseline. Correlation of JADAS 10, 27 and 71 with single DA markers was determined for all subtypes. All correlations were calculated using Spearman's rank statistic. Results: 262/1238 visits had sufficient data for calculation of JADAS (1028 (83%) AJC, 744 (60%) PGA, 843 (68%) PGE and 459 (37%) ESR). Median age at disease onset was 6.0 years (IQR 2.6-10.4) and 64% were female. Correlation between JADAS 10, 27 and 71 approached 1 for all subtypes. Median JADAS 71 was 5.3 (IQR 2.2-10.1) with a significant difference between median JADAS scores between subtypes (p < 0.01). Correlation of JADAS 71 with each single marker of DA was moderate to high in the total cohort (see Table 1). Overall, correlation with AJC, PGA and PGE was moderate to high and correlation with ESR, limited JC, parental pain and CHAQ was low to moderate in the individual subtypes. Correlation coefficients in the extended oligoarticular, rheumatoid factor negative and enthesitis related subtypes were interpreted with caution in view of low numbers. Conclusions: This study adds to the body of evidence supporting the construct validity of JADAS. JADAS correlates with other measures of DA in all ILAR subtypes in the routine clinical setting. Given the high frequency of missing ESR data, it would be useful to assess the validity of JADAS without inclusion of the ESR. Disclosure statement: All authors have declared no conflicts of interest. Table 1Spearman's correlation between JADAS 71 and single markers DA by ILAR subtype ILAR Subtype Systemic onset JIA Persistent oligo JIA Extended oligo JIA Rheumatoid factor neg JIA Rheumatoid factor pos JIA Enthesitis related JIA Psoriatic JIA Undifferentiated JIA Unknown subtype Total cohort Number of children 23 111 12 57 7 9 19 7 17 262 AJC 0.54 0.67 0.53 0.75 0.53 0.34 0.59 0.81 0.37 0.59 PGA 0.63 0.69 0.25 0.73 0.14 0.05 0.50 0.83 0.56 0.64 PGE 0.51 0.68 0.83 0.61 0.41 0.69 0.71 0.9 0.48 0.61 ESR 0.28 0.31 0.35 0.4 0.6 0.85 0.43 0.7 0.5 0.53 Limited 71 JC 0.29 0.51 0.23 0.37 0.14 -0.12 0.4 0.81 0.45 0.41 Parental pain 0.23 0.62 0.03 0.57 0.41 0.69 0.7 0.79 0.42 0.53 Childhood health assessment questionnaire 0.25 0.57 -0.07 0.36 -0.47 0.84 0.37 0.8 0.66 0.4

Interstate migration of the US poverty population: Immigration “pushes” and welfare magnet “pulls”

This study evaluates the social and demographic structure of poverty migration during the 1985–90 period based on an analysis of recent census data. Particular attention is given to the roles of two policy-relevant factors that are proposed to be linked to poverty migration. The first of these is the role of immigration from abroad and its effect on the net out-migration of longer-term residents with below-poverty incomes, from States receiving the highest volume of immigrants. Such a response, it is argued, could result from job competition or other economic and social costs associated with immigration. The second involves the poverty population “magnet” effect associated with State welfare benefits (AFDC and Food Stamp payments) which has come under renewed scrutiny in light of the impending reform of the federal welfare program. The impact of both of these factors on interstate poverty migration is evaluated in a broader context that takes cognizance of other sociodemographic subgroups, and State-level attributes that are known to be relevant in explaining internal migration. This research employs an exceptionally rich data base of aggregate migration flows, specially tabulated from the full migration sample of the 1990 US census (based on the “residence 5 years ago” question). It also employs an analysis technique, the nested logit model, which identifies separately the “push” and “pull” effects of immigration, welfare benefits, and other State attributes on the migration process. Our findings are fairly clear. The high volume of immigration to selected US States does affect a selective out-migration of the poverty population, which is stronger for whites, Blacks and other non-Asian minorities as well as the least-educated. These results are consistent with arguments that internal migrants are responding to labor market competition from similarly educated immigrants. Moreover, we found that the impact of immigration occurs primarily as a “push” rather than a reduced “pull.” In contrast, State welfare benefits exert only minimal effects on the interstate migration of the poverty population—either as “pulls” or “pushes,” although some demographic segments of that population are more prone to respond than others. In addition to these findings, our results reveal the strong impact that a State's racial and ethnic composition exerts in both retaining and attracting migrants of like race and ethnic groups. This suggests the potential for a greater cross-state division in the US poverty population, by race and ethnic status.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43484/1/11111_2005_Article_BF02208337.pd