Some research has reported an IQ discrepancy in different geographical regions of a country ( Kaufman, McClean, & Reynolds, 1988 Lynn, 1979), which could be associated with average regional incomes ( Almeida, Lemos, & Lynn, unpublished manuscript McDaniel, 2006). Investigations of geographic variables are complicated, and international inter-study comparison is meaningless due to the specificities of the populations and territories. One study found better scores among individuals who are currently employed ( Moraes et al., 2010) and another reported worse scores among individuals with occupations with low intellectual demands ( Anderson, Sachdev, Brodaty, Trollor, & Andrews, 2007). Information regarding employment status is relatively scarce. There has also been a lack of consensus regarding marital status, as some studies have reported greater performances among married persons ( Fratiglioni, Wang, Ericsson, Maytan, & Winblad, 2000 Moraes et al., 2010 Nguyen et al., 2002 Ribeiro et al., 2010 Wu, Lan, Chen, Chiu, & Lan, 2011), whereas others have found no influence on cognitive state assessment ( Bertolucci et al., 2001 Mías et al., 2007). Some studies have suggested that gender contributes significantly to the explanation of variance on scores of cognitive screening tests ( Han et al., 2008 Measso et al., 1993 Mías, Sassi, Masih, Querejeta, & Krawchik, 2007 Ribeiro, Oliveira, Cupertino, Neri, & Yassuda, 2010 Scazufca, Almeida, Vallada, Tasse, & Menezes, 2009), whereas others have not supported this hypothesis ( Bertolucci et al., 2001 Lieberman et al., 1999 Mathuranath et al., 2007 Morgado et al., 2010). The results regarding gender are more controversial. The magnitude of this effect is strong therefore, education is invariably considered a criterion for the establishment of normative data for cognitive tests ( Bravo & Hébert, 1997 Guerreiro, 1998 Han et al., 2008 Lieberman et al., 1999 Mathuranath et al., 2007 Measso et al., 1993 Moraes et al., 2010 Morgado, Rocha, Maruta, Guerreiro, & Martins, 2010 Nguyen, Black, Ray, Espino, & Markides, 2002 Rossetti et al., 2011). Regarding the educational level, the worst performance has been found among those with lower education levels, and ceiling effects have been observed among highly educated individuals. With regard to age, older age has been found to significantly increase the probability of obtaining lower scores ( Bravo & Hébert, 1997 Gallacher et al., 1999 Han et al., 2008 Langa et al., 2009 Matallana et al., 2011 Mathuranath et al., 2007 Moraes, Pinto, Lopes, Litvoc, & Bottino, 2010 Rossetti, Lacritz, Cullum, & Weiner, 2011). It has been widely reported that age and educational level have a significant effect on cognitive screening test performance. Several studies have demonstrated that performance on screening tests is influenced by sociodemographic variables. This study contributes a useful approach to understanding MoCA performance, stressing the great impact of education and age on scores.Īssessment, Elderly, Norms, Mild Cognitive Impairment, Alzheimer's disease, Dementia Introduction Regarding health variables, only the subjective memory complaints of the participant showed a small contribution (9%) to the variance on the MoCA scores. Educational level and age significantly contributed to the prediction of the MoCA scores, explaining 49% of the variance. The investigation was carried out in a Portuguese community-based sample of 650 cognitively healthy adults, who were representative of the distribution observed in the Portuguese population. The present study aimed to analyze the influence of sociodemographic (age, gender, educational level, marital and employment status, geographic region, geographic localization, and residence area) and health variables (subjective memory complaints of the participant and evaluated by the informant, depressive symptoms, and family history of dementia) on the participants' performance on the MoCA. The Montreal Cognitive Assessment (MoCA) is a brief cognitive instrument for screening milder forms of cognitive impairment.
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