Socioeconomic position over the life-course and subjective social status in relation to nutritional status and mental health among Guatemalan adults.

OBJECTIVE: We study how life course objective socioeconomic position (SEP) predicts subjective social status (SSS) and the extent to which SSS mediates the association of objective SEP with nutritional status and mental health outcomes. METHODS: We use data from participants of the INCAP Longitudinal Study 1969-2018 (n = 1258) from Guatemala. We use the MacArthur ladder for two measures of SSS - perceived community respect and perceived economic status. We estimate the association of SSS with health outcomes after adjusting for early life characteristics and life course objective SEP (wealth, schooling, employment) using linear regression. We use path analysis to study the extent of mediation by SSS on the health outcomes of body mass index (BMI; kg/m2), psychological distress (using the WHO Self-Reported Questionnaire; SRQ-20) and happiness, using the Subjective Happiness Scale (SHS). RESULTS: Median participant rating was 5 [IQR: 3-8] for the perceived community respect and 3 [IQR: 1-5] for the perceived economic status, with no differences by sex. Objective SEP in early life and adulthood were predictive of both measures of SSS in middle adulthood as well as health outcomes (BMI, SRQ-20 and SHS). Perceived community respect (z-scores; 1 z = 3.1 units) was positively associated with happiness (0.13, 95 % CI: 0.07, 0.19). Perceived economic status (z-scores; 1 z = 2.3 units) was inversely associated with psychological distress (-0.28, 95 % CI: -0.47, -0.09). Neither measure of SSS was associated with BMI. Neither perceived community respect nor perceived economic status attenuated associations of objective SEP with health outcomes on inclusion as a mediator. CONCLUSIONS: Subjective social status was independently associated with happiness and psychological distress in middle adulthood after adjusting for objective SEP. Moreover, association of objective SEP with health was not mediated by SSS, suggesting potentially independent pathways.

Relative and absolute wealth mobility since birth in relation to health and human capital in middle adulthood: An analysis of a Guatemalan birth cohort.

BACKGROUND: Wealth mobility, as both relative (positional) and absolute (material) wealth acquisition, may counteract negative consequences of early life adversities on adult health. METHODS: We use longitudinal data (1967-2018) from the INCAP birth cohort, Guatemala (n = 1386). Using wealth as a measure of socio-economic position, we assess the association of life course relative mobility using latent class analysis and absolute material gains using conditional wealth measures. We estimate associations of wealth mobility with indicators of human capital, specifically height, weight status (BMI in kg/m2), psychological distress (WHO SRQ-20 score) and fluid intelligence (Ravens Progressive Matrices score; RPM) in middle adulthood. RESULTS: We identified four latent classes of relative mobility - Stable Low (n = 498), Stable High (n = 223), Downwardly Mobile (n = 201) and Upwardly Mobile (n = 464). Attained schooling (years) was positively associated with membership in Upwardly Mobile (odds ratio; 1.50, 95%CI: 1.31, 1.71) vs Stable Low, and inversely with membership in Downwardly Mobile (0.65, 95%CI: 0.54, 0.79) vs Stable High. Being Upwardly Mobile (vs Stable Low) was positively associated with height (1.88 cm, 95%CI: 1.04, 2.72), relative weight (1.32 kg/m2, 95%CI: 0.57, 2.07), lower psychological distress (-0.82 units, 95%CI: 1.34, -0.29) and fluid intelligence (0.94 units, 95%CI: 0.28, 1.59). Being Downwardly Mobile (vs Stable High) was associated with lower fluid intelligence (-2.69 units, 95%CI: 3.69, -1.68), and higher psychological distress (1.15 units, 95%CI: 0.34, 1.95). Absolute wealth gains (z-scores) from early to middle adulthood were positively associated with relative weight (0.62 kg/m2, 95%CI: 0.28, 0.96), lower psychological distress (-0.37 units, 95%CI: 0.60, -0.14) and fluid intelligence (0.50 units, 95%CI: 0.21, 0.79). CONCLUSIONS: Higher attained schooling provided a pathway for upward relative mobility and higher absolute wealth gains as well as protection against downward relative mobility. Upward mobility was associated with lower psychological distress and higher fluid intelligence but also higher weight status.

Comparação de métodos de imputação única e múltipla usando como exemplo um modelo de risco para mortalidade cirúrgica / Comparison of simple and multiple imputation methods using a risk model for surgical mortality as example

INTRODUÇÃO: A perda de informações é um problema frequente em estudos realizados na área da Saúde. Na literatura essa perda é chamada de missing data ou dados faltantes. Através da imputação dos dados faltantes são criados conjuntos de dados artificialmente completos que podem ser analisados por técnicas estatísticas tradicionais. O objetivo desse artigo foi comparar, em um exemplo baseado em dados reais, a utilização de três técnicas de imputações diferentes. MÉTODO: Os dados utilizados referem-se a um estudo de desenvolvimento de modelo de risco cirúrgico, sendo que o tamanho da amostra foi de 450 pacientes. Os métodos de imputação empregados foram duas imputações únicas e uma imputação múltipla (IM), e a suposição sobre o mecanismo de não-resposta foi MAR (Missing at Random). RESULTADOS: A variável com dados faltantes foi a albumina sérica, com 27,1 por cento de perda. Os modelos obtidos pelas imputações únicas foram semelhantes entre si, mas diferentes dos obtidos com os dados imputados pela IM quanto à inclusão de variáveis nos modelos. CONCLUSÕES: Os resultados indicam que faz diferença levar em conta a relação da albumina com outras variáveis observadas, pois foram obtidos modelos diferentes nas imputações única e múltipla. A imputação única subestima a variabilidade, gerando intervalos de confiança mais estreitos. É importante se considerar o uso de métodos de imputação quando há dados faltantes, especialmente a IM que leva em conta a variabilidade entre imputações para as estimativas do modelo.

INTRODUCTION: It is common for studies in health to face problems with missing data. Through imputation, complete data sets are built artificially and can be analyzed by traditional statistical analysis. The objective of this paper is to compare three types of imputation based on real data. METHODS: The data used came from a study on the development of risk models for surgical mortality. The sample size was 450 patients. The imputation methods applied were: two single imputations and one multiple imputation and the assumption was MAR (Missing at Random). RESULTS: The variable with missing data was serum albumin with 27.1 percent of missing rate. The logistic models adjusted by simple imputation were similar, but differed from models obtained by multiple imputation in relation to the inclusion of variables. CONCLUSIONS: The results indicate that it is important to take into account the relationship of albumin to other variables observed, because different models were obtained in single and multiple imputations. Single imputation underestimates the variability generating narrower confidence intervals. It is important to consider the use of imputation methods when there is missing data, especially multiple imputation that takes into account the variability between imputations for estimates of the model.