BackgroundCross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies with techniques that directly estimate the prevalence ratio.MethodsWe compared Cox regression with constant time at risk, Poisson regression and log-binomial regression against the standard Mantel-Haenszel estimators. Models with robust variance estimators in Cox and Poisson regressions and variance corrected by the scale parameter in Poisson regression were also evaluated.ResultsThree outcomes, from a cross-sectional study carried out in Pelotas, Brazil, with different levels of prevalence were explored: weight-for-age deficit (4%), asthma (31%) and mother in a paid job (52%). Unadjusted Cox/Poisson regression and Poisson regression with scale parameter adjusted by deviance performed worst in terms of interval estimates. Poisson regression with scale parameter adjusted by χ2 showed variable performance depending on the outcome prevalence. Cox/Poisson regression with robust variance, and log-binomial regression performed equally well when the model was correctly specified.ConclusionsCox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to non-specialists than the odds ratio. However, precautions are needed to avoid estimation problems in specific situations.

This Lancet Series paper, one of three on the high rate of Caesarean Section (CS), describes the global, regional and selected country levels, trends, determinants and inequalities in CS. Based on data from 169 countries representing 98.4% of the world's births, we estimate that 21.1% (95% uncertainty range 19.9-22.4%) or 29.7 million births occurred through CS in 2015, representing almost a doubling since 2000 (12.1%; 10.9-13.3%). The differences in CS rates between regions in 2015 were tenfold, with a high of 44.3% (41.3-47.4%) in the Latin America and the Caribbean region and a low of 4.1% (3.6-4.6%) in the West and Central African region. The global and regional increases were driven both by increasing coverage of births by health facilities (66.5% of the global increase) and higher CS rates within health facilities (33.5%), with considerable variation between regions. Based on the most recent data, population-based CS rates exceeded 15% of births in 63% of 169 countries, while 28% countries had CS rates below 10%. National CS rates varied from 0.6% in South Sudan to 58.1% in the Dominican Republic. Within-country disparities in CS rates were also very large, with a sixfold difference in CS rates between births in the richest and poorest quintiles in low-and middle-income countries, markedly high CS rates among low obstetric risk births among especially more educated women in Brazil and China and 1.6 times higher CS rates in private facilities compared to public facilities.

In a PLOS Medicine Review, Aluísio Barros and Cesar Victora provide a practical guide to measuring and interpreting inequalities in the coverage of maternal, newborn, and child interventions in low- and middle-income countries using data collected by large household surveys.

Background Population-based data on COVID-19 are essential for guiding policies. There are few such studies, particularly from low or middle-income countries. Brazil is currently a hotspot for COVID-19 globally. We aimed to investigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence by city and according to sex, age, ethnicity group, and socioeconomic status, and compare seroprevalence estimates with official statistics on deaths and cases. Methods In this repeated cross-sectional study, we did two seroprevalence surveys in 133 sentinel cities in all Brazilian states. We randomly selected households and randomly selected one individual from all household members. We excluded children younger than 1 year. Presence of antibodies against SARS-CoV-2 was assessed using a lateral flow point-of-care test, the WONDFO SARS-CoV-2 Antibody Test (Wondfo Biotech, Guangzhou, China), using two drops of blood from finger prick samples. This lateral-flow assay detects IgG and IgM isotypes that are specific to the SARS-CoV-2 receptor binding domain of the spike protein. Participants also answered short questionnaires on sociodemographic information (sex, age, education, ethnicity, household size, and household assets) and compliance with physical distancing measures. Findings We included 25 025 participants in the first survey (May 14–21) and 31 165 in the second (June 4–7). For the 83 (62%) cities with sample sizes of more than 200 participants in both surveys, the pooled seroprevalence increased from 1·9% (95% CI 1·7–2·1) to 3·1% (2·8–3·4). City-level prevalence ranged from 0% to 25·4% in both surveys. 11 (69%) of 16 cities with prevalence above 2·0% in the first survey were located in a stretch along a 2000 km of the Amazon river in the northern region. In the second survey, we found 34 cities with prevalence above 2·0%, which included the same 11 Amazon cities plus 14 from the northeast region, where prevalence was increasing rapidly. Prevalence levels were lower in the south and centre-west, and intermediate in the southeast, where the highest level was found in Rio de Janeiro (7·5% [4·2–12·2]). In the second survey, prevalence was similar in men and women, but an increased prevalence was observed in participants aged 20–59 years and those living in crowded conditions (4·4% [3·5–5·6] for those living with households with six or more people). Prevalence among Indigenous people was 6·4% (4·1–9·4) compared with 1·4% (1·2–1·7) among White people. Prevalence in the poorest socioeconomic quintile was 3·7% (3·2–4·3) compared with 1·7% (1·4–2·2) in the wealthiest quintile. Interpretation Antibody prevalence was highly heterogeneous by country region, with rapid initial escalation in Brazil's north and northeast. Prevalence is strongly associated with Indigenous ancestry and low socioeconomic status. These population subgroups are unlikely to be protected if the policy response to the pandemic by th...

Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models.

ObjectiveTo provide an update on economic related inequalities in caesarean section rates within countries.DesignSecondary analysis of demographic and health surveys and multiple indicator cluster surveys.Setting72 low and middle income countries with a survey conducted between 2010 and 2014 for analysis of the latest situation of inequality, and 28 countries with a survey also conducted between 2000 and 2004 for analysis of the change in inequality over time.ParticipantsWomen aged 15-49 years with a live birth during the two or three years preceding the survey.Main outcome measuresData on caesarean section were disaggregated by asset based household wealth status and presented separately for five subgroups, ranging from the poorest to the richest fifth. Absolute and relative inequalities were measured using difference and ratio measures. The pace of change in the poorest and richest fifths was compared using a measure of excess change.ResultsNational caesarean section rates ranged from 0.6% in South Sudan to 58.9% in the Dominican Republic. Within countries, caesarean section rates were lowest in the poorest fifth (median 3.7%) and highest in the richest fifth (median 18.4%). 18 out of 72 study countries reported a difference of 20 percentage points or higher between the richest and poorest fifth. The highest caesarean section rates and greatest levels of absolute inequality were observed in countries from the region of the Americas, whereas countries from the African region had low levels of caesarean use and comparatively lower levels of absolute inequality, although relative inequality was quite high in some countries. 26 out of 28 countries reported increases in caesarean section rates over time. Rates tended to increase faster in the richest fifth (median 0.9 percentage points per year) compared with the poorest fifth (median 0.2 percentage points per year), indicating an increase in inequality over time in most of these countries.ConclusionsSubstantial within country economic inequalities in caesarean deliveries remain. These inequalities might be due to a combination of inadequate access to emergency obstetric care among the poorest subgroups and high levels of caesarean use without medical indication in the richest subgroups, especially in middle income countries. Country specific strategies should address these inequalities to improve maternal and newborn health.

Resumo ObjetivoEstudar os padrões de utilização de medicamentos, classificando-os por grupos farmacológicos e verificando os determinantes individuais desse uso. Métodos Delineamento transversal de base populacional. Amostra composta por 3.182 indivíduos com 20 anos de idade ou mais, residentes na região urbana do município de Pelotas, RS. O processo de amostragem foi conduzido em múltiplos estágios. O instrumento foi um questionário estruturado, utilizando um período recordatório de 15 dias e aplicado através de entrevistas individuais. Na análise bruta, foram utilizados os seguintes testes: qui-quadrado para comparação de proporções, teste t para comparação de médias e o teste de tendência linear. A análise ajustada foi conduzida através de uma regressão de Poisson. Resultados A prevalência de uso global de medicamentos foi de 65,9%. Os seguintes grupos apresentaram maiores prevalências de utilização de medicamentos após análise ajustada: mulheres, idosos, indivíduos de nível econômico mais elevado e com pior autopercepção de saúde. Os grupos farmacológicos mais utilizados foram os analgésicos, antiinflamatórios e anti-hipertensivos. Conclusões A prevalência de uso de medicamentos foi superior às encontradas em outros estudos nacionais e internacionais. O estudo dos determinantes individuais de utilização de medicamentos indica os grupos mais sujeitos ao uso excessivo, o que pode embasar estratégias específicas para diminuir a utilização nesses grupos, tais como políticas mais restritivas para prescrição e venda de medicamentos. Abstract ObjectiveTo study epidemiological patterns of drug utilization and its individual determinants and to classify drugs used into pharmacological groups. Methods In a population-based cross-sectional study, 3,182 subjects aged 20 years or more were selected from an urban area in Southern Brazil using a multi-stage sampling design. Data were collected through home interviews using a structured questionnaire.

Given that breastfeeding is a protective factor for other diseases of infancy, our findings indicate that the common risks approach is the most appropriate for the prevention of posterior cross bite in primary or initial mixed dentition.