Evaluating the impact of the Bolsa Familia conditional cash transfer program on premature cardiovascular and all-cause mortality using the 100 million Brazilian cohort: a natural experiment study protocol

Maternal and child nutrition programme of investigation within the 100 Million Brazilian Cohort: study protocol

INTRODUCTION

There is a limited understanding of the early nutrition and pregnancy determinants of short-term and long-term maternal and child health in ethnically diverse and socioeconomically vulnerable populations within low-income and middle-income countries. This investigation programme aims to: (1) describe maternal weight trajectories throughout the life course; (2) describe child weight, height and body mass index (BMI) trajectories; (3) create and validate models to predict childhood obesity at 5 years of age; (4) estimate the effects of prepregnancy BMI, gestational weight gain (GWG) and maternal weight trajectories on adverse maternal and neonatal outcomes and child growth trajectories; (5) estimate the effects of prepregnancy BMI, GWG, maternal weight and interpregnancy BMI changes on maternal and child outcomes in the subsequent pregnancy; and (6) estimate the effects of maternal food consumption and infant feeding practices on child nutritional status and growth trajectories.

METHODS AND ANALYSIS

Linked data from four different Brazilian databases will be used: the 100 Million Brazilian Cohort, the Live Births Information System, the Mortality Information System and the Food and Nutrition Surveillance System. To analyse trajectories, latent-growth, superimposition by translation and rotation and broken stick models will be used. To create prediction models for childhood obesity, machine learning techniques will be applied. For the association between the selected exposure and outcomes variables, generalised linear models will be considered. Directed acyclic graphs will be constructed to identify potential confounders for each analysis investigating potential causal relationships.

ETHICS AND DISSEMINATION

This protocol was approved by the Research Ethics Committees of the authors' institutions. The linkage will be carried out in a secure environment. After the linkage, the data will be de-identified, and pre-authorised researchers will access the data set via a virtual private network connection. Results will be reported in open-access journals and disseminated to policymakers and the broader public.

The impact of a randomized cash transfer intervention on mortality of adult household members in rural South Africa, 2011-2022

BACKGROUND

Increasing socioeconomic resources through cash transfer payments could help promote healthy longevity. However, research in this area is limited due to endogeneity in cash transfer exposures and limited geographic representation.

METHODS

We leveraged the HPTN 068 randomized cash transfer trial, conducted from 2011 to 2015 in a rural setting in South Africa. We assessed long-term mortality follow-up (until March 2022) on older adult members (n = 3568) of households enrolled in the trial from the complete Agincourt Health and socio-Demographic Surveillance System census of the underlying source population. The trial intervention was a monthly cash payment of 300 Rand conditional on school enrollment of index young women. The payments were split between the young woman (1/3) and their caregiver (2/3). Young women and their households were randomized 1:1 to intervention vs. control. We used Cox PH models to compare mortality rates in older adults living in intervention vs. control households.

FINDINGS

The cash transfer intervention did not significantly impact mortality in the full sample [HR (95% CI): 0.94 (0.80, 1.10)]. However, we observed strong protective effects of the cash transfer intervention among those with above-median household assets [HR (95% CI): 0.66 (0.50, 0.86)] and higher educational attainment [HR (95% CI): 0.37 (0.15, 0.93)].

INTERPRETATION

Our findings indicate that short-term cash transfers can lead to reduced mortality in certain subgroups of older adults with higher baseline socioeconomic status. Future work should focus on understanding the optimal timing, structure, and targets to maximize the benefits of cash transfer programs in promoting healthy aging and longevity.

Impact of Brazil's Bolsa Família Programme on cardiovascular and all-cause mortality: a natural experiment study using the 100 Million Brazilian Cohort

BACKGROUND

Cardiovascular disease (CVD) has a disproportionate effect on mortality among the poorest people. We assessed the impact on CVD and all-cause mortality of the world's largest conditional cash transfer, Brazil's Bolsa Família Programme (BFP).

METHODS

We linked administrative data from the 100 Million Brazilian Cohort with BFP receipt and national mortality data. We followed individuals who applied for BFP between 1 January 2011 and 31 December 2015, until 31 December 2015. We used marginal structural models to estimate the effect of BFP on all-age and premature (30-69 years) CVD and all-cause mortality. We conducted stratified analyses by levels of material deprivation and access to healthcare. We checked the robustness of our findings by restricting the analysis to municipalities with better mortality data and by using alternative statistical methods.

RESULTS

We studied 17 981 582 individuals, of whom 4 855 324 were aged 30-69 years. Three-quarters (76.2%) received BFP, with a mean follow-up post-award of 2.6 years. We detected 106 807 deaths by all causes, of which 60 893 were premature; and 23 389 CVD deaths, of which 15 292 were premature. BFP was associated with reductions in premature all-cause mortality [hazard ratio (HR) = 0.96, 95% CI = 0.94-0.98], premature CVD (HR = 0.96, 95% CI = 0.92-1.00) and all-age CVD (HR = 0.96, 95% CI = 0.93-1.00) but not all-age all-cause mortality (HR = 1.00, 95% CI = 0.98-1.02). In stratified and robustness analyses, BFP was consistently associated with mortality reductions for individuals living in the two most deprived quintiles.

CONCLUSIONS

BFP appears to have a small to null effect on premature CVD and all-cause mortality in the short term; the long-term impact remains unknown.

Biases arising from linked administrative data for epidemiological research: a conceptual framework from registration to analyses

Linked administrative data offer a rich source of information that can be harnessed to describe patterns of disease, understand their causes and evaluate interventions. However, administrative data are primarily collected for operational reasons such as recording vital events for legal purposes, and planning, provision and monitoring of services. The processes involved in generating and linking administrative datasets may generate sources of bias that are often not adequately considered by researchers. We provide a framework describing these biases, drawing on our experiences of using the 100 Million Brazilian Cohort (100MCohort) which contains records of more than 131 million people whose families applied for social assistance between 2001 and 2018. Datasets for epidemiological research were derived by linking the 100MCohort to health-related databases such as the Mortality Information System and the Hospital Information System. Using the framework, we demonstrate how selection and misclassification biases may be introduced in three different stages: registering and recording of people's life events and use of services, linkage across administrative databases, and cleaning and coding of variables from derived datasets. Finally, we suggest eight recommendations which may reduce biases when analysing data from administrative sources.