- ICH GCP
- Rejestr badań klinicznych w USA
- Badanie kliniczne NCT03207321
Early Childhood Nutrition and Adult Outcomes in India
Analysis of the Association Between Early Childhood Nutrition and Adult Outcomes Using Andhra Pradesh Children and Parents Study (APCAPS) Data
This study will investigate the association between exposure to a daily nutritional supplement in utero and during the first three years of life and adult educational, marriage, and labor market outcomes in India. During 1987-1990, a controlled nutrition trial offered a daily cooked meal to pregnant women and children below the age of six years in 15 intervention villages near the city of Hyderabad in South India. No supplementation was offered during the study in another 14 control villages. The trial and its follow up surveys are together known as the Andhra Pradesh Children and Parents Study (APCAPS).
This protocol registration is for an analysis of the publicly available APCAPS third follow up wave (2010-2012) data. It is not a registration of the underlying 1987-1990 nutrition trial.
Przegląd badań
Szczegółowy opis
The investigators plan to use the 2010-2012 wave of the APCAPS data. They will access these publicly available data by applying for collaboration with the APCAPS study group.
The 2010-2012 follow-up survey invited all surviving children born during the original trial period of 1987-1990 (hereafter called index children) to participate. These index children were 20-25 years old at the time of this survey. Of the invited index children, 1,360 (715 in intervention villages and 645 in control villages) participated. The APCAPS surveys have collected a wide variety of data on socio-demographics, lifestyle, medical history, mental and reproductive health, anthropometry, cardiovascular physiology, spirometry, and biomarkers.
Using these data, the investigators will examine the association between birth in an intervention village and adult educational, marriage and labor market outcomes. For each study participant, a survey question collected information on the highest level of education attained by the participant (self-reported). From this variable, the investigators will create two indicators of whether the adult: (1) completed at least secondary school, i.e. class X/XII, intermediate, vocational course, or equivalent; (2) completed at least graduate level, i.e. Bachelor's degree, diploma, or equivalent.
The third outcome variable of the analysis will be whether the adult was ever-married (currently married, widowed, or divorced) at the time of the survey. Finally, the investigators will also examine whether the adult was either employed in paid or unpaid (e.g. household agriculture) work, or enrolled in higher education (degree or training course).
The investigators will use at least two different analytical methods. First, they will conduct a multivariate regression analysis (logit or probit) of each of the four outcome indicators. Along with the main independent variable of interest - birth in an intervention village - the model will include the following covariates: age, sex (whether female), and birth order of the index child, indicators of parental schooling attainment, religion, caste, and household standard of living as measured by quintiles of a composite asset index. All standard errors of regression will be heteoskedasticity-robust and clustered at the village level. The analysis will be conducted (and results reported) for the full sample and separately for the male and female subsamples.
In order to mitigate any bias arising from systematic differences in the characteristics of the intervention and control village adults (e.g. due to non-random attrition or other reasons), the investigators will also use quasi-experimental matching methods. One widely used methodology is matching based on propensity scores. The investigators will first conduct a selection analysis in which the likelihood of birth in an intervention village is regressed (probit or logit model) on the set of participant, parental, and household covariates mentioned above. Then, based on the predicted probability of intervention assignment (called propensity score) obtained from this model, participants in the intervention group will be matched with similar participant(s) in the control group. The investigators will use a variety of matching algorithms in order to test the sensitivity of the results, e.g. one-to-one nearest neighbor, Kernel, and multiple nearest neighbors matching. Common metrics for the quality of matching exercise and covariate balancing tests will be reported.
After matching, the investigators will report the average difference in outcome indicators between the intervention and matched control groups (technically named as the average treatment effect on the treated) as the estimated association between birth in an intervention village and adult outcomes. Findings from the full sample as well as male and female subsamples will be reported.
Typ studiów
Zapisy (Rzeczywisty)
Kryteria uczestnictwa
Kryteria kwalifikacji
Wiek uprawniający do nauki
Akceptuje zdrowych ochotników
Płeć kwalifikująca się do nauki
Metoda próbkowania
Badana populacja
The 1987-1990 Hyderabad Nutrition Trial enrolled pregnant women and young children from 29 villages in administrative areas near the city of Hyderabad in the state of Andhra Pradesh (now in Telangana). First, two adjacent sub-districts (group of villages, called a block) were selected for the study - one for the intervention group and the other as control. Then, 15 intervention and 14 control villages were selected. Intervention and control group villages had similar levels of access to other public health programs such as immunization and anemia control in pregnancy.
The children originally born in the study villages during 1987-1990 have been tracked and surveyed several times during 2003-2012. This study will use the the 2010-2012 survey data which include 1,360 (715 intervention and 645 control) adults of age 20-25 years who were originally born during the trial.
Opis
Inclusion Criteria:
- All participants in the publicly available data from the APCAPS 2010-2012 survey round.
Exclusion Criteria:
- None
Plan studiów
Jak projektuje się badanie?
Szczegóły projektu
Kohorty i interwencje
Grupa / Kohorta |
Interwencja / Leczenie |
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Intervention
In 15 intervention villages, a balanced protein-calorie supplement - made from locally available corn-soya ingredients and called 'upma' - was offered daily to pregnant women and children under six years of age during 1987-1990.
The meal provided on average 500 kcal energy and 20-25g of protein to women and half of those amounts to children.
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A balanced protein-calorie supplement - made from locally available corn-soya ingredients and called 'upma'.
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Control
No supplement was provided in 14 control villages.
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Co mierzy badanie?
Podstawowe miary wyniku
Miara wyniku |
Opis środka |
Ramy czasowe |
---|---|---|
The likelihood of a study participant completing at least secondary school, i.e. class X/XII, intermediate, vocational course, or equivalent
Ramy czasowe: Up to 25 years
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Binary indicator of secondary level education
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Up to 25 years
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The likelihood of a study participant completing at least graduate level education, i.e. Bachelor's degree, diploma, or equivalent
Ramy czasowe: Up to 25 years
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Binary indicator of graduate level education
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Up to 25 years
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The likelihood of a study participant being ever-married (currently married, widowed, or divorced)
Ramy czasowe: Up to 25 years
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Binary indicator of marriage
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Up to 25 years
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The likelihood of a study participant being employed in paid or unpaid work, or enrolled in further education (degree or training courses)
Ramy czasowe: Up to 25 years
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Binary indicator of employment or higher education enrollment
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Up to 25 years
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Współpracownicy i badacze
Sponsor
Śledczy
- Główny śledczy: Arindam Nandi, PhD, University of Chicago
- Główny śledczy: Jere R Behrman, PhD, University of Pennsylvania
- Główny śledczy: Sanjay Kinra, PhD, London School of Hygiene and Tropical Medicine
- Główny śledczy: Ramanan Laxminarayan, PhD, Center for Disease Dynamics, Economics & Policy
Publikacje i pomocne linki
Publikacje ogólne
- Kinra S, Rameshwar Sarma KV, Ghafoorunissa, Mendu VV, Ravikumar R, Mohan V, Wilkinson IB, Cockcroft JR, Davey Smith G, Ben-Shlomo Y. Effect of integration of supplemental nutrition with public health programmes in pregnancy and early childhood on cardiovascular risk in rural Indian adolescents: long term follow-up of Hyderabad nutrition trial. BMJ. 2008 Jul 25;337:a605. doi: 10.1136/bmj.a605.
- Kinra S, Sarma KV, Hards M, Smith GD, Ben-Shlomo Y. Is relative leg length a biomarker of childhood nutrition? Long-term follow-up of the Hyderabad Nutrition Trial. Int J Epidemiol. 2011 Aug;40(4):1022-9. doi: 10.1093/ije/dyr074. Epub 2011 May 10.
- Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association. 1984;79:516-24
- Heckman JJ, Ichimura H, Todd PE. Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme. Review of Economic Studies. 1997;64:605-54
- Dehejia RH, Wahba S. Propensity Score-Matching Methods For Nonexperimental Causal Studies. The Review of Economics and Statistics. 2002;84:151-61
- Nandi A, Ashok A, Kinra S, Behrman JR, Laxminarayan R. Early Childhood Nutrition Is Positively Associated with Adolescent Educational Outcomes: Evidence from the Andhra Pradesh Child and Parents Study (APCAPS). J Nutr. 2015 Apr 1;146(4):806-813. doi: 10.3945/jn.115.223198.
Daty zapisu na studia
Główne daty studiów
Rozpoczęcie studiów (Rzeczywisty)
Zakończenie podstawowe (Rzeczywisty)
Ukończenie studiów (Rzeczywisty)
Daty rejestracji na studia
Pierwszy przesłany
Pierwszy przesłany, który spełnia kryteria kontroli jakości
Pierwszy wysłany (Rzeczywisty)
Aktualizacje rekordów badań
Ostatnia wysłana aktualizacja (Rzeczywisty)
Ostatnia przesłana aktualizacja, która spełniała kryteria kontroli jakości
Ostatnia weryfikacja
Więcej informacji
Terminy związane z tym badaniem
Inne numery identyfikacyjne badania
- APCAPS2017
Plan dla danych uczestnika indywidualnego (IPD)
Planujesz udostępniać dane poszczególnych uczestników (IPD)?
Badanie danych/dokumentów
Informacje o lekach i urządzeniach, dokumenty badawcze
Bada produkt leczniczy regulowany przez amerykańską FDA
Bada produkt urządzenia regulowany przez amerykańską FDA
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