About Research - The Utility of Secondary Data Analysis in Breastfeeding Research: Opportunities and Challenges

Abstract

Secondary data analysis has emerged as an important approach for researchers seeking to explore new research questions using existing datasets. These datasets often comprise large and diverse, as well as longitudinal data, enabling comprehensive analyses that might be impractical through primary data collection alone. This paper discusses the importance of secondary data analysis in breastfeeding research, provides examples of publicly available and restricted datasets containing breastfeeding variables, outlines the methodological steps in conducting secondary data analysis, and discusses common limitations associated with this approach. By emphasizing both the utility and challenges of secondary data analysis, the paper aims to encourage informed use of secondary data analysis to advance knowledge and address important research questions in breastfeeding.

Keywords

biostatistics breastfeeding breastfeeding practices epidemiological methods lactation secondary data analysis

Get full access to this article

View all access options for this article.

References

Artzi-Medvedik

Haile

Z. T.

Chertok

I. R. A.

(2022). Association between influenza vaccination during pregnancy and breastfeeding duration. Breastfeeding Medicine, 17(6), 484–492. https://doi.org/10.1089/bfm.2022.0001

Carsley

Borkhoff

C. M.

Maguire

J. L.

Birken

C. S.

Khovratovich

McCrindle

Macarthur

Parkin

P. C.

& on behalf of the TARGet Kids! Collaboration. (2015). Cohort profile: The Applied Research Group for Kids (TARGet Kids!). International Journal of Epidemiology, 44(3), 776–788. https://doi.org/10.1093/ije/dyu123

Chen

T.-C.

Clark

Riddles

M. K.

Mohadjer

L. K.

Fakhouri

T. H. I.

(2020). National Health and Nutrition Examination Survey, 2015-2018: Sample design and estimation procedures. Vital and Health Statistics. Series 2, Data Evaluation and Methods Research, 184, 1–35. https://stacks.cdc.gov/view/cdc/88305

Cohen

S. S.

Alexander

D. D.

Krebs

N. F.

Young

B. E.

Cabana

M. D.

Erdmann

Hays

N. P.

Bezold

C. P.

Levin-Sparenberg

Turini

Saavedra

J. M.

(2018). Factors Associated with breastfeeding initiation and continuation: A meta-analysis. The Journal of Pediatrics, 203, 190–196.e21. https://doi.org/10.1016/j.jpeds.2018.08.008

Connelly

Platt

(2014). Cohort profile: UK Millennium Cohort Study (MCS). International Journal of Epidemiology, 43(6), 1719–1725. https://doi.org/10.1093/ije/dyu001

Corsi

D. J.

Neuman

Finlay

J. E.

Subramanian

(2012). Demographic and health surveys: A profile. International Journal of Epidemiology, 41(6), 1602–1613. https://doi.org/10.1093/ije/dys184

Coy

K. C.

Haight

S. C.

Anstey

Grant

A. M.

Ruffo

J. Y.

(2021). Postpartum marijuana use, perceptions of safety, and breastfeeding initiation and duration: An analysis of PRAMS data from seven states, 2017. Journal of Human Lactation, 37(4), 803–812. https://doi.org/10.1177/0890334421993466

Donnellan

M. B.

Lucas

R. E.

(2013). Secondary data analysis. In Little

T. D.

(Ed.), The Oxford handbook of quantitative methods in psychology: Vol. 2: Statistical analysis (pp. 665–677). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199934898.013.0028

Fein

S. B.

Labiner-Wolfe

Shealy

K. R.

Chen

Grummer-Strawn

L. M.

(2008). Infant feeding practices study II: Study methods. Pediatrics, 122(Suppl. 2), S28–S35. https://doi.org/10.1542/peds.2008-1315c

10.

Fernández

C. R.

Guan

Rodriguez

Zork

Barbosa

Shuffrey

L. C.

(2023). The association of nutrition and exercise behaviors of women with diabetes in pregnancy with infant breastfeeding practices. Breastfeeding Medicine, 18(10), 794–799. https://doi.org/10.1089/bfm.2023.0059

11.

Froh

E. B.

Spatz

D. L.

(2016). Navigating return to work and breastfeeding in a hospital with a comprehensive employee lactation program: The voices of mothers. Journal of Human Lactation, 32(4), 689–694. https://doi.org/10.1177/0890334416663475

12.

Gray

Sanson

(2005). Growing up in Australia: The longitudinal study of Australian children. Family Matters, 72, 4–9. https://doi.org/10.3316/informit.052395322391224

13.

Hallal

P. C.

Bertoldi

A. D.

Domingues

M. R.

da Silveira

M. F.

Demarco

F. F.

da Silva

I. C. M.

Barros

F. C.

Victora

C. G.

Bassani

D. G.

(2018). Cohort profile: The 2015 Pelotas (Brazil) birth cohort study. International Journal of Epidemiology, 47(4), 1048–1048h. https://doi.org/10.1093/ije/dyx219

14.

Heafner

T. L.

Fitchett

P. G.

Knowles

R. T.

(2016). Using big data, large-scale studies, secondary datasets, and secondary data analysis as tools to inform social studies teaching and learning. In Crowe

A. R.

Cuenca

(Eds.), Rethinking social studies teacher education in the twenty-first century (pp. 359–383). Springer International Publishing. https://doi.org/10.1007/978-3-319-22939-3_19

15.

Kapa

H. M.

Litteral

J. L.

Keim

S. A.

Jackson

J. L.

Schofield

K. A.

Crerand

C. E.

(2022). Body image dissatisfaction, breastfeeding experiences, and self-efficacy in postpartum women with and without eating disorder symptoms. Journal of Human Lactation, 38(4), 633–643. https://doi.org/10.1177/08903344221076529

16.

Kara

(2022). The importance of secondary data. Sage Research Methods Community. https://researchmethodscommunity.sagepub.com/blog/the-importance-of-secondary-data

17.

Kelly

M. M.

Martin-Peters

Farber

J. S.

(2024). Secondary data analysis: Using existing data to answer new questions. Journal of Pediatric Health Care, 38(4), 615–618. https://doi.org/10.1016/j.pedhc.2024.03.005

18.

Khan

Hancioglu

(2019). Multiple indicator cluster surveys: Delivering robust data on children and women across the globe. Studies in Family Planning, 50(3), 279–286. https://doi.org/10.1111/sifp.12103

19.

Kindratt

T. B.

(2022). Complex survey design features. Big data for epidemiology: Applied data analysis using national health surveys. Mavs Open Press Open Educational Resources. https://uta.pressbooks.pub/bigdataforepidemiology/chapter/chapter5-complexsurvey/

20.

Kurniawan

D. W.

Chertok

I. R. A.

Haile

Z. T.

(2021). The relationship between place of birth and early breastfeeding initiation in Indonesia. Journal of Human Lactation, 37(2), 357–369. https://doi.org/10.1177/0890334420945299

21.

Lewis

(2017). Complex survey data analysis with SAS. CRC Press, Taylor & Francis Group.

22.

National Center for Education Statistics. (2005). Early Childhood Longitudinal Study—Birth Cohort: Users manual for the ECLS-B nine-month public use data file and electronic code book. U.S. Department of Education. https://nces.ed.gov/pubs2005/2005013.pdf

23.

Nelson

J. M.

Grossniklaus

D. A.

Galuska

D. A.

Perrine

C. G.

(2020). The mPINC survey: Impacting US maternity care practices. Maternal & Child Nutrition, 17(1), Article e13092. https://doi.org/10.1111/mcn.13092

24.

Pérez-Escamilla

Tomori

Hernández-Cordero

Baker

Barros

A. J. D.

Bégin

Chapman

D. J.

Grummer-Strawn

L. M.

McCoy

Menon

Neves

P. A. R.

Piwoz

Rollins

Victora

C. G.

Richter

(2023). Breastfeeding: Crucially important, but increasingly challenged in a market-driven world. The Lancet, 401(10375), 472–485. https://doi.org/10.1016/S0140-6736(22)01932-8

25.

Pfeffermann

(1996). The use of sampling weights for survey data analysis. Statistical Methods in Medical Research, 5(3), 239–261. https://doi.org/10.1177/096228029600500303

26.

Reno

Whipps

Wallenborn

J. T.

Demirci

Bogen

D. L.

Gross

R. S.

Mendelsohn

A. L.

Morris

P. A.

Shaw

D. S.

(2022). Housing insecurity, housing conditions, and breastfeeding behaviors for medicaid-eligible families in urban settings. Journal of Human Lactation, 38(4), 760–770. https://doi.org/10.1177/08903344221108073

27.

Ritchie-Ewing

Mitchell

A. M.

Christian

L. M.

(2019). Associations of maternal beliefs and distress in pregnancy and postpartum with breastfeeding initiation and early cessation. Journal of Human Lactation, 35(1), 49–58. https://doi.org/10.1177/0890334418767832

28.

Rosinger

A. Y.

Ice

(2019). Secondary data analysis to answer questions in human biology. American Journal of Human Biology, 31(3), Article e23232. https://doi.org/10.1002/ajhb.23232

29.

Santana

G. S.

Giugliani

E. R. J.

Vieira

G. O.

(2018). Factors associated with breastfeeding maintenance for 12 months or more: A systematic review. Jornal De Pediatria, 94(2), 104–122. https://doi.org/10.1016/j.jped.2017.06.013

30.

Seidenberg

A. B.

Moser

R. P.

West

B. T.

(2023). Preferred reporting items for complex sample survey analysis (PRICSSA). Journal of Survey Statistics and Methodology, 11(4), 743–757. https://doi.org/10.1093/jssam/smac040

31.

Shulman

H. B.

D’Angelo

D. V.

Harrison

Smith

R. A.

Warner

(2018). The pregnancy risk assessment monitoring system (PRAMS): Overview of design and methodology. American Journal of Public Health, 108(10), 1305–1313. https://ajph.aphapublications.org/doi/full/10.2105/AJPH.2018.304563

32.

Smith

A. K.

Ayanian

J. Z.

Covinsky

K. E.

Landon

B. E.

McCarthy

E. P.

Wee

C. C.

Steinman

M. A.

(2011). Conducting high-value secondary dataset analysis: An introductory guide and resources. Journal of General Internal Medicine, 26(8), 920–929. https://doi.org/10.1007/s11606-010-1621-5

33.

Smith

P. J.

Battaglia

M. P.

Huggins

V. J.

Hoaglin

D. C.

Rodén

A.-S.

Khare

Ezzati-Rice

T. M.

Wright

R. A.

(2001). Overview of the sampling design and statistical methods used in the National Immunization Survey. American Journal of Preventive Medicine, 20(4, Suppl. 1), 17–24. https://doi.org/10.1016/S0749-3797(01)00285-9

34.

Tripathy

J. P.

(2013). Secondary data analysis: Ethical issues and challenges. Iranian Journal of Public Health, 42(12), 1478–1479.

35.

U.S. Centers for Disease Control and Prevention, & National Center for Health Statistics. (n.d.). NHANES survey methods and analytic guidelines. NHANES Survey Methods and Analytic Guidelines. Retrieved November 11, 2024, from https://wwwn.cdc.gov/nchs/nhanes/analyticguidelines.aspx

36.

Vartanian

(2010). Secondary data analysis. Oxford Academic. Oxford University Press. https://global.oup.com/academic/product/secondary-data-analysis-9780195388817?cc=us&lang=en&

37.

Victora

C. G.

Bahl

Barros

A. J. D.

França

G. V. A.

Horton

Krasevec

Murch

Sankar

M. J.

Walker

Rollins

N. C.

& Lancet Breastfeeding Series Group. (2016). Breastfeeding in the 21st century: Epidemiology, mechanisms, and lifelong effect. Lancet, 387(10017), 475–490. https://doi.org/10.1016/S0140-6736(15)01024-7

38.

von Elm

Altman

D. G.

Egger

Pocock

S. J.

Gøtzsche

P. C.

Vandenbroucke

J. P

. (2007). Strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. British Medical Journal, 335(7624), 806. https://doi.org/10.1136/bmj.39335.541782.AD

39.

Washio

Raines

A. L.

Pei

Taylor

S. N.

Zhang

(2023). The association of maternal smoking and drinking changes during pregnancy and postpartum breastfeeding pattern and duration. Breastfeeding Medicine, 18(6), 449–461. https://doi.org/10.1089/bfm.2022.0130