Natalie Scime

Natalie Scime

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2019 in Journal of Affective Disorders
Verified
Journal Article
Closed access
NSNatalie Scime
Natalie Scime
AGAdam G. Gavarkovs
Adam G. Gavarkovs
KCKatie H. Chaput
Katie H. Chaput

18 October 2021 in BMJ Open
Verified
Journal Article
Open access
PDF file
PZPilar Zanoni
Pilar Zanoni
NSNatalie Scime
Natalie Scime
Karen BenziesKaren Benzies
Karen Benzies
DMDeborah A McNeil
Deborah A McNeil
KMKelly Mrklas
Kelly Mrklas
Objective: To evaluate the barriers and facilitators to implementing Alberta Family Integrated Care (AB-FICare [2019 Benzies]), a model of care for integrating parents into level II neonatal intensive care units (NICUs) care teams, from the perspective of healthcare providers (HCP) and hospital administrators.Design: Qualitative process evaluation substudy.Setting: Ten level II NICUs in six cities across Alberta, Canada.Participants: HCP and hospital administrators (n=32) who were involved in the cluster-randomised controlled trial of AB-FICare in level II NICUs.Methods: Post-implementation semi-structured interviews were conducted via phone or in-person. The Consolidated Framework for Implementation Research was used to develop interview guides, code transcripts and analyse data.Results: Key facilitators to implementation of AB-FICare included (1) a receptiveimplementation climate,(2)compatibilityof the intervention with individual and organisational practices, (3)available resourcesandaccess to knowledge and informationfor HCP and hospital administrators, (4) engagement ofkey stakeholdersacross the organisation, (5) engagement of and outcomes forintervention participants,and (6)reflecting and evaluatingon implementation progress and patient and family outcomes. Barriers were (1)design quality and packagingof the intervention, (2)relative priorityof AB-FICare in relation to other initiatives, and (3)learning climatewithin the organisation. Mixed influences on implementation depending on contextual factors were coded to eight constructs:intervention source, cost, peer pressure, external policy and incentives, staff needs and resources, structural characteristics, organisational incentives and rewards,andknowledge, beliefs and attitudes.Conclusions: The characteristics of an organisation and the implementation process had largely positive influences, which can be leveraged for implementation of AB-FICare in the NICU. We recommend site-specific consultations to mitigate barriers and assess how swing factors might impact implementation given the local context, with the goal that strategies can be put in place to manage their influence on implementation.Trial registration number: NCT02879799.

12 February 2022 in Acta Paediatrica
Verified
Journal Article
Closed access
PDF file
TBTalitha L. Bruney
Talitha L. Bruney
NSNatalie Scime
Natalie Scime
AMAda Madubueze
Ada Madubueze
KCKathleen H. Chaput
Kathleen H. Chaput

2 February 2023 in BMC Pregnancy and Childbirth
Verified
Journal Article
Open access
PDF file
NSNatalie Scime
Natalie Scime
AMAmy Metcalfe
Amy Metcalfe
ANAlberto Nettel-Aguirre
Alberto Nettel-Aguirre
KNKara Nerenberg
Kara Nerenberg
CSCynthia H. Seow
Cynthia H. Seow
KCKathleen H. Chaput
Kathleen H. Chaput
Background: Breastfeeding difficulties frequently exacerbate one another and are common reasons for curtailed breastfeeding. Women with chronic conditions are at high risk of early breastfeeding cessation, yet limited evidence exists on the breastfeeding difficulties that co-occur in these mothers. The objective of this study was to explore clusters of breastfeeding difficulties experienced up to 6 weeks postpartum among mothers with chronic conditions and to examine associations between chronic condition types and breastfeeding difficulty clusters. Methods: We analyzed 348 mothers with chronic conditions enrolled in a prospective, community-based pregnancy cohort study from Alberta, Canada. Data were collected through self-report questionnaires. We used latent class analysis to identify clusters of early breastfeeding difficulties and multinomial logistic regression to examine whether types of chronic conditions were associated with these clusters, adjusting for maternal and obstetric factors. Results: We identified three clusters of breastfeeding difficulties. The “physiologically expected” cluster (51.1% of women) was characterized by leaking breasts and engorgement (reference outcome group); the “low milk production” cluster (15.4%) was discerned by low milk supply and infant weight concerns; and the “ineffective latch” cluster (33.5%) involved latch problems, sore nipples, and difficulty with positioning. Endocrine (adjusted relative risk ratio [RRR] 2.34, 95% CI 1.10–5.00), cardiovascular (adjusted RRR 2.75, 95% CI 1.01–7.81), and gastrointestinal (adjusted RRR 2.51, 95% CI 1.11–5.69) conditions were associated with the low milk production cluster, and gastrointestinal (adjusted RRR 2.44, 95% CI 1.25–4.77) conditions were additionally associated with the ineffective latch cluster. Conclusion: Half of women with chronic conditions experienced clusters of breastfeeding difficulties corresponding either to low milk production or to ineffective latch in the first 6 weeks postpartum. Associations with chronic condition types suggest that connections between lactation physiology and disease pathophysiology should be considered when providing breastfeeding support.

19 March 2020 in The Journal of Maternal-Fetal & Neonatal Medicine
Verified
Journal Article
Closed access
NSNatalie Scime
Natalie Scime
Scott B PattenScott B Patten
Scott B Patten
STSuzanne C. Tough
Suzanne C. Tough
KCKatie H. Chaput
Katie H. Chaput
Background: The prevalence of chronic disease in pregnant women has consistently risen over the past two decades. Substantial evidence demonstrates that maternal chronic disease is associated with adverse medical outcomes like preterm birth, but less research has characterized postpartum outcomes such as infant feeding practices. It is recommended that infants be exclusively breastfed from birth to 6 months given the numerous health benefits it provides. Objective: To determine the association between maternal chronic disease and breastfeeding outcomes. Methods: We analyzed cross-sectional self-report data from the 2015/2016 Canadian Community Health Survey, restricted to women who gave birth within 2 years of data collection (n = 2100, rounded). The exposure was professionally diagnosed chronic physical disease (e.g. diabetes, arthritis, heart disease). The outcomes were breastfeeding non-initiation and early cessation of breastfeeding before 6 months. Multivariable logistic regression modeling was used to estimate adjusted odds ratios (AOR) with 95% confidence intervals (CIs). Estimates were bootstrapped and weighted to represent the national population. Results: Overall, 11.9% (95% CI 9.8–14.1) of women reported chronic disease, and were more likely to be single, be Canadian born, have low education, and be overweight/obese than women without chronic disease. The mean maternal age was approximately 30 years in both groups. Women with chronic disease had similar odds of breastfeeding non-initiation (AOR 0.96, 95% CI 0.54–1.71) and early cessation of any breastfeeding (AOR 1.40, 95% CI 0.82–2.40), but over twice the odds of early cessation of exclusive breastfeeding (AOR 2.48, 95% CI 1.49–4.12) compared to unaffected women. Conclusion: Mothers with chronic disease initiate and continue some form of breastfeeding to six months as often as their unaffected peers. However, they have substantially higher odds of ceasing exclusive breastfeeding before the recommended 6 months. Findings suggest a need to investigate the reasons for this disparity to ensure that appropriate breastfeeding support is available for women with chronic disease and their children.

14 August 2023 in Paediatric and Perinatal Epidemiology
Verified
Journal Article
Open access
SESeham Elmrayed
Seham Elmrayed
JPJahaira Pinto
Jahaira Pinto
STSuzanne Tough
Suzanne Tough
SMSheila W. McDonald
Sheila W. McDonald
NSNatalie Scime
Natalie Scime
TFTanis Fenton
Tanis Fenton
Background: Overweight and obesity and their consequent morbidities are important worldwide health problems. Some research suggests excess adiposity origins may begin in fetal life, but unknown is whether this applies to infants born preterm.Objective: The objective of the study was to assess the association between small for gestational age (SGA) birth and later adiposity and height among those born preterm.Data sources: MEDLINE, EMBASE and CINAHL until October 2022.Study selection and data extraction: Studies were included if they reported anthropometric (adiposity measures and height) outcomes for participants born preterm with SGA versus non‐SGA. Screening, data extraction and risks of bias assessments were conducted in duplicate by two reviewers.Synthesis: We meta‐analysed across studies using random‐effects models and explored potential heterogeneity sources.Results: Thirty‐nine studies met the inclusion criteria. In later life, preterm SGA infants had a lower body mass index (−0.66 kg/m2, 95% CI −0.79, −0.53; 32 studies, I2 = 16.7, n = 30,346), waist circumference (−1.20 cm, 95% CI −2.17, −0.23; 13 studies, I2 = 19.4, n = 2061), lean mass (−2.62 kg, 95% CI −3.45, 1.80; 7 studies, I2 = 0, n = 205) and height (−3.85 cm, 95% CI −4.73, −2.96; 26 studies, I2 = 52.6, n = 4174) compared with those preterm infants born non‐SGA. There were no differences between preterm SGA and preterm non‐SGA groups in waist/hip ratio, body fat, body fat per cent, truncal fat per cent, fat mass index or lean mass index, although power was limited for some analyses. Studies were rated at high risk of bias due to potential residual confounding and low risk of bias in other domains.Conclusions: Compared to their preterm non‐SGA peers, preterm infants born SGA have lower BMI, waist circumference, lean body mass and height in later life. No differences in adiposity were observed between SGA preterm infants and non‐SGA preterm infants.