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Birth Intervals and Health in Adulthood: A Comparison of Siblings Using Swedish Register Data.

ABSTRACT: A growing body of research has examined whether birth intervals influence perinatal outcomes and child health as well as long-term educational and socioeconomic outcomes. To date, however, very little research has examined whether birth spacing influences long-term health. We use contemporary Swedish population register data to examine the relationship between birth-to-birth intervals and a variety of health outcomes in adulthood: for men, height, physical fitness, and the probability of falling into different body mass index categories; and for men and women, mortality. In models that do not adjust carefully for family background, we find that short and long birth intervals are clearly associated with height, physical fitness, being overweight or obese, and mortality. However, after carefully adjusting for family background using a within-family sibling comparison design, we find that birth spacing is generally not associated with long-term health, although we find that men born after very long birth intervals have a higher probability of being overweight or obese in early adulthood. Overall, we conclude that birth intervals have little independent effect on long-term health outcomes.

SUBMITTER: Barclay KJ

PROVIDER: S-EPMC5992250 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Birth Intervals and Health in Adulthood: A Comparison of Siblings Using Swedish Register Data.

Barclay Kieron J KJ Kolk Martin M

Demography 20180601 3

A growing body of research has examined whether birth intervals influence perinatal outcomes and child health as well as long-term educational and socioeconomic outcomes. To date, however, very little research has examined whether birth spacing influences long-term health. We use contemporary Swedish population register data to examine the relationship between birth-to-birth intervals and a variety of health outcomes in adulthood: for men, height, physical fitness, and the probability of falling ...[more]

PMID: 29785527

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Project description:IntroductionThe Swedish Register of Palliative Care (SRPC) is a national quality register that collects data about end-of-life care from healthcare providers that care for dying patients. Data are used for quality control and research. Data are mainly collected with an end-of-life questionnaire (ELQ), which is completed by healthcare staff after the death of a patient. A previous validity assessment of the ELQ showed insufficient validity in some items including symptom relief. The aim of this study was to examine the validity of the revised ELQ.Materials and methodsData from 100 consecutive patients' medical records at two specialised palliative care units were used to complete new ELQs, which were then compared to the ELQ registrations from the SRPC for the same patients. The level of agreement was calculated for each ELQ item. To account for the possibility of the agreement occurring by chance, Cohen's kappa was calculated for suitable items. To examine the extent of registration mistakes when transferring the paper form to the web, the original paper versions of the ELQ filled out at the units were compared to data from the ELQs reported to the SRPC.ResultsLevel of agreement between ELQ registrations from the SRPC and the new ELQs based on the medical records varied between 0.55 and 1.00, where 24 items showed level of agreement above 0.80 and 9 items showed level of agreement below 0.80. Cohen's kappa with 95% confidence intervals was calculated for 24 items. The kappa values showed that two items had poor agreement, four fair agreement, 11 moderate agreement, five good agreement and two very good agreement. The level of agreement varied between 0.93 and 1.00 when comparing the ELQ registrations in the SRPC and the paper forms.ConclusionThe revised ELQ contains more items with high levels of agreement between registrations in the SRPC and notes in the patients' medical records when compared to the previous version. Validating issues around symptom assessment remains a challenge in our model of quality assessment.

Project description:BackgroundIn cohorts with voluntary participation, participants may not be representative of the underlying population, leading to distorted estimates. If the relevant sources of selective participation are observed, it is however possible to restore the representativeness by reweighting the sample to resemble the target population. So far, few studies in epidemiology have applied reweighting based on extensive register data on socio-demographics and disease history, or with self-reported data on health and health-related behaviors.MethodsWe examined selective participation at baseline and the first two follow-ups of the Scania Public Health Cohort (SPHC), a survey conducted in Southern Sweden in 1999/2000 (baseline survey; n = 13,581 participants, 58% participation rate), 2005 (first follow-up, n = 10,471), and 2010 (second follow-up; n = 9,026). Survey participants were reweighted to resemble the underlying population with respect to a broad range of socio-demographic, disease, and health-related characteristics, and we assessed how selective participation impacted the validity of associations between self-reported overall health and dimensions of socio-demographics and health.ResultsParticipants in the baseline and follow-up surveys were healthier and more likely to be female, born in Sweden, middle-aged, and have higher socioeconomic status. However, the differences were not very large. In turn, reweighting the samples to match the target population had generally small or moderate impacts on associations. Most examined regression coefficients changed by less than 20%, with virtually no changes in the directions of the effects.ConclusionOverall, selective participation with respect to the observed factors was not strong enough to substantially alter the associations with self-assessed health. These results are consistent with an interpretation that SPHC has high validity, perhaps reflective of a relatively high participation rate. Since validity must be determined on a case-by-case basis, however, researchers should apply the same method to other health cohorts to assess and potentially improve the validity.

Project description:BACKGROUND:Preterm birth has previously been linked with cardiovascular disease (CVD) in adulthood. However, associations with lipid disorders (e.g., high cholesterol or triglycerides), which are major risk factors for CVD, have seldom been examined and are conflicting. Clinicians will increasingly encounter adult survivors of preterm birth and will need to understand the long-term health sequelae. We conducted the first large population-based study to determine whether preterm birth is associated with an increased risk of lipid disorders. METHODS AND FINDINGS:A retrospective national cohort study was conducted of all 2,235,012 persons born as singletons in Sweden during 1973 to 1995 (48.6% women), who were followed up for lipid disorders identified from nationwide inpatient, outpatient, and pharmacy data through 2016 (maximum age 44 years). Cox regression was used to adjust for other perinatal and maternal factors, and co-sibling analyses assessed the potential influence of unmeasured shared familial (genetic and/or environmental) factors. A total of 25,050 (1.1%) persons were identified with lipid disorders in 30.3 million person-years of follow-up. Each additional 5 weeks of gestation were associated with a 14% reduction in risk of lipid disorders (adjusted hazard ratio [HR], 0.86; 95% CI, 0.83-0.89; P < 0.001). Relative to full-term birth (gestational age 39-41 weeks), the adjusted HR associated with preterm birth (<37 weeks) was 1.23 (95% CI, 1.16-1.29; P < 0.001), and further stratified was 2.00 (1.41-2.85; P < 0.001) for extremely preterm (22-27 weeks), 1.33 (1.19-1.49; P < 0.001) for very preterm (28-33 weeks), and 1.19 (1.12-1.26; P < 0.001) for late preterm (34-36 weeks). These findings were similar in men and women (e.g., preterm versus full-term, men: HR, 1.22; 95% CI, 1.14-1.31; P < 0.001; women: HR, 1.23; 1.12-1.32; P < 0.001). Co-sibling analyses suggested that they were substantially though not completely explained by shared genetic or environmental factors in families. The main study limitation was the unavailability of laboratory data to assess specific types or severity of lipid disorders. CONCLUSIONS:In this large national cohort, preterm birth was associated with an increased risk of lipid disorders in early- to midadulthood. Persons born prematurely may need early preventive evaluation and long-term monitoring for lipid disorders to reduce their future cardiovascular risks.

Project description:ObjectivesThis study aims to estimate the association between pregnancy-associated maternal cancers, diagnosed both prenatally and postnatally, and birth outcomes.DesignPopulation-based register study.SettingNational registers of Denmark and Sweden.ParticipantsA total of 5 523 365 children born in Denmark (1977-2008) and Sweden (1973-2006).Primary and secondary outcome measures: gestational age, birth weight, size for gestational age, Apgar score, caesarean section and sex were the outcomes of interest. ORs and relative risk ratios (RRR) with 95% CIs were estimated using logistic regression and multinomial logistic regression, respectively.ResultsIn this study, 2% of children were born to mothers with a diagnosis of cancer. Children whose mothers received a prenatal cancer diagnosis had higher risk of being born preterm (RRR: 1.77, 95%?CI 1.64 to 1.90); low birth weight (RRR 1.84, 95%?CI 1.69 to 2.01); low Apgar score (OR 1.36, 95%?CI 1.20 to 1.56); and by caesarean section (OR: 1.69, 95%?CI 1.59 to 1.80). Associations moved towards the null for analyses using postnatal diagnoses, but preterm birth (RRR: 1.13, 95%?CI 1.09 to 1.17) and low birth weight (RRR: 1.14, 95%?CI 1.09 to 1.18) remained statistically significant, while risk of caesarean section became so (OR: 0.95, 95%?CI 0.91 to 0.98). Additionally, statistical significance was reached for large for gestational age (RRR: 1.06, 95%?CI 1.01 to 1.11), high birth weight (RRR: 1.04, 95%?CI 1.01 to 1.06) and caesarean section (OR: 0.95, 95%?CI 0.91 to 0.98).ConclusionsResults suggest an association between pregnancy-associated cancers and adverse birth outcomes in the offspring. While this is strongest for prenatally diagnosed cancers, some smaller associations exist for postnatally diagnosed cancers, indicating that cancer itself could affect fetal development, or that cancer and adverse birth outcomes share risk factors. Future studies on maternal cancer during pregnancy should consider including some postnatal years in their exposure window.

Project description:Machine learning algorithms hold potential for improved prediction of all-cause mortality in cardiovascular patients, yet have not previously been developed with high-quality population data. This study compared four popular machine learning algorithms trained on unselected, nation-wide population data from Sweden to solve the binary classification problem of predicting survival versus non-survival 2 years after first myocardial infarction (MI).This prospective national registry study for prognostic accuracy validation of predictive models used data from 51,943 complete first MI cases as registered during 6 years (2006-2011) in the national quality register SWEDEHEART/RIKS-HIA (90% coverage of all MIs in Sweden) with follow-up in the Cause of Death register (> 99% coverage). Primary outcome was AUROC (C-statistic) performance of each model on the untouched test set (40% of cases) after model development on the training set (60% of cases) with the full (39) predictor set. Model AUROCs were bootstrapped and compared, correcting the P-values for multiple comparisons with the Bonferroni method. Secondary outcomes were derived when varying sample size (1-100% of total) and predictor sets (39, 10, and 5) for each model. Analyses were repeated on 79,869 completed cases after multivariable imputation of predictors.A Support Vector Machine with a radial basis kernel developed on 39 predictors had the highest complete cases performance on the test set (AUROC = 0.845, PPV = 0.280, NPV = 0.966) outperforming Boosted C5.0 (0.845 vs. 0.841, P = 0.028) but not significantly higher than Logistic Regression or Random Forest. Models converged to the point of algorithm indifference with increased sample size and predictors. Using the top five predictors also produced good classifiers. Imputed analyses had slightly higher performance.Improved mortality prediction at hospital discharge after first MI is important for identifying high-risk individuals eligible for intensified treatment and care. All models performed accurately and similarly and because of the superior national coverage, the best model can potentially be used to better differentiate new patients, allowing for improved targeting of limited resources. Future research should focus on further model development and investigate possibilities for implementation.

Dataset Information

Birth Intervals and Health in Adulthood: A Comparison of Siblings Using Swedish Register Data.

Publications

Birth Intervals and Health in Adulthood: A Comparison of Siblings Using Swedish Register Data.

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