Family composition and age at menarche: findings from the international Health Behaviour in School-Aged Children Study

This research was funded by The University of St Andrews and NHS Health Scotland.Background Early menarche has been associated with father absence, stepfather presence and adverse health consequences in later life. This article assesses the association of different family compositions with the age at menarche. Pathways are explored which may explain any association between family characteristics and pubertal timing. Methods Cross-sectional, international data on the age at menarche, family structure and covariates (age, psychosomatic complaints, media consumption, physical activity) were collected from the 2009–2010 Health Behaviour in School-aged Children (HBSC) survey. The sample focuses on 15-year old girls comprising 36,175 individuals across 40 countries in Europe and North America (N = 21,075 for age at menarche). The study examined the association of different family characteristics with age at menarche. Regression and path analyses were applied incorporating multilevel techniques to adjust for the nested nature of data within countries. Results Living with mother (Cohen’s d = .12), father (d = .08), brothers (d = .04) and sisters (d = .06) are independently associated with later age at menarche. Living in a foster home (d = −.16), with ‘someone else’ (d = −.11), stepmother (d = −.10) or stepfather (d = −.06) was associated with earlier menarche. Path models show that up to 89% of these effects can be explained through lifestyle and psychological variables. Conclusions Earlier menarche is reported amongst those with living conditions other than a family consisting of two biological parents. This can partly be explained by girls’ higher Body Mass Index in these families which is a biological determinant of early menarche. Lower physical activity and elevated psychosomatic complaints were also more often found in girls in these family environments.Publisher PDFPeer reviewe

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Flawed MIREC fluoride and intelligence quotient publications: A failed attempt to undermine community water fluoridation

Objective: To assess the evidence presented in a set of articles that use the Canadian Maternal–Infant Research on Environmental Chemicals (MIREC) study database to claim that community water fluoridation (CWF) is associated with harm to foetal and infant cognitive development. Methods: Critical appraisal of measurements and processes in the MIREC database, and articles derived therefrom. MIREC's cohort is approximately 2000 pregnant women recruited in 10 centres across Canada, 2008–2011, leading to measuring 512 children aged 3–6 years in six cities. Fluoride exposure was measured by city fluoridation status, self‐reports and maternal spot urine samples. Intelligence Quotient (IQ) was measured using the Wechsler Preschool and Primary Scale of Intelligence (WPPSI‐III) by different assessors in each city. Results: MIREC's fluoride and IQ measurements are invalid and therefore cannot support the claim that CWF is associated with IQ decline in children. Conclusions: The MIREC fluoride‐IQ articles' results should be considered unacceptable for legal and policy purposes; other water fluoridation studies and systematic reviews show no effect of fluoridation on cognition

The Impact of Meanders, Deepening and Broadening, and Seasonality on Agulhas Current Temperature Variability

AbstractFor the first time, the temperature transport of the Agulhas Current is quantified in a time series. Over a 25-month mooring deployment at 34°S, seven tall moorings were instrumented to measure current velocity, temperature, and salinity. Current- and pressure-recording inverted echosounders were used to extend geostrophic velocity, temperature, and salinity records to 300 km offshore. In the mean, the current transports 3.8 PW of heat southward relative to 0°C: −76 Sv (1 Sv ≡ 106 m3 s−1) at a transport-weighted temperature of 12.3°C. A 0.9-PW standard deviation in temperature transport is due to variability in both volume transport and the temperature field. Meandering of the current core dominates variability in the temperature field by warming temperatures offshore and cooling temperatures near the coast. However, meandering has a limited impact on the temperature transport, which varies more closely with a deepening and broadening of the current associated with an inshore isotherm shoaling and an offshore isotherm deepening. Stronger southward temperature transports correspond to a deeper current transporting more volume, yet at a cooler transport-weighted temperature. Seasonality is not observed in the temperature transport time series, possibly because of the offsetting effects of cooler temperatures during times of seasonally stronger volume transports. Although volume transport and temperature transport are highly correlated, the large variability in transport-weighted temperature means that using volume transport alone to infer temperature transport results in an error that could be as large as 24% of the southern Indian Ocean heat transport

The impact of meanders, deepening and broadening, and seasonality on Agulhas current temperature variability

For the first time, the temperature transport of the Agulhas Current is quantified in a time series. Over a 25-month mooring deployment at 34°S, seven tall moorings were instrumented to measure current velocity, temperature, and salinity. Current- and pressure-recording inverted echosounders were used to extend geostrophic velocity, temperature, and salinity records to 300 km offshore. In the mean, the current transports 3.8 PW of heat southward relative to 0°C: −76 Sv (1 Sv ≡ 106 m3 s−1) at a transport-weighted temperature of 12.3°C. A 0.9-PW standard deviation in temperature transport is due to variability in both volume transport and the temperature field. Meandering of the current core dominates variability in the temperature field by warming temperatures offshore and cooling temperatures near the coast. However, meandering has a limited impact on the temperature transport, which varies more closely with a deepening and broadening of the current associated with an inshore isotherm shoaling and an offshore isotherm deepening. Stronger southward temperature transports correspond to a deeper current transporting more volume, yet at a cooler transport-weighted temperature. Seasonality is not observed in the temperature transport time series, possibly because of the offsetting effects of cooler temperatures during times of seasonally stronger volume transports. Although volume transport and temperature transport are highly correlated, the large variability in transport-weighted temperature means that using volume transport alone to infer temperature transport results in an error that could be as large as 24% of the southern Indian Ocean heat transport

CORRIGENDUM: The impact of meanders, deeping and broadening, and seasonality on Agulhas Current temperature variability (v.50, pg3529, 2020)

Importantly, the error had negligible impact on the variability of the velocity, volume transport, and temperature transport and thus does not affect the main conclusions of the paper. Colors and thin contours show temperature, with each contour corresponding to 1°C. Thick contours show cross-track velocity, with each contour corresponding to 0.25 m s−1. (c) Meander time series, as measured by sea level anomaly at 33.6°S, 28°E. Meanders are defined as times during which the SLA is lower than −0.2 m (gray shading). Colors and thin contours show temperature, with each contour corresponding to 1°C. Thick contours show cross-track velocity, with each contour corresponding to 0.25 m s−1. (c) Meander time series, as measured by sea level anomaly at 33.6°S, 28°E. Meanders are defined as times during which the SLA is lower than −0.2 m (gray shading). Colors and thin contours show temperature, with each contour corresponding to 1°C. Thick contours show cross-track velocity, with each contour corresponding to 0.25 m s−1. (c) Meander time series, as measured by sea level anomaly at 33.6°S, 28°E. Meanders are defined as times during which the SLA is lower than −0.2 m (gray shading). Fig. 7. (a) Composite temperature (colors) and velocity (thick contours) of the strongest 10% of southward box temperature transport times, excluding meander times. (b) Composite of the weakest 10% of southward box temperature transport times, excluding meander times. (c) The difference between the composites of strong minus weak temperature transport. (d) Time series of the box volume transport above 1000 m [Sv; blue (left axis)] and the square of the difference of depth between the 10°C isotherm at 20 km and at 219 km offshore [m2; red (right axis)]. Fig. 7. (a) Composite temperature (colors) and velocity (thick contours) of the strongest 10% of southward box temperature transport times, excluding meander times. (b) Composite of the weakest 10% of southward box temperature transport times, excluding meander times. (c) The difference between the composites of strong minus weak temperature transport. (d) Time series of the box volume transport above 1000 m [Sv; blue (left axis)] and the square of the difference of depth between the 10°C isotherm at 20 km and at 219 km offshore [m2; red (right axis)]. Fig. 7. (a) Composite temperature (colors) and velocity (thick contours) of the strongest 10% of southward box temperature transport times, excluding meander times. (b) Composite of the weakest 10% of southward box temperature transport times, excluding meander times. (c) The difference between the composites of strong minus weak temperature transport. (d) Time series of the box volume transport above 1000 m [Sv; blue (left axis)] and the square of the difference of depth between the 10°C isotherm at 20 km and at 219 km offshore [m2; red (right axis)]. The corresponding principal component time series are shown in Fig. 11, below. (a) The first EOF of the temperature field, describing 40% of the variance. (b) The second EOF of the temperature field, describing 25% of the variance. (c) The third EOF of the temperature field, describing 15% of the variance. (d) The pointwise correlation coefficient between principal component 2 and the cross-track velocity. The corresponding principal component time series are shown in Fig. 11, below. (a) The first EOF of the temperature field, describing 40% of the variance. (b) The second EOF of the temperature field, describing 25% of the variance. (c) The third EOF of the temperature field, describing 15% of the variance. (d) The pointwise correlation coefficient between principal component 2 and the cross-track velocity. The corresponding principal component time series are shown in Fig. 11, below. (a) The first EOF of the temperature field, describing 40% of the variance. (b) The second EOF of the temperature field, describing 25% of the variance. (c) The third EOF of the temperature field, describing 15% of the variance. (d) The pointwise correlation coefficient between principal component 2 and the cross-track velocity

Factors Associated With Diabetic Ketoacidosis at Onset of Type 1 Diabetes Among Pediatric Patients: A Systematic Review.

ImportancePresenting with diabetic ketoacidosis (DKA) at onset of type 1 diabetes (T1D) remains a risk. Following a 2011 systematic review, considerable additional articles have been published, and the review required updating.ObjectiveTo evaluate factors associated with DKA at the onset of T1D among pediatric patients.Evidence reviewIn this systematic review, PubMed, Embase, Scopus, CINAHL, Web of Science, and article reference lists were searched using the population, intervention, comparison, outcome search strategy for primary research studies on DKA and T1D onset among individuals younger than 18 years that were published from January 2011 to November 2021. These studies were combined with a 2011 systematic review on the same topic. Data were pooled using a random-effects model.FindingsA total of 2565 articles were identified; 149 were included, along with 46 from the previous review (total 195 articles). Thirty-eight factors were identified and examined for their association with DKA at T1D onset. Factors associated with increased risk of DKA were younger age at T1D onset (Conclusions and relevanceIn this study, age younger than 2 years at T1D onset, belonging to an ethnic minority population, delayed diagnosis or misdiagnosis, and presenting during the COVID-19 pandemic were associated with increased risk of DKA. Factors associated with decreased risk of DKA included greater knowledge of key signs or symptoms of DKA, such as a family history of T1D or participation in screening programs. Future work should focus on identifying and implementing strategies related to these factors to reduce risk of DKA among new patients with T1D

Weighted Chi-square test of association between uptake of HIV testing and respondents’ characteristics.

<p>Weighted Chi-square test of association between uptake of HIV testing and respondents’ characteristics.</p

Logistic Regression Models HIV testing by Participants' Demographic and Reproductive Health Characteristics.

<p>Logistic Regression Models HIV testing by Participants' Demographic and Reproductive Health Characteristics.</p

Demographic and health characteristics of participants.

<p>Demographic and health characteristics of participants.</p