Maternal Cigarette Smoking and Congenital Upper and Lower Limb Differences: A Systematic Review and Meta-Analysis.

Maternal smoking during pregnancy has been associated with adverse effects on foetal development, including congenital limb anomalies. This systematic review aimed to provide an updated assessment of the association between maternal smoking during pregnancy and the risk of congenital limb anomalies. A systematic search was conducted to identify relevant studies published up to February 2023. Studies reporting on the relationship between maternal smoking during pregnancy and congenital digital anomalies or congenital limb reduction defects were included. Two independent reviewers screened the studies, extracted data, and assessed the quality of the included studies. Meta-analyses were performed to estimate the pooled odds ratios with 95% confidence intervals using fixed and random-effects models. In total, 37 publications comprising 11 cohort and 26 case-control studies were included in the systematic review. The meta-analysis demonstrated a significant increased risk of congenital limb reduction defects (pooled OR: 1.27, 95% CI: 1.18-1.38) in infants born to mothers who smoked during pregnancy. Similarly, a significant relationship was observed for the development of polydactyly/syndactyly/adactyly when considered as a single group (pooled OR: 1.32, 95% CI: 1.25-1.40). Yet, in contrast, no significant association was observed when polydactyly (pooled OR: 1.06, 95% CI: 0.88-1.27) or syndactyly (pooled OR: 0.91, 95% CI: 0.77-1.08) were considered individually. This systematic review provides updated evidence of a significant relationship between maternal smoking during pregnancy and increased risk of congenital limb anomalies. These findings highlight the potential detrimental effects of smoking on foetal limb development and underscore the importance of smoking cessation interventions for pregnant women to mitigate these risks.

The contribution of musculoskeletal factors to physical frailty: a cross-sectional study.

BACKGROUND: Musculoskeletal conditions and physical frailty have overlapping constructs. We aimed to quantify individual contributions of musculoskeletal factors to frailty. METHODS: Participants included 347 men and 360 women aged ≥60 yr (median ages; 70.8 (66.1-78.6) and 71.0 (65.2-77.5), respectively) from the Geelong Osteoporosis Study. Frailty was defined as ≥3, pre-frail 1-2, and robust 0, of the following; unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Measures were made of femoral neck BMD, appendicular lean mass index (ALMI, kg/m2) and whole-body fat mass index (FMI, kg/m2) by DXA (Lunar), SOS, BUA and SI at the calcaneus (Lunar Achilles Insight) and handgrip strength by dynamometers. Binary and ordinal logistic regression models and AUROC curves were used to quantify the contribution of musculoskeletal parameters to frailty. Potential confounders included anthropometry, smoking, alcohol, prior fracture, FMI, SES and comorbidities. RESULTS: Overall, 54(15.6%) men and 62(17.2%) women were frail. In adjusted-binary logistic models, SI, ALMI and HGS were associated with frailty in men (OR = 0.73, 95%CI 0.53-1.01; OR=0.48, 0.34-0.68; and OR = 0.11, 0.06-0.22; respectively). Muscle measures (ALMI and HGS) contributed more to this association than did bone (SI) (AUROCs 0.77, 0.85 vs 0.71, respectively). In women, only HGS was associated with frailty in adjusted models (OR = 0.30 95%CI 0.20-0.45, AUROC = 0.83). In adjusted ordinal models, similar results were observed in men; for women, HGS and ALMI were associated with frailty (ordered OR = 0.30 95%CI 0.20-0.45; OR = 0.56, 0.40-0.80, respectively). CONCLUSION: Muscle deficits appeared to contribute more than bone deficits to frailty. This may have implications for identifying potential musculoskeletal targets for preventing or managing the progression of frailty.

The Predictability of Frailty Associated with Musculoskeletal Deficits: A Longitudinal Study.

We investigated and quantified the predictability of frailty associated with musculoskeletal parameters. This longitudinal study included 287 men aged ≥ 50 yr at baseline (2001-2006) from the Geelong Osteoporosis Study. Baseline musculoskeletal measures included femoral neck bone mineral density (BMD), appendicular lean mass index (ALMI, kg/m2) and whole-body fat mass index (FMI, kg/m2) and lower-limb strength. Frailty at the 15 yr-follow-up (2016-2019) was defined as ≥ 3 and non-frail as < 3, of the following: unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Binary regression models and AUROC curves quantified the attributable risk of musculoskeletal factors to frailty and their predictive ability. Potential confounders included anthropometry, smoking, alcohol, FMI, socioeconomic status and comorbidities. Forty-eight (16.7%) men were frail at 15 yr-follow-up. Musculoskeletal models were better predictors of frailty compared to the referent (confounders only) model (AUROC for musculoskeletal factors 0.74 vs 0.67 for the referent model). The model with the highest AUROC (0.74; 95% CI 0.66-0.82) included BMD, ALMI and muscle strength (hip abductors) and was better than the referent model that included only lifestyle factors (p = 0.046). Musculoskeletal parameters improved the predictability model as measured by AUROC for frailty after 15 years. In general, muscle models performed better compared to bone models. Musculoskeletal parameters improved the predictability of frailty of the referent model that included lifestyle factors. Muscle deficits accounted for a greater proportion of the risk for frailty than did bone deficits. Targeting musculoskeletal health could be a possible avenue of intervention in regards to frailty.

Bone material strength index is associated with prior fracture in men with and without moderate chronic kidney disease.

BACKGROUND: Patients with chronic kidney disease (CKD) are at high risk for fracture. The ability of bone mineral density (BMD) to predict fractures in CKD patients has been inconsistent. Other measures such as trabecular bone score (TBS) and impact microindentation (IMI) may be more useful in this group. This study aimed to determine if TBS or IMI values differed between men with and without CKD and examine associations between prior fracture, TBS and IMI values. METHODS: Men (n = 343, age 33-96 yr) from the Geelong Osteoporosis Study were included. Femoral neck (FNBMD) and lumbar spine BMD (LSBMD) were measured using DXA (Lunar ProdigyPro). TBS was determined from lumbar spine scans (TBS iNsight software Version 2.2). IMI values (bone material strength index; BMSi) were measured using an OsteoProbe. CKD was defined as an eGFR<60 mL/min/1.73m2 (n = 53). Prior low trauma fractures (n = 37) were ascertained from radiological reports. Associations were examined using binary logistic regression, adjusting for potential confounders. Interaction terms were tested in all models. RESULTS: Men with CKD tended to have a higher likelihood of prior fracture (adjusted OR 2.27, 95%CI 1.02-5.01). Higher BMSi was associated with a lower likelihood of prior fracture (adjusted OR for 1SD increase: 0.70; 95%CI 0.51-0.97). This association was sustained after adjustment for FNBMD (OR 0.68; 95%CI 0.49-0.96) or LSBMD (OR 0.69; 95%CI 0.49-0.95). No interaction was detected between BMSi and CKD (p = 0.898). No associations were detected between FNBMD, LSBMD or TBS and prior fracture in either population and there were no interactions with CKD for FNBMD, LSBMD or TBS. CONCLUSIONS: BMSi was associated with prior fracture in men with and without CKD, however, FNBMD, LSBMD and TBS were not. Lack of an interaction term suggests that BMSi performed similarly in identifying the likelihood of prior fracture, regardless of CKD status. IMI may have clinical utility for assessing fracture risk in patients with CKD.