Background
Methods
Systematic review
Search strategy
Study selection
Data extraction and synthesis
Risk of bias assessment
Bradford Hill criteria for causation
Economic evaluation
Results
Systematic review
Search results
Summary of included studies
Author, country, and year | Study population and % women | Age of study population (mean ± SD) | Hip OA or hip pathologies related to hip OA | Prevalence % outcome (OA, DDH, α-angle, hip deformity) (men, women) | Follow-up time (mean ± SD) | Quality of studya |
---|---|---|---|---|---|---|
Hip bone shape abnormality | ||||||
Case-control study | ||||||
Chan et al., Australia, 1997 [35] | All live births during 1986–93 n = 151,257 47% | 28 days to 5 years | Self-reported DDH, birth registry | 0.75% DDH | N/A | Low |
Cross-sectional studies | ||||||
Orak et al., Turkey, 2015 [37] | Infants born in one hospital n = 467 44% | Preterm 31.11 ± 2.51 weeks Term 40.22 ± 0.36 weeks | α-angle < 60 ° of the hip joint suggestive of immature or pathologic hip | NR | N/A | Low |
Davis et al., UK, 1993 [36] | Infants born in one hospital n = 33 55% | 3–4.5 years | Hip deformity by footprint angle and hip rotation | NR | N/A | Low |
Hip OA | ||||||
Cohort studies | ||||||
Hussain et al., Australia 2015 [32] | n = 3604 participants 60% | No arthroplasty 51.8 ± 10.0 Hip arthroplasty 59.0 ± 9.5 | Hip arthroplasty for hip OA | 2.1% | 9.3 ± 2.1 | High |
Clynes et al., UK 2014 [34] | n = 444 50% | Median 75 years (IQR 73–77) | American College of Rheumatology algorithm to define hip OA Radiographic Kellgren and Lawrence (KL) score of hip to count osteophytes | Men 3.2% Women 6.0% | 13 years | Fair |
Assessment of hip pathology and hip OA
Assessment of low birth weight or preterm birth
Prevalence of hip bone abnormality and hip OA
Risk of bias
Association between LBW or preterm birth and hip bone abnormality
Author and year | Low birth weight/preterm measurement | Confounder adjusted for | Results | Conclusion |
---|---|---|---|---|
Hip bone shape abnormality | ||||
Case-control study | ||||
Chan et al., 1997 [35] | Birth weight from the birth registry | Maternal age, region of residence, parity, oligohydramnios, presentation and method of delivery, baby’s sex, birth weight, gestation | Low birth weight and DDH, where birth weight 3000–3500 g is referent Birth weight < 2000 g OR 0.30 (95% CI 0.12–0.77) Birth weight 2000–2500 g OR 0.52 (95% CI 0.31–0.88) | Those who were born with low birth weight (< 2500 g) were less likely to develop DDH |
Cross-sectional studies | ||||
Orak et al., 2015 [37] | Hospital-recorded birth weight | Unadjusted | Preterm born and α-angle of the hip joint suggestive of immature or pathologic hip Preterm born babies with α-angle < 60 ° = 2.7% Full-term born babies with α-angle < 60 ° = 28.5% (p < 0.001, Fisher’s exact test) | These results suggest that prematurity is not a predisposing factor for immature hip predictive of DDH |
Davis et al., 1993 [36] | Hospital-recorded birth weight | Unadjusted | Low birth weight and preterm birth with hip deformity Out-toeing 62% in low birth weight vs 35% in the term babies Total rotation of hip preterm group 119.20 (19.6) vs term group 99.20 (9.6) (p < 0.003) | Deformation of the lower limb including hip frequently seen in preterm babies during early infancy |
Hip OA | ||||
Cohort studies | ||||
Hussain et al., 2015 [32] | Self-reported birth weight and whether born ≥ 2 weeks preterm | Age, sex, BMI, hypertension, diabetes mellitus, smoking, and physical activity | Low birth weight and hip arthroplasty HR 2.02 (95% CI 1.10–3.73) Preterm birth HR 2.53 (95% CI 1.30–4.92) | Individuals born with LBW or at preterm are at increased risk of hip arthroplasty for OA in adult life |
Clynes et al., 2014 [34] | Birth weight from the birth registry | Age, sex, BMI, smoking and alcohol | Lower birth weight and radiographic hip OA OR 0.78 (95% CI 0.48–1.27) Lower birth weight andosteophytes in hip OR 1.51 (95% CI 1.13–2.01) | Individuals with lower birth weights were more likely to have hip osteophytes but not hip arthritis |
Association between LBW or preterm birth and hip OA
Evidence for causation using the Bradford Hill criteria for causation
Bradford Hill criterion and description | Hip osteoarthritis |
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Temporal relationship This is an essential criterion. For a possible risk factor to be the cause of a disease, it must come before the disease. This is generally easier to establish from cohort studies than from cross-sectional or case-control studies, when measurements of the possible cause and the effect are made at the same time | Criterion met: Yes Hussain et al. [32] In a cohort study people born with low birth weight (LBW) or preterm underwent hip arthroplasty for hip osteoarthritis (OA) at an average age of 59.0 (standard deviation (SD) 9.5) years Clynes et al. [34] Participants of the Hertfordshire Cohort Study who were born LBW had more osteophytes in the hip joint detected by x-ray at the age median of 75 (interquartile range (IQR) 73–77) years |
Plausibility A risk factor associated with a disease is more likely to be the cause of the disease if the association found is consistent with knowledge obtained from other sources, such as animal experiments and experiments on biological mechanisms. However, this criterion must be used with care as a lack of plausibility may simply reflect a lack of scientific knowledge | Criterion met: No |
Consistency If similar results have been found in different populations using different study designs, the association is more likely to be causal as it is unlikely that all studies were subject to the same types of errors (chance, bias or confounding). However, a lack of consistency does not exclude a causal association, as different exposure levels and other conditions may reduce the impact of the causal factor in certain studies | Criterion met: Yes |
Strength of an association The strength of an association is measured by the size of the relative risk. A strong association is more likely than a weak association to be causal, as a weak association could more easily be the result of confounding or bias | Criterion met: Yes A strong association was observed in one study [32] |
Dose-response relationship Further evidence of a causal relationship is provided if increasing levels of exposure lead to an increasing risk of disease | Criterion met: Yes A dose-response relationship was observed in one study [34] |
Specificity If a particular exposure increases the risk of a certain disease but not the risk of other diseases, this is strong evidence in favour of a cause-effect relationship. However, one-to-one relationships between exposure and disease are rare, and lack of specificity should not be used to say that a relationship is causal | Criterion met: Yes |
Reversibility When the removal of a possible risk factor results in a reduced risk of disease, the likelihood that this association is causal is increased. Ideally, this should be assessed by conducting a randomized intervention trial. For many exposures or diseases, such randomised trials are not possible in practice | Criterion met: Not applicable for this condition |
Coherence The suggested cause-effect relationship should essentially be consistent with the natural history and biology of the disease | Criterion met: No |
Analogy The causal relationship will be further supported if there are similarities with other (well-established) cause-effect relationships | Criterion met: Yes |
Modelling the economic burden
Year | Number of births | Low birth weight birthsa (%b) | Pre-term birthsc (%b) |
---|---|---|---|
2009 | 296,791 | 18,347 (6.2) | 22,645 (7.6) |
2010 | 297,357 | 18,522 (6.2) | 22,952 (7.7) |
2011 | 299,588 | 18,829 (6.3) | 23,282 (7.8) |
2012 | 309,861 | 19,243 (6.2) | 24,671 (8.0) |
2013 | 307,277 | 19,597 (6.4) | 24,582 (8.0) |
2014 | 310,330 | 19,833 (6.4) | 24,826 (8.0) |