Prevalence of arthritis according to age, sex and socioeconomic status in six low and middle income countries: analysis of data from the World Health Organization study on global AGEing and adult health (SAGE) Wave 1

Background

In higher income countries, social disadvantage is associated with higher arthritis prevalence; however, less is known about arthritis prevalence or determinants in low to middle income countries (LMICs). We assessed arthritis prevalence by age and sex, and marital status and occupation, as two key parameters of socioeconomic position (SEP), using data from the World Health Organization Study on global AGEing and adult health (SAGE).

Methods

SAGE Wave 1 (2007–10) includes nationally-representative samples of older adults (≥50 yrs), plus smaller samples of adults aged 18-49 yrs., from China, Ghana, India, Mexico, Russia and South Africa (n = 44,747). Arthritis was defined by self-reported healthcare professional diagnosis, and a symptom-based algorithm. Marital status and education were self-reported. Arthritis prevalence data were extracted for each country by 10-year age strata, sex and SEP. Country-specific survey weightings were applied and weighted prevalences calculated.

Results

Self-reported (lifetime) diagnosed arthritis was reported by 5003 women and 2664 men (19.9% and 14.1%, respectively), whilst 1220 women and 594 men had current symptom-based arthritis (4.8% and 3.1%, respectively). For men, standardised arthritis rates were approximately two- to three-fold greater than for women. The highest rates were observed in Russia: 38% (95% CI 36%–39%) for men, and 17% (95% CI 14%–20%) for women. For both sexes and in all LMICs, arthritis was more prevalent among those with least education, and in separated/divorced/widowed women.

Conclusions

High arthritis prevalence in LMICs is concerning and may worsen poverty by impacting the ability to work and fulfil community roles. These findings have implications for national efforts to prioritise arthritis prevention and management, and improve healthcare access in LMICs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12891-017-1624-z) contains supplementary material, which is available to authorized users.

[Validation of the French version of the Binge Eating Scale: Examination of its factor structure, internal consistency and construct validity in a non-clinical and a clinical population]

OBJECTIVE

The Binge Eating Scale is a widely used scale to assess binge eating disorder in obese patients. Until now, this scale has not been validated on a French population, and no psychometrically sound tool assesses binge eating disorder in the French. This study aimed to test the psychometric properties of a French version of the Binge Eating Scale by establishing its factor structure, internal consistency, and construct validity in both a non-clinical population and a clinical population (obese patients who are candidates for bariatric surgery).

METHODS

A total of 553 non-clinical subjects and 63 morbidly obese patients who were candidates for bariatric surgery were assessed with the BES and the Bulimic Investigatory Test, Edinburgh or BITE (which assesses both binge eating behaviours and use of inappropriate compensatory behaviours). We tested the factor structure of the instrument, its internal consistency, its construct validity with measures of binge eating, and its construct validity with measures of inappropriate compensatory behaviours to avoid weight gain. In 47 out of the 63 obese patients, we assessed binge eating disorder (SCID).

RESULTS

In the non-clinical population, the BES had a one-factor structure (which accounted for 61% of the variance), excellent internal consistency (α=0.93), and high construct validity with measures of binge eating. In this population, construct validity with measures of inappropriate compensatory behaviours was confirmed in overweight and obese subjects (P=0.42), but not in underweight and optimal weight subjects (P<0.001). In obese patients candidates for bariatric surgery, we demonstrated that the BES had a one-factor structure (which accounted for 46% of the variance), had high internal consistency (α=0.88) and high construct validity with measures of binge eating and good construct validity with measures of inappropriate compensatory behaviours to avoid weight gain. In the subpopulation of 47 obese patients, sensitivity, specificity, positive predictive value and negative predictive value were respectively 75%, 88.4%, 37.5% and 97.4% (BES threshold=18).

DISCUSSION

In this study, we validated a psychometrically sound French version of the Binge Eating Scale, both in a non-clinical and a clinical sample. The psychometric properties of the French version of the BES are comparable to its original version with a one-factor structure. The BES is a useful tool to assess binge eating disorder in obese patients (e.g., bariatric surgery candidates), but might not differentiate between binge eating disorder and bulimia nervosa in underweight and optimal weight subjects.

Initial locomotor sensitivity to cocaine varies widely among inbred mouse strains

Initial sensitivity to psychostimulants can predict subsequent use and abuse in humans. Acute locomotor activation in response to psychostimulants is commonly used as an animal model of initial drug sensitivity and has been shown to have a substantial genetic component. Identifying the specific genetic differences that lead to phenotypic differences in initial drug sensitivity can advance our understanding of the processes that lead to addiction. Phenotyping inbred mouse strain panels are frequently used as a first step for studying the genetic architecture of complex traits. We assessed locomotor activation following a single, acute 20 mg/kg dose of cocaine (COC) in males from 45 inbred mouse strains and observed significant phenotypic variation across strains indicating a substantial genetic component. We also measured levels of COC, the active metabolite, norcocaine and the major inactive metabolite, benzoylecgonine, in plasma and brain in the same set of inbred strains. Pharmacokinetic (PK) and behavioral data were significantly correlated, but at a level that indicates that PK alone does not account for the behavioral differences observed across strains. Phenotypic data from this reference population of inbred strains can be utilized in studies aimed at examining the role of psychostimulant-induced locomotor activation on drug reward and reinforcement and to test theories about addiction processes. Moreover, these data serve as a starting point for identifying genes that alter sensitivity to the locomotor stimulatory effects of COC.

Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach

Worldwide, one person dies every 40 seconds by suicide, a potentially preventable tragedy. A limiting step in our ability to intervene is the lack of objective, reliable predictors. We have previously provided proof of principle for the use of blood gene expression biomarkers to predict future hospitalizations due to suicidality, in male bipolar disorder participants. We now generalize the discovery, prioritization, validation, and testing of such markers across major psychiatric disorders (bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) in male participants, to understand commonalities and differences. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation and high suicidal ideation states (n=37 participants out of a cohort of 217 psychiatric participants followed longitudinally). We then used a convergent functional genomics (CFG) approach with existing prior evidence in the field to prioritize the candidate biomarkers identified in the discovery step. Next, we validated the top biomarkers from the prioritization step for relevance to suicidal behavior, in a demographically matched cohort of suicide completers from the coroner's office (n=26). The biomarkers for suicidal ideation only are enriched for genes involved in neuronal connectivity and schizophrenia, the biomarkers also validated for suicidal behavior are enriched for genes involved in neuronal activity and mood. The 76 biomarkers that survived Bonferroni correction after validation for suicidal behavior map to biological pathways involved in immune and inflammatory response, mTOR signaling and growth factor regulation. mTOR signaling is necessary for the effects of the rapid-acting antidepressant agent ketamine, providing a novel biological rationale for its possible use in treating acute suicidality. Similarly, MAOB, a target of antidepressant inhibitors, was one of the increased biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would show broad-spectrum predictive ability across psychiatric diagnoses. Indeed, the UP-Suicide was able to predict suicidal ideation across psychiatric diagnoses with an AUC of 92%. For bipolar disorder, it predicted suicidal ideation with an AUC of 98%, and future hospitalizations with an AUC of 94%. Of note, both types of tests we developed (blood biomarkers and clinical information apps) do not require asking the individual assessed if they have thoughts of suicide, as individuals who are truly suicidal often do not share that information with clinicians. We propose that the widespread use of such risk prediction tests as part of routine or targeted healthcare assessments will lead to early disease interception followed by preventive lifestyle modifications and proactive treatment.