Improving Health and Building Human Capital Through an Effective Primary Care System

To improve population health, one must put emphasis on reducing health inequities and enhancing health protection and disease prevention, and early diagnosis and treatment of diseases by tackling the determinants of health at the downstream, midstream, and upstream levels. There is strong theoretical and empirical evidence for the association between strong national primary care systems and improved health indicators. The setting approach to promote health such as healthy schools, healthy cities also aims to address the determinants of health and build the capacity of individuals, families, and communities to create strong human and social capitals. The notion of human and social capitals begins to offer explanations why certain communities are unable to achieve better health than other communities with similar demography. In this paper, a review of studies conducted in different countries illustrate how a well-developed primary health care system would reduce all causes of mortalities, improve health status, reduce hospitalization, and be cost saving despite a disparity in socioeconomic conditions. The intervention strategy recommended in this paper is developing a model of comprehensive primary health care system by joining up different settings integrating the efforts of different parties within and outside the health sector. Different components of primary health care team would then work more closely with individuals and families and different healthy settings. This synergistic effect would help to strengthen human and social capital development. The model can then combine the efforts of upstream, midstream, and downstream approaches to improve population health and reduce health inequity. Otherwise, health would easily be jeopardized as a result of rapid urbanization

A pilot study of heart rate variability biofeedback therapy in the treatment of perinatal depression on a specialized perinatal psychiatry inpatient unit

PURPOSE: Heart rate variability biofeedback (HRVB) therapy may be useful in treating the prominent anxiety features of perinatal depression. We investigated the use of this non-pharmacologic therapy among women hospitalized with severe perinatal depression. METHODS: Three questionnaires, the State Trait Anxiety Inventory (STAI), Warwick Edinburgh Mental Well-Being Scale (WEMWBS), and Linear Analog Self Assessment (LASA), were administered to fifteen women in a specialized inpatient perinatal psychiatry unit. Participants were also contacted by telephone after discharge to assess continued use of HRVB techniques. RESULTS: The use of HRVB was associated with an improvement in all three scales. The greatest improvement (−13.867, p<0.001 and −11.533, p<0.001) was among STAI scores. A majority (81.9%, n=9) of women surveyed by telephone also reported continued frequent use at least once per week, and over half (54.6%, n=6) described the use of HRVB techniques as very or extremely beneficial. CONCLUSIONS: The use of HRVB was associated with statistically significant improvement on all instrument scores, the greatest of which was STAI scores, and most women reported frequent continued use of HRVB techniques after discharge. These results suggest that HRVB may be particularly beneficial in the treatment of the prominent anxiety features of perinatal depression, both in inpatient and outpatient settings

Rate of Chiari I Malformation in Children of Mothers with Depression with and without Prenatal SSRI Exposure

Selective serotonin reuptake inhibitors (SSRIs) are frequently prescribed to pregnant women. Therefore, research on in utero exposure to SSRIs can be helpful in informing patients and clinicians. The aim of this retrospective two-cohort study was to determine whether there is a statistically significant increase in Chiari I malformations (CIM) in children exposed to SSRIs during pregnancy. A total of 33 children whose mothers received a diagnosis of depression and took SSRIs during pregnancy (SSRI-exposed cohort) were matched to 66 children with no history of maternal depression and no SSRI exposure. In addition, 30 children whose mothers received a diagnosis of depression, but did not receive antidepressants during pregnancy (history of maternal depression cohort), were matched to 60 children with no history of maternal depression and no SSRI exposure. Main outcome was presence/absence of CIM on MRI scans at 1 and/or 2 years of age. Scans were reviewed by two independent neuroradiologists who were blind to exposure status. The SSRI-exposed children were significantly more likely to be classified as CIM than comparison children with no history of maternal depression and no SSRI exposure (18% vs 2%, p=0.003, OR estimate 10.32, 95% Wald confidence limits 2.04–102.46). Duration of SSRI exposure, SSRI exposure at conception, and family history of depression increased the risk. The history of maternal depression cohort did not differ from comparison children with no history of maternal depression and no SSRI exposure in occurrence of CIM (7% vs 5%, p=0.75, OR estimate 1.44, 95% Wald confidence limits 0.23–7.85). Replication is needed, as is additional research to clarify whether SSRIs directly impact risk for CIM or whether this relationship is mediated by severity of depressive symptoms during pregnancy. We would discourage clinicians from altering their prescribing practices until such research is available