Parental stress: a neglected entity

Background: Parents feel very stressed when their child is sick and in Intensive care unit. Objectives of study were to identify common parental stressors during their child's critical illness and to examine its relationship with demographic variables.Methods: It's a Cross-sectional questionnaire based study done in PICU & NICU of a tertiary care medical college hospital in Mumbai, 62 parents of children admitted to PICU and NICU for at least 24 hours were interviewed using the Parental Stress Scale. The demographic variables were also recorded.The data analyzed using Cluster Analysis, Kruskal Wallis test, Chi- square test and spearman correlation.Results: The main cause of parental stress was to witness the child's sufferings (unresponsiveness/pain, procedures, tubes, monitors around child) (median of standardized score = 3.9, IQR = 0.5, p <0.005). The median of standardised stress score due to hospital environmental factors (monitor alarms, nurses, doctors around baby, other sick children) was 3.7 (IQR = 0.5) and that due to lack of intimacy with child was 3.6 (IQR =0.4). Age of parent inversely correlated with the level of stress (r = -0.638) and parents of infants were more stressed (p = 0.005). Number of children, socioeconomic status didn't affect the stress levels.Conclusions: Young parents and parents of infants were more stressful. Socioeconomic status, residential area and parental sex didn't affect stress. Few stress factors need remedial steps to meet parental needs. The clinician's awareness about these stressors, may help to provide optimized family-directed care.

Parental Perception Of Low Iq Facts Or Fiction: Retrospective Data From Clinic In Semi Rural Maharashtra

Objective: To study the association between physical and psychological problems perceived by parents and the IQ of their children. Methods: We studied 981 children in the child development center at Ahmednagar. Median age at followup was 7.8y (Q25=5.6y and Q75=10.4y, Babies underwent IQ evaluation by Binet Kamat scale (n=981); also their physical and psychological problems perceived by parents were documented. We categorized children into 4 categories using number of problems (physical and psychological separately) viz 1 (no problem), 2 (1 problem), 3 (2 problems), 4 (>2 problems). When we looked at physical problem data, 555 (56.6%) had no problem, 251 (25.6%) had 1, 117 (11.9%) had 2, and remaining 58 (5.9%) had more than 2. For psychological problems like not interested in studies, speech problems don't remember, don't understand, cannot concentrate, fears, etc. The distribution was 221 (22.5%), 212 (21.6%), 222 (22.6%) and 326 (33.3%) respectively. Result: The increasing trend of mean IQ for physical problem parameters from nil to >2 categories and decreasing prevalence of low IQ using Binet Kamat scale were not significant. However, for psychological problems the decreasing and statistically significant trend (p=0.000) was present for mean IQ, and a significant increasing trend (p=0.029) for prevalence of low IQ was observed. Conclusion: Psychological problems were associated with IQ. Numbers of problems were inversely correlated with IQ.

Revised IAP Growth Charts for Height, Weight and Body Mass Index for 5- to 18-year-old Indian Children.

Justification: The need to revise Indian Academy of Pediatrics (IAP) growth charts for 5- to 18-year-old Indian children and adolescents was felt as India is in nutrition transition and previous IAP charts are based on data which are over two decades old. Process: The Growth Chart Committee was formed by IAP in January 2014 to design revised growth charts. Consultative meeting was held in November 2014 in Mumbai. Studies performed on Indian children’s growth, nutritional assessment and anthropometry from upper and middle socioeconomic classes in last decade were identified. Committee contacted 13 study groups; total number of children in the age group of 5 to 18 years were 87022 (54086 boys). Data from fourteen cities (Agartala, Ahmadabad, Chandigarh, Chennai, Delhi, Hyderabad, Kochi, Kolkata, Madurai, Mumbai, Mysore, Pune, Raipur and Surat) in India were collated. Data of children with weight for height Z scores >2 SD were removed from analyses. Data on 33148 children (18170 males, 14978 females) were used to construct growth charts using Cole’s LMS method. Objectives: To construct revised IAP growth charts for 5-18 year old Indian children based on collated national data from published studies performed on apparently healthy children and adolescents in the last 10 years. Recommendations: The IAP growth chart committee recommends these revised growth charts for height, weight and body mass index (BMI) for assessment of growth of 5-18 year old Indian children to replace the previous IAP charts; rest of the recommendations for monitoring height and weight remain as per the IAP guidelines published in 2007. To define overweight and obesity in children from 5-18 years of age, adult equivalent of 23 and 27 cut-offs presented in BMI charts may be used. IAP recommends use of WHO standards for growth assessment of children below 5 years of age.