Abstract
Large population-based studies on the associations of childhood factors with late-life cognition are lacking in many low and middle income countries including India. In this study, we ...assessed the prevalence of late-life cognitive impairment and examined the associations of childhood socioeconomic status (SES) and health conditions with cognitive impairment among older adults in India. Data for this study were derived from the Longitudinal Ageing Study in India conducted in 2017–18. The effective sample size was 31,464 older adults aged 60 years and above. Cognitive functioning was measured through five global domains (memory, orientation, arithmetic function, executive function, and object naming). The overall score ranged between 0 and 43, and the score was reversed indicating cognitive impairment. Descriptive statistics along with mean scores of cognitive impairment were presented. Additionally, moderated multivariable linear regression models were employed to examine the association between explanatory variables, including childhood SES and health conditions and late-life cognitive impairment. The mean score of cognitive functioning among the study participants was 21.72 (CI 2.64–21.80). About 15% of older adults had poor health conditions, and 44% had lower financial status during their childhood. Older adults who had a fair health during their childhood were more likely to suffer from cognitive impairment in comparison to older adults who had good health during their childhood (Coef: 0.60; CI 0.39, 0.81). In comparison to older adults who had good childhood financial status, those who had poor childhood financial status were more likely to suffer from cognitive impairment (Coef: 0.81; CI 0.56, 1.07). Older adults who had fair childhood health status and poor childhood financial status were more likely to suffer from cognitive impairment in comparison to older adults who had good childhood health and good financial status (Coef: 1.26; CI 0.86, 1.66). Social policies such as improving educational and financial resources in disadvantaged communities and socioeconomically poor children and their families, would help to enhance a better cognitive ageing and a healthy and dignified life in old age.
Greater cognitive performance has been shown to be associated with better mental and physical health and lower mortality. The present study contributes to the existing literature on the linkages of ...self-perceived income sufficiency and cognitive impairment. Study also provides additional insights on other socioeconomic and health-related variables that are associated with cognitive impairment in older ages.
Data for this study is derived from the 'Building Knowledge Base on Population Ageing in India'. The final sample size for the analysis after removing missing cases was 9176 older adults. Descriptive along with bivariate analyses were presented to show the plausible associations of cognitive impairment with potential risk factors using the chi-square test. Also, binary logistic regression analysis was performed to provide the relationship between cognitive impairment and risk factors. The software used was STATA 14.
About 43% of older adults reported that they had no source of income and 7.2% had income but not sufficient to fulfil their basic needs. Older adults with income but partially sufficient to fulfil their basic needs had 39% significantly higher likelihood to suffer from cognitive impairment than older adults who had sufficient income OR: 1.39; OR: 1.21-1.59. Likelihood of cognitive impairment was low among older adults with asset ownership than older adults with no asset ownership OR: 0.83; CI: 0.72-0.95. Again, older adults who work by compulsion (73.3%) or felt mental or physical stress due to work (57.6%) had highest percentage of cognitive impairment. Moreover, older adults with poor self-rated health, low instrumental activities of daily living, low activities of daily living, low subjective well-being and low psychological health were at increased risk for cognitive impairment.
The study highlights the pressing need for care and support and especially financial incentives in the old age to preserve cognitive health. Further, while planning geriatric health care for older adults in India, priority must be given to financially backward, with no asset ownership, with poor health status, older-older, widowed, and illiterate older individuals, as they are more vulnerable to cognitive impairment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Hypertension is the most important cardiovascular risk factor in India, and representative studies of middle-aged and older Indian adults have been lacking. Our objectives were to estimate the ...proportions of hypertensive adults who had been diagnosed, took antihypertensive medication, and achieved control in the middle-aged and older Indian population and to investigate the association between access to healthcare and hypertension management.
We designed a nationally representative cohort study of the middle-aged and older Indian population, the Longitudinal Aging Study in India (LASI), and analyzed data from the 2017-2019 baseline wave (N = 72,262) and the 2010 pilot wave (N = 1,683). Hypertension was defined as self-reported physician diagnosis or elevated blood pressure (BP) on measurement, defined as systolic BP ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg. Among hypertensive individuals, awareness, treatment, and control were defined based on self-reports of having been diagnosed, taking antihypertensive medication, and not having elevated BP, respectively. The estimated prevalence of hypertension for the Indian population aged 45 years and older was 45.9% (95% CI 45.4%-46.5%). Among hypertensive individuals, 55.7% (95% CI 54.9%-56.5%) had been diagnosed, 38.9% (95% CI 38.1%-39.6%) took antihypertensive medication, and 31.7% (95% CI 31.0%-32.4%) achieved BP control. In multivariable logistic regression models, access to public healthcare was a key predictor of hypertension treatment (odds ratio OR = 1.35, 95% CI 1.14-1.60, p = 0.001), especially in the most economically disadvantaged group (OR of the interaction for middle economic status = 0.76, 95% CI 0.61-0.94, p = 0.013; OR of the interaction for high economic status = 0.84, 95% CI 0.68-1.05, p = 0.124). Having health insurance was not associated with improved hypertension awareness among those with low economic status (OR = 0.96, 95% CI 0.86-1.07, p = 0.437) and those with middle economic status (OR of the interaction = 1.15, 95% CI 1.00-1.33, p = 0.051), but it was among those with high economic status (OR of the interaction = 1.28, 95% CI 1.10-1.48, p = 0.001). Comparing hypertension awareness, treatment, and control rates in the 4 pilot states, we found statistically significant (p < 0.001) improvement in hypertension management from 2010 to 2017-2019. The limitations of this study include the pilot sample being relatively small and that it recruited from only 4 states.
Although considerable variations in hypertension diagnosis, treatment, and control exist across different sociodemographic groups and geographic areas, reducing uncontrolled hypertension remains a public health priority in India. Access to healthcare is closely tied to both hypertension diagnosis and treatment.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Lack of reliable and valid scales of Indian origin prompt researchers to borrow the marital satisfaction scale developed in different settings. The lack of a reliable scale to understand marital ...satisfaction in India prompted us to examine the marital satisfaction among young married men using ENRICH Marital Satisfaction (EMS) Scale developed in the Western context. Assessing the reliability of the EMS scale on the rural population of Lalitpur and Shrawasti, Uttar Pradesh, India; this study examines the determinants of marital satisfaction among young married men.
Cronbach's alpha coefficient of 0.936 confirms the high reliability of the EMS scale for the surveyed population in two districts of India. Men belonging to households with higher monthly income (OR- 3.33; 95% C.I. - 1.71-6.50) were more likely to be satisfied in their marriage than their counterparts. Similarly, fathers', mothers', and married men's educational status were other important determinants of marital satisfaction. The study emphasizes the importance of family education as a strong predictor of marital satisfaction, and therefore policymakers may look into this aspect.
The modernization and shift towards urbanized lifestyles have triggered several diseases, and the context of aging varies in urban and rural settings in India. The study aimed to investigate the ...urban-rural differences in successful ageing among older adults in India and the contributing factors in those differences. The study utilizes data from nationally representative Longitudinal Ageing Study in India (LASI, 2017-18). The analytical sample size for the study was 31,464 older adults aged 60 years and above. Descriptive statistics and bivariate analysis were carried out to present the initial results. Multivariable logistic regression and decomposition analysis was used to find the associations between explanatory variables and successful aging and to identify the contributions of covariates that explain the rural-urban differences in successful ageing. A proportion of 32% and 24% of older adults from rural and urban areas were successful agers with an urban disadvantage. Urban-dwelling older adults had 0.67 times 95% confidence interval (CI): (0.64, 0.71) lower unadjusted odds of successful ageing than rural older adults. Again, after adjusting for the effect of other explanatory variables, urban older adults had 0.92 times CI: (0.87, 0.98) lower odds of being successful agers than their rural counterparts. The major contributors to the rural-urban inequality in successful aging were differences in regional distribution (17% contribution), waist circumference (16%), working status (16%), body mass index (13%) and physical activity (8%) among rural and urban older adults. The urban disadvantage in aging successfully may reflect the higher prevalence of adverse lifestyle behaviours in urban dwellers and under-diagnosis and under-reporting of many diseases in rural areas, particularly non-communicable diseases, suggesting the need for further investigation.
The rapidly aging population is a major concern for countries, especially where cognitive health in older age is poor. The study examined the socioeconomic and health-related factors associated with ...cognitive impairment among older adults and the contribution of those factors to the concentration of low cognitive functioning among older adults from economically poor households.
Data this study were derived from the "Building Knowledge Base on Population Ageing in India" (BKPAI) survey, which was carried out in seven major states of India. The effective sample size for the analysis was 9176 older adults aged 60 years and above. Results from descriptive and bivariate analysis were reported in the initial stage. Multivariable logistic regression analysis was conducted to explore the associations. Additionally, the concentration index and concentration curve were used to measure socioeconomic inequality in cognitive impairment among older adults. Wagstaff decomposition was employed to explore the key contributors in the concentration index.
Nearly 60% of older adults suffered from cognitive impairment in the study. The likelihood of cognitive impairment were higher among older adults with a low level of self-perceived income sufficiency coefficient: 0.29; confidence interval (CI): 0.07- 0.52 compared to older adults with higher levels of perceived income status. Older adults with more than 10 years of schooling were less likely to be cognitively impaired coefficient: -1.27; CI: - 1.50- -1.04 in comparison to those with no education. Cognitive impairment was concentrated among older adults from households with the lowest wealth quintile (concentration index (CCI): - 0.10: p < 0.05). Educational status explained 44.6% of socioeconomic inequality, followed by 31.8% by wealth status and 11.5% by psychological health. Apart from these factors, difficulty in instrumental activities of daily living (3.7%), caste (3.7%), and perceived income sufficiency to fulfil basic needs (3.0%) explained socioeconomic inequality in cognitive impairment among older adults.
Findings suggest that older adults with lower perceived income, lower levels of education, poor physical and mental health, and poor physical and social resources were more likely to be cognitively impaired. Education, wealth and psychological health are major contributors in socioeconomic inequality in late-life cognitive impairment, which may be target areas in future policy formulation to reduce the inequality in cognitive impairment in older Indian adults.
ObjectiveThe study aims to explore the associations of elder abuse, crime victimhood and perceived safety with depression among older adults and examine the interactive effects of sex and place of ...residence in those associations.DesignA cross-sectional study was conducted using a large survey data.Setting and participantsThe study used data from the Longitudinal Ageing Study in India wave 1 (2017–2018). The effective sample size was 31 464 older adults (aged 60 years or older).Primary and secondary outcome measuresThe outcome variable was major depression, calculated using Short Form Composite International Diagnostic Interview. Descriptive statistics along with bivariate and multivariate analyses were performed to fulfil the objectives.Results5.22% of the older adults (n=1587) experienced abuse in the past 1 year. 1.33% of the older individuals (n=402) were victims of a violent crime, and 14.30% (n=1886) perceived an unsafe neighbourhood. Also, 8.67% of the older adults (n=2657) were suffering from depression. Older adults who were abused had 2.5 odds of suffering from depression (adjusted OR (AOR): 2.47, CI: 1.96 to 3.10) and victims of a violent crime were 84% more likely to be depressed (AOR: 1.84, CI: 1.15 to 2.95) compared with their counterparts. Besides, older individuals who perceived as living in unsafe neighbourhood were 61% more likely to be depressed (AOR: 1.61, CI: 1.34 to 1.93) compared with their counterparts. In the interaction analysis, older women who reported abuse had higher odds of suffering from depression (AOR: 3.27; CI: 2.34 to 4.57) compared with older men who were not abused. Similar result was found in older adults reporting abuse and residing in rural areas (AOR: 3.01, CI: 2.22 to 4.07) compared with those urban residents reporting no abuse.ConclusionsHealthcare providers should pay more attention to the mental health implications of elder abuse, crime victimhood and perceived safety to grasp the underlying dynamics of the symptomology of late-life depression.
Use of body mass index (BMI) to assess the nutritional status of adolescents requires many resources, especially for country-level assessment. This study aimed to determine the relationship between ...BMI and mid upper arm circumference (MUAC) among adolescent males and females in India and to examine whether MUAC effectively represents the nutritional status of adolescents. The study utilized anthropometric measurement data collected by India's National Family Health Survey-4 (2015-16). The weighted sample for analysis included 91,315 female and 14,893 male adolescents. The BMI and MUAC measurements showed a positive correlation in both female and male adolescents. Using BMI-for-age
-score classifications, 12.7% of the adolescents were undernourished. Using MUAC (in cm) as per NACS (Nutrition Assessment, Counselling, and Support) guidelines and Mramba
() classified 22.9% and 3.7% of the adolescents as undernourished respectively. Finally, using the MUAC-for-age
-score classification, 98.4% of adolescents were determined to be normal and 1.7% undernourished. Sensitivity and specificity tests of the MUAC cut-offs, in comparison with BMI cut-offs, showed that all three MUAC cut-off classifications had high specificity (NACS cut-off: 81.3%; Mramba
cut-off (cm): 97.7%; Mramba
cut-off (
-score): 99.1%). The NACS cut-off had moderately high sensitivity (52.2%) but the Mramba
cut-offs had low sensitivity (13.3% for the centimetre cut-off and 6.6% for the
-score cut-off). Sensitivity and specificity tests proved the relationship between BMI and MUAC, and that MUAC represents adolescent nutritional status with considerable efficiency. With further research, it may be established that MUAC is a better and promising measure of adolescent nutrition, having the advantage of needing fewer resources for data collection. The MUAC has the potential to offer a simple and low-resource alternative to BMI to assess nutritional status among adolescents in poor countries.
Abstract Background Considering India’s diversity, marked by differences in caste, class, ethnicity, religion, region, and language, discrimination can take on varying forms across social-structural ...locations. We examined the association between subjective social status (SSS) and perceived discrimination, and assessed the sociodemographic correlates of perceived discrimination among older persons in India. Methods Data come from the 2017-18 wave 1 of the Longitudinal Aging Study in India (LASI) with a sample of 30,253 adults 60 years or older. SSS was examined using the Macarthur scale with a ladder technique. Perceived discrimination was evaluated with the Everyday Discrimination Scale. Multivariable logistic regression models examined the odds of reporting discrimination by its types and attributions. Results 39% of older adults reported low SSS, whereas 7.3% reported high SSS. Older adults with low SSS had significantly higher odds of experiencing some discrimination than those with high SSS. Compared to high-SSS peers, low-SSS individuals attributed age, gender, caste, financial, and health status as reasons for discrimination. Older women attributed gender as a reason for discrimination. Caste was reported as a reason for discrimination by rural but not urban dwellers. Relative to northerners, those from southern India reported age, financial, and health statuses as reasons for discrimination. Conclusions That low-SSS older adults reported age, gender, caste, financial status, and health status as reasons for discrimination and that this association persisted after considering objective indicators of socioeconomic status (SES) is suggestive of SSS as independently consequential for perceived discrimination. These findings are useful for care providers and practitioners as they encourage older patients -- especially those with low SSS who may feel stigmatized -- to seek care, comply with care regimen, and engage in behaviors that protect and promote health.
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