1
|
Barman P, Das M, Verma M. Epidemiology of type 2 diabetes mellitus and treatment utilization patterns among the elderly from the first wave of Longitudinal Aging study in India (2017-18)using a Heckman selection model. BMC Public Health 2023; 23:699. [PMID: 37059974 PMCID: PMC10103042 DOI: 10.1186/s12889-023-15661-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 04/11/2023] [Indexed: 04/16/2023] Open
Abstract
INTRODUCTION Unmanaged Type 2 diabetes mellitus (T2DM) substantially contributes to the multi-morbidity of the elderly. Fewer research has concentrated on understanding the determinants of treatment utilization among older people, with even lesser concerns about missing data in outcome variables leading to biased estimates. The present study intends to evaluate the epidemiology of T2DM in the elderly in India and explore the socioeconomic and behavioral risk factors determining the treatment utilization among the elderly > 60 years in India by addressing the missing data to generate robust estimates. METHODS The secondary analysis used data from the Longitudinal Ageing Study in India. The key dependent variables were the presence or absence of T2DM and treatment utilization. Descriptive statistics were used to understand the differences in the prevalence of diabetes and the utilization of treatment across various socio-demographic characteristics. Heckman's statistical technique evaluated the predictors of T2DM and treatment utilization. Analysis was done using STATA software version 14.0. RESULTS Almost 14% elderly reported to be living with T2DM. The odds of living with T2DM increased with non-working status, a sedentary lifestyle, and a higher BMI. A higher proportion of the elderly was on oral drugs than insulin and had been practicing lifestyle modifications to control their disease. The probability of developing T2DM was lower among females than males, but females had better odds for treatment utilization of health medication than males. Lastly, treatment utilization was significantly affected by socio-demographic characteristics like education and monthly per capita expenditure. CONCLUSIONS Treatment utilization by the elderly living with T2DM is significantly affected by socio-demographic characteristics. Keeping in mind the increasing proportion of the geriatric population in our country, it is pertinent to tailor-made counseling sessions for the elderly to improve medication utilization and adherence and realize our goals concerning non-communicable diseases.
Collapse
Affiliation(s)
- Papai Barman
- International Institute for Population Sciences (IIPS), Mumbai, India
| | - Milan Das
- International Institute for Population Sciences (IIPS), Mumbai, India
| | - Madhur Verma
- Department of community & Family medicine, All India institute of medical sciences Bathinda, Bathinda, India.
| |
Collapse
|
2
|
Dai X, Gil GF, Reitsma MB, Ahmad NS, Anderson JA, Bisignano C, Carr S, Feldman R, Hay SI, He J, Iannucci V, Lawlor HR, Malloy MJ, Marczak LB, McLaughlin SA, Morikawa L, Mullany EC, Nicholson SI, O'Connell EM, Okereke C, Sorensen RJD, Whisnant J, Aravkin AY, Zheng P, Murray CJL, Gakidou E. Health effects associated with smoking: a Burden of Proof study. Nat Med 2022; 28:2045-2055. [PMID: 36216941 PMCID: PMC9556318 DOI: 10.1038/s41591-022-01978-x] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 07/28/2022] [Indexed: 12/17/2022]
Abstract
As a leading behavioral risk factor for numerous health outcomes, smoking is a major ongoing public health challenge. Although evidence on the health effects of smoking has been widely reported, few attempts have evaluated the dose-response relationship between smoking and a diverse range of health outcomes systematically and comprehensively. In the present study, we re-estimated the dose-response relationships between current smoking and 36 health outcomes by conducting systematic reviews up to 31 May 2022, employing a meta-analytic method that incorporates between-study heterogeneity into estimates of uncertainty. Among the 36 selected outcomes, 8 had strong-to-very-strong evidence of an association with smoking, 21 had weak-to-moderate evidence of association and 7 had no evidence of association. By overcoming many of the limitations of traditional meta-analyses, our approach provides comprehensive, up-to-date and easy-to-use estimates of the evidence on the health effects of smoking. These estimates provide important information for tobacco control advocates, policy makers, researchers, physicians, smokers and the public.
Collapse
Affiliation(s)
- Xiaochen Dai
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
| | - Gabriela F Gil
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Marissa B Reitsma
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Noah S Ahmad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jason A Anderson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Catherine Bisignano
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Sinclair Carr
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Rachel Feldman
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Jiawei He
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Vincent Iannucci
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Hilary R Lawlor
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Matthew J Malloy
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Laurie B Marczak
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Susan A McLaughlin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Larissa Morikawa
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Erin C Mullany
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Sneha I Nicholson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Erin M O'Connell
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Chukwuma Okereke
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Reed J D Sorensen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Joanna Whisnant
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Aleksandr Y Aravkin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | - Peng Zheng
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Christopher J L Murray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Emmanuela Gakidou
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
3
|
Puri P, Shil A, Shetty A, Dhar B, Singh SK, Pati S, Billah B. Contribution of modifiable risk factors on the burden of diabetes among women in reproductive age-group in India: a population based cross-sectional study. J Public Health Policy 2022; 43:89-108. [PMID: 35042964 DOI: 10.1057/s41271-021-00334-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/16/2021] [Indexed: 01/24/2023]
Abstract
The diabetes burden is rapidly accelerating in India, particularly since the 2000s. We explore the burden and contribution of modifiable risk factors in diabetes among reproductive women across geographic regions of India. The study uses data from the National Family Health Survey in India 2015-2016, Census of India 2011, and World Population Prospects 2015. We computed Population Attributable Fractions and the number of total and estimated avoidable diabetic cases across regions. The prevalence of diabetic cases in India were 24.4 per 1000 women, varying across geographic regions. Diabetes affected around 8.2 million women (15-49 years) in India. Overweight (PAF = 19.5%) and obesity (PAF = 18.3%) contributed to the diabetes burden; if mitigated optimally, these can reduce diabetic cases by 2.8 million in India. Controlling diabetes should be region specific for maximum impact. Extending chronic disease screening during maternal and child health consultations might help decelerate the growing menace of diabetes in the country.
Collapse
Affiliation(s)
- Parul Puri
- Department of Survey Research and Data Analytics, International Institute for Population Sciences, Mumbai, Maharashtra, India.
| | - Apurba Shil
- International Institute for Population Sciences, Mumbai, Maharashtra, India.,Department of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beersheba, Israel
| | - Aishwarya Shetty
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Bidita Dhar
- International Institute for Population Sciences, Mumbai, Maharashtra, India.,Department of Migration and Urban Studies, International Institute for Population Sciences, Mumbai, Maharashtra, India
| | - Shri Kant Singh
- Department of Survey Research and Data Analytics, International Institute for Population Sciences, Mumbai, Maharashtra, India
| | - Sanghamitra Pati
- Department of Health Research Chandrasekharpur, ICMR Regional Medical Research Centre, Indian Council of Medical Research, Bhubaneswar, Odisha, India
| | - Baki Billah
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| |
Collapse
|
4
|
The emergence of insulin resistance following a chronic high-fat diet regimen coincides with an increase in the reinforcing effects of nicotine in a sex-dependent manner. Neuropharmacology 2021; 200:108787. [PMID: 34571112 DOI: 10.1016/j.neuropharm.2021.108787] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 08/24/2021] [Accepted: 09/09/2021] [Indexed: 12/17/2022]
Abstract
The present study assessed the sex-dependent effects of insulin resistance on the reinforcing effects of nicotine. Female and male rats received a chronic high-fat diet (HFD) or regular diet (RD) for 8 weeks. A subset of rats then received vehicle or a dose of streptozotocin (STZ; 25 mg/kg) that induces insulin resistance. To assess insulin resistance, glucose levels were measured 15, 30, 60, 120, and 180 min after an insulin injection (0.75 U/kg). Nine days later, the rats were given extended access to intravenous self-administration (IVSA) of nicotine (0.015, 0.03, 0.06 mg/kg) in an operant box where they consumed their respective diet ad libitum and performed responses for water deliveries. Each nicotine dose was delivered for 4 days with 3 intermittent days of abstinence in their home cage. The day after the last IVSA session, physical signs were compared following administration of mecamylamine (3.0 mg/kg) to precipitate nicotine withdrawal. The results revealed that there were no changes in insulin resistance or nicotine intake in HFD alone rats regardless of sex. Insulin resistance was observed in HFD-fed rats that received STZ, and the magnitude of this effect was greater in males versus females. Our major finding was that nicotine intake was greater among HFD + STZ female rats as compared to males. Lastly, the physical signs of withdrawal were similar across all groups. Our results suggest that females diagnosed with disorders that disrupt insulin signaling, such as diabetes may be at risk of greater vulnerability to nicotine use due to enhanced reinforcing effects of this drug.
Collapse
|
5
|
Greco A, Capodanno D. Differences in coronary artery disease and outcomes of percutaneous coronary intervention with drug-eluting stents in women and men. Expert Rev Cardiovasc Ther 2021; 19:301-312. [PMID: 33706641 DOI: 10.1080/14779072.2021.1902806] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Despite common perceptions, coronary artery disease (CAD) is not a male-specific condition, and sex-based differences do occur in many aspects, including clinical outcomes after percutaneous coronary intervention (PCI) with stent implantation. New-generation drug-eluting stents (DES) significantly improved post-PCI outcomes. However, no sex-specific guidelines on PCI and the use of DES are available as current evidence was derived from clinical trials enrolling predominantly male patients. AREAS COVERED This review aims at exploring sex-based disparities in CAD characteristics and manifestations, and comparing PCI outcomes and the efficacy and safety profiles of DES according to sex. In addition, a critical approach to trials' interpretation with an analysis of sources of bias is provided to inform future research and clinical practice. EXPERT OPINION Sex gap in clinical outcomes after PCI with DES implantation is narrowing due to improved performances of new-generation DES. However, scientific research and biomedical engineering are striving to optimize DES profiles and generate new iterations of devices. At the same time, gender initiatives and sex-specific trials are accruing to overcome current issues in the field. Advances in these areas will foster improvements in early and long-term clinical outcomes of both women and men.
Collapse
Affiliation(s)
- Antonio Greco
- Division of Cardiology, A.O.U. Policlinico "G. Rodolico - S. Marco", University of Catania, Catania, Italy
| | - Davide Capodanno
- Division of Cardiology, A.O.U. Policlinico "G. Rodolico - S. Marco", University of Catania, Catania, Italy
| |
Collapse
|
6
|
Prevalence of overweight and obesity and associated factors among women of childbearing age in Brazil. Public Health Nutr 2021; 24:5481-5490. [PMID: 33500016 DOI: 10.1017/s1368980021000409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To assess the factors associated with overweight and obesity among women of childbearing age in Brazil. DESIGN Cross-sectional study. SETTING Using the National Health Survey (PNS) database, from the year 2013. The socio-economic and demographic factors analysed were age, race/skin colour, region, marital status, education level, employment and family income. Concerning health history, diagnoses of hypertension, diabetes mellitus, high cholesterol, heart attack, stroke, chronic kidney disease, menarche, parity and depression were evaluated. For lifestyle information, health status, alcoholic beverage consumption, smoking and physical activity were included. The outcomes were obesity and overweight. The association of excess weight with socio-economic and demographic factors, health history and lifestyle characteristics was investigated according to the appropriate theoretical-conceptual model for the topic. PARTICIPANTS The sample size was 17 109 women aged 18-49 years. RESULTS The prevalence of women with excess weight was 55·20 %, with 33·26 % being overweight and 21·94 % with obesity. The factors associated with excess weight were age, non-white skin colour, having a partner, family income of up to two minimum wages, menarche before the age of 12, multiparity, diabetes mellitus, depression, hypertension, high cholesterol, stroke and heart attack. CONCLUSION The results showed an association between excess weight and socio-demographic factors, both determinants of general and reproductive health history. Implementation of effective public health policies is necessary to prevent unfavourable outcomes related to the health of women of childbearing age with excess weight.
Collapse
|