Is Transient and Persistent Poverty Harmful to Multimorbidity?: Model Testing Algorithms

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Abstract

Multimorbidity, the coexistence of two or more long-term medical conditions in one person, has been known to disproportionally affect the low-income population. Little is known about whether long-term income is more crucial for multimorbidity than income measured in one time point; whether persistent poverty is more harmful than transient one; how changes in wealth affect multimorbidity. This is a longitudinal study on a population representative dataset, the Korean Health Panel (KHP) survey (2010–2015). A multivariate analysis was conducted using logistic regressions. A variety of income and wealth variables was investigated. Low-income Koreans (lowest 20%) were more likely to have multiple disorders; average income was more significantly associated with multimorbidity than the yearly income measured for the same year; persistent episodes of poverty had a greater hazard than transient ones; and income changes appeared to be statistically insignificant. We found that long-term income and persistent poverty are important factors of multimorbidity. These findings support the importance of policies reducing the risk of persistent poverty. Policies to promote public investment in education and create jobs may be appropriate to address multimorbidity.

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The inverse care law: clinical primary care encounters in deprived and affluent areas of Scotland.

S. Mercer, G Watt (2007)

The inverse care law states that the availability of good medical care tends to vary inversely with the need for it in the population served, but there is little research on how the inverse care law actually operates. A questionnaire study was carried out on 3,044 National Health Service (NHS) patients attending 26 general practitioners (GPs); 16 in poor areas (most deprived) and 10 in affluent areas (least deprived) in the west of Scotland. Data were collected on demographic and socioeconomic factors, health variables, and a range of factors relating to quality of care. Compared with patients in least deprived areas, patients in the most deprived areas had a greater number of psychological problems, more long-term illness, more multimorbidity, and more chronic health problems. Access to care generally took longer, and satisfaction with access was significantly lower in the most deprived areas. Patients in the most deprived areas had more problems to discuss (especially psychosocial), yet clinical encounter length was generally shorter. GP stress was higher and patient enablement was lower in encounters dealing with psychosocial problems in the most deprived areas. Variation in patient enablement between GPs was related to both GP empathy and severity of deprivation. The increased burden of ill health and multimorbidity in poor communities results in high demands on clinical encounters in primary care. Poorer access, less time, higher GP stress, and lower patient enablement are some of the ways that the inverse care law continues to operate within the NHS and confounds attempts to narrow health inequalities.

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Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany

Hendrik van den Bussche, Daniela Koller, Tina Kolonko … (2011)

Background Growing interest in multimorbidity is observable in industrialized countries. For Germany, the increasing attention still goes still hand in hand with a small number of studies on multimorbidity. The authors report the first results of a cross-sectional study on a large sample of policy holders (n = 123,224) of a statutory health insurance company operating nationwide. This is the first comprehensive study addressing multimorbidity on the basis of German claims data. The main research question was to find out which chronic diseases and disease combinations are specific to multimorbidity in the elderly. Methods The study is based on the claims data of all insured policy holders aged 65 and older (n = 123,224). Adjustment for age and gender was performed for the German population in 2004. A person was defined as multimorbid if she/he had at least 3 diagnoses out of a list of 46 chronic conditions in three or more quarters within the one-year observation period. Prevalences and risk-ratios were calculated for the multimorbid and non-multimorbid samples in order to identify diagnoses more specific to multimorbidity and to detect excess prevalences of multimorbidity patterns. Results 62% of the sample was multimorbid. Women in general and patients receiving statutory nursing care due to disability are overrepresented in the multimorbid sample. Out of the possible 15,180 combinations of three chronic conditions, 15,024 (99%) were found in the database. Regardless of this wide variety of combinations, the most prevalent individual chronic conditions do also dominate the combinations: Triads of the six most prevalent individual chronic conditions (hypertension, lipid metabolism disorders, chronic low back pain, diabetes mellitus, osteoarthritis and chronic ischemic heart disease) span the disease spectrum of 42% of the multimorbid sample. Gender differences were minor. Observed-to-expected ratios were highest when purine/pyrimidine metabolism disorders/gout and osteoarthritis were part of the multimorbidity patterns. Conclusions The above list of dominating chronic conditions and their combinations could present a pragmatic start for the development of needed guidelines related to multimorbidity.

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The contribution of risk factors to socioeconomic inequalities in multimorbidity across the lifecourse: a longitudinal analysis of the Twenty-07 cohort

Srinivasa Vittal Katikireddi, Kathryn Skivington, Alastair Leyland … (2017)

Background Multimorbidity is a major challenge to health systems globally and disproportionately affects socioeconomically disadvantaged populations. We examined socioeconomic inequalities in developing multimorbidity across the lifecourse and investigated the contribution of five behaviour-related risk factors. Methods The Twenty-07 study recruited participants aged approximately 15, 35, and 55 years in 1987 and followed them up over 20 years. The primary outcome was development of multimorbidity (2+ health conditions). The relationship between five different risk factors (smoking, alcohol consumption, diet, body mass index (BMI), physical activity) and the development of multimorbidity was assessed. Social patterning in the development of multimorbidity based on two measures of socioeconomic status (area-based deprivation and household income) was then determined, followed by investigation of potential mediation by the five risk factors. Multilevel logistic regression models and predictive margins were used for statistical analyses. Socioeconomic inequalities in multimorbidity were quantified using relative indices of inequality and attenuation assessed through addition of risk factors. Results Multimorbidity prevalence increased markedly in all cohorts over the 20 years. Socioeconomic disadvantage was associated with increased risk of developing multimorbidity (most vs least deprived areas: odds ratio (OR) 1.46, 95% confidence interval (CI) 1.26–1.68), and the risk was at least as great when assessed by income (OR 1.53, 95% CI 1.25–1.87) or when defining multimorbidity as 3+ conditions. Smoking (current vs never OR 1.56, 1.36–1.78), diet (no fruit/vegetable consumption in previous week vs consumption every day OR 1.57, 95% CI 1.33–1.84), and BMI (morbidly obese vs healthy weight OR 1.88, 95% CI 1.42–2.49) were strong independent predictors of developing multimorbidity. A dose–response relationship was observed with number of risk factors and subsequent multimorbidity (3+ risk factors vs none OR 1.91, 95% CI 1.57–2.33). However, the five risk factors combined explained only 40.8% of socioeconomic inequalities in multimorbidity development. Conclusions Preventive measures addressing known risk factors, particularly obesity and smoking, could reduce the future multimorbidity burden. However, major socioeconomic inequalities in the development of multimorbidity exist even after taking account of known risk factors. Tackling social determinants of health, including holistic health and social care, is necessary if the rising burden of multimorbidity in disadvantaged populations is to be redressed. Electronic supplementary material The online version of this article (doi:10.1186/s12916-017-0913-6) contains supplementary material, which is available to authorized users.

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Journal ID (nlm-ta): Int J Environ Res Public Health

Journal ID (iso-abbrev): Int J Environ Res Public Health

Journal ID (publisher-id): ijerph

Title: International Journal of Environmental Research and Public Health

Publisher: MDPI

ISSN (Print): 1661-7827

ISSN (Electronic): 1660-4601

Publication date (Electronic): 05 July 2019

Publication date (Print): July 2019

Volume: 16

Issue: 13

Electronic Location Identifier: 2395

Affiliations

[1 ]College of Nursing, Eulji University, Seongnam 13135, Korea

[2 ]Department of Humanities and Social Medicine, College of Medicine and Catholic Institute for Healthcare Management, The Catholic University of Korea, Seoul 06591, Korea

[3 ]Department of Health Administration, Department of Information & Statistics, Yonsei University, Wonju 26493, Korea

[4 ]Department of Healthcare Management, Eulji University, Seongnam 13135, Korea

[5 ]Global Health Unit, Department of Health Sciences, University Medical Centre Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands

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[* ]Correspondence: jinwon.noh@ 123456gmail.com ; Tel.: +82-31-740-7148

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Sukyong Seo https://orcid.org/0000-0001-8205-7163

Young Dae Kwon https://orcid.org/0000-0002-8781-6832

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Publisher ID: ijerph-16-02395

DOI: 10.3390/ijerph16132395

PMC ID: 6651201

PubMed ID: 31284519

SO-VID: eb363e5b-d199-42e6-8ddd-960772f36c27

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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

Is Transient and Persistent Poverty Harmful to Multimorbidity?: Model Testing Algorithms

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Most cited references 14

The inverse care law: clinical primary care encounters in deprived and affluent areas of Scotland.

Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany

The contribution of risk factors to socioeconomic inequalities in multimorbidity across the lifecourse: a longitudinal analysis of the Twenty-07 cohort

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