An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study.

OBJECTIVE: To explore associations among twenty formal and informal, societal and individual-level factors and quality of life (QOL) among people living with congestive heart failure (CHF) in two settings with different healthcare and social care systems and sociocultural contexts. SETTING AND PARTICIPANTS: We recruited 367 adult patients with CHF from a single heart failure clinic within two countries with different national social to healthcare spending ratios: Minneapolis, Minnesota, United States (US), and Nijmegen, Netherlands (NL).
DESIGN: Cross-sectional survey study. We adapted the Social Quality Model (SQM) to organize twenty diverse factors into four categories: Living Conditions (formal-societal: e.g., housing, education), Social Embeddedness (informal-societal: e.g., social support, trust), Societal Embeddedness (formal-individual: e.g., access to care, legal aid), and Self-Regulation (informal-individual: e.g., physical health, resilience). We developed a survey comprising validated instruments to assess each factor. We administered the survey in-person or by mail between March 2017 and August 2018. OUTCOMES: We used Cantril's Self-Anchoring Scale to assess overall QOL. We used backwards stepwise regression to identify factors within each SQM category that were independently associated with QOL among US and NL participants (p<0.05). We then identified factors independently associated with QOL across all categories (p<0.05).
RESULTS: 367 CHF patients from the US (32%) and NL (68%) participated. Among US participants, financial status, receiving legal aid or housing assistance, and resilience were associated with QOL, and together explained 49% of the variance in QOL; among NL participants, financial status, perceived physical health, independence in activities of daily living, and resilience were associated with QOL, and explained 53% of the variance in QOL.
CONCLUSIONS: Four formal and informal factors explained approximately half of the variance in QOL among patients with CHF in the US and NL.

Introduction

Social determinants of health over the life course influence the risk of cardiovascular disease incidence and its trajectory. [1] A growing body of literature is converging around the concept that even the highest quality healthcare, delivered without consideration for social care, is insufficient to promote cardiovascular health and quality of life (QOL). [1-4] To promote health and high QOL, a paradigm describing the importance of integrating health and social services is emerging. However, this macro-level paradigm must be accompanied by more granular exploration of this phenomenon at the individual-level to enact meaningful integration and change. The availability of such integrated services at the individual-level is especially important for people living with debilitating chronic illness, including congestive heart failure (CHF). [5] In addition to the availability of formal health and social services (e.g., hospitals, food assistance), informal health and social services (e.g., caregiving, social support, self-management) are also necessary to support cardiovascular health and QOL. [2–4, 6] Indeed, the absence of these informal health and social services has been linked to higher cardiovascular mortality and incident heart failure, poorer physical functioning, and lower QOL. [7-10]

The Social Quality Model (SQM) provides a comprehensive overview of these formal and informal health and social factors that influence quality of daily life (Fig 1). [11] The SQM describes the conditions that enhance people’s well‐being, capacity, and potential, and enables them to shape their own circumstances and contribute to society. [12] SQM factors are grouped into four conditions across the two constituting dimensions of the SQM, from formal to informal (x-axis) and from societal to individual (y-axis): Living Conditions (societal-formal), Social Embeddedness (societal-informal), Societal Embeddedness (individual-formal), and Self-Regulation (individual-informal). [13] Assessing factors across the SQM may give important clues to frontline service providers as to what is necessary to support the health and QOL of patients. However, while various factors related to the four SQM conditions are associated with health outcomes and/or QOL, the relative importance of each of these factors in supporting an individual’s QOL remains unknown. [12, 14] Further, access to and valuation of these factors across the four SQM conditions may vary by sociocultural context and societal values and norms. For example, access to care may be more important to promote health and quality of life among those living in the United States (US) compared to countries where insurance coverage is nearly ubiquitous. Alternatively, responsiveness of services may be more important in countries where health insurance is universal and nationally organized. However, cross-national variation in individual residents’ prioritization of the factors across the four SQM conditions has yet to be examined.

Fig 1

The social quality model.

Theoretical framework describing four conditions necessary to support quality of life, adapted from Wolf (2016). [13]

Societal valuation of health and social services may be inferred from the relative national spending on each. Bradley et al., (2011) reported that US spending from public sources on social services relative to healthcare services was significantly lower than all other countries in the Organization for Economic Cooperation and Development (OECD), suggesting that US public policy places lower relative value on social services compared to healthcare services. [15] Among OECD countries, higher social to healthcare service spending ratios were associated with better health outcomes, including longer life expectancy and lower infant mortality. It is plausible that these observed differences in national public spending are associated with differences in perceived access to and reported utilization of health and social resources, which in turn influence health and QOL at the individual level. If this logic holds, it is likely that these effects are magnified among individuals living with serious chronic illness due to greater proximate needs. Accordingly, we performed a cross-national survey study to characterize the presence or utilization of SQM factors, as well as to assess which combination of factors were independently associated with QOL among CHF patients living in two countries above and below the OECD average of social to health service spending ratios, the Netherlands (NL) and the US, respectively. We hypothesized that differing cultural norms and values between the NL and US would affect individual-level valuation of SQM factors in supporting QOL.

Methods

Overview

We designed the Reframing Healthcare through the Lens of Coproduction (RHeLaunCh) study to explore healthcare and social care use and expenditure among patients with chronic disease living in the US or the NL. [16] We focused on CHF as a common, chronic condition that requires intensive healthcare and social care services for effective management, particularly in the later stages of disease. Our study combined quantitative and qualitative research methods, including (1) a literature scan; (2) a retrospective database study; (3) a survey study; and (4) a series of qualitative case studies. This paper describes our results from the cross-sectional survey study that assessed the prevalence of SQM factors and their association with QOL among a sample of patients living with CHF recruited from a single hospital site in the US and in the NL.

Study setting

The study setting in the US was a cardiology clinic within a public, urban, university-affiliated, safety-net hospital, Hennepin Healthcare System (HHS) in Minneapolis, Minnesota. The study setting in the NL was an outpatient heart failure clinic within a public, academic health center, Radboud university medical center (Radboudumc) in Nijmegen, South Gelderland. Both sites are public institutions with similar missions (patient care, research, and education). At both sites, social services are not delivered directly via the healthcare system. Both sites have a fragmented system of institutions that deliver social services, though NL has more public funding to support these institutions compared with the US.

Participant recruitment and survey administration

At both study sites, we used the following criteria for eligibility to participate in the study: 18 years of age or older, competent for consent, had a cardiologist-confirmed diagnosis of CHF, engaged in longitudinal care for CHF at a cardiology clinic at HHS or Radboudumc, and able to understand English in the US and Dutch or English in the NL. Patients with severe cognitive impairment or severe comorbid conditions (e.g., end-stage cancer) were excluded.

Participant recruitment and mode of survey administration varied between study sites due to a variety of factors, including population literacy levels. In the NL, a survey was mailed to all 447 eligible patients at their home address with an enclosed information letter that stated assistance for completing the questionnaire was available. After two weeks, non-responders received a reminder by mail. If, after four weeks, a potential participant did not respond to the mailed invitation, a nurse practitioner who works at the Radboudumc heart failure clinic reminded him or her to participate in the study at the time of a clinic visit. Patients who agreed to participate upon invitation from the nurse practitioner had the option of completing the questionnaire on paper or electronically, with or without assistance from a researcher.

In the US, study investigators screened patients who were scheduled for an in-person cardiology follow-up visit for study eligibility between March 2017 and August 2018. If eligible, the investigators called the patient prior to the visit to provide information about the survey study and invited him or her to participate. Any concerns about the patient’s cognitive ability or other eligibility criteria were addressed in advance with the patient’s provider (physician or advanced practice provider). The survey was administered by a trained researcher in the clinic room in which the patient had just completed his or her cardiology consultation, or in another nearby office room. The questionnaire was also mailed to 266 eligible participants from HHS for sensitivity analyses to assess for differences in mode of administration.

Institutional review boards at HHS and Radboudumc approved this study. At Radboudumc, consent was implied if participants completed and mailed the survey. At HHS, verbal informed consent was obtained from all participants prior to survey administration. A scripted statement describing the purpose of the study, as well as how the data will be used, the confidential nature of the data, approximate time to complete the survey, the voluntary nature of the survey, and reassurance that participating or not participating would not influence their care at the clinic, was read to the participant by the in-person surveyor prior to beginning the survey. Contact information for the principal investigator was also given. If the patient did not want to participate, the survey was not completed. Completion of the survey implied that consent was given. The only persons present in the room at the time of verbal consent were the in-person surveyor and the subject.

Patient and public involvement

Prior to the start of this study, we hosted conversations with people living with heart failure and their caregivers in the US and NL to explore factors they felt contributed to their QOL and their ability to manage their chronic disease. Based on these discussions, we adapted the social quality model to categorize the variety of formal and informal supports patients reported affected their QOL and disease management capability.

Survey measures

The SQM provides a comprehensive overview of a variety of formal and informal individual and societal factors that influence quality of daily life across four conditions (Fig 1). We adapted existing, validated measures to assess factors related to each of the four SQM conditions. We used overall QOL as measured by current life evaluation as a proxy measure for quality of daily life.

First, American and Dutch experts in the fields of social determinants or social quality performed a literature scan and identified relevant measures or subscales that assess factors within each SQM condition. Then, all measures assessing a particular factor were discussed among a subgroup of study team members, considering face and content validity, length, internal consistency, availability of the measure in English and Dutch, and accessibility. We achieved consensus on inclusion of a single measure for each factor in the final survey (Table 1). We used the forward-backward translation method to translate measures only available in English to Dutch. [17] The resulting questionnaire was pilot tested in both study sites on a small sample of the target population to evaluate experiences administering the questionnaire as well as the understandability and feasibility of the questionnaire (i.e., clarity and relevance of items, length of questionnaire, order of items). Based on these findings, we made appropriate changes, resulting in two final questionnaires (i.e., NL (S1 File) and US (S2 File) versions). Both versions included the same measures and content, but the order of items differed to maintain optimal psychometric properties within each setting (e.g., in the US, demographic questions were placed towards the end to prevent influence on subsequent responses). [18]

Table 1

Measures adapted to assess each factor within the social quality model.

SQM Quadrant	SQM Factor	Measure
Living Conditions	Housing conditions	Lehman Scale (living situation subscale) [19, 20]
	Perceived financial status	MacArthur Network Sociodemographic Questionnaire [21]
	Education	MacArthur Network Sociodemographic Questionnaire
	Employment	MacArthur Network Sociodemographic Questionnaire
Social Embeddedness	Social support	Duke Social Support Scale [22]
	Neighborhood cohesion	Collective Efficacy (social cohesion subscale) [23]
Societal Embeddedness	Responsiveness of services	CollaboRATE [24]
	Insurance status	RHeLaunCh team created
	Receiving assistance for basic needs	RHeLaunCh team created
Self-Regulation	Physical health	Lehman Scale (health subscale) [19, 20]
	Mental health	Behavioral Risk Factor Surveillance System
	Physical functioning	QoL Respiratory Illness Questionnaire (daily and domestic activities) [25]
	Activities of daily living	Activities of Daily Living [26]
	Resilience	Dutch Empowerment Scale [27]

Our primary outcome was overall QOL, measured using Cantril’s Self-Anchoring Scale. [28] This measure assesses perceived overall QOL, rated using the visual of a ladder with rungs numbered from zero (worst possible QOL) to ten (best possible QOL). Cantril’s Self-Anchoring Scale has been adopted by the Gallup World Poll and has been used in all OECD countries and found to have good psychometric properties across populations, with a Cronbach’s alpha of 0.76 at the individual level and 0.81 at the national level. [29]

Analysis

We first compared sociodemographic characteristics and health and social quality factors using t-tests or Chi-squared tests, depending on the scale of the characteristics and factors. Next, we assessed whether the number of reported social or healthcare services utilized were correlated with QOL using Pearson’s correlation coefficients. Then, we used backwards stepwise regression to first identify factors that were significantly independently associated with QOL among US and NL participants within each SQM condition. We then combined the variables that were significantly and independently associated with QOL within each condition into a final model to identify variables that were significantly and independently associated with QOL across all conditions. In sensitivity analyses, we repeated these steps stratified by mode of administration (i.e., mailed versus administered in-person within each site’s sample) and by level of education. Educational systems and standard levels of achievement differ across the US and NL. Therefore, we stratified by attainment of high school education because this was identified as a common threshold in both countries after discussions by Dutch and US researchers and reviewing the US and Dutch educational system.

Data were analyzed using Statistical Package for the Social Sciences (v22.0 for Windows, SPSS Inc., Chicago, IL, USA) and Stata SE (v14.1, College Station, TX). Statistical significance was set at p<0.05.

Results

Of the 447 questionnaires mailed to patients from Radboudumc, 249 were returned, resulting in a response rate of 55.7%. Of these, 23 questionnaires had missing data and were excluded from analyses, resulting in a sample size of 226 NL participants. Approximately 75% of patients invited by phone by HHS researchers to participate in the study on the day of their clinic visit agreed (N = 118). Of the 266 questionnaires mailed to patients from HHS, 20 were returned (response rate 7.5%).

Participant characteristics

Approximately one-third of the US and NL participants were women (Table 2). More NL participants were married, owned a home, had at least a high school education, and were retired. More US participants used tobacco, alcohol, and illicit drugs, and reported fair or poor mental health. There was no difference between groups in self-reported fair or poor health, but more US participants reported at least one other medical condition and had poorer functional status. More NL participants reported “a lot” of informal social support and were more trusting of neighbors. Both groups reported a strong sense of purpose in life.

Table 2

US and NL participant demographic, clinical, and social characteristics.

Item	NL (N = 226)	US (N = 118)	P-value
Demographic characteristics
Age (mean)	66.1	62.9	0.05
Gender (%Female)	31.7	29.8	0.73
Marital status (%married)	64.4	26.3	<0.001
Home ownership (%)	52.3	27.1	<0.001
Live alone (%)	22.1	39.8	<0.001
Less than high school education (%)	31.8	70.3	<0.001
Employed (full or part time) (%)	16.1	22.9	0.11
Retired (%)	51.2	30.5	<0.001
Clinical characteristics
Comorbidity* (%)	59.8	98.9	<0.001
Polypharmacy** (%)	75.5	98.9	<0.001
Any tobacco use (%)	15.7	44.3	<0.001
Any alcohol use (%)	40.0	22.6	0.001
Any illicit drug use (%)	1.7	22.6	<0.001
Physical health (%fair/poor)	44.5	50.4	0.29
Unable to walk up stairs (%)	15.6	32.2	<0.001
Mental health (%fair/poor)	10.2	22	0.002
Social characteristics
Social support (%”a lot”)	51	26.5	<0.001
My life has purpose (%Excellent/Very Good)	92.0	92.8	0.81
Trust neighbors (%Agree/Strongly Agree)	91.4	71.7	<0.001
Resilience (mean)	3.92	4.19	<0.001

*Comorbidity was defined as being under treatment by a medical doctor for one or more health problems other than heart failure

**Polypharmacy was defined as use of ≥6 different types of prescribed medication

Overall QOL and correlated health and social service utilization

NL participants reported higher QOL than US participants (mean 7.12 vs. 6.5; p = 0.001). US participants reported using more social and healthcare services than NL participants. US participants reported using a mean (standard deviation (SD)) of 2.1 (1.9) social services and 3.9 (1.0) healthcare services, while NL participants reported using a mean of 1.1 (1.6) social services and 2.5 (1.4) healthcare services. Among the NL sample, use of social care services was negatively correlated with overall QOL (r = -0.19; p<0.01). No correlation between healthcare or social care service utilization and QOL was noted in the US sample. Among both samples, healthcare and social care service utilization were positively correlated (r = 0.2; p<0.05).

Independent associations between SQM factors and QOL

Among the US sample, two or three factors from each SQM condition were independently associated with QOL (Table 3). Together, these two or three factors within each SQM condition explained anywhere from 14% (Living Conditions) to 30% (Self-Regulation) of the variance in QOL. In our sensitivity analyses using data from US participants who returned the survey by mail, results were similar.

Table 3

US condition-specific models: Factors within each condition that are independently associated with quality of life.

Living Conditions (R2 = 0.14)		Social Embeddedness (R2 = 0.22)
Factor	ß (p value)	Factor	ß (p value)
Perceived financial status	0.23 (0.001)	Social support	1.57 (<0.001)
Housing conditions	0.78 (0.041)	Neighborhood cohesion	1.38 (0.002)
Societal Embeddedness (R2 = 0.20)		Self-Regulation (R2 = 0.30)
Factor	ß (p value)	Factor	ß (p value)
Responsiveness of services	0.38 (<0.001)	Physical functioning	0.34 (0.033)
Legal aid	-1.58 (0.008)	Resilience	1.82 (<0.001)
Housing aid	1.24 (0.014)

Among the NL sample, two or three variables from each SQM condition were also independently associated with QOL (Table 4). Together, these two or three factors within each SQM condition explained anywhere from 6% (Societal Embeddedness) to 49% (Self-Regulation) of the variance in QOL.

Table 4

NL condition-specific models: Factors within each condition that are independently associated with quality of life.

Living Conditions (R2 = 0.19)		Social Embeddedness (R2 = 0.16)
Factor	ß (p value)	Factor	ß (p value)
Housing conditions	0.51 (0.035)	Social support	0.95 (<0.001)
Perceived financial status	0.28 (<0.001)	Neighborhood cohesion	0.58 (0.008)
Employment	0.48 (0.043)
Societal Embeddedness (R2 = 0.06)		Self-Regulation (R2 = 0.49)
Factor	ß (p value)	Factor	ß (p value)
Responsiveness of services	0.12 (0.003)	Physical health	p<0.001
		Fair/poor	-0.83
		Good	-0.33
		Very good/excellent	(ref)
Financial support	-0.54 (0.04)	Activities of daily living	0.22 (<0.001)
		Resilience	1.00 (<0.001)

In our final models that included all factors independently associated with QOL within each condition, we found four variables from three SQM conditions explained approximately half of the variance in QOL in the US and NL samples (Tables 5 and 6). In the US sample, better perceived financial status (β = 0.17, p = 0.004; Living Conditions), not receiving legal aid (β = -1.14, p = 0.012) and receiving housing aid (β = 0.93, p = 0.029; Societal Embeddedness), and greater resilience (β = 2.43, p<0.001; Self-Regulation) were independently associated with higher QOL; together, these variables explained 49% of the variance in QOL. In the NL sample, better financial status (β = 0.18, p<0.001; Living Conditions), greater resilience (β = 0.96, p<0.001), better perceived physical health (β = 0.77; p<0.001) and greater independence in activities of daily living (β = 0.18, p = 0.002; Self-Regulation) were independently associated with higher QOL; together, these variables explained 53% of the variance in QOL.

Table 5

US final model: SQM factors that are independently associated with quality of life (R2 = 0.49).

Living Conditions		Social Embeddedness
Factor	ß (p value)	Factor	ß (p value)
Perceived financial status	0.17 (0.004)	-	-
Societal Embeddedness		Self-Regulation
Factor	ß (p value)	Factor	ß (p value)
Legal aid	-1.14 (0.012)	Resilience	2.43 (<0.001)
Housing aid	0.93 (0.029)

Table 6

NL final model: SQM factors that are independently associated with quality of life (R2 = 0.53).

Living Conditions		Social Embeddedness
Factor	ß (p value)	Factor	ß (p value)
Perceived financial status	0.18 (<0.001)	-	-
Societal Embeddedness		Self-Regulation
Factor	ß (p value)	Factor	ß (p value)
-	-	Physical health	p<0.001
		• Fair/poor	-0.77
		• Good	-0.31
		• Very good/excellent	(ref)
-	-	Activities of daily living	0.18 (0.002)
		Resilience	0.96 (<0.001)

After pooling data from both countries and stratifying by attainment of high school education, results were largely similar, but neighborhood cohesion remained independently associated with QOL in our combined models including factors from all SQ conditions. Among those who did not complete high school (n = 47), better perceived financial status (β = 0.33, p = 0.004; Living Conditions), stronger neighborhood cohesion (β = 1.15, p = 0.024; Social Embeddedness), and greater resilience (β = 1.25, p = 0.016; Self-Regulation) were associated with higher QOL. Among those who had at least a high school education (n = 320), better perceived financial status (β = 0.21, p<0.001; Living Conditions), stronger neighborhood cohesion (β = 0.53, p = 0.002; Social Embeddedness), and better daily functioning (β = 0.24, p<0.001) and higher resilience (β = 1.10, p<0.001; Self-Regulation) were associated with higher QOL.

Discussion

We explored associations between a wide range of social and healthcare factors with higher QOL among CHF patients recruited from two countries with markedly different societal spending patterns on social and healthcare services. In both the US and NL samples, four formal and informal factors explained approximately half of the variation in perceived QOL. Though we hypothesized that the different societal contexts would result in a different set of factors associated with QOL, we found that higher perceived financial status and resilience were independently associated with higher QOL among both samples. Our results do suggest, however, that between country differences also exist in the valuation of social service utilization and perceived health.

We inferred that societal public spending patterns reflected sociocultural norms and values regarding the accessibility of formal healthcare and social services, as well as informal health and social care resources. We hypothesized that these differing cultural norms and values may affect individual-level valuation of these resources. However, the US participants had higher rates of utilization of both healthcare and social services and use of these resources was not associated with higher QOL. Among the NL sample, higher utilization of social services was negatively correlated with QOL. Rather, use of informal social resources, including higher social support and neighborhood cohesion, were both rated higher in the NL than the US and were associated with higher QOL. These findings suggest that the collective cultural ethos in the NL places greater value on the support from informal social resources to foster QOL. While this extends to societal provision of formal social services, if one needs to use these resources, it is associated with a poorer QOL in the NL perhaps because the higher valued informal resources are unavailable. Decentralization of formal social services in the NL in 2015 has been reported to have resulted in greater difficulty accessing services as well as poorer quality of services. [30]

Our findings support the need for integrated social and health programs to promote QOL among people living with serious chronic illness. [1, 5] There are several examples of programs that have successfully achieved better health outcomes, including fewer hospital readmissions, better physical functioning, fewer depressive symptoms, and lower costs of care, through the implementation of interdisciplinary teams that support social and health care needs. These programs also are more holistic and patient-centered, improving the QOL of the patients they serve. Our results are aligned with and augment these findings by also highlighting that informal social support systems and personal resources, such as resilience, should also be fostered to further improve QOL.

Perceived financial status and resilience were independently associated with QOL among participants from both countries. The link between higher income and QOL up to an annual gross income of approximately $70,000 has been well-established, and our results are consistent with the existing literature that higher perceived financial status is associated with better QOL. [31-33] Emerging literature also reports that greater resilience is linked to higher QOL among older adults and among individuals living with cancer. [34-37] It has been noted that the presence of positive social relationships and community integration at least partially mediates this relationship. [34] Related factors within the Social Embeddedness condition, measured by social support and neighborhood cohesion in our study, were significantly associated with QOL in the condition-specific analyses and in the pooled education-stratified analyses, but they were not independently associated with QOL in the final model once resilience and financial status were included. This suggests that in our sample, these SQ factors may also act as mediators of the relationship between resilience and QOL, but this relationship remains to be further explored.

In the NL, better perceived physical health and independence in activities of daily living were associated with higher QOL. These findings contradict those from a meta-analysis performed by Smith, et al., who reported that mental health was more closely related to QOL than physical health or physical functioning. [38] Similarly, a study performed in a large US sample reported weak correlations between QOL and perceived health. [31] It is possible that there are cultural, political, and environmental differences between the US and the NL that explain these differences. Around the time of this study, the Social Support Act (2015), a strong political movement in the NL to promote living as long as possible in the home, was gaining traction, suggesting high societal value of maintaining the physical capability to age in the community. In addition, the community environment in Nijmegen and its surrounding area is typically accessed by walking or biking, and thus, opportunities to participate and engage in meaningful activities require physical functioning. It has been reported that over half of the Dutch population participates in sports or engages in other physical activity at least once weekly, and that the Dutch highly value physical participation as well as having enough vitality to maintain independence. As such, it is plausible that impediments to physical health have a more negative impact on QOL in the NL than in the US.

Our sample in the US had fewer material and immaterial resources than the population in the NL. This group was less educated and less likely to be married or partnered. These factors may have resulted in the US sample’s lower reported quality of life as they affect an individual’s ability to cope with daily life, enjoy a dignified life, and access opportunities. [39] As such, these sociodemographic characteristics may also have influenced the factors that we found to be independently associated with quality of life among this sample including factors in the social embeddedness quadrant, such as receiving legal and housing aid. Populations with lower education and income also tend to have fewer or weaker social relationships and tend to be embedded in neighborhoods with lower social cohesion, [40] and are therefore less protected by personal ties (e.g., being married is a protective factor for health and well-being). This has implications for quality of life because social support is an important source for well-being and vital in ensuring health (Cobb, 1976; Vaux, 1985). [41, 42] This may be the underlying reason that neighborhood cohesion was independently associated with quality of life among the subgroup that had less than a high school diploma or equivalent in our secondary analyses.

Nevertheless, the fact that the social quality factors that were independently associated with QOL in our final models originated from more than one SQ condition, and that together these factors explained half the variation in QOL, supports the theory underlying the Social Quality Model that formal and informal resources at the societal and individual levels are essential to promote QOL. This is aligned with other person-centered models that describe multiple domains of determinants of health and well-being. [43-45] No single resource is sufficient to maintain high quality of life, and individuals benefit from access to high quality resources in all four SQ conditions. As such, outcomes-driven policies that support multi-level, multi-sector change are more likely to foster high QOL among residents. [46, 47]

Our study had several limitations. First, people in the US sample were less educated. As such, our secondary analyses stratified by education shed some light on the similarities and differences in associations with QOL among more similar groups. Because of the differences in education level among our two populations, each site used a different primary mode of survey administration, which may have biased results. It is plausible that those who had the survey verbally administered would not want to disclose undesirable information, such as illicit drug use. However, in our sensitivity analysis among the US sample comparing verbally administered versus mailed responses, there was no difference in reported tobacco, alcohol, or illicit drug use by mode of administration, suggesting this had little impact. Second, participants in the US were more likely to report having at least one other medical condition and being prescribed at least six medications. As such, it is likely US participants were sicker than NL participants, but we did not have comparable data across sites on detailed clinical information, such as left ventricular ejection fraction, brain natriuretic peptide, device therapy, and specific comorbid medical conditions to further characterize these differences. Third, we were only able to test SQM factors for which we could find validated measures. It is possible that there are other unmeasured factors within the SQM that affect QOL, but the measures we included explained approximately half of the variance in QOL. Finally, our samples were recruited from a single site in the US and the NL, respectively. Though we chose these sites because they provided comparable access to health and social services, making our inferences about health and social service utilization more valid, these sites may not be representative of their respective country’s typical health system. HHS is a public health system serving primarily low-income, Medicaid patients, yet it offers greater access to health and social service care compared to most US health systems. [48] This limits the generalizability of our results.

Conclusions

This report adds to the literature by providing a comprehensive, patient-level assessment of the need for adequate integration of healthcare and non-healthcare, formal and informal services to support QOL among people living with severe chronic illness. Our findings may add further insight into the population health effects of observed international differences in spending patterns on healthcare and social services. In this cross-national survey study, including a site in the US and a site in the NL that provided similar access to health and social services, we found four factors from three conditions of the SQM were independently associated with QOL, and explained approximately half of the variation in QOL within each population. These factors were diverse, including societal and individual level factors, as well as formal and informal factors. Our findings provide individual-level data that support the call for integrated, holistic systems of care that address formal and informal health and social needs for people living with chronic illness.

NL version of RHeLaunCH survey.

(PDF)

Click here for additional data file.

US version of RHeLaunCH survey.

(DOC)

Click here for additional data file.

Deidentified data file.

(XLSX)

Click here for additional data file.

Original version of social quality model.

(PDF)

Click here for additional data file.

6 Jan 2020

PONE-D-19-33707

An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study

PLOS ONE

Dear Dr. Roy,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Both reviewers raised significant concerns about the validity of the results and their interpretation. Among others, additional data are required and extensive revision is needed before the manuscript may be considered. In particular, the cohorts need te be much better described. In addition, analyses must consider the differences in the populations.

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Hans-Peter Brunner-La Rocca, M.D.

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Reviewer #1: No

Reviewer #2: Partly

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: No

**********

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Review of “An international comparison of factors affecting quality of life among patients with

congestive heart failure: A cross-sectional study” by Roy et al.

This study explored associations among twenty formal and informal, societal and individual-level factors and quality of life (QOL) among people living with HF in two settings (NL and US) with different healthcare and social care systems and sociocultural contexts. At the end, four formal and informal factors explained approximately half of the variance in QOL among patients with HF in the US and NL.

This study deepens into the concept that even the highest quality healthcare, delivered without consideration for social care, is insufficient to promote cardiovascular health and quality of life. This is a very well-designed and conducted study in an increasingly relevant topic. Methodologically clean at the pre-survey level.

The survey was conducted at 2 public institutions with similar missions (patient care, research, and education). At both sites, social services are delivered not via the healthcare system but via a fragmented system of social institutions. It would be worthwhile to know what would have been the results if a private US institution, which is the paradigm of US healthcare, was included in the study. I’m uncertain whether these sites are representative of their respective country’s typical health system.

Comments:

- 55.7% returned questionnaires in the NL, only 7.5% in the US. Most of the US participants completed the survey in their clinic visit, which is a different setting. This is a major bias of the data reported.

- People in the US were sicker and less educated, both variables with important influence in the reported data.

- Table2 – A relevant demographic item, such as age is missing.

- 22.6% of illicit drug use beyond tobacco and alcohol in the US seems quite extreme.

- Please provide data on aucasic, afro-american or Hispanic origin.

- Figure 1 is the same as found in reference 16.

Reviewer #2: In the present paper the authors looked at the association between formal and informal, societal and individual-level factors and quality of life (QOL) among patients with heart failure. The analysis was based on a battery of established questionnaires and assessment of QOL by the Cantril Ladder, an established QOL scale. To evaluate the role of different healthcare and social care systems and sociocultural contexts on the relative contribution of formal and informal, societal and individual-level factors on QOL two cohorts in the US (n=118) and the Netherlands (n=226) were studied. The authors report the following key findings: financial status and resilience were associated with QOL in both cohorts. Among US participants, receiving legal aid or housing assistance were also associated with QOL, and among NL participants, perceived physical health and independence in activities of daily living were in addition associated with QOL. In both cohorts approximately 50% of the variance of QOL were explained by the assessed between formal and informal, societal and individual-level factors.

General comment: This study looks at an interesting aspect, and the findings deserve attention. However, the interpretation of the results is not easy for several reasons. First, already in Table 2 it becomes evident that the cohorts differed significantly. Participants were not only more often married but also more often retired (age is not reported!). Thus, in the different periods of life different aspects may have different impact on QOL. Therefore, the impact of the place of living and the healthcare and social care system is hard to discriminate given these differences between groups. Furthermore, we know that patients had “heart failure” but no details are reported. To understand the results, we need information on LVEF, NYHA class, BNP/NT-proBNP, exercise capacity, medication and device therapy as well as comorbidities. There is some vague information on comorbidities and medication. However, “polypharmacy” is typically present in heart failure patients, and this is not necessarily bad. Insufficient or overtreatment as well as comorbidities including orthopedic or psychiatric diseases (alcohol or illicit drug dependence) may be relevant. I think that the study we benefit from additional information on these aspects.

**********

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Reviewer #1: No

Reviewer #2: No

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24 Feb 2020

Dear Dr. Brunner-La Rocca,

Thank you for your careful consideration of our manuscript titled, “An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study” (PONE-D-19-33707), for publication in PLOS ONE. My co-authors and I appreciate the reviewers’ comments and we welcome the opportunity to resubmit a revised version of the manuscript. We believe we have adequately addressed the reviewer’s concerns and the subsequent changes we have made to the manuscript have improved it.

Below we have responded directly to each of the reviewers’ comments and we have specified where we have made changes to the text based on these comments. All line numbers refer to those in the file labeled ‘Revised Manuscript with Track Changes.’

Reviewer #1:

1. This study explored associations among twenty formal and informal, societal and individual-level factors and quality of life (QOL) among people living with HF in two settings (NL and US) with different healthcare and social care systems and sociocultural contexts. At the end, four formal and informal factors explained approximately half of the variance in QOL among patients with HF in the US and NL. This study deepens into the concept that even the highest quality healthcare, delivered without consideration for social care, is insufficient to promote cardiovascular health and quality of life. This is a very well-designed and conducted study in an increasingly relevant topic. Methodologically clean at the pre-survey level.

Response: This is an accurate summary of our study, and we are pleased the reviewer finds the topic interesting and relevant.

2. The survey was conducted at 2 public institutions with similar missions (patient care, research, and education). At both sites, social services are delivered not via the healthcare system but via a fragmented system of social institutions. It would be worthwhile to know what would have been the results if a private US institution, which is the paradigm of US healthcare, was included in the study. I’m uncertain whether these sites are representative of their respective country’s typical health system.

Response: It is true that only approximately one-quarter of US hospitals are public hospitals, like Hennepin Healthcare (HHS), and therefore may not be reflective of the majority, private healthcare system. We were limited to choosing only one site within each country, and therefore had to choose between internal versus external consistency. Because our goal was to assess the role of both social and health care, we chose two institutions with similar access to social services to enhance internal consistency. Likely, if a private US healthcare organization had been selected, access to social services would have been more limited than at HHS. We agree with the reviewer’s comment and we have acknowledged this limitation in the discussion section. That said, our primary findings – factors that affect quality of life among people living with severe chronic illness – are unlikely to be influenced by the type of healthcare institution a patient utilizes, but rather by access to other services that affect social quality.

3. 55.7% returned questionnaires in the NL, only 7.5% in the US. Most of the US participants completed the survey in their clinic visit, which is a different setting. This is a major bias of the data reported.

Response: The literacy level of the HHS population is much lower than that of the Radboudumc population. In addition, response rates to mailed surveys in the US have been declining steadily over the years. As such, the US study team opted to administer the survey during clinic visits to mitigate the threat of response bias among this sample. However, surveys were also mailed to a subset of the HHS population in order to assess whether differences based on mode of administration exist. Though the response rate to the mailed survey was very low among HHS patients, as anticipated, we found no consistent differences among responses to the mailed surveys compared to the administered surveys. Of note, the rate of reporting socially undesirable behaviors, such as drug and alcohol use, was no different among those who completed the survey by mail or administered by a healthcare professional. As such, we believe bias based on mode of administration is minimal, and we have noted this in the limitations section (lines 448-460).

4. People in the US were sicker and less educated, both variables with important influence in the reported data.

Response: We agree with this statement. We attempted to control as much as possible for these differences by incorporating variables that capture levels of education, health, and functioning in our models using backwards stepwise regression. This method identifies factors associated with quality of life, independent of all other factors in the model, including education, health, and physical functioning. Further, we performed stratified analyses among subgroups of higher and lower education, and explored independent associations of all social quality factors with quality of life within these groups to assess differences. Despite these efforts, we acknowledge there may be residual confounding, as we have stated in the limitations (lines 461-463). However, we have added new content to the discussion to further contextualize the interpretation of our findings among a group that was sicker and less educated (lines 423-436).

5. Table2 – A relevant demographic item, such as age is missing.

Response: Thank you for highlighting this unintended omission. We agree with the reviewer that age is an important influencer of heart failure. We have now included mean age in Table 2 (line 289).

6. 22.6% of illicit drug use beyond tobacco and alcohol in the US seems quite extreme.

Response: While one-fifth of the population using illicit drugs seems high, these rates are consistent with population estimates of the Minneapolis metropolitan statistical area. A report from SAMHSA in 2010a estimated 15.7% of the population over 12 years of age in Minneapolis-St. Paul used illicit drugs (the entire US average was 14.7%, in comparison). Because our sample was over 18 years of age and primarily low-income, and rates of opioid use have been steadily increasing across the US over the past decade, 22.6% is likely accurate.

a. https://www.samhsa.gov/data/sites/default/files/NSDUHMetroBriefReports/NSDUHMetroBriefReports/NSDUH-Metro-Minneapolis.pdf

7. Please provide data on aucasic, afro-american or Hispanic origin.

Response: While we can report these data for US participants, these race/ethnicity categories are not applicable in NL. Further, after World War II demonstrated the ease by which Nazis were able to identify persons of Jewish ancestry, most physicians in the NL refuse to code ethnicity. As such, ethnicity data are unreliable in the NL and we do not believe it would be valuable to include incomparable categories of race/ethnicity.

8. Figure 1 is the same as found in reference 16.

Response: Figure 1 was adapted from the Wolf JR, et al. (2013) paper, which is reference 13. Our team initially published this adaptation of the figure in the paper describing the protocol for the larger grant of which this study is a part in reference 16, Hesselink, et al., (2017). Both are referenced in the manuscript, and if the editor wishes, we are open to modifying the order of references to clarify this.

Reviewer #2:

1. General comment: This study looks at an interesting aspect, and the findings deserve attention. However, the interpretation of the results is not easy for several reasons.

Response: We appreciate the reviewer’s interest in the study and in our findings. We have responded to the reviewer’s concerns about interpretation of results below.

2. First, already in Table 2 it becomes evident that the cohorts differed significantly. Participants were not only more often married but also more often retired (age is not reported!). Thus, in the different periods of life different aspects may have different impact on QOL. Therefore, the impact of the place of living and the healthcare and social care system is hard to discriminate given these differences between groups.

Response: We agree that the sociodemographic characteristics of these samples were different. As noted above (Reviewer 1, Comment #5), we have now included age in Table 2. NL participants had a mean age of 66 years and US participants had a mean age of 63 years, though this difference was not statistically significant. As such, participants were generally in similar stages of life, though it is possible they had different resources available to them based on retirement status. Participants in the US did have fewer material and immaterial resources, however, and these can influence health and quality of life. Though we controlled for many of these differences using backwards stepwise regression (i.e., all factors in the final model were associated with quality of life independent of all other factors in the social quality model), residual confounding may still be present. We have added additional content to contextualize the differences in our cross-national sample to the discussion (Lines 423-436).

3. Furthermore, we know that patients had “heart failure” but no details are reported. To understand the results, we need information on LVEF, NYHA class, BNP/NT-proBNP, exercise capacity, medication and device therapy as well as comorbidities. There is some vague information on comorbidities and medication. However, “polypharmacy” is typically present in heart failure patients, and this is not necessarily bad. Insufficient or overtreatment as well as comorbidities including orthopedic or psychiatric diseases (alcohol or illicit drug dependence) may be relevant. I think that the study we benefit from additional information on these aspects.

Response: Clinical diagnosis is the gold standard for diagnosis of heart failure, and all participants included in the study had a cardiologist-confirmed diagnosis of heart failure. This has now been clarified on lines 172-173. We have also included how we defined comorbidity and polypharmacy to clarify these descriptive statistics (Lines 290-292). We also have included alcohol and illicit drug dependence. Although we did not assess the NYHA class, we asked questions regarding physical functioning and exercise capacity that provide similar data (see Table 2). If the editor wishes, we can perform a chart review to obtain additional clinical data on specific medication and device therapy to include in Table 2 for HHS patients (this data is not available for Dutch participants), however, this would be a major departure from our theoretical framework. Because this study was not a clinical trial, and instead aimed to assess the impact of social and health care services on our primary outcome of quality of life, we do not believe these clinical data would impact the strength and relevance of our conclusions. Rather, functional and psychosocial factors assessed in the survey are likely to have a greater impact.

Again, we thank you for the opportunity to revise our manuscript and we hope you will find this version suitable for publication in PLOS ONE. If you have any further recommendations on how to improve the manuscript, we welcome these suggestions and we will work hard to implement them. We believe this publication will be a valuable contribution to the literature, and we appreciate your time and consideration.

Submitted filename: Response to Reviewers_PONE-D-19-33707_FINAL.docx

Click here for additional data file.

17 Mar 2020

PONE-D-19-33707R1

An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study

PLOS ONE

Dear Dr. Roy,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

I would like to ask the authors to include the lack of data mentioned by reviewer #2 as a limitation to the study.

We would appreciate receiving your revised manuscript by May 01 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Hans-Peter Brunner-La Rocca, M.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: The authors have appropriately responded to the reviewers' comments. I was thinking that a better characterization of the patients in terms of measures of cardiac function, functional capacity, comorbidities and medication would have strengthened the paper. Obviously, this data is not available, and the authors argue that the findings can be properly interpreted even in absence of this information. I think that it is up to the editors to decide whether the paper is acceptable despite this Limitation.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

19 Mar 2020

Dear Dr. Brunner-La Rocca,

Thank you again for your consideration of our manuscript titled, “An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study” (PONE-D-19-33707), for publication in PLOS ONE. Below we have responded directly to the remaining editor’s and reviewer’s comments and we have specified where we have made changes to the text based on these comments. All line numbers refer to those in the file labeled ‘Revised Manuscript with Track Changes.’

Editor: I would like to ask the authors to include the lack of data mentioned by reviewer #2 as a limitation to the study.

Reviewer 2: The authors have appropriately responded to the reviewers' comments. I was thinking that a better characterization of the patients in terms of measures of cardiac function, functional capacity, comorbidities and medication would have strengthened the paper. Obviously, this data is not available, and the authors argue that the findings can be properly interpreted even in absence of this information. I think that it is up to the editors to decide whether the paper is acceptable despite this Limitation.

Response: We have added the following text to the limitations paragraph to directly address the constraints of our comparable data (lines 420-424): “participants in the US were more likely to report having at least one other medical condition and being prescribed at least six medications. As such, it is likely US participants were sicker than NL participants, but we did not have comparable data on detailed clinical information, such as left ventricular ejection fraction, brain natriuretic peptide, device therapy, and specific comorbid medical conditions to further characterize these differences.”

Again, we thank you for the opportunity to revise our manuscript and we hope you will find this version suitable for publication in PLOS ONE.

Sincerely,

Brita Roy, MD, MPH, MHS

Assistant Professor of Medicine and Epidemiology

Submitted filename: Response to Reviewers_PONE-D-19-33707_R2_FINAL.docx

Click here for additional data file.

23 Mar 2020

An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study

PONE-D-19-33707R2

Dear Dr. Roy,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Hans-Peter Brunner-La Rocca, M.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

26 Mar 2020

PONE-D-19-33707R2

An international comparison of factors affecting quality of life among patients with congestive heart failure: A cross-sectional study

Dear Dr. Roy:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Hans-Peter Brunner-La Rocca

Academic Editor

PLOS ONE